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1
MACRO ECONOMIC EFFECTS OF EXTERNAL MONETARY POLICY SHOCKS TO
ECONOMIC GROWTH IN WEST AFRICA
by
Jonathan Olusegun Famoroti
University of Kwazulu-Natal
Email: [email protected]
and
Christian K. Tipoy
University of Kwazulu-Natal
Email: [email protected]
Abstract
The study analyzed the impact of monetary policy shocks to economic growth in fourteen countries
of Economic Community of West African States (ECOWAS) sub region, using quarterly data from
1980(1) to 2017(4). We employed a Panel Structural Vector Autoregressive (SVAR) model for
the study. The results suggest that the external shocks have significant effects on the economic
growth and stability of ECOWAS. The shocks of FFR Federal Fund Rate (FFR) significantly
impacts economic growth and inflation rates in the ECOWAS economy. Also, oil price shocks
significantly affected exchange rates. However, the internal shocks have greater effects than the
external shocks. Furthermore, Money supply has the prime impact on the economic growth,
inflation rate and interest rate. It further suggests a positive and significant effect on the inflation
rate, which is in line with the Monetarist school of thought that inflation is a monetary
phenomenon. This implied that monetary policy instruments played an important role in the output
growth and other macroeconomic policies in ECOWAS. It was also discovered that the inflation
rate majorly contributes to money supply. Our findings further suggest that there are idiosyncratic
evidences found in the robustness check, as price and exchange rate puzzles were apparent within
the period.
Key words: Monetary policy; economic growth; ECOWAS.
JEL: E5
1. INTRODUCTION
1.1 BACKGROUND OF STUDY
Monetary policy shocks occur when a central bank departs, without proper advance warning, from
an established pattern of interest rate increase or decrease, or money supply control. These shocks
might be necessitated due to different reasons, which could be internally or externally motivated.
However, these deviations from the monetary authorities are meant to ultimately promote the
economic growth and stability of these countries but in most cases the effect is usually counter-
2
productive (IMF, (2016), The natural question then is how has monetary policy shocks drove
economic growth?
One of the major key drivers of economic growth is monetary policy, through its shock effects on
macro-economic variables. And the unstable economic growth and unsustainable rise in inflation
inflationary rate can be checkmated through appropriate transmission mechanism. This is because
weak transmission of the monetary policy tools results into results into counterintuitive reaction
of the inflation (Rabanal, 2007).
Thus, monetary policy is a vital policy instrument like fiscal policy to achieve targeted results, of
which the objectives are based on priorities. In a small open economy, it could be inflation
targeting while in some others it could be exchange rate targeting or output growth targeting (See
Punita Rao et al, (2006) and Kandil, 2014). Meanwhile, Mishkin, (1995) opined that monetary
authorities should have the right assessment of the period and the impact of their monetary policy
on the economy, which requires an appropriate knowledge of the monetary policy mechanism as
it affects the economy. This opinion was further buttressed by Raghavan and Silvapulle (2006),
that propelling monetary policy in the right direction demands that policy makers should have a
better understanding of the transmission mechanism by which the monetary policy shocks affect
the economy, particularly, the real sectors. However, the issue of what constitute the channels of
monetary transmission mechanism is yet to be resolved. This includes advanced economies like
United States of America (US), where a lot of literature has been written, there is yet to be an
agreement on the channel and the impact of monetary policy shocks to the macro economic
variables. (Allen and Robinson, (2015). For instance, Mishra et al, (2010) examined the Orthodox
monetary transmission mechanism in Low income countries and opined that the bank lending
channel are more effective while other channels are weak, particularly the interest rate.
Conversely, the empirical findings of Boivin et al (2010) and Ncube and Ndou, (2011) suggest
that interest rates are the main transmission mechanism. While Acosta-Ormaechea and Coble,
(2011) in their findings revealed that though, the interest rate is effective channel of transmission
mechanism, but the exchange rate is more effective. Apart from the conventional channels of
interest rate, money supply, bank reserves, asset prices and exchange rate, the use of
unconventional monetary policy is on the increase.
