Nigerian Economic Growth and Capital Flight Determinants · Keywords: Capital flight, Co-integration, Economic Growth, Determinants. 1.0 introduction Over the years, the issue of

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ISSN: 2047-2528 Vol. 1 No. 11 [76-84]

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Nigerian Economic Growth and Capital Flight Determinants

F.T.KOLAPO

Department of Banking and Finance

Ekiti State University,Ado Ekiti, Ekiti state, Nigeria.

E-mail: [email protected]

OKE, MICHEAL OJO. (PhD)(Corresponding Author)

Department of Banking and Finance

Faculty of Management Sciences Ekiti State University, Ado Ekiti, Nigeria

E-mail: [email protected]

ABSTRACT This study examines the effect of the determinants of capital flight on the Nigerian economic growth between 1985 and 2010. The indicator of economic growth used in the study is the Gross Domestic Product (GDP) while the determinants of capital flight variables adopted are Foreign Direct Investment (FDI), Inflation Rate (INF), Exchange Rate (EXGR) and Fiscal Deficit (FISD). The ordinary least square (OLS) and the co-integrating analytical technique were used for analysis and the result shows that both the parameters and the model were significant. Specifically, the short run analysis shows that capital flight is mostly caused by inflation while the long run shows that both inflation

rate and exchange rate significantly determine capital flight which in turn adversely affects economic growth.

Keywords: Capital flight, Co-integration, Economic Growth, Determinants.

1.0 INTRODUCTION

Over the years, the issue of capital flight from developing countries including Nigeria has

received appreciable attention from researchers. Concerns have been expressed about the

causes and consequences of these capital outflows because the lack of financial resources for appropriate economic development in Nigeria and most sub-Saharan African countries

for which many have been led to into external borrowings to augment domestic resources in

their quest for economic growth.

According to cooper and Hardt (2000) capital flight entails flow of financial assets resulting from the holder’s perception that capital is subjected to inordinate level of risk due to

devaluation, hyperinflation, political turmoil or expropriation of retained earnings at home

in domestic currencies . The owner of funds in this hostile environment is seeking a safe

haven for his funds. Ndikumana and Boyce (2002) also defined capital flight as residents’

capital outflows, excluding recorded investment abroad.

Capital flight from developing countries including Nigeria, not only aggravates the shortage

of resources for development; it indirectly leads to a decline in growth. Growth is reduced

partly because investment has been diverted abroad and also because necessary imports

are limited by the foreign exchange drain from both the flight itself and the fact that

earnings on such assets are often not repatriated (Pastor, 1990).

Capital flight is different from capital export which is a normal phenomenon. It can foster

growth and generate employment in addition to providing solution to other national

economic problems (Grigoryev and kosarev 2000). Causes of capital flight according to Ajayi

mailto:[email protected]

mailto:[email protected]


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(2005) include varying risk perception, exchange rate misalignment, financial sector

constraints and repression, fiscal deficits, weak institutions, macroeconomic policy

distortions, corruption among others.

According to Deppler and Willamson (1987), capital flight leads to a net loss investment and

growth. Given the fact that capital flight is a diversion of domestic savings away from

domestic real investment, the pace of growth and development in the economy is retarded

2.0 LITERATURE AND EMPIRICAL REVIEW

The term “capital flight” arouses emotions in some quarters. Some analysts view capital

flight as a symptom of a sick society while others view capital flight as the cause of heavily

indebted countries’ inability to recover from their present debt problems. Capital flight is

regarded by others as a ‘pejorative’ description of natural, economically rational responses to the portfolio choices that have confronted wealthy residents of some indebted countries

in recent years” (Lessard and Williamson, 1987)

In general, it is believed that the investors from all countries whether developed or

developing will base their investment decisions on the relative returns and risks of such

investment at home and abroad. There are possibly a number of valid reasons why capital flows from developing countries is labeled as “capital flight”. The first is the general

presumption in economics that capital should flow towards capital-scarce countries. Any

flow in the opposite direction, that is from developing to developed countries are not only

unusual but abnormal. The second reason is related to a policy issue. What is important is

the extent to which those assets held abroad could be utilized at home to reduce the level of external indebtedness and relieve the inherent liquidity problems brought about by debt

service obligations (pastor, 1990).

