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i
ROLE OF INSTITUTIONS AND POLICIES IN ECONOMIC
GROWTH: A CROSS COUNTRY ANALYSIS
DOCTOR OF PHILOSOPHY DISSERTATION
BY
AZRA KHAN
FUUAST, SCHOOL OF ECONOMIC SCIENCES
FEDERAL URDU UNIVERSITY OF ARTS, SCIENCE AND TECHNOLOGY
ISLAMABAD
2016
ii
ROLE OF INSTITUTIONS AND POLICIES IN ECONOMIC
GROWTH: A CROSS COUNTRY ANALYSIS
A thesis for the partial fulfillment of the degree requirement of
Doctor of Philosophy
BY
AZRA KHAN
FUUAST, SCHOOL OF ECONOMIC SCIENCES
FEDERAL URDU UNIVERSITY OF ARTS, SCIENCE AND TECHNOLOGY
ISLAMABAD
2016
iii
ROLE OF INSTITUTIONS AND POLICIES IN ECONOMIC
GROWTH: A CROSS COUNTRY ANALYSIS
A thesis for the partial fulfillment of the degree requirement of the
degree of
Doctor of Philosophy
BY
AZRA KHAN
SUPERVISED BY
PROF. DR. SYED NAWAB HAIDER NAQVI
FUUAST, SCHOOL OF ECONOMIC SCIENCES
FEDERAL URDU UNIVERSITY OF ARTS, SCIENCE AND TECHNOLOGY
ISLAMABAD
2016
iv
Acknowledgement
In The Name of Allah, Most Beneficial and Merciful
I would like to start this page with my heartfelt, deepest gratefulness and gratitude
presented to Allah Almighty “Praise be to Allah, the Lord of the worlds”. His
benevolence, affection, generosity, and blessings are even beyond our imaginations and
deeds. The completion of this dissertation would have been entirely a dream without the
strength and guidance provided by Allah Almighty. Thanks to God for wisdom and
perseverance which has been bestowed upon me as we are able to turn impossible in to
possible through Him who gives us strength.
I would like to express my sincere and wholehearted gratitude to my principal advisor
Professor Dr. Syed Nawab Haider Naqvi, HEC Distinguished National Professor and ex
Director General, School of Economic Sciences, Federal Urdu University of Arts Science
and Technology (FUUAST) Islamabad, for his invaluable encouragement and support. He
is no doubt a professional, competent and expert economist along with strong personal
traits as being the most generous, affectionate, patient and loving one. I really feel lucky
and among the blessed ones to get an opportunity to work under his supervision.
My special appreciation goes to Professor Dr. Abdul Salam who was always available to
encourage and motivate me. He has always been very much kind, affectionate and
generous to me. His motivation has been the most supportive factor in the completion of
this dissertation.
I am also thankful to my other fellow colleagues especially Dr. Adiqa K. Kiani and Dr.
Ihtisham ul Haq for their moral support.
Dr. Sadia Safdar, a very close friend of mine and colleague, has also been very supportive
to me since the times I know her. I present my heartfelt thanks to her as being a sincere
and close friend of mine.
With due regard and respect, I would also like to thank my father, for his support,
encouragement and best wishes.
At last but not least I cannot forget the sincere wishes of my family and dear students, they
also deserve my special appreciation and thanks.
v
Table of Contents
Chapter # 1 Introduction ......................................................................................................... 1
1.1 Motivation and background of the study .............................................................................. 1
1.2 Review of policies and institutions in developing countries ................................................ 2
1.2.1 Institutions in developing countries ............................................................................. 2
1.2.2 Stabilization policies in developing countries ............................................................ 4
1.2.3 Liberalization policies in developing countries ........................................................... 7
1.2.4 Link between institutions and policies ...................................................................... 10
1.3 Significance and contribution of the study ......................................................................... 11
1.4 Choice of the countries and time period ............................................................................. 13
1.5 Objectives of the study ....................................................................................................... 14
1.6 Organization of the study .................................................................................................... 17
1.7 Concluding remarks ............................................................................................................ 17
Chapter # 2 Literature Review .............................................................................................. 19
2.1 Institutions and economic growth ....................................................................................... 19
2.1.1 Theoretical review ..................................................................................................... 19
2.1.2 Empirical review ........................................................................................................ 20
2.1.3 Concluding remarks ................................................................................................... 28
2.2 Financial liberalization and economic growth ................................................................... 30
2.2.1 Theoretical review ..................................................................................................... 30
2.2.2 Empirical review ........................................................................................................ 31
2.2.3 Concluding remarks ................................................................................................... 37
2.3 Trade liberalization and economic growth ......................................................................... 38
2.3.1 Theoretical review ..................................................................................................... 38
2.3.2 Empirical review ........................................................................................................ 39
2.3.3 Concluding remarks ................................................................................................... 46
2.4 Fiscal policy and economic growth .................................................................................... 47
2.4.1 Theoretical review ..................................................................................................... 47
2.4.2 Empirical review ........................................................................................................ 48
2.4.3 Concluding remarks ................................................................................................... 54
2.5 Monetary policy and economic growth .............................................................................. 57
vi
2.5.1 Theoretical review ..................................................................................................... 57
2.5.2 Empirical review ........................................................................................................ 57
2.5.3 Concluding remarks ................................................................................................... 63
2.6 Policy volatility and economic growth ............................................................................... 65
2.6.1 Theoretical review ..................................................................................................... 65
2.6.2 Empirical review ........................................................................................................ 65
2.6.2.1 Fiscal policy volatility and economic growth ................................................. 66
2.6.2.2 Monetary policy volatility and economic growth ........................................... 69
2.6.2.3 Capital flows volatility and economic growth ................................................ 72
2.6.2.4 Trade flows volatility and economic growth .................................................. 75
2.6.2.5 External factors volatility and economic growth ............................................ 77
2.6.3 Concluding remarks ................................................................................................... 79
2.7 Determinants of policy volatility ........................................................................................ 82
2.7.1 Empirical review ........................................................................................................ 82
2.7.1.1 Determinants of capital flows volatility ........................................................... 82
2.7.1.2 Determinants of trade flows volatility ............................................................. 87
2.7.1.3 Determinants of fiscal policy volatility ............................................................ 90
2.7.1.4 Determinants of monetary policy volatility ...................................................... 94
2.7.2 Concluding remarks ................................................................................................... 96
2.8 Literature gap .................................................................................................................... 100
Chapter # 3 An Over View of Selected Developing Countries ........................................ 102
3.1 An overview of the economies of selected countries ....................................................... 102
3.2 Dynamics of institutions and policies of selected countries ............................................. 129
3.3 Institutional reforms in developing countries ................................................................... 132
3.4 Concluding remarks .......................................................................................................... 137
Chapter # 4 Model Specification ......................................................................................... 139
4.1 Theoretical Model ............................................................................................................. 139
4.2 Description of variables .................................................................................................... 148
4.3 Methodology ..................................................................................................................... 159
4.4 Concluding remarks .......................................................................................................... 161
Chapter # 5 Results and Discussion .................................................................................... 164
5.1 Descriptive statistics ......................................................................................................... 164
vii
5.2 Pairwise correlation matrix ............................................................................................... 165
5.3 Results of GMM ............................................................................................................... 167
5.3.1 Effect of institutions and policies on economic growth ......................................... 167
5.3.1.1 Diagnostic tests ............................................................................................. 179
5.3.1.2 Concluding remarks ...................................................................................... 180
5.3.2 Disaggregated analysis of institutions .................................................................... 181
5.3.2.1 Diagnostic tests ............................................................................................. 187
5.3.2.2 Concluding remarks ...................................................................................... 188
5.3.3 Effect of policy volatility on economic growth ...................................................... 188
5.3.3.1 Diagnostic tests ............................................................................................. 194
5.3.3.2 Concluding remarks ...................................................................................... 195
5.3.4 Determinants of policy volatility ........................................................................... 195
5.3.4.1 Determinants of fiscal policy volatility ........................................................ 198
5.3.4.1.1 Diagnostic tests ............................................................................... 200
5.3.4.1.2 Concluding remarks ........................................................................ 200
5.3.4.2 Determinants of monetary policy volatility ................................................... 201
5.3.4.2.1 Diagnostic tests ............................................................................... 205
5.3.4.2.2 Concluding remarks ........................................................................ 205
5.3.4.3 Determinants of capital flows volatility ........................................................ 205
5.3.4.3.1 Diagnostic tests ............................................................................... 209
5.3.4.3.2 Concluding remarks ........................................................................ 209
5.3.4.4 Determinants of trade flows volatility .......................................................... 209
5.3.4.4.1 Diagnostic tests ............................................................................... 212
5.3.4.4.2 Concluding remarks ........................................................................ 212
Chapter # 6 Conclusions and Policy Recommendations ................................................... 220
6.1 Conclusions....................................................................................................................... 214
6.2 Policy recommendations ................................................................................................... 220
6.3 Limitations and future research directions ...................................................................... 224
References .............................................................................................................................. 226
viii
Appendices:
Appendix I: Percentile score of countries at governance index ............................................. 247
Appendix II: Summary of literature review ........................................................................... 248
Appendix III: Trends of the variables .................................................................................... 266
Appendix IV: Policy volatility in selected countries ............................................................. 276
Appendix V: Cyclical behaviour of policies in selected countries ........................................ 279
Appendix VI: Scattered plots of variables .............................................................................. 288
Appendix VII: Unit Root Test ............................................................................................... 290
Appendix VIII: Pairwise correlation matrix .......................................................................... 291
List of Tables
Table 1.1 Percentile score of selected countries at institutional index .................................... 14
Table 3.1 Main economic indicators of selected countries .................................................... 103
Table 3.2 Indicators of fiscal and monetary policy and trade liberalization (Pakistan) ......... 106
Table 3.3 Indicators of fiscal and monetary policy and trade liberalization (India) .............. 108
Table 3.4 Indicators of fiscal and monetary policy and trade liberalization (Bangladesh) ... 110
Table 3.5 Indicators of fiscal and monetary policy and trade liberalization (Srilanka) ........ 112
Table 3.6 Indicators of fiscal and monetary policy and trade liberalization (Maldives) ....... 114
Table 3.7 Indicators of fiscal and monetary policy and trade liberalization (Nepal) ............ 116
Table 3.8 Indicators of fiscal and monetary policy and trade liberalization (Thailand) ........ 118
Table 3.9 Indicators of fiscal and monetary policy and trade liberalization (Vietnam) ........ 120
Table 3.10 Indicators of fiscal and monetary policy and trade liberalization (Philippines) .. 122
Table 3.11 Indicators of fiscal and monetary policy and trade liberalization (Mexico) ........ 124
Table 3.12 Indicators of fiscal and monetary policy and trade liberalization (Brazil) .......... 126
Table 3.13 Indicators of fiscal and monetary policy and trade liberalization (Kenya) ......... 128
Table 4.1 Description of variables ......................................................................................... 157
Table 5.1 Descriptive Statistics ............................................................................................. 165
Table 5.2 Pair wise correlation matrix ................................................................................... 166
Table 5.3 Effect of institutions and policies on economic growth ........................................ 169
Table 5.4 Disaggregated analysis of institutions ................................................................... 182
Table 5.5 Effect of policy volatility on economic growth .................................................... 190
Table 5.6 Determinants of policy volatility .......................................................................... 197
ix
List of Figures
Figure 3.1 Governance indictors (Pakistan) ........................................................................... 106
Figure 3.2 Indicators of financial liberalization (Pakistan) .................................................... 106
Figure 3.3 Governance indictors (India) ................................................................................. 108
Figure 3.4 Indicators of financial liberalization (India) .......................................................... 108
Figure 3.5 Governance indictors (Bangladesh) ...................................................................... 110
Figure 3.6 Indicators of financial liberalization (Bangladesh) ............................................... 110
Figure 3.7 Governance indictors (Srilanka) ............................................................................ 112
Figure 3.8 Indicators of financial liberalization (Srilanka) .................................................... 112
Figure 3.9 Governance indictors (Maldives) .......................................................................... 114
Figure 3.10 Indicators of financial liberalization (Maldives) ................................................. 114
Figure 3.11 Governance indictors (Nepal) ............................................................................. 116
Figure 3.12 Indicators of financial liberalization (Nepal) ...................................................... 116
Figure 3.13 Governance indictors (Thailand) ......................................................................... 118
Figure 3.14 Indicators of financial liberalization (Thailand) .................................................. 118
Figure 3. Governance indictors (Vietnam) ............................................................................. 120
Figure 3.16 Indicators of financial liberalization (Vietnam) .................................................. 120
Figure 3.17 Governance indictors (Philippines) ..................................................................... 122
Figure 3.18 Indicators of financial liberalization (Philippines) .............................................. 122
Figure 3.19 Governance indictors (Mexico) ........................................................................... 124
Figure 3.20 Indicators of financial liberalization (Mexico) .................................................... 124
Figure 3.21 Governance indictors (Brazil) ............................................................................. 126
Figure 3.22 Indicators of financial liberalization (Brazil) ...................................................... 126
Figure 3.23 Governance indictors (Kenya) ............................................................................ 128
Figure 3.24 Indicators of financial liberalization (Kenya) ..................................................... 128
x
Abstract
Given the importance of institutions this study tries to find out the relatively unexplored
areas on the relationship between institutions, policies and economic growth. As there is
extensive literature so far on institutions-growth relationship as well as macroeconomic
policies-growth relationship therefore the study contributes by filling the gap on
institutions-policies link for developing countries specifically the role of institutions in
reducing policy instability. Choice of the countries is based on the governance status or
percentile rank of the countries provided by the World Bank, World Governance
Indicators. Choice of the time period is relevant to policy initiatives in developing as an
agenda of neoliberal approach. Our empirical analysis employs annual data for a set of 12
developing countries, according to the World Bank classification, from South Asia, East
Asia and Pacific, Latin America and Sub Saharan Africa. The sample period spans from
1990–2014. In the light of motivation and significance of the study there are three main
objectives and also sub objectives. Main objectives discuss the role of policies (both
stabilization and liberalization policies) and institutions in economic growth. In addition to
the level effect of domestic macroeconomic policies on economic growth the study also
evaluates the volatility effect and last the indirect effect of institutions on economic
growth through reducing the policy instability or volatility which contributes to the
literature as an unexplored area.
We have derived a dynamic panel data model to study the role of institutions and policies
in economic growth, following Mankiw et al. (1992), in the empirics of neoclassical
growth model. Derived model shows the effect of institutions and policies (stabilization
and liberalization policies) on economic growth along with traditional factors and
convergence. We have further manipulated our equation according to our objectives. To
xi
control the unobserved country specific effects and econometric problems related to the
possible endogeniety of explanatory variables with the growth we use dynamic panel data
GMM method of estimators developed by Arellano and Bond (1991), and Arellano and
Bover (1995). Regarding the empirical results of GMM we explain these according to our
objectives below.
Regarding our first objective we analyze the effect of institutions and policies on
economic growth. There is evidence of conditional convergence moreover the traditional
growth variables; physical capital, human capital and population growth also follow the
empirical literature. Institutions promote the economic growth by creating an environment
for capital creation. Regarding the fiscal policy our results support the Keynesian
hypothesis. Capital expenditures positively contribute to economic growth by providing
necessary infrastructure for the encouragement of private sector investment. Results
regarding the monetary policy support the Monetarists hypothesis, monetary policy do
affect the economic growth through aggregate demand. Trade liberalization increases the
economic growth. Liberalizing the capital goods promotes the economic growth through
technology transfer. Regarding financial liberalization both the De jure and De facto
measure negatively affect the economic growth. Literature provides the evidence that in
developing countries financial liberalization increases the risk of crisis, especially due to
short run capital flows. Disaggregated analysis shows that FDI inflows positively
contribute to economic growth being long term and stable investment while short term
investment (portfolio equity and debt) negatively contribute to economic growth due to
higher reversal rate. Disaggregated analysis of institutional quality shows that political
stability is insignificant in affecting the economic growth while all other indicators of
institutional quality positively contribute to economic growth. Rule of law is the most
significant factor in affecting the economic growth.
xii
Regarding our second objective we evaluate the effect of policy instability or volatility on
economic growth. We accomplish that volatility of domestic macroeconomic policies
brings the uncertainty regarding investment decisions therefore reducing the growth.
Volatility of the fiscal policy creates uncertainty about future taxes and the future behavior
of fiscal parameters which negatively affects the behavior of economic agents. Volatility
of the monetary policy brings volatility in consumption and investment decisions. Access
to the external market has destabilized the economies of less developed countries because
of volatility associated with trade and capital flows. Volatility of both negatively affects
the economic growth by reducing the domestic and foreign investment. Higher integration
makes countries vulnerable to external fluctuations that can deteriorate their growth rate.
Regarding our third objective we examine the effect of institutions on policy volatility.
Results show that institutions play an important role in reducing policy volatility by
putting restrictions on policy makers. Regarding the fiscal policy volatility institutional
constraints make it difficult for the governments to frequently change the policy.
Regarding monetary policy an independent central bank can provide more consistent
policy by reducing the uncertainty, in addition to lower inflationary outcome. High
institutional quality enables countries to stabilize financial markets and capital flows.
Good institutions make the trade flows stable through greater predictability which reduces
the trading cost. Besides the institutional quality volatility of domestic macroeconomic
policies can be reduced by increasing the level of income, reducing macroeconomic
instability indicated by inflation volatility, ensuring the exchange rate stability, higher
export diversification, controlling the external debt or reducing the deficit, improving the
financial sector development which plays the role of shock absorber in globally integrated
world and managing the external shocks.
xiii
Findings propose that increased globalization has raised the need for transparent, efficient
and responsive institutions. To encourage the private investment it is the responsibility of
the state to create a suitable legal and economic environment that ensure protection of
property rights, strong judiciary and improved transparency. Moreover strong fiscal,
monetary and economic institutions reduce policy uncertainty.
1
Introduction
This is an introductory chapter of the thesis. It is divided into seven sections; first section
provides the motivation and background of the study, second section describes a review of
institutions and policies in developing countries and develops an institution-policy link,
third section explains the significance and contribution of the study by highlighting the
research gap, section four discusses the rationale for the choice of countries and time
period, fifth section broadly explains the objectives of the study, sixth section explains the
organization or sequence of the study and last section discusses the concluding remarks of
this chapter.
1.1 Motivation and background of the study:
The neoliberal approach to development stresses the importance of market competition
and of policies that provoke market competition such as free-trade policies, financial
liberalization, deregulation, and privatization. International organizations such as the
World Bank explicitly advocated this approach in the 1980's and 1990's. Under
Washington consensus the policy advice consist of change in fiscal composition including
tax reforms, central bank independence, capital account and trade liberalization,
maintaining exchange rates competitiveness, denationalization and deregulation, etc1.
In many developing countries the Washington consensus policies were extensively
implemented and several policies followed wide reforms however, in providing
sustainable growth the policy program terribly failed. By the 1990s it was recognized that
policy incentives will not provide the required results until there are suitable institutions
and regulatory framework to support. Policy failures in many countries provided the
1 See Rodrik (2006)
Chapter # 1
Chapter # 1 Introduction
2
initiative to institutional reforms. First was the failure of price reform and privatization in
Russia in the absence of a helpful legal, regulatory, and political framework. A second was
the failure of market led reforms in Latin America and the third was the financial crisis of
Asia which has revealed that financial liberalization without the financial regulation brings
instability and crunch, same as the crises of Mexico, Brazil, and many other places.
In 1991 the World Bank recognized that;
“The reasons for underdevelopment are sometimes attributable to weak institutions, lack
of an adequate legal framework, damaging discretionary interventions, uncertain and
variable policy frameworks and a closed decision making process which increases risks of
corruption and waste”
In recent years it has become the aim and condition of development assistance to
strengthen the good governance in developing countries. It indicates the move in policies
and approaches of the World Bank during the 1990s. The Bank has significantly extended
its policy frontiers by pursuing good governance as a core element of its development
strategy.
The objective of first generation reforms was stabilization and liberalization of the
economy while second generation reforms focus on strengthening governing institutions
(Naim 1995).
1.2 Review of institutions and policies in developing countries:
Given the motivation and background of the study this section discusses the characteristics
of institutions and policies of developing countries. At the end we develop a link between
institutions and policies.
1.2.1 Institutions in developing countries:
Institutions are defined as the rules of the game in a society or constraints on human
behavior, whether political, social or economic. These rules can be formal as well as
Chapter # 1 Introduction
3
informal, formal ones include laws and regulations while informal ones include culture,
norms and behaviour.
The institutional concept in the economic growth acquired thrust in the mid-1990s, with
the publication of two innovative studies: one “Institutions and Economic Performance”
by Stephen Knack and Philip Keefer and the other “Corruption and Growth” by Paolo
Mauro. Knack and Keefer (1995) explain that the institutional quality such as secured
property rights and contract enforcement is vital to economic growth and investment.
Economic institutions have implications for long run growth in particular they provide the
stimulus to investment and technology. Better rule of law, lower corruption, secure
property rights, contract enforcement and better citizen access to justice all foster growth.
Political institutions affect the economic institutions and vice versa. Institutions enhance
the return of private investment by reducing the risk of doing business. Institutions also act
as a securing device for foreign investors. Institutions put checks and balances on the
government, restricting the desirability to abuse its own power, enforce property rights.
Developing countries’ institutions are characterized by poor legal structures, corrupt
governments, lack of property rights and weak contract enforcement. The East Asian crisis
has highlighted the importance of strong institutions in enabling countries to successfully
integrate with global world. It needs improved financial market transparency and a strong
financial system that ensure financial stability and market discipline. Developing countries
have made progress towards a well-developed financial system in the past few years.
There is a lack of system of formal property rights in developing countries. Weak
enforcement frameworks raise transaction costs of investors significantly. It encourages
and develops a dead capital or non-market transfers, a large informal economy in which
assets are undervalued, unreported and untaxed in developing countries. In countries like
China, investors in productive sectors enjoy greater stability regarding their expectations
Chapter # 1 Introduction
4
of future profits while in other sectors property rights are weak. In contrast, in poor
countries the problem is that productive entrepreneurs often face great uncertainty
regarding their future profits and as a result investments are low.
According to the liberal market consensus institutional structure that maximizes growth is
one that ensures the absence of rent seeking behaviour. Markets fail when participants
engage in rent seeking behavior. In developing countries corruption is common whereby
the rent-seeker have the usual practice to use bribes to influence public officials. In
developing countries the absence of democracy and an inefficient bureaucracy are the
main cause of rent-seeking. Corruption diverts the resources from productive uses, as well
as disturbs the normal functioning of the markets and thereby creates uncertainty for
investors. Moreover political corruption is also common in almost all the developing
countries.
Institutional characteristics of developing countries indicate the need for well-established
supporting institutions for the development of a well-functioning market economy.
1.2.2 Stabilization policies in developing countries:
The objective of stabilization policy is to keep the current account deficit and inflation at
adequate levels while stabilizing the output. Fiscal and monetary policy are the main
instruments of stabilization policy, each has its own focus and instruments.
The main objective of fiscal policy in developing countries is long run growth but in past
there has been an excessive focus on the objective of short-run stabilization as opposed to
long-run growth. Government finances in many developing countries are weak due to
inflexible public expenditures and low tax revenues which lead to high deficits, debts and
debt-servicing obligations. There seems a more need for discretionary fiscal policy in
Chapter # 1 Introduction
5
developing countries as automatic stabilizers seem less powerful2. Tax structures in
developing countries are not particularly progressive. The share of income tax is smaller
within that smaller tax base, taxes on consumption are the more important source of
revenue in developing countries while import tax revenue has declined due to the
liberalization and world integration. Globalization also puts pressure on developing
countries by making it difficult to increase taxes due to the fear of capital flight. It may
raise the issue of developing alternative revenue sources. There is also extensive tax
evasion due to the informal sector which is twice in size as compared to developed
countries. Financial liberalization has reduced the cost of capital there by improving the
international allocation of savings in developing countries but it has also increased the
opportunities of tax evasion. There are also limited automatic stabilizers on the
expenditure side in developing countries. Government expenditures do not change very
much in the short run because the level of government expenditures are determined by
what the economy needs in terms of public services (general administration, social
services, etc.). Most of government current expenditure is on salaries and it becomes
difficult to reduce these expenditures. Moreover an important expenditure category in
developed countries with a highly anti-cyclical pattern is social security expenditure,
which is absent in most developing countries.
Besides the characteristics of tax and expenditure level in developing countries as
discussed above another important characteristic of fiscal variables is their relative
instability, uncertainty or volatility. For many developing countries fiscal variables are
more volatile and also the movement of fiscal variables is pro-cyclical3. The credit
2 Strong automatic stabilizers ensure the stability of expenditures and revenues; which may reduce
uncertainty having positive effects on long run growth. 3 Due to low tax revenues and narrow tax base and inelastic public expenditure tax revenues and
expenditures decline during recession while during expansion revenues and expenditures both increase for
similar reasons.
Chapter # 1 Introduction
6
constraints at the level of the government lead to procyclical fiscal policy at the time of
downturn. There are likely to be considerable pressures for expanding public expenditures
when the budgetary position is favourable leading to a procyclical bias. Expenditures
outpace revenues and the resultant deficit is financed through external sector and the
central bank. Many developing countries have to opt monetary financing of the deficit by
compromising central bank autonomy.
It is generally accepted that in developing countries the primary role of monetary policy
is to facilitate economic growth with stability in prices. Today due to world integration
mostly developing countries’ economies are tied to the business cycles of the advanced
industrialized economies, having very little control over it. Hence most developing
countries sometime find themselves pursuing short-term goals of monetary policy.
The institutional features of monetary policy differ widely between developed and less
developing countries which hinder the transmission of monetary policy to the real
economy in developing countries. Developing countries are characterized by weak
financial sector, low reliability of monetary authorities, fiscal dominance and exogenous
shocks (Ghatak and Sanchez-Fung 2007). Due to these features the transmission of
monetary policy differs from advanced countries. Underdeveloped financial sector is
exposing the developing countries to considerably prolonged consequences of financial
shocks. Inappropriate legal framework and poor fiscal management has resulted in fiscal
dominance in these countries which has led to macroeconomic instability. Furthermore
developing countries are more prone to exogenous shocks than advanced countries, which,
combined with substantial supply shocks, lead to prolonged macroeconomic instability.
In many developing countries the framework of monetary policy has followed the
monetary targeting or exchange rate targeting. However many developing countries have
adopted inflation targeting over the last two decades. Interest rates have been historically
Chapter # 1 Introduction
7
high in many developing countries. In the same way interest rate spread in these countries
has been high there by discouraging the savings and investment. The high interest rate also
has consequences for capital inflows and exchange rate volatility. There is little room for
the implementation of an independent monetary policy in developing countries due to the
limited degree of central bank independence4. In an underdeveloped economy monetary
policy has an important role to play in managing the balance of payment deficit and debt
management.
In developing countries in spite of its various limitations an appropriate monetary policy
supports in controlling inflation, reducing balance of payments gap, boosting capital
formation and stimulating economic growth.
1.2.3 Liberalization policies in developing countries:
Economic liberalization refers to the reduction of government regulations in an economy
to increase the participation of the private sector in order to encourage the economic
development. In developing countries, economic liberalization mentions to further opening
up of their respective economies to trade and foreign capital.
Trade liberalization signifies to the reduction and elimination of trade barriers (tariff and
non-tariff barriers). The concept of import-substitution policy was wide spread in late
1960s and mid 1970s as an instrument for economic development in the third-world. It
was believed that developing countries would produce substitute of imports and these
industries would need protection at their initial stage. Another supportive measure of fixed
exchange rate was also adopted to get access to cheap imports of capital goods.
Historically import-substitution proved to be inefficient in most of the countries. Krueger
(1997) explains that protectionist measures violated the basic principle of the comparative
advantage. Moreover it increased capital intensity, unemployment, inflation and foreign
4 However central banks are becoming increasingly independent as a result of economic reforms among developing
countries.
Chapter # 1 Introduction
8
borrowing. Export and agriculture sectors were neglected therefore export earnings were
very low and balance of payment was deteriorated. Fiscal deficit and higher borrowing
caught the countries to debt trap. The resulting debt crises in the mid-1980s led to the trade
liberalization policy as advised by donor organizations, especially the World Bank and
International Monetary Fund. Moreover East Asian miracle also directed towards export
led growth policies therefore countries moved from an inward oriented trade policy
towards outward oriented policy.
To stimulate the economic growth, development and poverty reduction world integration
has proven a potent instrument for developing countries. The globalization and integration
has raised living standards of the people all over the world. Trade liberalization has
changed the export pattern of developing countries. Share of manufacture export has
increased in many developing countries while share of primary export has declined.
Contribution of manufactures has risen to 80 percent in total exports of developing
countries. Many developing countries in Asia and Latin America have made progress due
to the participation in global trade. Trade liberalization has also helped these countries to
attract foreign direct investment inflows. This is true for China and India since they
incorporated trade liberalization and other market based reforms and also other countries
in Asia, like Korea and Singapore. The developing countries that reduced the trade barriers
quickly developed more in 1990s than those that did not.
Though protection has dropped significantly over the past three decades, it remains
significant where developing countries have comparative advantage; mostly in areas such
as agriculture goods or labor-intensive manufactures. Trade liberalization also entails
substantial cost to developing countries due to loss of quota rents and the worsening of
terms of trade. Tariff has been a larger source of government finance in many developing
countries therefore in order to manage their budgets these countries will have to
Chapter # 1 Introduction
9
compensate through large increases in other taxes. It is also argued that liberalization
brings with itself important distributional changes in domestic economies. It has worsened
the income distribution, decreasing the relative wage of low-skilled workers, by
encouraging the adoption of skill-biased technology.
Financial liberalization denotes to ease restrictions on capital flows across a country’s
borders by domestic residents and foreigners. Openness to capital flows makes investors
or countries sensitive regarding corporate or capital tax rates, changes in interest rates,
credit controls etc. Debate on the merits of financial liberalization started after the severe
consequences of the emerging market crises of the 1990s, particularly the Mexican and the
Asian crisis. There is a broad literature trying to assess the benefits from financial
integration. Empirical literature provides the evidence of some direct channels through
which financial liberalization could benefit developing countries.
Risk sharing is regarded as one of the important channels. This risk sharing process
ultimately reduces the level of income volatility. Regarding developing countries literature
does not provide any reliable evidence of such volatility reductions as a result of financial
liberalization. During the 1980s and 1990s as a result of increased liberalization
consumption-growth as well as income volatility increased in the more financially
integrated economies (Prasad et al. 2003).
The second major channel describing the benefit from capital account liberalization is the
relaxation of capital scarcity or borrowing constraint in developing countries. Gourinchas
and Jeanne (2006) provide the evidence that benefits to developing countries from foreign
borrowing are very little because of insecure property rights. Prasad and Rajan (2008)
explain that over the 2000s, there was evidence of capital flows from poor to rich
countries, rather than from rich to poor. Only exception was the FDI that followed the
predictable pattern of moving from rich to poor countries.
Chapter # 1 Introduction
10
Kose et al. (2006) define four structural characteristics of an economy that can raise the
benefits countries obtain from financial liberalization: improved financial sector, over all
institutional quality, the macroeconomic policy and the trade openness. Financial sector
distortions have historically lead to financial crises. Various other institutions also play an
important role for financial inflows. These include protection of property rights, political
stability, judicial efficiency and the control of corruption. Institutional weaknesses reduce
the overall level of financial inflows to an economy. The macroeconomic policy also plays
an important role to stabilize the capital flows. Institutions that ensure fiscal limits and
transparency can all participate to the stabilization of capital flows. The exchange-rate
regime also plays an important role regarding financial liberalization. Fixed or inflexible
exchange rate regime has caused most of the financial crises. Finally more openness also
decreases the exposure to a sudden stop in foreign lending. Martin and Rey (2006) explain
that higher trade barriers are prone to financial crash more likely.
The financial crises of Asia, Latin America and Russia provide the lesson that
liberalization of short-term capital flows has adverse consequences for developing
countries due to their volatile and procyclical nature. Nonetheless, long-term capital flows,
FDI flows particularly, are considered as stable and positively affect the long term growth.
The capital markets in developing countries are imperfect: there is the problem of
information asymmetry and investors’ behaviour is often based on herd instincts which
lead to unsustainable investment booms and then large outflows of capital.
1.2.4 Link between institutions and policies:
We conclude from the above discussion that developing countries tend to have the
characteristics of poor legal framework, inefficient governments, weak property rights
protection and contract enforcement. An insecure environment deters foreign firms to
invest abroad. Government finances in many developing countries are weak due to
Chapter # 1 Introduction
11
inflexible public expenditures and low tax revenues which lead to high deficits and debts.
The lack of political stability and an inefficient bureaucracy allow rent-seeking to
continue. Moreover political corruption is also common in almost all the developing
countries. The institutional features of monetary policy are characterized by weak
financial sector, low reliability of monetary authorities, fiscal dominance and exogenous
shocks which slow down the transmission of monetary policy to the real economy. There
is little room for the enactment of a sovereign monetary policy in developing countries due
to the limited degree of central bank sovereignty. Macroeconomic instability, political
instability and other institutional weaknesses have destabilized the financial inflows to
developing countries. Financial sector distortions have historically lead to financial crises.
In the light of above discussion we accomplish that without a well-established and secure
institutional framework, that ensure policy implementation and enforcement, policy
objective cannot be achieved. For example strong budgetary institutions provide the rules
to govern the budget process and checks and balances over public finances. In the same
way a sovereign central bank can provide more consistent policy in addition to lower
inflationary outcome. Good quality institutions enable the countries to apply counter-
cyclical monetary and fiscal policies. Improved financial market transparency, strong
financial system and institutional checks and balances lead to stable trade and capital
flows.
1.3 Significance and contribution of the study:
The study highlights the importance of institutions in developing countries for steady state
growth as well as for policy stability and effectiveness. As discussed in the previous
section that policy failures in many developing countries were caused by weak institutions
and regulatory framework which have led towards the importance of institutions and their
strengthening.
Chapter # 1 Introduction
12
Empirical literature on the institutions-growth nexus describes that institutions stimulate
the economic growth by creating a favourable environment for capital creation. Higher
economic growth is characterized by higher bureaucratic efficiency, lesser degree of
corruption, judicial efficiency and protection of property rights. Stronger institutions also
reduce the policy instability, uncertainty or volatility by putting constraints on the policy
makers thereby reducing uncertainty in private investment. Poor institutional structure
provides an environment that allows inefficient and politically motivated policies to take
place. Given the importance of institutions for investment and policy effectiveness
institutional reforms ranked high on the agenda of IMF and the World Bank containing
issues relating to market regulation, decentralization, tax reforms and public sector
management as well as corruption.
Study tries to find out the relatively unexplored areas on the relationship between
institutions, policies and economic growth. Detailed review of the literature, in the next
chapter, specifies that there is extensive literature available on the relationship between
institutions and economic growth as well as macroeconomic policies and economic
growth. However, not much work has so far been done on the institutions-policies link for
developing countries, specifically with respect to its implication for policy uncertainty or
volatility which provides the gap in the empirical literature as discussed in detail in the
next chapter (section 2.8) and also constitutes the contribution.
Study will also be useful to policy makers or authorities regarding policy perspective. The
study will also provide the help to other researchers, by providing a stimulus to carry out
further research on the same subject matter or related so as to increase the already existing
volume of knowledge.
Chapter # 1 Introduction
13
1.4 Choice of the countries and time period:
We have selected the countries based on the percentile score on institutional quality index.
Table in the appendix-I provides the percentile score of 211 countries in the year 2014 as
provided by the World Bank, World Governance Indicators. Percentile score is also
divided into different categories which provides the guideline about the status of each
country at institutional index, table below provides this information.
Percentile score Status
0-10 Extremely low
11-25 Very low
26-50 Low
51-75 Average
76-90 High
91-100 Very high
A closer look at the table in appendix-I shows that low income countries lie in the category
of extremely low and very low at institutional quality index. Lower middle income
countries mostly lie in the category of low but with distance from average. Upper middle
income countries lie in the category of average and some closer to average. While high
income countries mostly lie in the categories of high and very high at institutional quality
index.
We have selected twelve developing countries from different regions, some lower middle
income countries and some upper middle income countries given the World Bank
classification. These are Pakistan, India, Bangladesh, Srilanka, Maldives, Nepal,
Philippines, Thailand, Vietnam, Brazil, Mexico and Kenya. As for as institutional status is
concerned, Pakistan persistently lie in the category of very low at institutional quality
index. Nepal and Kenya both keep switching between very low and low. India and
Vietnam both persistently lie in the category of low. Philippines and Brazil both lie in low
and closer to average. Bangladesh keeps switching between average and low. Maldives
and Thailand moves between average and closer to average. Srilanka persistently remains
Chapter # 1 Introduction
14
closer to average. Mexico switches between average and closer to average. We have
skipped the categories of extremely low, high and very high. We have taken a mixed
sample of very low, low, closer to average and average (but with a distance from upper
limit) to avoid the biasedness. Table below shows the percentile score of selected countries
over time with their status as discussed above.
Table 1.1 Percentile score of selected countries at institutional index Countries 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 Status
Maldives 68.2 65.67 61.43 60.33 48.8 49.89 39 42.4 39.22 48.19 Average and closer to average
Thailand 59.1 61.15 62.06 50.01 52.07 43.92 43.1 43 44.18 43.96 Average and closer to average
Bangladesh 56.9 55.36 52.9 33.49 38.2 43.23 40.4 41.3 39.66 36.29 Average and low
Philippines 49.6 53.31 41.63 42.02 36 37.25 37.2 35 39.96 45.36 Low and closer to average
Nepal 44.2 33.87 32.76 29.19 20 24.25 23.8 22.2 20.87 26.69 Very low and low
Srilanka 42.8 42.19 42.76 48.31 44.7 42.09 40.2 40 41.86 44.72 Closer to average
Mexico 42.6 46.42 50.84 53.33 52.3 48.92 44.6 45.9 47.82 43.49 Closer to average and average
Vietnam 35.9 34.78 34.1 32.03 32.2 34.93 33.7 33.3 34.85 36.81 Persistently low
Brazil 32.8 34.74 33.46 34.75 38.8 41.43 41.9 41.6 43.47 43.15 Low and closer to average
India 24.2 35.13 32.04 31.07 32.1 28.83 29.9 29.2 28.34 26.7 Persistently low
Kenya 24.1 23.94 26.76 26.89 27 20.12 18 14.6 16.85 18.88 Very low and low
Pakistan 23.4 24.79 19.97 22.15 18.8 25.09 21 20.5 17.56 20.95 Persistently very low
As for as the choice of the time period is concerned macroeconomic stabilization, trade
and financial liberalization were imposed on developing countries in the form of
neoliberal policy agenda in the late 1980s while in1990s second generation reforms
highlighted the importance of well-functioning institutions for development. Therefore our
rational choice regarding the selection of the time period becomes from the decade of
1990s.
1.5 Objectives of the study:
Our empirical analysis will employ annual data for a set of 12 developing countries,
according to the World Bank classification, from South Asia, East Asia and Pacific, Latin
America and Sub Saharan Africa. The sample period spans from 1990–2014.
Keeping in mind the motivation and background of the study and also the significance the
main objectives of the study are following.
First, to identify the role of countries’ institutions and policies in economic growth.
Also the analysis of disaggregated institutions and economic growth.
Chapter # 1 Introduction
15
Second, to analyze the effect of policy instability or volatility on economic growth.
Third, to develop a link between countries’ institutional environment and policy
instability or volatility.
Beside the main objective there are also other sub objectives;
To provide theoretical foundations to the per-capita growth equation.
To test for conditional convergence across countries and to determine the role of
traditional factors of production in economic growth.
To present an overview of the economies of selected countries with a dynamic
analysis of their institutions and policies.
To determine the level of volatility of individual countries and also cyclical
behaviour of policies in sample countries.
To provide suitable policy implications based on empirical findings.
Now we discuss our main objectives with more detail;
Regarding our first objective we will evaluate the role of institutions and policies (both
stabilization and liberalization policies) in economic growth. We will also disaggregate the
institutional quality into its components; voice and accountability, political stability,
government effectiveness, regulatory quality, rule of law and control of corruption for a
wider analysis and comprehensive policy implication. Empirical literature infers that
institutional quality affect the economic growth through capital formation. The objective
of stabilization policies is to ensure macroeconomic stability through fiscal and monetary
policy. The liberalization policies ensure movement towards more global integration, a
more free economy with less restriction on trade and capital flows. For a comprehensive
policy analysis we will use alternative indicators of fiscal and monetary policy and
similarly of trade and capital account liberalization. The empirical analysis will shed light
on the alternative institutions and policies for generating long term growth. Regarding the
Chapter # 1 Introduction
16
institutional quality we will test the null hypothesis of no significant relationship between
institutional quality and economic growth against the alternative. Regarding the fiscal
policy we will test the null hypothesis that fiscal policy has no effect on economic growth
(Classical hypothesis) against the alternative (Keynesian hypothesis). Regarding monetary
policy we will test the null hypothesis that monetary policy does not affect economic
growth (Keynesian hypothesis) against the alternative (Monetarist hypothesis). Regarding
trade liberalization our null hypothesis will be to test that trade liberalization is not
associated with economic growth against the alternatives. For financial liberalization we
will test the null hypothesis that there is no significant relationship between financial
liberalization and economic growth against the alternatives.
First objective is related to the level effect of domestic macroeconomic policies on
economic growth. Second objective evaluate the effect of policy volatility on economic
growth as there is problem of frequent policy switching in developing countries, due to
some internal and external factors that lead to lower rates of investment and economic
growth by causing uncertainty to investors. We will test the null hypothesis that policy
volatility does not affect the economic growth against the alternative.
As described above that policy volatility or uncertainty is harmful to economic growth by
making investment uncertain therefore it is important to analyze the factors that contribute
to policy volatility. Regarding the third objective we will analyze the role of institutions
in reducing the policy instability. Empirical literature explicates that institutions play an
important role to reduce policy volatility or instability by putting restrictions or check and
balances on policy makers. We will test the null hypothesis that institutions do not affect
policy volatility against the alternative. Besides the institutional quality we will also
examine the effect of some domestic macroeconomic and external factors contributing to
policy volatility. This last objective will indirectly analyze the effect of institutions on
Chapter # 1 Introduction
17
economic growth, by reducing the policy instability or volatility. The empirical analysis
will fill the gap in existing literature as discussed in section 1.4 and also identified by
literature gap in the next chapter (section 2.8).
1.6 Organization of the study:
Chapter one discusses the introduction, chapter two deals with theoretical as well as
empirical literature regarding the role of institutions and policies in economic growth
moreover the link between policy instability and economic growth and last the institution
policy link with the discussion of the literature gap. Chapter three describes an overview
of the economies of selected developing countries, dynamics of their institutions and
policies and an overview of institutional reforms. Chapter four develops the theoretical
foundations of the per capita growth model. It also discusses the variables and
methodology. Chapter five discusses the empirical results of the panel data model by using
generalized method of moments (GMM) introduced for dynamic panel data models. Last
chapter discusses the conclusion emerging from theoretical discussion and empirical
estimation. This chapter also presents policy recommendations and highlights the
limitations of the study and areas of future research.
1.7 Concluding remarks:
The chapter discusses in background of the study that policy failure in developing
countries was due to weak institutional structure; the failure of price reform and
privatization in Russia, failure of market-oriented reforms in Latin America and the
financial crisis of Asia were all the results of the lack of helpful legal, regulatory and
political framework. The review of institutions and policies in developing countries
indicate that the monetary transmission mechanism is weak in developing countries due to
weak monetary, financial and fiscal institutions. Government finances in many developing
Chapter # 1 Introduction
18
countries are also weak which lead to high deficits, debts and debt-servicing obligations.
The lack of political stability and an inefficient bureaucracy allow rent-seeking to
continue. Financial sector distortions have historically lead to financial crises. All it
provides the rationale for the importance of institutions and their strengthening in
developing countries for policy effectiveness. The study tries to find out the relatively
unexplored areas on the relationship between institutions, policies and economic growth.
As there is extensive literature so far on institutions-growth relationship as well as
macroeconomic policies-growth relationship therefore the study contributes by filling the
gap on institutions-policies link for developing countries specifically the role of
institutions in reducing policy instability. Choice of the countries is based on the
governance status or percentile rank of the countries provided by the World Bank, World
Governance Indicators. Choice of the time period is relevant to policy initiatives in
developing as an agenda of neoliberal approach. In the light of motivation and significance
of the study there are three main objectives and also sub objectives. Main objectives
discuss the role of policies (both stabilization and liberalization policies) and institutions
in economic growth. In addition to the level effect of domestic macroeconomic policies in
economic growth the study also evaluates the volatility effect and last the indirect effect of
institutions in economic growth through reducing the policy instability or volatility which
contributes to the literature as an unexplored area of institutional policy link.
19
Literature Review
This chapter provides an overview of the available empirical and theoretical literature on
the link between policies, institutions and economic growth. Its main objective is to
discover the unexplored areas which need to focus and that require further research.
Chapter is divided into eight sections. First section discusses the available studies on the
relationship between institutions and economic growth. Second and third section presents
a brief overview of the available literature regarding liberalization policies, both financial
and trade liberalization, and economic growth. Fourth and fifth section deals with the
available literature regarding stabilization policies, both fiscal and monetary policy, and
economic growth. Section six provides an over view of the available literature on the
relationship between policy volatility and economic growth. Section seven discusses the
empirical evidence from the literature on determinants of policy volatility. Last section
discusses the literature gap.
2.1 Institutions and economic growth:
2.1.1 Theoretical review:
In the period of 1990s the institutional concept gained popularity, with the publication of
two revolutionary studies: “Institutions and Economic Performance” by Stephen Knack
and Philip Keefer and “Corruption and Growth” by Paolo Mauro. These pioneer studies
provided a motivation towards a new wave of research regarding the institutional
proposition in a cross country setting. Knack and Keefer (1995) describe that institutional
quality represented as secured property rights and contract enforcement, is important for
investment and ultimately for growth. Mauro (1995) explains that corruption is inversely
Chapter # 2
Chapter # 2 Literature Review
20
related to investment and growth. Further empirical investigations support these initial
findings. The literature provides the empirical support to the notions of North (1990) and
Olson (1994) who emphasized the role of protection of property rights and contract
enforcement for growth and prosperity.
Some earlier studies have highlighted the importance of economic and political freedom
for economic growth and development including Owens (1987) and Sen (1991). However
most of the previous literature emphasized only on some specific features of governance,
which are theoretical in nature.
Endogenous growth theory provides the evidence of conditional convergence which
depends on institutional characteristics of a country. New growth theory explains this
concept through “knowledge spillovers” assumption, where less developed countries can
catch up through technological development which in turn depends upon the institutional
measures. As discussed by North and Thomas (1975) that technological changes depend
on the prevailing institutions and their incentive structures.
2.1.2 Empirical review:
To date there has been an ample body of empirical literature that has examined the
institutional growth link. These studies have evaluated the effect of institutions on
economic growth by using different measures of institutional quality. Differences in
findings are based on changes in the sample period, sample size and specification. Below
we examine some empirical literature.
Mauro (1995) analyzes the association between corruption and economic growth for a
cross section of countries from 1980-83. Objective is to explore the ways through which
corruption and other institutional indicators affect the economic growth. Findings illustrate
that an important mechanism through which corruption affects the economic growth is by
depressing the private investment. He uses the data of Business International (BI) indices
Chapter # 2 Literature Review
21
on corruption, red tape, and the judicial efficiency. Political stability is also used
representing other indicator of institutional quality. He has also taken an aggregate
measure of bureaucratic efficiency, aggregating the above three indicators, because it’s a
more comprehensive index of corruption. Study contributes well to the literature by using
a comprehensive indicator of bureaucratic efficiency.
Knack and Keefer (1995) examine the link between property rights and economic growth
for a cross section of countries from 1974-89. The study contributes by using property
rights and rent seeking in growth model. Findings comprise that property rights are
associated with greater investment and economic growth besides they increase the rate of
convergence. The study contributes well regarding the indicator of property rights as many
earlier studies have used indicators of political stability to represent property rights; like
political freedom, civil liberties, coups and revolutions etc. But these indicators only
partially capture the variations in the property rights which incorporate considerable
measurement error.
Goldsmith (1995) observes the connection between democracy, property rights and
economic growth for 59 less developed and transitional economies. The study examines
the link among institutional factors and economic growth in the 1980s and early 1990s.
Study uses the data of political freedom from Freedom House while of economic freedom
from Heritage Foundation. Findings infer that democratic freedom and property rights
significantly contribute to economic growth. Results also imply that higher protection of
property rights is associated with more democratic economies due to the effect of strong
lobby, which induces the private investment and growth. The study is in contrast to many
other studies which show a negative effect of democracy.
Kaufmann et al. (1999) provide the evidence that better governance contribute to
development, such as higher per capita income, lower mortality rate and higher literacy
Chapter # 2 Literature Review
22
rate etc. The study uses a cross section of more than 150 countries. They compile a
comprehensive indicator of governance based on six aggregate dimensions of the
governance. These include; voice and accountability, political instability and violence,
government effectiveness, regulatory burden, rule of law, and control of corruption. All
these indicators significantly contribute to economic growth as well as development.
Study also checks the reliability of results exclusive of all OECD economies which
provides the similar results by assuring that differences in the sample do not matter. The
study does not discuss the channels through which governance will contribute towards
development. Revised version of 2008 extends the data further to 212 countries. Moreover
the revised version has also discussed a number of important measurement issues
regarding the construction of these indicators and implicit margins of errors.
Campos and Nugent (1999) evaluate the effect of institutions on the development of East
Asia and Latin America. Per capita income, infant mortality rate and adult literacy
represent the level of development of the countries. Four dimensions of governance are
addressed; the executive, the bureaucracy, the rule of law and civil society. The study
utilizes the data for institutional measures from three sources, ICRG, BERI and polity III.
Institutional characteristics of both regions are different so the study analyzed the data for
both regions separately and also jointly. As for as the differences in per capita income are
concerned strength of civil society significantly contributes in East Asia while rule of law
and bureaucratic efficiency play an important role in Latin America. Regarding the infant
mortality rule of law plays an important role in Latin America while in East Asia quality
of bureaucracy plays an important role. While regarding the adult literacy rule of law and
bureaucratic efficiency are significant for both regions. For Latin America rule of law
significantly contributes to development in all specifications while in East Asia
Chapter # 2 Literature Review
23
bureaucratic efficiency plays its role. The study can be enriched by expanding the sample
size and also other regions.
Mauro (2002) analyses the corruption growth relationship by extending his previous study
(1995), incorporating two models of multiple equilibrium. The two models view the
corruption from different angels. In first model individuals play role in corruption by
stealing from the government (offering bribe to obtain a driving license). While in second
model government steal from the public (political corruption), it incorporates political
instability in the model through the probability of reelection. The model obtains multiple
equilibrium in corruption, political instability and economic growth. Large public sectors
and more government intervention are associated with higher corruption in developing
countries. Broad policy implications imply comprehensive reforms moreover policies of
improved transparency.
Kaufmann et al. (2002) inspect the connection between income per capita and institutional
quality using governance indicators covering 175 countries for the period 2000-01 and
results are interpreted for Latin American and Caribbean countries. The findings show a
robust positive association between per capita income and institutional quality while a
weak negative correlation running in the opposite direction. The first highlights the
prevailing evidence regarding the significance of good governance for development while
second shows the lack of virtuous circles where higher growth leads to good governance.
The negative correlation can be attributed to the measurement error or the biased created
due to omitted variables. Moreover the elite influence and state capture are more relevant
to the developing countries. There is lack of much empirical evidence as this reverse
channel of causation has not been addressed in the literature. The study does not discuss
the channels by which institutions contribute to growth.
Chapter # 2 Literature Review
24
Glaeser et al. (2004) evaluate the association between institutions and economic growth
using cross country evidence from 1960-2000. The study examines two hypotheses first,
institutional development promotes human and physical capital investment and therefore
economic growth while the second stresses the need for human and physical capital to
promote the institutional development. The reverse that growth in income and human
capital causes institutional improvement relates to the Martin Lipset (1960) hypothesis.
Lipset relate his hypothesis to the economic success of East Asia in the post war era. Three
measures of institutional quality are used; risk of expropriation by the government,
government effectiveness and constraints on the executive. Results provide the support to
the Martin Lipset (1960) hypothesis. We cannot generalize these results, which relates to
the specific post war experience of East Asian countries. Moreover there might be some
conceptual problems related to the institutional measures used in the study as well as the
limitations of econometric techniques.
Chong et al. (2004) explore the link between institutional quality and economic growth for
Latin America. History of Latin American shows the role of military supported
autocracies. Institutions were characterized by bureaucratic traditions and highly
politicized, passed over from its Spanish and Portuguese tradition. Study uses three
measures of institutional quality; possibility of expropriation, abandonment of contracts by
government, law and order tradition from International Country Risk Guide (ICRG) and
Business Environmental Risk Intelligence (BERI). Since the subjective measures can be
biased, as they depend upon the rating of experts. As an objective measure of institutional
quality they also use Contract Intensive Money5 (CIM). Higher the ratio more favorable
5 It is the proportion of non-currency money to the total money supply, or (M2 - C)/M2, where M2 is broad
money and C is currency held outside banks.
Chapter # 2 Literature Review
25
the institutional environment will be. Results show that all the measures of institutional
quality contribute to economic growth.
Drury and Lusztig (2006) explore the association between corruption, democracy and
economic growth for more than hundred countries from 1982–97. Corruption is adversely
related to economic growth while democracy indirectly affects the growth through its
effect on corruption as it alleviates the harmful effects of corruption. Although corruption
certainly occurs in democracies, the electoral system inhibits politicians from engaging in
corrupt activities by threatening their political endurance.
Siddique and Ahmed (2010) explore the institutional-growth relationship for Pakistan
from 1984-2006. Findings provide the evidence of long run association between the both.
While there is evidence of unidirectional causality running from institutions to economic
growth. For institutional measure study develops an index of institutionalized social
technologies. This index is made up of risk reducing technologies. This index put weights
to technologies that help to restrict the rent seeking prospect arising from institutions and
political system. It is proposed that there is need of strong political and social institutions
that reduce rent seeking behaviour and also businesses risk. Study contributes in a way
that it incorporates the institutional quality index different from all other studies. But the
significance of the study can be increased by incorporating other indicators of institutional
quality commonly used in the literature which will also provide a sensitivity analysis.
Gani (2011) empirically examines the governance growth link for 84 developing
economies using panel data from 1996 – 2005. The study examines the various
dimensions of governance using data from (WGI) for low and middle income countries.
Regression specification shows that political stability and government effectiveness are
directly associated to economic growth while voice and accountability and corruption are
adversely related to economic growth. The regulatory quality and rule of law remain
Chapter # 2 Literature Review
26
insignificant. The results for voice and accountability is surprising, which is mostly
positive in many other studies as well as rule of law and regulatory quality, which are
insignificant. The study does not provide the rationale for such relationship.
Ahmad and Marwan (2012) examine the relation between institutions and economic
growth in a panel of 69 developing countries from1985-2008. Three institutional measures
are used; property rights, bureaucratic efficiency and political institutions. Three sources
of institutional variables are utilized; International Country Risk Guide (ICRG), Gastil
index and polity II. Property rights appear as the most significant institutional indicator for
growth for whole sample as well as for East Asia. Bureaucratic efficiency also contributes
to growth in whole sample but not in East Asia. Negative coefficient for political rights for
East Asia favours the non-democratic government in the East Asian economies. Study
confines that institutions affect the growth through total factor productivity.
Albassam (2013) observes the relationship between governance and economic growth in
the presence of crisis. The study is different in a way that most of the earlier literature
discusses only the governance growth link. The study examines the relationship between
governance and growth in the presence of crisis. Economic crisis of 2008 has affected the
economies of all the countries economically and politically as a result of weak
infrastructure at global as well as local level. Taking the data of all the countries from
(WGI) study considers the time period from 2006-11. Study divides the sample into pre
(2006-08) and post crises period (2009-11). Results of the correlation show that before and
after crisis a significant relationship holds between economic growth and each indicator of
governance. Further he analyzes the effect of level of development on this relationship, by
dividing the sample into four groups; very high, high, medium and low level of
development, based on HDI statistics. Now previous results do not hold for each group. In
groups with very high and high level of development previous relationship hold but in
Chapter # 2 Literature Review
27
other two groups reverse hold. It is suggested for the governments to adopt the measures
that maintain a strong association between governance and economic growth in the long
run as well as short run.
Fayissa et al. (2013) evaluate the relationship between governance and economic growth
for 28 Sub Saharan African countries from 1990-2004. The economies of these countries
are characterized by political instability, government ineffectiveness, poor law and
massive corruption which represent the bad governance. Six governance measures are
used both at aggregate and disaggregate level as given by (WGI). Results imply that good
governance positively contributes to economic growth regardless of the measure used.
Government effectiveness highly contributes to economic growth followed by voice and
accountability while control of corruption has least contribution. Study also evaluates the
impact of good governance on different income groups (low, middle and high income
groups). Study concludes that good governance is important for growth especially for
those countries which are at lower level of income.