3
The- increasing globalization in the area of trade and economic integrations has made the World
to become a global village, which has created a platform for which the macro economic variables
interact across countries. Also, there are global variables, like crude oil price, creating economic
variabilities across the countries. Fluctuations in these variables create shocks to various
economies, that must be responded to by the affected countries. (Lukeman and Olomola 2016)
West African Countries inclusive.
Indeed, International monetary policy debates have in the recent times focused on the cross-border
spillover effects, particularly since the global economic crisis. Recently, studies further considered
probable effects of globalization of monetary policy and proclaimed that some monetary policy
verdicts from the advanced World reduces the monetary autonomy in developing and emerging
markets. (Buch et al., 2018). The empirical study of Yellen, (2016) suggests that the spillover of
monetary policy has a positive effect on other economies. The tragic effects of the global economic
depression of the 80s, created the need to identify diverse internal and external shocks that could
regulate the economic fluctuations. In This study, we provide an empirical support for Ecowas
region as it responds to external macroeconomic shocks.
1.2 Problems and Motivation
Unsustainable economic growth has become a thing of concern among the ECOWAS countries
going by the recent statistics. The real growth rate experienced was still on the increase up to 2011
and decline subsequently. Worst still, by 2014, due to the global economic shock, the growth rate
was at a lower rate of 3.2%, which fell further to 0.5% in 2016. In the same vein, all
macroeconomic variables in the regions recently have not been impressive. For instance, the
inflation rate in West Africa, between 2006 and 2008, was 8.1%, upsurge to 13.3% in 2017. (IMF,
Economic Outlook,, 2016, 2017 and 2018). These macro-economic problems may not be
unconnected with external shock effects of monetary policy shocks.
The plethora of economic literatures on the monetary policy shocks to economic growth, focused
on the advanced countries and emerging markets, but there is still dearth of literatures on this
topical issue in west Africa. Furthermore, there is yet to be a consensus on the empirical findings
on the effects of the international monetary transmission to economic growth. For instance,
empirical investigations revealed that external shocks accounted for greater proportions of the
4
economic fluctuations in developing countries (Bucke et al, 2007). Whereas, the developing
countries, like ECOWAS, which are generally susceptible to external shocks because of their
structural characteristics, dependence on international trade, greater reliance on foreign direct
investments and foreign aids (Kousar, et al 2016), require further empirical investigations to
address their macro-economic issues. Therefore, the adequate knowledge and management of
external shocks, is a vital issue for consideration in the management of monetary policy.
The study of monetary policy shocks effects to economic growth is of immense importance for the
monetary authorities to design an effective monetary policy in this sub region, particularly in their
transition to a common monetary union.
Based on the above background therefore, this study objectively examined the internal and
External shock effects of the monetary policy transmission mechanism to economic growth in
Economic Community of West African States (ECOWAS). This objective extensively analyses
the policy transmission mechanism channel that is most effective in transmission policy shocks to
output growth and ascertain the extent to which the policy shocks are significant.
The rest of this study is organized thus: Section two contains ECOWAS and Economic Statistical
Data, section three related literature, section four presented methodology and analysed data,
section five contains the empirical findings. Section six concluded the study with
recommendations.
2. ECOWAS and Economic Statistical Data
ECOWAS is a sub-region in the Sub Saharan African (SSA) countries was formed in May 1975
and it has fifteen countries as members- Viz Benin, Burkina Faso, Cape Verde, Cote d’lvoire, Mali,
Guinea, Senegal, Togo, and Guinea Bissau. Others country members are Gambia, Ghana, Niger,
Nigeria, Sierra Leone and Liberia. Mauritania left in 2002. The region has a historical economic
integration known as Economic Community of West African States, (ECOWAS) since 1975. It is
an aged-long regional cooperation, particularly in trade and monetary integrations. By Article 2
of the ECOWAS treaty, the basic aim and objective include promotion of economic cooperation
and integration, establishment of an economic union, maintenance and enhancement of economic
stability, fostering relations among the member states and contribute to the development of African
continent. Supporting this purpose, Metzger, (2008) in summary asserted that, these objectives
5
enhance aggregate monetary stability and economic growth when the member states integrate
indiscriminately into the global economy rather than remaining independent. By ECOWAS
statistical data of 2018, the total population of the region stands at 367,255,391M, Annual GDP
565,089M$, GDP per cap 1,539$, and Debt (%GDP) 30.36%. (Table 1) The Goods Exported from
US to Ecowas in 2017 amounts to $4.8b, imported goods from ECOWAS were $9.3b (IMF, 2018).