In distinguishing between capital flight and normal capital flows, two broad approaches are

taken in the literature. The first is an identification of specific episodes (or countries) that are characterized by abnormally adverse economic conditions for investment and consider

all estimates of the acquisition of external claims by the private sector as capital flight. The

second approach distinguishes capital flight from other capital movements by considering

capital flight to consist of the acquisition of external claims that are not reported to the

domestic authorities. (Chang and Cumby, 1991); Dooley (1988). Those various difficulties

lie at the heart of the varying definitions and computational methodologies which have been employed to quantify the capital flight is one of the quandaries in this area in a sense and

yet perhaps one of the strong points. One cannot but therefore agree with Chang and

Cumby (1991) that there exists more than one viable definitions of capital flight and the

appropriate choice will depend on the policy questions more pertinent to the country for

which capital flight is being estimated and the time period under consideration. A distinction is often made between capital flight and so called “normal” capital flows.

“Capital flight is capital that flees” (Walter, 1987; Kindle Berger, 1987). Normal capital

flows on the other hand, refer to flows that correspond to ordinary portfolio diversification of

domestic residents. According to Cuddington (1987), capital flight refers to short-term

private capital outflows. It involves “hot money” that responds to political and financial crisis, heavier taxes, a prospective tightening of capital or a major devaluation of the

domestic currency arising from a high misalignment of the currency. In the Morgan

Guaranty Trust Company (1986) an expansive definition is adopted where capital flight is

“the reported and unreported acquisition of foreign assets by the non-bank private sector

and elements of the public sector”.

Capital flight at the broad extreme has been defined to include all private capital outflows

from developing countries (Kahn and UI Hague, 1987) while at the narrow extreme, it

includes only illegal capital exports (Lessard and Williamson, 1987). The broad perspective

takes into consideration all private capital outflows from developing countries be they short-

term or long-term, portfolio or equity investments could be termed capital flight. This is because developing countries are generally considered to be short of capital and should


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therefore be net borrowers in the development process, supplementing domestic savings

with the external finance. Thus, Kindleberger (1987) and Walter (1987) broadly define

capital flight as all capital that “flees” irrespective of the motive. Alternatively, capital flight can be considered as the change in the private sector’s net foreign assets (World Bank,

1985; Erbe, 1985; Morgan Trust, 1986; Chang and Cumby, 1991).

The major constraint to consensus on a definition of capital flight is traceable to the

difficulties involved in distinguishing between those flows that can be considered “normal”

and those that fall in the category of “flight capital”. Normal capital outflows are defined as the legal capital outflows, while all capital outflows based on the desire to place assets

beyond the control of domestic authorities are labeled capital flight (Dooley, 1988). However

separating capital flight from normal portfolio diversification and trade transactions is

fraught with difficulties (Eggerstedt et al, 1995) and could involve some elements of value –

laden judgment (Ojo, 1992) which explains in parts the variations in definitions of capital flight.

Forgha (2008) and Valeria Gusarova (2009) studing Cameroon and some developing nations

respectively observed that capital flight adversely impact real economic growth.

Beja (2006) notes that with capital flight presents the possibility of cutting off a nation from external sources of funds. Consequently, it becomes more difficult to implement economic

policies, and improving the social conditions of people also becomes more difficult.

Ajilore (2010) and De Boyrie (2011) observed that trade faking and mis-invoicing account

majorly for capital flight in selected African countries including Nigeria and hinder long-term economic growth.

Ayadi (2008) found interest differential and exchange rate depreciation significant causes

of capital flight in Nigeria and concluded that capital flight is depriving Nigerian economy of

substantial and critical financial resources needed for investment and building of social

capital among others.

Kosarev (2000) identified capital export as a normal economic phenomenon which does not

affect the economy significantly from global perspective, while capital flight presents a

danger and leads to the impoverishment of the economy.