Yerrabati and Hawkes (2015) empirically examine the relationship between governance
and growth for South Asia, East Asia and Pacific region from 1980-2012. Governance has
been a highly controversial matter in the Asian context. Six disaggregated measures of
governance by (WGI) are used, findings through the Meta regression analysis imply that
voice and accountability and extent of corruption are positively related to economic
growth. They explain that if corruption reduces the bureaucratic delays then it facilitate
investment and hence economic activity. Political stability, government effectiveness and
rule of law are negatively associated to economic growth. Regarding the political stability
it is argued that if it is achieved through oppression or if it produces stagnation then it
negatively contributes to economic growth. Negative effect of government effectiveness is
surprising. Negative effect of regulation is also surprising as most of the countries in this
Chapter # 2 Literature Review
28
region have gone under deregulation process since late 1980s. There is need of further
research regarding this aspect of institutions. The study does not discuss the channels
through which governance will affect the growth.
Bhattacharjee et al. (2015) empirically examine the role of institutions in economic growth
for four major South Asian economies. Poor institutional quality especially political
instability and crisis along with other factors make South Asia an appropriate case
regarding this context. Institutional measures provided by (WGI) are used for the period
1996-2010. Findings from both the fixed effect and dynamic panel data by GMM provide
the evidence that institutions significantly contribute to economic growth. Voice and
accountability and government effectiveness contribute to economic growth while others
measures of institutional quality remain insignificant in explaining the growth. Speed of
convergence slightly improves while controlling voice and accountability. The study
proposes reforms regarding the institutional framework. The study does not discuss the
rationale for the insignificant indicators.
2.1.3 Concluding remarks:
Empirical review of literature on institutions-growth link shows that these studies have
concentrated on either one or more institutional measures. Main sources of the institutional
measures are; Worldwide Governance Indicators, International Country Risk Guide
(ICRG), Business Environmental Risk Intelligence (BERI), Freedom House and Polity.
Dimensions of institutions that these sources discuss are; political rights, economic
freedom, bureaucratic efficiency, corruption and regulatory infrastructure. Studies use
different sources also for sensitivity analysis. We have examined the empirical literature
regarding developing countries. All the studies included show that institutions positively
contribute to economic growth except one study, Yerrabati and Hawkes (2015), which
shows the negative association between institutions and economic growth because many
Chapter # 2 Literature Review
29
of the individual indicators are adversely associated to economic growth. There is also
another study which explains the inverse causality from economic growth to institutional
quality, Glaeser et al. (2004), supporting the East Asian experience. The way through
which institutional quality enhances economic growth is the provision of secure
environment for investment. Regarding individual institutional indicators voice and
accountability, government effectiveness, rule of law positively contribute to economic
growth. Political stability, regulatory quality and corruption show mixed results, some
studies show positive effect, some show negative or insignificant effect. Political stability
or democracy may indirectly contribute to economic growth through reduction in
corruption and increasing bureaucratic efficiency, rule of law which provides a favourable
environment for investment. While the negative sign of political stability shows that that if
it is achieved through oppression or if it produces stagnation then it negatively contributes
to economic growth. Moreover the negative sign for those samples where East Asian
countries are included shows that autocratic government are able to govern the markets
and pursue pro-growth policies. Regarding corruption only one study shows that
corruption increases the growth while all other studies follow the empirical literature that
corruption reduces the economic growth by misallocation of resources. Negative sign is
supported that some types of corruption might increase the growth by reducing the
bureaucratic delays and contribute to investment. Negative sign of regulatory quality in
one study is surprising as most of the developing countries have reduced the regulatory
burden to promote economic growth. Excess regulatory burden might retard the growth
but it needs further research. At the end we conclude that differences in institutional
measures, time period, sample and econometric methods have provided mixed results.
Most of the studies do not explain the channels through which institutions contribute to
Chapter # 2 Literature Review
30
economic growth. Moreover there is limitation of the data of institutional quality, which is
subjective and more prone to measurement error.
2.2 Financial liberalization and economic growth:
2.2.1 Theoretical review:
McKinnon and Shaw (1973) introduced the concept of financial liberalization. They
recognized that the inadequate growth performance of developing countries is caused by
financial repression therefore they advocated the need for financial liberalization.
Financial liberalization theory explains that financial control keeps interest rates low
which discourages savings and investment. Under a regime of repression low return
projects will be under taken therefore the quality of investment will be low. With financial
liberalization interest rate will increase thereby encouraging the savings and investment
which will encourage high yield projects. The theory of financial liberalization, since
McKinnon (1973) and Shaw (1973) has advanced merely focusing on credit markets
towards the equity markets and their association with economic growth in developing
countries.
Orthodox economists based their arguments on the assumption that markets are efficient.
Opponents of capital account liberalization propose that it makes a country prone to
external shocks and capital flight thereby reducing economic growth. Arnott, Greenwald
and Stiglitz (1994) criticize that poor information prevalent in the financial markets of less
developed countries can be harmful to financial liberalization. Van Wijnbergen and Taylor
(1983) criticized the McKinnon-Shaw hypothesis. They explain, using Tobin’s portfolio
framework for a household, that households will make substitution for gold or cash and
loans in the informal sector as a result of higher interest rate.
Chapter # 2 Literature Review
31
2.2.2 Empirical review:
Over the past three decades there has been enormous capital account liberalization in
many countries, including developing and emerging countries. Liberalization has provided
benefits to some countries while some have not experienced higher economic growth or
have even undergone severe financial crises and recessions. Hence, a question as to
whether financial openness is crucial to sustained economic growth requires further
clarification. Below we review some empirical literature regarding the relationship
between both.
Alesina, Grilli and Milesi-Ferretti (1993) provide the indication of a direct relationship
between capital account liberalization and economic growth for a sample of 20 high-
income countries from 1950s to the 1990s. They measure the openness by the share of
years in which transactions on capital account are unrestricted, as indicated by IMFs
Annual Report on Exchange Arrangements and Exchange Restrictions. While Grilli and
Milesi-Ferretti (1995) considers a larger cross section of 61 countries and the findings
show an inverse relation between capital account openness and economic growth in a
sample dominated by developing Countries. But both the studies do not explain the
channels through which this relationship might occur.
Quin (1997) examines the correlations of capital account liberalization and economic
growth for a sample of 65 OECD and non OECD countries from 1958-89. Using de jure
measure of IMF capital account openness he finds a positive correlation between the two
variables. Another study by Quin et al. (2008) also provides the same findings for 95
developed and developing countries. The study uses a new measure of capital account
liberalization6 that also not only considers the limitations or controls but also the
magnitude of de jure controls for residents as well as nonresidents. The study replicates six
6 It is scaled from 0–4, where 4 represents full capital account liberalization.
Chapter # 2 Literature Review
32
prior studies that show conflicting results. With new measure of capital account liberation
findings show significant results. They argue that measurement error in capital account
variables, different time periods, choice of methods and collinearity among the variables
might be the reasons for different outcome of previous studies.
Rodrik (1998) evaluates the link between capital account openness and economic growth
for a sample of 100 developed and less developing countries using data for the period
1975-1989. He uses binary measure for financial openness constructed by the IMF. He
finds no association between financial liberalization and economic growth. He provides
the evidence of Asian financial crisis which tells us that liberalization will always bring
financial crises and there is no magic bullet to stop them. Interacting capital-account
liberalization with institutions quality also provides insignificant results.
Edwards (2000) investigates the effect of capital mobility on economic performance of 20
industrial and developing economies during the 1980s. He evaluates the behaviour of FDI
flows, debt flows and portfolio flows during the sample period. Behaviour of capital flows
seems different across regions and periods. Using Quinn’s measure of openness he
concludes that liberalization contributes to growth in high-income countries while slows it
down in low-income countries. However, the evidence also points to the fact that the
positive impact of liberalization is constrained to a certain degree of economic
development. Findings propose the sequencing of capital account liberalization.
Klein and Olivei (2001) explore the relationship between capital account liberalization and
economic growth through the channel of financial deepening in a cross section of
developed and developing countries from 1986-95. They use de jure measure of
liberalization. Results regarding the developed countries infer that these countries with
higher financial liberalization have experienced greater financial deepness than countries
with higher capital controls and enjoyed higher economic growth. Results of the sub
Chapter # 2 Literature Review
33
sample show that financial liberalization does not provide same benefits to all countries.
Benefits are more concentrated towards developed countries. Results imply that policy
reforms in developing countries should concentrate on legal, economic and social
institutions before the liberalization of capital account, in order to have greater financial
depth. Study can be enriched through sensitivity analysis using other measures of
liberalization.
Arteta et al. (2001) empirically explore the association between capital account
liberalization and economic growth for 61 developed and developing countries. Capital
account openness is measured by Quinn’s index of liberalization and IMF capital account
openness measure. The findings imply that liberalization of capital account contribute to
economic growth only in countries that have well developed institutions. The study also
tests two hypotheses regarding sequencing of capital account. Results suggest that capital
account openness contributes to growth when a country has greater macroeconomic
stability and higher degree of trade openness.
Reisen and Soto (2001) observe the relationship between private capital inflows and
economic growth in a panel of 44 developing countries over the period 1986–97. Study
highlights that domestic saving solely is not enough to enhance the economic growth there
is also need of foreign resources of finance. Study emphasizes on the wide-ranging
categories of inflows; foreign direct investment, portfolio equity investment as well as
short-term and long-term bank lending. The findings propose that to stimulate the long run
growth developing countries should boost foreign direct investment and portfolio equity
investment.
McLean and Shrestha (2002) investigate the correlation between international financial
integration and economic growth for 40 developed and developing countries. The sample
period spans 1976–1995. They use the data of total capital inflows also disaggregated into
Chapter # 2 Literature Review
34
FDI inflows flows, portfolio inflows and bank inflows. The relationship between capital
account liberalization and economic growth is not robust. Findings regarding FDI and
portfolio flows remain robust moreover FDI remains the largest contributor followed by
portfolio flows and bank flows. Historically the contribution of foreign direct investment
has remained higher in developing countries as compared to other forms of capital flows.
Edison et al. (2002) examine the link between financial integration and economic growth
for a sample of 57 countries from 1980-2000. They use different measures of financial
liberalization (de jure as well as de facto measures); IMF’s restriction measure, Quinn
(1997) measure of capital account restriction, total stock of capital flows and stock of
capital inflows by Lane and Milesi-Ferretti (2002). De jure measures show the
government restrictions but do not show the magnitude and effectiveness of government
restrictions whereas de facto measures are not the subjective measures and show actual
integration. Findings do not provide the evidence of robust relationship between financial
openness and economic growth. Moreover findings also do not remain robust when
controlling for level of development, financial deepening, institutional and policy
characteristics. Study does not explain the underlying causes of such results.
Eichengreen and Leblang (2003) explore the association between capital account openness
and economic growth for a panel of 21 countries from 1880-1997 and as well for wider
panel for the post 1971 period. Capital controls is captured by presence or absence of
control during the initial year of each period while for recent years IMFs binary measure
of restrictions on capital transactions is utilized. They contend that previous studies
provide inconclusive results because they have not considered the impact of crisis on
growth and for the capability of controls to limit those effects. They consider these effects
by including capital controls and crisis in their dynamic panel. Findings infer that controls
neutralize the impact of crisis on growth and otherwise they have no additional effects.
Chapter # 2 Literature Review
35
Singh (2003) examines the empirical literature regarding capital account liberalization,
specifically short and long term capital account liberalization. The study consists of 118
developed and developing countries spanning the period 1972-98. The study analyzes the
relationship between capital flows and economic growth as well the effect of short run and
long run capital flows on saving and investment behaviour. Findings provide the evidence
of adverse consequences of short-term capital flows in Asia and Latin America in the
1990s. Contrary to this, the long term capital flows are considered more stable and growth
promoting. Such flows contribute to growth through better technology and access to an
improved human capital.
Bekaert et al. (2005) analyze the impact of financial openness on economic growth,
especially equity market liberalization. They use panel data of 95 countries from 1980 to
1997. Different de jure measures7 of capital account liberalization are employed for
robustness where each measure represents 0-1 scale. For robustness they also use
alternative measures of financial liberalization: First sign measure, capital intensity
measure, IMF openness measure and the other proposed by Quinn (1997). As the
liberalization effect is not expected to be same in all countries so heterogeneity effect is
related to the reforms regarding financial development and quality of institutions. Findings
imply that financial openness decreases the cost of capital thereby increasing the
investment and the efficiency of investment which leads to higher growth. In addition,
countries with improved legal structure, better institutional quality and supportive
investment climate show larger growth effects. Results remain valid with different group
of countries, measures of financial liberalization, regional indicators and other
specifications.
7 See for detail Bekaert et al. (2005)
Chapter # 2 Literature Review
36
Bonfiglioli (2005) evaluates the effect of financial liberalization and crises on investments
and productivity in a sample of 93 countries from 1975 to1999. He employs two measures
of openness one, de jure measure, for capital account openness and other for equity market
openness by Bekaert et al. (2003). He also uses binary variable for banking crisis. Study
discusses two channels through which capital account openness contributes to growth;
investment and productivity. Findings imply that financial liberalization boosts
productivity growth through financial development. Capital account liberalization
increases the likelihood of financial crises in developed countries only which dampens
both investments and TFP. Institutions and level of development indirectly enhance the
positive effects of financial openness on productivity.
Mody and Murshid (2005) evaluate the link between capital flows and investment for a
panel of 60 developing countries from different regions for the time span 1979 to 1999.
Study uses aggregate capital flows and also their components; foreign direct investment,
portfolio flows and bank lending. For financial integration binary variable of liberalization
dates is used. Findings show that main channel of the capital flows is foreign direct
investment (FDI) whereas the portfolio investment has the characteristic of weak
investment stimulus. Findings propose that stronger policy environment will not only
stimulate the foreign direct investment in these economies but it can also strengthen the
link between foreign inflows and domestic investment.
Kim et al. (2012) examine the dynamic relationship between financial openness, economic
growth and macroeconomic uncertainty for a panel of 70 developed and developing
countries for the period 1960-2007. They use de facto measure of financial liberalization;
external financial stocks, stock of inflows and outflows as a ratio to GDP and FDI stocks.
Findings provide the evidence of adverse effects of financial liberalization in the short run
while favourable effects in the long run. Liberalization also reduces macroeconomic
Chapter # 2 Literature Review
37
uncertainty in the long run while increases it in short run. Liberalization increases the
chances of financial crises and instability that have short-run concerns but also strengthens
financial sector that affect long-run growth and macroeconomic uncertainty.
2.2.3 Concluding remarks:
Despite intensive research regarding the association between capital account openness and
economic growth literature has produced conflicting results; positive, negative or
insignificant and conditional on other factors. An important issue regarding the capital
account liberalization is related to its measurement. There are de jure measures of capital
account liberalization that are mostly used; IMF capital account openness measure, Quin
(1997) measure of capital openness, Bekaert and Harvey (2002) measure of equity market
liberalization, Chinn and Ito (2008), Schinlder (2009) and there are many other such
measures available developed by many researchers. All these measures are based on
information by IMFs Annual Report on Exchange Arrangements and Exchange
Restrictions. All these are binary or subjective measures which only describe the presence
or absence of restriction and also have certain other shortcomings. Many researchers have
explained that variability in the results regarding capital account liberalization is also
caused by these subjective measures that increase the possibility of measurement error.
There are some studies that provide a positive association between capital account
liberalization and economic growth. These studies have used the data prior to the financial
crisis or of shorter span that undermines the effect of crisis. Few studies provide the
evidence of positive effect only in long run but not in the short run. Some studies consider
only few low income developing countries and more developed countries and find the
positive effect only for developed countries. Positive effect indicates that financial
liberalization decreases the cost of capital thereby increasing the investment and the
efficiency of investment which leads to higher growth. Empirical evidence also indicates
Chapter # 2 Literature Review
38
that financial liberalization does not provide same benefits to all countries, benefits are
more concentrated towards developed countries having well developed legal, financial and
institutional framework and fewer market distortions. Disaggregated analysis of capital
flows shows that the long term capital flows (particularly FDI) are considered more stable
and growth promoting. Such flows provide the access to technology to poor developing
countries.
Studies that show the negative correlation between the both are either of developing
countries or they explain that capital account liberalization brings with it financial crisis
mostly in developing countries that deteriorate the long run growth and some discuss that
negative relationship exists only in short run. Moreover capital account liberalization
negatively contributes to growth in countries having lower level of development, weak
institutional and financial structure and poor macroeconomic environment.
Some studies show insignificant or non-robust effect of capital account liberalization on
economic growth. It proposes sequencing of capital account liberalization and
strengthening of legal, economic and social institutions before the liberalization of capital
account.
Many studies do not explain the channels through which capital account liberalization
contributes to growth. We conclude that measurement error in liberalization measures,
sample selection, time period and methodology all contribute to different findings.
2.3 Trade liberalization and economic growth:
2.3.1 Theoretical review:
Trade has been regarded as a source of efficient allocation of resources and well-being in
orthodox theories, since the Ricardian era. The neoclassical theory proposes that trade
liberalization increases the output and consumer welfare due to efficient resource
allocation and lower prices of output and intermediate inputs.
Chapter # 2 Literature Review
39
Differences in opportunity cost between the countries determine the pattern of trade in the
Ricardian model. In the absence of trade barriers comparative advantages determine
country’s trade pattern which ensures efficient resource allocation and income distribution.
Herschel-Ohlin model determines the trade pattern through the relative abundance of
factors and their intensity in production. Models of imperfect competition propose that
trade openness and liberalization provides better resource allocation and enhances welfare.
Free trade between the countries increases competition which ultimately leads to lower
prices of inputs and output. Additionally higher openness becomes a source of technology
and which increases the growth.
The predictions of traditional trade theories, Heckscher-Ohlin and Stolper-Samuelson
models, failed abruptly as the resource abundant countries were not growing by utilization
of their abundant factor. Prebisch-Singer theory explains that rapid deterioration of the
terms of trade was the main cause of this failure due to the heavy dependence of
developing countries on primary commodities exports.
The failure of the traditional theories provided the space for the new theories which
emphasize on the industrialization and liberalization as the engine of growth. Moreover
they also explain that most comparative advantages are not inherent and they might be
developed through learning-by-doing, knowledge creation and technology transfer.
2.3.2 Empirical review:
Over the last 20 years trade liberalization in developing countries has often been
encouraged with the probability of higher growth nevertheless the evidence on its growth
promoting effects is mixed. Below we review some empirical literature.
Sachs and Warner (1995) explain that one of the sufficient condition for poor countries to
achieve higher growth and convergence lies behind the open trade policies. They introduce
an index of openness policy. The index is a dummy variable which classifies countries as
Chapter # 2 Literature Review
40
open or closed based on five criteria; tariffs, nontariff barriers, exchange rate distortion,
export marketing boards and socialist system of production. Countries are called open if
they do not fulfill any one of the criteria above mentioned. Findings show that countries
with liberal trade regimes experience 2.45 percentage points higher growth than those
under a restricted trade regime. A number of other researchers also used the Sachs and
Warner index as a measure of liberalization.
Harrison and Hanson (1999) examine the association between trade liberalization and
economic growth, employment and wage inequality. They estimate a cross-country growth
regression using individual indicators of the Sachs and Warner measure. Findings do not
provide a robust relationship between more liberal trade policy and economic growth.
They argue that previous studies that provide positive association between the both are
suffered from many econometric and data complications. Moreover the impact of
liberalization reforms on employment is small. Micro data for both Mexico and Morocco
from 1984 to 1990 provides the evidence of lesser profit margins and falling wages in
previously protected sectors. There is also evidence of rising wage inequality which is
against the Heckscher–Ohlin proposition.
The widespread belief that trade liberalization promote the growth is severely criticized by
Rodriguez and Rodrik (2000) by discussing the methodological errors in the five most
illustrative empirical studies regarding the relationship between trade liberalization and
economic growth; Dollar (1992); Ben-David (1993); Sachs and Warner (1995); Edwards
(1998); and Frankel and Romer (1999). They argue that these studies provide the strong
results which are caused either by misspecification or by the use of liberalization measures
that are proxies for other policy or institutional variables. They criticize the tariff averages
as they undervalue the high tariff rates while nontariff coverage does not discriminate
Chapter # 2 Literature Review
41
between high restrictive and less restrictive barriers. There are also conceptual
imperfections such as (effect of smuggling, data weaknesses, coding problems, etc.).
Zhang (2001) provide the evidence regarding trade liberalization, economic growth and
convergence for 10 East Asian economies from 1960 to 1996. East Asia has experienced
not only strong economic performance, but also rapid and impulsive integration over the
past few decades. The study examines the interrelationship between regional integration
and economic convergence. Exports as a ratio to GDP indicate to trade liberalization
measure. Findings provide the week evidence of convergence. It is argued that the kind of
FDI that some of the East Asian developing economies have attracted is mainly in labour-
intensive industries with low value-added, creating immiserizing growth. There is
evidence of substantial convergence of the four Asian NIEs8 and Japan. Study can be
criticized on the grounds of trade liberalization measure, exports as a ratio to GDP is a
poor indicator of liberalization which represents only trade orientation but not trade
liberalization. The evidence of week convergence among the East Asian economies might
be the result of this poor indicator of trade liberalization.
Greenaway et al. (2002) examine the impact of trade liberalization on economic growth
for a sample of 73 developing countries from 1975-93. They explore the relationship in a
panel framework using three indicators of liberalization; World Bank (1993), Dean et al.
(1994) and Sachs and Warner (1995). First indicator is a binary variable which indicates
the beginning of reform, representing a country’s first structural adjustment loan (SAL).
Second indicator is of Dean et al. (1994), which assesses timing of liberalization with
reference to four indicators: tariffs, quotas, export barriers and exchange rate distortions.
Third indicator is of Sachs and Warner (1995), a measure of movement from a closed
towards open trade policy regimes based on five criterions also described previously.
8 Newly industrializing economies; Hong Kong, Singapore, South Korea, and Taiwan.
Chapter # 2 Literature Review
42
Findings imply that liberalization contributes to growth though the effect appears after lag
as liberalization never leads to an instant shift to free trade. Sachs–Warner index provides
the stronger growth effects and whereas (SAL) provides the weakest.
Wacziarg and Welch (2003) observe the link between trade liberalization and economic
growth for 141 countries from 1970-99. For the trade liberalization measure they use the
dummy variable approach developed by Sachs and Warner (1995) but with an extended
data set for the 1990s. Findings show that trade liberalization contributes to economic
growth, investment and trade openness. Countries with liberalized trade regimes have
experienced higher growth as compared to pre-liberalization period. Time pattern reveal
that growth is raised two years after the reforms. Individual country effects show that
countries where trade liberalization contributes to growth are those with massive trade
reforms.
Goldar and Kumari (2003) analyze the effect of import liberalization on productivity
growth in Indian manufacturing industries during 1990s. During the decade of 1990 major
economic reforms took place in India regarding industrial and trade policy. The objective
of these reforms along with changes in industrial policy was to make industrial sector
more efficient and technology oriented. Tariff rate was reduced and quantitative
restrictions were also removed. Study compares the productivity growth of major
manufacturing and industrial groups for the post reform period (1990s) with pre reform
period (1980s). Findings show that reduction in the effective protection to industries
increased the productivity growth.
Dollar and Kraay (2004) discuss an important dimension of liberalization, its effect on
inequality and poverty. They have selected a sample of developing countries that have
substantially reduced tariffs and experience large increases in trade volumes since 1980.
China, India and numerous other large economies are included in this sample. Study
Chapter # 2 Literature Review
43
conducts analysis of 39 developing countries where changes in trade volumes indicate the
liberalization. Per capita growth rates of the economies have increased in the 1990s
comparative to the 1980s; China, Argentina, Philippines, Mexico are few of the successful
examples. Findings show that greater openness has reduced the gap between rich and poor
countries. Inequality has reduced in many countries such as India, Malaysia, Philippines
and Thailand. Absolute poverty has declined sharply in globalizing economies in the past
20 years. Findings are contrary to many other studies exhibiting that globalization hurts
the poor.
Aksoy Ataman (2006) analyzes the growth effects of trade liberalization, before and after
the trade reforms, for 39 developing countries from 1970-2004. He uses dummy variable
representing liberalization (zero for pre reform period and one after reform period). Trade
liberalization reveals a significant increase in GDP. Moreover, trade liberalization has also
increased investment and manufacturing exports. Acceleration occurred irrespective of
region and income per capita level moreover small countries benefited most from the
reforms. It is concluded that in developing countries trade liberalization has contributed to
sustained economic development.
Yasmin et al. (2006) examine the role trade liberalization in economic development of
Pakistan. Four measures representing economic development are examined; per capita
GDP, income inequality, poverty and employment over time span 1960-2003. For nearly
four decades Pakistan has followed a mixed inward-oriented/outward-oriented trade
policy. But this policy generated rent seeking attitudes, anti-export bias and inefficiencies.
Therefore benefits of outward-orientation policies motivated Pakistan to open up its
economy for trade in the early 1990s. Findings imply that trade liberalization has reduced
the GDP per capita. This is in contrast with previous literature. It may be due to the import
substitution policies. It has increased the employment level while it has no effect on
Chapter # 2 Literature Review
44
poverty and distribution of income has become worse. Liberalization has reduced the
proportion of labor in production and concentration of income more in favor of capital
owners. The study can be enriched by undertaking before and after analysis of
liberalization which will also provide a sensitivity analysis.
Morgan and S. Kanchanahatakij (2008) examine the effect of trade liberalization on
economic growth for a sample of 37 liberalizing countries from 1970-98. As a measure of
liberalization they use the liberalization dates from Sachs and Warner (1995) index and
updated by Wacziarg and Welch (2003). As this measure does not capture the extent of
liberalization therefore they also use another measure the ratio of trade taxes and several
measures of trade volume. Findings imply that trade liberalization promotes the economic
growth. It is concluded that countries can benefit from trade liberalization with lower trade
taxes, higher human capital and higher imports of R & D. It is proposed that to examine
the true impact of trade liberalization study of single country can provide a more fruitful
finding.
Chang et al. (2009) empirically explore that free trade contributes to faster growth using
an unbalanced panel of 82 countries spanning the 1960–2000. The sample includes 22
developed countries and 60 developing ones. Using two measure of outward orientation;
trade openness and import duties, they also find that to improve productive efficiency and
growth trade liberalization needs to be supplemented by corresponding reforms. These
include macroeconomic and institutional reforms (including governance and financial
development). Findings are robust to various specifications.
Ghani (2011) analyzes the link between trade liberalization and economic performance
(exports, imports and GDP per capita) for 24 OIC9 countries that have undergone trade
liberalization process between 1970 and 2001. Liberalization is represented by dummy
9 Organization of Islamic Cooperation.
Chapter # 2 Literature Review
45
variable that equals zero before liberalization and one after liberalization. Findings imply
that trade liberalization has improved GDP per capita but unlike the GDP the ratio of
exports, imports and trade has not improved much after liberalization. The improvement in
GDP per capita does not reflect the dynamic gains from trade as there is not much gain
from trade.
Mani and Afzal (2012) examine the effect of trade liberalization on the economy of
Bangladesh from 1980-2010. Liberal trade policies of late 1980s provided an opportunity
to Bangladesh economy to enhance economic growth and development. In the last two
decades Bangladesh has expanded its export oriented garment and textile industry. The
study analyzes the achievement of the economy in the sense of growth, inflation, exports
and imports after liberalization. Liberalization is measured as trade openness. Empirical
findings show that GDP growth has increased after liberalization. Liberalization has also
increased real exports and imports but it has not affected the inflation. Increase in exports
has increased the economic growth after 1990s. Use of other liberalization measures
commonly used in literature can strengthen the validity of results.
Falvey et al. (2013) observe the impact of trade liberalization on economic growth for 58
developing countries from 1970-2005. They use Sachs-Warner index of openness and also
the date of liberalization. In panel growth regression trade liberalization and openness
contributes to economic growth. They identify the effect of liberalization on economic
growth through four channels; capital formation, government finance, openness to trade
and price distortions.
Paudel (2014) investigates the relationship between trade liberalization and economic
growth for a large set of panel data covering the period of 1985-2010. He updates the
Sachs and Warner (1995) index of trade liberalization for 193 countries up to 2010.
Findings comprise that trade liberalization positively contributes to economic growth and
Chapter # 2 Literature Review
46
consistent with the previous literature. Study concludes that not all income group benefit
equally by the liberalization their stage of development matters to benefit from
liberalization. Their trade and investment capability, and distortion level determines the
benefit from the liberalization.
2.3.3 Concluding remarks:
Literature on trade liberalization and growth is not as broad as that on trade orientation and
growth. Most of the literature identifies positive association between trade liberalization
and economic growth. Very few studies find no relationship, or even a negative one
between both variables. Some studies emphasize on other conditional factors to get the
benefit of liberalization. Most of the literature also undertakes before and after analysis.
Most of the literature that emphasizes on the contribution of trade liberalization in
economic growth analyses its role indirectly through different channels; capital
accumulation, export diversification, higher imports of R & D that indicate technology
transfer and through total factor productivity (TFP) enhancement. In the same way few
studies discuss that contribution of trade liberalization in economic growth can be
enhanced through macroeconomic and institutional factors as well as level of development
of countries also matters to benefit from liberalization.
The channel through which trade liberalization negatively contributes to economic growth
explains the evidence of increase in poverty, income inequality and declining wages.
Liberalization has reduced the fraction of labor in production making distribution of
income concentrated towards capital owners. It is also argued that imports increase after
liberalization and generally trade balance become worse. In the same way only few studies
discuss that trade liberalization and growth are unrelated and do not provide robust results.
Main reason of no association is the misspecification and use of misleading indicators of
trade liberalization.
Chapter # 2 Literature Review
47
Normally the indicators of liberalization that are extensively used in the literature are
subjective measures; dates of liberalization, Dean et al. (1994) and Sachs and Warner
Index (1995). All these are dummy variables that do not show the extent of liberalization
and as well the policy reversals. Although most of the studies use trade openness as an
indicator of liberalization but it’s the measure of trade orientation not liberalization.
Rodriguez and Rodrik (2000) criticize the previous literature on the grounds of proxies
used.
2.4 Fiscal policy and economic growth:
2.4.1Theoretical review:
Classical model has the characteristics of perfectly competitive markets and there is price,
wage and interest rate flexibility. It assumes that there is full employment in the economy
and the aggregate supply curve becomes vertical. Higher government expenditures raise
the interest rate through the demand for funds, deficit financing, which reduces the private
investment. This crowding out effect offset any positive effects of the policy implemented
thus fiscal policy has no effect on the economy and it cannot be used as a stabilizing tool.
Keynesian theory is characterized by short run price rigidity while individuals experience
money illusion10
. There is unemployment in the economy as there are unused resources.
Aggregate supply curve is fully elastic in short run at unchanged prices while it is vertical
in the long run at full employment. Fiscal policy significantly affects the output and
employment while the total effect of higher government spending depends on relative
magnitude of the multiplier and crowding out effects (Mankiw 2000).
In the neoclassical model there comes the role of expectations, workers predict the price
level and adapt their expectations at the real level of prices (P = Pe). Differences between
the real and the expected levels of prices in short run can affect the level of equilibrium
10
It refers to the behavior of people to think of money in nominal, rather than real, terms. The nominal value
of money is wrongly considered for its real value.
Chapter # 2 Literature Review
48
output and the aggregate supply curve becomes positive sloped in the short-run. While in
the long run it becomes vertical therefore for the stabilization of the economy fiscal policy
is not important. The neoclassical model has been used widely for the analysis of fiscal
policy and was developed by Lucas, Sargent and Wallace.
Unlike the Keynesian theory the assumption of money illusion is not central in neo-
Keynesian models. Due to imperfect information, as workers do not have complete
knowledge regarding future prices, economic activity fluctuations. Aggregate supply curve
is more elastic and the level of output fluctuate more in the short run.
2.4.2 Empirical Review:
Fluctuations in fiscal policy either through taxation or expenditure have been extensively
investigated in the empirical literature. Endogenous growth models predict that the effect
of fiscal policy on economic growth is of both temporary and permanent nature. Empirical
studies regarding the relationship between fiscal policy and economic growth, however,
have produced mixed outcomes. Below we review the literature regarding developing
countries.
Barro (1989) analyses the relationship between growth, savings and government policies
for a cross section of about 120 countries from 1960-85. Government consumption
expenditures excludes the defence and education expenditures, which he treats productive
expenditures. Investment expenditures represents to a proxy for infrastructure activities
that affect the private investment. Defence expenditures represent national security and
property rights. Their effects on investment and growth are expected as productive
government spending. Variable of education also works like investment expenditures.
Government transfers for social insurance and transfers represent the consumption
expenditures. Consumption spending declines with per capita income. Transfers are
positively associated with growth but negatively associated with investment. This positive
Chapter # 2 Literature Review
49
relationship might reflect the reverse causation from growth to spending. Public
investment positively contributes to growth and investment. Education and defence
spending remain insignificant in explaining the growth and investment contrary to the
expectations.
Engen and Skinner (1992) examine the link between fiscal policy and economic growth
for 107 developed and developing countries from 1970-85. Government expenditures and
average tax rate indicate fiscal policy instruments. Findings comprise that both are
negatively related to economic growth. Government spending reduces the output growth
in Africa, Latin America and developing countries. The study can be improved by further
undertaking disaggregated analysis of expenditures and revenues which can provide the
rationale for the negative effect of both. Regarding the tax rate it can be argued that
structure of the tax and tax base across the countries might undermine the results.
Easterly and Rebelo (1993) evaluate the effect of fiscal policy on economic growth and
development in a wide cross section of 100 countries from 1970-1988. Findings imply that
government budget surplus positively contribute to private investment and economic
growth. Investment on transportation and communication is robustly related to growth.
Public investment has a positive effect on capital formation and growth. Fiscal structure
contribute to level of economic development; less developed countries rely more on trade
taxes while developed countries rely more on direct taxes moreover rich countries have
higher health and social security expenditures.
Devarajan et al. (1996) analyse the relationship between public expenditures and
economic growth for a panel of 43 developing countries from 1970-90. Findings show that
current expenditures positively contribute to per capita income and while capital
expenditures are negatively associated to economic growth which is opposite to believed
hypothesis. Aggregate government expenditures remain insignificant. Expenditure share
Chapter # 2 Literature Review
50
according to functional classification show that defence and infrastructure expenditures
are negatively related to growth which is in sharp contrast to earlier findings. Different
categories of health and education expenditure are negative or insignificant. Findings
remain robust while using other methodologies. It is argued that some white elephant
capital expenditures might be in governments’ objective function which lowers the
marginal productivity of capital. Findings imply that developing countries’ governments
are misallocating the resources. There are also problems in the data that might be liable to
contradictory results as some countries include development expenditures in productive
expenditures while others contain some current expenditure as well.
Guseh (1997) examines the relation between government size and economic growth across
political and economic systems in 59 middle income developing countries from 1960–85.
As a measure of government size he uses two specifications; one is the current expenditure
growth rate while the other is the growth of the relative size of public expenditure. Former
indicates the short run effect while latter reveals the long run effect. Findings show that
government creates distortions in the economy through the devices of taxation and
spending and also through rent seeking behaviour. These distortions retard the economic
growth but the existence of socialist and nondemocratic systems brings higher decline.
Findings propose that a suitable remedy for economic growth and development includes a
fall in government size and the provision of economic and political freedom.
Gupta et al. (2002) evaluate the relationship between fiscal adjustment, structure of public
expenditures and economic growth for 31 low income countries from 1990-2000. Findings
reveal that strong fiscal position and improvement in the fiscal balance, is related to
economic growth in the short as well as long run. Fiscal composition shows that
expenditures on wages and salaries are negatively related to growth while expenditures on
other goods and services and capital expenditures foster the growth. Moreover a
Chapter # 2 Literature Review
51
reallocation of current outlays to capital is positively associated to more persistent fiscal
consolidation. It is concluded that fiscal composition towards more productive uses is
important for enhancing the growth and towards fiscal adjustment.
Bose et al. (2003) examine the impact of disaggregated government expenditures on
economic growth for a panel of 30 developing countries over the period 1970-90. Findings
show that capital expenditures positively contribute to growth while current expenditures
remain insignificant. The sectoral analysis shows that government investment and
expenditures on education remain significant and contribute to growth. While public
investments and expenditures in other sectors (transport and communication, defence) do
not remain robust. Government budget deficit is negatively associated to economic
growth. Analysis strongly supports the widespread belief in modern growth theory that
education is the key to success. Findings propose that developing countries should invest
on capital expenditures in order to enhance the growth. The study does not provide the
supportive arguments why the current expenditures do not contribute to growth as well the
capital expenditures.
Kukk Kalle (2007) evaluates the effect of fiscal policy on economic growth using a panel
of 52 developed and developing countries. Findings show that indirect taxes positively
contribute to economic growth while direct taxes remain insignificant. It implies that if the
government wants to increase the revenue it should chose the indirect taxes instead of
direct taxes. Direct taxes are distortionary in the sense that they distort the decision to
invest. On the expenditures side spending on employees, consumption spending or social
benefits are negatively related to economic growth while investment expenditures are
positively related to growth. Interest spending is negatively associated to economic growth
indicating that debt financing do not contribute to growth. It is proposed that to accelerate
Chapter # 2 Literature Review
52
growth, government should raise taxes and cut current expenditure or increase investment
expenditures.
Alam and Butt (2010) examine the long run relationship between social sector
expenditures such as education, health and social security and economic growth in 10
developing countries from (1970-2005). Empirical analyses provide the evidence of a long
run dynamic relationship among education, health and social security expenditures and
economic growth for all countries included in the sample. These social sector expenditures
increase the economic growth through productivity enhancement. Panel cointegration
investigation also provides the evidence of a long run dynamic relationship. Findings
imply that expenditure composition has a significant role in stimulating the economic
growth. There is need of modification in fiscal expenditures such that that a decrease in
unproductive expenditures and increase in the social sector expenditures.
Ali and Ahmad (2010) empirically evaluate the effect of fiscal policy on economic growth
for Pakistan from 1972-2008. In Pakistan the growing budget deficit is considered as one
of the key restraints to economic growth. Findings show that in the long run fiscal deficit
is negatively associated to national savings and reduces the economic growth. Politically
motivated and unproductive expenditure of the government is a major constraint to
economic growth in Pakistan. Only the debt servicing and security expenditures outstrip
the development budget. Findings propose that the government should curtail
unproductive expenditures while paying high attention on the public sector development
plan to promote the long run growth.
Gallo and Sagales (2011) evaluate the impact of different fiscal policy instruments on
economic growth and inequality for a panel of 43 upper, middle and high income countries
from 1972-2006. The empirical findings show that higher current expenditures and direct
taxes reduce the economic growth and inequality. Public investment expenditures increase
Chapter # 2 Literature Review
53
the growth rate and reduce the inequality. Current expenditures show the tradeoff between
growth and inequality while investment expenditures improve both. Findings propose that
government can avoid the trade off by curtailing the current expenditures and increasing
the capital expenditures.
Acosta Ormaechea and Yoo (2012) examine the effect of tax composition on economic
growth for 69 high, middle and low income countries from 1970-2010. Findings show that
with constant overall tax burden an increase in income tax and reduction in consumption
and property taxes is negatively related to economic growth. A shift from income to
property taxes significantly fosters the growth and remains robust. When the decrease in
income tax is adjusted with a rise in VAT and sales taxes it significantly contributes to
growth. Disaggregated sample according to income levels also provide consistent findings
as earlier in case of middle and upper income countries. Findings do not remain robust for
low income countries. It might be due to their poorer quality of tax administration and tax
enforcement.
Ormaechea and Morozumi (2013) examine the public expenditures-growth relationship for
56 low, medium and high income countries from 1970-2010. There are many studies
relating the change in expenditure composition to economic growth. They highlight the
components which can be used as compensating factors in order to keep the level of total
spending fixed. Reallocations of government spending across different expenditures do not
show a robust behaviour except the education spending. When a rise in this spending is
compensated by a fall in social protection spending, there appears to be a robust relation
with economic growth. This implies that education could have been a relatively more
efficient outlay to foster growth, through human capital accumulation. Finding is robust to
additional control variables and the use of a subset of countries.
Chapter # 2 Literature Review
54
Gangal and Gupta (2013) evaluate the link between public expenditures and economic
growth for India from 1998-2012. One of the objectives of public expenditure policy is
higher and sustainable growth. Findings reveal that public expenditures are positively
associated with growth. Moreover there is evidence of unidirectional causality from public
expenditures to economic growth. There is also positive effect of shocks in public
expenditures to GDP. Findings imply that government should increase the public
expenditures to encourage the economic growth. Study does not explain the channels
through which public expenditures contribute to growth.
Morozumi and Veiga (2014) examine the role of institutions in spending growth
relationship for 80 developed and developing countries from 1970-2010. They use
constraints on executives as a proxy for checks and balances on the policy makers, and the
type of government as democracy/autocracy as a measure of political and economic
freedom of citizen’s. Findings show that capital expenditures significantly contribute to
economic growth in the presence of institutional constraints. An increase in current
spending does not provide robust findings. Institutions enhance the efficiency of capital
spending providing little room for rent seeking behaviour and thus promote growth11
.
2.4.3 Concluding remarks:
Empirical literature regarding the role of fiscal policy in economic growth contrasts in
terms of data sets, indicator used regarding fiscal policy, econometric techniques and
sample selection. There are numerous deficiencies in the quality of fiscal data regarding
the classification that might be accountable to contradictory results as some countries
include development expenditures in productive expenditures while others contain some
current expenditure as well. Structure of the tax and tax base across the countries also
11 There tends to be larger possibility for discretion in capital than current spending because current spending
is on fixed outlays (e.g., wages, pensions and interest payments on the debt).
Chapter # 2 Literature Review
55
differ as some countries have high tax base and low tax rate while others go opposite so it
becomes difficult to intercept the results with these limitations. The link between public
expenditure and economic growth is highly dependent on the set of countries taken into
consideration. A large body of literature is based on the experiences of developed
countries there remains little prospect of economic growth for developing countries.
Most common findings regarding the public expenditure and their composition across the
countries show that aggregate government spending adversely contribute to economic
growth while the disaggregated analysis shows that public investment expenditures
positively contribute to growth while current or consumption expenditures are negatively
associated with economic growth or remain insignificant. It is argued that fiscal policy
depresses the economic growth through distortionary effect of taxes and inefficient public
spending. On the other hand the opposing view also holds that there is an important role of
the government in providing public goods and services and infrastructure. Capital
expenditures provide necessary infrastructure to promote private investment. Regarding
current expenditures it is argued that some categories of these expenditures are
unproductive moreover these expenditures are utility or welfare enhancing not growth
enhancing. Higher taxes need to finance the consumption expenditures reduce the
incentive to invest. Functional classification of expenditures shows that government
investment expenditures such as infrastructure services, transportation and communication
increase the private sector productivity and growth. While certain government
consumption expenditures such as transfers to households increase the utility or welfare of
the households but lower the economic growth as higher taxes need to finance the
consumption expenditures reduces the incentive to invest. Expenditures on wages and
salaries, interest payment adversely affect the growth while expenditures on goods and
services foster the growth. Regarding the social sector expenditures findings are
Chapter # 2 Literature Review
56
ambiguous. In developing countries fiscal adjustment that relies on cuts in transfers and
wages can be expansionary while those rely on tax increase and cuts in investment
spending tend to be contractionary. Empirical literature proposes the reallocation of
expenditures composition from current to capital expenditures as growth enhancing
strategy for developing countries as these countries already lack infrastructures like
transport and communications, roads, railways etc. that help promote private capital
accumulation.
There is exception of some studies that provide conflicting results like; Devarajan et al.
(1996) provides the evidence of positive association between current expenditures and
economic growth while a negative one between capital expenditures and growth in
developing countries. It is argued that there might be some white elephant projects which
lower the marginal productivity of capital investment. However several components of
current expenditure might have higher return than capital expenditure. Sattar (1993) finds
that government consumption expenditures positively contribute to economic growth for
Asian developing countries therefore efficiency enhancing role of government outweighs
the efficiency reducing role. Gong and Zou (2002) argue that higher infrastructure
spending may deteriorate the economic growth if spending on basic economic services is
ignored.
Regarding the tax revenue and tax composition empirical literature shows that tax revenue
positively contribute to growth while tax composition shows that direct taxes are
negatively associated with growth while indirect taxes (VAT and sales taxes) positively
contribute to growth. Direct taxes are called production taxes they decrease the rate of
return to private investment by discouraging the investment and reducing the rate of
growth.
Chapter # 2 Literature Review
57
2.5 Monetary policy and economic growth:
2.5.1 Theoretical review:
Regarding the effect of monetary policy on economic activity there are two limiting cases
in theoretical literature, Keynesians and Monetarists. Keynesians intend that money policy
has no role to play therefore it is ineffective to influence the long run growth. While
Monetarists believe that money does play a role thereby monetary policy affects the
economic growth. Monetarists on the other hand believe on a direct association between
the real and monetary sector of the economy. There are two important considerations that
ensure the relation between changes in real money stock and changes in income. First, the
relation between interest rate and money stock and second the interest rate and aggregate
demand. It is concluded that expansionary monetary policy increases the output and
economic activity by increasing the aggregate demand in the short run.
Keynes introduced the concept of liquidity trap which explains that at very low level of
interest rate a rise in money supply will not affect the output and growth. Monetarists
support their argument through the equation of exchange specified by Irvin Fisher, where
only the money supply brings changes in output. Keynes argues that in order to curtail
recession and to control the inflation stimulating the demand is accurate approach, but
both cannot be achieved at the same time.
Robert Mundell (1963) advocates monetary policy, in response to Keynes doctrine, if the
objective is to manage inflation whereas in order to stimulate the employment and output
fiscal policy can play its role.
2.5.2 Empirical review:
Monetary policy has an important role to play in economic stability; price and output
stability. The central bank autonomy has often been limited in developing economies due
to fiscal pressures leaving little room for independent monetary policy actions.
Chapter # 2 Literature Review
58
Nonetheless, as a result of recent economic reforms in less developed economies central
banks are becoming increasingly independent. The monetary transmission mechanism is
weaker in developing countries as compared to advanced and emerging economies. Below
we examine the empirical evidence regarding the effectiveness of monetary policy in
developing countries.
Christiano et al. (1996) evaluate the impact of monetary policy shocks on the US economy
from 1960Q1-1992Q4. They use federal funds rate and non-borrowed reserves as
indicators of monetary policy to analyse the effect of monetary policy shocks on flow of
funds between different sectors. VAR analysis shows that contractionary monetary policy
declines business sector flow of funds. Net funds raised by the households remain
unchanged for several quarters as households do not adjust their financial assets and
liabilities instantaneously after a monetary shock. The net funds raised by the government
sector increases after a temporary reduction as the deficit goes up. Monetary shock also
affects the macroeconomic aggregates; decline in real GDP, employment, retail sales, non-
corporate financial profits and a sharp decline in prices. It increases the unemployment
and manufacturing inventories.
Fatima and Iqbal (2003) analyse the relative efficiency of fiscal and monetary policy for 5
developing countries from South and East Asia for the time span 1970-2000. They use
money supply and government expenditures as indicators of monetary and fiscal policy
respectively. In case of Thailand there is evidence of bidirectional causality between fiscal
policy, monetary policy and economic growth (economic growth negatively affects the
fiscal and monetary variables). In case of Indonesia, Pakistan and India there is
unidirectional causality between the fiscal and monetary variables and economic growth
(fiscal policy negatively influence the economic growth). Unidirectional causality in
Malaysia provides the evidence of effectiveness of both policies in economic growth. It is
Chapter # 2 Literature Review
59
concluded that effectiveness of both policies differ in each country depending on the
nature of the economy.
Cheng (2006) investigates the effect of monetary policy shock on output, prices and
nominal effective exchange rate for Kenya from 1976-2005 using VAR analysis. Using
short term interest rate as an indicator of monetary policy findings infer that a positive
monetary policy shock reduces the prices and leads to appreciate the currency value.
Monetary policy shock has no effect on output. One reason for no response of output
against the shock might be the poor financial and regulatory system of Kenya which
hampers the monetary transmission to the real sector. Effectiveness of the study can be
enhanced by including some other countries from the same region and comparing their
results with the results of Kenya which will also provide a robustness check.
Ali et al. (2008) examine the relative significance of fiscal and monetary policies for
South Asian countries from 1990-2007. Though fiscal and monetary policies are
implemented by different authorities hence both are not independent. Fiscal balance and
broad money represent fiscal and monetary policy respectively. Findings indicate that
money supply significantly contribute to economic growth while fiscal balance remains
insignificant. Findings illustrate that monetary policy is a powerful tool than fiscal policy
in order to boost economic growth. We can criticise the study on the grounds that it does
not provide the mechanism through which monetary policy will affect the growth.
Buigut (2009) identify the importance of interest rate channel for the East African
countries from 1984-2005. A parallel monetary policy action leads to different outcome
between countries. Study uses the VAR to assess the similarity of transmission mechanism
in the East African countries. Impulse response functions ascertain the speed and size of
the effects of unanticipated monetary policy tightening. Findings imply that a monetary
contraction affect the output in a relatively similar way for all the countries but seems
Chapter # 2 Literature Review
60
insignificant while its effect on inflation rate in terms of the speed and direction seems
different for the countries. One of the most important underlying reason for insignificant
effect of interest rate channel might be the underdeveloped financial system in these
economies therefore it is likely that the credit channel might constitute the main source of
investment finance.
Gul et al. (2012) examine the linkage between monetary policy instruments and economic
growth for Pakistan from 1995-2010 by using monthly data. The objective of central bank
is to stabilize the output and prices through an efficient monetary policy. Findings reveal
that a positive interest rate shock (contractionary monetary policy) shows a persistent rise
in the price level. A tight monetary policy is generally believed to reduce the price level,
not increase it. It suggests that monetary policy shocks are not a source of output
fluctuations in Pakistan. Regression results intend that contractionary monetary policy in
terms of higher interest rate is negatively associated to economic growth which
discourages the private investment. It is proposed that central bank can improve the
economic health by by eradicating the price uncertainties associated with inflation.
Hussain and Siddiqi (2012) analyze the relationship between fiscal, monetary policies,
institutions and economic growth for Pakistan from 1976 to 2008. Fiscal and monetary
policies both play an important role in the economic growth and stabilization of a country.
In the developing countries like Pakistan growth is not consistent at a certain level.
Therefore to enhance the effectiveness of these policies and to foster the economic growth
institutions can play their role. Findings show that monetary policy is effective and
economic institutions play an important role in increasing the per capita GDP growth.
Fiscal policy, political and social institutions have no significant association with
economic growth. Findings propose that there is need to enhance the efficiency of
Chapter # 2 Literature Review
61
institutions. Effectiveness of the study can be enhanced by including some countries from
the same region for comparison.
Coric et al. (2012) examine the impact of monetary policy shocks on output and prices in a
cross country analysis of 48 developed and developing countries by using the structural
VAR model. They use quarterly data from 1975-2009. Money supply and domestic
interest rate are used as monetary policy indicators. Findings show that a monetary policy
shock has a greater effect on output and prices in countries with a larger financial sector.
The effect of a monetary policy shock on output and prices are smaller in the countries
with fixed exchange rates. In financially open economies, a flexible exchange rate regime
leads towards a more effective monetary policy12
. In larger economies monetary policy
shock has a larger effect on output as well. The effects of a monetary policy shock on
output and prices are not different while considering different income groups. It is
concluded that higher integration has increased the significance of foreign factors.
Younus (2013) examine the effect of fiscal and monetary policy on output growth for
Bangladesh from 1980-2011. Since 1970s Bangladesh has been following expansionary
monetary policy with substantial fiscal deficits. Centrally planned framework of early
1970s has also contributed significantly in accumulating huge fiscal deficits. As a result of
economic reforms since early 1990s monetary policy has gained some independence in
achieving and sustaining price stability. Broad money and government expenditures
represent monetary and fiscal policy respectively. The empirical findings show that both
the monetary and fiscal policies significantly contribute to output growth with different
magnitudes and significance. Monetary policy has relatively stronger impact than that of
12
As in fixed exchange rate regime any monetary policy shock is compensated by the opposite reaction in
order to maintain the exchange rate fixed.
Chapter # 2 Literature Review
62
fiscal policy on output growth in Bangladesh. Findings propose that there is need to rely
more on monetary policy as compared with fiscal policy to achieve higher growth.
Fetai (2013) explores the effectiveness of fiscal and monetary policy during financial
crises in developing economies. Financial crisis are associated with output loss or cost.
The banking crises and currency crises are related to intense recession in these economies.
They use two measures of monetary stance; change in discount rate and change in
international reserves. Stance of fiscal policy is measured through discretion in the fiscal
policy. Findings show that contractionary fiscal and monetary policy increases the cost of
crisis. Expansionary monetary policy is unrelated to output cost associated with financial
crises while fiscal expansion is associated with lower output cost of crises. Findings
propose that a policy mix, expansionary fiscal and a neutral monetary policy, decreases the
output cost in the presence of crisis in developing countries. Study can be criticized as it
does not explain the mechanism through which expansionary fiscal policy will be more
effective during the crisis while expansionary monetary policy will remain neutral.
Ivrendi and Yildirim (2013) analyze the impact of monetary policy shocks on
macroeconomic variables for six emerging economies (BRICS_T)13
from 1995: M01-
2012:M08. Findings through the VAR analysis show that contractionary monetary policy
shock appreciates the domestic currency as nominal exchange rate initially rises in all the
countries, there is evidence of overshooting behavior. Monetary policy shock controls the
inflation by exchange rate appreciation in all countries except Russia as Russian monetary
policy has failed to achieve sustained low inflation due to the policy of exchange rate
targeting. These shocks are effective in reducing output in India, South Africa, Russia and
China. Moreover these shocks have negative effects on exports while the response of
13
Brazil, Russia, India, China, South Africa and Turkey.
Chapter # 2 Literature Review
63
imports is significantly positive in the all countries. Net effect on the trade balance is
negative as the shock initially deteriorates the trade balances in these economies.
Kandil (2014) examine the impact of monetary policy shocks on output and prices for a
sample of 105 developing countries from 1968 to 2008. He undertakes both the time series
and cross country analysis. Many central banks in developing countries are not
independent in their operations and are somehow obliged to finance the government
spending. Study undertakes two channels that cause the interaction between monetary
policy shocks and the aggregate economy: an aggregate demand channel and an aggregate
supply channel. Time series evidence shows that expansionary monetary shocks increase
both the output and price. Supply related constraints impede output expansion and increase
price inflation against the expansionary shocks. Cross country analyses shows that the real
effects of monetary shocks depends on price flexibility, demand elasticity, and monetary
policy variability. Findings show that output growth decreases significantly against the
expansionary monetary shocks with price flexibility. This specifies a strong substitution
between the real and inflationary effects of monetary shocks, reflecting supply-side
constraints. Expansion in the aggregate demand increases the real effect of monetary
shocks, implying that transmission channel of aggregate demand appears to be more
strong. Monetary shocks increase the price variability moreover the variability of
monetary shocks is positively related to inflation variability.
2.5.3 Concluding remarks:
The analysis of monetary policy in developing countries has been hindered due to the lack
of a clear announcement of the direction of monetary policy. It is common perception that
central banks in many developing countries lack independence in their operations as they
are obligated to finance the government deficits. There are different monetary
transmission channels such as interest rate, credit and exchange rate. Monetary policy
Chapter # 2 Literature Review
64
affects the real economy through these channels. The significance of each of these
channels is determined by the economic, legal and financial structure of the economies. A
similar monetary policy action can lead to different behaviour between countries.
Conventional economic literature links the monetary policy and the real economy through
the aggregate demand. There is also some supply side evidence where a change in the
nominal interest rate is associated to output changes through production costs.
Empirical findings of almost all the studies show that contractionary monetary policy
declines the economic activity by discouraging the private investment through the
aggregate demand channel. Expansionary monetary policy increases the output and
decreases the output variability, indicating an important role for monetary policy to revive
growth by availing liquidity. There are only few studies that show the insignificant effect
due to the underdeveloped financial and regulatory framework especially from Afrcican
countries. Many studies evaluate the relative efficiency of fiscal and monetary policy by
using St. Louis equation14
. Findings are relevant to the empirical literature of developed
countries that monetary policy is an important tool to stabilize the economy. Additionally,
Vector Autoregressive (VAR) models have also been used extensively to examine the
transmission mechanism of monetary policy. They analyze the influence of monetary
policy shocks on aggregate economic activity. Monetary policy shock largely effect the
output in countries with a larger financial sector. The effect of a monetary policy shock is
smaller when there is fixed exchange rate. Negative monetary policy shocks raise the real
output growth through expansion in economic activity. Contractionary monetary policy
shock declines business sector flow of funds, real GDP, employment, retail sales and non-
corporate financial profit. Monetary policy shock controls the inflation by exchange rate
14
A three variable equation (including output, fiscal and monetary policy indicators), known as St. Louis
equation in the economics literature, was developed by Anderson and Jordan (1968) with the objective of
testing the relative significance of monetary and fiscal policy for stabilization in the US.
Chapter # 2 Literature Review
65
appreciation. These shocks have negative effects on exports while they make the imports
cheaper by deteriorating the trade balance.