Table 1. ECOWAS STATISTICAL DATA
Country Population Annual GDP GDP per capita HDI Debt (%GDP)
1 Benin 11,175,692 $9,247M $827 0.515 49.68%
2 Burkina Faso 19,193,382 $12,323M $642 0.423 38.28%
3 Cape Verde 546,388 $1,773M $3,244 0.654 129.49%
4 Ghana 28,833,629 $58,997M $2,046 0.592 73.41%
5 Guinea 12,717,176 $10,473M $823 0.459 42.85%
6 Guinea-Bissau 1,700,000 $1,347M $792 0.455 48.83%
7 Ivory Coast 24,294,750 $37,353M $1,538 0.492 46.98%
8 Liberia 4,731,906 $3,286M $694 0.435 28.30%
9 Mali 18,541,980 $15,334M $827 0.427 35.89%
10 Niger 21,477,348 $8,120M $378 0.354 45.12%
11 Nigeria 190,886,311 $375,746M $1,968 0.532 19.61%
12 Senegal 15,850,567 $21,070M $1,329 0.505 60.43%
13 Sierra Leone 7,408,000 $3,775M $510 0.419 54.88%
14 The Gambia 2,100,568 $1,490M $709 0.46 118.48%
15 Togo 7,797,694 $4,758M $610 0.503 81.59%
TOTAL:
ECOWAS 367,255,391 $565,089M $1,539 30.36%
Source: Countryeconomy, 2018
6
3. Brief Literature Review
International monetary policy debates have in the recent times focused on the cross-border
spillover effects, particularly since the global economic crisis of 1980s, 90s, 2008, and the most
recent, 2014 of which there are no consensus. The Studies of Kim, (2001); Miniane and Rogers,
(2003); Jannsen and Klein, (2011) suggest that Monetary policy shocks from US has a positive
effect on the output of the developed countries. While the policy shocks from the developed nations
reflects a negative effect on the economies of the emerging markets. Mackowiak, (2007); and
Ivrendi and Yildirim, (2013) investigated the impact of both domestic and external monetary
policy shocks on the macroeconomic variables on the emerging markets of Brazil, Russia, China,
South Africa and Turkey, captioned ‘BRICS_T’. Using SVAR econometric model, they found that
the chief transmission mechanism is the exchange rate. Also, tight monetary policy leads to an
appreciated value of the domestic currency, rising interest rates, controlled inflation and reduction
in output. Similarly, Sato et al (2009), employed SVAR to investigate the effects of the external
policy shocks arising from US between the period 1978-2007, and revealed that the external shock
played a leading role to influence the fluctuations in the macroeconomic variables in East Asia.
IMF, (2007), adopted Panel Analysis, SVAR and dynamic factor model and examine the extent to
which the emerging economies can decouple from the economy of US and the effects of monetary
policy shocks from US affect East Asia, Latin America, and Sub Saharan Africa Countries. Zhang
and McAleer (2009), investigated the external effects of monetary policy shocks of US on the
regional in East Asia which comprise of Korea, Taiwan, Hong Kong, Singapore, Malaysia,
Indonesia, Thailand, Philippine and China. The authors used SVAR with block exogeneity to
ascertain whether the internal or the external shocks dominate the shock disturbance and found
that the US shocks played an important role in the determination of real output variations in five
Asian Countries. Also, the shock effects are positive and much higher in these countries, while the
Chinese and Japanese shocks are less important. Starr, (2005) used Structural VAR model to
analyze and ascertain the effects of monetary policy in commonwealth states and finds that there
is significant effect of the interest rates on output growth in Russia, but little impact in others.
In Summary, these reports show that both the emerging markets and developing economies are
significantly being affected by external shocks from the Developed nations particularly from US.