2.1 Determinants of Capital Flight in Nigeria

Based on the existing literature, the determinants of capital flight are many. These various

causes can be grouped under relative risks, exchange rate misalignment, financial sector constraints and/or repressions, fiscal deficits and external incentives (Khan et.al 1987) and

disbursement of new loans to LDCs (Cuddingtom 1987). These are no doubt economic causes of capital flight. There are, however, other non-economic causes which though

important are often ignored. These include the corruption of political leaders. The study of

Ajayi in 2005 affirmed that the determinants of capital flight in Nigeria which in turn

impact economic growth include varying risk perception, exchange rate misalignment,

financial sector constraints and repression, fiscal deficits, weak institutions,

macroeconomic policy distortions, corruption and extraordinary access to government funds among others.

3.0 MODEL AND ESTIMATION TECHNIQUE

This study adopts the real growth model of Forgha (2008) in a study of Cameroun. In the study, Forgha established that capital flight adversely impact real economic growth. The

original model is specified as follows;

LRGDPt=bo+b1 ∆CAPFLt+b2∆EDTYt+b3∆TOTt+b4∆POPGt+b5∆INFLAt+U2……..1


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Where:

∆LRGDPt= change in log of real Gross Domestic Product in current period.

∆CAPFLt= Capital flight in U.S Dollar in current period.

∆EDTYt= Change in log of external debt/ GDP ratio in current period to capture debr

burden

∆POPGt= Active population growth rate used as proxy for labour force in current

period

∆INFLAt= Inflation rate in current period.

However, to achieve the objectives of the study, the above model is modified as follows for

the analysis of the Nigerian case.

GDP = f (FDI, INF, EXGR, FISD, U)………..(2)

The explicit form of equation 1 is represented as

GDP = β0+ β1FDI+ β2INF + β3EXGR + β4FISD + U………..(3)

Where:

GDP = Gross Domestic Product

FDI = Foreign Direct Investment

INF = Inflation Rate

EXGR= Exchange Rate

FISD = Fiscal Deficit

U = Stochastic Disturbance (Error Term)

F = Functional Relationship

Bo = Intercept of relationship in the model/ constant

B1 – B4 = coefficients of each of the independent variables

The following are the a priori expectations of the coefficient of the model β 2, β 3, β

4 0, β 1 > o.

By log linearizing, the model becomes;

Log (GDP) = β0 + β1log (FDI) + β2 log (INF) + β3log(EXGR)+ β4 log(FISD) + µ .....(4)

Where: Log = Natural log

From the Equation 3, the model can be specified in a time series form as;

Log (GDP)t= β0 + β1 log (FDI)t + β2 log (INF)t + β3 log (EXGR)t + β4 log (FISD)t + µ ......(5)

From equation (4), an error correction (ECM) model formulation can be express as:


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Where:

Error Correction term

t-1 meaning the variables were lagged by one period

White Noise Residual

To test the existence of long run relationship, equation (5) can be conducted by placing

some restrictions on estimated long run coefficient of variable. Hence, the hypothesis for

the test is formulated as follows:

3.1 Estimation Techniques

To examine the long run and short run relationships, we applied the Johansen Co-

integration test. The choice of the technique is to examine the long run relationship

between the dependent variable and explanatory variables unlike the Ordinary Least Square

(OLS) estimation technique which produce spurious and short run results which may be

misleading.

3.2 Empirical Analysis and Discussion

The model formulated for the study revealed the Gross Domestic Product (GDP) as the

dependent variable while the foreign Direct Investment (FDI), Inflation Rate (INF), Exchange

Rate (EXGR), and Fiscal Deficits are the independent variables and the determinants of

capital flight which invariably affects the economic growth.

4.0 RESULTS OF STATIONARITY (Unit Root Test)

Testing for the existence of unit roots is a principal concern in the study of time series

models and co-integration. The presence of a unit root implies that the time series under investigation is non-stationary; while the absence of a unit root shows that the stochastic

process is stationary.