Short term interest rate and money supply are mostly used as indicators of monetary
policy. Most of the empirical literature has focused on the developed countries moreover
cross country evidence is scarce as studies focus on time series data using quarterly
frequency mostly.
2.6 Policy volatility and economic growth:
2.6.1 Theoretical review:
Business-cycle theory and growth theory have traditionally been treated as unrelated. Fynn
Kydland and Edward Prescott (1982) and Long and Plosser (1983) presented new
evidence for analyzing economic variations that combined growth and business-cycle
theory. These models assume that output variations are influenced by stochastic variations
in technology. Long run growth is not influenced by policy uncertainty in the standard
neoclassical growth model. Due to policy shocks economy deviate from its long run
growth path only temporarily. In contrast, endogenous growth model propose that policies
and policy instabilities can have permanent effects on growth.
2.6.2 Empirical review:
In order to improve the climate for private investment and growth countries have adopted
macroeconomic and structural policies however these policies have unproductive to
provide the required outcome. New wisdom focuses not only at the right policies but also
the need to minimize the uncertainty about the future policies. As a predicted or certain
environment reduces the risk associated with private entrepreneurs and increases the
productivity of investment and growth. Below we review empirical studies regarding the
relationship between policy volatility and economic growth.
Chapter # 2 Literature Review
66
2.6.2.1 Fiscal policy volatility and economic growth:
Aizenman and Marion (1991) explore the links between policy uncertainty and economic
growth for 46 developing countries from 1970-85. They use government expenditures,
revenue and budget deficit as indicators of fiscal policy while growth in money and
domestic credit represent monetary policy indicators. Volatility is measured as the
standard deviation of the residual. Findings show that volatility of government
expenditures adversely affects the economic growth in both Latin America and Asia, but
the correlation is much higher in Asia. There is evidence of negative association between
monetary policy volatility and economic growth in Latin America but positive in Asia.
There is evidence of a negative association between all policy volatility measures and
economic growth in low growth countries while for the high-growth countries, some
correlations are negative but others are positive. Cross-sectional regressions show that
policy volatility adversely contributes to economic growth. Findings are consistent
with above correlation results. Theoretical model explain that policy volatility
might change the pattern of investment.
Ramey and Ramey (1995) provide an empirical analysis of volatility (growth volatility,
government spending volatility and innovations volatility) and economic growth in a
sample of 92 developed and developing countries from 1960- 1985. They use the standard
deviation of growth rate of GDP, variance of innovations and government spending as a
measure of volatility. Findings provide the evidence of lower growth rates for countries
with higher volatility. Government spending-induced volatility adversely affects the
economic growth even after controlling time and country fixed effects. Innovations
volatility is also inversely related to economic growth. Findings remain robust by the
Chapter # 2 Literature Review
67
addition of control variables. Empirical literature link volatility to growth via investment
however findings reveal the little impact of volatility on the investment share of GDP.
Gong and Zou (2002) examine the link between volatility of public expenditures and
economic growth for 90 developed and developing countries from 1970-1994. Variance of
the growth rate of public expenditures measures volatility. They disaggregate government
expenditures by economic15
and functional classification.16
Economic classification shows
that volatility of both the current and capital expenditures adversely affect the economic
growth. Functional classification shows that volatility of general public services is directly
related to economic growth. Volatility of education and defence expenditures as well as
economic services is inversely related to economic growth. Volatility of transportation and
communication expenditures is directly and weekly related to economic growth.
Ali., M. Abdiweli (2005) examine the effect of volatility of fiscal policy on economic
growth and investment for 90 developed and developing countries from 1975-1998.
Literature emphasizes that certainty of the fiscal policy is important for the decision to
invest. Uncertainties regarding future behavior of fiscal parameters reduce the growth rate
by making investment riskier. Aggregated and disaggregated revenue and expenditure
represent fiscal policy measure. The standard deviation of the residual measures the
volatility or the uncertainty associated with changes in fiscal policy. Findings imply that
most of the fiscal policy parameters are inversely related to economic growth. Through the
investment channel fiscal volatility does not seem to have much impact. With the
exception of government expenditure and trade taxes all the other fiscal volatility
measures have no noticeable impact on economic growth.
15
Expenditures are divided into current and capital. 16
Expenditures are divided into six broad categories: general public service, defence, education, human
welfare services, transportation and communication and economic affairs.
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Sirimaneetham Vatcharin (2006) evaluate the volatility of macroeconomic, fiscal and
development policies in 65 developing countries from 1970-99. Policy volatility is
measured by standard deviation of the residuals from a first order autoregressive process
or AR(1). Budget deficit and central government debt are used to represent the volatility of
fiscal policy. Macroeconomic volatility is represented by interest rate, inflation rate and
exchange rate. Development policy volatility is represented by trade liberalization and
government regulations and protection of property rights. Findings show that only
macroeconomic volatility is inversely related to economic growth while fiscal and
development policy volatility remain insignificant in explaining the growth. Regarding the
role of fiscal volatility statistics in the study show that low-income countries are not
subject to much higher budget deficits, most studies which provide an inverse relationship
between fiscal policy volatility and growth use government consumption as a proxy. The
limited role of development policy volatility is surprising as it is expected that unstable
government regulations discourage the investment and growth.
Davide Furceri (2007) explore the link between cyclical volatility of government
expenditure and long run growth using panel data of 116 developed and developing
countries from 1970-2000. Standard deviation of the government expenditure measures
the volatility while cyclical part is obtained through different filtering methods; HP and
BP filters17
. Findings show that government expenditure volatility and economic growth
are inversely related. Findings remain robust to different cyclical measures and
subsamples. It is concluded that government expenditure volatility indicate a larger effect
on long-run growth for developing countries while a smaller effect for OECD countries.
This might be due to the better domestic stabilizers in developed countries which absorb
the volatility of expenditures.
17
Hodrick–Prescott and Baxter King filters.
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Fatas and Mihov (2008) empirically explore the effect of fiscal policy volatility on
economic growth, investment and output volatility for ninety-one for the period 1960-
2000. They use only government spending for the empirical analysis of fiscal policy
because it remains less volatile as compared to taxes, as spending reacts less to economic
cycle. As a measure of discretionary change in fiscal policy they use the volatility of the
residual. Empirical analysis shows that volatility of discretionary fiscal policy adversely
affects the output and investment. It is concluded that fiscal policy volatility leads to more
volatility of output, which in turn lowers investment and economic growth. There is also
evidence of a procyclical behavior of fiscal policy for many countries included in the
sample. In poor countries a combination of discretionary fiscal policy and procyclical
fiscal policy increases the volatility and harms long-run growth.
Afonso and Jalles (2012) examine the link between fiscal volatility, financial crisis and
economic growth for a sample of developed and developing countries from 1970-2008.
They use the standard deviation of cyclical component of aggregate government
expenditures and revenues. Findings imply that government expenditures volatility lowers
the economic growth, finding is also robust across country groups. Government revenue
volatility appears to be larger for OECD countries than for emerging economies. Moreover
with a financial crisis government spending is less flexible than revenues. Revenues drop
substantially due to the crisis therefore magnifying the imbalance. Findings propose that
the implementation of stable and smoother fiscal policy can help to create an investment
friendly environment that allows private investors to plan better in the long run.
2.6.2.2 Monetary policy volatility and economic growth:
Peterson (1998) evaluates the association between monetary instability and economic
growth for 87 developed and developing countries from 1968-92. The sample period is
divided into two equal parts one from 1968-80 and other from 1980-92 as the rate of
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70
growth of the sample countries declined in the 1980-92 period as compared to 1968-80.
The key intent of the study is to explore the circumstances causing to this decline.
Findings show that higher instability of money supply growth contributed to this decline
of growth rate. This instability seems highest in the middle and low income countries
whereas in high income countries money supply growth seems to reduce from the first to
the second period. Findings propose that a sustainable (3 to 4) percent growth rate requires
moderate, non-inflationary, and stable money supply growth in the (4 to 5) percent range.
It further requires a well-organized fiscal policy where spending keeps in line with
revenue, eradicating the need to print money to finance deficits.
Ismail et al. (1999) observe the effect of interest rate uncertainty on economic activity in
Malaysia using monthly data from 1998-2002. Interest rate represents three month
treasury bill rate and its volatility is measured by conditional variance from the GARCH.
The study investigates the effect of uncertainty in interest rate on industrial production
used as a proxy to aggregate output. Findings show an inverse association between interest
rate uncertainty and aggregate output. It also shows that investor has information about
market and he can predict small probability of change.
Bo and Sterken (2002) evaluate the relationship between interest rate volatility, debt and
firm investment using a panel of 82 Dutch firms for the period 1984–1995. There is ample
literature discussing the impact of uncertainty on investment behavior. Irreversibility
indicates an inverse relationship between investment and uncertainty. Study uses three
measures of volatility; the ARCH model of volatility, the variance of the residual through
AR(1) process and the normal variance. Two measures of interest rate are used; firm
interest rate and market interest rate. Besides the whole sample study uses two sub
samples; one for high indebted firms and other for low indebted firms. Finding show that
higher interest depresses the firm investment while the interest rate volatility shows
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ambiguous result. Interest rate volatility and debt jointly increase the investment and this
effect is larger for highly indebted firms. Findings imply that the debt readjustment work
for highly indebted firms as a higher interest rate volatility decreases the real value of
debt.
Bloom and Bond (2007) explore the dynamics of uncertainty and investment both at
aggregate level using time series properties and also firm level data for UK manufacturing
firms from (1972-91). Standard deviation of daily stock returns measure volatility. The
empirical findings show consistency with the partial irreversibility theory where
investment becomes unresponsive to demand shocks due to higher uncertainty. This
specifies that an increase in uncertainty during major shocks, such as September eleven
and the oil shocks of 1970s, reduce the sensitivity of investment to consequent monetary
or fiscal policy.
Gulen and Ion (2013) investigate the correlation between uncertainty and corporate
investment using a quarterly data of 7861 US firms from 1987-2011. They use uncertainty
index by Baker, Bloom, and Davis (2012) which is a comprehensive indicator representing
monetary as well as fiscal policy uncertainty. Businesses often face uncertainty related to
the timings and content of policy changes. Findings show that policy uncertainty reduces
the industry and firm investment with a substantial magnitude. Relationship is not alike to
all US firms included in the sample hence it is stronger for firms having higher degree of
irreversibility, have more financial constraints and those who are less competitive.
Moreover statistics show that two thirds of the 32% drop in corporate investments during
the 2007-2009 crisis can be attributed to policy uncertainty.
Bretscher et al. (2016) examine the effect of uncertainty on investment both at the
aggregate and firm level by using the data of 1600 firms from 1994-2014. Interest rate
uncertainty reveals uncertainty about the future stance of monetary policy. Uncertainty can
Chapter # 2 Literature Review
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lead firms to delay investment projects when these are irreversible. Interest rate
uncertainty is measured by treasury implied volatility. Findings show that uncertainty
adversely affects the investment both at the aggregate and firm level. Findings also show
that the negative relationship of interest rate uncertainty and future investment is stronger
in more financially constrained and levered firms. Findings imply the need to reduce
uncertainty around the future path of monetary policy as the Fed’s main policy instrument
by means of effective forward guidance.
2.6.2.3 Capital flows volatility and economic growth:
Lensink and Morrissey (2001) examine the link between FDI flows, volatility and
economic growth for 88 developed and developing countries from 1975-1998. Standard
deviation of the residual represents volatility. Findings of the cross section and panel data
provides consistent finding that FDI is positively associated to economic growth whereas
FDI volatility is inversely related. FDI volatility may represent underlying economic,
political, institutional uncertainty and risks in a country. These uncertainties reduce the
growth and the productivity of investment. Effectiveness of the study can be enhanced by
incorporating other capital flows and then comparing their results.
Sulla and Willett (2007) examine the reversibility of different capital flows to emerging
markets using data of 35 economies from 1990-2003. As sharp reversals of capital inflows
accompanied by currency crises have severe consequences in the form of output losses in
emerging market. The study explores the behavior of different type of capital flows
during crises. Study uses the volatility measure while splitting the sample into crisis and
non-crises periods. Disaggregated capital flows are represented by foreign direct
investment, portfolio investment and private loans. Findings show that excluding for FDI,
all other flows exhibit large reversals during crises. The reduction appears largest
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regarding private loans during the Asian crises. The findings propose the demand for
international reserves and risk management to avoid the crisis.
Demir Firat (2009) explore the link between volatility of short term capital flows and
private investment in emerging markets from 1991-2001 using the biannual data. There
was a sharp surge in private capital flows to developing countries during the decade of
1990s. There is growing body of literature representing that unregulated short-term capital
flows have adversely affected the long-term investment and growth in developing
countries. Study employs firm level data for three countries separately; Argentina, Turkey
and Mexico. Standard deviation of net short term net capital inflows represents volatility.
Findings imply that higher volatility of the short term capital inflows is inversely related to
economic growth. Moreover this volatility has a significantly larger effect on small firms
as large firms have better access to capital and can manage reversals better. Findings
propose capital controls to decrease the excess volatility of short term capital flows.
Ferreira and Laux (2009) analyze the association between portfolio flows, volatility and
growth for a panel of 50 developed and developing countries from 1988-2001.Volatility is
considered an important characteristic of hot money which badly affect the growth in
developing countries, especially during crisis. Portfolio flows are usually considered most
volatile and their volatility has increased in emerging markets after liberalization. Findings
imply that the volatility of portfolio flows is weakly related to growth whereas it does not
dampen growth. Findings remain robust to different measures of portfolio flows, volatility,
presence or absence of controls and estimation methodology. Finding is in sharp contrast
to many other studies explaining that volatility of short term flows has severe negative
consequences for growth and investment especially in developing countries having less
developed financial and legal system.
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Choong et al. (2011) analyze the link between foreign direct investment volatility and
economic growth in 5 ASEAN countries from 1974-2005. FDI volatility has increased
considerably since the late 1990s owing to domestic and international shocks therefore the
rate of return on foreign investment has become more uncertain. When foreign investors
face the risk they may reverse or withdraw the investments. Findings show that FDI
volatility is negatively associated with growth in Indonesia, Malaysia, Philippines and
Thailand while it has a minimal effect on Singapore. The financial system of Singapore is
highly developed than other sample countries and has a much higher ability to stabilize the
variability of FDI.
Carp (2014) examines the correlation of capital flows volatility and economic growth in
emerging economies from 1991-2012. World integration and financial openness has
enhanced the connections and interdependencies between countries. After the financial
crisis the destination of these capital flows has changed. At the start of the crisis,
developed economies observed a sharp decline in capital flows, mostly FDI. By contrast,
emerging markets experienced a surge in FDI inflows contributing their growth. During
the same period there was a sharp increase in portfolio inflows as these flows are thought
to be a form of short term speculations. Findings imply that macroeconomic instability has
augmented the volatility of capital flows, especially short term flows, by exerting a
downward influence on economic growth.
Neanidis (2015) observes the impact of volatile capital flows on economic growth using
cross country data of 78 developed and developing countries from 1973-2013. Standard
deviation of capital flows represents volatility. Findings show that aggregate capital flows
remain insignificant in influencing the economic growth while from disaggregated flows
debt flows are negatively related to economic growth whereas equity flows are positively
Chapter # 2 Literature Review
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related. Volatility of all the capital flows, aggregated and disaggregated both, are
negatively related to economic growth.
2.6.2.4 Trade flows volatility and economic growth:
Yotopoulos and Nugent (1976) examine the effect of export instability on economic
growth for 38 developing countries from 1958-68. They measure instability through
squared deviations from an exponential trend. Findings show that export instability
reduces the marginal propensity to consume thereby increasing savings and growth.
Findings of the study are in sharp contrast to many other studies that explain the negative
effect of export instability on economic growth.
Ozler and Harrigan (1988) empirically examine the link between export instability and
economic growth and investment in 26 developing countries from 1963-82. Instability
index is measured by applying autoregressive conditional heteroscedasticity (ARCH)
model. Findings shows that export instability adversely affect the economic growth.
Country differences matters as instability hurts the countries that are more open, having
large exports. Regarding the composition of exports the largest negative effect is on the
countries whose exports are concentrated in capital intensive sectors, chemicals and
machinery. This indicates that negative effect of export instability works through reducing
the productivity of capital stock. Effect of instability on investment is much smaller than
its effect on growth.
Love (1989) evaluates the association between export instability and income instability for
20 developing countries. Selection of the sample is based on composition of exports,
representing the primary commodities as these goods face more fluctuations in demand
and supply as compared to manufacture goods export. Instability is measured through
deviations from a five-year moving average. Findings show that export instability brings
instability in capital goods imports and, in turn, investment and growth.
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Gyimah-Brempong (1991) examines the association between export instability and
economic growth for 34 Sab Saharan African countries from 1960-86. Three indicators of
export instability are used; coefficient of variation, trend method and average of the
squares of the ratio of actual export earnings to trend earnings. Using the aggregate
production function, findings show that all the measures of export instability indicate a
negative association with economic growth.
Sinha (1999) examines the link between exports instability and economic growth in nine
Asian countries; India, Japan, Malaysia, Myanmar, Pakistan, Philippines, Korea, Sri Lanka
and Thailand, using annual data from 1950-97. Study uses the deviations of exports from a
five-year moving average as an indicator of instability. The results are not identical across
countries. Export instability adversely affects the economic growth in Japan, Malaysia,
Philippines and Sri Lanka. Negative relationship implies that instability in exports brings
instability in foreign reserves that affect the industrial production by deteriorating
important imports and making the investment and growth riskier. Export instability is
directly related to economic growth in (South) Korea, Myanmar, Pakistan and Thailand
whereas India shows ambiguous findings. The positive association between both variables
specifies a decrease in consumption which induces an increase in saving and investment
and thereby growth.
Chaudhary and Qaisrani (2002) evaluate the link between trade instability and economic
growth in Pakistan from 1972-1994. Pakistan economy is dependent on imports of certain
goods; industrial inputs, machinery, fuel etc. Import of these goods depends on the foreign
exchange earnings from exports while exports consist of mostly primary commodities and
agricultural products. Due to the composition of exports, term of trade shocks and other
domestic factors exports remain highly unstable. Findings shows that export instability do
not affect investment, growth and imports of capital goods in Pakistan. The trade deficit is
Chapter # 2 Literature Review
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continuously met through foreign borrowings. The study can be criticized as it does not
explain the measurement of export instability index.
Rashid et al. (2012) evaluate the relationship between export instability and economic
growth of SAARC countries; Pakistan, India, Sri-Lanka and Nepal from 1972-2008.
Export is an important source of foreign exchange earnings and for the payments of
imports for LDCs. They experience higher export instability due to their export patterns
and inelastic and unstable demand and supply of their exports. Instability index is
measured by the trend method. Empirical findings imply that export instability is inversely
associated with economic growth for all selected countries. Magnitude of export instability
is highest in Sri-Lanka while it is lowest for Pakistan. Findings propose export
diversification and liberalization of foreign exchange markets as a control of instability.
Kaushik et al. (2008) examine the effect of export instability on economic growth of India
from 1971 to 2005. Export instability is measured through the squared deviations of export
earnings. Findings infer that export instability is inversely related to short-run stability and
directly related to longer-run growth of income. Findings propose that that if India wants
to reduce the short run negative effect it should diversify its exports. The study can be
criticized on the ground that it does not provide the economic rationale or channels
through which export instability adversely affects the economic growth in the short run
while relationship turns to positive in the long run.
2.6.2.5 External factors volatility and economic growth:
Mendoza (1997) evaluates the correlation between term of trade uncertainty and economic
growth in 40 industrial and developing countries from 1970-91. As a result of world
integration global markets volatilities have a substantial impact on the macroeconomic
indicators of participating economies. The effect of these volatilities is more severe on less
developed economies as compared to developed ones. Standard deviation of the residual
Chapter # 2 Literature Review
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through autoregressive process measures volatility. Findings show that consumption
growth is directly associated with term of trade volatility whereas economic growth is
adversely affected by term of trade volatility. Findings remain robust with the addition of
other control variables. It is concluded that increased global uncertainty reduces social
welfare.
Andrews and Rees (2009) examine the link between term of trade volatility and
macroeconomic volatility using a sample of 71 countries from 1971–2005. As a result of
globalization economies have become more prone to external shocks. Terms of trade
shock is likely to have a greater impact on macroeconomic volatility in countries more
open to international trade. Standard deviation of growth rate of terms of trade represents
volatility. Findings show that term of trade volatility is positively related to output growth
and inflation volatility. Differences in the magnitudes depend on the policy and the market
structures. Study also explores the channels through which term of trade volatility affect
the macroeconomic volatility. Findings reveal that terms of trade volatility primarily
affects through the volatility of household consumption, exports and imports while
investment volatility seems less affected by terms of trade volatility.
Olaberria and Rigolini (2009) examine the effect of East Asia’s macroeconomic volatility
on economic growth and its volatility for a sample of 80 countries from 1966-2005.
Standard deviation of residuals through AR (1) process represents volatility of each
respective variable. Findings show that beside the volatility of domestic factors volatility
of external factors or shocks has also contributed to the slow growth of emerging
economies. On the one hand, higher openness has contributed to economic growth on the
other hand, it has increased the exposure of countries to external shocks. Volatility of
terms of trade, growth rates of trading partners, foreign interest rate and foreign capital
Chapter # 2 Literature Review
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flows reduces the growth rate of domestic economy by transmitting these shocks through
globalization and making the domestic growth more volatile.
Abaidoo (2012) evaluate the effect of macroeconomic volatility on different indicators for
39 Sub Saharan African countries from 1980-2011. The study determines the effect of
external and domestic volatility indicators on economic growth, investment and savings.
Access to external market together with weak domestic structures and policies creates
significant threats to long term growth prospects in the sub-region. Volatility is measured
by standard deviation of specific macroeconomic variable. Findings suggest that external
volatility parameters have more influence on macroeconomic performance in the sub-
region than domestic indicators.
2.6.3 Concluding remarks:
The empirical studies of macroeconomic policies and economic growth have concentrated
predominantly on the level effects of policy parameters on economic growth and largely
ignored the volatility of macroeconomic policies. Regarding the volatility of stabilization
and liberalization policies and external shocks we conclude below the findings from the
empirical literature discussed above.
Regarding volatility of fiscal policy empirical evidence shows that uncertainties
regarding future behavior of fiscal parameters reduce the growth rate by making
investment riskier. In an uncertain policy environment, investors might delay investment
as a result of irreversibility. There is also evidence that fiscal policy is procyclical mostly
in developing countries. Countries that face more political constraints exhibit more
procyclical fiscal policy. In poor countries a combination of discretionary fiscal policy and
procyclical fiscal policy increases the volatility and harms long-term growth. The effect of
fiscal volatility in developed countries is marginal due to strong automatic stabilizers.
Volatility of fiscal policy is measured by standard deviation of the residuals.
Chapter # 2 Literature Review
80
Regarding volatility of monetary policy empirical literature provides the evidence that it
adversely affects the economic growth through investment channel. Interest rate
uncertainty reveals uncertainty about the future stance of monetary policy. Uncertainty of
the interest rate affects the firm’s profitability by reducing the corporate investment
especially when there is irreversibility. Moreover link between interest rate uncertainty
and future investment is stronger in more financially constrained and levered firms and
also those firms who are less competitive. Opposite also holds as for more indebted firm’s
interest rate volatility can increase the investment by reducing the real value of debt
holdings. This debt readjustment effect has important implications for highly indebted
firms.
There is mostly firm level literature that explains the link between interest rate volatility
and investment. Literature is scarce at aggregate level and also for developing countries.
Mostly used volatility measures are standard deviation of residual of short term interest
rate through auto regressive process, conditional variance through ARCH and GARCH
model, Standard deviation of daily stock returns measure.
Regarding volatility of capital flows empirical literature provides the evidence that it
reduce the economic growth. Over the past decades, World integration and financial
openness has enhanced the connections and interdependencies between countries. Higher
volatility is an indicator of country specific risk, when foreign investors face the risk they
may reverse or withdraw the investments. FDI volatility discourages the technology
adaption and thereby is harmful to economic growth. There is growing body of literature
representing that unregulated short-term capital flows have adversely affected the long-
term investment and growth in developing countries. Volatility of capital flows affects
domestic investment through interest rates, exchange rate and inflation expectations.
Portfolio flows and debt flows are usually considered more volatile part of capital flows
Chapter # 2 Literature Review
81
while FDI remain the most stable and are less associated with output volatility. Asian
crisis represents the largest reversal in private loans. Moreover the pro-cyclical behavior of
capital flows adds to their volatility in developing countries. Volatility of capital flows is
measured by standard deviation of the residual of respective capital flow indicator through
auto regressive process.
Regarding volatility of trade flows empirical literature provides ambiguous findings.
Almost all the available literature examines the effect of export instability on economic
growth regarding developing countries. Export is an important source of foreign exchange
earnings and for the payments of imports for LDCs. They experience higher export
instability due to their export patterns and inelastic and unstable demand and supply of
their exports. Composition of exports toward primary commodities plays an important role
in their instability. Such factors may contribute to destabilize the investment and economic
growth. Most of the studies examine negative association between both variables and
some studies find positive association. Negative association between both variables
indicate that export instability bring instability in foreign reserves that reduces the imports
of important capital goods and hence reduces the productivity of industrial sector. Positive
association between both variables implies that export instability reduces the consumption
thereby increasing the saving and investment and hence economic growth.
Volatility is measured by export instability index; using the trend method, deviations of
exports from a five-year moving average, autoregressive conditional heteroscedasticity
(ARCH) model, the coefficient of variation.
Regarding the volatility of external factors or external shocks empirical literature
shows that these volatilities; term of trade, foreign growth and foreign interest rate
volatility, volatility of capital flows, deteriorate economic growth especially in developing
countries. As a result of world integration global markets volatilities have a substantial
Chapter # 2 Literature Review
82
impact on the macroeconomic indicators of participating economies. The effect of these
volatilities is more severe on less developed economies as compared to developed ones
due to poor macroeconomic and institutional framework to absorb such shocks. These
shocks directly or indirectly reduce the growth of domestic economies.
We can conclude the above discussion that volatility of domestic and foreign
macroeconomic policies deteriorate economic growth mostly through the investment
channel. Regarding the volatility measurement most of the studies have used standard
deviation measure.
2.7 Determinants of policy volatility:
2.7.1 Empirical review:
As we have concluded from the previous section that policy uncertainty or volatility
reduces the economic growth specifically through investment channel therefore it is
important to investigate the factors that contribute to volatility to identify the policy
options to reduce the volatility. Below we provide the evidence from the empirical
literature regarding the volatility of stabilization policies, capital flows and trade flows.
2.7.1.1 Determinants of capital flows volatility:
Beck Ronald (2001) examines the volatility of capital flows to emerging markets and role
of foreign banks and trade liberalization regimes in the stability of the capital flows in 54
developing countries from 1990-98. It is argued that regarding trade in financial services
Asian countries had fairly restricted regime. Foreign banks play an important role in
reducing the information asymmetry and bring higher transparency. Volatility of capital
flows is measured through standard deviation. Share of foreign bank numbers and share of
foreign bank assets reflect foreign bank penetration. Limitations on foreign banks measure
the magnitude to which activities of foreign banks are restricted. Other variables include
inflation rate, economic freedom and rule of law. Findings show that foreign bank
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83
penetration tends to increase the volatility of capital flows by increasing competitive
pressures. Rule of law reduces the volatility of capital flows. It shows that the regulatory
environment matters more than macroeconomic indicators.
Alfaro et al. (2005) examine the factors that determine the volatility of capital flows by
focusing particularly on institutional weaknesses versus bad policies for a sample of 97
countries from 1970-2000. Aggregated and disaggregated net capital flows are considered
which include net equity flows (FDI and portfolio equity investment) and debt. Inflation
rate, inflation volatility and government consumption as a ratio to GDP represent the
policy variables. All are hypothesized to be positively related to volatility. Institutional
quality also plays an important role in determining the pattern of capital flows. Initial level
of GDP represents the level of development of countries. Findings show that institutional
quality remains insignificant in explaining the volatility of total capital flows. Volatility of
aggregated and disaggregated capital flows reduces the GDP per capita. Inflation,
inflation volatility and government consumption are positively associated with net equity
flows. Robustness analysis including other monetary and fiscal indicators also provides
the consistent findings. Institutional quality does not appear to be significant there might
be a role of measurement error in the institutional quality indicators hence causing a
downward bias. Findings illustrate the role of poor macroeconomic policies towards the
high volatility of capital flows. Study ignores the external factors as important
determinants of volatility of capital flows in globally integrated world.
Broner and Rigobon (2005) explore the factors responsible for higher volatility of capital
flows in emerging countries from 1965-2003. Volatility is measured by standard deviation
method. They consider domestic and foreign macroeconomic factors and country
characteristics as the fundamental cause of volatility. Domestic macroeconomic factors
include GDP, inflation, exchange rate, nominal interest rate and term of trade. External
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84
factors include foreign real interest rate, GDP, nominal exchange rate and inflation of
major trading partners. Income per capita, financial sector development and institutional
quality represent country characteristic. Findings show that internal and external
macroeconomic factors contribute very little towards the volatility of capital flows while
country characteristics explain substantial amount of volatility. Financial development,
good institutional quality and higher per capita income decrease the volatility of capital
flows. It is concluded that supply side factors are more important in explaining the capital
flows to emerging markets than the demand side factors. Findings propose that developing
countries can reduce the volatility of capital flows by improving their financial sector and
institutions.
Broto et al. (2008) evaluate the factors that affect the volatility of different type of capital
inflows in emerging economies for the period1980-2006. These factors are categorized
into domestic macroeconomic factors, financial sector factors, institutional and
geopolitical factors and global factors. Domestic macroeconomic factors include; GDP per
capita and growth rate, inflation and public deficits, stock of foreign exchange reserves
and trade openness. Financial sector variables represent the factors determining the
domestic banking system. Global determinants include world growth rate, global liquidity,
US inflation and the 3-months T-bill rate. Institutional variables include economic and
political liberties, corruption, law and order and bureaucratic quality. Geopolitical factors
include average of oil and gas assets and the countries’ nuclear capability. Findings
provide the evidence of a non-linear relation between economic development and the
volatility of capital inflows. Financial factors play an important role in reducing the
volatility of all inflows. Regarding the volatility of portfolio flows domestic
macroeconomic factors paly a very little role. Economic and political stability play an
important role in reducing the volatility of portfolio inflows while global and geopolitical
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85
factors contribute in reducing the volatility of all type of capital inflows. It is concluded
that global factors have reduced the relative importance of domestic factors however
domestic factors can still play their role in reducing the volatility, in particular stable
macroeconomic policies and a sound financial system.
Neumann and Tanku (2009) analyze the relationship between financial openness and
volatility of capital flows for of 22 developing and developed countries using panel data
from 1981–2000. They examine the response of different capital flows to financial
liberalization; foreign direct investment, portfolio investment and debt flows. Other
control variables include changes in world rate of interest, world output growth and
domestic output growth. Findings show that liberalization increases the volatility of FDI
flows especially in emerging markets while unexpectedly portfolio flows show a slight
response. Higher world interest rate volatility reduces the volatility of all capital flows.
Higher world growth volatility increases the volatility of portfolio and other flows except
foreign direct investment volatility. Volatility of domestic growth rate increases the
volatility of almost all capital flows. Results of the study regarding the volatility of foreign
direct investment are in contrast to many other studies that explain FDI flows are most
stable and less volatile as compared to other flows. Study does not provide any rationale
for this outcome.
Mercado and Park (2011) explore the factors that affect the size and volatility of different
capital inflows to emerging economies from 1980–2009. They examine the impact of
internal and external factors on the level and volatility of disaggregated capital flows.
Internal macroeconomic factors comprise economic growth, inflation, trade openness and
exchange rate. Financial sector indicators include stock market capitalization and interest
rate differential. Apart from the macroeconomic and financial indicators, institutional
quality index is also examined. Global economic indicators are global growth expectation
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86
and global broad money growth. Findings show that trade openness and volatility of real
exchange rate is directly associated to the volatility of all capital inflows in full sample as
well as in Developing Asia. Stock market capitalization, economic growth and
institutional quality decrease the volatility of capital inflows in Developing Asia. Global
money growth is inversely related to the FDI inflows in Developing Asia. The findings
suggest that pull factors play an important role in the determination of capital inflows for
both the full sample and developing Asia as well. The findings propose that stable
macroeconomic environment and higher institutional quality is crucial to attract stable
capital flows.
Globan (2012) investigates the relationship between reversals of capital flows during
global financial crisis and composition of capital flows for 75 developed and developing
countries. Capital flows came to a sudden stop with the spread of the financial crisis in
2008. Findings show that those countries with higher dependence on foreign loan (debt)
rather than FDI (equity) financing observed higher reversals of foreign capital during the
crisis. Developing and emerging economies were harder hit by the crisis than advanced
economies.
Waqas et al. (2015) explore the macroeconomic factors that determine volatility of
portfolio investment for South Asian countries based on monthly data from 2000-2012.
Macroeconomic variables considered in the study are; interest rate, exchange rate,
inflation, stock market return, industrial production, GDP growth rate and foreign direct
investment. Less volatility in international portfolio investment is associated with high
interest rate, currency depreciation, lower inflation, higher stock market return, higher
GDP growth, higher industrial production and higher foreign direct investment. Findings
show that inflation rate reduces the volatility in case of China and India, while it has no
effect for Pakistan and Srilanka as both of these countries have hyper inflation rate which
Chapter # 2 Literature Review
87
reduces the real rate of return on portfolio investment. Real exchange increases the
volatility in case of China as China is intentionally increasing its currency value which has
reduced the return thereby increasing the volatility. In Pakistan and India, higher interest
rate raises the volatility because higher inflation rate reduces the benefit of portfolio
investment to foreigners. Foreign direct investment, economic growth and industrial
production reduce the portfolio investment volatility in all countries. Higher stock market
return reduces portfolio volatility but opposite hold in case of China and Pakistan as stock
market is not fully liberalized in China and in case of Pakistan sudden breakages enhance
the volatility. Study focus on stable macroeconomic environment of the country while
ignoring the external factors and also institutional quality. In a globalized world external
factors have an important role to play in determining the volatility of capital flows.
2.7.1.2 Determinants of trade flows volatility:
Massell (1970) analyze the effect of a set of variables, that describe an economy’s
structure, on export instability for 55 developed and developing countries from 1950-66.
He discusses some supply side as well as demand side factors that determine export
instability. Some foods and agriculture products face supply instability. Demand side
factors include change in income and change in prices of related goods. Goods having
more income elasticity of demand (raw material) are more unstable as compared to goods
having less income elasticity of demand (food). Moreover commodity concentration as
well as geographic concentration also affects the instability of exports. On the bases of
above discussion he uses commodity concentration, geographic concentration,
specialization on food, specialization on raw materials, export market share, domestic
consumption of exported goods, size of the export sector and per capita income as
determinants of export instability. He uses Hirschman index to measure export
concentration and geographical concentration. Findings show that less export
Chapter # 2 Literature Review
88
diversification and higher domestic consumption increases the instability. Higher size of
the export sector, specialization in food items and higher level of development reduce the
instability. Study ignores exchange rate fluctuations and global factors as determinants of
export instability.
Aslam (1985) examines the determinants of export instability in case of Pakistan 1960-61
to 1979-80. The study considers the determinants such as commodity concentration and
geographical concentration, size of the export sector, income per capita, share of food and
exports raw material exports. Gini-Hirschman index is used to measure commodity
concentration and geographical concentration. Findings show that geographical
concentration reduces the instability of exports. As a result of commodity agreements with
its partners during the sixties and seventies trade fluctuations smoothed out in Pakistan.
Size of the export sector reduces the instability as the larger size of the export sector
reduces fluctuations. Higher per capita income increases the diversification hence reducing
the instability. Exports share of food in total exports increases instability as they are
subject to supply side fluctuations. Export share of raw material reduces instability due to
commodity agreements and price pegging policies in Pakistan on the part of importing
countries. Study ignores domestic macroeconomic and external factors as determinants of
export instability. Inclusion of such factors can enhance the significance of the study.
Charette (1985) investigates the determinants of export instability in 15 less developing
countries’ primary commodity markets between 1960 and the mid-1970's. He examines
the price, quantity and earning instability. As described above fluctuations or shift in
demand and supply both brings fluctuations in export earnings. Shifts in exports supply
are caused by fluctuations in output and domestic demand. Demand shifts are caused by
cyclical fluctuations in developed countries. Higher geographical concentration as a result
of international commodity agreements increases the stability. Geographical concentration
Chapter # 2 Literature Review
89
is measured through Herfindahl index. Percentage of exports as a share of domestic output
and percentage of exports as a share of world exports and dummy variables representing
agricultural and raw material markets are the other explanatory variables. Findings show
that higher share of exports out of domestic production reduces the instability of exports
earnings, prices and output. Geographical concentration reduces the instability also.
Sarada et al. (2006) investigates the determinants of Indian sea food export instability
from 1981-82 to 2003-04. Most of the developing countries (including India) find their
major share of export earnings from particular few commodities and the trade is
concentrated with a few nations as well. These developing countries have hardly any
mechanisms at their disposal to hedge against the adverse consequences of instability.
Bearing in mind the strengths of Indian fisheries sector the causes of instabilities in export
of seafood is of enormous importance. Study includes commodity concentration and
geographical concentration as determinants of export instability of seafood. Other
variables include shrimp production, fisheries and non- fisheries GDP. Findings show that
commodity concentration reduces the instability while geographical concentration, the
instability of fisheries and non-fisheries GDP and instability of shrimp production
increases the instability of seafood export. Study proposes that government can take
stabilization measures using domestic stabilization schemes as well as external measures
by the international community.
Baum and Caglayan (2009) examine the association between exchange rate uncertainty
and volatility of trade flows over 1980–2006 including Eurozone countries, other
industrialized countries, and newly industrialized countries (NICs). It is commonly
believed that exchange rate uncertainty lowers the trade volume by increasing the riskiness
of trading activity. It affects the investors’ decision-making process, in particular
production, investment and hiring decisions. They measure the exchange rate and trade
Chapter # 2 Literature Review
90
volatility through bivariate GARCH model. Findings show that exchange rate uncertainty
is positively related to the volatility of trade flows.
Neena (2015) explores the sources of export instability in India by using time series data
from 1987-88 to 2012-13. Most of the literature in this context link the instability of
export with commodity and geographic concentration of exports. Composition of exports
especially overdependence on primary exports in LDCs is an important determinant of
export instability. Study includes different explanatory variables like instability index of
primary exports, chemical products exports, engineering products exports, petroleum
products exports, commodity concentration and geographic concentration index by using
multiple regression analysis. Findings show that instability of textile products and
petroleum products reduces the export instability while instability of primary products,
chemical products, engineering products and geographical concentration of exports
increases the total export instability.
2.7.1.3 Determinants of fiscal policy volatility:
Henisz (2004) evaluates the relationship between political institutions and volatility of
fiscal policy for 91 developed and developing countries from 1971-92. Disaggregated
expenditure and revenue represent the fiscal policy. Constraints on the policy maker’s
discretion are represented by political constraints index. Findings show that higher
political constraints reduce the volatility of different categories of capital and current
expenditures as well as tax and non-tax revenues. Volatility of tax and non-tax revenue
seems to be highly affected by institutional changes. It implies that government can
readily alter these sources against the short term need to increase availability of funds.
Regarding the expenditures it appears that capital expenditure volatility is highly related to
political institutions which shows large discretion in these expenditures for political
motive. Volatility in goods and services expenditure and political institutions is smaller
Chapter # 2 Literature Review
91
representing the less discretion. Study ignores the role of macroeconomic and global
factors that play an important role in fiscal policy volatility.
Fatas and Mihov (2008) analyze the association between institutions and volatility of
fiscal policy for ninety one developed and developing countries over the period 1960-
2000. They use only government spending for the empirical analysis of fiscal policy
because it remains less volatile as compared to taxes. They examine the effect of
macroeconomic and institutional determinants on volatility of fiscal policy. Institutional
determinants include political constraints, political system, electoral system and number of
elections. Other determinants include urbanization, openness, dependency ratio and GDP
per capita. Empirical analysis shows that institutional quality represented by political
constraints significantly and robustly contributes to fiscal policy volatility which implies
that increasing the degree of checks and balances reduces policy volatility. Political and
electoral system and number of elections do not show the robust behavior. Urbanization
and dependency ratio increases the volatility while openness and GDP per capita reduces
the volatility of fiscal policy. Findings propose imposition of institutional constraints to
reduce the volatility of fiscal policy. Fatas and Mihov (2013) add an additional variable of
institutional quality to earlier study which is represented as constraints on the executive.
Findings show that constraints significantly reduce the policy volatility.
Agnello and Sousa (2009) evaluate the factors that determine volatility of public deficit for
a panel of 125 countries from 1980-2006. High and volatile fiscal deficits can lead towards
inefficient allocation of resources, they may raise the debt-to-GDP ratio thereby reducing
the fiscal sustainability. The main objective of the study is to evaluate the political,
institutional and economic determinants of fiscal policy volatility. Political instability,
democracy, per capita income, inflation, trade openness and budget deficit represent the
political, institutional and economic determinants of fiscal policy volatility respectively.
Chapter # 2 Literature Review
92
Findings show that higher political instability increases the volatility of public deficit
while democracy reduces the volatility. Poor countries tend to have more volatile budget
deficits due to weak automatic stabilizers while richer countries are characterized with
stable deficits. Higher inflation increases the fiscal volatility as it brings economic
uncertainty making volatile the spending and revenue. Trade openness increases the
volatility of budget deficit as it exposes the countries to external shocks. Higher public
deficit increases the instability due to unanticipated changes in government expenditures
and taxation.
Bleaney and Halland (2009) examine the effect of primary exports on output volatility and
fiscal volatility for 75 countries from 1980-2004. Due to the volatile prices of primary
products countries experience greater real exchange rate volatility that increases growth
volatility and also fiscal volatility. Exports of primary product are disaggregated into sub
components; fuels and raw materials and food. Study focuses on resource curse as a source
of fiscal policy volatility. Share of primary exports is directly associated to both output
and fiscal volatility. Institutional constraints reduce the volatility of fiscal policy. Study
has given no importance to macroeconomic variables which are also considered an
important source of fiscal volatility.
Albuquerque Bruno (2010) provides empirical evidence regarding the quality of fiscal
institutions and volatility of discretionary fiscal policy for a panel of 25 EU countries over
the 1980-2007. Developed countries have experienced a general surge in budget deficits
along with higher public debt during last decades. Study focuses on institutional and other
factors that can reduce such volatility. Following Fatas and Mihov (2008) they measure
the discretionary fiscal policy18
. Fiscal institutions are represented by the fiscal rule index
18
Volatility of the residuals by running a regression of government consumption growth on output growth,
lagged government consumption growth and on other control variables measures the discretionary fiscal
policy.
Chapter # 2 Literature Review
93
and the delegation index. Fiscal rules and delegation index represent explicit and implicit
constraints faced by the policy makers. Political variables include type of the electoral
system and the number of elections. Macroeconomic variables include per capita income,
government size, country size, openness to represent the degree of integration, inflation as
an indicator of macroeconomic uncertainty. Empirical findings provide the evidence that
fiscal institutions reduce the volatility of fiscal policy significantly. Political variables
remain insignificant. Bigger countries and larger government reduces spending volatility
due to larger automatic stabilizers. Findings propose the strengthening of fiscal institutions
to manage the fiscal volatility.
Attiya et al. (2011) empirically examine the determinants of fiscal deficit volatility for
South Asian and ASEAN countries from 1984 to 2010. Beside the persistent increase in
budget deficits its volatility has also become a great concern for many developed and
developing countries. They focus on the economic, political and institutional determinants
of budget deficit volatility. Economic factors include level of budget deficit, income per
capita, inflation and openness. Political and institutional factors include political stability,
democracy and low level of corruption. Findings show that income per capita, deficit to
GDP, inflation and openness increase the volatility of budget deficit. Countries with
higher level of development are more dynamic and this dynamic characteristic increases
the volatility though this finding is in contrast to many other empirical studies. Moreover
budget deficit volatility has persistence effect. Findings show that all the political and
institutional variables reduce the volatility of budget deficit.
Agnello and Sousa (2014) examine the factors influencing the volatility of fiscal discretion
for 113 countries from 1980-2006. Main focus of the study is to highlight the importance
of institutions in reducing fiscal discretion. They use the discretionary component of fiscal
policy with respect to deficit, revenue and spending. They emphasize on political,
Chapter # 2 Literature Review
94
institutional and macroeconomic determinants of the volatility. Political and institutional
determinants include democracy, cabinet changes in addition to the political system and
political constraints. Economic variables include trade openness, financial openness and
the exchange rate regime. The importance of the country size is considered through
population. Findings show that fiscal policy volatility shows persistence. Higher
democracy and parliamentary systems reduces volatility. Higher government turnover
increases volatility. Country size and less flexible exchange rate regime reduces the
volatility. The results remain robust by considering different regions and country sub
groups. The presidential regimes are related to larger instability in non-OECD countries,
developing countries and non-EU countries and the effects of the country size is more
important for this sample also.
2.7.1.4 Determinants of monetary policy volatility:
Koedijk et al. (1997) examine the dynamics of interest rate volatility using monthly and
weekly data of short term interest rate for the US from January 1968–July 1996. To
analyze the behavior of volatility they use CKLS19
and the conditional heteroskedasticity
GARCH model. Findings propose that both GARCH and level effect play an important
role in determining the interest rate volatility. Weekly frequency provides the most
accurate evaluation of the volatility.
Ball and Torous (1999) examine the dynamics of short-term interest rates over a number
of countries using monthly data. They use a variety of short term interest rates and
estimate a stochastic volatility model of short-term interest rate dynamics. They also use
EGARCH model for comparison. Analysis shows that interest rate dynamics are affected
by economic shocks. Short-term interest rates are more responsive to these shocks.
19
Chan, Karolyi, Longstaff and Sanders (1992)
Chapter # 2 Literature Review
95
Moreover interest rate dynamics are similar across a number of countries. Level of the
interest rate is also an important determinant of volatility.
Edwards and Susmel (2003) analyze the behavior of interest rate volatility using high
frequency weekly data from 1994-1999 for Latin American and Asian countries. They use
univariate and bivariate switching volatility model and also rolling standard deviation
model. Findings provide the signal of co-movement of interest-rate volatility across
countries. These co-movements depict the effect of domestic and international shocks;
Mexican (1995), East Asian (1997), Russian (1998), and Brazilian (1999) crises.
Argentine’s interest rate illustrates the largest increase in the aftermath of the Mexican and
Russian crisis. Mexican interest rate increased sharply in the aftermath of the Mexican
peso crisis and also has been sensitive to major international crises. Hong Kong
experiences a larger increase at the time of the East Asian crisis and around the time of the
Russian crisis.
Olweny (2011) examines the relationship between level of short term interest rate and its
volatility for Kenya using monthly data of 3 month Treasury bill rate from 1991M8 to
2007M12. The financial sector in Kenya suffered from severe repression before the
implementation of Structural Adjustment Programme (SAP) in 1983. Interest rate
deregulation took place accompanying the SAP. Findings illustrate that volatility is
positively associated with the level of the short term interest rate. Findings also reveal that
the GARCH model is a better measure of volatility of short rates as compared to ARCH
model. GARCH model provides a better description of interest rate dynamics with
normality assumptions.
Duncan (2013) evaluates the impact of institutional quality on the cyclicity and volatility
of monetary policy and volatility of output for 56 developed and developing countries
from 1984.Q1-2008.Q4. Emerging markets are characterized by procyclical or acyclical
Chapter # 2 Literature Review
96
monetary policy. This characteristic of monetary policy can be related to weak
institutional quality. Findings show that institutional quality is significantly related to
monetary cyclicity. The model shows a positive co-movement between output and the
interest rate (countercyclical monetary policy) at relatively high levels of institutional
quality. There is an inverse relationship between volatility of both output and interest rates
and the institutional quality. Moreover lower institutional quality discourages both FDI
and foreign borrowing. Study ignores other macroeconomic and external factors that can
enrich the findings of the study.
2.7.2 Concluding remarks:
Regarding the determinants of the volatility of capital flows empirical literature
examines the domestic and global factors as a cause of volatility. Domestic factors are also
called pull factors while global factors are called push factors. Domestic factors include
macroeconomic variables, financial sector variables and institutional variables.
Macroeconomic variables include income per capita as a measure of level of development,
inflation as a measure of economic uncertainty, trade openness as a measure of world
integration, government consumption or budget deficit, interest rate and its volatility,
exchange rate and its volatility, stock market return and industrial production. Empirical
literature shows that higher level of development shows improvement in economic
conditions; saving, investment, financial system all of which make capital flows less
volatile. Volatility of capital flows increases in countries with higher inflation rates as it
reflects unpredictable and distortionary monetary conditions. Trade openness increases the
volatility as countries become more vulnerable to external conditions and especially if
their export base is weak. Higher public deficits increase the probability of undergoing a
debt crisis there by increasing volatility. Higher interest rate increases the capital flows, by
decreasing the borrowing cost, while decreasing their volatility. Devaluation of host
Chapter # 2 Literature Review
97
country currency encourages the foreigners to invest due to higher return thereby
decreasing their volatility. Higher interest rate and exchange rate volatility increases the
volatility of capital flows. The stock of foreign exchange reserves lowers volatility as low
reserves lead to liquidity crises by increasing the volatility. Industrial production signals
higher and stable economic growth which decreases volatility
Financial sector variables include bank asset, credit and deposit ratios as a ratio to GDP
and represent the size or level of development of the banking sector. Empirical findings
show that higher asset, credit and deposit ratios are the representative of more developed
banking systems, thereby reducing volatility.
Institutional factors include institutional quality, economic freedom, rule of law etc.
Higher institutional quality lowers the volatility of capital flows. Higher institutional
quality is an indicator of stable macroeconomic conditions, strong financial and legal
system which makes capital flows stable.
Global factors which are also called push factors in the empirical literature include global
growth, foreign interest rate, interest rate volatility, inflation and global liquidity.
Countries that are dependent more on international funds become more sensitive to global
push factors. Higher foreign interest rate, global growth rate and global liquidity lower the
volatility of capital flows in developing countries. It reduces the incentive for foreign
investors to go offshore as well as it increases the risk for investing in developing
countries which discourage foreign capital inflows. Higher inflation is associated to higher
volatility. On the other hand higher foreign interest rate may also increase the volatility in
domestic market if there is business cycle co-movement. Higher foreign growth can also
increase the volatility in domestic market by the availability of funds for investment.
Regarding the determinants of volatility of trade flows literature provide the empirical
evidence regarding instability of exports. Empirical literature discusses both the demand
Chapter # 2 Literature Review
98
and supply side factors. Based on these factors studies analyze some determinants that
affect instability these include commodity concentration, geographical concentration,
share of primary exports (food and raw materials), domestic consumption of exported
goods, export market share, size of the export sector, per capita income, exchange rate
uncertainty etc.
Instability reduces if exports are more diversified. Geographic concentration also brings
higher export instability as it increases the dependence on one or few countries and any
change in economic condition of these countries bring higher export instability. More
diversified export destinations reduce the export instability. There is also opposing view
that higher geographical concentration as a result of international commodity agreements
increases the stability. Primary products face more unstable demand and supply curves and
lead to greater degree of fluctuation in export receipts. Higher domestic consumption
increases the export instability. Larger export market share contributes to more diversified
exports and absorb the demand fluctuations. Size of the export sector also represents the
export share in the world market. Higher per capita income shows flexibility where a
country is better able to shift the resources among products as a result of demand
fluctuations. Exchange rate volatility reduces trade volume and increases the trade
variability by inducing the risk.
We conclude that available literature on export instability discusses some common factors
as commodity concentration, geographical concentration, size of export sector and
composition of exports. There is only one study that discusses the relationship of export
instability with exchange rate uncertainty while there are level studies available in this
respect. Moreover available literature also ignores external factors as determinants of
export instability. Therefore while explaining our result we will get empirical support from
level studies for some variables.
Chapter # 2 Literature Review
99
Regarding the determinants of fiscal policy volatility empirical literature examines the
political, institutional macroeconomic and demographic variables as a cause of volatility.
Moreover policy persistence is also included as a lag of dependent variable. Literature
ignores the role of external factors in explaining the fiscal policy volatility. In a globalized
world external factors are an important source of policy volatility in domestic economy.
Political and institutional factors include political constraints, constraints on the executive,
political system, electoral system and number of elections, political instability, democracy,
rule of law etc. Volatility of fiscal policy increases in countries with proportional as
opposed to majoritarian electoral systems and with presidential regimes. Governments that
face political constraints on decision making like checks and balances, from parliament or
from the judiciary, cannot use fiscal policy too aggressively with higher discretion. It
generates policy which is highly predictable and this predictability reduces the volatility.
Macroeconomic variables include per capita GDP, inflation, trade openness and level of
fiscal variables. Poor countries have more volatile budget deficits as a result of their larger
output voariability, less developed financial markets, poor institutions and weak automatic
stabilizers while richer countries are characterized with stable deficits. Higher inflation
increases the fiscal volatility as it brings economic uncertainty making volatile the
spending and revenue. Trade openness increases the volatility of budget deficit as it
exposes the countries to external shocks. Higher public deficit increases the instability due
to unanticipated changes in government expenditures and taxation.
Demographic variables include population size, urbanization and dependency ratio. Large
population spreads the cost of financing over a large pool of tax payers and brings less
volatility in budget deficits. Urbanization and dependency ratio increases the volatility.
Regarding the volatility of monetary policy or interest rate empirical literature is scant.
General tradition is to use high frequency data of different short term interest rates using
Chapter # 2 Literature Review
100
time series properties and measure the volatility through different methods and then
compare the magnitude of volatility. It just provides the information that the method
which provides the lowest magnitude of volatility is better. We have just one study that
describes the link between institutional quality and cyclicity of monetary policy and its
volatility. It shows positive co-movement between output and the interest rate
(countercyclical monetary policy) at relatively high levels of institutional quality. There is
an inverse association between volatility of interest rates and the institutional quality.
As we have described above that empirical literature is scare regarding the volatility of
monetary policy or interest rate and the available literature discuss only the magnitudes of
volatility through different measures therefore we will get literature support from the level
studies while explaining our results because we are not interested in magnitudes of
volatility through different measures but in determinants of monetary volatility.
2.8 Literature gap:
As discussed in the previous sections that policy volatility reduces the economic growth
mainly through investment channel therefore it is important to explore the factors that can
reduce the volatility. In this regard there is a lot of literature relating the level of policies to
different macroeconomic factors but literature is scarce regarding the volatility of policy.
Moreover there are only few studies that incorporate institutional quality as an important
determinant to reduce the uncertainty or volatility of policy. So it leaves the gap for
identifying the effect of different domestic macroeconomic, institutional and global factors
on policy volatility. Present study fills the gap by addressing the policy volatility and
identifying the factors contributing to it specifically institutional quality. This establishes
the link between institutional quality and policy instability or uncertainty.
We have described in concluding remarks of previous section (2.7.2) that the determinants
of fiscal policy have been extensively empirically examined but unluckily the literature on
Chapter # 2 Literature Review
101
fiscal volatility is scant. Similarly an increasing body of literature has highlighted the
importance of the level of capital flows by incorporating pull and push factors. In
contrast, relatively few empirical studies have tried to identify the factors that shape
volatility of capital flows. Regarding the volatility of monetary policy or interest rate
empirical literature is also scant. General tradition is to use high frequency data of
different short term interest and measure the volatility through different methods and then
compare the magnitude of volatility. While we are not interested in magnitude of volatility
but in domestic macroeconomic and external factors that determine monetary volatility
specifically institutional quality. Regarding the volatility of trade flows there are only few
studies and they ignore institutional and external factors as determinants of export
instability.
103
102
An Overview of Selected Developing Countries
The chapter is divided into four sections; the first section gives a brief overview of the
economies of selected countries, the second section discusses the dynamics of institutions
and policies of selected countries and the third section provides an overview of
institutional reforms in developing countries. The last section draws the conclusion from
the preceding sections.
3.1 An overview of the economies of selected countries:
We will start this section by giving a synoptic view of the economic performance of
selected countries, in a tabular form to compare the state of their economies. Table 3.2
shows the comparison of per capita growth rates, population growth, inflation rate, human
development and perception of corruption among the selected countries in year 2000 and
2014. Comparison of per capita growth rate shows that in year 2000 growth rate of
Srilanka was highest (6%) while of Kenya was lowest (-1.87%). In year 2014 again
Srilankas’ growth rate was highest (7.36%) while it was lowest in Brazil (-0.73%). During
2000 to 2014 the percentage increase in growth was highest in Kenya (237%), India
ranked second after Kenya having (203 %) increase in growth, while maximum reduction
in growth rate between these two years was in Brazil (91%). Second, population growth
rate in 2000 was highest in Maldives (3.99%) while lowest in Srilanka (0.93%). In 2014
population growth rate was highest in Kenya (2.88%) while it was lowest in Brazil (0.3%).