7
Thus, the need to carry out similar investigation in ECOWAS economy is imperative, where there
are death of literature,
4 Data, scope, and Definition of variables
This study used quarterly panel data for the period 1980q1-2017q4, covering fourteen-member
countries in ECOWAS Viz: Benin, Burkina Faso, Cape Verde, Cote d’lvoire, Mali, Guinea and
Senegal. Others are Togo, Gambia, Ghana, Niger, Nigeria, Sierra Leone, and Liberia.
Following Che and MacDonald (2011), Ngalawa and Viegi (2011), Popescu (2012), Coric et al
(2015) and Joonyoung Hur (2017), the study used Real GDP rate (RGDP): it is used in the study
as the proxy for economic growth, which measures the economic effects of the policy shocks.
Domestic Interest Rate (IR)- it represents the policy indicator of the respective central banks. It is
the monetary policy related rate in percentages, which is brought into the model as a monetary
tool. Exchange rate (ER)- this is the value of national currency per USD. An increase in the
exchange rate implies a depreciation of the country’s currency, which implies that the variable has
effects on inflation. It is introduced into the model being an open economy. Money supply (M2)-
this is monetary base growth rate. It is the aggregate money supply rate, representing the total
money in circulation plus demand deposit plus time deposit (i.e. broad money). This is
incorporated into the model as an intermediate monetary policy target. Inflation Rate (INF)- this
is the general increases in price level. According to literature, the interest rate may be affected
through the flexibility of the exchange rates (Bernanke and Blinder (1992). Finally, Global Oil
price (Oil) and Federal funds rate (FFR) are incorporated as exogenous variables to the domestic
economy. These data are obtained from international Financial Statistics (IFS) and Federal
Reserve Bank of St Louis.
4.2 Methodology
4.2.1 Introduction
The study examined the extent to which economic growth fluctuations in West Africa arising from
external shocks. It focused on the external shocks from US as they affect the economic variables
in the ECOWAS. This is because the economic development of US certainly has a substantial
impact on the global economy, comprising West Africa. This is based on its international relations
and size. In the first instance, US dollar is the most generally used currency in the global financial
8
transactions and trade, hence fluctuations in the monetary policy of US plays a vital role among
the drivers of global financial transactions. Thus, about 62% of the world currency that is in
reserves are being held in US dollars (Glassman, 2019). Also, World-widely, US has the only
single main economy that accounts for about 22% of the total output of the world, 20% of global
FDI, 10% of world trade and about 20% of world energy demand (Kose et al, 2017).
4.2.1 Model
The Panel SVAR employed is preferred to VAR because, it captures the dynamic behavior of all
the variables in the model. Unlike VAR model, the estimation of the parameters is more efficient
in SVAR and the rationale for the imposition of restrictions to identify the monetary policy shocks
are equally provided, making it a more powerful instrument for analyzing macroeconomic policy.
Apart from the restrictions, the main assumption in panel SVAR is that all the variables are
independent and endogenous, unless identified otherwise. Various studies have employed this
technique (Kutu and Ngalawa, 2016; Rotimi and Ngalawa, 2017, Akande and Kwenda, 2017).
4.2.2 A Recursive Structural VAR Model
The structure of the economic model is expressed in a reduced form as:
𝑌𝑡 = 𝐴𝑖 𝑌𝑡−1 + …+ 𝐴𝑞 𝑌𝑡−𝑞 + 𝐵𝑍𝑡 + 𝐵1 𝑍𝑡−1 + …+ 𝐵𝑝 𝑍𝑡−𝑞 + 𝑈𝑡 ……………..… (1)
Where t=1… T, 𝑌𝑡=Mx1 the vector of the endogenous variables with intercept determinants and
time trend. Z is also the vector of the exogenous variables. while 𝑈𝑡 is the vector of the residuals,
𝐴𝑖𝑎𝑛𝑑𝐵𝑖 represent the matrices of the coefficients.