Table 4.1: Result of Stationary Test

Variables ADF Test Statistic Value

Mackinnon Critical Value

@ 5%

Order of Integration

Remark

GDP -3.292758 -2.9969 I(1) Stationary

FDI -3.608625 -2.9969 I(1) Stationary

INF -3.285252 - 2.9907 I(0) Stationary

EXGR -3.309450 -2.9969 I(1) Stationary

FISD -4.305396 -2.9969 I(1) Stationary

Sources: Extracted from computer output


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The table above shows the stationarity of the variables at different levels of differencing. It

could be seen that INF is the only variable that is stationary at level difference while other

variables (GDP, FDI, INF, EXGR and FISD) are stationary at first difference

Table 4.2 The Least Square Estimation Results

Below is the presentation of the least square estimation results from the analysis conducted

on the specified model.

Dependent variable

Independent Variable

Constant FDI INF EXGR FISD

GDP 10.46043

(9.907017)

0.1246

(1.124826)

-0.3228

(-2.5221056)

1.0943

(11.42640)

0.0113

(0.502761)

R2= 0.949967 DW= 0.888602

Fc= 99.68012

From the above results, it can be seen that the co-efficient of the constant parameter is

positively related with the GDP. This indicates that if all explanatory variables are held

constant, GDP will increase by 10.46045units. The co-efficient of the FDI is 0.124587, which shows that a positive relationship exist between GDP and FDI which is also in

accordance with the stated a priori expectation meaning that a unit increase in FDI will

lead to 0.124587 increase in GDP.

The co-efficient of INF is negative (-0.322763). This reveals that a negative relationship exist

between the GDP and the INF which is in consonance with the stated a priori expectation. This implies that any unit increase in INF will lead to a 0.322763 decrease in GDP.

The result also shows that a positive relationship exists between GDP and EXGR. This is a

deviation from the a priori expectation. This means that a N/$ variation in exchange rate

will result to 1.094336 change in GDP. It could be deduced that a positive relationship exist between FISD and GDP indicating that an unit increase in FISD will lead to 0.011284

increase in GDP. This is a deviation from the a priori expectation. The result shows that in

the short run, capital flight is mostly influenced by inflation rate.

The explanatory power of the model is estimated at 0.949967 which indicates that 94.99%

variations or changes that occurs in the present state of GDP is determined by the changes in the values of the independent variables while the remaining 5.01% is explained by the

variation outside the model or captured by the error term.

4.1 The Long Run Model

From the co-integration result, it is evident that the long run test indicates four co-

integrating equations at 5% significance level.

The long run or co-integrating equation is presented as:

GDP = 0.154554 FDI -1.990459INF - 0.878450EXGR+ 0.172016 FISD-

8.600382 (0.24462) (0.96035) (0.17601) (0.08398)

From the above, FDI and FISD have a positive relationship with GDP on the long run, while

INF and EXGR have a negative relationship. Holding all the independent variables constant,

the value of GDP is expected to decrease by 8.600382 on the long run. The long run analysis reveals that inflation rate and exchange rate significantly influence capital flight

and as a result, adversely impacts the Gross Domestic Product

The equation also shows that there is tendency for all the variables to meet at equilibrium,

though the speed of adjustment is slow, in the long run, there is tendency of the equation

cointegrating.


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4.2 Test for the Statistical Significance of the Parameters (Standard error test)

To test for the statistical significance of each of the parameters, the standard error test is be employed. This involves the comparison of half of the co-efficients of the variables with the

standard error.

The result is presented in the table below

Table 4.3: Standard error Test

Variable Co-efficient Coefficient

2

Standard Error Decision

FDI 0.154554 0.077277 0.24462 Not Significant

INF -1.990459 0.99523 0.96035 Significant

EXGR -0.878450 0.439225 0.17601 Significant

FISD 0.172016 0.086008 0.08398 Significant

From the above table, it could be seen that all the variables are significantly determine capital flight and indirectly the economic growth except FDI.

4.3 Test for Overall Significance of the Model (F-Test)

The test is done at 95% confidence level equivalent to 5% significance level. The table below

summarized the result.