During 2000-2014 population growth rate was increased in Nepal (20%) while reduced in
all other countries, with maximum reduction in Thailand (81%)
Chapter # 3
103
Table 3.1 Main economic indicators of selected countries
Indicators years Pakistan India Bangladesh Srilanka Maldives Nepal Philippines Vietnam Thailand brazil Mexico Kenya
GDP per capita
growth
2000 1.92 2.01 3.26 6 2.96 4.29 2.20 5.36 3.54 2.81 3.71 -1.87
2014 3.21 6.10 4.86 7.36 5.66 4.20 4.41 4.79 0.30 -0.73 0.78 2.57
%
change 67.19 203.48 49.08 22.67 91.22 -2.10 100.45 -10.63 -91.53 -125.98 -78.98 237.43
Population
growth
2000 3.10 2.18 2.81 0.93 3.99 2.10 2.56 2.60 1.63 2.15 2.02 3.33
2014 2.48 1.73 1.95 0.42 2.05 2.52 1.92 1.07 0.30 0.88 1.83 2.88
%
change -20.00 -20.64 -30.60 -54.84 -48.62 20.00 -25.00 -58.85 -81.60 -59.07 -9.41 -13.51
Inflation rate 2000 4.4 4 2.2 6.2 -1.17 2.5 4 -1.7 1.6 7 9.5 10
2014 7.2 6.4 7 3.3 2.1 8.4 4.1 4.1 1.9 6.3 4 6.9
%
change 63.64 60.00 218.18 -46.77 279.49 236.00 2.50 341.18 18.75 -10.00 -57.89 -31.00
Human
development
index
2000 0.45 0.48 0.45 0.67 0.59 0.44 0.61 0.56 0.64 0.68 0.69 0.45
2014 0.53 0.60 0.57 0.75 0.70 0.54 0.66 0.66 0.72 0.75 0.75 0.54
%
change 17.78 25.00 26.67 11.94 18.64 22.73 8.20 17.86 12.50 10.29 8.70 20.00
Corruption
perception
index
2000 23 27 4 37 24 22 29 26 32 40 37 20
2014 29 38 25 38 27 29 38 31 38 43 35 25
%
change 26.09 40.74 525.00 2.70 12.50 31.82 31.03 19.23 18.75 7.50 -5.41 25.00
Source: World Bank and Transparency international.
Note: Human Development Index lies between 0-1 while Corruption perception index lies between 1-100, where 100 shows no corruption.
Chapter # 3 An Over View of Selected Developing Countries
104
Third, comparison of inflation rate in 2000 shows that it was highest in Kenya (10%)
while lowest in Maldives (-1.17). In year 2014 inflation was highest in Nepal (8%) while
lowest in Thailand (1.9%). Highest percentage increase between these two years was in
Vietnam (341%) while maximum reduction during these years was in Mexico (57%).
Fourth, Human development, represented by (HDI), was highest in Mexico (0.69) while
lowest in Nepal (0.44) in the year 2000. In 2014 it was highest in Mexico, Brazil and
Srilanka with equal score (0.75) while lowest in Pakistan (0.53). Percentage increase
during 2000-2014 was highest in Bangladesh (26%) while lowest in Philippines (8%).
Last, perception of corruption, represented by corruption perception index, was highest in
Bangladesh (4) while lowest in Brazil (40) in 2000. In 2014 it was highest in Bangladesh
and Kenya with an index value of (25) for both countries while it was lowest in Brazil
again (43). Percentage increase in corruption perception during these two years was only
in Mexico with a (5%) increase while reduction took place in all other countries, with
maximum reduction Bangladesh (525%) and least reduction in Maldives with a (12% )
reduction.
We may now proceed with a country wise explanation of the absolute positions of each of
the twelve countries.
3.1.1 Pakistan:
Pakistan is a developing country having population over 190 million and with a nominal
GDP per capita of $1,561 according to 2016 estimates20
. Pakistan has undergone a process
of economic liberalization including privatization, financial and trade liberalization and
fiscal reforms. Until a few years ago Pakistan's economy was highly unstable and exposed
to global and domestic shocks. Though the economy proved to be resistant against the
20
World Bank country reports, The World Factbook. Central Intelligence Agency, Pakistan economic
survey, various issues, Ministry of finance.
Chapter # 3 An Over View of Selected Developing Countries
105
adverse shocks during (1998-2002) which include the Asian financial crisis, economic
sanctions , the global recession, a severe famine, military operation in Afghanistan, after
9/11, which caused a huge inflow of immigrants.
Government has made substantial economic reforms since 2000 for poverty reduction and
job creation under medium-term projections. Pakistan is continuously cutting tariffs and
encouraging the exports by improving the infrastructure. Fall in money-market interest
rate and a greater expansion in bank credit as a result of monetary policy stability is
changing consumption and investment patterns. The government is following an export-
led strategy of economic growth following South East Asia and China. Financial sector
reforms have improved the financial sector.
Pakistan's economic outlook has deteriorated since the beginning of 2008. Greater
instability has created by security concerns and Pakistan is playing a major role in the War
on Terror. These security concerns have created imbalance in financial resources by
reducing the social sector expenditure and has led to a decline in Foreign Direct
Investment from approximately $8 billion to $3.5billion. Higher global commodity prices
have increased the trade deficit, induced higher inflation and a continuous decline in the
value of the currency. Pakistan has a low tax to GDP ratio which is far below other
countries of the region such as India and Sri Lanka.
The sectoral share of agriculture in GDP has declined over time. There is rapid growth in
industrial (such as apparel, textiles, and cement) and services sector (such as
telecommunications, transportation, advertising, and finance). Industrial sector growth has
accelerated due to the policies of the government to diversify the industrial sector and
boost export industries.
Chapter # 3 An Over View of Selected Developing Countries
106
Figure 3.1 Governance indictors (percentile score):
Source: World Governance Indicators (World Bank)
Figure 3.2 Indicators of financial liberalization (% of GDP):
Source: Lane and Ferretti (2007).
Table 3.2 Indicators of fiscal and monetary policy and trade liberalization
Variables 1990 1994 1998 2002 2006 2010 2014 Govt. expenditures
(% of GDP) Current expenditures
Capital expenditures
29.17 26.05 25.56 19.93 19.89 21.05 21.5
21.79 20.95 21.36 16.89 15.49 16.75 16.75
7.38 5.1 4.2 3.05 4.4 4.31 4.75
Tax revenue
(% of GDP) 13.32 12.75 12.83 10.31 8.75 9.98 10.2
Interest rate 7.64 11.52 4.16 4.63 10.98 14.04 11.73
Average tariff rate tariff rate capital goods
tariff rate consumer goods
60.58 52.87 45.61 17.17 14.79 14.8 13.63
30.56 32.56 28.45 26.96 23.97 22.23 22.64
40.36 36.41 32.41 27.14 21.42 22.52 21.79
Trade openness
(% of GDP) 38.909 35.327 34.012 30.538 35.682 32.869 31.168
Import tax revenue (% of imports)
65.459 39.441 25.312 10.073 6.65 3.516 2.451
Source: Asian Development Bank (ADB) and World Development Indicators (World Bank).
0
10
20
30
40
1996 2000 2004 2008 2012
control of corruption
govt. effectiveness
political stability
regulatory quality
rule of law
voice & accountability
0
50
1990 1994 1998 2002 2006 2010 2014
portfolio assets & liabilities
FDI assets & liabilities
Debt assets & liabilities
Chapter # 3 An Over View of Selected Developing Countries
107
3.1.2 India:
India is a newly industrialized country, a member of BRICS and one of the G-20 major
economies, with an average growth rate of approximately 7% over the last two decades21
.
After the end of British subjugation the India was governed by protectionist policies with
little or no liberalization. Indian economy was characterized by widespread regulation,
protectionism, public ownership, extensive corruption and slow growth. Economic
liberalization has led the country towards a more liberal and market friendly economy
since 1991. Liberalization has lower down the trade barriers including tariff rates and the
policies of deregulation and privatization have shattered public monopolies by
encouraging foreign investment in many sectors. By reducing the state control and
improved financial liberalization India has moved towards a free-market economy by the
21st century.
With an annual growth rate of above 9%, India has one of fastest growing service sectors
in the world. India has also become a major exporter of information technology (IT) and
software services. India has one of the largest auto mobile industries in the world.
The value of India's international trade has increased sharply since liberalization. As a part
of financial sector reforms India's relaxed its FDI policy in 2005 by allowing up to a 100%
FDI stake in ventures. Industrial reforms have significantly lower the restrictions and
enabled easy access to foreign technology and foreign investment. Though India has put
controls on short term capital inflows in order to avoid the currency crisis. The
government has also approved significant banking reforms since liberalization.
A major and widespread problem affecting the Indian economy is corruption. India was
ranked at 95th place in public sector corruption in 2011 by the Transparency International.
By reducing the corruption India enhanced the ranking to 85th place in 2014. The Indian
21
World Bank – India Country Overview, CIA – The World Factbook – India, Reserve Bank of India.
Chapter # 3 An Over View of Selected Developing Countries
108
economy has a huge underground economy, Swiss Bankers Association recommended
India topped the worldwide list for black money.
Figure 3.3 Governance indictors (percentile score):
Source: World Governance Indicators (World Bank)
Figure 3.4 Indicators of financial liberalization (% of GDP):
Source: Lane and Ferretti (2007)
Table 3.3 Indicators of fiscal and monetary policy and trade liberalization
Variables 1990 1994 1998 2002 2006 2010 2014 Govt. expenditures
(% of GDP) Current expenditures
Capital expenditures
19.08 16.33 15.81 18.27 15.39 16.52 14.56
14.27 13.2 13.39 14.98 13.58 14.36 12.89
4.81 3.13 2.42 3.3 1.81 2.16 1.67
Tax revenue
(% of GDP) 9.82 8.83 7.97 8.53 11.03 10.19 9.21
Interest rate 16.5 14.75 13.54 11.91 11.18 8.33 10.25
Average tariff rate tariff rate capital goods
tariff rate consumer goods
81.56 52.98 28.23 28.18 10 8.31 9.37
72.72 36.45 22.15 20.79 4.99 4.59 4.89
25.28 16.58 26.85 30.04 10.13 9.77 8.35
Trade openness
(% of GDP) 15.239 19.732 23.291 29 52.269 48.308 49.558
Import tax revenue (% of imports)
78.212 54.49 33.536 18.832 2.601 2.517 1.803
Source: Asian Development Bank (ADB) and World Development Indicators (World Bank)
0
10
20
30
40
50
60
70
1996 2000 2004 2008 2012
control of corruption
govt. effectiveness
political stability
regulatory quality
rule of law
voice & accountability
0
20
40
1990 1994 1998 2002 2006 20102014
portfolio assets & liabilities
FDI assets & liabilities
debt assets & liabilities
Chapter # 3 An Over View of Selected Developing Countries
109
3.1.3 Bangladesh:
By purchasing power parity the economy of Bangladesh is the 32nd largest in the world.
Bangladesh has an average GDP growth rate of 6.5%, throughout last decades. Per-capita
income remained at US$3,840 (PPP) and US$1,466 (Nominal) in 201622
.
Inefficiency and economic stagnation in early period was the result of static policies
adopted by early leaders which included the nationalization of much of the industrial
sector. Government slowly moved to liberal policies by allowing and encouraging the
private sector in the economy in late 1975. Privatization and liberalization led the
economy towards progress in the mid-1980s The government successfully followed an
enhanced structural adjustment facility (ESAF) with the International Monetary Fund
(IMF) from 1991 to 1993 but remain unsuccessful to follow it completely because of
domestic political distresses.
Textile industry of Bangladesh has an important contribution in export sector which
includes knitwear and ready-made garments along with other textile products. Bangladesh
is second in world textile exports, behind China, which exported $120.1 billion worth of
textiles in 2009. It is an important source of employment and earnings for the female
sector. More than one million formal sector jobs for women are created by the garment
industry, contributing to the high female labour participation in Bangladesh.
Government has provided a large number of inducements to investors comprising 10-year
tax holidays, tariff and non-tariff reductions on import of capital goods, raw materials and
dividend tax exceptions. Bangladesh has improved the climate for foreign investors by
liberalizing the capital markets. Reforms were aimed at development of financial
22
Bangladesh Economy - Asian Development Bank, The World Factbook. Central Intelligence Agency.
Bangladesh Economic Review, various issues, Ministry of finance.
Chapter # 3 An Over View of Selected Developing Countries
110
institutions and regulations. Millions of investors have been rendered bankrupt due to the
capital market crash during 2010.
Figure 3.5 Governance indictors (percentile score):
Source: World Governance Indicators (World Bank)
Figure 3.6 Indicators of financial liberalization (% of GDP):
Source: Lane and Ferretti (2007)
Table 3.4 Indicators of fiscal and monetary policy and trade liberalization
Variables 1990 1994 1998 2002 2006 2010 2014 Govt. expenditures
(% of GDP) Current expenditures
Capital expenditures
12.42 15.05 12.92 14.92 14.69 12.7 13.68
6.71 6.72 7.1 8.3 8.8 9.17 9.3
5.7 8.32 5.81 6.61 5.88 3.53 4.38
Tax revenue
(% of GDP) 6.75 9.22 9.5 10.2 10.78 9.51 10.4
Interest rate 16 14.5 14 16 15.33 13 13
Average tariff rate tariff rate capital goods
tariff rate consumer goods
27.52 24.36 22.26 21.01 15.21 13.91 12.56
55.23 42.86 26.34 12.45 9.63 6.66 7.18
126.23 62.85 38.25 29.86 27.55 15.1 14
Trade openness
(% of GDP) 18.967 22.866 27.88 28.967 38.112 37.803 44.988
Import tax revenue (% of imports)
94.25 85.839 56.006 43.948 22.121 10.048 6.879
Source: Asian Development Bank (ADB) and World Development Indicators (World Bank).
0
10
20
30
40
50
1996 2000 2004 2008 2012
control of corruption
govt. effectiveness
political stability
regulatory quality
rule of law
voice & accountability
0
50
1990 1994 1998 2002 2006 20102014
portfolio assets & liabilities
FDI assets & liabilities
debt assets & liabilities
Chapter # 3 An Over View of Selected Developing Countries
111
3.1.4 Srilanka:
Sri Lanka has mostly strong growth rates in recent years with $233.637 billion GDP at
purchasing power parity and a per capita GDP of about $11,068.996 (PPP) in 201523
.
During the last decade robust annual growth rate was 6.4 percent. In Sri Lanka tax-to-GDP
ratios are lowest in the world. Sri Lanka is now concentrating on long-term strategic and
development challenges since the end of the three-decade civil war.
The economy of Sri Lanka has been affected by natural disasters such as the 2004 Indian
Ocean earthquake. Internal conflicts also destabilized the economy such as the 1971, the
1987-89and the 1983-2009 civil wars. Since 1977, the move away from a socialist
orientation the, the government has taken many steps towards deregulation, privatization
and encouraging the foreign competition. Country moved from import substitution
towards free market policies and export-led growth.
The key sectors include tourism, tea export, textile, rice production and other agricultural
products. In Srilanka overseas employment contributes greatly in foreign exchange as
large number of emigrants lives in Middle East. Tourism is one of the main industry of
Srilanka and an important source of finance. Due to Indian Ocean Tsunami and the
instabilities caused by internal conflicts this industry suffered greatly however beginning
in early 2008 tourists visiting have been recently increasing.
Sri Lanka is on track to meet most of the MDGs, overtaking other South Asian countries;
Sri Lanka has met the target of halving extreme poverty and moving ahead towards other
targets. Between 2002 and 2009 Sri Lanka witnessed a huge drop in poverty, from 23
percent to 9 percent of the population.
23
Sri Lanka Overview - World Bank, Sri Lanka: Economy - Asian Development Bank , CIA Factbook,
Central Bank of Sri Lanka.
Chapter # 3 An Over View of Selected Developing Countries
112
Figure 3.7 Governance indictors (percentile score):
Source: World Governance Indicators (World Bank)
Figure 3.8 Indicators of financial liberalization (% of GDP):
Source: Lane and Ferretti (2007)
Table 3.5 Indicators of fiscal and monetary policy and trade liberalization
Variables 1990 1994 1998 2002 2006 2010 2014 Govt. expenditures
(% of GDP) Current expenditures
Capital expenditures
28.72 27.19 24.27 23.8 24.17 22.11 18.22
22.58 21.94 19.09 20.22 18.65 16.72 13.52
6.14 5.25 5.18 3.58 5.52 5.39 4.7
Tax revenue
(% of GDP) 19.02 17.17 14.48 13.56 14.58 12.93 10.73
Interest rate 13 18.12 15.02 13.17 12.85 10.21 7.83
Average tariff rate tariff rate capital goods
tariff rate consumer goods
26.54 24.3 16.23 9.86 11.29 9.39 9.33
13.76 16.99 8.25 6.65 7.29 5.18 4.5
29.98 32.64 18.36 12.85 13.16 13.96 12.01
Trade openness
(% of GDP) 68.244 79.431 78.495 76.335 71.261 53.062 53.211
Import tax revenue (% of imports)
64.181 29.896 20.225 13.132 7.527 4.116 7.726
Source: Asian Development Bank (ADB) and World Development Indicators (World Bank)
0
10
20
30
40
50
60
70
1996 2000 2004 2008 2012
control of corruption
govt. effectiveness
political stability
regulatory quality
rule of law
voice & accountability
0
50
100
1990 1994 1998 2002 2006 20102014
portfolio assets & liabilitiesFDI ssets & liabilitiesdebt assets & liabilities
Chapter # 3 An Over View of Selected Developing Countries
113
3.1.5 Maldives:
Main sectors of the economy of the Maldives are tourism, fishing and shipping. Tourism
accounted for 28% of GDP and more than 60% of the Maldives' foreign exchange
receipts24
. Tourism is the largest industry and Maldives has successfully promoted it.
Tourism-related taxes account for 90 % of government tax revenue.
Second leading sector in the Maldives is fishing. In 1989 as a result of economic reforms
the government reduced the trade barriers and allowed the private sector to participate in
this sector’s exports. Later on government further relaxed the regulations to permit more
foreign investment. Dried or canned fish consist of 42%, frozen fish consists of 31% and
the remaining fresh fish consists of 10% of total fish exports. The contribution of this
sector in GDP is 10% and provides the employment to 20% of the labour force. Due to the
unavailability of enough cultivable land and lack of domestic labour agriculture and
manufacture sector do not play a major role in the economy.
The banking industry of Maldives dominates the small financial sector. The Maldives has
been considered to have the simplest tax code in the world, no income, sales, property, or
capital-gains taxes. As for as economic assistance is concerned different multilateral
organizations have contributed in this regard such as United Nations Development
Programme, Asian Development Bank and the World Bank have played a major role in
the economy of Maldives.
Regarding the Millennium Development Goal (MDG), Maldives has successfully
achieved the target of poverty reduction by reducing the percentage of people living below
poverty line to one half according to the estimates of 2011. Malaria has been removed,
Starvation is non-existent and HIV rates have dropped.
24
CIA World Factbook Maldives, Maldives Overview - World Bank, Ministry of Finance and Treasury,
Maldives.
Chapter # 3 An Over View of Selected Developing Countries
114
Figure 3.9 Governance indictors (percentile score):
Source: World Governance Indicators (World Bank)
Figure 3.10 Indicators of financial liberalization (% of GDP):
Source: Lane and Ferretti (2007)
Table 3.6 Indicators of fiscal and monetary policy and trade liberalization
Variables 1990 1994 1998 2002 2006 2010 2014 Govt. expenditures
(% of GDP) Current expenditures
Capital expenditures
14.9 19.57 23.85 23.21 42.36 40.26 41.74
7.257 9.976 14.64 15.62 33.61 30.85 34.3
7.64 9.6 9.21 7.6 8.74 9.4 7.44
Tax revenue
(% of GDP) 13.96 13 14.2 10.3 14.21 10.73 25.02
Interest rate 19 12 15 13.54 13 10.37 11.41
Average tariff rate tariff rate capital goods
tariff rate consumer goods
21.39 21.26 21.38 21.98 21.21
24.34 24.64 23.74 22.38 22.65
21.3 19.81 22.09 20.43 16.74
Trade openness
(% of GDP) 168.08 156.946 161.091 104.41 123.665 158.656 195.604
Import tax revenue (% of imports)
90.175 93.659 64.372 62.89 29.796 24.985 11.017
Source: Asian Development Bank (ADB) and World Development Indicators (World Bank)
0
20
40
60
80
100
1996 2000 2004 2008 2012
control of corruption
govt. effectiveness
political stability
regulatory quality
rule of law
voice & accountability
0
50
100
1990 1994 1998 2002 2006 20102014
portfolio assets & liabilities
FDI assets & liabilities
debt assets & liabilities
Chapter # 3 An Over View of Selected Developing Countries
115
3.1.6 Nepal:
Since 1950s Nepal has made progress toward sustainable economic growth. Nepal is
devoted to the program of privatization and deregulation. Many state enterprises have been
privatized and its currency has been made convertible. Foreign assistance from different
multilateral and bilateral donor agencies plays an important part in the development
budget of Nepal. To develop the transportation and communication sector and to increase
the efficiency and productivity of industrial sector have remained the priorities of the
government over the years.
Agriculture is the key sector of the economy, contributing 37% of GDP and providing
employment to 70% of the population according to 2013 estimates25
. In recent years
industrial sector has grown rapidly and contribute to nearly 70% of merchandise exports.
Remittances of foreign workers are a big source of income in Nepal. Overall balance of
payments and international reserves have improved due to increased productivity of export
sector and income from tourism sector. Tourism plays an important role in the economy of
Maldives.
Foreign investment is taking place mostly in real estate and tourism. Having huge
capacity of Hydroelectricity in Nepal large many foreign firms are in line but the process
has stopped due to political instability. Numerous multilateral organizations also provide
assistance such as the World Bank, the Asian Development Bank and the UN
Development Programme.
Development in infrastructure and social services has not made remarkable progress.
Country wide universal education system is not well developed also. In Nepal the Cost of
Living Index in is relatively smaller as compared to many other countries. In recent years
25
Nepal Overview - World Bank, Nepal: Economy - Asian Development Bank, Economic Review - Central
Bank of Nepal.
Chapter # 3 An Over View of Selected Developing Countries
116
the quality of life has deteriorated. Out of 81 ranked worst countries Nepal was ranked
54th
.
Figure 3.11 Governance indictors (percentile score):
Source: World Governance Indicators (World Bank)
Figure 3.12 Indicators of financial liberalization (% of GDP):
Source: Lane and Ferretti (2007)
Table 3.7 Indicators of fiscal and monetary policy and trade liberalization
Variables 1990 1994 1998 2002 2006 2010 2014 Govt. expenditures
(% of GDP) Current expenditures
Capital expenditures
17.72 15.65 17.35 17.43 14.54 19.04 19.6
6.012 5.78 8.4 10.58 10.25 15.64 16.31
11.7 9.87 8.95 6.85 4.3 3.4 3.29
Tax revenue
(% of GDP) 7 7.73 8.64 8.56 8.78 13.4 16.1
Interest rate 14.41 7.31 14 6.77 8 8 6.13
Average tariff rate tariff rate capital goods
tariff rate consumer goods
22.56 20.88 21.69 14.57 12.51 12.62 11.82
32.56 42.58 21.45 13.96 14.23 11.16 8.56
35.58 34.25 33.55 28.63 20.85 19.2 18.63
Trade openness
(% of GDP) 32.189 50.432 56.71 46.231 44.762 45.985 52.445
Import tax revenue (% of imports)
86.536 42.684 40.198 33.013 16.047 6.433 4.765
Source: Asian Development Bank (ADB) and World Development Indicators (World Bank
0
10
20
30
40
50
60
70
1996 2000 2004 2008 2012
control of corruptiongovt. effectivenesspolitical stabilityregulatory qualityrule of lawvoice & accountability
0
20
40
60
80
1990 1994 1998 2002 2006 20102014
portfolio assets & liabilitiesFDI assets & liabilitiesdebt assets & liabilities
Chapter # 3 An Over View of Selected Developing Countries
117
3.1.7 Thailand:
Thailand is a newly industrialized country and export sector play a major role in the
economy. Exports account for more than two-thirds of its gross domestic product (GDP).
Average growth rate of the economy is 6.5 percent with an inflation rate of 3.02 percent26
.
Industrial and service sectors play an important role in the economy of Thailand,
contributing to 39.2 and 54.4 percent of GDP respectively according to 2012 estimates.
Thailand’s trade balance has improved much with the help of automobile exports since
2005, with over one million cars produced annually. About 15 percent of total exports
electronics is Thailand's largest export sector. Trade in services has emerged as a source of
industrial expansion and economic competitiveness. Thailand has pursued many free-trade
agreements. Tourism is an important sector significantly contributing to the Thai
economy, around 8.5 percent of GDP.
Thai economy collapsed confronted with the 1997 financial crisis. The crisis was the result
of over investment in the real estate and share market. As a result of crisis the Stock
Exchange of Thailand fell from a peak of 1,753.73 in 1994 to a low of 207.31 in 1998.
Foreign debt increased due to sharp decline in the value of baht. Many financial
institutions undergo bankruptcy.
The country has confronted a number of internal and external challenges since 2007; in
late 2006 having a military coup, from 2008 to 2011 political disorder, from 2008 to 2009
the US financial crisis, floods in 2010 and 2011 and Eurozone crisis of 2012.
Through the collaboration of state and foreign-owned institutions the government has
attempted to strengthen the financial sector. The reforms of the financial sector, corporate-
26
Thailand Overview - World Bank, Thailand: Economy - Asian Development Bank, Economic Reports,
Ministry of Finance Thailand.
Chapter # 3 An Over View of Selected Developing Countries
118
debt restructuring, stimulus to foreign investment and exports have improved the
economy.
Figure 3.13 Governance indictors (percentile score):
Source: World Governance Indicators (World Bank)
Figure 3.14 Indicators of financial liberalization (% of GDP):
Source: Lane and Ferretti (2007)
Table 3.8 Indicators of fiscal and monetary policy and trade liberalization
Variables 1990 1994 1998 2002 2006 2010 2014 Govt. expenditures
(% of GDP) Current expenditures
Capital expenditures
13.94 15.96 22.36 24.06 18.52 19.73 19.87
11.41 10.55 16.37 21.19 16.52 17.83 18.58
2.53 5.41 5.99 2.87 2 1.9 1.29
Tax revenue
(% of GDP) 16 12.86 15.25 13.68 16.52 14.57 15.31
Interest rate 14.41 10.89 14.41 6.87 7.35 5.93 6.77
Average tariff rate tariff rate capital goods
tariff rate consumer goods
41.22 24.36 32.05 13.76 10.81 11.1 8.42
38.35 20.56 26.52 7.69 4.55 5.39 2.57
45.76 36.54 32.14 17.85 10.16 13.48 5.58
Trade openness
(% of GDP) 75.782 82.587 101.868 121.697 143.804 135.142 142.731
Import tax revenue (% of imports)
54.821 25.03 23.424 13.658 3.432 1.944 0.728
Source: Asian Development Bank (ADB) and World Development Indicators (World Bank)
0
10
20
30
40
50
60
70
1996 2000 2004 2008 2012
controll of corruption
govt. effectiveness
political stability
regulatory quality
rule of law
voice & accountability
0
50
100
1990 1994 1998 2002 2006 2010 2014
portfolio assets & liabilities
FDI assets & liabilities
debt assets & liabilities
Chapter # 3 An Over View of Selected Developing Countries
119
3.1.8 Vietnam:
Vietnam's economy is a developing market economy. Vietnam has moved from a highly
centralized economy to a mixed economy since the mid-1980s. The economy has
experienced rapid growth over that period. The nominal GDP reached to US$198.8 billion
with nominal GDP per capita of US$2,073 in 201527
.
The economy of Vietnam experienced a slowdown in productivity and growth after the
end of the Cold War. Country has moved towards a more market-oriented economy as a
result of liberalization, though government has still control over the key sectors such as
financial sector, state-owned enterprises and foreign trade.
Vietnam is one of the largest exporters of rice in the world market followed by coffee.
Manufacturing sector experienced rapid growth including food processing, electrical
goods, chemicals, cigarettes and tobacco. Real estate sector has contributed greatly in the
economy over the last 2 decades but also caused "bubble" to the economy. Share of the
services sector to the GDP increased to an average annual rate of 6.0% from 1994 to 2004.
Vietnam is also an attractive destination for tourists.
The economy of Vietnam depends greatly on foreign investment. In this regard Vietnam
encourages and facilitates the foreign direct investment to attract the capital from overseas.
Industry and construction are the largest sectors for licensed FDI. Important channels of
investments in the economy are mergers and acquisitions especially after 2005.
There are three objectives of World Bank's support program for Vietnam; to encourage
Vietnam’s switch to a market economy, to support good governance and to enhance
equitable and sustainable development. Major obstacles to investment include Corruption,
lack of transparency, poor property rights to investors and bureaucracy.
27
Vietnam Overview - World Bank , Viet Nam: Economy -Asian Development Bank, Vietnam country
statistics by Ministry of Finance and State Bank.
Chapter # 3 An Over View of Selected Developing Countries
120
Figure 3.15 Governance indictors (percentile score):
Source: World Governance Indicators (World Bank)
Figure 3.16 Indicators of financial liberalization (% of GDP):
Source: Lane and Ferretti (2007)
Table 3.9 Indicators of fiscal and monetary policy and trade liberalization
Variables 1990 1994 1998 2002 2006 2010 2014 Govt. expenditures
(% of GDP) Current expenditures
Capital expenditures
21.89 25.01 20.34 24.16 25.28 27.17 25.61
16.83 18.68 14.65 15.72 16.96 18.68 20.33
5.06 6.33 5.68 8.44 8.32 8.49 5.28
Tax revenue
(% of GDP) 14.7 22 19.6 22.3 26.8 26.71 21.76
Interest rate 26.4 18.9 14.4 9.06 11.17 13.13 8.66
Average tariff rate tariff rate capital goods
tariff rate consumer goods
21.68 14.5 15.45 14.21 11.9 7.29 6.7
11.25 9.58 12.56 11.44 6.22 3.3 1.56
26.53 24.25 22.96 22.32 15.5 10.19 6.35
Trade openness
(% of GDP) 81.316 77.473 97.001 107.829 138.314 152.217 165.094
Source: Asian Development Bank (ADB) and World Development Indicators (World Bank)
0
10
20
30
40
50
60
1996 2000 2004 2008 2012
control of corruption
govt. effectiveness
political stability
regulatory quality
rule of law
voice & accountability
0
50
100
150
1990 1994 1998 2002 2006 20102014
portfolio assets & liabilities
FDI assets & liabilities
debt assets & liabilities
Chapter # 3 An Over View of Selected Developing Countries
121
3.1.9 Philippines:
The Economy of the Philippines is one of the emerging markets. The GDP estimates for
2016 are $811.726 billion at Purchasing power parity. Political instability aggrieved the
country and the economy. Currently it is one of Asia's fastest growing economies.
The Philippines is a newly industrialized economy, transitioning from agriculture to
services and manufacturing. Services sector has become the dominant sector of the
economy. The industrial sector consists of processing and assembly processes in the
manufacturing of electronics and other high-tech components. Tourism plays an important
role by sector contributing 7.8% to the gross domestic product (GDP) according to 2014
estimates. Tourism sector is major source of employment as it provided employment to 3.8
million people in 201428
. Overseas workers are a significant contributor to the economy.
Business process outsourcing (BPO) is regarded as one of the fastest growing industries in
the world. Many reputed BPO firms of the United States operate in Philippines. BPO
industry continues to show significant improvements. Philippines is regarded as choice of
location owing to less expensive labour and operational costs and a highly educated labor
pool. Government provides the incentives to further encourage the investors such as tax
holidays, tax exclusions, and easy business processes.
Both tourism and foreign investment play an important role in the development of the
economy. To improve and encourage the tourism industry certain policies are introduced
such as Holiday Economics, encourage celebrating certain holidays.
28
Philippines: Economy- Asian Development Bank, CIA World Factbook, Economic statistics, Central
Bank of Phillipines.
Chapter # 3 An Over View of Selected Developing Countries
122
Figure 3.17 Governance indictors (percentile score):
Source: World Governance Indicators (World Bank)
Figure 3.18 Indicators of financial liberalization (% of GDP):
Source: Lane and Ferretti (2007)
Table 3.10 Indicators of fiscal and monetary policy and trade liberalization
Variables 1990 1994 1998 2002 2006 2010 2014 Govt. expenditures
(% of GDP) Current expenditures
Capital expenditures
20.4 18.85 19.22 19.84 17.31 16.9 18
17.28 16.38 17.56 18.57 16.81 16.88 16.98
3.12 2.47 1.66 1.27 0.5 0.02 1.02
Tax revenue
(% of GDP) 14.08 16.03 14.11 11.82 13.71 12.15 13.6
Interest rate 24.11 15.05 16.77 9.13 9.77 7.67 5.52
Average tariff rate tariff rate capital goods
tariff rate consumer goods
19.54 21.22 10.4 5.29 5.4 4.84 2.76
10.53 6.32 3.94 0.67 0.88 1.37 1.23
26.53 22.75 18.42 9.15 8.93 11.37 3.85
Trade openness
(% of GDP) 60.8 73.96 98.662 102.435 94.941 71.419 60.573
Import tax revenue
(% of imports) 80.872 46.134 21.449 17.473 15.78 15.012 12.142
Source: Asian Development Bank (ADB) and World Development Indicators (World Bank)
0
10
20
30
40
50
60
1996 2000 2004 2008 2012
control of corruption
govt. effectiveness
political stability
regulatory quality
rule of law
voice & accountability
0
100
200
1990 1994 1998 2002 2006 2010 2014
portfolio assets & liabilities
FDI assets & liabilities
debt assets & liabilities
Chapter # 3 An Over View of Selected Developing Countries
123
3.1.10 Mexico:
Mexican economy grew at an annual rate of 2.5 % through 2015 and 2016. Government
has improved the country's macroeconomic fundamentals since the 1994 crisis. Mexico
was most affected by the 2008 recession relative to other Latin American nations with a
6% decline in the GDP growth.
Since 1998 exchanged rate has remained stable under the reforms commenced after the
1994 peso crisis. The tax revenue is also lowest at 19.6 percent of GDP in 2013 among the
34 OECD countries29
. Human development index of Mexico was reported at 0.75, ranked
74th in the world, within the group of high-development according to 2014 estimates.
Services sector contribution to GDP is 60% followed by the industrial sector at 37%
according to 2013 estimates. Trade liberalization has improved the industrial sector.
Automotive industry is among the major industrial manufacturers, whose quality standard
is internationally recognized. The electronics industry of Mexico ranks sixth largest in the
world after China, Japan, Taiwan, South Korea and United States. Many foreign firms
have business set up in Mexico such as Phillips, Vizio and LG.
The financial sector is dominated by either foreign firms or mergers. The process of
institution building in the financial sector has developed with the efforts of financial
liberalization and integration. After the 1994–95 financial crisis Mexico’s monetary policy
was reconsidered, price stability was set as the main goal of monetary policy to sustained
growth.
More than 90% of Mexican trade is under free trade agreements. Remittances are the
largest source of foreign income. Tourism is an important industry and a largest source of
foreign exchange earnings.
29
Mexico Overview - World Bank, Mexico Economic Review.
Chapter # 3 An Over View of Selected Developing Countries
124
Figure 3.19 Governance indictors (percentile score):
Source: World Governance Indicators (World Bank)
Figure 3.20 Indicators of financial liberalization (% of GDP):
Source: Lane and Ferretti (2007)
Table 3.11 Indicators of fiscal and monetary policy and trade liberalization
Variables 1990 1994 1998 2002 2006 2010 2014 Govt. expenditures
(% of GDP) Current expenditures
Capital expenditures
18.82 15.92 16.71 17.59 13.58 14.59 15.7
14.38 12.52 11.59 11.47 10.5 11.66 12.28
4.44 3.4 5.12 6.12 3.08 2.93 3.42
Tax revenue
(% of GDP) 12.01 11.9 12.23 15.84 16.46 14.63 16.95
Interest rate 22.56 19.3 26.35 8.21 7.51 5.28 3.55
Average tariff rate tariff rate capital goods
tariff rate consumer goods
14.78 13.57 14.72 15.29 8.04 7.73 6.5
20.65 7.56 10.22 3.91 1.74 1.58 1.23
18.56 10.74 16.11 6.49 3.81 8.47 9.56
Trade openness
(% of GDP) 38.306 29.297 51.776 48.371 56.362 60.947 66.394
Import tax revenue
(% of imports) 33.722 18.475 7.616 4.17 2.19 1.169 1.006
Source: Asian Development Bank (ADB) and World Development Indicators (World Bank)
0
10
20
30
40
50
60
70
1996 2000 2004 2008 2012
controll of corruption
govt. effectiveness
political stability
regulatory quality
rule of law
voice & accountability
0
50
100
1990 1994 1998 2002 2006 20102014
portfolio assets & liabilities
FDI assets & liabilities
debt assets & liabilities
Chapter # 3 An Over View of Selected Developing Countries
125
3.1.11 Brazil:
Brazil is one of the ten largest markets in the world with a population of over 204 million
and abundant natural resources. With respect to nominal GDP Brazil has the world's
seventh largest economy. It’s a moderately free market and inward looking economy.
Brazil was regarded as one of the largest economy in the world based on growth rate
during 2000 to 2012 with a 5% average annual GDP growth rate. However in 2013
Brazil’s economic growth declined and also showed no liquid growth throughout 201430
.
Since the 1990s measures taken towards liberalizing the economy and fiscal sustainability
provided a better environment for private-sector development by boosting country's
competitiveness. Industrial sector constitutes a major sector of the economy. High foreign
direct investment is attracted by scientific and technological development, which has
averaged US$30 billion per year. Trade surplus also allowed for currency gains and
external debt pay down.
The contribution of the services sector to GDP is 76 percent while the share of the
industrial sector is 18.5 percent of GDP according to 2016 estimates. Out of total labour
force 66 percent is occupied in the service sector according to 2013 estimates. Brazil's
industries consist of automobiles, consumer durables, steel and petrochemicals, computers
and aircraft. Important sources of industrial raw materials and export earnings are large
iron and manganese reserves.
Under the liberalization program besides providing the local businesses Brazil's financial
sector is attracting several new entrants, including U.S. financial firms. To improve its
social security (retirement pensions) and tax system Brazil carried out reforms. Policies
were also formed to create windows of opportunity for local and international investors, to
encourage the exports, industry and trade. Administrative efficiency was also improved.
30
Brazil Overview - World Bank, Economic Survey of Brazil. CIA World Factbook.
Chapter # 3 An Over View of Selected Developing Countries
126
Brazil has reduced its vulnerability with these reforming efforts; domestic debt has
decreased and exports grew on average by 20% a year.
Figure 3.21 Governance indictors (percentile score):
Source: World Governance Indicators (World Bank)
Figure 3.22 Indicators of financial liberalization (% of GDP):
Source: Lane and Ferretti (2007)
Table 3.12 Indicators of fiscal and monetary policy and trade liberalization
Variables 1990 1994 1998 2002 2006 2010 2014 Govt. expenditures
(% of GDP) Current expenditures
Capital expenditures
24.19 26.21 21.82 22.59 26.75 25.89 26.96
19.29 17.63 19.89 19.67 18.81 19.01 20.19
4.9 8.58 1.93 2.92 7.94 6.88 6.77
Tax revenue
(% of GDP) 12.01 11.9 12.23 15.84 16.46 14.63 16.65
Interest rate 88 82 86.36 62.87 50.8 39.99 32
Average tariff rate tariff rate capital goods
tariff rate consumer goods
33.5 14.46 17.15 14.56 12.2 13.44 12.01
32.46 19.16 17.72 12.06 9.1 9.48 9.58
28.57 16.68 21.67 11.74 8.47 9.32 10.96
Trade openness
(% of GDP) 15.162 19.333 16.38 27.576 26.04 22.512 25.792
Import tax revenue
(% of imports) 10.155 7.176 5.281 4.016 1.575 1.171 0.992
Source: Asian Development Bank (ADB) and World Development Indicators (World Bank)
0
10
20
30
40
50
60
70
1996 2000 2004 2008 2012
control of corruption
govt. effectiveness
political stability
regulatory quality
rule of law
voice & accountability
0
20
40
60
80
1990 1994 1998 2002 2006 20102014
portfolio assets & liabilities
FDI assets & liabilities
debt assets & liabilities
Chapter # 3 An Over View of Selected Developing Countries
127
3.1.12 Kenya:
Kenya is considered a market-based and liberalized economy with a few state-owned
enterprises. Regarding financial, communication and transportation services Kenya is
usually considered as Eastern and central Africa's hub. Kenya had a GDP of $69.977
billion while Per capita GDP was estimated at $1,587 according to 2015 estimates31
.
Import substitution policy of Kenya made its manufacturing sector uncompetitive and
inefficient. Domestic environment for investment has been less attractive due to absence
of export inducements, foreign exchange controls and tight import controls. The
government of Kenya undertook a reform program in 1993 with the support of the World
Bank and the International Monetary Fund. Under this program a series of measures were
undertaken which include the removal of price and foreign exchange controls,
privatization of several public owned enterprises and introduction of conservative fiscal
and monetary policies.
Services sector of Kenya is dominated by tourism and contributes about 61 percent of
GDP according to 2015 estimates. Tourism sector faced downfall in late 1990s due to
security concerns, blasting of the U.S Embassy in Nairobi in 1998. After the service sector
the share of agriculture sector is largest in Kenya’s gross domestic product. Agriculture
accounted for about 24 percent of GDP and 50 percent of export revenue in 2005.
Manufacturing contributes only 14 percent of gross domestic product. The trade balance
fluctuates extensively because of major share of primary exports in total exports which
face unstable prices in the world market. Remittances by non-resident Kenyans are a
significant portion of Kenya's foreign inflows. For future economic growth vision 2030 is
Kenya's current program. The vision is divided into three different parts: economic, social
31
Kenya Overview - World Bank, Kenya Economic Outlook - African Development Bank.
Chapter # 3 An Over View of Selected Developing Countries
128
and institutional. The long-term goals of this vision are to move towards a successful and
globally competitive nation by the year 2030.
Figure 3.23 Governance indictors (percentile score):
Source: World Governance Indicators (World Bank)
Figure 3.24 Indicators of financial liberalization (% of GDP):
Source: Lane and Ferretti (2007)
Table 3.13 Indicators of fiscal and monetary policy and trade liberalization
Variables 1990 1994 1998 2002 2006 2010 2014 Govt. expenditures
(% of GDP) Current expenditures
Capital expenditures
18.69 19.58 18.36 18.98 17.21 18.04 19.96
13.64 15.15 16.25 17.08 14.35 14.16 14.01
5.05 4.43 2.11 1.9 2.86 3.88 5.95
Tax revenue
(% of GDP) 16.21 14.94 15.06 17.29 17.38 19.4 20.89
Interest rate 18.75 36.24 29.49 18.45 13.63 14.37 16.51
Average tariff rate tariff rate capital goods
tariff rate consumer goods
33.53 31.23 24.93 20.45 12.27 12.12 11.52
30.25 15.23 10.58 9.39 4.03 3.73 4.58
24.56 18.56 15.74 15.65 11.04 12.89 13.25
Trade openness
(% of GDP) 57.021 71.266 48.897 55.173 55.236 54.227 50.277
Import tax revenue
(% of imports) 25.659 17.722 17.127 14.592 3.124 2.125 1.2
Source: Asian Development Bank (ADB) and World Development Indicators (World Bank)
0
10
20
30
40
50
1996 2000 2004 2008 2012
control of corruption
govt. effectiveness
political stability
regulatory quality
rule of law
voice & accountability
0
20
40
60
80
1990 1994 1998 2002 2006 20102014
portfolio assets & liabilities
FDI assets & liabilities
debt assets & liabilities
Chapter # 3 An Over View of Selected Developing Countries
129
3.2 Dynamics of institutions and policies of selected countries:
We will discuss the characteristics of institution and policies of selected countries with the
help of country tables and graphs given in previous section. We will also discuss volatility
and cyclical behaviour of policies given in appendix IV and V respectively.
3.2.1 Institutional dynamics:
In previous section percentile score of each individual indicator of governance provides
the dynamics of governance in each country. Pakistan has highest score on government
effectiveness and least on political stability. India has highest score on voice and
accountability followed by rule of law and government effectiveness and least on political
stability. Bangladesh has highest score on voice and accountability and least on control of
corruption and political stability. Srilanka has highest score on rule of law followed by
control of corruption and regulatory quality where both have more or less same score
while political stability has least score. Maldives has highest score on political stability
then comes regulatory quality and government effectiveness both having same magnitude
and least on voice and accountability. Nepal has highest score on control of corruption
followed by rule of law and least on political stability. In Philippines government effective
has highest score followed by regulatory quality and voice and accountability both having
same magnitude and least on political stability. Thailand has highest score on government
effectiveness followed by regulatory quality and rule of law and least on political stability.
Vietnam has highest score on political stability followed by government effectiveness and
least on voice and accountability. Brazil has highest score on control of corruption
followed by regulatory quality and voice and accountability and least on political stability.
Mexico has highest score on regulatory quality followed by government effectiveness and
Chapter # 3 An Over View of Selected Developing Countries
130
least on political stability. Kenya has highest score on regulatory quality and lowest on
control of corruption and political stability.
3.2.1 Dynamics of stabilization policies:
Regarding the fiscal policy government expenditures show increasing trends in Maldives
and Vietnam while declining trends in Pakistan, Philippines and Srilanka. All other
countries show mixed trends. While the composition of government expenditures show
that current expenditures are greater than capital expenditures in all the countries, mainly
due to higher expenditures regarding security concerns worldwide and higher debt
servicing payment as developing countries are highly indebted etc., moreover total
government expenditures and current expenditures follow the same trends. In appendix IV
table IVA shows that government expenditures are less volatile in India, Bangladesh and
Mexico while more volatile in all other countries. In appendix V table VA shows that
government expenditures show the procyclical and acyclical behavior in Pakistan, Kenya,
Nepal, Thailand and Vietnam. Government expenditures show countercyclical behaviour
in all other countries. Countries with procyclical or acyclical expenditures show higher
volatility. Higher volatility in some countries with countercyclical expenditures shows the
effect of non-cyclical factors. Tax revenues show increasing trends in Nepal, Mexico,
Brazil and Kenya while declining trends in Srilanka, Pakistan and Philippines. All other
countries show mixed trends. Table IVB shows that tax revenues are less volatile in
Bangladesh while more volatile in all other countries. Table VB shows that tax revenues
are procyclical and acyclical in Brazil, India, Maldives, Mexico, Srilanka and Vietnam,
Bangladesh, Kenya, Pakistan, Philippines and Thailand while they show countercyclical
behaviour only in Nepal. Almost all the countries show the acyclical or procyclical
behavior along with higher volatility.
Chapter # 3 An Over View of Selected Developing Countries
131
Regarding the monetary policy interest rate shows declining trends in Brazil, India,
Philippines and Thailand while mixed trends in all other countries. In appendix IV table
IVC shows that interest rate is less volatile in all countries except Brazil. In appendix V
table VC shows that monetary policy shows procyclical and acyclical behaviour in
Bangladesh, India, Philippines, Thailand, Vietnam., Brazil, Kenya, Mexico, Nepal and
Srilanka while countercyclical behaviour in Maldives and Pakistan. Most of the countries
show acyclical or procyclical behavior along with less volatility therefore non-cyclical
factors are playing their role in reducing the volatility.
3.2.3 Dynamics of liberalization policies:
In previous section indicators of trade liberalization are represented by average tariff
rate, trade openness and import tax revenue. As a result of globalization average tariff rate
shows declining trends in all countries except Maldives where it shows mixed trends.
Composition of the tariff rate shows that tariff rate on consumer and capital goods both are
declining but tariff on consumer goods is greater than capital goods. Trade openness
shows that increasing trends in Bangladesh, India, Thailand, Mexico and Vietnam while
all other countries show mixed trends. Table IVD in appendix IV shows that trade flows
are less volatile in India, Bangladesh and Brazil while more volatile in all other countries.
In previous section indicators of capital account liberalization are represented by
portfolio assets and liabilities, FDI assets and liabilities and debt assets and liabilities.
Gross capital flows show increasing trends in India, Nepal, Pakistan, Maldives and Brazil
while other countries show mixed trends. Disaggregated data shows that in almost all the
countries debt flows are highest while in non-debt flows FDI flows are greater than
portfolio flows moreover portfolio flows show more swings and are considered more
volatile. FDI inflows show increasing trend, as a result of incentive provided by the
countries to foreign investors, in almost all countries except Vietnam, Philippines and
Chapter # 3 An Over View of Selected Developing Countries
132
Bangladesh where they show mixed trend. Table IVE in appendix IV shows that FDI
inflows are more volatile in Srilanka, Thailand, Vietnam and Philippines while less
volatile in all other countries. Table VD in appendix V shows that FDI inflows are counter
cyclical in Brazil, India, Srilanka and Thailand. They are procyclical and acyclical in
Kenya and Nepal, Bangladesh, Maldives, Mexico, Pakistan, Philippines and Vietnam.
Countries with acyclical or procyclical behavior are less volatile therefore non-cyclical
factors are playing their role in reducing volatility. Brazil and India show countercyclical
behavior along with less volatility while Srilanka and Thailand show higher volatility
along with countercyclical behavior therefore other factors are responsible for higher
volatility.
Portfolio inflows show increasing trend in Kenya, Nepal, India and Maldives and mixed
trends in other countries. Table IVF in appendix IV shows that portfolio inflows are more
volatile in Srilanka, Thailand, Philippines and Mexico while they are less volatile in all
other countries. Table VE in appendix V shows that portfolio inflows are countercyclical
in Brazil, India and Srilanka while they are procyclical and acyclical in Bangladesh,
Kenya, Mexico, Nepal and Vietnam, Maldives, Pakistan, Philippines and Thailand. In
most of the countries portfolio inflows show the acyclical or procyclical behavior but only
few shows the evidence of higher volatility therefore non-cyclical factors are important in
reducing the volatility. Brazil and India show the counter cyclical behaviour with less
volatility therefore cyclical fluctuations are source of volatility.
3.3 Institutional reforms in developing countries:
3.3.1 South Asia:
There are cultural and institutional resemblances in most South Asian countries due to
their common political past and history of colonial rule. There was an increased demand of
institutional reforms throughout South Asia during 1990s. The main intentions behind this
Chapter # 3 An Over View of Selected Developing Countries
133
demand include institutional reforms as a consequence of Asian crisis; the consolidation of
democracy in Bangladesh, Nepal and Pakistan; economic liberalization; the movement
toward decentralization, inefficient judicial system and massive administrative corruption.
World Bank has supported the South Asian governments to enhance the performance of
public institutions. Beside the Bank assistance the region has also commenced reforms.
There are three main objectives of the assistance for public institutional reform: public
sector reorientation, forming regulatory frameworks, reforming key government functions.
Reorienting the public sector:
In order to encourage the private sector South Asian governments have taken many steps
though, privatization process has been slow due to the resistance of vested interests.
Beside other institutional changes power sector reforms are notable. Many Indian states
have initiated reforms to privatize power sector with the Bank support. In Bangladesh also
the Bank has started efforts for the power sector reform while except this sector
privatization has also been commenced. Nepal, Pakistan, and Sri Lanka are making efforts
to encourage privatization to continue. Bank has supported the privatization process in
Srilanka beginning from tea estates and the national airline to the telecommunications. The
Bank has also provided the support to privatize the financial sector in Pakistan.
Privatization experience in Bangladesh has not remained very successful and Bank has to
be cancelled a large structural adjustment credit
Establishing regulatory frameworks:
To help the governments establish effective and appropriate regulation the Bank has given
considerable attention. With a poor regulatory framework privatization can be ineffective
causing abuses. South Asia’s banking system demonstrates the dangers of inadequate
regulation. Weak banking regulations and poor implementation has allowed undue loans
to be too high in Bangladesh and Nepal. In India, Pakistan, and Sri Lanka, improvement
Chapter # 3 An Over View of Selected Developing Countries
134
has also been made with Bank support. Bank is also assisting the sovereign regulations in
power, environment, water management and telecommunications.
Reforming key government functions:
Bank has made extensive efforts to improve key government functions including financial
systems and financial controls in many countries; civil service reform and tax
administration in Sri Lanka, Pakistan, Bangladesh and some Indian states. Bank has
provided the assistance through both structural adjustment loans and technical assistance.
3.3.2 East Asia and Pacific:
Before the economic crisis it was misconception that public institutions were working
efficiently in the region whereas crisis exposed institutional weaknesses. It also exposed
the poor management and regulatory practices of the financial sector. Beside the crisis
increased globalization has elevated the desire for responsible governance.
Before the crisis the Bank had focused mainly on stimulating public policy rather than
restructuring institutions. With the growing importance of the institutional agenda Bank
faces the challenge to assist the countries regarding institutional restructurings. These
reforms comprise four areas: financial sector management, reinforcing the administrative
and civil service, regulatory and legal improvement and governance and anticorruption
reforms.
Emerging market economies:
Indonesia, Korea, Malaysia, Philippines and Thailand are generally wealthier and more
competitive economies as compared to other countries of the region however, the crisis
has raised debt levels and deficits. These countries have common wide goals for
institutional transformation supported by the Bank. These include better fiscal
management to achieve the macroeconomic objectives, spending and debt management,
Chapter # 3 An Over View of Selected Developing Countries
135
improved service delivery to achieve long term development objectives and encouraging
the anti-poverty programs, struggle to reduce the opportunities for corruption through
deregulation, development of special watchdog agencies and resilient judicial system,
strong civil society institutions and last, decentralization.
To achieve these objectives the region is using both lending and non-lending sources. In
Indonesia, Korea and Thailand Technical assistance (TA) loans have stimulated an
institutional agenda. The Bank has also collaborated with other institutions in the region
for specific projects; with the UNDP, USAID and the Asia Foundation for anticorruption
reforms in the Philippines. To restructure the financial sector Bank has also worked
together with Asian Development Bank.
Small economies:
Bilateral donors play an important role in the resource transfers in the smaller economies
of the region (Cambodia, Laos, Mongolia, Papua New Guinea and Pacific Islands). In
smaller countries progress has been mixed. With steady implementation of reforms Fiji is
one of the countries that have tried to restructure its expenditures. Other countries of the
region, such as the Papua New Guinea and Laos, have made less improvement, as
inefficient governance has reversed wider reforms.
3.3.3 Latin America and Caribbean region:
In the 1980s with the consolidation of democracy, there was strong demand for change by
the civil society including higher transparency and accountability on the part of the
government. Beside this demand the debt crisis of 1980s, due to poor performance of most
governments, also initiated the need for reform by political leaders.
The Bank initiated institutional reforms in the early 1980s for fiscal adjustment and
economic liberalization. Bank provided assistance to many countries in the form of
Chapter # 3 An Over View of Selected Developing Countries
136
structural adjustment. By the late 1980s and early 1990s, Bank adopted a modernization
approach. The ultimate objective of this approach has been to enhance the efficiency of
financial system by implementing modern information technology. In enhancing the
efficiency of existing bureaucratic institutions these projects invested heavily on
modernizing the legal framework.
Considerable success of the economic stabilization programs in the 1990s led governments
to look for Bank assistance in new areas. Later in the mid-1990s, the Bank has initiated
judicial reform, decentralization and anticorruption efforts. Bank reforms also support
sectoral decentralization, provision of safety nets and social service delivery. Judicial
reforms help providing anticorruption measures by refining legal processes and discipline.
Moreover the Bank has initiated efforts to incorporate more participatory (voice)
approaches.
3.3.4 Sub Saharan Africa:
Africa has deep rooted institutional development problems. The high levels of aid
dependence that complemented reform weaken the capability of governments regarding
management of public spending. This institutional weakness was an already fragile basis
of accountability and legitimacy for many governments. In some countries rent-seeking
absorbed much of the energy of African elites at the cost of development measures.
In 1980s African region moved from investment-oriented development projects to policy
reform and adjustment lending. The region invested heavily on reform efforts of public
sector management. 70 of 102 civil service reform projects were in sub-Saharan Africa
between 1987 and 1997. But the experience of region regarding public sector management
has been uneven. During 1990s attention turned towards participation and building local
capacity. The public sector management program was accompanied by participation and
building local capacity.