Let the matrix of the variance and the covariance be
∅ = E (𝑈𝑡 𝑈′𝑡) ………………………………………………………………..……… (2)
For this study OLS shall be used for the estimation of 𝐴𝑖 , 𝐵 𝑎𝑛𝑑 ∅
The parameters of the structural form is:
𝐶0 𝑌𝑡 = 𝐶1 𝑌𝑡−1+ … + 𝐶𝑞 𝑌𝑡−𝑞 + D𝑍𝑡 + 𝜀𝑡 ………………………………………..………… (3)
Where 𝐶𝑖 and D represent the matrices of the parameters of the economic variables, and 𝜀𝑡
represents the structure of the economic shock, with variance and covariance matrices denoted as
9
W= E (𝜀𝑡 𝜀𝑡′). Equations a and b representing the reduced and the structural form are related in the
form
𝐴𝑖 = 𝐶0−1𝐶𝑖 , 𝜀𝑡 = 𝐶0 𝑈𝑡 ……………………………………………………….………… (4)
Similarly, the variance and covariance matrix relationship of the reduced (1) and structural forms
(2) is written as ∅ = 𝐶1 W (𝐶0−1)′.
4.2.3 Lag length
2-lag length criterion has been selected. This is considered adequate for this study because the lag
number captures the dynamism of the system without the problem of degree of freedom and it does
not give room for serial correlation of the residuals. Indeed, under specification of model leads to
model misspecification; while over specification causes loss of degrees of freedom. This approach
follows studies like Sharifi- Renani (2010), Coric et al (2015) Kutu and Ngalawa, (2016) who have
given guidance for the choice of the lag.
4.2.4 Shocks identification-Several authors including, Christiano et al (1999, 2005), have
identified shocks of the monetary policy to an economy using Cholesky decomposition. Similarly,
in this study we apply recursive restrictions to the ECOWAS economy. The recursive VAR
involves structural rigidity of the underlying relationships between the variables, which therefore
leads to the questioning of its ability to appropriately describe the dependences between the
variables of a model. Hence, in order to eliminate these weaknesses, it is essential to use SVAR
identification method.
The Ecowas monetary policy equation can be specified in the order: Y= [Global oil price, Federal
fund rate Real GDP, inflation rate, money supply, domestic interest rate and exchange rate,]. The
basis of this ordering centers on the implicit assumption of the monetary authority that some
variables may or may not contemporaneously vary with the policy decisions. For instance, Output
growth and prices do not respond simultaneously with the monetary policy changes, except the
world oil price. Similarly, the domestic interest rate may not respond simultaneously with the
changes in output growth and the exchange rate. However, the exchange rate has contemporaneous
relationship with the various shocks of all the variables. Furthermore, we consider two external
10
shocks for the purpose of giving a better capturing of the various sources of vulnerabilities of west
African countries during the studied period. These are the Global oil price and the Federal funds
rate, which are herein assumed to be exogenous contemporaneously to all the identified variables
in the domestic economy. while the federal fund rate is endogenous to the world oil price. This
structure of the economy has been identified, because the West African countries are highly open
and being affected through foreign shocks. These shocks are identified through the imposition of
zero restrictions to the matrix coefficients of A and B. Following Amisano and Giannini, (1997);
Coric, et al, (2015); Kutu and Ngalawa, (2016) and Nazamani et al, (2017), the Panel SVAR
requires 2𝑛2 -n(n+1)/2 or 70 restrictions to matrices A and B altogether. (n= no of variables).
A=
[
𝑈𝑂𝑖𝑙
𝑈𝐹𝐹𝑅
𝑈𝑅𝐺𝐷𝑃
𝑈𝐼𝑛𝑓
𝑈𝑀2
𝑈𝐼𝑛𝑡
𝑈𝐸𝑥ℎ ]
=
[
1 0 0 0 0 0 0𝑎21 1 0 0 0 0 0𝑎31 0 1 0 0 0 0𝑎41 0 𝑎43 1 0 0 00 0 𝑎53 𝑎54 1 𝑎56 0
𝑎61 𝑎62 𝑎63 0 0 1 𝑎67
𝑎71 𝑎72 𝑎73 𝑎74 𝑎75 𝑎76 1 ]
[
𝑉𝑜𝑖𝑙
𝑉𝐹𝐹𝑅
𝑉𝑅𝐺𝐷𝑃
𝑈𝐼𝑛𝑓
𝑈𝑀2
𝑉𝐼𝑛𝑡
𝑉𝐸𝑥ℎ ]
B =
[ 𝑏11 0 0 0 0 0 00 𝑏22 0 0 0 0 00 0 𝑏33 0 0 0 00 0 0 𝑏44 0 0 00 0 0 0 𝑏55 0 00 0 0 0 0 𝑏66 00 0 0 0 0 0 𝑏77 ]
5. EMPIRICAL RESULTS
5.0 Preliminary diagnostics
5.1 Descriptive statistics for 14 west African countries under study
The result of the descriptive statistics for the 2128 observations is as presented in Table 2.