F- Statistics

From the above analysis, it can be deduced that the F-calculated (99.68012) is greater than

the value of F-tabulated (2.84). This is a clear indication that the whole model is statistically significant.

4.4 Mimplications of Findings

A clear observation of the aforementioned results show that both in the short run and long

run, FDI and FISD have a positive relationship with GDP, while in the short run, EXGR has a positive relationship with GDP but a negative relationship in the long run. A negative

relationship exists between INF and GDP both in the short run and long run.

From the result also, INF, EXGR and FISD are all significant while FDI is found to be

statistically insignificant.

The result reveals that the EXGR is significant, indicating the importance of the variable in

the repatriation of profits legally and illegally from the country. EXGR determines the

foreign currency equivalence of the capital displaced from the country and also the eroded

amount of financial resources moved out of the country.

It also shows that FISD is significant. The FISD is being financed through borrowings from

international financial organizations. However, the servicing of such debts in form of

interest payments and principal repayment causes a whole lot of financial movements out

of the country. This however would have a positive impact on the economy if the loan

Decision

F –calculated F –tabulated H0 H1

99.68012 2.84 Reject accept


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obtained initially were used for social and infrastructure development. INF is estimated to

be significant meaning that INF and its effects in the model is significant because of its

depressing impact on the economy at large. In other words, a persistent increase in prices of goods and services in the economy will encourage capital flight.

FDI is estimated to be statistically insignificant but economically significant as it will

undeniably contribute to the filling of the resource gap between desired investment and

locally mobilized savings. The FDI will contribute greatly to the GDP but capital flight will

certainly set-in in the event of repatriation of profits by foreign investors to home country, thus will have a negative influence on GDP and the economy at large.

5.0 CONCLUSION

Based on the result obtained and interpreted, we concluded that of all the determinants of capital flight, FDI plays lesser a role in affecting GDP while the FISD, INF and EXGR play

significant roles in affecting the level of GDP in Nigeria.

From the long run analysis, it could be seen that FDI is positively related to GDP and also

insignificant. The relationship is in conformity with the apriori expectation. Likewise, FISD

is also positively related to GDP and also significant though this is a deviation from the

apriori expectation. INF and EXGR are negatively related to GDP which conforms to the

apriori expectations. This means that the inflation rate and the exchange rate are the

prominent determinants of capital flight which affect the Gross Domestic Product within the period examined (i.e. 1985-2010). The model is well represented at the explanatory power of

the model is very high. It can be concluded that capital flight has a negative impact on the

economic growth in Nigeria.

5.1 Policy Recommendations

In view of our findings, we recommend the following;

The monetary authorities should strengthen monetary and fiscal policies to further reduce

inflation rate, boost confidence in the domestic currency and thereby stem the tide of

capital outflow from the economy.

The monetary authorities should also initiate policies that would encourage stable and

realistic exchange rate regime in order to reduce investors’ preference for foreign assets over

domestic assets.

Also, government fiscal and monetary policies should be strengthened to reduce fiscal

deficits and promote monetary stability.

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Seminar Titled: Capital Flows and Economic Transformation in Nigeria, at the Central Bank of Nigeria’s 5th Annual Monetary Policy Conference. CBN Conference

Hall, Abuja Nov. 10-11. Ajilore. O. Taiwo (2010): “An Economic Analysis of Capital Flight from Nigeria, International

Journal of Economics and Finance. 2(4),

Ayadi, (2008): “Econometric Analysis of Capital Flight in Developing Countries”, 8th Global

Conference & Economics.978-09742114-5-9

Chang, P.H.K and Cumby, (1991): “Capital Flight in Sub-Saharan African Countries”. Policy Research Working Paper series No. 1186. The World Bank, Washington, D.C.

Cooper H.W & J.P Hardt (2000): ”Russian Capital Flight, Economic Reforms, and U.S

Interests”: An Analysis, Congressional Research Service (CRS), Report for Congress,

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Documents

Nigerian Economic Growth and Capital Flight Determinants · Keywords: Capital flight, Co-integration, Economic Growth, Determinants. 1.0 introduction Over the years, the issue of