Chapter # 3 An Over View of Selected Developing Countries
137
3.4 Concluding remarks:
We start this chapter by providing an overview of economies of selected countries on main
economic indicators; per capita growth, population growth, inflation rate, human
development and corruption perception. We compare their relative performance on these
indicators between 2000-2014. We conclude that percentage increase in per capita growth
was highest in Kenya, India stood next to Kenya. Percentage reduction in population
growth was highest in Thailand between these two periods. Percentage reduction in
inflation was highest in Mexico. Percentage increase in human development was highest
in Bangladesh and percentage reduction in corruption perception was also highest in
Bangladesh. Then we provide a snapshot of the economy of each country showing their
absolute position. We also provide a view of different indicators representing institutional
quality, stabilization and liberalization policies for selected countries which deliver the
dynamics of these variables. Regarding governance we conclude that among all the six
indicators the percentile score of political stability is lowest in all the countries except
Maldives and Vietnam where it is highest. Most of the countries have highest score on
regulatory quality and government effectiveness. Srilanka, Brazil and Nepal have highest
scores on control of corruption and rule of law while Bangladesh and Kenya have lowest
score on control of corruption. India and Bangladesh have highest scores on voice and
accountability while Maldives and Vietnam have lowest. Regarding stabilization policies
we conclude that government expenditures and revenue show increasing, declining and
mixed trends in different countries. Composition of government expenditures shows that
current expenditures are higher than capital expenditures in all countries mainly due to
higher expenditures regarding security concerns worldwide and higher debt servicing
payment as developing countries are highly indebted etc. Interest rate show declining and
mixed trends in different countries. Regarding trade liberalization average tariff rate and
Chapter # 3 An Over View of Selected Developing Countries
138
import tax revenue show declining trends in almost all countries as a result of
globalization, trade openness show increasing trends. Regarding capital account
liberalization FDI flows, portfolio flows and debt flows show increasing trends in some
countries while in some countries mixed trends. In most of the countries FDI inflows show
increasing trends as a result of incentives provided by countries to foreign investors.
Composition of capital flows show that debt flows are larger than non-debt flows. In non-
debt flows FDI flows are larger than portfolio flows moreover portfolio flows show more
swings and are considered more volatile. We have also discussed the volatility of fiscal,
monetary and liberalization indicators by calculating mean volatility for each country.
Similarly we have also discussed the cyclical behaviour of these indicators. In some
countries cyclical fluctuation are responsible for higher volatility while in others countries
non-cyclical factors are playing their role. At the end we provide a brief over view of
institutional reforms in developing countries by the World Bank. These include better
fiscal management to achieve the macroeconomic objectives, spending and debt
management, improved service delivery, struggle against corruption, privatization,
deregulation, strong judicial system, strong civil society institutions and decentralization.
139
Model Specification
This chapter derives the theoretical/empirical specification of growth model in first
section, second section provides the description of variables in detail, third section
describes the estimation methodology and the last section concludes the chapter.
4.1 Theoretical model:
Growth models are formulated into two main strands; Neoclassical models, whose bases
stem from Solow (1956), and other is endogenous growth models, initiated by Romer
(1989). Researchers traditionally focused on the former because of easy data availability
and cross country implications such as convergence. Neoclassical models assume constant
returns to scale and diminishing returns to capital. Countries reach their steady state in the
long run based on their exogenous steady state variables, population growth and savings.
There are several variants of neoclassical growth model (Cass 1965; Koopmans 1965). We
use the version of Neoclassical growth model that was empirically estimated and
augmented by Mankiw et al. (1992). Mankiw finds that adding the human capital results
in more reasonable factor shares and convergence. We use the same general empirical
methodology but make slight modification by adding institutional and policy variables, the
findings could be considerably different from those obtained by Mankiw et al. (1992). The
approach is very much comparable with the work of Barro and Sala-i- Martin (1991),
Islam (1995), Gundlach (2007), Freire-Seren (1999), Cellini (1997).
Chapter # 4
Chapter # 4 Model Specification
140
1
Following Mankiw et al. (1992) we use human capital augmented Cobb-Douglas
production function with constant returns to scale, where production in each period takes
place as follows;
Here K and H is the physical and human capital stock respectively in period t, AL is the
effective labour in period t, Y is output in period t while α and β are the coefficients
representing the elasticity or share of each input in output. We use Harrod neutral
technical progress where for a given capital output ratio the relative input shares remain
unchanged. Moreover the function exhibits diminishing returns to scale, allowing for the
steady state values to be constant. It is assumed that labour grows exogenously at constant
rate (n).
nt
t eLL )0(
“A” represents the economic and technological efficiency, the level of technological
progressed is assumed to grow exogenously at rate (g), X is a vector of variables
(institutions and policies) that represents the level of economic efficiency in the economy
and θ is the vector of coefficients associated to these variables.
P
m
mm Xgt
t eAA 1)0(
“A” in our study is different from Mankiw et al. (1992) and bears a resemblance to Erich
Gundlach (2007). “A” is assumed to grow for each country with the same constant rate (g)
over time [as in Menkiw, Romer and Weil (1992)] but at different levels determined by
several factors (Xm), like institutional framework of a country that differ considerably
across countries. A(0) stands for initial level of narrow concept of technology that is same
for all the countries and Xm may capture the factors that differ across countries but remain
)1()( 1 eqLAHKY ttttt
Chapter # 4 Model Specification
141
fairly stable over time (m=1………….p). For simplicity we take constant exogenous rate
of growth of technology (g) while the constant growth rate of labour (n) shows that when
new labour enters in the market at the same time some labour retires and leaves the market
(inflow and outflow of labor in the labour market).
Taking the production function in labour intensive form we get;
tt
tttt
tt
t
LA
LAHK
LA
Y
1)(
)2(eqhky ttt
Where ,tt
tt
LA
Yy ,
tt
tt
LA
Kk
tt
tt
LA
Hh
A fraction of output is saved which is spent on either the accumulation of physical and
human capital or consumption. The net increase in the stock of physical capital at a point
in time equals gross investment less depreciation.
ttt KIK .
KYsK tKt .
10 s
Here .
K denotes differentiation with respect to time. I is gross investment while δ shows
rate of depreciation, Ks is the share of capital in output. Dividing both sides of equation
by effective labour gives;
tt
t
tt
tK
tt
t
LA
K
LA
Ys
LA
K
.
ktk
tt
t ysLA
K
.
The right hand side represents per capita variables in order to convert left hand side in per
capita form we take derivative of AL
Kk with respect to time;
Chapter # 4 Model Specification
142
t
tt
ttttt kgn
LA
K
dt
LAKdk )(
)/(.
.
Where (n+g) is the growth rate of effective labour, substituting the value of AL
K.
from
previous equation gives the evolution of physical capital;
)3()(.
eqkgnysk ttkt
Growth rate of technology is assumed to be constant (g) as described earlier, in the same
way depreciation rate is also assumed to be constant, share of output to physical capital
(sk) is also constant.
In the same way as described above the evolution of human capital takes the following
form;
)4()(.
eqhgnysh ttht
hs shows the proportion of output devoted to human capital, δ shows the rate of
depreciation of human capital, n and g are described earlier. For simplicity we postulate
that both the physical and human capital depreciate at the same rate (δ).
Allocation of savings between physical and human capital depends on rates of returns of
both. As marginal productivity theory says that factors are paid according to their marginal
product. We will equate the marginal product of both capitals. First we calculate the
marginal product of physical capital by taking derivative of production function, in labour
intensive form, with respect to capital per effective worker.
As
ttt hky
tt hkMPk
1
t
t
k
yMPk .
In the same way marginal product of human capital is;
Chapter # 4 Model Specification
143
t
t
h
yMPh .
Rate of return to physical capital is t
t
k
y. while Rate of return to human capital is
t
t
h
y. .Equating the rate of return of both capitals;
tt kh
)(Aeqkh tt
The equality between both capitals shows one to one relation between them. This
relationship is used to calculate the steady state values of physical and human capital. We
write the equation of .
k again.
ttkt kgnysk )(.
kgnhksk ttkt )(
.
We use equation (A) to eliminate h from above equation.
tttkt kgnkksk )(.
t
k
httkt kgn
s
skksk )(
.
tthkt kgnkssk )(1
.
Steady state implies that 0.
k
thkt ksskgn
1)(
After solving for k we get steady state value of k;
)5(1
11
*
eqgn
ssk hk
t
In the same way steady state value of h will be;
t
t
t
t
h
y
k
y..
Chapter # 4 Model Specification
144
)6(1
11*
eqgn
ssh hk
t
Substituting steady state values of k and h into the production function we get;
1
111
11
gn
ss
gn
ssy hkhk
t
After simplifying the above equation we get;
1
11
)(
)()(
gn
ssy hk
t
We get the equation of income per capita as follows;
)7(
)(
)()(
1
11*
eq
gn
ssAy hk
t
Where t
tt
L
Yy *
By taking logs we get
)ln(1
)ln(1
)ln(1
lnln*
gnssAy hktt
m
P
m
mtt XgAA
1
0lnln
)8()ln(1
)ln(1
)ln(1
lnln1
0
*
eqgnssXgAy hkm
P
m
mtt
To find the convergence around the steady state we need the growth rate of physical and
human capital.
)9()(1
.
eqgnhksk
kttk
t
t
ttt hky
Chapter # 4 Model Specification
145
Log linearization of above equation implies;
In the same way we get the log linear equation of human capital;
)11()(ln)1(ln
.
eqgneesh
h hk
h
t
t
The growth rate of y is a weighted average of the growth rate of the two inputs;
t
t
t
t
t
t
h
h
k
k
y
y...
If we use log linear equations of physical and human capital and take a two dimensional
first order Taylor series expansion we get;
)ln)]](ln1([[
)ln](ln)]1([[
*ln)1(lnlnln)1(
*ln)1(lnlnln)1(
.
****
****
tt
hk
h
hk
k
tt
hk
h
hk
k
t
t
hheesees
kkeeseesy
y
At the steady state **
lnln)1( hk
k ees and **
ln)1(ln hk
h ees is equal to gn with the
assumption that rate of depreciation is same for both types of capital and k is closer to *
k
and similarly h is closer to*
h .
)12()ln(ln*
.
eqyyy
yttt
t
t
))(1( gn
or
)ln(lnln *
.
tt
t
tt yyy
y
dt
yd
)]ln(ln)ln(ln)[)(1(**
.
tttt
t
t hhkkgny
y
)10()(lnln)1(
.
eqgneesk
k hk
k
t
t
Chapter # 4 Model Specification
146
Here λ is the convergence coefficient which shows the speed of convergence to the steady
state.
If we integrate above differential equation with respect to time from t0 to t1 we get;
)13()(lnln)1(ln 0
*
eqyeyey tt
t
Subtracting lny0 from both sides
00
*
0 ln)(lnln)1(lnln yyeyeyy tt
t
)14()ln)(ln1(lnln 0
*
0 eqyyeyy t
t
0
1
0
0
ln
)ln(1
)ln(1
)ln(1
ln)1(lnln
y
gnssXgAeyy
hkm
P
m
mtt
t
Formally our empirical specification, for the i-th country in the t-th period, for the panel
data can be written in the reduced form as under;
)15(ln11
110 eqZcXbyaagy itititj
q
j
jitm
p
m
mitit
Where gy is the growth rate of GDP per capita of ith country at time (t) and yt-1 is the
lagged value of GDP per capita, Xm shows vector of institutions and policies, Zj is a vector
of control variables; physical capital, human capital and population growth. Equation
shows that growth rate of GDP per capita is determined by physical and human capital,
population growth, initial level of GDP per capita and vector of institutions and policies
determined by “A”. Above equation is the basic empirical specification of the model.
εit is the error term with constant variance and zero mean while νi and µt represent both
country and time specific factors. They represent unobserved characteristics that are either
country specific and time invariant (e.g. geography, culture, religion, language, distance
etc.) or time specific and country invariant (e.g. global economic cycles).
Chapter # 4 Model Specification
147
We can further expand/explain last equation according to our objectives, as our first
objective is to assess the effect of policies (both stabilization and liberalization policies)
and institutions on economic growth so we will estimate the above equation directly or we
can further explain the equation as follows;
)15(ln 111
1
21110 aeqZcPbIQbyaagyitititj
q
j
jitititit
Here Zj includes vector of traditional or control variables (physical capital, human capital
and population growth). Our first objective will provide us the empirical significance of
alternative policies and institutions in economic growth.
Regarding our second objective we will analyze the effect of policy volatility on economic
growth. As there is problem of policy volatility, uncertainty or policy switching in
developing countries that lead to lower rates of investment and economic growth by
causing uncertainty to investors both foreign and domestic (Fatas and Mihov, 2008;
Aizenman and Marion, 1991; Sirimaneetham Vatcharin, 2006).
)15(ln 222
1
43132 beqVdPVbIQbyaagyitititn
r
n
nitititit
Here Vn includes traditional factors of production; physical capital, human capital and
population growth and some external factors (foreign growth volatility, term of trade
volatility and foreign interest rate volatility).
Given the importance of institutions our last objective is to empirically investigate the
effect of institutions on policy volatility as better institutions reduce the policy volatility
by putting constraints on the policy makers (Henisz, 2004; Albuquerque Bruno, 2010;
Agnello and Sousa, 2014).
)15(333
1
5154 ceqWfIQbPVaaPVititits
v
s
sititit
Chapter # 4 Model Specification
148
Here Ws consist of control variables inflation volatility representing macroeconomic
volatility, GDP per capita representing level of development of a country, previous
period’s debt, exchange rate volatility, export concentration, financial development and
some external factors which include foreign growth volatility, term of trade volatility and
foreign interest rate volatility.
4.2 Description of variables:
4.2.1 Economic Growth (GDP per capita growth):
Economic growth is represented by annual percentage growth rate of real GDP per capita
based on current U.S. dollars. There are many studies in the literature that use growth of
output per capita to represent the economic growth, Kappler (2004), Islam (1995), Mankiw
et al. (1992), Zhang (2001), Dalgaard and Strulik (2013), Aiello and Scoppa (2007), Li
and Zhou (2011), Ali (2002). Data is collected from World Development Indicators
(WDI).
4.2.2 Initial GDP per capita (Convergence):
It is one of the key implications of the Neoclassical growth model that growth rate is
influenced by the initial condition of the economy. Higher the distance from the steady
state higher will be speed of convergence and hence higher the growth. The rationale
behind is that poor countries have the capability to grow faster than rich ones due to the
proposition of diminishing returns. Absolute or unconditional convergence hypothesis
states that assuming same economic characteristics of economies the lower the initial
income the higher will be the growth rate whereas conditional convergence accounts for
heterogeneity across countries. It allows countries to converge not towards a common
steady state but towards their own steady state. We control for the initial state of the
economy by including the level of real per capita GDP in previous period.
Chapter # 4 Model Specification
149
4.2.3 Capital stock (% of GDP):
Capital stock represented by gross fixed capital formation comprises expenditures on
additions to the fixed assets of the economy. Gross fixed capital formation is commonly
used in empirical studies, Kappler (2004), Mankiw et al. (1992), Bassanini et al. (2001),
Ali (2002), Gundlach (2007), Dalgaard and Strulik (2013). Data is collected from World
Development Indicators (WDI).
4.2.4 Human capital:
Human capital represents all the knowledge, talents, skills, abilities, experience,
intelligence and training possessed individually and collectively by individuals in an
economy. To account for differences in human capital we have used human capital index
per person, which uses the data on the average years of schooling (primary, secondary and
tertiary) from Barro and Lee (2010) and rates of return for completing different sets of
years of education (primary, secondary and tertiary) by Psacharopoulos (1994). Data is
collected from Pen World Table (8.0) given for 135 countries.
4.2.5 Population growth:
It represents annual population growth rate (15-64). It include all residents irrespective of
legal status excluding refugees not invariably settled and are generally regarded as part of
the population of the source country. Data is collected from World Development
Indicators (WDI).
4.2.6 Stabilization policies:
Stabilization policies are macroeconomic policies executed by the government and central
banks in order to keep economic growth stable along with price stability. There are two
common devices available to stabilize the economy: fiscal and monetary policy. Fiscal
policy is the policy of central government concerning outlays and taxation. Monetary
Chapter # 4 Model Specification
150
policy is the policy of the central bank to control money supply and interest rate within the
parameters of monetary policy.
4.2.6.1 Government expenditures (% of GDP):
It includes both the current and capital expenditures of the central government.
Consumption expenditure consist of all government current expenditures for the provision
of goods and services, reward to employees (wages and salaries), interest and subsidies,
grants, social benefits, defence and other outlays such as rent and dividends. Capital
expenditures include expenditures on additions to the fixed assets of the economy for
future benefits such as expenditures on physical and social infrastructure etc. We have
used both the aggregated and disaggregated expenditures. Data is collected from Asian
Development Bank (ADB).
4.2.6.2 Tax revenue (% of GDP):
Tax revenue denotes necessary transfers to the central government for public purposes
from both the direct and indirect sources. Direct taxes comprise income, profits and capital
taxes (as a liability to individuals and enterprises) whereas indirect taxes comprise taxes
on goods and services (general taxes, sales tax, value added taxes), excise duties, taxes on
trade (custom and other import duties, taxes on exports) etc. Data is collected from Asian
Development Bank (ADB).
4.2.6.3 Interest rate:
Interest rate is represented by lending rate, the rate that fulfills the short and medium term
financing needs of the private sector. Data is collected from World Development
Indicators (WDI).
4.2.7 Liberalization Policies:
Economic liberalization refers to the reduction of government regulations and restraints to
encourage the contribution of the private sector in order to stimulate economic
Chapter # 4 Model Specification
151
development. Liberalization policies include larger labour market flexibility, fewer
restrictions on domestic and foreign capital, open markets, etc. In developing countries,
economic liberalization mentions to further opening up of their respective economies to
foreign capital and trade.
4.2.7.1 Trade liberalization:
Trade liberalization denotes fewer restrictions on trade in the form of tariff and non-tariff
barriers. There is no unified measure of trade liberalization, literature provides few
measures; average tariff rate, revenue collected from imports, trade openness as a common
measure and trade liberalization index by Sachs and Warner (1995)32
. Index is available
only from 1950-92 for 152 countries. Since, due to the unavailability of the index for
recent years we have used average tariff rate for all products subject to tariffs33
weighted
by the product import shares analogous to each partner country. We have also used
disaggregated measure of tariff for capital and consumer goods as most of the imports of
sample countries consist of these goods. Moreover we also have used trade openness as an
indicator of liberalization mostly used in the literature. Data of tariff rate is collected from
World Integrated Trade Solutions (WITS) given by the World Bank while the data of trade
openness is collected from World Development Indicators (WDI).
4.2.7.2 Financial liberalization:
Financial liberalization denotes to ease restrictions on capital flows across a country’s
borders by domestic residents and foreigners. There are two type of measures used for
financial liberalization in empirical literature; de-jure and de-facto measures. A traditional
approach to measure financial liberalization is De- jure measure, declaring to the legal
32 Sachs and Warner (1995) developed a measure of movement towards a liberal trade policy regime. 33 Capital goods, consumer goods, intermediate goods and raw material.
Chapter # 4 Model Specification
152
status of financial liberalization34
. All these measures are based on the information
available in the IMF's Annual Report on Exchange Arrangements and Exchange
Restrictions (AREAER). We use Chinn and Ito (2008) index35
, based on principal
component analysis an average measure of four binary indicators; multiple exchange rates,
current account, capital account and export proceeds from (AREAER). Data is available
from 1970 to recent for 182 countries. However, de jure measures are not true measure of
liberalization as they only capture the presence or absence of restrictions.
An alternative measure is the use of de facto approach which measures the actual openness
of financial market transactions. One of the most reliable data sources for de facto
measures of financial liberalization has been offered by Lane and Milesi-Feretti (2007).
They have computed the accumulated stock of foreign assets and liabilities as a percentage
of GDP for a broad sample of 178 countries from 1970 to recent. The composition of
international financial position is distinguished on the basis of foreign direct investment,
foreign portfolio investment, external debt (portfolio debt and other investments) and
others (financial derivative and total reserves minus gold)36
. We have also used net FDI
inflows being long term and stable flows while portfolio equity and debt inflows being
short term flows. Data is collected from World Development Indicators (WDI).
4.2.8 Institutional Quality:
The World Bank has collected the data for governance usually known as World
Governance Indicators (WGI). There are six compound measures representing wide
aspects of governance covering 215 countries from 1996 to recent; voice and
34 Chinn and Ito (2008), Quinn (1997), Schinlder (2009) etc. 35 It is a scale measure (0-1) of capital account openness; it takes value of one when capital account is fully liberalized
and zero with full restrictions on capital transactions.
36
For accounting framework see Lane and Milesi-Feretti (2007).
Chapter # 4 Model Specification
153
accountability, political stability and absence of violence, government effectiveness,
regulatory quality, rule of law and control of corruption. These indicators are based on
numerous indicators from different sources; survey respondents, business sector, public
and nonpublic sector organizations all over the world. Index ranges between (-2.5 weak) to
(2.5 strong). We can explain these broad dimensions as;
Voice and Accountability; is the degree to which the citizens have right to elect their own
government and representatives, and while media is free from censorship and enjoys
independence.
Political Stability and Absence of Violence; refers to the probability that a political
dispensation will be undermined by resort to violence or unlawful means.
Government Effectiveness; measures the capacity of an administration to ensure public
service delivery, conception and execution of a policy framework, and the evidence of
probity in such processes.
Regulatory Quality; looks at instances of comprehensive policy frameworks that
spearhead development and advancement of private sector enterprises.
Rule of Law; explains the prospects of reasonable and foreseeable rules and regulations
that will govern commercial and social exchanges such as enforcement of contracts,
protection of property rights, judicial processes, as well as the probability of wrongdoing
and violence.
Control of Corruption; refers to the impression generated by practices of abusing public
authority for private benefit.
We have used all the six indicators individually for a broader view and comprehensive
policy implication and also a single governance indicator by taking average of all.
We have also used data of institutional constraints as a measure of checks and balances on
the decision power of policy makers. Henisz (2002) provides a measure of political
Chapter # 4 Model Specification
154
constraint which measures the possibility of policy change using the number of
independent veto players. Data is collected from POLCONIII. Index ranges from 0 to 1,
where a higher score represents stronger constraints.
As a measure of monetary institutions we have used data on central bank independence.
Published data at annual frequency is available by Polillo and Guillen (2005) but with low
frequency and less country coverage. Therefore we have used governor turnover as an
indicator of central bank independence. It is a dummy variable where 1 is being assigned
to all those years where governor turnover is taking place (Cukierman et al. 1992, Dreher
et al. 2010, Haider et al. 2011). We have collected the information regarding the turnover
of the governor from the web site of each country’s central bank.
4.2.9 Inflation:
Inflation as measured by the consumer price index reveals the annual percentage change in
the price of attaining a basket of goods and services, such as yearly (base 2010=100). Data
is collected from World Development Indicators (WDI).
4.2.10 Exchange rate:
Official exchange rate denotes to the exchange rate that is determined by the legally
authorized exchange market. Usually it is the average of monthly exchange rate and
defined as the ratio of local currency units to the corresponding foreign currency (usually
US dollar). Data is collected from World Development Indicators (WDI).
4.2.11 Export concentration:
Export concentration refers to a limited export structure of a country where a lower range
of the goods is produced which is closely related. Most commonly used measure is
Herfindahl-Hirschmann Index. It is calculated by taking the square of export shares of all
export categories in the market. It varies between zero and one, index value nearer to 1
specifies that exports are highly concentrated on a few commodities whereas closer to 0
Chapter # 4 Model Specification
155
reflect less concentration. We use data from World Bank where export concentration is
measured through Herfindahl-Hirschmann Index. It includes the number of products
exported at the three-digit SITC, Rev. 3 level.
4.2.12 Financial development:
Financial development is usually defined as a process that makes improvement in quantity,
quality, and efficiency of financial intermediary services. Commonly used measure of
financial development in the literature is domestic credit to private sector by financial
institutions. It denotes to financial resources provided to the private sector by financial
institutions, such as loans, purchases of securities, trade credits and others, which create a
claim for repayment. Data is collected from World Development Indicators (WDI).
4.2.13 External debt stocks, long-term public sector (% of GDP):
Long-term external debt refers to debt that has maturity of more than one year and that is
payable to nonresidents by residents of a country. Data is collected from World
Development Indicators (WDI).
4.2.14 Volatility:
Volatility refers to the fluctuations in any economic activity, the pace at which the
economic activity moves up or down and how widely they swing. Less volatility shows
stability, it shows minor fluctuations/consistent behavior of economic variables. Higher
volatility is harmful for an economy which leads to instability.
There are different methods to measure volatility such as standard deviation of the residual
through an autoregressive process, conditional variance through ARCH and GARCH
model. ARCH and GARCH models are used with high frequency data mostly weekly and
monthly. Most widely used measure is standard deviation method with annual frequency.
The volatility of any variable can be measured by fitting a first-order autoregressive
process of the form:
Chapter # 4 Model Specification
156
ttt YY 110 )(
where α1 is the autoregressive parameter. The standard deviation of the residual (ε)
measures the volatility or the uncertainty associated with changes in variable “Y”. The
standard deviation measures the dispersion of a variable around its mean value.
Observations on a variable tend to be far away from the variable’s mean value if the
standard deviation is high while these clustered around the average value if standard
deviation is low.
4.2.15 External shocks:
Due to globalization and more integrated economies the extent of external shocks also
affects the domestic economy upon which they have little control. To capture the effect of
external shocks we have incorporated term of trade shock, fluctuations in foreign interest
rate and foreign growth rate. The Term of trade is calculated as the percentage ratio of the
export unit value index to the import unit value index, measured relative to the base year
(2010=100). For foreign growth we have used the data of US growth, being a major
trading partner of countries included in the sample. Data of term of trade index and US
growth is collected from World Development Indicators (WDI). For the foreign interest
rate we have used Federal Funds Rate, the rate banks claim each other to borrow funds,
data is collected from International Financial Statistics (IFS).
157
Table 4.1 Description of variables
variable description unit Source
Economic Growth The rate of change of real per capita GDP. Annual percentage World Development
Indicators (WDI).
convergence Previous period’s GDP per capita in logs. Current US dollars World Development
Indicators (WDI).
Capital stock
(private sector)
Gross fixed capital formation, entails expenditures on additions to the
fixed possessions of the economy by the private sector.
Percentage of GDP World Development
Indicators (WDI).
Human capital Human capital index per person, which uses the data on the average
years of schooling from Barro and Lee (2010) and rate of return to
education from Psacharopoulos (1994).
Index Pen World Table
(8.0)
Population growth Annual population growth rate (15-64). Rate of growth of population
from year t-1 to t, expressed as a percentage.
Annual percentage World Development
Indicators (WDI).
Inflation Annual percentage change in consumer price index (CPI) Index
2010=100
World Development
Indicators (WDI).
Real exchange rate Ratio of local currency units to the U.S. dollar deflated by price index of
both countries.
Index
World Development
Indicators (WDI).
Export
concentration
Export shares of all export categories in the market. Index (0-1) World Development
Indicators (WDI).
Financial
development
Domestic credit to private sector. Percentage of GDP World Development
Indicators (WDI).
External debt stock
(long-term public
sector)
Debt that has a maturity of more than one year and that is payable to
nonresidents by residents of a country.
Percentage of GDP World Development
Indicators (WDI).
Volatility Standard deviation of the residual of AR(1) process Own calculation
Stabilization policies (fiscal and monetary policy)
Government
expenditures
It includes all the current and capital expenditures of the central
government.
Percentage of GDP Asian Development
Bank (ADB).
Tax revenue Tax revenue denotes compulsory transfers to the central government for
public purposes from both the direct and indirect taxes.
Percentage of GDP Asian Development
Bank (ADB).
158
Interest rate Interest rate is represented by lending rate, rate that generally fulfills the
short and medium term financing requirements of the private sector.
Annual percentage World Development
Indicators (WDI).
Liberalization policies (trade and financial liberalization)
Average tariff rate Average tariff rate for all products. Annual percentage World Development
Indicators (WDI).
Trade openness Sum of exports and imports of goods and services measured as a share
of gross domestic product.
Percentage of GDP World Development
Indicators (WDI).
Financial
liberalization
(De jure measure)
Measure of restrictions on capital account. Index (0-1) Chinn and Ito
(2008)
Gross capital flows
(De facto measure)
Sum of gross inflows and outflows. Percentage of GDP Lane and Ferretti
(2007)
Institutional quality
Governance
Political
constraints
Central bank
independence
Six composite indicators of governance; voice and accountability,
political stability and absence of violence, government effectiveness,
regulatory quality, rule of law and control of corruption.
It measures the checks and balances on the policy makers.
It represents the governor turnover.
Index (-2.5 to 2.5)
Index (0-1).
A dummy variable
(0/1)
World Governance
Indicators (WGI)
POLCONIII.
External shocks
Term of trade
(TOT)
Percentage ratio of export prices to import prices Index
2010=100
World Development
Indicators (WDI).
Foreign growth
rate
Rate of change of real GDP of US Annual percentage World Development
Indicators (WDI).
Foreign interest
rate
US federal funds rate, the rate banks claim each other to borrow funds. Annual percentage International
Financial Statistics
(IFS)
Chapter # 4 Model Specification
159
4.3 Methodology:
The general regression equation that we will estimate for economic growth as described in
theoretical model eq (15) is the following;
)15(lnlnln11
1101eqZcXbyaayy itititj
q
j
jitm
p
m
mittiti
Here left hand side is the growth rate of GDP per capita of ith country at time (t) and yt-1 is
the lagged value of GDP per capita, Xm shows vector of institutions and policies, Zj is a
vector of traditional control variables. εit is the error term while νi and µt represent both
country and time specific factors. After accounting the time specific affects we can write
the above equation as;
)16(lnln11
110 eqZcXbyjay itiitj
q
j
jitm
p
m
mitti
There are some estimation concerns related to above regression equation. The first is the
existence of unobserved country-specific effects. Country specific effect combines factors
that influence the GDP per capita and are correlated with the explanatory variables. The
second is the possibility of most explanatory variables to be endogenous with economic
growth, so there is need to control for the biases resulting from simultaneity or reverse
causation. The last is to control for the econometric problems resulting from the inclusion
of the initial per capita GDP as an explanatory variable. The above concerns provide the
motivation for the use of econometric methodology in a dynamic model of panel data.
We use the generalized method of moments (GMM) established for dynamic models of
panel data, initiated by Holtz-Eakin, Newey and Rosen (1988), Arellano and Bond (1991),
and Arellano and Bover (1995). These estimators control the unobserved effects through
differencing. There is possibility of correlation between the levels variables and the
Chapter # 4 Model Specification
160
country specific effect (vi) in equation (16) while differencing eliminates this possibility.
This can be illustrated as:
)17()(
)(()ln(lnlnln
1
1
1
1
1
21101
eq
ZZcXXbyyjayy
itit
itjitj
q
j
jitmitm
p
m
mitittiti
There is need of instruments to handle the possible endogeneity of the explanatory
variables and the correlation of the new error term, 1 itit , with the lagged dependent
variable, 21 lnln itit yy . The instruments comprise preceding values of the explanatory
and lagged-dependent variables. Following the supposition that the error term, ε, is not
serially correlated and that the explanatory variables (X and Z) are weakly exogenous,
GMM dynamic panel estimator uses the following moment conditions:
Here s ≥2; t=3…….T
The GMM estimator based on the moment conditions described above (18a) and (18b) is
known as the difference estimator. For the level equation lagged differences of the
explanatory variables are used as instruments. It ensures that though there may be
correlation between the levels of explanatory variables and the country specific effect (vi)
in equation (16), there is no correlation between those variables in differences and the
country specific effect (vi). The moment conditions for the regression in level are;
The reliability of the GMM estimators depends on the validity of instruments/moment
conditions. We use two specification tests for this purpose, first is the Sargan test of over
identifying restrictions, which tests the validity of the instruments. We test the null
)18(0)([,0)([
)18(0)([ln
11
1
beqZEXE
aeqyE
ititsitititsit
ititsit
)19(10))([(0))([(
)19(10))([(
11
1
beqforsvZZandEvXXE
aeqforsvyyE
itisitsititisitsit
itisitsit
Chapter # 4 Model Specification
161
hypothesis that restrictions are valid against the alternative; rejection of the null shows the
presence of hetroskedasticity. This test is valid only for homoscedastic errors; rejection of
the null implies that we need to reconsider the model or instruments unless we attribute the
rejection of hetroskedasticity. The second test examines whether the original error term εit
(eq 16) is serially correlated. We test the null hypothesis of no second order serial
correlation against the alternative. The model is, therefore, supported when the null
hypothesis is not rejected. First-order serial correlation of the differenced error term is
expected even if the original error term (in levels) is uncorrelated. Serial correlation of
order higher than one implies that moment conditions used are not valid.
4.4 Concluding remarks:
In this chapter we have derived a dynamic panel data model to study the role of
institutions and policies in economic growth, following Mankiw et al. (1992), in the
empirics of Neoclassical growth model. Derived model shows the effect of institutions and
policies (stabilization and liberalization policies) on economic growth along with
traditional factors and convergence. Traditional determinants of growth are physical
capital, human capital and population growth. We have further manipulated the equation
according to our objectives.
Economic growth is measured by annual growth rate of GDP per capita. For physical
capital we have used gross fixed capital formation for private sector, for human capital we
have used human capital index per person which uses the data of average years of
schooling and rate of returns to schooling from Pen World Table (0.8), population growth
is measured by annual population growth from (15-64). To measure the convergence we
have used log of previous year’s GDP per capita.
Chapter # 4 Model Specification
162
For institutional quality we have used the data of World Bank, World Governance
Indicators, which defines governance in six broad dimensions; voice and accountability,
political stability and absence of violence, government effectiveness, regulatory quality,
rule of law and control of corruption. For stabilization policies we have used fiscal and
monetary policy. For fiscal indicator we have used total government expenditure and also
disaggregated current and capital expenditures and tax revenue, for monetary policy
indicator we have used interest rate as a policy variable. For liberalization policy we have
used trade liberalization and financial liberalization. For trade liberalization we have used
average tariff rate for all commodities and also disaggregated tariff rate for capital and
consumer goods. We have also used trade openness as an indicator of trade liberalization.
For financial liberalization we have used both the De jure (Chinn and Ito (2008) and De
facto measure (Milesi-Feretti (2007)). We have used these alternate measures of
stabilization and liberalization policies for comprehensive and broader policy implications.
Moreover we are also interested in analyzing the role of policy volatility in economic
growth and last, the factors affecting the policy volatility where we emphasize on the
importance of institutions in reducing the policy volatility.
The standard deviation of the residual of first-order autoregressive process measures the
volatility. Factors affecting the policy volatility are classified into some domestic and
global factors; domestic factors include macroeconomic volatility measured by inflation
volatility, level of development of a country (represented by GDP per capita), previous
period’s debt, exchange rate volatility, export concentration, financial development and
institutional quality and some global factors; foreign growth volatility, term of trade
volatility and foreign interest rate volatility. Inflation is measured through annual
percentage change in general price level using consumer price index. Debt shows long-
Chapter # 4 Model Specification
163
term public sector external debt. Exchange rate denotes to official exchange rate (ratio of
local currency units to US dollars). Financial development is measured through domestic
credit to the private sector. Export concentration is measured through Herfindahl-
Hirschmann Index. Foreign growth is measured by the growth rate of US GDP, Term of
trade (TOT) is represented by an index of export to import price ratio, foreign interest rate
is represented by US Federal Funds Rate.
Main sources of the data are the World Bank (World Development Indicators),
International Financial Statistics (IFS), Pen World Tables (8.0), Asian Development Bank
(ADB), World Governance Indicators (WGI), Chinn and Ito (2008) and Lane and Ferretti
(2007).
Next we discuss the methodology used; to control the unobserved country specific effects
and due to the possible endogeniety of explanatory variables with the growth we use
dynamic panel data GMM method of estimators initiated by Holtz-Eakin, Newey, and
Rosen (1988), Arellano and Bond (1991), and Arellano and Bover (1995). The
methodology consists of the level as well as differencing the equation to control for
country specific effects. For the level equation the lagged differences of the variables are
used as instruments whereas for differenced equation level of the preceding observations.
Last we explain two specification tests to check the reliability of GMM estimators; first is
the Sargan test of over identifying restrictions and second is the test of second order serial
correlation.
164
Results and Discussion
This chapter provides the empirical evidence of the model derived in previous chapter. We
estimate the model using panel data of twelve developing countries included in the sample
by GMM methodology. The objective is to analyze and explain the dynamics of
relationships. First of all we test the reliability of our data using summary statistics or
descriptive statistics. Next we see the relationships between variables through pair wise
correlation matrix. Last section provides the results of GMM. We estimate the equations
according to our objectives and discuss the results in detail with empirical support from
the literature.
5.1 Descriptive statistics:
Descriptive statistics provide an understanding and analysis of the data before estimation.
It tests the reliability of data both through numerical and graphical procedure by giving a
summary of the data. The main objective of data analysis is to draw valuable
conclusions from the data, which can further be used to make logical decisions.
Commonly used measures of data analysis are measures of central tendency and measures
of variability or dispersion. Mean, median and mode are used as a measure of central
tendency while measure of dispersion includes standard deviation, range, quartile,
derivative and mean derivative. Mean represents the average while median is the central
value and mode is the repeatedly occurring value. In case of normal distribution mean and
median are equal to each other showing the symmetry of data or no skewness. Standard
deviation is commonly used as a measure of dispersion or variability. If variation is small
standard deviation will be small, less variation shows consistency.
Chapter # 5
Chapter # 5 Results and Discussion
165
Table 5.1 Descriptive Statistics
Variable Mean Median Std. Dev.
Economic growth 3.137768 3.146415 3.302225
Income per capita 2.992272 2.73348 0.994312
Private capital stock 24.24362 22.945 6.239235
Human capital 2.178215 2.101236 0.455816
Population growth 2.14666 2.192232 0.860336
Institutional quality -0.372571 -0.355 0.573965
Government expenditures 20.22351 18.93862 6.11414
Tax Revenue 13.33183 13.505 3.37175
Interest rate 2.992272 2.73348 0.994312
Trade openness 66.77416 54.17934 41.58757
Average tariff rate 15.60543 14.17 7.820966
Gross capital flows 0.904347 0.840569 0.325011
External debt 25.01145 22.85242 13.38216
Financial development 31.41746 29.06498 22.84897
Inflation volatility 1.687431 1.603041 1.413896
Exchange rate volatility 1.29125 1.231465 0.917792
Export concentration 0.164004 0.163896 0.090217
Political constraints 0.506203 0.445961 0.416059
Foreign growth volatility 0.61892 0.504591 0.492058
Term of trade volatility 0.058762 0.05222 0.037583
Foreign interest rate volatility 0.035309 0.025603 0.034395
Results in the above table show that mean and median of almost all the variables is more
or less same which further provide the evidence of symmetry of data or no skewness.
Normal distribution is always symmetric. Moreover trade openness shows higher variation
as standard deviation of this variable is higher.
5.2 Pair wise correlation matrix:
Correlation explains the linear relationship between two variables; like correlation
between trade and growth, inflation and interest rate, interest rate and capital flows etc. it
does not show causality. It lies between -1 and +1, a positive value shows a direct
relationship between variables while negative value shows inverse relationship. -1 and +1
Chapter # 5 Results and Discussion
166
shows perfect negative or positive relationship while zero shows no relationship.
Coefficient closer to either -1 or +1 shows stronger correlation between two variables.
Table 5.2 Pair wise correlation matrix
Note: gy shows economic growth, PG represents population growth rate, H and K show human and physical
capital stock respectively. TE, CE and KE represent total government expenditures, current and capital
expenditures respectively. TR represents tax rate and R is interest rate. TO shows trade openness. TF, TFK
and TFC represent total tariff rate, tariff rate for capital and consumer goods respectively. GFC and FDI
show gross capital flows and net FDI inflows. IQ represents institutional quality.
Results of the correlation matrix show that population growth has weak negative
correlation with economic growth while human and physical capital both have positive
correlation with economic growth. Aggregate and current expenditures have negative
correlation with economic growth while capital expenditures and tax revenue are
positively correlated with economic growth. Interest rate is negatively correlated with
economic growth. Trade openness has positive correlation with economic growth while
tariff rate has negative correlation. Gross capital flows and net FDI inflows both show
positive correlation with economic growth. Institutional quality is also positively
correlated with economic growth. Results show that most of the relationships are
according to economic theory. Further there is evidence of high correlation between total
government expenditures and current expenditures. There is also high correlation between
gy PG H K TE CE KE TR R TO TF TFK TFC GCF FDI IQ
gy 1.00
PG -0.14 1.00
H 0.52 -0.48 1.00
K 0.48 -0.51 0.49 1.00
TE -0.34 0.10 0.03 -0.31 1.00
CE -0.38 0.07 0.15 -0.19 0.91 1.00
KE 0.24 0.11 -0.24 0.36 0.56 0.17 1.00
TR 0.39 -0.04 0.27 0.21 0.36 0.32 0.23 1.00
R -0.38 -0.01 0.05 -0.30 0.23 0.24 0.04 0.03 1.00
TO 0.31 -0.07 0.15 0.49 0.48 0.55 0.28 0.53 -0.33 1.00
TF -0.34 0.36 -0.51 -0.06 0.18 0.10 0.23 0.23 0.04 -0.15 1.00
TFK -0.36 0.43 -0.61 -0.08 0.26 0.13 -0.35 0.41 0.06 -0.15 0.79 1.00
TFC -0.44 0.33 -0.60 -0.01 0.00 -0.16 0.32 0.36 -0.08 -0.18 0.73 0.47 1.00
GCF 0.36 -0.16 0.35 0.27 0.53 0.52 0.03 0.44 -0.13 0.62 -0.29 -0.28 -0.37 1.00
FDI 0.39 -0.02 0.06 0.44 0.57 0.49 -0.40 0.48 0.05 0.78 0.00 0.06 -0.13 0.62 1.00
IQ 0.40 0.38 0.47 0.54 -0.10 0.13 0.00 0.01 0.17 0.11 0.14 0.02 -0.12 0.15 0.17 1.00
Chapter # 5 Results and Discussion
167
total tariff rate and tariff rate for consumer goods similarly a high correlation exists
between total tariff rate and tariff rate for capital goods. There is also evidence of high
correlation between trade openness and net FDI inflows.
5.3 Results of GMM:
5.3.1 Effect of institutions and policies on economic growth:
Our first objective is to analyze the effect of policies (both stabilization and liberalization
policies) and institutions in economic growth. We again write the equation here which we
have already explained in previous chapter in section 4.1 as follows;
)15(ln 111
1
21110 aeqZcPbIQbyaagyitititj
q
j
jitititit
Here Zj represents vector of traditional or control variables (physical capital, human capital
and population growth). IQ shows institutional quality while P represents policies, both
stabilization and liberalization policies. yt-1 is the lagged value of GDP per capita which
represents convergence. To represent institutional quality we have used the data of World
Bank which explains six dimensions of the governance, we have used the aggregate index
in this equation. The detail is mentioned in previous chapter section 4.2. For stabilization
policies we have used fiscal and monetary policy. We have used government expenditures
and tax revenue as indicators of fiscal policy while we have used interest rate as a
monetary policy instrument. For liberalization policies we have used trade liberalization
and financial liberalization. Trade liberalization is represented by trade openness index
and average tariff rate. To represent the financial liberalization we have used De- jure
measure [Chinn and Ito (2008)] and De facto measure, gross assets and liabilities as a
percentage of GDP [Milesi-Feretti (2007)]. Moreover we have also used net FDI inflows
as a long term and stable source of foreign capital flows.
Chapter # 5 Results and Discussion
168
Institutional quality is hypothesized to have a positive effect on economic growth by
providing an environment conducive to investment. We would test the null hypothesis that
institutional quality is unrelated to economic growth against the alternative. Regarding the
fiscal policy we would test the null hypothesis that fiscal policy does not contribute to
economic growth (Classical hypothesis) against the alternative (Keynesian hypothesis).
Regarding monetary policy we assume that it affects the economic growth through
aggregate demand, we would test the null hypothesis that monetary policy does not affect
economic growth (Keynesian hypothesis) against the alternative (Monetarist). Trade
liberalization is also assumed to have a positive effect on economic growth through
positive externality. We would test the null hypothesis that trade liberalization has no
association with economic growth against the alternative. Financial liberalization is
assumed to have a positive effect on economic growth by relaxing the borrowing
constraint and providing more investment opportunities while on the other hand there is
also opposing view that financial liberalization increases the risk of crisis in economies
where financial sector is week thereby reducing the growth. We would test the null
hypothesis of no association between financial liberalization and economic growth against
the alternatives. Physical and human capital both are hypothesized to have a positive effect
on economic growth while population growth is assumed to have a negative effect. It is
hypothesized that higher initial income reduces the steady state growth (convergence).
Estimation of this equation will provide the significance of institutions and alternative
policies in economic growth.
Chapter # 5 Results and Discussion
169
Table 5.3 Effect of institutions and policies on economic growth
Dependent variable: Economic growth variables Eq1 Eq2 Eq3 Convergence -.098229*
(0.002)
-.064413*
(0.000)
-.048807*
(0.011)
Private capital stock .1916751*
(0.012)
.0420228
(0.540)
.1415328**
(0.067)
Human capital 1.423672*
(0.050)
1.184211**
(0.065)
1.166283*
(0.021)
Population growth - .506445
(0.374)
-1.04926**
(0.067)
-1.954578 **
(0.083)
Institutional quality .25147*
(0.049)
.1269705**
(0.081)
.1928122**
(0.063)
Stabilization policies ( Fiscal and monetary policy) Aggregate govt. expenditures -.2308414*
(0.043)
Current expenditures -.1467202**
(0.062)
Capital expenditures .3285581*
(0.031)
Tax revenue
.0930385*
(0.044)
Interest rate -.1040991*
(0.023)
-.1353151*
(0.007)
Liberalization policies ( Trade and financial liberalization) Trade openness .1138372*
(0.042)
Tariff rate total - .1834675*
(0.020)
Tariff rate consumer goods -.0346299
(0.329)
Tariff rate capital goods -.2844151*
(0.014)
Financial liberalization
(De jure measure)
-.126968**
(0.075)
Gross capital flows
(De facto measure)
-.344006*
(0.043)
Net FDI inflows .626968*
(0.025)
Portfolio inflows
(equity and debt securities)
-0.0869**
(0.06718)
constant .0666723
(0.993)
17.3845*
(0.016)
-3.591562
(0.619)
No. of countries 12 12 12
No. of observations 210 210 210
Wald chi2(prob) 0.0000 0.0000 0.0014
Sargan (prob. chi2) 0.2577 0.2267 0.2240
AR1(prob. Z)
AR2(prob. Z)
0.0197
0.1202
0.0911
0.1918
0.0010
0.1403
Note: Values in the parentheses show the probability of „Z‟ statistics. * shows the significance at 1% and 5
% level of significance while ** shows the significance at 10 %. Wald test check the joint significance of the
model, Sargan test checks the reliability of instruments while AR test checks the presence of autocorrelation.
Chapter # 5 Results and Discussion
170
Convergence:
We have described the concept of convergence as one of the key implications of the
Neoclassical growth model in previous chapter in section 4.2. Following the Neoclassical
tradition many researchers have tested the convergence hypothesis using different
methodologies, sample and data sets and some studies have strongly rejected the
hypothesis and some have accepted. According to Mankiw (1995) most of the studies
show estimates of speed of convergence around 2%. The consistency of 2% reflects same
economic structures across countries while in reality economic structures vary across the
countries and hence cannot be the source or 2 % uniformity. As the level of technology is
assumed to be constant among countries in cross section estimates, so these estimates of
rate of convergence are considered biased [Islam (1995)]. Owing to the technological
differences across countries researchers adopted a panel data approach providing different
estimates from cross country estimates because economies are supposed to converge more
quickly towards their own steady state than to common one.
Our results show that initial GDP is inversely related to economic growth in all the
equations providing the proof of conditional convergence. Speed of convergence lies
between 5% to 10%; in first equation speed of convergence is 10%, in second equation 6%
and 5% 37
in last equation. Our results are consistent with previous economic literature.
Conditional convergence estimates by Islam (1995) for OECD and non-oil countries
ranges from 4.6% to 10.7%, Caselli, Esquivel and Lefort (1996) replicate the previous
models using cross country and panel data and provide the estimates of rate of
convergence between 2% to 10%, Edwards (1991) provide the estimates from 5% to 17%
in different specifications in a cross section of developing countries. McLean and Shrestha
(2002) provide the estimates for developed and developing countries from 4% to 6%. Li et
37
Speed of convergence is calculated as λ = - ln (1+ coefficient of initial GDP).
Chapter # 5 Results and Discussion
171
al. (2016) provide estimates of conditional convergence for 120 world economies with the
speed ranging from 0.03 percent to 22 percent. Speed of convergence for Europe is 22 %,
Asia 25 %, Latin America 23 % while there is evidence of no convergence for Africa.
Mathur (2005) measures the speed of conditional convergence for EU, East Asian and
South Asian regions together and there is evidence of conditional convergence from 0.2 %
in a year to 22%.
Traditional determinants of growth (Human capital, physical capital and population
growth):
In the theoretical literature the role of human capital has been extensively analyzed. The
literature identifies the role of human capital in economic growth in two ways; human
capital can directly affect the growth by including in production function as an additional
factor and secondly human capital indirectly affect the economic growth through
technological progress. Mankiw, Romer and Weil (1992) develop an extension of the
Solow growth by human capital augmented growth model.
We have used human capital index which uses the data on the average years of schooling
and rates of return to schooling, which we have discussed in detail in description of
variables. Higher the average years of schooling and rate of returns to schooling higher
the accumulation of human capital and therefore the economic growth. Results show that a
1 % increase in human capital index leads to an increase in economic growth by 1.424%,
1.18% and 1.16% respectively. Our findings have empirical support such as Levine and
Renelt (1992), Islam (1995), Harrison and Hanson (1999), Freire-Seren (1999), Bosworth
and Collins (2003), Chang et al. (2009) and Falvey et al. (2013) find a significant role of
human capital in economic growth by using different indicators.
Investment in physical capital is considered an important factor of economic growth in
the neoclassical growth model with the assumption of diminishing returns. An increase in
Chapter # 5 Results and Discussion
172
the physical capital stock (plant, machinery, and infrastructure investment) enhances the
economic activities and hence economic growth through increase in productivity,
employment opportunities, scale economies and by raising the overall welfare of
countries. Our Results show that a 1% increase in private investment increases the
economic growth by 0.19%, and 0.14% respectively. Our results follow the empirical
literature such as Edwards (1989, 1991), Levine and Renelt (1992), Harrison and Hanson
(1999), Freire-Seren (1999), Greenaway et al. (2002), Bosworth and Collins (2003) and
Falvey et al. (2013).
Higher population growth reduces the per capita growth as both have inverse
relationship. In two equations coefficient of population growth is negative and significant
(-1.04 and -1.95) respectively while in first equation this variable is insignificant. Our
findings are in line with Mankiw, Romer and Weil (1992), Levine and Renelt (1992),
Greenaway et al. (2002), Bosworth and Collins (2003), Salinas et al. (2006), Falvey et al.
(2013).
Institutional quality:
Most of the literature provides the evidence that institutions promote the economic growth
by creating an environment for capital creation. They reduce the risk of doing the business
thereby increasing the investment return. Some studies highlight the role of institutions in
attracting the capital flows particularly FDI and portfolio investment. In the same way
institutions play a significant role in attracting the aid flows. Control of corruption,
secured property rights and the rule of law all enhance the economic growth. Poor
institutions impede the economic growth by reducing economic activity and also induce
lower investment returns
Our findings are consistent with the earlier studies that institutional quality positively
affects the economic growth. In the first equation a 1% increase in institutional quality
Chapter # 5 Results and Discussion
173
increases the economic growth by 0.25 %. Second equation shows that a 1 % increase in
institutional quality increases the economic growth by 0.12%. Last equation shows that a 1
% increase in institutional quality promotes the economic growth by 0.19%. Our findings
have support of the empirical literature. Kaufmann et al. (1999) and Al Bassam (2013)
explain that better governance leads to growth and development. Chong et al. (2004) and
Fayissa et al. (2013) conclude that all the aggregated and disaggregated measures of
institutional quality positively contribute to economic growth. Siddique and Ahmed (2010)
provide the evidence of long run relationship between institutions and economic growth.
Ahmad and Marwan (2012) illustrate that property right protection appears the most
important institutional measure in affecting the economic growth.
Fiscal policy:
Regarding the fiscal policy and growth association there is extensive empirical research
using different fiscal measures, using cross-sectional, panel, and time-series methods. The
existing empirical findings are mixed regarding the role of fiscal policy, either positive,
negative or indeterminate. Supporters of government intervention believe that such
intervention can increase the long term growth by productive investment, law and order,
provision of public goods and services, research and development both in the short- and
long-run Opponents hold the view that government brings inefficiency and therefore
reduce the growth.
For fiscal policy we have used aggregate and disaggregate government expenditure,
current and capital expenditures. Moreover we have also used tax revenue as an indicator
of fiscal policy (revenue includes from both the direct and indirect sources). Our results
show that aggregate government expenditures negatively affect the economic growth with
a coefficient (-0.230). Capital expenditures positively contribute to economic growth with
a coefficient (0.328) while current expenditures adversely affect the economic growth with
Chapter # 5 Results and Discussion
174
a coefficient (-0.146). Tax revenue positively affects the economic growth as suggested by
the literature, with a coefficient (0.093). Our finding are supported by empirical literature
as Barro (1990) and Gallo and Sagales (2011) find that government investment raises the
growth while government consumption brings distortions, such as high tax rates, without
providing a stimulus to investment and growth. Easterly and Rebelo (1993) provide the
evidence that government investment expenditure on transportation and communication
enhance economic growth by raising the return to private investment. Gupta et al. (2002)
illustrate that expenditures on wages and salaries are negatively related to economic
growth while expenditures on other goods and services and capital expenditures foster the
growth. Kukk Kalle (2007) explains that current expenditures are inversely related to
economic growth while investment expenditures are directly related. Moreover spending
on employees, consumption spending or social benefits and interest spending are
negatively related to economic growth. Ali and Ahmad (2010) explain that the
unproductive expenditures become the main cause of persistent deficit in Pakistan.
Ormaechea and Morozumi (2013) find that increase in capital spending financed through
reduction in current spending is positively associated with economic growth. Engen and
Skinner (1992) and Guseh (1997) provide the evidence that government size reduces the
economic growth.
Regarding the tax and tax revenue Easterly and Rebelo (1993), Kukk Kalle (2007), Gallo
and Sagales (2011), Acosta Ormaechea and Yoo (2012) provide the evidence that tax
revenue positively contribute to economic growth while the disaggregated analysis show
that in developing countries indirect taxes positively contribute to economic growth while
direct taxes specifically income tax reduce the economic growth.
Our findings are in contrast to some studies such as Sattar (1993) find that government
consumption expenditures positively contribute to economic growth for Asian developing
Chapter # 5 Results and Discussion
175
countries therefore efficiency enhancing role of government outweighs the efficiency
reducing role. Devarajan et al. (1996) find positive relationship between current
expenditures and economic growth, negative relationship between capital expenditures
and economic growth. Gong and Zou (2002) find that current expenditures positively
contribute to economic growth while capital expenditures remain insignificant. He further
explains that higher infrastructure spending may deteriorate the economic growth if
spending on basic economic services is ignored. Gangal and Gupta (2013) and Morozumi
and Veiga (2014) find that aggregate public expenditures are positively associated with
economic growth.
Monetary policy:
Conventionally monetary policy affects the real economy through aggregate demand. The
interest rate is regarded as a most important transmission channel. Higher interest rate
decreases the consumption expenditures by increasing the opportunity cost of
consumption. In the same way it also reduces the investment expenditures by the firms by
raising the cost of capital. It leads to decrease the aggregate demand in both cases which
decreases economic growth.
Findings show that monetary policy does affect the economic growth therefore supporting
the Monetarists hypothesis. An increase in interest rate, a tight monetary policy, reduces
the economic growth by 0.10% and 0.13% respectively. Results of our study are in line
with earlier studies that provide the evidence of an inverse relationship between interest
rate and the growth. Fatima and Iqbal (2003), Ali et al. (2008), Hussain and Siddiqi (2012)
and Younus (2013) explain that in case of developing countries monetary policy is
effective in enhancing the economic activity. Gul et al. (2012), Coric et al. (2012) and
Kandil (2014) explain that contractionary monetary policy is negatively associated to
economic growth by discouraging the private investment.
Chapter # 5 Results and Discussion
176
In contrast to our findings Cheng (2006) and Buigut (2009) explain that monetary policy
remains insignificant in African countries due to underdeveloped financial and regulatory
framework. It is also argued that a lower interest rate policy in developing countries
encourages the unproductive investment in luxury consumer goods, real estate and gold
rather than on fixed capital goods having no effect on real activity.
Trade liberalization:
Trade liberalization affects economic growth through various channels. It creates more
employment opportunities by expanding the market size, provides benefits of economies
of scale and better resource allocation, technological spillover, increases variety, increases
international competitiveness through elimination of government trading monopolies,
provides the consumers the access to cheaper commodities and also enables firms to get
access to cheaper inputs by expanding the market for their output. Many developing
countries adopted import-substitution policy in the 1970s but this inward oriented policy
proved to be inefficient and caused a shift from inward oriented policy towards outward
oriented.
As a measure of trade liberalization we have used average tariff rate38
. We have also used
the tariff rate for capital and consumer goods separately for a comprehensive policy
implication39
. Additionally as a traditional measure of trade liberalization we have also
used trade openness. Results show that trade liberalization boost the economic growth as a
1% reduction in average tariff rate increases the economic growth by 0.18 % points.