The mean values of the variables are all nearer the minimum, except the exchange rate that is
nearer the maximum. This implies that the data for the oil price, FFR, RGDP, inflation rate, Money
supply, interest rate are concentrated art the lower bound of the distribution, while that of the
exchange rate is at the upper bound. The value of the probability affirms that the data distribution
11
is free of heteroscedasticity (unequal variations among the variables) of the model, which is at a
significance level of 1%. This implies that both the data and the residuals used for the modelling
of ECOWAS are normally distributed. The standard deviation of the money supply is 44.61 and
that of oil price is 30.58, which implies that the data of these two variables in ECOWAS are more
dispersed than other variables in the model. Nonetheless, the normality tests of the Jarque-Bera,
skewness and Kurtosis show normality.
Table 2 : Descriptive statistics
Variables Observations Mean Standard
Deviation
Minimum Maximum Skewness Probability
Oil Price 2128 42.11064 30.58540 11.09000 122.4767 1.241578 0.000000
FFR 2128
4.799211
4.099521 0.070000 19.10000 1.005421 0.000000
RGDP 2128 3.451956 8.384729 -53.72007 112.7299 2.437052 0.000000
Inflation
rate
2128 10.88424 18.99674 -38.88010 189.1817 3.613157 0.000000
Money
Supply
2128 19.19720 44.61635 -159.8664 754.6267 10.61844 0.000000
Interest
rate
2128 19.59705 11.90618 0.546875 69.15625 2.396792 0.000000
Exchange
rate
2128
4.783421
2.557390 -8.199277 8.927695 -
2.196658
0.000000
*** significance level at 1%
Source: Author’s computation
5.2 Unit Root Test
The stochastic non-stationarity of the series was examined in this study and their integration order
were established through the unit root test. This was considered necessary in order to avoid
misleading and spurious results. Therefore, for a consistent and reliable result, three statistical tests
had been conducted, viz Fisher Dickey- Fuller (ADF), Levin, Lin Chu and Im, Pesaran Shin. (IPS).
From Table 3 shows that all the variables, are stationary at their levels 1(0), except Oil price, which
becomes stationary at 1(1). This implies that all the variables are integrated at order 1(1), at 1%
significance level.
12
Table 3: Unit root test results
Variable ADF Remark LLC Remark IPS Remark
Oil Price
881.562***
1(1) -36.6180 ***
1(1) -35.0544 ***
1 (1)
FFR
99.1884***
1(0)
-9.76121 ***
1(0) -6.82653 ***
1(0)
RGDP
143.819***
1(0) -3.03415 ***
1(0) -8.82983 ***
1(0)
Inflation 68.7366***
1(0) -
28.0104***
1(1) -
4.52815***
1(0)
Money Supply
122.152***
1(0) -3.97720 ***
1(0) -7.82656 ***
1(0)
Domestic Int Rate
544.003***
1(0) -2.86290 ***
1(0) -0.83216 **
1(0)
LExch Rate
53.2958 ***
1(0) -5.29650 ***
1(0) -2.94332 ***
1(0)
Significance level: ***(1%),
Source: Author’s computation
5.3 Correlation and co-variance Analysis
The correlation matrix of the panel data is shown in Table4. Diverse form of relationship has been
exhibited in the relationship amongst the variables of the ECOWAS. However, our focus here is
their relationship with the economic growth (RGDP) and inflation. Generally, the growth rate has
a positive relationship with the oil price, interest rate and the exchange rate, but inverse relationship
with the FFR, Inflation rate and the money supply. The inflation rate has a direct relationship with
the money supply (weak) and FFR. while other variables show inverse relationship with the
inflation rate.
13
Table 4: Correlation Matrix
OIL_PRICE FFR RGDP INF M2 INTR LEXCR
OIL_PRICE 1.000000
FFR -0.486795 1.000000
RGDP 0.097212 -0.123710 1.000000
INF -0.203375 0.229641 -0.051107 1.000000
M2 -0.048547 0.035591 -0.004072 0.201248 1.000000
INTR 0.023688 -0.160357 -0.030965 0.278001 0.141595
1.000000
LEXCR 0.132966 -0.259514 0.036795 -0.376036 -0.108200
0.179274
1.000000
Source: Authors computation from data
5.4 Impulse Response Analysis
Figure 1 shows the responsiveness of Federal Funds rate of the US, Economic growth, inflation
rate, money supply, interest rate, exchange rate to one standard deviation in the global oil price.
The FFR has a positive and significant response to the oil price shock. Its rate falls steadily, and it
becomes negative at the 4th quarter. Similarly, the exchange rate has a significant effect to the
shock of oil price. It falls up to the 2nd quarter and relatively stable thereafter. Other variables have
insignificant response to the shock of oil price within the period.
Figure 1: Impulse responses to shock1- Oil prices
-4
-2
0
2
4
6
8
10
12
1 2 3 4 5 6 7 8 9 10 11 12
Response of OIL_PRICE to shock1- Oil_Price
-0.4
-0.2
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1 2 3 4 5 6 7 8 9 10 11 12
Response of FFR to shock1- Oil_Price
-4
-3
-2
-1
0
1
2
3
4
1 2 3 4 5 6 7 8 9 10 11 12
Response of RGDP to shock1 Oil_Price
-4
-2
0
2
4
6
8
1 2 3 4 5 6 7 8 9 10 11 12
Response of INF to shock1-Oil_Price
-40
-20
0
20
40
1 2 3 4 5 6 7 8 9 10 11 12
Response of M2 to shock1- Oil_Price
-6
-5
-4
-3
-2
-1
0
1
2
1 2 3 4 5 6 7 8 9 10 11 12
Response of INTR to shock1- Oil_Price
-.12
-.10
-.08
-.06
-.04
-.02
.00
.02
.04
1 2 3 4 5 6 7 8 9 10 11 12
Response of LEXCR to shock1- Oil_Price
The impulse response of the variables to the shock of FFR is shown in figure 2. The shock has
significant impact on all the variables in the model, except money supply and interest rate. The oil
price and the FFR falls steadily to the shock. Conversely, the inflation rate responds positively,
and at an increasing rate.
14
Figure 2: Impulse Responses to shock2- FFR
-4
-2
0
2
4
6
8
10
12
1 2 3 4 5 6 7 8 9 10 11 12
Response of OIL_PRICE to shock2- FFR
-0.4
-0.2
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1 2 3 4 5 6 7 8 9 10 11 12
Response of FFR to shock2 FFR
-4
-3
-2
-1
0
1
2
3
4
1 2 3 4 5 6 7 8 9 10 11 12
Response of RGDP to shock2 -FFR
-4
-2
0
2
4
6
8
1 2 3 4 5 6 7 8 9 10 11 12
Response of INF to shock2 - FFR
-40
-20
0
20
40
1 2 3 4 5 6 7 8 9 10 11 12
Response of M2 to shock 2- FFR
-6
-5
-4
-3
-2
-1
0
1
2
1 2 3 4 5 6 7 8 9 10 11 12
Response of INTR to Shock2- FFR
-.12
-.10
-.08
-.06
-.04
-.02
.00
.02
.04
1 2 3 4 5 6 7 8 9 10 11 12
Response of LEXCR to Shock2 - FFR
Figure 3 shows the impact of one standard deviation in economic growth (RGDP) to other
variables of the monetary transmission mechanism in ECOWAS. The responsiveness of the oil
price, FFR and the inflation rate to the shock exhibit insignificant effects. On the other hand, the
response of the money supply was significant and positive up to the 9th quarter and falls thereafter,
the impact of the shock to exchange rate is also significant.