Moreover liberalization of capital goods positively contributes to economic growth with a
coefficient (0.2844) while liberalization of consumer goods is unrelated to economic
growth. Higher imports of capital goods stimulate the investment while consumer goods
38 Aggregate of consumer goods, capital goods, intermediate goods and raw material as a proxy of trade liberalization. 39 We have chosen tariff rate of capital and consumer goods because a large proportion of imports of developing
countries (included in sample) consists of these goods.
Chapter # 5 Results and Discussion
177
stimulate the consumption. Imports of capital goods increase the industrial sector
efficiency through technology transfer and boost the exports thereby improving the trade
balance. Trade openness as another indicator of trade liberalization positively affects the
economic growth with coefficient (0.1138) as common in the literature. Our findings have
empirical support from the literature. Greenaway et al. (2002) and Morgan and S.
Kanchanahatakij (2008) empirically analyze that trade liberalization positively contributes
to economic growth. Goldar and Kumari (2003) explain that import liberalization has
increased industrial productivity in India. Wacziarg and Welch (2003), Aksoy Ataman
(2006) and Falvey et al. (2013) explain that trade liberalization also increases capital
formation and manufacture exports by increasing export diversification in developing
countries. Dollar and Kraay (2004) find that globalization contributes to higher growth
rate and decline in poverty.
There is also some evidence in contrast to our results which shows that trade liberalization
may reduce economic growth. Harrison and Hanson (1999) find that trade liberalization
amplify wage inequality in less developed countries. Yasmin et al. (2006) conclude the
trade liberalization makes income distribution more worse.
Financial liberalization:
According to financial liberalization literature the association between financial
liberalization and growth is weak in developing countries. Stiglitz et al. (1994) criticize
the financial liberalization due to the increased market imperfections prevalent in
developing countries. Moreover financial liberalization in countries with weak financial
structure increase the risk of crisis, Mexican and Asian crisis in particular provide this
evidence40
. Excess capital inflows are associated with appreciation of the domestic
currency which is harmful for trade balance and divert the resources from trade able to
40
Both the crises witnessed the potential risks of short-term capital flows that lead to balance-of-payments
crises.
Chapter # 5 Results and Discussion
178
non-trade able sectors (construction, housing etc.). Furthermore huge and unanticipated
inflows encourage the consumption growth and lead to high inflation.
For financial liberalization we have used two measures; De jure and De facto measures
(detail is given in the previous chapter section 4.2). Both measures show that financial
liberalization negatively affects the economic growth with coefficients (-.1269) and (-
.3440) respectively. Our findings are in line with empirical literature. Kim et al. (2012)
find that capital account liberalization is inversely related to economic growth in the short
run both in the developed and developing countries. Eichengreen and Leblang (2003)
explain that capital account liberalization hurts the growth in the presence of crisis.
Alesina, Grilli and Milesi-Ferretti (1993, 1995) find that capital account liberalization
significantly contributes to economic growth in developed countries while it retards the
growth in developing countries. Klein and Olivei (2001), Arteta et al. (2001) and Edwards
(2000) depicts that capital account liberalization negatively contributes to growth in
countries having weak financial and institutional structure and lower level of development.
The negative sign of financial liberalization actually contradict the proposition advocated
by supporters of financial liberalization that liberalization enhances the growth rate of
economies. Bekaert et al. (2005) find that liberalization decreases the cost of capital
thereby increasing the investment and the efficiency of investment which leads to higher
growth. Quin (1997, 2008) explains that capital account liberalization contributes to
economic growth equally in developed and developing countries. Kim et al. (2012)
explains that capital account liberalization is helpful to economic growth in the long run
only.
There are certain weaknesses of both the De jure and De facto measures. De jure measure
only declares the legal status of financial liberalization of countries. De facto measure is
the sum of gross assets and liabilities; it includes both the short term and long term
Chapter # 5 Results and Discussion
179
flows41
. Aggregate measures of capital flows could conceal the individual effect of
different types of capital flows. Therefore we also use disaggregated measures
representing net FDI inflows being long term and stable investment while portfolio equity
and debt being short term investment.
Results show that net FDI inflows positively contribute to economic growth with
coefficient (.6269). Foreign investment plays an important role in developing countries
which are characterized by lack of capital and technology. This is also shown by Singh
(2003), McLean and Shrestha (2002), Reisen and Soto (2001), Mody and Murshid (2005).
Short term capital inflows negatively contribute to economic growth with a coefficient
(0.0869). They are highly volatile42
and bring macroeconomic and financial instability as
discussed above. Singh (2003), Mody and Murshid (2005) and Demir Firat (2009) provide
the evidence that short term capital flows negatively contribute to economic growth in
developing countries while they positively affect the growth in developed countries.
5.3.1.1 Diagnostic tests:
As described in the methodology in previous chapter section 4.3 that the validity of GMM
estimators depend on two specification tests; first the Sargan test of over identifying
restrictions, it tests the reliability of instruments, the second is the serial correlation test.
The null hypothesis of Sargan test explains that restrictions are valid against the
alternative. The second test examines whether there is higher order or second order serial
correlation. We test the null hypothesis of no serial correlation against the alternative.
Results of all equations show that we fail to reject both hypotheses. Chai square
probability shows that instruments are valid and errors are homoscedastic. Probability of Z
statistics in autocorrelation test shows that there is no evidence of second order serial
correlation. Moreover the Wald test checks the joint significance of all estimators in an
41
FDI being long term flows while loans and bonds are short term flows. 42
There reversal rate is higher as compared to other capital inflows.
Chapter # 5 Results and Discussion
180
equation. The results show that chai square probability is highly significant indicating that
overall goodness of the fit is satisfactory.
5.3.1.2 Concluding remarks:
To fulfill our first objective we analyze empirically the effect of institutions and policies
on economic growth. The results provide the proof of conditional convergence. Traditional
growth variables; physical and human capital and population growth also follow the
empirical literature. Physical capital increases the growth rate by increasing the economic
activities; increase in productivity, employment opportunities and economies of scale.
Human capital affects the economic growth through quality improvements in labour.
Population growth reduces the economic growth by increasing the consumption and
reducing the savings. Institutional quality promotes the economic growth by creating an
environment for capital creation. They reduce the risk of doing the business thereby
increasing the investment return. Results regarding the fiscal policy support the Keynesian
hypothesis. Capital expenditures positively contribute to economic growth by providing
necessary infrastructure for the encouragement of private sector investment. Current
expenditures adversely affect the economic growth by reducing the incentive for
investment, higher tax-finance outweighs the utility derived from it. Tax revenues also
positively affect the economic growth by increasing the ability of the government to
finance its expenditures. Results regarding the monetary policy support the Monetarists
hypothesis, monetary policy do affect the economic growth through aggregate demand.
Results show that contractionary monetary policy reduces the investment and economic
growth. Trade openness as a proxy for trade liberalization positively affects the economic
growth through externality as common in the literature. Reduction in the tariff rate also
positively contributes to economic growth. Disaggregated analysis shows that
liberalization of capital goods increases the economic growth by stimulating the
Chapter # 5 Results and Discussion
181
investment while liberalization of consumer goods is unrelated to economic growth.
Regarding the financial liberalization both De jure and De facto measure show that it
negatively affects the economic growth. In developing countries financial liberalization
brings macroeconomic and financial instability. Disaggregated analysis shows that FDI
inflows positively contribute to economic growth being long term and stable investment
while short term investment (portfolio equity and debt) negatively contribute to economic
growth due to higher reversal rate.
5.3.2 Disaggregated analysis of institutions
For a detailed analysis of institutional quality and for more comprehensive policy
implication we have also taken disaggregated measure of the institutional quality; voice
and accountability, political stability, government effectiveness, regulatory quality, rule of
law and control of corruption. We test the null hypothesis of no effect of each institutional
variable on economic growth against the alternative. Other independent variables are
initial GDP which captures the convergence, traditional determinants of growth; physical
capital, human capital and population growth. As an indicator of fiscal policy we use
government investment expenditures. We use interest rate as an instrument of monetary
policy. For trade liberalization we use average tariff rate and for financial liberalization we
use net FDI inflows.
Except the institutional variable, which we have taken in disaggregated form, results of
other variable; including convergence, traditional growth variables, indicators of fiscal and
monetary policy, indicators of trade and financial liberalization, have been discussed
already in detail in the previous section 5.3.1 with empirical evidence from previous
studies. Here again the detail will show only repetition so to avoid repetition we will only
explain the direction of relationship between the variables. We will discuss the results of
each institutional indicator with detail and support of empirical evidence.
Chapter # 5 Results and Discussion
182
Table 5.4 Disaggregated analysis of institutions
Dependent variable: Economic growth variables Eq1 Eq2 Eq3 Eq4 Eq5 Eq6
Convergence -.0340781*
(0.001)
-.0790415*
(0.001)
-.1170197*
(0.033)
-.0912243*
(0.000)
-.0450525*
(0.035)
-.0587423*
(0.003)
Capital stock .2267513*
(0.006 )
.1378771*
(0.043)
.1779449*
(0.016)
.1997953*
(0.010)
.1990583*
(0.008)
.157573
(0.283)
Human capital 1.293482
(0.249)
.7308444*
(0.023)
1.842145*
(0.046)
1.783189
(0.491)
.6684316*
(0.000)
1.018186*
(0.037)
Population growth -.5233922*
(0.050)
-.2684542
(0.268)
-.1813858
(0.204)
.4088777*
(0.047)
-1.855763*
(0.008)
.5466093
(0.217)
Institutional quality
voice and
accountability
.214876*
(0.031)
political stability
and absence of
violence
.1370642
(0.418)
government
effectiveness
.09379**
(0.069)
regulatory quality .1623408**
(0.080)
rule of law .3316861*
(0.003)
control of
corruption
.257809*
(0.042)
Stabilization policies (Fiscal and monetary policy)
Govt. investment
expenditures
.5098117*
(0.000)
.5676061*
(0.000)
.4370075 *
(0.001)
.5399704*
(0.000)
.4349869*
(0.001)
.602409*
(0.000)
Interest rate -.0545692
(0.279)
-.1258617*
(0.009)
-.1080105*
(0.024)
-.0552043
(0.251)
-.1090939*
(0.022)
-.0643816**
(0.056)
Liberalization policies (Trade and financial liberalization)
Tariff rate -.0993893*
(0.041)
-.0869403**
(0.081)
-.1457545*
(0.007)
-.1453519*
(0.044)
-.1392638*
(0.008)
-.1108772**
(0.066)
Net FDI inflows
.4329936*
(0.030)
.178682
(0.430)
.4492691*
(0.038)
.2171839
(0.256)
.4444044*
(0.040)
.2058977*
(0.006)
constant .0194078
(0.998)
8.488722
0.298
19.67251*
(0.032)
11.04793
(0.391)
19.52491*
(0.034)
-.9370931
(0.960)
No. of countries 12 12 12 12 12 12
No. of
observations
210 195 195 213 195 195
Wald chi2(prob) 0.0013 0.0100 0.0058 0.0000 0.0009 0.0007
sargan (prob. chi2) 0.0874 0.0763 0.1775 0.1221 0.0711 0.0745
AR1(prob. Z)
AR2(prob. Z)
0.0182
0.4985
0.0685
0.2554
0.0853
0.5336
0.0263
0.2122
0.0392
0.2248
0.0889
0.1537
Note: Values in the parentheses show the probability of „Z‟ statistics. * shows the significance at 1% and 5
% level of significance while ** shows the significance at 10 %. Wald test check the joint significance of the
model, Sargan test checks the reliability of instruments while AR test checks the presence of autocorrelation.
Results show that there is evidence of conditional convergence, speed of convergence
ranges between 3% to 12%. Again as discussed in previous section traditional factors of
production follow empirical findings. Physical and human capital both are positively
Chapter # 5 Results and Discussion
183
associated to economic growth while population growth is inversely related to economic
growth. Government investment expenditures as an indicator of fiscal policy positively
affect the economic growth. Interest rate as a measure of contractionary monetary policy
negatively affects the economic growth. Average tariff rate as a measure of trade
liberalization shows inverse relationship with economic growth indicating that higher the
liberalization higher will be growth. Net FDI inflows as an indicator of financial
liberalization has direct relationship with economic growth implying that higher the
financial liberalization higher will be growth. Next we discuss the effect of each
institutional variable on economic growth in detail.
Voice and accountability:
As described in the previous chapter section 4.2 the World Bank defines the voice and
accountability as the extent to the possibility that the people of a country have freedom of
expression or choice. Economic as well as political freedom is regarded an important pillar
of institutional structure of a country. Higher economic freedom increases the rate of
private investment in GDP, productivity of private investment and growth of countries.
Our results show that a 1% increase in voice and accountability index increases the
economic growth by 0.21%. Our results follow the find empirical support as Kaufmann et
al. (1999), Fayissa et al. (2013), Yerrabati and Hawkes (2015) and Bhattacharjee et al.
(2015) conclude that voice and accountability is positively correlated with economic
growth. Gwartney et al. (2003) describe that countries with higher degree of economic
freedom achieved higher economic growth. Azman Saini et al. (2010) provide the
evidence that the effect of FDI on economic growth is conditional on the degree of
economic freedom.
In contrast to our findings Bjornskov (2014) provide the evidence that higher economic
freedom is associated with high crime rates.
Chapter # 5 Results and Discussion
184
Political stability:
Relationship between political stability and economic growth depends on how we define
political stability. Literature uses different indicators for this variable. Executive turnover
represents the frequency of government collapses, Polity II democratization score,
assassinations and war casualties, occurrence of strikes, violence and coup etc. Mostly it is
observed through democratic and non-democratic governments and we also explain this
variable with this aspect. Research regarding the role of democracy in economic growth
provides ambiguous findings. The opponents argue that democracy impedes the growth
especially in less developed countries through creating consumption pressures which
hampers capital accumulation. Supporters emphasize that democracy increases economic
growth by providing civil liberties and political rights creating an environment beneficial
to economic growth. The skeptical view argues that both democracy and economic growth
are unrelated. A democratic system alone is not enough to effect on economic growth,
institutional structure and government development strategies are important factors
without which we cannot relate democracy to economic growth.
Most of the empirical studies provide the evidence of insignificant or negative association
between both variables. Our results show that political stability is unrelated to economic
growth as this variable becomes insignificant. Moreover the political stability has the
lowest percentile rank over time in nearly all the countries included in the sample which
shows that this indicator is not an important indicator of institutional quality (chapter 3
section 3.1).
Bhattacharjee et al. (2015) find that political stability has no relationship with economic
growth. Ahmad and Marwan (2012) find the evidence of negative effect of political rights,
favouring the strong authoritarian in the East Asian countries to pursue the pro-growth
Chapter # 5 Results and Discussion
185
policies. Yerrabati and Hawkes (2015) argue that if political stability is achieved through
oppression or if it produces stagnation then it negatively contributes to economic growth.
In contrast to our findings some empirical studies find positive relationship between both
variables as Goldsmith (1995), Chong et al. (2004), Gani (2011), Fayissa et al. (2013)
provide the evidence of positive relationship.
Government effectiveness:
Effective state has an important role for the provision of goods and services, public
welfare, maintaining law and order, creating an enabling policy environment for
productive activities. United Nations43
defined governance as “the process of decision-
making and the process by which decisions are implemented.” Literature provides the
evidence of a significant association between improved quality of governance and
economic growth. Findings infer that government effectiveness is positively related to
economic growth having a coefficient 0.09 which follows the empirical studies. A cross
section analysis of developing countries shows that countries having poor governance
experience a lesser growth per year relative to other countries. The work of Kaufmann et
al. (1999) provides the same conclusion about the importance of governance to economic
growth. Similar findings are provided by Gani (2011), Fayissa et al. (2013) and
Bhattacharjee et al. (2015).
Regulatory quality:
The relationship between regulatory quality and economic growth is of considerable
interest for the researchers in recent years. Through regulatory framework state affects the
behavior of the private sector. Regulatory policy in developing countries has transformed
from interventionist state to deregulation. It highlights the role of private sector for
production decision, which also ensures well-functioning competitive markets, and
43
United Nations Economic and Social Commission for Asia and the Pacific [UNESCAP], 2009.
Chapter # 5 Results and Discussion
186
emphasizes the role of state regulations to correct the market failures44
. World Bank has
emphasized the importance of improving the regulatory framework for better investment
climate for the private sector.
Our findings are consistent with the regulatory theory that effective regulation is related to
higher economic growth, which is conducive to the development of international business.
Results show that a 1% increase in regulatory quality index increases the economic growth
by 0.16%. Kaufmann et al. (1999) and Fayissa et al. (2013) explain that regulatory quality
increases the growth and development.
Rule of Law:
World Bank defines the rule of law as the contract enforcement, property rights protection,
the police and the courts, control of crime and violence. A better judicial system fosters
the economic growth by enforcing the property rights which are necessary for the increase
in private investment, moreover it keeps the checks and balances on the government,
controls the corruption. There is evidence that many African countries have shown poor
performance in terms of economic growth while they are rich in natural resources because
in the absence of property rights, these resources are exploited by power-full interest
groups45
.
Our results support the empirical literature as a 1% increase in rule of law index increases
the economic growth by 0.33% which is also highly significant. Campos and Nugent
(1999) and Kaufmann et al. (1999) explain that rule of law significantly contributes to
growth and development. Knack and Keefer (1995), Goldsmith (1995) and Ahmad and
Marwan (2012) describe that property rights increase the investment and economic
growth.
44
World Bank, 2001: 1 45
See Lane and Tornell (1996).
Chapter # 5 Results and Discussion
187
In contrast to our findings Yerrabati and Hawkes (2015) explain that rule of law is
negatively correlated to growth for South Asia, East Asia and Pecific regions. Negative
effect of rule of law indicates the less developed legal system of the region which does not
contribute to economic growth.
Control of Corruption:
World Bank defines the corruption as the use of public power for the private gain. There is
broad consensus in the literature that corruption impedes the economic growth by
lowering the rate of investment both domestic and foreign, reducing trade flows, creating
uncertainty and lowering the quality and efficiency of public projects. Corruption is
treated as detrimental to economic growth because it reduces the efficient allocation of
resources because individuals engage in rent-seeking activities rather than socially
productive activities.
Our results show that less corruption enhances the economic growth as a 1% increase in
control of corruption index boost the economic growth by 0.25 %. Mauro (1995) and
Mauro (2002) explain that corruption reduces the economic growth through reduction in
private investment. Drury and Lusztig (2006) and Gani (2011) also provide the evidence
of an inverse relationship between corruption and economic growth.
There is also evidence in sharp contrast to our results which describes that corruption
contributes to economic growth. Yerrabati and Hawkes (2015) explain that corruption
reduces the bureaucratic delays and facilitate investment and hence economic activity.
5.3.2.1 Diagnostic tests:
As described in previous section that to check the validity of the GMM estimators we use
two specification tests; first the Sargan test of over identifying restrictions the second is
the serial correlation test. Chai square probability of the Sargan test shows that instruments
are valid. Probability of Z statistics in autocorrelation test shows that there is no evidence
Chapter # 5 Results and Discussion
188
of second order serial correlation. Wald test checks the joint significance of all estimators
in an equation. The results show that chai square probability is highly significant all
equations, indicating that overall goodness of the fit is satisfactory.
5.3.2.2 Concluding remarks:
Disaggregated analysis of institutional measures demonstrates that voice and
accountability positively contribute to economic growth. Economic as well as political
freedom is regarded an important pillar of institutional structure of a country. Political
stability is unrelated to economic growth as it alone cannot affect economic growth,
institutional set up and government development strategies are important factors without
which we cannot relate political stability to economic growth. Results show that there is a
positive relationship between improved quality of government services and economic
growth. Effective state has an important role for the provision of goods and services,
public welfare, maintaining law and order, delivering public services, creating an enabling
policy environment for productive activities. Regulatory quality is also positively related
to economic growth. Through regulatory framework state affects the performance of the
private sector. Rule of law and economic growth are also positively related. A better
judicial system fosters the economic growth by enforcing the property rights which are
necessary for the increase in private investment, moreover it keeps the checks and
balances on the government, controls the corruption. Lesser corruption significantly
contributes to economic growth. Corruption retards the economic growth because it
reduces the efficient allocation of resources.
5.3.3 Effect of policy volatility on economic growth:
First objective examines the level effect of policies whereas second objective examines
volatility effect of domestic macroeconomic policies on economic growth. We again write
Chapter # 5 Results and Discussion
189
the equation here which we have already explained in previous chapter in section 4.1 as
follows;
)15(ln 222
1
43132 beqVdPVbIQbyaagyitititn
r
n
nitititit
Here Vn includes traditional factors of production; physical capital, human capital and
population growth and some external factors (foreign growth volatility, term of trade
volatility and foreign interest rate volatility). IQ shows institutional quality while PV
represents policy volatility. yt-1 is again the lagged value of GDP per capita which
represents convergence.
Volatility refers to the fluctuations in any economic activity, less volatility shows stability,
while higher volatility is harmful for an economy which leads to instability. To measure
the volatility we have used the first-order autoregressive process where the standard
deviation of the residual measures the volatility. We have also discussed the measurement
of volatility in previous chapter section 4.2. For fiscal policy volatility we have used
volatility of aggregate government expenditures. Interest rate volatility represents the
volatility of monetary policy. Volatility of financial liberalization is represented by FDI
inflows volatility. For volatility of trade policy we have used volatility of trade flows. We
have already discussed all other variables in detail in previous section 5.3.1 here again
discussion will be just repetition. Both the volatility of domestic macroeconomic policies
and external factors affect the investment and economic growth. We hypothesize that
policy volatility reduces the economic growth thus we will test the null hypothesis that
policy volatility does not affect the economic growth
Except the policy volatility which we have taken in this equation results of other variables;
including convergence, traditional growth variables and institutional quality, we have
already discussed in detail in previous section 5.3.1 with empirical evidence from the
Chapter # 5 Results and Discussion
190
literature. Here again the detail will show only repetition therefore to avoid the repetition
we will only explain the direction of relationship between these variables. We will discuss
the results of policy volatility with detail and support of empirical literature.
Table 5.5 Effect of policy volatility on economic growth
Dependent variable: Economic growth variables Eq1 Eq2 Eq3 Eq4
Convergence -.0425199*
(0.000)
-.0976269
(0.224)
-.0721738
(0.200)
-.0271405*
(0.031)
Capital stock .1469909*
(0.021)
.1504829*
(0.049)
.1482574**
(0.091)
.1959927*
(0.035)
Human capital 2.271369*
(0.023)
2.051568**
(0.095)
1.889191*
(0.016)
1.977229*
(0.038)
Population growth -.5207025
(0.440)
-.4406616*
(0.046)
.4672669**
(0.084)
-.881823
(0.760)
Institutional
quality
.1487524**
(0.076)
.3259461
(0.137)
.1276399*
(0.043)
.0673953**
(0.092)
Fiscal policy
volatility
-.138725**
(0.069)
Monetary policy
volatility
-.098406*
(0.046)
Trade flows
volatility
-.170112**
(0.092)
Capital flows
volatility
-.0351274*
(0.033)
External shocks Foreign growth
volatility
-.0852388**
(0.052)
-.1497384*
(0.001)
-.1013687
(0.214)
-.0117363*
(0.000)
TOT volatility -.5109134*
(0.020)
-.6786726**
(0.060)
-.2893842*
(0.033)
.4122176
(0.759)
Foreign interest
rate volatility
-.0611558
(0.281)
-.0376918*
(0.007)
-.0966214*
(0.013)
-.0148586*
(0.038)
constant -14.07357*
(0.036)
-13.4263*
(0.047)
-13.65986*
(0.045)
-8.666981
(0.647)
Number of obs 201 201 201 201
Number of
countries
12 12 12 12
Wald chi2(prob) 0.0014 0.0013 0.0013 0.0000
sargan (prob. chi2) 0.8142 0.3861 0.4482 0.4850
AR1(prob. Z)
AR2(prob. Z)
0.0828
0.4563
0.0485
0.3539
0.0267
0.9152
0.0670
0.2600 Note: Values in the parentheses show the probability of „Z‟ statistics. * shows the significance at 1% and 5
% level of significance while ** shows the significance at 10 %. Wald test check the joint significance of
the model, Sargan test checks the reliability of instruments while AR test checks the presence of
autocorrelation.
Results show that there is evidence of conditional convergence implying the negative
association between initial GDP and economic growth. Again as discussed in previous
Chapter # 5 Results and Discussion
191
section traditional factors of production follow empirical literature. Physical and human
capital both are positively related to economic growth while population growth is
inversely related to economic growth. Institutional quality positively affects the economic
growth. Next we discuss the effect of policy volatility on economic growth in detail.
Volatility of domestic policies:
Developing countries face the problem of uncertainty or frequent switches in their
macroeconomic policies due to some internal and external factors which reduces the rate
of economic growth and investment. Consistency of the policy is most important because
inconsistent decisions loose the public confidence, creating uncertainty for investors, reducing
the investment and growth. Investors become sensitive to policy changes and the associated
risks because of irreversible nature of certain investments. In an uncertain environment
firms delay investment and it takes a long time to investors to assure themselves that
changes of policies are permanent.
Our results show that a 1% increase in fiscal policy volatility as represented by
government expenditures reduces the economic growth by 0.13%. Our results follow the
empirical literature. Empirical literature shows that predictability or certainty of the fiscal
policy is important for the decision to invest. Uncertainties regarding future behavior of
fiscal parameters reduce the growth rate by making investment riskier. In poor countries a
combination of discretionary fiscal policy and procyclical fiscal policy increases the
volatility and harms long-term growth. Aizenman and Marion (1991), Ramey and Ramey
(1995), Ali M. Abdiweli (2005) and Fatas and Mihov (2008) explain that volatility of the
fiscal policy, uncertainty about future taxes and the future behavior of fiscal parameters,
negatively affect the behavior of economic agents altering the investment patterns. Davide
Furceri (2007) find that government expenditures volatility is negatively associated to
long-run growth for developing countries while it has a small effect for OECD countries.
Chapter # 5 Results and Discussion
192
Afonso and Jalles (2012) explain that both the discretionary and transitory variations in
fiscal policy raise the output volatility and decrease the economic growth. Moreover with
a financial crisis government spending is less flexible than revenues in developing
countries.
Regarding the volatility of monetary policy as represented by short term interest rate our
results show that a 1% increase in monetary policy volatility reduces the economic growth
by 0.09%. Uncertainty of the interest rate affects the firm‟s profitability by reducing the
corporate investment especially when there is irreversibility. Firms delay investment in
order to get information regarding the future stance of monetary policy. Findings are also
supported by empirical literature. Peterson (1998) finds that an unstable money supply
growth has contributed to slower growth in developing countries. Gulen and Ion (2013)
and Bretscher et al. (2016) explain that policy uncertainty reduces the industry and firm
investment with a substantial magnitude. Relationship is stronger for firms having higher
degree of irreversibility, have more financial constraints and those who are less
competitive. Bo and Sterken (2002) show that an increase in interest rate volatility
increases the interest rate burden and decreases the real value of debt holdings and the
effect is larger for highly indebted firms.
Regarding the volatility of capital inflows as represented by net FDI inflows our results
show that it negatively affects the economic growth, a 1 % increase in the volatility of
capital inflows reduce the economic growth by 0.03%. Volatility of capital inflows is a
proxy for country specific risk, given the higher risk foreign investors might delay or even
reverse the investments. Increasing volatility of capital flows affects domestic investment
through interest rates, exchange rate, inflation expectations and risk and uncertainty
regarding future profitability. FDI volatility is detrimental to economic growth by
discouraging the innovation and technology adaption. There is growing body of literature
Chapter # 5 Results and Discussion
193
indicating that unstable short-term capital flows have deteriorated the long-term growth
prospects in developing countries. Our findings are supported by empirical literature.
Choong et al. (2011) explain that FDI volatility is negatively associated with all ASEAN
countries while it has a marginal effect on Singapore because the financial system of
Singapore is well developed having the ability to alleviate the variability of FDI inflows.
Demir Firat (2009) conclude that volatility of the short term capital inflows is negatively
associated with economic growth. Neanidis (2015) find that volatility of all the capital
flows aggregated and disaggregated (FDI, equity and debt flows) is negatively related to
economic growth.
Volatility associated with trade flows as represented by export instability also reduces
the economic growth. Our results show that a 1% increase in the volatility of trade flows
reduces the economic growth by 0.17%. Economic literature provides the evidence that
trade flows are more volatile in less developed economies as compared to developed
countries as global integration has exposed these countries to external shocks and the
difficulty to manage these shocks has made their trade flows more volatile thereby
reducing the growth. Volatility of export earnings bring instability in foreign reserves that
reduce the imports of capital goods and hence decrease the efficiency of industrial sector.
Our findings follow the empirical literature. Ozler and Harrigan (1988) find that largest
negative effects of export instability are on countries who are more open and whose
exports are concentrated in capital intensive sectors. Love (1989) concludes that export
instability brings instability in capital goods imports and, in turn, investment and growth.
Gyimah-Brempong (1991) and Rashid et al. (2012) explain that export instability
negatively affect the economic growth in Asian and African countries.
In contrast to our findings Yotopoulos and Nugent (1976) and Sinha (1999) infer that
export instability reduces the marginal propensity to consume, thereby increasing savings
Chapter # 5 Results and Discussion
194
and higher growth. While Chaudhary and Qaisrani (2002) explain that export instability
does not affect economic growth and investment in Pakistan because the trade deficit is
met through foreign borrowings.
Volatility of external factors:
With the increased globalization and integration of world market economies are greatly
influenced by the growth volatility of their trading partners such as the financial crisis of
2008. Terms of trade shocks affect in particular growth of small open economies. Interest
rate shocks make the credit and investment more expensive bringing the firms towards
bankruptcy. Results show that volatility of foreign growth, term of trade volatility and
foreign interest rate volatility all inversely related to economic growth. Literature provides
the empirical support to our findings. Mendoza (1997) and Andrews and Rees (2009)
explain that term of trade volatility reduces the economic growth by increasing the
volatility of consumption, exports and imports. Olaberria and Rigolini (2009) explain that
besides the volatility of domestic factors volatility of external factors has also contributed
to the slow growth of emerging economies. Abaidoo (2012) conclude that external
macroeconomic volatility has larger effect on macroeconomic performance of African
countries than domestic volatility.
5.3.3.1 Diagnostic tests:
Sargan and auto correlation test both check the reliability of GMM estimates. Results of
the Sargan test show that instruments are valid and results of autocorrelation test provide
the evidence of no second order serial correlation. Results of the Wald test the joint
significance of the model implying that overall significance of the model is satisfactory.
Chapter # 5 Results and Discussion
195
5.3.3.2 Concluding remarks:
Our second objective examines the association between policy volatility and economic
growth. Results show that volatility of domestic macroeconomic policies brings the
uncertainty regarding investment decisions therefore reducing the growth. A predictable
policy is an important factor that affects the behaviour of investors. Volatility makes the
investors sensitive to policy change and the associated risks because of irreversible nature
of certain investments. Volatility of the fiscal policy creates uncertainty about future taxes
and the future behavior of fiscal parameters which negatively affects the behavior of
economic agents. Uncertainty of the interest rate affects the firm‟s profitability by
reducing the corporate investment especially when there is irreversibility. Access to the
external market has destabilized the economies of less developed countries because of
volatility associated with trade and capital flows. Volatility of both negatively affects the
economic growth by reducing the domestic and foreign investment.
5.3.4 Determinants of policy volatility:
Our last objective is to analyze the effect of institutions on policy volatility. We again
write the equation here which we have already explained in previous chapter in section 4.1
as follows;
)15(333
1
5154 ceqWfIQbPVaaPVititits
v
s
sititit
Here Ws consist of control variables including domestic macroeconomic and external
factors; inflation volatility representing macroeconomic volatility, GDP per capita
representing level of development of a country, previous period‟s debt, exchange rate
volatility, export concentration, primary exports, financial development and some external
factors which include foreign growth volatility, term of trade volatility and foreign interest
rate volatility.
Chapter # 5 Results and Discussion
196
As explained in previous chapter section 4.2 and also in previous section 5.3.2 that
volatility refers to the fluctuations in any economic activity. To measure the volatility we
have used the first-order autoregressive process where the standard deviation of the
residual measures the volatility. As explained in previous section 5.3.2 that for fiscal
policy volatility we have used volatility of aggregate government expenditures, for
monetary policy volatility we have used interest rate volatility. Volatility of capital flows
is represented by FDI inflows volatility and for volatility of trade policy we have used
volatility of trade flows.
Developing countries are more volatile and their volatility stems from three sources. First,
they experience more domestic shocks due to macroeconomic instability second, they face
bigger exogenous shocks due to global integration third ,they have weak shock absorbers46
due to which exogenous factors have strong influence on their macroeconomic volatility.
Institutions play an important role to reduce policy volatility by putting restrictions or
check and balances on policy makers. We hypothesize that institutions reduce the policy
volatility hence we will test the null hypothesis that institutions does not affect policy
volatility against the alternative.
46
Financial markets and macroeconomic stabilization policies are regarded shock absorbers. Financial
markets diversify the risk and stabilization policies help to absorb the shocks.
Chapter # 5 Results and Discussion
197
Table 5.6 Determinants of policy volatility
Dependent variable: Policy volatility variables Fiscal policy
volatility
Monetary policy
volatility
Capital flows
volatility
Trade flows
volatility
Previous period‟s policy
volatility
.1471345*
(0.000)
.0931952**
(0.075)
.0534053*
(0.014)
.0269583*
(0.005)
Inflation volatility .09235722*
(0.000)
.0174039*
(0.039)
.0475569*
(0.030)
GDP per capita -.2252021*
(0.000)
-.0127363*
(0.291)
-.0689597*
(0.001)
-.0449205**
(0.076)
Previous period‟s debt .0553092*
(0.035)
0.312784*
(0.043)
Exchange rate volatility .0215541*
(0.025)
.075566**
(0.063)
.1289132*
(0.004)
Financial development -.290425*
(0.008)
-.2651632**
(0.052)
Export concentration .0858227*
(0.002)
Institutional quality
Fiscal institutions (Political constraints)
- .0834411*
(0.048)
Economic institutions (rule of law and control of
corruption)
-.1300039**
(0.076)
-.1614577*
(0.031)
Monetary institutions (Central Bank independence)
.0282034*
(0.046)
External shocks
Foreign growth volatility .0358045*
(0.000)
.0137612
(0.543)
-.1573719*
(0.049)
.0725686*
(0.042)
TOT volatility .416788
(0.422)
.654213
(0.631)
.22249
(0.230)
.850552*
(0.007)
Foreign interest rate
volatility
.0865999
(0.171)
.1565321*
(0.026)
-.0888771*
(0.005)
.1520388
(0.530)
constant .2302051
(0.116)
.8180584*
(0.000)
.5367057*
(0.000)
2.101226*
(0.001)
Number of obs 204 204 204 204
countries 12 12 12 12
Wald chi2(prob) 0.0140 0.0029 0.0001 0.0337
sargan (prob. chi2) 0.1134 0.1034 0.6959 0.1928
AR1(prob. Z)
AR2(prob. Z)
0.0069
0.1132
0.0845
0.1460
0.0125
0.9843
0.0845
0.1848 Note: Values in the parentheses show the probability of „Z‟ statistics. * shows the significance at 1% and 5
% level of significance while ** shows the significance at 10 %. Wald test check the joint significance of
the model, Sargan test checks the reliability of instruments while AR test checks the presence of
autocorrelation.
Chapter # 5 Results and Discussion
198
5.3.4.1 Determinants of fiscal policy volatility:
Volatility of fiscal policy is associated with cyclical fluctuations or some exogenous
factors, exogenous factors bring fluctuations in fiscal policy that are not associated to
economic or business cycle fluctuations; politically motivated changes in taxes or
spending and changes in fiscal policy caused by exogenous shocks. For the empirical
analysis of fiscal policy volatility we have used government spending because it is less
volatile, reacts much less to the cyclical fluctuations in general.
Previous period’s fiscal volatility increases the volatility in current period because it
becomes difficult to reverse certain spending due to some political constraints. Results
show that a 1% increase in volatility of the previous period increases the volatility in
current period by 0.14%.
Fatas and Mihov (2008), Agnello and Sousa (2014) and Attiya et al. (2011) explain that
fiscal policy volatility has persistence effect.
GDP per capita represents the level of development of the countries. As the level of
development increases it reduces the volatility of fiscal policy. Results show that GDP per
capita and fiscal policy volatility are inversely related. It indicates that rich countries have
more stable fiscal policy with lower volatility of fiscal discretion and larger automatic
stabilizers. While poor countries are likely to have more volatile business cycle and more
prone to discretionary fiscal policy. Fatas and Mihov (2008, 2013), Agnello and Sousa
(2009) and Bleaney and Halland (2009) explain that higher level of development
represented by GDP per capita reduces the volatility of fiscal policy.
Higher inflation volatility represents the macroeconomic instability which is positively
associated with the fiscal policy instability. A 1 % increase in the inflation volatility
increases the fiscal policy by 0.09%. Higher inflation increases the fiscal volatility as it
brings economic uncertainty making volatile the spending and revenue. Agnello and Sousa
Chapter # 5 Results and Discussion
199
(2009) and Attiya et al. (2011) explain that inflation and inflation volatility increases the
volatility of capital flows.
Higher external debt in developing countries, due to higher fiscal deficits, increases the
volatility of fiscal policy. Our results also follow the empirical literature indicating a direct
relationship between external debt and fiscal policy volatility with a coefficient of 0.05.
Large fiscal adjustments are required for the accumulation of debt which affects the
country‟s long run fiscal sustainability. Higher external debt reduces the efficiency of
fiscal policy in controlling economic fluctuations due to increase in taxes, generating a
more procyclical fiscal policy. Fatas and Mihov (2008), Attiya et al. (2011) and Agnello
and Sousa (2008, 2014) explain that higher public debt and deficits lead to higher fiscal
instability due to frequent taxes and spending variations.
Regarding the institutional quality our results show a significant negative effect of the
quality of institutions on government spending volatility with a coefficient 0.08. Empirical
literature provides the evidence that institutional constraints make it hard for the
governments to frequently change the policy. Strong budgetary institutions provide the
rules to govern the budget process and checks and balances over public finances. Also the
checks and balances by the parliament or judiciary put constraints on the governments and
generate the fiscal policy which is highly predicable. Our results follow the empirical
literature. Fatas and Mihov (2008, 2013) and Henisz (2004) explain that institutional
quality represented by political constraints significantly and robustly contributes to fiscal
policy volatility. Agnello and Sousa (2009, 2014) explain that higher political instability
increases the volatility of public deficit while higher democracy and parliamentary
systems reduces volatility. Bruno (2010) finds that institutions, both the explicit and
implicit constraints, reduce the volatility of fiscal policy significantly. Attiya et al. (2011)
depicts that political and institutional constraints reduce the volatility of budget deficit.
Chapter # 5 Results and Discussion
200
Results show that external factors also enhance the volatility of fiscal policy. Foreign
growth volatility increases the fiscal policy volatility with a coefficient 0.03. With
increased globalization, integration and external competitiveness economies are therefore
more exposed to external shocks, which put an upward pressure on domestic
macroeconomic policy making it more volatile, as documented by Agnello and Sousa
(2009, 2014).
5.3.4.1.1 Diagnostic tests:
Sargan test provides the evidence of the reliability of instruments while the auto
correlation test provides the evidence of no second order serial correlation. In both tests
we fail to reject the null hypothesis. Wald test provides the overall significance of the
model which is satisfactory.
5.3.4.1.2 Concluding remarks:
We conclude that volatility of the fiscal policy is affected by some domestic and external
factors. We determine the fiscal policy volatility by its past behaviour, previous period‟s
volatility induces volatility in the current period. GDP per capita represents the level of
development of the countries. With higher level of development countries have more
stable fiscal policy with lower volatility of fiscal discretion and larger automatic
stabilizers. Inflation volatility which represents the macroeconomic instability induces
economic uncertainty which makes fiscal policy highly volatile. Higher external debt, due
to higher fiscal deficits, increases the volatility of fiscal policy inducing large fiscal
adjustment for the accumulation of debt leading to frequent changes in spending and
taxation. Institutional checks and balances by the parliament or judiciary put constraints on
the governments and generate the fiscal policy which is highly predicable. With increased
globalization, integration and external competitiveness economies are therefore more
Chapter # 5 Results and Discussion
201
exposed to external shocks, which put an upward pressure on domestic macroeconomic
policy.
5.3.4.2 Determinants of monetary policy volatility:
Less volatility of monetary policy is closely associated with the transparency of monetary
authority‟s actions and decisions. There are certain internal and external factors affecting
the volatility of monetary policy. External factors explain the degree of market integration.
Since the last two decades trade and foreign investment barriers have reduced in
developing countries due to deregulation, accompanied by high interest rate volatility.
Monetary policy volatility is represented by short term interest rate though short term
interest rate is considered highly volatile but due to data constraints its common practice in
empirical literature.
Previous period’s volatility increases the volatility of monetary policy in current period.
Results show that a 1% increase in previous period‟s volatility increases the volatility in
current period by 0.09%. Previous period‟s volatility makes the profits of investors
uncertain so they delay their investment decisions also in the current period by assuming
that previous pattern will prevail in current period which increases the volatility further.
As described in previous equation that GDP per capita represents level of development of
a country. Results show that GDP per capita and volatility of monetary policy are
inversely related. A 1% increase in GDP per capita reduces the monetary policy volatility
by 0.01%. Higher level of development show macroeconomic stability, less market
imperfections or distortions, financial market stability and autonomy of the central bank
will reduce the volatility of monetary policy.
Our results show that inflation volatility and interest rate volatility are directly related
with a coefficient 0.01. Inflation is a major determinant of interest rate according to
Fischer‟s theory, loanable funds and liquidity preference. There are many studies that
Chapter # 5 Results and Discussion
202
investigate this relationship at levels. Payne and Ewing (1997) and Ahmad (2010) provide
the evidence of positive association between expected inflation and interest rate in
developing countries. Berument and Malatyali (2001) and Berument et al. (2007) also
consider inflation uncertainty and provide the evidence that both inflation and inflation
uncertainty positively contribute to interest rate in developed and developing countries.
Noula (2012) explain that uncertainty in inflation affects the investor‟s welfare, for a given
level of risk they want to have higher return.
Management of public sector deficit or debt is an important aspect of fiscal policy. In
many developing countries unsustainable fiscal deficits and public debt lead towards high
and volatile inflation therefore making monetary policy more volatile. Though financial
liberalization policies have been executed in many developing countries, government
interventions still remain significant in many countries. Empirical literature provides
mixed results regarding the relationship between government debt or deficits and interest
rate. Some studies support the non Ricardian47
hypothesis, public debt and deficits
increase interest rates while others support the Ricardian equivalence48
hypothesis, no link
between the both because private savings fully offset the effect of a higher deficit. It is
also argued that sensitivity of interest rate to deficit has decreased due to the globalization
and financial market integration, due to increasing flow of foreign capital to finance the
deficit.
Our results show that a 1 % increase in previous periods‟ debt increases the volatility of
monetary policy in current period by 0.31%. Our results support the non Recardian
hypothesis that fiscal policy distortions caused by higher deficit or debt bring distortions in
monetary policy. Our results are supported by empirical literature. Lal et al. (2001)
47
In a non-Ricardian regime fiscal policy becomes active and monetary policy passive, monetary policy
accommodates higher fiscal deficits. 48
In a Ricardian regime monetary policy is active which determines the prices and fiscal policy is passive.
Chapter # 5 Results and Discussion
203
explain that the higher fiscal deficit and debt have led to higher interest rates and crowding
out of private investment in India. Kwon et al. (2006) explain that a higher public debt is
strongly related with higher inflation and interest rate in countries under higher debt
obligations. Claeys et al. (2012) explain that only in OECD countries the effect of public
debt on interest rate is small due to globalization while emerging markets are not well
integrated so the effect is larger there.
In contrast to our results Gale and Orszag (2002) and Chakraborty (2012) argue that fiscal
expansion does not increase the interest rate due to availability of foreign savings
replacing domestic savings and due to interest rate deregulation.
The relative strength of the domestic currency affects the inflation and interest rate. A
decline in the value of domestic currency raises the cost of imported inputs and final goods
via the cost push inflation. It not only increases price of imported goods but also indirectly
increases the price of domestic goods which are under competitive pressure from imported
goods, via demand pull inflation. Opposite holds in case of appreciation of domestic
currency so the volatility in exchange rate brings inflation volatility which is associated
with interest rate volatility. Results show that a 1% increase in exchange rate volatility
increases the interest rate volatility by 0.02%. Hol (2006) and Aisen and Hauner (2008)
explain that devaluation leads to higher domestic interest rate in small semi open
economies. Chakraborty (2012) explains that a higher exchange rate attracts the demand
for domestic financial assets from abroad, by making the domestic currency less valuable,
which may lead to increase the interest rate.
Institutional quality plays an important role in the effectiveness and consistency of
monetary policy. Results show an inverse association between central bank independence
and volatility of monetary policy. A 1% decrease in central bank autonomy increases the
volatility of monetary policy by 0.02%. Institutions affect the transmission of monetary
Chapter # 5 Results and Discussion
204
policy through their effect on the elasticity of investment demand to changes in interest
rates. An independent central bank can provide more consistent policy by reducing the
uncertainty, in addition to lower inflationary outcome. Independent central banks are much
less sensitive to political influence and are more concerned about price stability while
higher political influence changes central bank laws randomly within short time spans.
Krause and Rioja (2006) provide the evidence that higher institutional quality and central
bank independence contribute towards a more efficient monetary policy outcome in both
developed and developing countries. Burdekin et al. (2011) provide the evidence of
central bank independence and inflation consistency both for developed and developing
countries. Duncan (2013) provides the evidence that strong institutional quality reduces
the volatility of interest rate and brings a positive co-movement between output and the
interest rate (countercyclical monetary policy).
Over the past two decades the global integration (through trade and financial channels)
has resulted in a higher degree of business cycle co-movement by faster transmission of
shocks. This has reshaped the monetary policy framework in developing countries, short
and long term interest rates have become more responsive to global conditions. Monetary
policy volatility in the world or large countries has significant effect on monetary policy in
developing countries. Results show that volatility of foreign interest rate increases the
volatility of monetary policy by 0.15%. Lorde et al. (2008) and Aisen and Hauner (2008)
provide the evidence of a positive correlation between domestic interest and US interest
rate. Hol (2006) provide the evidence that external factors have more influence on
domestic interest rate as compared to domestic macroeconomic factors. Noula (2012) and
many other studies explain that with higher openness interest rate is determined by
external factors, interest rate parity relationship.
Chapter # 5 Results and Discussion
205
5.3.4.2.1 Diagnostic tests:
Sargan test provides the evidence of validity of instruments while serial correlation test
provides the evidence of no higher order serial correlation. Wald test provides the
evidence that level of significance of the model is satisfactory.
5.3.4.2.2 Concluding remarks:
We conclude that there are some domestic and global factors that affect the volatility of
monetary policy. Previous period‟s volatility increases the volatility of monetary policy in
current period by making uncertain the profits of the investors. Higher level of
development shows macroeconomic stability, financial market stability and independence
of the central bank causing more stable monetary policy. Increased inflation uncertainty
increases the unanticipated inflation which is associated with anticipated and uncertainty
effects on interest rate. Regarding the previous period‟s debt our results support non
Ricardian hypothesis. We conclude that distortions in fiscal policy caused by public debt
or deficit bring distortions in monetary policy. The relative strength of the domestic
currency affects the inflation and interest rate. Institutions play an important role in the
consistency of monetary policy. An independent central bank can provide more consistent
policy by reducing the uncertainty. Due to global integration and a greater business cycle
co-movement monetary policy volatility in the world or large countries has significant
effect on monetary policy in developing countries.
5.3.4.3 Determinants of capital flows volatility:
Literature shows that there are certain external (push) and internal (pull) factors that are
accountable for the volatility of capital flows in developing countries. Prior to financial
crisis 1997-98 many developing countries observed a significant increase in net capital
inflows, mainly driven by the banking sector capital flows, these short term flows reversed
during crisis. Again prior to global financial crisis 2007-08 developing countries
Chapter # 5 Results and Discussion
206
experienced large short term inflows, during the crisis larger reversal lead to financial
market instability in developing countries. An effective management of these capital flows
has been a major policy concern for many developing countries. In this respect,
understanding the factors that drive capital flows is vital for the effective management of
such flows. We use net FDI inflows to represent volatility of capital flows because these
are considered more stable as compared to other flows.
Results show that previous period’s volatility positively affects the volatility of capital
flows in current period because it increases uncertainty and the risk on the part of
investors. Results show that a 1% increase in previous period‟s volatility increases the
volatility in current period by 0.05%. (Broner and Rigobon, 2005).
Results show an inverse relationship between GDP per capita and volatility of capital
flows with a coefficient 0.06. Countries with higher development level exhibit lower
volatility of capital flows due to fewer distortions in the capital market. It is argued that
the presence of market imperfections such as information asymmetry, moral hazard and
herding destabilize the capital flows in both developed and developing countries. There
are a number of studies finding these distortions as a key factor behind destabilized capital
flows to developing countries. Alfaro et al. (2005), Broner and Rigobon (2005), Mercado
and Park (2011), Waqas et al. (2015) explain that level of development reduces the
volatility of capital flows. While Broto et al. (2008) provide the evidence of nonlinear
relationship between both variables.
Inflation volatility represents macroeconomic uncertainty which is positively related with
volatility of capital flows. Findings indicate that a 1 % increase in inflation volatility
increases the volatility of capital flows by 0.04%. Capital flows respond to the
macroeconomic uncertainty because the foreign investor bears the risk, and uncertainty of
inflation is detrimental to the profitability of investors. Countries having lesser inflation
Chapter # 5 Results and Discussion
207
volatility incline to experience lower levels of volatility in terms of the net foreign flows
of capital. Alfaro et al. (2005) and Waqas et al. (2015) explain that volatility of capital
flows increases in countries with higher inflation and inflation volatility rates as it reflects
unpredictable and distortionary monetary conditions.
Regarding the Exchange rate volatility results indicate a direct relationship between both
variables with a coefficient of 0.07. Volatility of exchange rate creates uncertainty about
the profits, by putting the investors into dilemma of how to infer these changes, by
restricting the international capital flows. Our results follow the empirical literature.
Gerardo and Felipe (2002) conceal that a stable exchange rate is essential to stabilize FDI
flows. Mercado and Park (2011) and Ullah Sami et al. (2012) explain that devaluation of
host country currency encourages the foreigners to invest due to higher return thereby
decreasing their volatility while higher exchange rate volatility increases the volatility of
capital flows.
Financial development provides more efficient risk diversification. More developed
financial system contributes to financial integration by attracting foreign investment. Our
results follow the empirical literature indicating an inverse relationship between financial
sector development and volatility of capital flows having coefficient 0.29. Chinn and Ito
(2006) provide empirical evidence that the benefits from financial integration are possible
only if financial system is well developed. Broner and Rigobon (2005), Broto et al. (2008)
and Mercado and Park (2011) explain that a developed financial system lessens the
instability of capital inflows. Countries with underdeveloped financial system experience
more volatile capital flows and also the risk of crises
Institutional quality plays an important role in reducing the volatility of capital flows.
Results show that a 1% increase in institutional quality index reduces the volatility of
capital flows by 0.13%. A strong legal system for financial transactions is especially
Chapter # 5 Results and Discussion
208
important. When the legal system in an economy does not clearly define the property
rights and guarantee the contract enforcement the incentives for credit activities become
limited. Legal safeties for creditors and the reliability and transparency of accounting
procedures are also likely to affect investor‟s financial decisions. Higher corruption
represents country specific risk and distorts the persistence of capital inflows. Corruption
may also weaken domestic financial system and increases the chance of a financial crisis.
Lambsdorff, J. G. (2003) explains that corruption reduces the persistence of capital flows
as investors prefer to export their capital to safe havens. Broto et al. (2008) explain that
economic and political stability reduces the volatility of portfolio flows. Broner and
Rigobon (2005) and Mercado and Park (2011) describe that institutional quality lowers the
volatility of capital flows. Beck Ronald (2001) finds that regulatory environment
represented by rule of law matters more than macroeconomic indicators in reducing the
volatility of capital flows.
Regarding the volatility of external factors our findings show that volatility of foreign
growth rate and interest rate reduces the volatility of capital flows. Literature also provides
the empirical evidence that changes in global economic conditions also bring changes in
capital flows to developing countries. Global conditions also work as push factors to
capital flows in developed countries. Demir Firat (2006), Neumann and Tanku (2009)
conclude that volatility of US interest rate and growth rate is inversely related to the
volatility of capital inflows to domestic market. By examining the volatility of different
type of capital flows in emerging economies Broto et al. (2008) explain that global
conditions significantly affect the volatility of portfolio and other investment flows but
less the FDI flows. Mercado and Park (2011) conclude that global factors significantly
contribute to volatility of capital flows.
Chapter # 5 Results and Discussion
209
5.3.4.3.1 Diagnostic tests:
Both the Sargan and serial correlation tests provide the evidence that instruments are valid
and there is no second order serial correlation and Wald test indicates the overall
significance of the model.
5.3.4.3.2 Concluding remarks:
We conclude that there are some domestic and global factors that contribute to the
volatility of capital flows. Previous period‟s volatility increases the volatility in current
period by creating the uncertainty and risk on the part of investors. At higher level of
development there is expectation of less market distortions, information asymmetry and
moral hazard etc., hence capital flows will be less volatile. Inflation and exchange rate
volatility makes the investor‟s profits uncertain which increases the uncertainty of the
foreign capital flows. While the exchange rate stability is positively associated with
stability of capital flows. Financial market development reduces the volatility of capital
flows by providing more efficient risk diversification. Institutional quality plays an
important role to stabilize the capital flows. A strong legal system for financial
transactions and the reliability and transparency of accounting procedures affects the
investor‟s financial decision. Due to world integration and globalization changes in global
economic conditions also bring changes in capital flows to developing countries. External
shocks affect the volatility of capital flows in developing countries and work as push
factors.
5.3.4.4 Determinants of trade flows volatility:
Importance of trade flows in determining the competiveness of the economy is
incontestable. As a result of liberalization and world integration trade flows have become
responsive to changes in internal and global economic scenario and show frequent
Chapter # 5 Results and Discussion
210
changes, especially in less developed countries. We use volatility of exports to represent
trade flows as is common in empirical literature.
Previous period’s volatility increases the volatility of trade flows in current period. It
creates uncertainty on the part of investors regarding their profits. They delay their
investment decisions assuming that previous period‟s pattern of volatility will continue in
the current period. Results show that a 1% increase in GDP per capita reduces the
volatility of trade flows by 0.02%
GDP per capita indicates the level of development of the country. Results show that a 1%
increase in GDP per capita reduces the volatility of trade flows by 0.04%. Countries with
higher level of development exhibit lower volatility of trade flows due to less market
imperfections, more competitiveness, macroeconomic stability, exchange rate stability,
financial market stability and higher export diversification. Our findings are in line with
the previous literature Massell (1970), Aslam (1985) and Sarada et al. (2006).
Exchange rate is an important indicator of trade flows. Exchange rate volatility can affect
the trade both directly and indirectly. At the one hand it raises the uncertainty and
adjustment cost whereas on the other hand it deteriorates the production and investment
decisions. Results show a positive association between exchange rate instability and
export instability with a coefficient 0.12. Our findings are supported by empirical
literature. Baum and Caglayan (2009) provide the evidence of a positive association
between exchange rate uncertainty and volatility of trade flows. Many studies are available
that discuss the impact of exchange rate or its volatility on trade performance at levels
while empirical evidence regarding volatility of trade flows is scarce. Arize et al. (2000),
Chit et al. (2008), Demir (2012) and Khan (2014) all provide the evidence that exchange
rate uncertainty or volatility adversely affect the trade both export and import volumes in
developing and emerging economies.
Chapter # 5 Results and Discussion
211
Financial development relaxes the liquidity constraints facing by the firms. Economies
with developed financial sectors enjoy comparative advantage in sectors with high scale
economies. Firms are more likely to export when they enjoy lower credit constraints and
higher productivity levels. Credit constraints also matter for export patterns therefore
literature supports that financial development promotes the production and trade. Our
results support the empirical findings and show a negative relationship between financial
development and exports instability also supported by Beck (2002; 2003) and Hur et al.
(2006).
Regarding export concentration our results show that a 1 % increase in the export
concentration index increases the volatility or instability of exports by 0.08%. A country
with a large share of its exports by producing a single good or closely related goods
experience more instability in exports than a country with diversified export base. Higher
the diversification, the larger the number of goods a country exports, the more evenly
resources are spread over the different goods which reduces the instability. Our results are
supported by empirical literature. Massell (1970), Sheehey (1977), Aslam (1985), Sarada
et al. (2006) and Neena (2015) provide the empirical evidence that there is higher export
concentration in developing countries which increases the instability of exports.
Findings show a1% increase in institutional quality index decreases the volatility of trade
flows by 0.16%. Institutions increase the transparency of trading system through greater
predictability which reduces the trading cost. Besides their direct effect institutions also
indirectly affect the trade through their effect on investment and productivity. Sound
regulation, efficient administration, low corruption and effective law enforcement
facilitate the trade flows. Contract enforcement, property rights and investor protection
also matter by allowing the investors to overcome distortions. Our findings are supported
by empirical literature. Anderson and Marcouiller (2002), Groot et al. (2004), Levchenko
Chapter # 5 Results and Discussion
212
(2007) and Helble et al. (2007) provide the evidence that institutional quality (contract
enforcement, secured property rights, shareholder protection and the like) and quality of
governance determine the bilateral trade flows between the countries. Moreover higher
transparency of the trading system has an important impact on trade costs in developed
and developing countries.
Access to external market has exposed less developed countries to volatilities prevalent in
the global market. These volatilities have significant impact on country‟s trade flows.
Global financial crisis of 2008 provides the evidence of shortage of finance for trade
because of bankruptcy of financial institutions which also increased the cost of capital by
lowering the trade volume. Moreover global crises resulted in significant change in
countries‟ terms of trade. Our results show that external shocks positively affect the
volatility of trade flows. Foreign growth volatility and term of trade volatility increase the
volatility of trade flows by 0.07% and 0.85% respectively. Shelburne (2010) examine the
effect of global financial crisis of 2007-10 on the world and European emerging
economies. Crisis severely affected the trade of the European emerging economies and the
world as the terms of trade deteriorated significantly.
5.3.4.4.1 Diagnostic tests:
Sargan test and serial correlation test provide the evidence of reliability of instruments and
no higher order serial correlation respectively while Wald test provides the evidence of
overall significance of the model.
5.3.4.4.2 Concluding remarks
There are certain domestic and global factors that are responsible for the volatility of trade
flows. Previous period‟s volatility increases the volatility of trade flows in current period
by creating uncertainty on the part of investors regarding their profits. Higher the level of
development lower the volatility of trade flows due to less market imperfections, more
Chapter # 5 Results and Discussion
213
competitiveness, macroeconomic stability, exchange rate and financial market stability
and more diversified exports. Exchange rate volatility positively affects the volatility of
international trade flows. at the one hand it raises the uncertainty and adjustment costs and
on the other hand it deteriorates the production and investment decisions. Financial sector
development relaxes the liquidity constraints facing by the firms and reduces the volatility
of trade flows. Economies with developed financial sectors enjoy comparative advantage
in sectors with high scale economies. Higher export concentration increases the volatility
of trade flows. A country with a large share of its exports by producing a single good or
closely related goods experience more instability in exports than a country with diversified
export base. Institutions increase the transparency of trading system through greater
predictability which reduces the trading cost. Sound regulation, efficient administration,
low corruption and effective law enforcement facilitate the trade flows. Access to external
market has exposed less developed countries to volatilities inherent in the global market.
These volatilities have significant impact on country‟s trade flows.
214
Conclusions and Policy Recommendations
This chapter discusses the summary of the whole thesis moreover it also draws some
important policy recommendations based on empirical findings and last it discusses the
limitations of the study and provides the direction for future research. First section
discusses the conclusions of the study, second section discusses important policy
recommendations and last section discusses limitations and future research directions.
6.1 Conclusions:
Policy failures in many developing countries were caused by weak institutions structure;
the failure of price reform and privatization in Russia, failure of market-oriented reforms
in Latin America and the financial crisis of Asia were all the results of the lack of helpful
legal, regulatory and political framework. Moreover the monetary transmission
mechanism is weak in developing countries due to weak monetary, financial and fiscal
institutions. Government finances in many developing countries are also weak which lead
to high deficits, debts and debt-servicing obligations. The lack of political stability and an
inefficient bureaucracy allow rent-seeking to continue. Financial sector distortions have
historically lead to financial crises. All it provides the rationale for the importance of
institutions and their strengthening in developing countries for policy effectiveness. The
second generation reforms focus on restructuring the state and institutions.
Given the importance of institutions this study tries to discover the relatively unexplored
areas on the relationship between institutions, policies and economic growth. As there is
extensive literature so far on institutions-growth relationship as well as macroeconomic
policies-growth relationship therefore the study contributes by filling the gap on
Chapter # 6
Chapter # 6 Conclusions and Policy Recommendations
215
institutions-policies link for developing countries specifically the role of institutions in
reducing policy instability. Choice of the countries is based on the governance status or
percentile rank of the countries provided by the World Bank, World Governance
Indicators. Choice of the time period is relevant to policy initiatives in developing as an
agenda of neoliberal approach. Our empirical analysis employs annual data for a set of 12
developing countries, according to the World Bank classification, from South Asia, East
Asia and Pacific, Latin America and Sub Saharan Africa. The sample period spans from
1990–2014. In the light of motivation and significance of the study there are three main
objectives and also sub objectives. Main objectives discuss the role of policies (both
stabilization and liberalization policies) and institutions on economic growth. In addition
to the level effect of domestic macroeconomic policies on economic growth the study also
evaluates the volatility effect and last the indirect effect of institutions on economic
growth through reducing the policy instability or volatility which contributes to the
literature as an unexplored area.
First chapter discusses background and motivation of the study, review of institutions
and policies in developing countries which establishes an institution policy link,
significance and contribution and objectives of the study, which we have already discussed
above in a summarized way.
Second chapter discusses the review of theoretical and empirical literature according to
our objectives. Moreover it also discusses the unexplored areas regarding institutional
policy link.
Third chapter provides an overview of the economies of selected countries. It also
discusses the dynamics of their institutions and policies and institutional reforms in
developing countries. It provides a view of different indicators representing institutional
quality, stabilization and liberalization policies for selected countries which delivers the
Chapter # 6 Conclusions and Policy Recommendations
216
dynamics of these indicators. We have discussed the volatility of fiscal, monetary and
liberalization policies for each country. We have also discussed the cyclical behaviour of
fiscal and monetary policy and also of FDI and portfolio inflows as literature discusses
that one of the reasons for high volatility of these policies is their procyclical behaviour in
most developing countries.
Fourth chapter discusses the derivation of theoretical model, description of variables and
methodology. We have derived a dynamic panel data model to study the role of
institutions and policies in economic growth, following Mankiw et al. (1992), in the
empirics of neoclassical growth model. Derived model shows the effect of institutions and
policies (stabilization and liberalization policies) on economic growth along with
traditional factors and convergence. We have further manipulated our equation according
to our objectives.
Main sources of the data are the World Bank (World Development Indicators),
International Financial Statistics (IFS), Pen World Tables (8.0), Asian Development Bank
(ADB), World Governance Indicators (WGI), Chinn and Ito (2008) and Lane and Ferretti
(2007).
Considering the unobserved country specific effects and econometric problems related to
the possible endogeniety of explanatory variables with the growth we use dynamic panel
data GMM method of estimators developed by Holtz-Eakin, Newey, and Rosen (1988),
Arellano and Bond (1991), and Arellano and Bover (1995).
Fifth chapter provides the detailed empirical results and discussion. Before the empirical
estimation we have tested the reliability of the data through descriptive statistics.
Moreover the pair wise correlation explains the linear relationship between two variables.
We have also tested the stationarity properties of the data through Im, Pesaran and Shin
Chapter # 6 Conclusions and Policy Recommendations
217
(IPS) test. Regarding the empirical results of GMM we explain these according to our
objectives below.
6.1.1 Effect of institutions and policies on economic growth:
To fulfill our first objective we examine empirically the effect of institutions and policies
on economic growth. The result provides the evidence of conditional convergence.
Traditional growth variables; physical and human capital and population growth also
follow the empirical literature. Physical capital increases the growth rate by increasing the
economic activities. Human capital affects the economic growth through quality
improvements in labour. Population growth reduces the economic growth by increasing
the consumption and reducing the savings. Institutional quality promotes the economic
growth by creating an environment for capital creation. Results regarding the fiscal policy
support the Keynesian hypothesis. Capital expenditures positively contribute to economic
growth by providing necessary infrastructure for the encouragement of private sector
investment. Current expenditures adversely affect the economic growth by reducing the
incentive for investment, higher tax-finance outweighs the utility derived from it. Tax
revenues also positively affect the economic growth by increasing the ability of the
government to finance its expenditures. Results regarding the monetary policy support the
Monetarists hypothesis, monetary policy do affect the economic growth through aggregate
demand. Results show that contractionary monetary policy reduces the investment and
economic growth. Trade liberalization positively contributes to economic growth. Trade
openness as a proxy of trade liberalization positively affects the economic growth through
externality as common in the literature. Reduction in the tariff rate also positively
contributes to economic growth. Disaggregated analysis shows that liberalization of
capital goods increases the economic growth by stimulating the investment while
liberalization of consumer goods is unrelated to economic growth. Regarding the financial
Chapter # 6 Conclusions and Policy Recommendations
218
liberalization both De jure and De facto measure show that it negatively affects the
economic growth. In developing countries financial liberalization increases the risk of
crisis. Additionally large and unanticipated inflows induce higher consumption, inflation
and unmanageable current account deficits. Disaggregated analysis shows that FDI
inflows positively contribute to economic growth being long term and stable investment
while short term investment (portfolio equity and debt) negatively contribute to economic
growth due to higher reversal rate.
6.1.2 Disaggregated institutions:
Disaggregated analysis of institutional variables show that higher economic and political
freedom increases the rate of private investment, productivity and growth. Political
stability is unrelated to economic growth as political stability alone cannot affect
economic growth without institutional set up and government development strategies.
There is direct association between improved quality of government services and
economic growth. Regulatory quality is also positively related to economic growth.
Through regulatory framework state affects the performance of the private sector. Rule of
law and economic growth are also positively related. A better judicial system fosters the
economic growth by enforcing the property rights which are necessary for the increase in
private investment, moreover it keeps the checks and balances on the government, controls
the corruption. Corruption retards the economic growth because it reduces the efficient
allocation of resources.
6.1.3 Effect of policy volatility on economic growth:
Our second objective evaluates the link between policy volatility and economic growth.
Results show that volatility of domestic macroeconomic policies brings uncertainty
regarding investment decisions therefore reducing the growth. Volatility makes the
investors highly sensitive to policy change and the associated risks because of irreversible
Chapter # 6 Conclusions and Policy Recommendations
219
nature of certain investments. Volatility of the fiscal policy creates uncertainty about
future taxes and the future behavior of fiscal parameters which negatively affects the
behavior of economic agents. Uncertainty of the interest rate affects the firm’s profitability
by reducing the corporate investment especially when there is irreversibility. Access to the
external market has destabilized the economies of less developed countries because of
volatility associated with trade and capital flows. Volatility of both negatively affects the
economic growth by reducing the domestic and foreign investment.
6.1.4 Determinants of policy volatility:
Our last objective is to emphasize on the role of institutions in enhancing the policy
stability. Institutions play an important role to reduce policy volatility by putting controls
or check and balances on policy makers and providing an environment favorable to good
policies. Regarding the fiscal policy volatility institutional constraints make it difficult for
the governments to frequently change the policy. Regarding monetary policy volatility an
independent central bank can provide more consistent policy by reducing the uncertainty,
in addition to lower inflationary outcome. Furthermore, high institutional quality enables
countries to apply counter-cyclical monetary and fiscal policies. As for as the volatility of
capital flows is concerned it is argued that low institutional quality has less ability to deal
with economic shocks. High institutional quality enables countries to stabilize financial
markets and capital flows. Good institutions make the trade flows stable through greater
predictability which reduces the trading cost. Sound regulation, low corruption and
effective law enforcement facilitate the trade flows.
Above and beyond the institutions there are some other domestic and global factors that
affect the volatility of domestic macroeconomic policies; these include per capita income
which embodies the level of development of a country, inflation volatility which
represents the macroeconomic uncertainty, financial sector development work as shock
Chapter # 6 Conclusions and Policy Recommendations
220
absorber, external debt, exchange rate instability, export concentration and some external
factors which include foreign growth volatility, term of trade volatility and foreign interest
rate volatility.
Higher the level of development lower the volatility of domestic macroeconomic policies
due to less market imperfections, macroeconomic stability, exchange rate and financial
market stability, larger automatic stabilizers and independence of the central bank etc.
Higher inflation volatility makes the domestic macroeconomic policies more volatile.
Higher external debt increases the volatility of fiscal policy inducing large fiscal
adjustment. Fiscal deficits and debt lead towards high and volatile inflation therefore
making monetary policy more volatile. Exchange rate instability makes the profits
uncertain which increase the uncertainty of the foreign capital flows and trade flows.
Financial market development reduces the volatility of capital flows by providing more
efficient risk diversification. Financial sector development also relaxes the liquidity
constraints facing by the firms and reduces the volatility of trade flows. Higher export
concentration increases the volatility of trade flows. A country with a large share of its
exports by producing a single good or closely related goods experience more instability in
exports than a country with diversified export base. World integration has increased the
exposure of lees developing countries to volatilities of global market. Access to external
market has exposed developing countries to volatilities prevailing in the world market.
These volatilities significantly affect the macroeconomic policies of the countries.
6.2 Policy recommendations:
The results presented in this study emphasize the importance of sensible long run growth
oriented policies. The important policy recommendations that stems from our analysis are
regarding the role of institutional quality, fiscal and monetary policies, trade and financial
liberalization in economic growth. Moreover, as we have also addressed the issue of
Chapter # 6 Conclusions and Policy Recommendations
221
policy volatility in developing countries so we will also discuss some policy implications
regarding policy volatility or uncertainty. Keeping in view the findings of the study we
propose some specific policy recommendations.
6.2.1 Institutions:
The subject matter of good governance and institutional reforms received attention in
developing countries in 1990s due to emergence of political and economic disorders.
Moreover increased globalization has raised the need for transparent, efficient and
responsive institutions. Institutional reforms lead to restructuring state institutions so that
they respect human rights, rule of law and are accountable to their constituents. To
encourage the private investment it is the responsibility of the state to create a suitable
legal and economic environment that ensure protection of property rights, strong judiciary
and improved transparency. There is also a role of external support as the World Bank and
the IMF are giving a great deal of attention to issues concerning the governance and
institutions. Regarding the institutional reforms it is needed to divide the reform areas into
basic and advanced reforms49
. The objective is to provide the guideline to authorities
towards the choice of a few specific areas in which reform would be both beneficial and
practicable given the political, institutional and capacity constraints facing the countries.
6.2.2 Fiscal policy:
Findings regarding government expenditures lead to the implication that given the
resource constraint a reallocation of government expenditures from current to capital
expenditures will increase the economic growth. It is needed to formulate the expenditures
such as to reduce the unproductive expenditures while enhancing public investment.
Developing countries already lack infrastructure like transport and communications, roads,
railways, electricity, gas etc. that help promote private capital accumulation. The
49 So-called “platform approach” proposed by Brooke (2003).
Chapter # 6 Conclusions and Policy Recommendations
222
government should increase its investment in areas that facilitate the private sector and
avoid from those that crowd it out. It is also argued that with capital expenditures there
comes rent seeking while current expenditure have less probability of this as these are on
fixed outlays. Institutional checks and balances can prevent this rent seeking behavior. As
tax revenue significantly contributes to economic growth therefore if a government wishes
to increase its revenue it should reduce the tax evasion and greater emphasis on collection
moreover to increase the tax base by reducing the tax exemptions.
6.2.3 Monetary policy:
Through its stabilizing role monetary policy plays a significant role in the welfare of an
economy. The interest rate channel of the monetary policy transmission mechanism
associates the fluctuations in in monetary aggregates to the economy. An expansionary
monetary policy decreases the financial constraints of private enterprises thus encouraging
the private investment. However, the financial redundancy following from expansionary
monetary policy leads to inefficient or unproductive investments by private enterprises;
investment in luxury consumer goods, real estate, gold and jewellery etc. Policy makers
should focus on improving corporate investment efficiency and to avoid over-investment.
Continuous fluctuations in interest rate bring uncertainty about return on investment and
may also decrease the confidence of investors.
6.2.4 Trade liberalization:
The policies should be emphasized towards more free trade and the abolition of trade
barriers. Corruption and rent-seeking associated with trade interventions can be reduced
with a free-trade regime. This will make the trade and investments opportunities more
attractive in a country. The government has to focus on motivating the development
through technology transfers to high growth sectors in developing countries because low
growth sectors have very little potential of productivity growth. Primary objective of
Chapter # 6 Conclusions and Policy Recommendations
223
relaxing the trade barriers should be to encourage the exports of less developed countries.
Liberalizing the imports of capital goods will increase the industrial efficiency and also the
manufacture exports.
6.2.5 Financial liberalization:
Given the harmful consequences of financial liberalization there is need to adopt
restrictive policy. Relative restrictive capital account regime of India and China provided
the protection against the East Asian crisis in 1997. The Indian policy placed emphasis on
encouraging larger non-debt flows, particularly foreign direct investment and longer-
maturity debt flows while having restrictions on short-term capital flows. Controls on
capital inflows can also serve to stabilize outflows. While discussing the effectiveness of
controls on inflows, there is also evidence of Chilean experience. During 1978-82 Chile
has imposed tax on short-term inflows which has stabilized these flows, without any
harmful effects on long-term flows of productive capital. The main purpose of the control
is to slow down the size of capital inflows and to change the structure of capital inflows
towards longer maturities. Certain pre conditions are also required to stabilize the capital
flows; a stable exchange rate policy, macroeconomic stability and a better institutional
framework which ensures transparency and accountability, regulatory quality and rule of
law. The Asian crisis highlighted the importance of the financial system.
6.2.6 Policy volatility:
As described in previous chapter that developing countries are more volatile and there are
three sources of their volatility first, the domestic factors or shocks second, exogenous
shocks and last, weak shock absorbers due to which exogenous factors have strong
influence on their macroeconomic volatility. Findings imply that domestic policy induced
volatility or uncertainty can be reduced by reducing macroeconomic instability indicated
by inflation volatility, achieving the exchange rate stability, higher export diversification,
Chapter # 6 Conclusions and Policy Recommendations
224
controlling the external debt or deficit, increasing the level of income and improving the
institutional quality. External shocks are beyond the control of domestic economies but
their affect can be minimized by strengthening the economy’s shock absorbers, stable
macroeconomic policies and improved financial sector.
As our central concern is related to the role of institutions in reducing policy volatility
therefore there is need of strong fiscal, monetary and economic institutions. Fiscal
institutions put constraints on the governments and generate the fiscal policy which is
highly predicable. Monetary institutions provide more consistent policy in addition to
lower inflationary outcome. Sound regulation, low corruption and effective law
enforcement stabilize the financial and trade flows.
6.3 Limitations and future research directions:
All the studies have some limitations which should be regarded while explaining the
results and present study is no exception. Limitations will provide some directions for
future research. Like in most empirical studies there are the issues of the quality or
reliability of data which can affect the reliability of results. There is limitation of the data
of institutional quality, which is subjective and more prone to measurement error as it
depends upon the rating of experts. Subjective measures of capital account liberalization,
de jure measures, also increase the possibility of measurement error. Regarding
institutional quality variable we have considered only formal institutions while ignoring
the informal institutions thus by allowing the other category of institutions will provide the
significance of each in economic growth. Regarding fiscal policy indicator we have
disaggregated the government expenditures by type not by function which can provide a
more comprehensive analysis regarding each functional category. Moreover we have also
taken total tax revenue as an indicator of fiscal policy. We can further disaggregate the tax
into its direct and indirect tax components which will provide the significance of different
Chapter # 6 Conclusions and Policy Recommendations
225
taxes in economic growth. Regarding the effect of capital account liberalization on
economic growth the study can also test the hypothesis about sequencing of capital
account by introducing the interaction term regarding trade openness, financial
development, institutional quality, level of development etc. to determine the most
effective channel of capital account liberalization. Regarding monetary policy we have
used interest rate as one of the channel of monetary transmission mechanism. We can also
include other channels of monetary transmission mechanisms to determine the most
reliable one. Regarding the data of physical capital stock we have used gross fixed capital
formation of the private sector which is commonly used in the literature. We can improve
our study in the future by using capital stock itself. We could update our data set including
more countries. Study can be extended by adding different regions which will provide
more insight on the comparative significance of alternative government policies in
different regional context. Last, we could also apply additional estimation methods
commonly used in empirical literature for robustness analysis.
It is not possible to include everything in a single study hence limitations are definite. By
incorporating these limitations we can further extend the study in future.
226
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Appendix I: Percentile score of countries at governance index (2014)
sr # Country Name 2014 sr # Country Name 2014 sr # Country Name 2014 sr # Country Name 2014 sr # Country Name 2014
1 New Zealand 98.79 46 Virgin Islands (U.S.) 76.43 91 Tonga 55.13 136 Dominica 37.15 181 Cuba 21.87
2 Georgia 98.22 47 Benin 76.41 92 Trinidad and Tobago 55.07 137 Haiti 37 182 Pakistan 20.95
3 Switzerland 97.58 48 Angola 76.26 93 Serbia 54.4 138 Vietnam 36.81 183 Kenya 18.88
4 Norway 96.22 49 Reunion 76.17 94 Iraq 53.47 139 Malawi 36.64 184 Congo, Dem. Rep. 17.82
5 Sweden 95.57 50 Slovenia 75.9 95 Rwanda 52.14 140 Bangladesh 36.29 185 Chad 17.42
6 Lao PDR 95.5 51 Mauritius 75.81 96 Korea, Dem. Rep. 51.78 141 Swaziland 33.36 186 Tajikistan 16.49
7 Netherlands 95.08 52 Finland 75.53 97 Greece 51.77 142 Cayman Islands 33.26 187 Congo, Rep. 16.23
8 Colombia 94.68 53 Spain 74.28 98 Algeria 50.88 143 Nauru 33.23 188 Aruba 15.91
9 Equatorial Guinea 94.43 54 Slovak Republic 74 99 Antigua and Barbuda 50.87 144 Tanzania 33.22 189 Uzbekistan 15.45
10 Liberia 94.12 55 Macao SAR, China 73.95 100 Burkina Faso 50.48 145 West Bank and Gaza 33.12 190 Nigeria 14.79
11 Bermuda 93.7 56 Kyrgyz Republic 73.92 101 Palau 50.04 146 Guam 32.87 191 Turkmenistan 14.02
12 Albania 93.48 57 Croatia 72.8 102 Hong Kong SAR, China 49.75 147 Guinea-Bissau 31.75 192 Eritrea 13.58
13 Grenada 92.02 58 Puerto Rico 72.35 103 Turkey 49.53 148 Papua New Guinea 31.58 193 Hungary 13.52
14 Italy 91.87 59 Brunei Darussalam 72.34 104 Mongolia 49.47 149 Nicaragua 30.9 194 Guyana 10.69
15 Jersey, Islands 91.86 60 St. Vincent 72.11 105 Senegal 49.26 150 Paraguay 30.76 195 Myanmar 10.31
16 Iceland 89.79 61 Dominican Republic 71.63 106 Maldives 48.19 151 Mozambique 30.74 196 Zimbabwe 9.863
17 Iran, Islamic Rep. 89.75 62 Cabo Verde 71.18 107 Cote d'Ivoire 48.19 152 Libya 29.68 197 Venezuela, RB 9.32
18 Gambia, The 88.83 63 United Arab Emirates 71.03 108 Lesotho 47.96 153 Azerbaijan 29.68 198 Cambodia 8.951
19 Argentina 88.72 64 Samoa 69.98 109 Saudi Arabia 46.54 154 Uganda 29.31 199 Kazakhstan 8.473
20 Singapore 88.31 65 St. Lucia 69.78 110 Gabon 46.52 155 Guinea 29.29 200 Yemen, Rep. 8.457
21 United Kingdom 88.29 66 Qatar 69.69 111 Suriname 46.18 156 Ethiopia 29.03 201 Estonia 8.292
22 San Marino 88.18 67 Jamaica 69.37 112 Botswana 45.61 157 Russian Federation 28.8 202 Cook Islands 8.15
23 Indonesia 87.95 68 Ireland 69.05 113 Philippines 45.36 158 Bolivia 28.69 203 Afghanistan 7.84
24 Bahrain 86.39 69 Israel 66.91 114 Sri Lanka 44.72 159 American Samoa 28.6 204 Canada 6.546
25 Belize 85.37 70 Malaysia 66.43 115 Morocco 44.23 160 Czech Republic 28.2 205 Sudan 5.31
26 Fiji 84.35 71 Denmark 66.15 116 Jordan 44.01 161 Cyprus 27.87 206 Liechtenstein 4.72
27 United States 84.08 72 China 66.11 117 Thailand 43.96 162 Madagascar 27.71 207 Central African Republic 4.682
28 Malta 83.9 73 Bahamas, The 65.23 118 Tunisia 43.89 163 Ukraine 26.8 208 Syrian Arab Republic 3.778
29 Australia 83.86 74 Guatemala 63.74 119 Macedonia, FYR 43.85 164 India 26.7 209 Kosovo 3.628
30 Burundi 83.04 75 St. Kitts and Nevis 63.58 120 Mexico 43.49 165 Nepal 26.69 210 South Sudan 2.269
31 Ghana 82.66 76 Namibia 61.91 121 Djibouti 43.33 166 Niger 26.54 211 Somalia 0.726
32 Greenland 82.28 77 French Guiana 61.31 122 Brazil 43.15 167 Timor-Leste 26.47
33 Taiwan, China 81.34 78 Germany 61.08 123 Belarus 43.13 168 Comoros 25.78
34 Ecuador 79.67 79 Oman 60.2 124 Marshall Islands 43.02 169 France 25.71
35 Portugal 79.14 80 Bhutan 60.08 125 Peru 42.96 170 Mali 25.02
36 Austria 79.03 81 South Africa 59.88 126 Zambia 42.57 171 Sierra Leone 23.93
37 Uruguay 78.83 82 Romania 58.97 127 Moldova 42.01 172 Bosnia and Herzegovina 23.53
38 El Salvador 78.57 83 Seychelles 58.39 128 Barbados 41.61 173 Kuwait 23.49
39 Anguilla 78.44 84 Montenegro 58.08 129 Japan 41.29 174 Luxembourg 23.19
40 Kiribati 78.1 85 Korea, Rep. 57.48 130 Latvia 40.04 175 Egypt, Arab Rep. 22.75
41 Chile 78.03 86 Vanuatu 57.37 131 Bulgaria 39.41 176 Armenia 22.51
42 Martinique 77.37 87 Panama 57.23 132 Solomon Islands 38.39 177 Togo 22.28
43 Monaco 77.27 88 Cameroon 57.13 133 Belgium 38.21 178 Andorra 22.22
44 Poland 77.13 89 Tuvalu 56.49 134 Honduras 38.18 179 Lithuania 22.19
45 Lebanon 76.78 90 Micronesia, Fed. Sts. 55.84 135 Sao Tome and Principe 38.06 180 Mauritania 22.01
Source: World Governance Indicators (World Bank)
248
Appendix II: Summary of literature review
Institutions and economic growth author country technique institutional measures main objective main findings
Mauro (1995),
Mauro (2002)
67 countries
(1980-83)
OLS and
instrumental
variables
Data of Business International (BI)
indices on corruption, bureaucratic
inefficiency and judicial system.
Association between
corruption and economic
growth.
Corruption reduces the economic growth by
reducing the private investment.
Knack and
Keefer (1995)
Cross country
(1974-89)
OLS and
instrumental
variables
Expropriation risk and rule of law from
ICRG, contract enforcement from BERI.
Link between property rights
protection and economic
growth.
Property rights increase the investment and
economic growth.
Goldsmith
(1995)
59 less
developed
countries.
(1988-93)
OLS
regression
Freedom House and Heritage
Foundation
Correlation between
institutions and economic
growth.
Both the political freedom (democracy) and
property rights positively contribute to
economic growth.
Kaufmann et
al. (1999)
Cross country OLS and
instrumental
variables
six aggregate aspects of the governance;
voice and accountability, political
stability and violence, government
effectiveness, regulatory quality, rule of
law, and control of corruption developed
by Kaufmann et al. (1999)
Relationship between
governance and economic
growth.
Better governance is associated to higher
development, such as higher per capita
income, lower mortality rate and higher
literacy rate.
Campos and
Nugent (1999)
Panel of Latin
America and
East Asia
(1982-95)
OLS
regression
International Country Risk Guide
(ICRG), Business Environmental Risk
Intelligence (BERI), polity III
Effect of institutions on
development; per capita
income, infant mortality rate
and adult literacy.
For Latin America rule of law significantly
contributes to development in all
specifications while in East Asia bureaucratic
efficiency plays its role.
Kaufmann et
al. (2002)
Cross country
(2000-01)
OLS and
instrumental
variables
Kaufmann et al. (1999) Correlation between
institutions and economic
growth.
A robust positive correlation between per
capita income and institutional quality while
a weak negative correlation running in the
opposite direction.
Glaeser et al.
(2004)
Cross country
(1960- 2000)
OLS and
instrumental
variables
risk of expropriation by the government
from the ICRG, government
effectiveness by Kaufmann et al.(2003),
restraints on the executive from the
Polity IV
Link between institutions and
economic growth.
Economic growth leads to institutional
development.
Chong et al.
(2004)
Panel of Latin
American
countries
(1970-1995)
Fixed effect International Country Risk Guide
(ICRG), Business Environmental Risk
Intelligence (BERI) and contract
intensive Money (CIM).
Association between
institutions and economic
growth.
All the aggregated and disaggregated
indicators of institutional quality are
positively related to economic growth.
249
Drury and
Lusztig (2006)
More than
100 countries
(1982–97)
OLS
regression Freedom House Relationship between
corruption, democracy and
economic growth.
Democracy indirectly affects the economic
growth while corruption has direct and
negative impact on economic growth.
Siddique and
Ahmed (2010)
Pakistan
(1984-2006)
Johansen
cointegration,
Granger
causality
Index of institutionalized social
technologies.
Impact of institutional quality
on economic growth. There is long run relation between
institutions and economic growth moreover
causality goes from institutions to economic
growth.
Gani (2011) Panel of 84
developing
economies
(1996 – 2005)
OLS
regression
Worldwide Governance Indicators,
(Kaufmann et al., 2010).
Relationship between
governance and economic
growth.
Political stability and government
effectiveness are directly associated to
economic growth whereas voice and
accountability and corruption are inversely
related.
Haider et al.
(2011)
Pakistan regression Index of Corruption, Index of
Governance.
Outcome of political
instability, governance and
corruption on inflation and
growth.
High corruption and poor governance cause
high inflation and low growth. Both
corruption and weak governance coincide
with political instability during the
democratic regimes.
Ahmad and
Marwan
(2012)
69
developing
countries
(1985-2008)
GMM, Fixed
effect
International Country Risk Guide
(ICRG), Gastil index and polity II.
Relationship between
institutions and economic
growth.
Property rights protection appears as the
highly significant institutional indicator to
affect the growth for whole sample as well as
for East Asia. Albassam
(2013)
All countries
listed on
(WGI)
(2006-11)
correlations Kaufmann et al. (1999) Whether the crisis and the
level of development affect
the relationship between
governance and growth?
Economic crisis has not affected the
relationship between governance and growth
but the level of development of the countries
does affect it.
Fayissa et al.
(2013)
Panel of 28
Sub Saharan
African
countries
(1990-2004)
Fixed effect
and random
effect, quintile
regression.
Worldwide Governance Indicators,
(Kaufmann et al., 2010).
Link between governance
and economic growth. Both the aggregate and disaggregate
measures of governance positively
contributes to economic growth.
Yerrabati and
Hawkes
(2015)
South Asia,
East Asia and
Pecific.
(1980-2012)
Meta
regression
analysis.
Worldwide Governance Indicators,
(Kaufmann et al., 2010). Relationship between
governance and economic
growth.
Voice and accountability and corruption are
positively associated with economic growth.
Political stability, government effectiveness,
regulation and rule of law are negatively
correlated to growth. Bhattacharjee
et al.(2015)
Panel data of
South Asia
(1996-2010)
Fixed effect
and dynamic
panel GMM.
Worldwide Governance Indicators,
(Kaufmann et al., 2010).
Relationship between
institutions and economic
growth.
Voice and accountability and government
effectiveness contribute to economic growth
while others measures remain insignificant.
250
Financial liberalization and economic growth author country technique financial liberalization measures main objective main findings
Alesina, Grilli
and Milesi-
Ferretti (1993),
Grilli and
Milesi-Ferretti
(1995)
20 high-income
countries.
61 developing
countries from
1950s to the 1990s.
Instrumental
variables. Binary measure for capital account
liberalization constructed by the
IMF.
Relationship between capital
account openness and
economic growth.
Capital account openness is directly
associated to economic growth for
developed countries while there is
negative association for developing
countries.
Quin (1997)
Quin(2008) 65 developed and
developing
countries.
(1958-89)
Instrumental
variables. De Jure indicators of capital account
openness. Relationship between capital
account openness and
economic growth.
Capital account openness positively
contributes to economic growth alike in
developed and developing countries.
Rodrik (1998) 100 industrial and
developing
countries.
(1975-1989)
Binary measure for capital account
liberalization constructed by the
IMF.
Relationship between capital
account openness and
economic growth.
No relationship between capital account
liberalization and economic growth.
Edwards
(2000)
20 emerging
economies during
the 1980s.
Instrumental
variables.
Quinn’s indicator of capital account
liberalization.
Association between capital
account openness and
economic growth.
The positive impact of an open capital
account depends on the level of
development.
Klein and
Olivei (2001)
Cross section of
developed and
developing
countries.
(1986-95)
Instrumental
variables.
De Jure indicators of capital account
liberalization; IMF capital account
openness.
Relationship between capital
account openness and
economic growth through
financial development.
Capital account liberalization contributes
to economic growth through financial
deepening only in developed countries.
The relationship does not hold in
developing countries.
Arteta et al.
(2001)
61 developed and
developing
countries.
Instrumental
variables Quinn’s index and IMF capital
account openness measure.
Correlation between capital
account openness and
economic growth.
Capital account openness contributes to
growth only in countries having strong
institutions.
Reisen and
Soto (2001)
Panel of 44
developing
countries.
(1986–97).
Instrumental
variables.
Disaggregated capital inflows. Association between capital
inflows and economic growth.
Foreign direct investment and portfolio
equity inflows contribute to economic
growth.
McLean and
Shrestha
(2002)
40 developed and
developing
countries
(1976-95)
Instrumental
variables.
Capital inflows also disaggregated
into FDI inflows flows, portfolio
inflows and bank inflows.
Effect of capital account
openness on economic growth.
FDI and portfolio flows positively
contribute to growth.
Edison et al.
(2002)
Panel of 57
countries
(1980-2000)
OLS,2SLS,
GMM
De Jure and de facto indicators of
capital account liberalization.
Impact of capital account
openness on economic growth. No robust association between financial
openness and economic growth.
251
Eichengreen
and Leblang
(2003)
21 countries.
(1880-1997)
Instrumental
variables.
Capital controls is captured by
presence or absence of control
during the initial year of each period
while for recent years, IMFs binary
indicator is utilized.
Relationship between capital
account openness and
economic growth in the
presence of crisis.
Capital account openness hurts the
growth in the presence of crisis.
Singh (2003) 118 developed and
developing
countries.
(1972-98)
Instrumental
variables.
FDI flows, portfolio flows and debt
flows
Relationship between capital
account openness and
economic growth.
Long run capital flows (FDI) positively
contributes to economic growth.
Bekaert et al.
(2005)
panel of 95
countries
(1980-97)
Fixed effects,
time effects,
GMM
De Jure indicators of capital account
openness; Bekaert and Harvey
(2002), IMF capital account
openness, Quinn (1997), first sign
indicator and capital intensity
measure.
Relationship between capital
account openness and
economic growth.
Capital account openness positively
contributes to economic growth in
different specifications.
Bonfiglioli
(2005)
93 countries.
(1975 to1999)
Instrumental
variables. De jure measure for capital account
liberalization as well as for equity
market liberalization.
Effect of capital account
openness on economic growth
through productivity and
investment.
Financial openness has a little and non-
robust effect on investment while it
boosts productivity growth. Capital
account liberalization enhances the
possibility of banking crises in developed
countries only.
Mody and
Murshid
(2005)
60 developing
countries.
(1979-99)
Instrumental
variables. Aggregate capital flows and also
their components; foreign direct
investment, portfolio flows and
bank loans; liberalization dates.
Relationship between capital
flows and investment. FDI flows significantly contribute to
investment and their effect can be
enhanced through better policy
environment.
Kim et al.
(2012)
Panel of 70
developed and
developing
countries.
(1960-2007)
PMG,MG de facto measure of financial
liberalization; external financial
stocks and FDI stocks
Impact of capital account
openness on economic growth. In long run both are positively related but
in short run both are inversely related.
252
Trade liberalization and economic growth author country technique trade liberalization measures main objective main findings
Sachs and
Warner (1995)
Cross section of
117 countries
(1970-1989)
regression Sachs and Warner Index (1995) Relationship convergence and
economic policies.
Open trade regimes increase the growth and
convergence.
Harrison and
Hanson (1999)
Cross country
(1970-98)
regression Sachs and Warner (1995) Effect of trade liberalization on
economic growth, employment
and wages.
No association between trade liberalization
and economic growth. Liberalization has
very small impact on employment and it
increases the wage inequality.
Rodriguez and
Rodrik (2000) Trade liberalization and
economic growth.
There is no robust correlation between trade
liberalization and economic growth due to
misspecification and misleading proxies of
liberalization.
Zhang (2001) 10 East Asian
economies from
1960 to 1996
regression Exports as a ratio to GDP. Link between trade
liberalization, convergence and
economic growth.
There is evidence of weak convergence due
to world integration.
Greenaway et
al. (2002)
73 developing
countries from
1975-93.
GMM Sachs and Warner (1995), Dean et
al. (1994) and one based on World
Bank (1993).
Effect of trade liberalization on
economic growth.
Trade liberalization positively contributes to
economic growth.
Wacziarg and
Welch (2003)
141 countries.
(1970-99)
Fixed effect. Dummy variable approach as
developed by Sachs and Warner
(1995) but with extended data set,
liberalization dates.
Effect of trade liberalization on
economic growth.
Trade liberalization contributes to economic
growth, investment and trade openness.
Goldar and
Kumari (2003)
India
(1981-98)
Effective protection rate, non-tariff
barriers.
Relationship between import
liberalization and productivity
growth in manufacturing sector.
Import liberalization increases industrial
productivity.
Dollar and
Kraay (2004)
39 developing
countries
(1975-97)
regression Changes in trade volumes indicate
the liberalization.
Trade liberalization, poverty
and economic growth. Globalization leads to faster growth and
poverty reduction.
Aksoy Ataman
(2006)
39 developing
countries.
(1970-2004)
Fixed effects Dummy variables representing
liberalization dates from World
Bank’s Trade Assistance
Evaluation.
Effect of trade liberalization on
economic growth. Trade liberalization contributes to economic
growth. Moreover, trade liberalization also
increases investment and manufacture
exports by increasing export diversification.
Yasmin et al.
(2006)
Pakistan
(1960-2003)
2SLS Two measures of trade
liberalization; trade-GDP ratio and
import duties.
Effect of trade liberalization on
economic development; per
capita GDP, income inequality,
poverty and employment.
Liberalization has reduced the GDP per
capita. It has increased the employment
level while it has no effect on poverty and
distribution of income has become worse.
253
Morgan and S.
Kanchanahatakij
(2008)
37 liberalising
countries.
(1970-98)
Fixed effect. Dummy representing date of
liberalization, ratio of trade taxes
to GDP.
Relationship between trade
liberalization and economic
growth.
Positive relationship between trade
liberalization and economic growth.
Chang et al.
(2009)
Panel of 82
developed and
developing
countries.
(1960–2000)
GMM Two measure of outward
orientation; trade openness and
import duties.
Relationship between trade
liberalization and economic
growth.
Trade liberalization contributes to faster
growth but its effect can be enhanced by
undertaking macroeconomic and
institutional reforms.
Ghani (2011) 24 OIC
countries
(1970-2001)
regression Dummy variable that equals zero
before liberalization and one after
liberalization.
Effect of trade liberalization on
economic performance (GDP
per capita, exports and imports)
Liberalization increases the GDP per capita
but exports, imports and trade has not
improved much after liberalization.
Mani and Afzal
(2012)
Bangladesh
(1980-2010)
regression Liberalization is measured as trade
as a ratio to GDP.
Impact of trade liberalization
on economic performance;
growth, inflation, exports and
imports.
Trade liberalization boost economic growth,
real exports and imports. While
liberalization has no effect on inflation.
Falvey et al.
(2013)
Panel data for 58
developing
countries.
(1970-2005)
Sachs-Warner index of trade
Liberalization. Association between trade
liberalization and economic
growth.
Trade liberalization enhances economic
growth through four channels; investment,
government finance, trade openness and
price variations.
Paudel, R. C.
(2014)
panel data of
193countries
(1985-2010)
Fixed effects. Sachs and Warner Index updated
by countries and time period. Link between trade
liberalization and economic
growth.
Trade liberalization positively contributes to
economic growth but its effect also depends
on the level of development of countries.
254
Fiscal policy and economic growth author country technique fiscal policy measures main objective main findings
Barro (1989) Cross section of
120 countries.
(1960-85)
regression Disaggregated government
expenditures.
Relationship between
growth, savings and
government
expenditures.
Public investment increases the investment and
growth while public consumption reduces both.
Engen and
Skinner (1992)
107 developed
and developing
countries.
(1970-85)
Regression Change in government
expenditures as a ratio to
GDP, government
expenditures as a ratio to
GDP, change in tax rate,
average tax rate.
Effect of fiscal policy on
economic growth.
Government expenditures and taxation both are
negatively related to economic growth.
Easterly and
Rebelo (1993)
Cross section of
100 countries.
(1970-1988)
regression Aggregated and disaggregated
expenditures and revenues.
Impact of fiscal policy
on economic growth.
Government investment is positively correlated with
investment and growth. Investment on transportation
and communication is robustly related to growth. In
poor countries indirect taxes contribute to growth
while in developed countries direct taxes.
Sattar (1993) Asian developing
countries.
(1950-85)
regression Government consumption
expenditures.
Effect of government
expenditures on
economic growth
Government consumption expenditures positively
contribute to economic growth for Asian developing
countries. Efficiency enhancing role of government
outweighs the efficiency reducing role.
Devarajan et al.
(1996)
Panel of 43
developing
countries.
(1970-90)
Regression Disaggregated current and
capital expenditures.
Association between
public outlays and
economic growth.
Positive association between current expenditures
and economic growth while a negative association
between capital expenditures and growth. Defence,
infrastructure, education and health expenditures are
negatively related to growth. Guseh (1997) 59 middle income
developing
countries.
(1960–85)
fixed effects Growth of consumption
expenditure, growth in the
relative size of expenditure.
The effect of government
size on economic growth
across political and
economic systems.
Government size reduces the economic growth but
growth rate slows down more in nondemocratic and
socialist system.
Gupta et al.
(2002)
31 low income
countries.
(1990-2000)
Feasible
generalised
least squares
(FGLS),
GMM
Disaggregated current
expenditures, capital
expenditure, and tax and non-
tax revenues.
Relationship between
fiscal adjustment,
structure of expenditures
and economic growth.
Fiscal composition shows that expenditures on wages
and salaries are negatively related to growth while
expenditures on other goods and services and capital
expenditures foster the growth.
255
Bose et al.
(2003)
Panel of 30
developing
countries.
(1970-90)
Seemingly
unrelated
regression
(SURE).
Disaggregated current and
capital expenditures. Relationship between
public expenditures and
economic growth.
Capital expenditures positively contribute to growth
while current expenditures remain insignificant.
Expenditures on education contribute to growth
while expenditures in other sectors (transport and
communication, defence) do not remain robust.
Kukk Kalle
(2007)
Panel of 52
developed and
developing
countries.
regression Disaggregated expenditures
and taxes. Effect of fiscal policy on
economic growth. Current expenditures retard economic growth while
investment expenditures enhance economic growth.
Tax revenue and indirect taxes positively contribute
to economic growth.
Alam and Butt.
(2010)
Panel of
developing
countries.
(1970-2005)
GMM and
panel
cointegration.
Education, health and social
security expenses.
Correlation between
social expenditures and
economic growth.
Long run relationship among education, health and
social security expenses and economic growth.
Ali and Ahmad
(2010)
Pakistan
(1972-2008)
ARDL Fiscal deficit Effect of fiscal policy on
economic growth.
Fiscal deficit is inversely related to economic growth
in the long run.
Gallo and
Sagales (2011)
Panel of 43 upper,
middle and high
income countries.
(1972-2006)
Instrumental
variables.
Disaggregated expenditures
and taxes. Contribution of fiscal
policy in economic
growth and inequality.
Higher consumption expenditures and direct taxes
reduce the economic growth and inequality whereas
investment expenditures reduce the inequality
without reducing growth.
Acosta
Ormaechea and
Yoo (2012)
69 high, middle
and low income
countries.
(1970-2010)
Pooled Mean
Group (PMG)
Tax revenue as a percentage
of GDP, tax-composition
variables as a share of total tax
revenue.
Relationship between tax
composition and
economic growth.
Direct taxes specifically income tax negatively
contributes to economic growth while indirect taxes;
VAT and sales taxes significantly contribute to
growth.
Ormaechea and
Morozumi
(2013)
56 low, medium
and high income
countries.
(1970-2010)
GMM, fixed
effects.
Total expenditures and
disaggregated into defence,
education, health, social
protection and transport and
communication spending.
Link between public
expenditures and
economic growth.
Reallocation of expenditures, an increase in
education spending by a fall in social protection
significantly contributes to economic growth.
Aggregate spending negatively contributes to growth.
Gangal and
Gupta (2013)
India.
(1998-2012)
Cointegration
and Granger
Causality.
Aggregate public
expenditures.
Connection between
public expenditures and
economic growth.
Aggregate public expenditures are positively
associated with growth.
Morozumi and
Veiga (2014)
80 developed and
developing
countries.
(1970-2010)
GMM Aggregated and disaggregated
expenditures and revenues.
The role of institutions in
spending growth
relationship.
Findings show that capital expenditures significantly
contribute to economic growth when complement
with institutional quality. Current expenditure does
not show robust growth enhancing effect. Aggregate
spending and revenues positively contributes to
growth.
256
Monetary policy and economic growth author country technique Monetary policy measures main objective main findings
Christiano et al.
(1996)
US
(1960Q1-1992Q4)
VAR Federal funds rate, non-
borrowed reserves.
Effect of monetary policy
shocks on different sectors of
the economy.
Monetary shock affects the macroeconomic
aggregates; decline in real GDP, employment,
retail sales, non-corporate financial profits and a
sharp decline in prices. It increases the
unemployment and manufacturing inventories.
Fatima and
Iqbal (2003)
5 developing
countries from South
and East Asia.
(1970-2000)
Cointegration,
Granger
causality.
Money supply and
government expenditures as
indicators of monetary and
fiscal policy respectively.
Relative effectiveness of
fiscal and monetary policies.
In case of Indonesia, Pakistan and India only
monetary policy is powerful while in case of
Malaysia and Thailand both fiscal as well as
monetary is effective.
Cheng (2006) Kenya.
(1976-2005)
VAR Short term interest rate. Effect of the interest rate on
output, prices and exchange
rate.
A contractionary monetary policy shock reduces
the prices but has insignificant effect on output.
Moreover it appreciates the exchange rate.
Ali et al. (2008) South Asian
countries.
(1990-2007)
ARDL Fiscal balance and broad
money represent fiscal and
monetary policy
respectively.
Relative significance of fiscal
and monetary policies.
Monetary policy is an effective tool than fiscal
policy in order to boost economic growth.
Buigut (2009) East African
countries.
(1984-2005)
VAR Short term interest rate. Effect of the interest rate
channel on output and prices.
Interest rate channel does not seem to be appear
so important as the monetary policy shock
remains insignificant while it has a very small
effect on inflation.
Gul et al. (2012) Pakistan
(1995-2010)
regression interest rate Linkage between monetary
policy instruments and
economic growth.
Tight or contractionary monetary policy in terms
of higher interest rate is inversely related to
economic growth by discouraging the private
investment.
Hussain and
Siddiqi (2012)
Pakistan
(1976 to 2008)
ARDL Fiscal policy: government
expenditures and revenues.
Monetary policy: money
supply and interest rate.
Institutions: civil liberty,
political rights and polity.
Relationship between fiscal,
monetary policies,
institutions and economic
growth.
Monetary policy is effective and economic
institutions play an important role in increasing
the per capita GDP growth. Fiscal policy,
political and social institutions have no
significant association with economic growth.
Coric et al.
(2012)
48 lower-middle,
upper-middle and
high-income
countries.
(1975-2009)
Regression,
Structural
VAR.
Money supply and domestic
interest rate.
Influence of monetary policy
shocks on output and prices.
In countries having more flexible exchange rate,
higher financial openness, larger financial sector
and greater share of trade in GDP a
contractionary monetary policy shock has a
larger negative effect on output and prices.
257
Younus (2013) Bangladesh (1980-
2011)
Cointegration
and Granger
Causality.
Broad money and
government expenditures
represent monetary and
fiscal policy.
Effectiveness of fiscal and
monetary policy on output
growth.
Monetary policy has relatively stronger impact
than that of fiscal policy on output growth.
Fetai (2013)
66 emerging
countries.
(1980 to 2010)
Regression,
GMM
Monetary policy: Discount
rate, international reserves.
Fiscal policy: budget
balance.
Relative effectiveness of
fiscal and monetary policies
during financial crises.
Fiscal policy is a more powerful tool than
monetary policy in the course of financial crisis.
Ivrendi and
Yildirim (2013)
Six emerging
economies.
(1995: M01-
2012:M08)
VAR Short term interest rate. Influence of monetary policy
shocks on macroeconomic
variables.
Contractionary monetary policy shock
appreciates the domestic currency, increases the
interest rate, controls the inflation, reduces the
output and trade balance.
Kandil (2014) 105 developing
countries.
(1968- 2008)
regression Money supply growth
represents monetary policy.
Effects of monetary policy
shocks on output and prices.
Positive monetary policy shocks increase the
real output growth, average trend growth and
reduce the variability of output. Demand side
channel portray a significant role.
258
Policy volatility and economic growth
author country technique measure of policy volatility main objective main findings
Fiscal policy volatility and economic growth Aizenman and
Marion (1991)
46 developing
countries.
(1970-85)
regression Standard deviation of the
residual through
autoregressive process
measures the volatility of
different measures of fiscal
and monetary policy.
Links between policy
uncertainty (fiscal and
monetary policy
uncertainty) and growth.
Policy volatility is inversely related to economic
growth.
Ramey and
Ramey (1995)
92 developed and
developing
countries (1960-
1985).
Fixed effects. Standard deviation of growth
rates of variables represents
volatility.
Analysis of government
spending volatility and
economic growth.
There is evidence of an inverse association
between government spending-induced volatility
and economic growth.
Gong and Zou
(2002)
90 developed and
developing
countries.
(1970-1994)
regression Variance of the growth rate of
public expenditures measures
volatility.
Consequences of public
expenditure volatility on
economic growth.
Volatility of both the current and capital
expenditures is inversely related to economic
growth.
Ali., M.
Abdiweli (2005)
90 developed and
developing
countries.
(1975-1998)
regression The standard deviation of the
residual measures the
volatility of aggregated and
disaggregated expenditures
and revenues.
Effect of volatility of fiscal
policy on economic growth.
Almost all the fiscal volatility measures are
negatively associated with economic growth.
Sirimaneetham
Vatcharin (2006)
65 developing
countries.
(1970-99)
regression Policy volatility is measured
by standard deviation of the
residual.
Effect of volatility of
macroeconomic, fiscal and
development policies on
economic growth.
Only macroeconomic volatility is inversely
related to economic growth while fiscal and
development policy volatility remain
insignificant in explaining the growth.
Davide Furceri
(2007)
116 developed and
developing
countries.
(1970-2000)
regression Standard deviation of the
government expenditure
measures the volatility.
Association between
cyclical volatility of
expenditures and long run
growth.
Government expenditure volatility is negatively
associated to long run growth of developing
countries whereas it has a smaller effect on
OECD countries.
Fatas and Mihov
(2008)
91 developed and
developing
countries.
(1960-2000).
Instrumental
variables.
Volatility of residual of
government spending
represents fiscal volatility.
Effect of fiscal policy
volatility on economic
growth, investment and
output volatility.
Volatility of fiscal policy leads to more volatility
of output, which in turn lowers investment and
leads to slower economic growth.
Afonso and
Jalles (2012)
Cross country.
(1970-2008)
GMM Standard deviation of
aggregate government
expenditures and revenues.
Link between fiscal
volatility, financial crisis
and economic growth.
Fiscal policy volatility lowers the economic
growth.
259
Monetary policy volatility and economic growth
Peterson (1998) 87 developed and
developing
countries.
(1968-92)
Comparison of
growth rates in
different
periods.
Standard deviation of money
supply growth.
Effect of monetary instability
on economic growth.
Higher money supply instability contributes to
slower growth.
Ismail et al.
(1999)
Malaysia.
monthly data from
(1998-2002)
regression Volatility is measured by
conditional variance of 3
month Treasury bill rate from
the GARCH.
Relationship between interest
rate uncertainty and economic
activity.
There is an inverse correlation between
interest rate uncertainty and aggregate output.
Bo and Sterken
(2002)
82 listed Dutch
listed firms.
(1984–1995)
Fixed effects The ARCH model of volatility
and the variance of the
residual through AR(1).
Effect of interest rate volatility
and debt on firm investment.
Higher interest depresses the firm investment
while the interest rate volatility shows
ambiguous result. Joint effect of interest rate
volatility and debt increases the investment.
Bloom and Bond
(2007)
UK
manufacturing
firms.
(1972-91).
GMM Standard deviation of daily
stock returns measure
volatility.
Dynamics of uncertainty and
investment both at aggregate
and also firm level.
Higher interest rate uncertainty decreases the
effect of demand shocks on investment.
Gulen and Ion
(2013)
data of 7861 US
firms from (1987-
2011)
Fixed effects Uncertainty index by Baker,
Bloom, and Davis (2012).
Relationship between
uncertainty and corporate
investment.
Policy uncertainty reduces the industry and
firm investment. Effect is stronger for firms
having higher degree of irreversibility,
financial constraints and less competitive.
Bretscher et al.
(2016)
Cross section of
1600 firms.
(1994-2014)
regression Uncertainty is measured by
treasury implied volatility.
Consequences of interest rate
uncertainty on investment
behaviour.
Uncertainty adversely affects the investment
both at the aggregate and firm level. The link
is stronger in more financially constrained and
levered firms.
Capital flows volatility and economic growth Lensink and
Morrissey
(2001)
88 developed and
developing
countries.
(1975-1998)
OLS
regression,
instrumental
variables.
Volatility is measured by
standard deviation of residual
from the autoregressive
process.
Link between FDI flows,
volatility and economic
growth.
FDI volatility has a negative effect on
economic growth.
Sulla and
Willett (2007)
35 emerging
economies.
(1990-2003)
OLS, Seeming
unrelated
regression
(SUR)
Standard deviation of capital
flows.
Reversal of various type of
capital flows.
Excluding FDI, all other capital flows exhibit
large reversals throughout crises. Reversals of
capital inflows have severe consequences in
the form of output losses.
Demir Firat
(2009)
3 emerging
economies.
(1991-2001)
GMM Standard deviation of net short
term net capital inflows
represents volatility.
Link between volatility of
short term capital flows and
private investment.
Volatility of the short term capital inflows is
inversely related to economic growth.
260
Ferreira and
Laux (2009)
Panel of 50
countries.
Fixed effects Standard deviation of the
residual of portfolio flows.
Link between portfolio flows,
volatility and growth.
Volatility does not have any detrimental effect
on growth.
Choong et al.
(2011)
5 ASEAN
countries.
(1974-2005)
ARDL Standard deviation of the
residual through AR (1)
process and EGARCH
represents the volatility of
FDI.
Relationship between foreign
direct investment volatility
and economic growth.
FDI volatility is negatively related to
economic growth in Indonesia, Malaysia,
Philippines and Thailand while it has a
negligible effect on Singapore.
Carp (2014) Emerging
economies.
(1991 – 2012)
Pearson
correlation.
Standard deviation of the
residual of capital flows.
Relationship between capital
flow volatility and economic
growth.
Volatile capital flows exert an adverse impact
on economic growth.
Neanidis (2015) 78 developed and
developing
countries.
(1973-2013)
Regression,
GMM
Standard deviation of capital
flows represents volatility.
Relation between volatile
capital flows and economic
growth.
Volatility of all the capital flows, aggregated
and disaggregated, (FDI, equity and debt
flows) are negatively related to economic
growth.
Trade flows volatility and economic growth Yotopoulos and
Nugent (1976)
Cross section of
38 developing
countries.
(1958-68)
regression Squared deviations represent
export instability.
Consequences of export
instability for economic
growth.
Export instability reduces the marginal
consumption thereby increasing savings and
higher growth.
Ozler and
Harrigan (1988)
26 developing
countries from
(1963-82)
regression Instability index is measured
by applying autoregressive
conditional heteroscedasticity
(ARCH) model.
Effect of export instability on
economic growth and
investment.
Findings exhibit that export instability is
negatively related to economic growth and
investment.
Love (1989) 20 developing
countries.
Granger and
Sims causality
Instability is measured by
absolute deviations from a
five-year moving average.
Impact of export instability on
income instability.
Export instability brings instability in capital
goods imports and, in turn, investment and
growth.
Gyimah-
Brempong
(1991)
34 Sab Saharan
African countries.
(1960-86)
regression The coefficient of variation
and the mean of the absolute
difference between actual and
estimated value.
Correlation between export
instability and economic
growth.
Export instability has a negative effect on
economic growth.
Sinha (1999) Nine Asian
countries.
(1950-97)
Johanson
cointegration.
Deviations of actual exports
from a five-year moving
average.
Reaction of export instability
to investment and economic
growth.
In some countries export instability is
negatively related to economic growth while
in others
there is evidence of a positive association.
Chaudhary and
Qaisrani (2002)
Pakistan
(1972-94)
regression Not mentioned. Association between trade
instability and economic
growth.
Export instability does not affect economic
growth and investment.
261
Kaushik et al.
(2008)
India
(1971 to 2005)
Johanson
cointegration.
Export instability is measured
through squared deviations.
Link between export
instability and economic
growth.
Export instability is inversely related to short-
run stability and directly related to longer-run
growth of income.
Rashid et al.
(2012)
SAARC
countries.
(1972-2008)
Johanson
cointegration.
Instability index is measured
through trend method.
Effect of export instability on
economic growth.
Export instability is inversely related to
economic growth for all countries.
External factors volatility and economic growth Mendoza (1997) 40 industrial and
developing
countries.
(1970-91)
regression Standard deviation of the
residual through autoregressive
process measures volatility.
Association between term
of trade uncertainty and
economic growth
Term of trade volatility adversely affect the
economic growth through consumption growth.
Andrews and
Rees (2009)
71 countries.
(1971–2005)
Fixed effects Standard deviation term of
trade growth represents
volatility.
Correlation between term
of trade volatility and
macroeconomic volatility.
Term of trade volatility increases the volatility
of output growth. It also enhances the
consumption, exports and imports volatility.
Olaberria and
Rigolini (2009)
80 emerging
economies.
(1966-2005)
GMM Standard deviation of residuals
through AR (1) process
represents volatility of each
respective variable.
Effect of East Asia’s
macroeconomic volatility
on economic growth.
Findings show that beside the volatility of
domestic factors volatility of external factors or
shocks has also contributed to the slow growth
of emerging economies.
Abaidoo (2012) 39 Sub Saharan
African countries.
(1980-2011)
Fixed effects Volatility is measured by
standard deviation of specific
macroeconomic variable.
Effect of macroeconomic
volatility on
macroeconomic indicators.
External macroeconomic volatility has higher
impact on macroeconomic measures as
compared to domestic volatility.
262
Determinants of policy volatility
author country technique determinants of policy volatility main objective main findings
Determinants of capital flows volatility Beck Ronald
(2001)
54 emerging and
developing
countries.
(1990-98)
regression Share of foreign bank numbers
and share of foreign bank assets,
macroeconomic and institutional
variables.
Role of foreign banks and
trade liberalization regimes to
capital flow instability in
emerging markets.
Findings show that foreign bank penetration
enhances the volatility of capital flows.
Regulatory environment represented by rule of
law matters more than macroeconomic
indicators.
Alfaro et al.
(2005)
Sample of 97
countries.
(1970-2000)
regression Macroeconomic policy variables,
GDP per capita and institutional
quality.
Determinants of capital flows
volatility.
Institutional quality remains insignificant in
explaining the volatility of capital flows.
Inflation, inflation volatility and government
consumption increases the volatility. GDP per
capita reduces the volatility.
Broner and
Rigobon (2005)
58 countries.
(1965-2003)
regression Domestic macroeconomic factors,
external factors, income per
capita, financial development and
institutional quality.
Motives behind the higher
volatility of capital flows in
emerging countries.
Findings show that internal and external
macroeconomic factors contribute very little to
volatility of capital flows. Financial
development, good institutional quality and
higher per capita income reduce the volatility
of capital flows.
Broto et al.
(2008)
48 emerging and
developing
countries.
(1980-2006)
regression Domestic macroeconomic factors,
financial sector variables, global
factors, institutional variables.
Factors contributing to the
volatility of various capital
inflows (FDI, portfolio and
other inflows).
Financial sector do play a stronger role in
reducing the volatility of capital flows. Global
factors are important in reducing the volatility
as compared to domestic factors. Economic and
political stability discourages the capital flows
instability.
Neumann and
Tanku (2009)
22 developing and
developed
countries.
(1981–2000)
regression Financial liberalization, volatility
of domestic output growth and global factors.
To examine the volatility of
capital flows.
FDI flows show increase in volatility in
emerging markets as a result of liberalization.
Higher world growth volatility increases the
volatility of portfolio and other flows while
reduces the volatility of FDI inflows.
Mercado and
Park (2011)
50 emerging
market economies.
(1980–2009)
regression Domestic macroeconomic factors,
financial indicators, global
economic indicators, institutional
quality.
Factors that determine the
size and variability of various
capital inflows.
Trade openness and volatility of real exchange
rate contribute to the volatility of all capital
inflows. Per capita income, financial
development, institutional quality and global
liquidity lower the volatility of capital inflows. Globan (2012) 75 developed and
developing
countries.
regression FDI, loan and total capital
inflows, GDP per capita, debt.
Relationship between
reversals of capital flows
during global financial crisis.
Countries with higher dependence on foreign
loan rather than FDI financing observed higher
reversals of foreign capital during the crisis.
263
Waqas et al.
(2015)
South Asian
countries.
(2000-2012)
GARCH
methodology.
Macroeconomic variables
include; interest rate, exchange
rate, inflation, industrial
production, GDP growth rate,
foreign direct investment.
Determinants of volatility of
portfolio investment.
Inflation rate reduces the volatility only in case
of China and India. Real exchange increases
the volatility in case of China. In Pakistan and
India, higher interest rate raises the volatility.
Foreign direct investment, industrial production
and economic growth reduce the volatility in
all countries.
Determinants of trade flows volatility
Massell (1970) 55 developed and
developing
countries.
(1950-66)
regression Commodity concentration,
geographic concentration, food
and raw materials, domestic
consumption, size of the export
sector and per capita income.
Relationship between export
instability and a set of
variables that describe an
economy’s structure.
Less export diversification and higher domestic
consumption increases the instability. Higher
size of the export sector, specialization in food
items and higher level of development reduce
the instability.
Aslam (1985) Pakistan
(1961 to 1980)
regression Commodity and geographical
concentration, size of the export
sector, income per capita, share of
food and raw material exports.
Determinants of export
instability.
Geographical concentration reduces the
instability of exports while commodity
concentration remains insignificant. Size of the
export sector, higher per capita income, export
share of raw material reduces instability.
Charette (1985) 15 less developing
countries primary
commodity
markets.
(1960-1970's)
regression Geographical concentration,
Percentage of exports as a share
of domestic output.
Determinants of export
instability.
Higher share of exports out of domestic
production reduces the instability of exports
earnings, prices and output. Geographical
concentration reduces the instability also.
Sarada et al.
(2006)
India
(1981-2004)
Johansen
Cointegration
Commodity concentration and
geographical concentration,
shrimp production, fisheries and
non-fisheries GDP.
Determinants of Indian sea
food export instability.
Commodity concentration reduces the
instability. Geographical concentration, the
instability of fisheries and non-fisheries GDP
and instability of shrimp production increases
the instability of seafood export.
Baum and
Caglayan
(2009)
Eurozone countries
and newly
industrialized
countries.
(1980-2006)
GARCH Exchange rate uncertainty. Association between
exchange rate instability and
instability of trade flows.
Exchange rate instability significantly
contributes to the instability of bilateral trade
flows.
Neena (2015) India
(1987-2013)
regression Instability index of different
export categories, commodity
and geographic concentration.
Sources of export instability. Instability of textile and petroleum products
reduces the export instability while of primary,
chemical and engineering products and
geographical concentration increases the export
instability.
264
Determinants of fiscal policy volatility
Henisz (2004) 91 developed and
developing
countries.
(1971-92)
Fixed effect Checks and balances on policy
makers are represented by political
constraints index, macroeconomic
volatility.
Correlation between political
institutions and fiscal
volatility.
Findings show that higher political constraints
reduce the volatility of different categories of
capital and current expenditures as well as tax
and non-tax revenues. Macroeconomic
volatility is negatively associated with fiscal
policy volatility.
Fatas and
Mihov (2008)
&
Fatas and
Mihov (2013)
Ninety-one
developed and
developing
countries.
(1960-2000).
Instrumental
variables.
Institutional variables (political
constraints, constraints on the
executive, political and electoral
system and number of elections),
macroeconomic and demographic
variables.
Effect of fiscal policy
volatility and institutions on
economic growth and
investment.
Institutional quality considerably contributes to
fiscal policy volatility. Urbanization increases
the volatility while openness and GDP per
capita reduces the volatility of fiscal policy.
Agnello and
Sousa (2009)
Panel of 125
countries.
(1980-2006)
GMM Political instability, democracy and
macroeconomic determinants of
fiscal policy volatility.
Determinants of public
deficit volatility.
Higher political instability increases the
volatility of public deficit while democracy
reduces the volatility. GDP per capita reduces
the volatility of budget deficits. Higher
inflation, openness and fiscal deficit increase
the fiscal volatility.
Bleaney and
Halland (2009)
75 countries.
(1980-2004)
regression Institutional constraints, rule of
law, electoral system, per capita
income, primary product exports.
Effect of primary exports on
growth, growth volatility and
fiscal volatility.
Institutional constraints and per capita income
reduce the volatility of fiscal policy. Higher
share of primary exports enhances the fiscal
volatility.
Albuquerque
Bruno (2010)
25 EU countries.
(1980-2007)
fixed and
random
effects.
Political and institutional variables
(type of the polling system, the
number of elections, cabinet
changes), macroeconomic
variables.
Effect of institutional quality
on volatility of discretionary
fiscal policy.
Fiscal institutions reduce the volatility of fiscal
policy significantly. Bigger countries and larger
government reduce government spending
volatility.
Attiya et al.
(2011)
South Asian and
ASEAN countries.
(1984-2010)
GMM Macroeconomic factors, political
and institutional factors (political
stability, democracy, low level of
corruption, less conflict).
Determinants of fiscal deficit
volatility.
Income per capita, deficit to GDP, inflation and
openness increase the volatility of budget
deficit. Moreover budget deficit volatility has
persistence effect. Population growth and all
the political and institutional variables reduce
the volatility of budget deficit.
Agnello and
Sousa (2014)
113 countries.
(1980-2006)
GMM Political and institutional
determinants, macroeconomic
economic variables.
Factors contributing to the
volatility of fiscal discretion.
Higher democracy and parliamentary system
reduces volatility. Higher government turnover
increases volatility. Country size and less
flexible exchange rate decrease the volatility.
265
Determinants of monetary policy volatility
Koedijk et al.
(1997)
US
(January 1968–July
1996)
CKLS and
GARCH
model.
Short term interest rate. Dynamics of short term
interest rate volatility.
Interest rate volatility is determined by
GARCH and level effects.
Ball and Torous
(1999)
Cross country EGARCH
model
Variety of short term interest rates. Dynamics of short-term
interest rates.
Interest rate dynamics are influenced by
economic shocks.
Edwards and
Susmel (2003)
Latin American
and Asian
countries.
(weekly data 1994-
1999)
univariate
and bivariate
switching
volatility
model.
Short term interest rate. Behavior of interest rate
volatility.
There is evidence of interest-rate volatility co-
movement across countries due to domestic and
international shocks.
Olweny (2011) Kenya
(1991M8 to
2007M12)
ARCH and
GARCH
models
Short term interest rate. Relationship between level of
short term interest rate and its
volatility.
Volatility is positively associated with the level
of the short term interest rate.
Duncan (2013) 56 developed and
developing
countries.
(1984.Q -2008.Q4)
Instrumental
variables
Institutional quality, Financial
openness, central bank
independence, output volatility,
inflation.
Consequences of a better
institutional quality for the
cyclicity and volatility of
monetary policy.
The model shows a positive co-movement
between output and the interest rate at
relatively high levels of institutional quality.
Higher institutional quality reduces the interest
rate volatility.
266
11
12
13
14
15
16
90 92 94 96 98 00 02 04 06 08 10 12 14
Bangladesh
21
22
23
24
25
26
27
28
29
90 92 94 96 98 00 02 04 06 08 10 12 14
Brazil
14
15
16
17
18
19
20
90 92 94 96 98 00 02 04 06 08 10 12 14
India
16
17
18
19
20
21
22
23
90 92 94 96 98 00 02 04 06 08 10 12 14
Kenya
10
15
20
25
30
35
40
45
50
90 92 94 96 98 00 02 04 06 08 10 12 14
Maldives
12
13
14
15
16
17
18
19
20
90 92 94 96 98 00 02 04 06 08 10 12 14
Mexico
14
15
16
17
18
19
20
21
22
23
90 92 94 96 98 00 02 04 06 08 10 12 14
Nepal
16
18
20
22
24
26
28
30
32
90 92 94 96 98 00 02 04 06 08 10 12 14
Pakistan
15
16
17
18
19
20
21
90 92 94 96 98 00 02 04 06 08 10 12 14
Phillipines
18
20
22
24
26
28
30
90 92 94 96 98 00 02 04 06 08 10 12 14
Srilanka
12
14
16
18
20
22
24
26
90 92 94 96 98 00 02 04 06 08 10 12 14
Thailand
14
16
18
20
22
24
26
28
30
90 92 94 96 98 00 02 04 06 08 10 12 14
Vietnam
Appendix III: Trends of the variables
Fiscal policy Government expenditures (% of GDP)
267
6
7
8
9
10
11
90 92 94 96 98 00 02 04 06 08 10 12 14
Bangladesh
9
10
11
12
13
14
15
16
17
90 92 94 96 98 00 02 04 06 08 10 12 14
Brazil
7
8
9
10
11
12
90 92 94 96 98 00 02 04 06 08 10 12 14
India
14
15
16
17
18
19
20
21
90 92 94 96 98 00 02 04 06 08 10 12 14
Kenya
8
12
16
20
24
28
90 92 94 96 98 00 02 04 06 08 10 12 14
Maldives
9
10
11
12
13
14
15
16
17
18
90 92 94 96 98 00 02 04 06 08 10 12 14
Mexico
6
8
10
12
14
16
18
90 92 94 96 98 00 02 04 06 08 10 12 14
Nepal
8
9
10
11
12
13
14
90 92 94 96 98 00 02 04 06 08 10 12 14
Pakistan
11
12
13
14
15
16
17
18
90 92 94 96 98 00 02 04 06 08 10 12 14
Philippines
10
12
14
16
18
20
90 92 94 96 98 00 02 04 06 08 10 12 14
Srilanka
12
13
14
15
16
17
90 92 94 96 98 00 02 04 06 08 10 12 14
Thailand
12
16
20
24
28
32
90 92 94 96 98 00 02 04 06 08 10 12 14
Vietnam
Fiscal policy Tax revenue (% of GDP)
268
12.5
13.0
13.5
14.0
14.5
15.0
15.5
16.0
16.5
90 92 94 96 98 00 02 04 06 08 10 12 14
Bangladesh
20
30
40
50
60
70
80
90
90 92 94 96 98 00 02 04 06 08 10 12 14
Brazil
8
10
12
14
16
18
20
90 92 94 96 98 00 02 04 06 08 10 12 14
India
10
15
20
25
30
35
40
90 92 94 96 98 00 02 04 06 08 10 12 14
Kenya
10
12
14
16
18
20
90 92 94 96 98 00 02 04 06 08 10 12 14
Maldives
0
10
20
30
40
50
60
90 92 94 96 98 00 02 04 06 08 10 12 14
Mexico
6
7
8
9
10
11
12
13
14
15
90 92 94 96 98 00 02 04 06 08 10 12 14
Nepal
2
4
6
8
10
12
14
16
90 92 94 96 98 00 02 04 06 08 10 12 14
Pakistan
5
10
15
20
25
90 92 94 96 98 00 02 04 06 08 10 12 14
Philippines
6
8
10
12
14
16
18
20
22
90 92 94 96 98 00 02 04 06 08 10 12 14
Srilanka
4
6
8
10
12
14
16
90 92 94 96 98 00 02 04 06 08 10 12 14
Thailand
5
10
15
20
25
30
35
90 92 94 96 98 00 02 04 06 08 10 12 14
Veitnam
Monetary policy
(Interest rate)
269
12
16
20
24
28
90 92 94 96 98 00 02 04 06 08 10 12 14
Bangladesh
8
12
16
20
24
28
32
36
90 92 94 96 98 00 02 04 06 08 10 12 14
Brazil
0
10
20
30
40
50
60
70
80
90
90 92 94 96 98 00 02 04 06 08 10 12 14
India
10
15
20
25
30
35
90 92 94 96 98 00 02 04 06 08 10 12 14
Kenya
21.1
21.2
21.3
21.4
21.5
21.6
21.7
21.8
21.9
22.0
90 92 94 96 98 00 02 04 06 08 10 12 14
Maldives
4
6
8
10
12
14
16
18
20
90 92 94 96 98 00 02 04 06 08 10 12 14
Mexico
10
12
14
16
18
20
22
24
90 92 94 96 98 00 02 04 06 08 10 12 14
Nepal
10
20
30
40
50
60
70
90 92 94 96 98 00 02 04 06 08 10 12 14
Pakistan
0
4
8
12
16
20
24
90 92 94 96 98 00 02 04 06 08 10 12 14
Philippines
8
12
16
20
24
28
90 92 94 96 98 00 02 04 06 08 10 12 14
Srilanka
8
12
16
20
24
28
32
36
40
44
90 92 94 96 98 00 02 04 06 08 10 12 14
Thailand
4
8
12
16
20
24
90 92 94 96 98 00 02 04 06 08 10 12 14
Veitnam
Trade liberalization
(Average tariff rate)
270
15
20
25
30
35
40
45
50
90 92 94 96 98 00 02 04 06 08 10 12 14
Bangladesh
14
16
18
20
22
24
26
28
30
90 92 94 96 98 00 02 04 06 08 10 12 14
Brazil
10
20
30
40
50
60
90 92 94 96 98 00 02 04 06 08 10 12 14
India
45
50
55
60
65
70
75
90 92 94 96 98 00 02 04 06 08 10 12 14
Kenya
100
120
140
160
180
200
220
240
90 92 94 96 98 00 02 04 06 08 10 12 14
Maldives
20
30
40
50
60
70
90 92 94 96 98 00 02 04 06 08 10 12 14
Mexico
30
35
40
45
50
55
60
65
90 92 94 96 98 00 02 04 06 08 10 12 14
Nepal
28
30
32
34
36
38
40
90 92 94 96 98 00 02 04 06 08 10 12 14
Pakistan
50
60
70
80
90
100
110
90 92 94 96 98 00 02 04 06 08 10 12 14
Philippines
40
50
60
70
80
90
90 92 94 96 98 00 02 04 06 08 10 12 14
Srilanka
70
80
90
100
110
120
130
140
150
160
90 92 94 96 98 00 02 04 06 08 10 12 14
Thailand
60
80
100
120
140
160
180
90 92 94 96 98 00 02 04 06 08 10 12 14
Vietnam
Trade liberalization
Trade openness (% of GDP)
271
40
45
50
55
60
65
70
90 92 94 96 98 00 02 04 06 08 10 12 14
Bangladesh
30
40
50
60
70
80
90
100
110
90 92 94 96 98 00 02 04 06 08 10 12 14
Brazil
10
20
30
40
50
60
70
80
90
90 92 94 96 98 00 02 04 06 08 10 12 14
India
60
70
80
90
100
110
120
130
90 92 94 96 98 00 02 04 06 08 10 12 14
Kenya
60
80
100
120
140
160
90 92 94 96 98 00 02 04 06 08 10 12 14
Maldives
50
60
70
80
90
100
110
90 92 94 96 98 00 02 04 06 08 10 12 14
Mexico
20
30
40
50
60
70
80
90
90 92 94 96 98 00 02 04 06 08 10 12 14
Nepal
40
44
48
52
56
60
64
68
72
76
90 92 94 96 98 00 02 04 06 08 10 12 14
Pakistan
80
90
100
110
120
130
140
150
90 92 94 96 98 00 02 04 06 08 10 12 14
Philippines
72
76
80
84
88
92
96
100
104
108
90 92 94 96 98 00 02 04 06 08 10 12 14
Srilanka
0
20
40
60
80
100
120
140
160
90 92 94 96 98 00 02 04 06 08 10 12 14
Thailand
20
40
60
80
100
120
140
90 92 94 96 98 00 02 04 06 08 10 12 14
Vietnam
Financial Liberalization
Gross capital flows (% GDP)
272
3
4
5
6
7
8
9
90 92 94 96 98 00 02 04 06 08 10 12 14
Bangladesh
5
10
15
20
25
90 92 94 96 98 00 02 04 06 08 10 12 14
Brazil
0
2
4
6
8
10
90 92 94 96 98 00 02 04 06 08 10 12 14
India
6
7
8
9
10
11
12
13
14
90 92 94 96 98 00 02 04 06 08 10 12 14
Kenya
0
5
10
15
20
25
90 92 94 96 98 00 02 04 06 08 10 12 14
Maldives
4
8
12
16
20
24
28
90 92 94 96 98 00 02 04 06 08 10 12 14
Mexico
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
90 92 94 96 98 00 02 04 06 08 10 12 14
Nepal
0
4
8
12
16
20
90 92 94 96 98 00 02 04 06 08 10 12 14
Pakistan
0
10
20
30
40
50
90 92 94 96 98 00 02 04 06 08 10 12 14
Philippines
4
6
8
10
12
14
16
18
90 92 94 96 98 00 02 04 06 08 10 12 14
Srilanka
0
4
8
12
16
20
24
90 92 94 96 98 00 02 04 06 08 10 12 14
Thailand
0
20
40
60
80
100
120
140
90 92 94 96 98 00 02 04 06 08 10 12 14
Vietnam
Financial Liberalization
FDI inflows (% GDP)
273
-.1
.0
.1
.2
.3
.4
.5
90 92 94 96 98 00 02 04 06 08 10 12 14
Bangladesh
-5
0
5
10
15
20
90 92 94 96 98 00 02 04 06 08 10 12 14
Brazil
-8
-4
0
4
8
12
16
20
90 92 94 96 98 00 02 04 06 08 10 12 14
India
-8
-7
-6
-5
-4
-3
-2
-1
0
1
90 92 94 96 98 00 02 04 06 08 10 12 14
Kenya
-.5
-.4
-.3
-.2
-.1
.0
.1
.2
90 92 94 96 98 00 02 04 06 08 10 12 14
Maldives
-4
-2
0
2
4
6
8
10
90 92 94 96 98 00 02 04 06 08 10 12 14
Mexico
-6
-5
-4
-3
-2
-1
0
1
90 92 94 96 98 00 02 04 06 08 10 12 14
Nepal
-1.0
-0.5
0.0
0.5
1.0
1.5
2.0
2.5
90 92 94 96 98 00 02 04 06 08 10 12 14
Pakistan
-8
-4
0
4
8
12
16
20
24
28
90 92 94 96 98 00 02 04 06 08 10 12 14
Philippines
-0.8
-0.4
0.0
0.4
0.8
1.2
90 92 94 96 98 00 02 04 06 08 10 12 14
Srilanka
-8
-4
0
4
8
12
90 92 94 96 98 00 02 04 06 08 10 12 14
Thailand
-4
-3
-2
-1
0
1
2
3
4
90 92 94 96 98 00 02 04 06 08 10 12 14
Vietnam
Financial Liberalization
Portfolio inflows (% GDP)
274
-1.2
-1.1
-1.0
-0.9
-0.8
-0.7
-0.6
-0.5
90 92 94 96 98 00 02 04 06 08 10 12 14
Bangladesh
-.15
-.10
-.05
.00
.05
.10
.15
90 92 94 96 98 00 02 04 06 08 10 12 14
Brazil
-1
0
1
2
3
4
5
90 92 94 96 98 00 02 04 06 08 10 12 14
India
-.85
-.80
-.75
-.70
-.65
-.60
-.55
90 92 94 96 98 00 02 04 06 08 10 12 14
Kenya
-.4
-.2
.0
.2
.4
.6
90 92 94 96 98 00 02 04 06 08 10 12 14
Maldives
-.4
-.3
-.2
-.1
.0
.1
90 92 94 96 98 00 02 04 06 08 10 12 14
Mexico
-1.1
-1.0
-0.9
-0.8
-0.7
-0.6
-0.5
-0.4
-0.3
-0.2
90 92 94 96 98 00 02 04 06 08 10 12 14
Nepal
-1.2
-1.1
-1.0
-0.9
-0.8
-0.7
90 92 94 96 98 00 02 04 06 08 10 12 14
Pakistan
-.6
-.5
-.4
-.3
-.2
-.1
.0
.1
90 92 94 96 98 00 02 04 06 08 10 12 14
Philippines
-.50
-.45
-.40
-.35
-.30
-.25
-.20
-.15
-.10
90 92 94 96 98 00 02 04 06 08 10 12 14
Srilanka
-.4
-.3
-.2
-.1
.0
.1
.2
.3
.4
90 92 94 96 98 00 02 04 06 08 10 12 14
Thailand
-.60
-.56
-.52
-.48
-.44
-.40
90 92 94 96 98 00 02 04 06 08 10 12 14
Veitnam
Institutional Quality
Governance index (-2.5 to 2.5)
275
0
2
4
6
8
10
12
14
50 100 150 200 250 300
fiscal policy volatility (govt. exp. vol)
0
10
20
30
40
50
60
70
50 100 150 200 250 300
trade flows volatility
0
10
20
30
40
50 100 150 200 250 300
monetary policy volatility (interest rate vol)
0
10
20
30
40
50
50 100 150 200 250 300
volatility of gross capital flows
0
4
8
12
16
20
24
50 100 150 200 250 300
portfolio inflows volatility
-40
-20
0
20
40
60
50 100 150 200 250 300
FDI inflows volatility
276
Appendix IV: Policy volatility in selected countries
Fiscal policy volatility:
Table IVA: Volatility of government expenditures:
Note: values highlighted show the highest and lowest mean volatility.
Countries with low volatility: India, Bangladesh and Mexico are less volatile. India has the lowest
volatility.
Countries with high volatility: Maldives, Thailand, Nepal, Vietnam, Brazil, Kenya and Pakistan, Srilanka
and Philippines are more volatile. Maldives has highest volatility.
Table IVB: Volatility of tax revenue:
countries mean st. dev conclusion
sample 0.371435 0.25176
Bangladesh 0.371435 0.256728
Brazil 0.639073 0.498674 More volatile
India 0.746015 0.637084 More volatile
Kenya 1.050356 1.140975 More volatile
Maldives 1.441895 1.688477 More volatile
Mexico 0.69162 0.659662 More volatile
Nepal 0.456427 0.393752 More volatile
Pakistan 0.577324 0.513079 More volatile
Philippines 0.49723 0.365531 More volatile
Srilanka 0.535333 0.402578 More volatile
Thailand 1.119483 0.82626 More volatile
Vietnam 0.992825 0.81804 More volatile
Note: values highlighted show the highest and lowest mean volatility.
Countries with low volatility: Only Bangladesh is less volatile.
Countries with high volatility: All other countries are more volatile. Maldives has highest volatility.
countries mean st. dev conclusion
sample 0.845557 0.724544
Bangladesh 0.845557 0.738841
Brazil 1.176981 0.965521 More volatile
India 0.675428 0.45284 Less volatile
Kenya 1.171637 1.01464 More volatile
Maldives 2.758448 2.914094 More volatile
Mexico 0.76428 0.62359 Less volatile
Nepal 1.232032 0.944487 More volatile
Pakistan 1.00296 0.755478 More volatile
Philippines 0.947691 0.745652 More volatile
Srilanka 0.943453 0.891672 More volatile
Thailand 1.460231 2.013776 More volatile
Vietnam 1.233746 0.783562 More volatile
277
Monetary policy volatility: Table IVC: Volatility of interest rate: countries mean st. dev conclusion
sample 3.061241 4.68077
Bangladesh 3.061241 4.773135
Brazil 5.529767 8.062967 More volatile
India 1.149238 1.044939 Less volatile
Kenya 1.69735 2.039695 Less volatile
Maldives 1.426535 1.000072 Less volatile
Mexico 2.374221 2.199237 Less volatile
Nepal 1.098336 0.992405 Less volatile
Pakistan 1.361078 1.346797 Less volatile
Philippines 1.475784 1.24348 Less volatile
Srilanka 2.182876 1.385985 Less volatile
Thailand 2.613641 4.102664 Less volatile
Vietnam 1.721329 1.677794 Less volatile
Note: values highlighted show the highest and lowest mean volatility.
Countries with low volatility: All the countries are less volatile except Brazil.
Trade flows volatility:
Table IVD: Volatility of trade flows:
countries mean st. dev conclusion
sample 2.43331 2.030559
Bangladesh 2.43331 2.070627
Brazil 1.415308 1.189719 Less volatile
India 2.328346 2.059569 Less volatile
Kenya 6.543141 6.307455 More volatile
Maldives 14.31889 17.72622 More volatile
Mexico 2.555064 2.097271 More volatile
Nepal 2.740027 2.012154 More volatile
Pakistan 3.318793 3.028445 More volatile
Philippines 3.34458 2.287367 More volatile
Srilanka 3.897936 3.44121 More volatile
Thailand 7.589699 5.134877 More volatile
Vietnam 5.379801 5.968367 More volatile
Note: values highlighted show the highest and lowest mean volatility.
Countries with low volatility: Brazil, India and Bangladesh are less volatile. Brazil has lowest volatility.
Countries with high volatility: Maldives, Vietnam, Thailand, Kenya, Srilanka, Pakistan, Philippines, Nepal
and Mexico are more volatile. Maldives has highest volatility.
278
Capital flows volatility:
Table IVE: Volatility of FDI inflows:
countries mean st. dev conclusion
sample 2.313539 5.453756
Bangladesh 0.261717 0.202579 Less volatile
Brazil 1.037513 0.862832 Less volatile
India 0.224832 0.320834 Less volatile
Kenya 1.067834 0.984751 Less volatile
Maldives 0.801113 0.651529 Less volatile
Mexico 1.238032 1.160907 Less volatile
Nepal 0.169701 0.099194 Less volatile
Pakistan 0.372387 0.251062 Less volatile
Philippines 6.032109 7.728823 More volatile
Srilanka 0.69125 0.407184 More volatile
Thailand 2.723219 1.787229 More volatile
Vietnam 12.71872 13.35248 More volatile
Note: values highlighted show the highest and lowest mean volatility.
Countries with low volatility: Nepal, India, Bangladesh, Pakistan, Maldives, Brazil, Kenya and Mexico
are less volatile. Nepal has lowest volatility
Countries with high volatility: Vietnam, Philippines and Thailand are more volatile. Vietnam has highest
volatility.
Table IVF: Volatility of portfolio inflows:
countries mean st. dev conclusion
sample 1.164023 2.443761
Bangladesh 0.221066 0.172438 Less volatile
Brazil 0.570545 0.503159 Less volatile
India 0.4016 0.397703 Less volatile
Kenya 0.177591 0.136298 Less volatile
Maldives 0.208782 0.013749 Less volatile
Mexico 1.809491 1.375955 More volatile
Nepal 0.165003 0.088078 Less volatile
Pakistan 0.596402 0.400106 Less volatile
Philippines 5.262285 6.976316 More volatile
Srilanka 0.415942 0.213085 More volatile
Thailand 2.790677 2.641137 More volatile
Vietnam 0.699684 1.082116 Less volatile
Note: values highlighted show the highest and lowest mean volatility.
Countries with low volatility: Nepal, Kenya, Maldives, Bangladesh, India, Brazil, Pakistan, and Vietnam
are less volatile. Nepal has lowest volatility.
Countries with high volatility: Philippines, Thailand and Mexico are more volatile. Philippines has highest
volatility.
279
Appendix V: Cyclical behaviour of policies in selected countries
Cyclical behaviour of fiscal policy (government expenditures):
Table VA: Cross Correlation between GDP and government expenditures at t+i and t-i (i = 0……2)
countries t-2 t-1 t t+1 t+2 Nature of co-movement conclusion
sample -0.0612 -0.1332 -0.3766 -0.1138 0.0189 countercyclical and coincident Stabilizing effect
Bangladesh -0.5753 -0.7424 -0.8859 -0.5862 -0.3516 countercyclical and coincident Stabilizing effect
Brazil -0.3415 -0.464 -0.5275 -0.3249 -0.1292 countercyclical and coincident Stabilizing effect
India -0.3058 -0.4589 -0.6388 -0.6002 -0.4962 countercyclical and coincident Stabilizing effect
Kenya -0.0866 -0.0542 -0.0051 -0.1002 -0.0526 acyclical No effect
Maldives -0.243 -0.2335 -0.3902 -0.2993 -0.1762 countercyclical and coincedent Stabilizing effect
Mexico -0.3527 -0.5325 -0.7537 -0.6294 -0.5452 countercyclical and coincedent Stabilizing effect
Nepal 0.0462 0.1291 0.1304 0.0871 0.0637 acyclical No effect
Pakistan 0.3398 0.5501 0.7636 0.6633 0.581 procyclical and coincedent Destabilizing
effect
Philippines -0.6436 -0.8183 -0.9045 -0.6273 -0.3707 countercyclical and coincedent Stabilizing effect
Srilanka -0.384 -0.5208 -0.6409 -0.4832 -0.3206 countercyclical and coincedent Stabilizing effect
Thailand -0.2457 -0.2272 -0.2597 -0.193 0.0286 acyclical No effect
Vietnam 0.1096 0.1841 0.1316 0.294 -0.2577 acyclical No effect
Note: Values highlighted show the coefficients those are statistically significant at 5% significance level.
Cyclical behaviour of fiscal policy (tax revenue):
Table VB: Cross Correlation between GDP and tax revenue at t+i and t-i (i = 0……2)
countries t-2 t-1 t t+1 t+2 Nature of co-movement conclusion
sample 0.1188 0.0408 -0.219 -0.0662 -0.0187 acyclical No effect
Bangladesh -0.1554 -0.0446 0.0821 0.0363 -0.0065 acyclical No effect
Brazil 0.0782 -0.054 -0.5608 -0.1036 0.0746 procyclical and coincident Destabilizing
effect
India -0.3911 -0.3911 -0.5196 -0.3619 -0.3056 procyclical and coincident Destabilizing
effect
Kenya -0.1811 -0.0803 0.1761 -0.0596 -0.0531 acyclical No effect
Maldives 0.0738 0.0258 -0.4954 -0.1062 -0.0278 procyclical and coincident Destabilizing
effect
Mexico -0.1356 -0.203 -0.1322 -0.4131 -0.3882 Procyclical and lags output by
one year.
Destabilizing
effect
Nepal 0.2954 0.4168 0.4289 0.4562 0.3199 countercyclical and coincident Stabilizing effect
Pakistan -0.2467 -0.2559 -0.2812 -0.289 -0.0845 acyclical No effect
Philippines 0.0227 -0.1445 -0.2997 -0.1101 -0.099 acyclical No effect
Srilanka -0.2505 -0.3213 -0.3049 -0.3253 -0.2972 Procyclical and lags output by
one year
Destabilizing
effect
Thailand -0.1321 -0.1019 -0.072 -0.0035 -0.026 acyclical No effect
Vietnam 0.2315 0.2708 0.2689 0.1204 -0.3337 procyclical and lags output by
two years
Destabilizing
effect
Note: Values highlighted show the coefficients those are statistically significant at 5% significance level.
280
Cyclical behaviour of monetary policy (interest rate):
Table VC: Cross Correlation between GDP and interest rate at t+i and t-i (i = 0……2)
countries t-2 t-1 t t+1 t+2 Nature of co-movement conclusion
sample -0.2785 -0.2735 -0.3120 -0.3332 -0.3431 procyclical and lags output
by one year Destabilizing effect
Bangladesh -0.5292 -0.7439 -0.9859 -0.6558 -0.3942 procyclical and coincident Destabilizing effect
Brazil -0.3099 -0.1181 -0.0518 -0.0547 -0.0680 acyclical No effect
India -0.4263 -0.5656 -0.7237 -0.3816 -0.1835 procyclical and coincident Destabilizing effect
Kenya 0.1072 0.0470 -0.0888 -0.1684 -0.2248 acyclical No effect
Maldives 0.3235 0.4041 0.4696 0.3395 0.2400 countercyclical and
coincident Stabilizing effect
Mexico -0.0971 -0.1263 -0.1251 0.0007 0.1255 acyclical No effect
Nepal -0.2042 -0.2421 -0.3108 -0.1179 -0.0451 acyclical No effect
Pakistan -0.0464 0.1199 0.2167 0.3009 0.4413 countercyclical and lags
output by two years Stabilizing effect
Philippines -0.3253 -0.5216 -0.6494 -0.3723 -0.1810 procyclical and coincident Destabilizing effect
Srilanka -0.0382 -0.2077 -0.2004 -0.2502 -0.2093 acyclical No effect
Thailand -0.4001 -0.4625 -0.5445 -0.3081 -0.1618 procyclical and coincident Destabilizing effect
Vietnam -0.2254 -0.3491 -0.5328 -0.3344 -0.1440 procyclical and coincident Destabilizing effect
Note: Values highlighted show the coefficients those are statistically significant at 5% significance level.
Cyclical behaviour of capital inflows (FDI inflows):
Table VD: Cross Correlation between GDP and FDI inflows at t+i and t-i (i = 0……2)
countries t-2 t-1 t t+1 t+2 Nature of co-movement conclusion
sample 0.0051 -0.0408 -0.1332 -0.0506 -0.0166 acyclical No effect
Bangladesh 0.008 -0.1227 -0.1391 0.0737 0.0541 acyclical No effect
Brazil -0.3189 -0.4185 -0.7562 -0.2599 -0.1193 countercyclical and
coincident Stabilizing effect
India -0.4171 -0.6513 -0.9296 -0.7108 -0.5026 countercyclical and
coincident Stabilizing effect
Kenya 0.0593 0.2238 0.7047 0.331 0.2773 procyclical and coincident Destabilizing effect
Maldives -0.0881 -0.1662 -0.2111 0.0502 0.1401 acyclical No effect
Mexico -0.0426 -0.0723 -0.0298 -0.144 -0.126 acyclical No effect
Nepal 0.4539 0.6185 0.8219 0.6622 0.498 procyclical and coincident Destabilizing effect
Pakistan 0.026 0.0482 0.0038 0.027 0.0122 acyclical No effect
Philippines -0.07 -0.0094 -0.122 -0.1862 -0.1832 acyclical No effect
Srilanka -0.2385 -0.3434 -0.6788 -0.3358 -0.2502 countercyclical and
coincident Stabilizing effect
Thailand -0.3267 -0.5693 -0.965 -0.5945 -0.3884 countercyclical and
coincident Stabilizing effect
Vietnam 0.1107 0.146 0.143 -0.0058 -0.2169 acyclical No effect
Note: Values highlighted show the coefficients those are statistically significant at 5% significance level.
281
Cyclical behaviour of capital inflows (portfolio inflows):
Table VE: Cross Correlation between GDP and portfolio inflows at t+i and t-i (i = 0……2)
countries t-2 t-1 t t+1 t+2 Nature of co-movement conclusion
sample 0.0051 -0.0408 -0.1332 -0.0506 -0.0166 acyclical No effect
Bangladesh -0.0469 -0.0132 0.5508 0.1218 0.0999 procyclical and coincident Destabilizing effect
Brazil 0.0004 -0.095 -0.7668 -0.1946 -0.114 countercyclical and
coincident Stabilizing effect
India -0.1699 -0.2851 -0.4006 -0.305 -0.1803 countercyclical and
coincident Stabilizing effect
Kenya 0.3811 0.4581 0.5854 0.3044 0.1109 procyclical and coincident Destabilizing effect
Maldives 0.0456 0.0489 0.0682 0.1949 0.2285 acyclical No effect
Mexico 0.0433 0.0961 0.3403 0.0834 -0.0215 procyclical and coincident Destabilizing effect
Nepal 0.4808 0.6258 0.7863 0.5875 0.3812 procyclical and coincident Destabilizing effect
Pakistan 0.0383 -0.0721 -0.1149 -0.1484 -0.257 acyclical No effect
Philippines 0.017 0.1479 0.0846 -0.0655 -0.1373 acyclical No effect
Srilanka -0.057 -0.1868 -0.5454 -0.4006 -0.3857 countercyclical and
coincident Stabilizing effect
Thailand -0.115 -0.0632 0.1953 -0.0518 -0.1254 acyclical No effect
Vietnam 0.3586 0.5373 0.8192 0.5811 0.3427 procyclical and coincident Destabilizing effect
282
Table VF: Summary of cyclical behaviour of policies:
countries Govt. expenditures Tax revenue Interest rate FDI inflows Portfolio inflows conclusion
sample countercyclical acyclical procyclical acyclical acyclical
Bangladesh countercyclical acyclical procyclical procyclical procyclical Policy makers can use govt. expenditures as a hedge
against shock.
Brazil countercyclical procyclical
acyclical countercyclical countercyclical
Policy makers can use govt. expenditures, FDI inflows
and portfolio inflows as a hedge against shock.
India countercyclical procyclical procyclical countercyclical countercyclical Policy makers can use govt. expenditures, FDI inflows
and portfolio inflows as a hedge against shock.
Kenya acyclical acyclical acyclical acyclical procyclical
Maldives countercyclical procyclical countercyclical countercyclical acyclical Policy makers can use govt. expenditures, monetary
policy and FDI inflows as a hedge against shock.
Mexico countercyclical Procyclical acyclical countercyclical procyclical Policy makers can use govt. expenditures and FDI
inflows as a hedge against shock.
Nepal acyclical countercyclical acyclical procyclical procyclical Policy makers can use tax policy as a hedge against
shock.
Pakistan procyclical acyclical countercyclical acyclical acyclical Policy makers can use monetary policy as a hedge
against shock.
Philippines countercyclical acyclical procyclical acyclical acyclical Policy makers can use govt. expenditures as a hedge
against shock
Srilanka countercyclical Procyclical acyclical acyclical countercyclical Policy makers can use Govt. expenditures and portfolio
inflows as a hedge against shock
Thailand acyclical acyclical procyclical countercyclical acyclical Policy makers can use FDI inflows as a hedge against
shock.
Vietnam acyclical procyclical procyclical acyclical procyclical
283
-6
-4
-2
0
2
4
6
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP govt. exp
Bangladesh
-12
-8
-4
0
4
8
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP govt. exp
Brazil
-4
-2
0
2
4
6
8
10
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP govt exp.
India
-2
-1
0
1
2
3
4
5
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP govt. exp
kenya
-8
-4
0
4
8
12
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP govt exp
Maldives
-10
-8
-6
-4
-2
0
2
4
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP govt exp
Mexico
-5
-4
-3
-2
-1
0
1
2
3
4
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP govt. exp
Nepal
-4
-3
-2
-1
0
1
2
3
4
5
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP govt exp
Pakistan
-5
-4
-3
-2
-1
0
1
2
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP govt exp
Philippines
-3
-2
-1
0
1
2
3
4
5
6
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP govt exp
Srilanka
-4
-2
0
2
4
6
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP govt exp
Thailand
-8
-6
-4
-2
0
2
4
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP govt exp
Vietnam
Graphical analysis of cyclical behaviour of policies.
Cyclical behaviour of fiscal policy
Correlation between GDP and Government expenditures
284
-2
-1
0
1
2
3
4
5
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP tax rev
Bangladesh
-10
-8
-6
-4
-2
0
2
4
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP tax rev
Brazil
-4
-2
0
2
4
6
8
10
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP tax rev
India
-2
-1
0
1
2
3
4
5
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP tax rev
Kenya
-4
-2
0
2
4
6
8
10
12
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP tax rev
Maldives
-4
-3
-2
-1
0
1
2
3
4
5
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP tax rev
Mexico
-5
-4
-3
-2
-1
0
1
2
3
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP tax rev
Nepal
-2.0
-1.5
-1.0
-0.5
0.0
0.5
1.0
1.5
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP tax rev
Pakistan
-2
-1
0
1
2
3
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP tax rev
Philippines
-3
-2
-1
0
1
2
3
4
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP tax rev
Srilanka
-2
-1
0
1
2
3
4
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP tax rev
Thailand
-5
-4
-3
-2
-1
0
1
2
3
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP tax rev
Vietnam
Cyclical behaviour of fiscal policy
Correlation between GDP and tax revenue
285
-40
-30
-20
-10
0
10
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP interest rate
Bangladesh
-20
-10
0
10
20
30
40
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP interest rate
Brazil
-10
-5
0
5
10
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP interest rate
India
-8
-4
0
4
8
12
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP interest rate
Kenya
-6
-5
-4
-3
-2
-1
0
1
2
3
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP intetrest rate
Maldives
-10
0
10
20
30
40
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP interest rate
Mexico
-4
-2
0
2
4
6
8
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP interest rate
Nepal
-6
-4
-2
0
2
4
6
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP interest rate
Pakistan
-8
-6
-4
-2
0
2
4
6
8
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP interest rate
Philippines
-6
-4
-2
0
2
4
6
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP interest rate
Srilanka
-8
-6
-4
-2
0
2
4
6
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP interest rate
Thailand
-8
-4
0
4
8
12
16
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP interest rate
Vietnam
Cyclical behaviour of monetary policy
Correlation between GDP and interest rate
286
-2
-1
0
1
2
3
4
5
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP FDI inflows
Bangladesh
-12
-8
-4
0
4
8
12
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP FDI inflows
Brazil
-12
-8
-4
0
4
8
12
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP FDI inflows
India
-2
-1
0
1
2
3
4
5
6
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP FDI inflows
Kenya
-6
-4
-2
0
2
4
6
8
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP FDI inflows
Maldives
-8
-4
0
4
8
12
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP FDI inflows
Mexico
-12
-10
-8
-6
-4
-2
0
2
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP FDI inflows
Nepal
-3
-2
-1
0
1
2
3
4
5
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP FDI inflows
Pakistan
-20
-10
0
10
20
30
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP FDI inflows
Philippines
-2
0
2
4
6
8
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP FDI inflows
Srilanka
-15
-10
-5
0
5
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP FDI inflows
Thailand
-40
-20
0
20
40
60
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP FDI inflows
Vietnam
Cyclical behaviour of capital inflows
Correlation between GDP and FDI inflows
287
-1
0
1
2
3
4
5
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP Portfolio inflows
Bangladesh
-10
-5
0
5
10
15
20
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP portfolio inflows
Brazil
-10
-5
0
5
10
15
20
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP portfolio inflows
India
-8
-6
-4
-2
0
2
4
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP portfolio inflows
Kenya
-3.5
-3.0
-2.5
-2.0
-1.5
-1.0
-0.5
0.0
0.5
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP portfolio inflows
Maldives
-4
-2
0
2
4
6
8
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP portfolio inflows
Mexico
-6
-5
-4
-3
-2
-1
0
1
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP portfolio inflows
Nepal
-1.0
-0.5
0.0
0.5
1.0
1.5
2.0
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP portfolio inflows
Pakistan
-10
-5
0
5
10
15
20
25
30
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP portfolio inflows
Philippines
-0.8
-0.4
0.0
0.4
0.8
1.2
1.6
2.0
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP portfolio inflows
Srilanka
-8
-4
0
4
8
12
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP portfolio inflows
Thailand
-5
-4
-3
-2
-1
0
1
2
3
4
90 92 94 96 98 00 02 04 06 08 10 12 14
GDP portfolio inflows
Vietnam
Cyclical behaviour of capital inflows
Correlation between GDP and portfolio inflows
288
3.2
3.6
4.0
4.4
4.8
5.2
5.6
6.0
6.4
6.8
7.2
0.0 0.4 0.8 1.2 1.6 2.0 2.4
fiscal policy volatility
econ
omic
gro
wth
Appendix VI: Scattered plots of variables (pair wise correlation)
3.2
3.6
4.0
4.4
4.8
5.2
5.6
6.0
6.4
6.8
7.2
3 4 5 6 7 8 9
govt. expenditures (% of GDP)
econ
omic
gro
wth
3.2
3.6
4.0
4.4
4.8
5.2
5.6
6.0
6.4
6.8
7.2
-1.1 -1.0 -0.9 -0.8 -0.7
institutional quality
econ
omic
gro
wth
3.2
3.6
4.0
4.4
4.8
5.2
5.6
6.0
6.4
6.8
7.2
2 4 6 8 10 12 14
interest rate
econ
omic
gro
wth
3.2
3.6
4.0
4.4
4.8
5.2
5.6
6.0
6.4
6.8
7.2
0 20 40 60 80 100 120 140
tariff rate
econ
omic
gro
wth
3.2
3.6
4.0
4.4
4.8
5.2
5.6
6.0
6.4
6.8
7.2
0.0 0.2 0.4 0.6 0.8 1.0 1.2
net FDI inflows (% of GDP)
econ
omic
gro
wth
289
0
2
4
6
8
10
-1.2 -1.1 -1.0 -0.9 -0.8 -0.7 -0.6 -0.5
institutional quality
trad
e flo
ws
voal
tility
.0
.1
.2
.3
.4
.5
-1.2 -1.1 -1.0 -0.9 -0.8 -0.7 -0.6 -0.5
institutional quality
capi
tal f
low
s vo
altil
ity
.0
.1
.2
.3
.4
.5
.6
.7
.8
.9
.40 .45 .50 .55 .60 .65 .70
institutional quality
fisca
l pol
icy
vola
tility
1.80
1.85
1.90
1.95
2.00
2.05
2.10
2.15
2.20
0.0 0.5 1.0 1.5 2.0 2.5
monetary policy volatility
econ
omic
gro
wth
3.2
3.6
4.0
4.4
4.8
5.2
5.6
6.0
6.4
6.8
7.2
.00 .01 .02 .03 .04 .05 .06 .07 .08
volatility of FDI inflows
econ
omic
gro
wth
3.2
3.6
4.0
4.4
4.8
5.2
5.6
6.0
6.4
6.8
7.2
0.0 0.4 0.8 1.2 1.6 2.0 2.4
trade flows volatilityec
onom
ic g
row
th
290
Appendix VII: Unit Root Test (Im, Pesaran and Shin (IPS))
Table VIIA Results of the unit root test:
Im, Pesaran and Shin W-stat
variables Level 1st Difference
Statistic Prob. Statistic Prob.
Economic growth -8.84783 0.0000* -15.3595 0.0000*
GDP per capita -4.13905 0.0000* -9.24540 0.0000*
Private capital stock -1.92892 0.0389* -12.0747 0.000*
Human capital -1.34802 0.0888** -4.21906 0.000*
Population growth -2.02781 0.0213* -3.10159 0.0010*
Institutional quality -3.16962 0.0008* -9.48141 0.0000*
Govt. expenditures -2.28235 0.0112* -14.0242 0.0000*
Tax revenue -1.43597 0.0501* -5.57544 0.0000*
Interest rate -1.49581 0.0474* -11.5019 0.0000*
Trade openness -2.43848 0.0074* -10.5498 0.0000*
Average tariff rate -1.56327 0.0490* -10.6388 0.0000*
Gross capital flows -1.18300 0.0784** -5.23312 0.0000*
Fiscal policy volatility -8.22254 0.0000* -19.0345 0.0000*
Monetary policy volatility -9.62713 0.0000* -24.4598 0.0000*
Trade flows volatility -10.8329 0.0000* -18.2460 0.0000*
Capital flows volatility -6.64604 0.0000* -18.3190 0.0000*
Inflation volatility -10.5538 0.0000* -15.3217 0.0000*
Financial development -9.15345 0.0000 0.0056* -4.42139 0.0000*
Exchange rate volatility -5.24132 0.0000* -15.9672 0.0000*
Export concentration -13.3802 0.0000* -19.2223 0.0000*
External debt -3.09266 0.0010* -12.1040 0.0000*
Central bank independence -9.54796 0.0000* -21.8706 0.0000*
Political constraints -4.59616 0.0000* -10.2196 0.0000*
Foreign growth volatility -7.30402 0.0000* -14.2082 0.0000*
Foreign interest rate volatility -10.0606 0.0000* -16.7115 0.0000*
TOT volatility -7.80977 0.0000* -17.3146 0.0000*
Note: To ensure that the residuals are white noise we have chosen lag length based on the Akaike Info
Criterion (0 to 4). Probabilities are computed assuming asympotic normality. * denote the rejection of null
hypothesis of unit root at 5 percent level of significance while ** denote the rejection of null hypothesis of
unit root at 10 percent level of significance.
Source: Authors’ calculation using Eviews-8 software.
291
Appendix VIII: Pairwise correlation matrix
Effect of policy volatility on economic growth
convergence
Human
capital
Physical
capital
Pop
growth
Institutional
quality
Fiscal
vol
Monetary
vol
Trade
vol
Capital
flows vol
Term of
trade vol
Foreign
growth vol
Foreign interest
rate vol
convergence 1.00
Human capital 0.39 1.00
Physical capital 0.27 0.49 1.00
Pop growth -0.31 -0.48 -0.51 1.00
Institutional quality 0.45 0.17 -0.54 0.38 1.00
Fiscal vol 0.04 -0.01 -0.07 -0.06 0.04 1.00
Monetary vol -0.06 0.43 0.39 -0.55 -0.44 0.30 1.00
Trade vol 0.01 0.27 0.25 -0.29 -0.41 -0.06 0.02 1.00
Capital flows vol -0.42 0.05 0.09 -0.14 -0.47 0.32 0.17 0.26 1.00
Term of trade vol 0.19 0.39 0.32 -0.53 -0.20 0.55 0.47 0.00 0.56 1.00
Foreign growth vol 0.06 0.13 0.03 -0.30 -0.16 0.42 0.55 -0.10 0.22 0.48 1.00
Foreign interest rate vol -0.35 -0.06 -0.02 -0.12 -0.22 0.48 0.43 0.06 0.39 0.43 0.40 1.00
292
Determinants of fiscal policy volatility
Previous
period vol
Inflation
vol
Per capita
income
Previous
period debt
Political
constraints
Foreign
growth vol
Term of
trade vol
foreign interest
rate vol
Previous period vol 1.00
Inflation vol -0.19 1.00
Per capita income 0.22 0.11 1.00
Previous period debt 0.29 0.14 0.11 1.00
Political constraints 0.06 0.25 -0.05 0.42 1.00
Foreign growth vol 0.42 -0.01 0.02 -0.14 -0.11 1.00
Term of trade vol 0.51 -0.25 0.10 -0.31 -0.25 0.48 1.00
Foreign interest rate vol 0.34 0.06 -0.24 0.17 0.33 0.27 0.24 1.00
Determinants of monetary policy volatility
Previous
period vol Inflation
vol Per capita
income Exchange
rate vol Previous
period debt Central bank
independence Foreign
growth vol Term of
trade vol foreign interest
rate vol
Previous period vol 1.00
Inflation vol 0.03 1.00
Per capita income -0.20 0.11 1.00
Exchange rate vol 0.31 0.06 -0.26 1.00
Previous period debt -0.39 0.14 0.11 -0.25 1.00
Central bank independence 0.48 -0.19 -0.38 0.32 -0.17 1.00
Foreign growth vol 0.55 -0.01 0.02 -0.04 -0.14 0.15 1.00
Term of trade vol 0.42 -0.25 0.10 0.10 -0.31 0.22 0.48 1.00
Foreign interest rate vol 0.37 0.06 -0.24 0.37 0.17 -0.01 0.27 0.24 1.00
293
Determinants of capital flows volatility
Previous
period vol
Inflation
vol
Per capita
income
Exchange
rate vol
Financial
development
Economic
institutions
Foreign
growth vol
Term of
trade vol
Previous
period vol
Previous period vol 1.00
Inflation vol -0.11 1.00
Per capita income -0.41 0.17 1.00
Exchange rate vol 0.39 -0.03 -0.17 1.00
Financial development -0.02 -0.05 0.17 0.05 1.00
Economic institutions -0.40 0.29 0.53 -0.43 0.00 1.00
Foreign growth vol 0.22 0.07 0.07 -0.02 0.03 -0.14 1.00
Term of trade vol 0.56 -0.06 0.20 0.20 0.11 -0.13 0.48 1.00
Foreign interest rate vol 0.38 -0.04 -0.34 0.42 -0.03 -0.22 0.39 0.43 1.00
Determinants of trade flows volatility
Previous
period vol
Per capita
income
Exchange
rate vol
Financial
development
Export
concentration
Economic
institutions
Foreign
growth vol
Term of
trade vol
Previous
period vol
Previous period vol 1.00
Per capita income 0.02 1.00
Exchange rate vol 0.50 -0.17 1.00
Financial development 0.06 0.17 0.05 1.00
Export concentration 0.13 -0.23 -0.18 -0.07 1.00
Economic institutions -0.42 0.53 -0.43 0.00 -0.09 1.00
Foreign growth vol -0.10 0.07 -0.02 0.03 0.19 -0.14 1.00
Term of trade vol 0.00 0.20 0.20 0.11 0.10 -0.13 0.48 1.00
Foreign interest rate vol 0.06 -0.34 0.42 -0.03 0.18 -0.22 0.39 0.43 1.00