Figure 3: Impulse Responses to shock 3 – RGDP
The impulse response of other variables to the shock of inflation is as depicted in figure4. The
responses of money supply, interest rate, and exchange rate are to the shock show positive and
significant effects, while others are negative and insignificant.
-4
-2
0
2
4
6
8
10
12
1 2 3 4 5 6 7 8 9 10 11 12
Response of OIL_PRICE to shock3- RGDP
-0.4
-0.2
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1 2 3 4 5 6 7 8 9 10 11 12
Response of FFR to shock3- RGDP
-2
-1
0
1
2
3
4
1 2 3 4 5 6 7 8 9 10 11 12
Response of RGDP to shock3- RGDP
-4
-2
0
2
4
6
8
1 2 3 4 5 6 7 8 9 10 11 12
Response of INF to shock3-RGDP
-10
-5
0
5
10
15
20
25
30
1 2 3 4 5 6 7 8 9 10 11 12
Response of M2 to shock3- RGDP
-1.0
-0.5
0.0
0.5
1.0
1.5
2.0
2.5
3.0
1 2 3 4 5 6 7 8 9 10 11 12
Response of INTR to shock3- RGDP
-.04
-.02
.00
.02
.04
.06
.08
.10
.12
1 2 3 4 5 6 7 8 9 10 11 12
Response of LEXCR to shck3- RGDP
15
Figure 4: Impulse Responses to shock 3 – Inflation
Figure 5 is the impulse responses of the variables to one standard deviation of the money supply
in the ECOWAS. The impact of the shock to RGDP, inflation and interest rate were positive and
significant. The RGDP rises steadily to the 6th quarter and declined subsequently. Furthermore, the
responses of the FFR and exchange rate were insignificant.
Figure 5: Impulse response to Money Supply shock
Figure 6 shows the impact of the shock of interest rate to other variables. The responsiveness of
the inflation rate and the money supply are positive and significant. Conversely, FFR and RGDP
that are negative and insignificant, which conforms with the findings of Kevin (2006) that interest
rate has insignificant impact on output. Inflation rate had positive response. The shock led to
increasing rate of inflation. This is an indication of idiosyncratic evidence, as it appears there is
presence of price puzzle within this period (Bernanke and Blinder, 1992 and Onyemenam, 2013).
This is because the increase in interest rate results to increase (instead of decrease) in inflation rate
within this period. As described by Onyemenam, (2013), there appears to be exchange rate puzzle,
as the increase in interest rate leads to decrease in the value of the local currencies in Ecowas
countries.
-4
-2
0
2
4
6
8
10
12
1 2 3 4 5 6 7 8 9 10 11 12
Response of OIL_PRICE to shock4 - INF
-0.4
-0.2
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1 2 3 4 5 6 7 8 9 10 11 12
Response of FFR to shock4 - INF
-2
-1
0
1
2
3
4
1 2 3 4 5 6 7 8 9 10 11 12
Response of RGDP to shock4 -INF
-4
-2
0
2
4
6
8
1 2 3 4 5 6 7 8 9 10 11 12
Response of INF to shock4 - INF
-10
-5
0
5
10
15
20
25
30
1 2 3 4 5 6 7 8 9 10 11 12
Response of M2 to shock4 -INF
-1.0
-0.5
0.0
0.5
1.0
1.5
2.0
2.5
3.0
1 2 3 4 5 6 7 8 9 10 11 12
Response of INTR toshock4 - INF
-.04
-.02
.00
.02
.04
.06
.08
.10
.12
1 2 3 4 5 6 7 8 9 10 11 12
Response of LEXCR to shock4 - INF
-4
-2
0
2
4
6
8
10
12
1 2 3 4 5 6 7 8 9 10 11 12
Response of OIL_PRICE to shock5 -M2
-0.4
-0.2
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1 2 3 4 5 6 7 8 9 10 11 12
Response of FFR to shock 5- M2
-2
-1
0
1
2
3
4
1 2 3 4 5 6 7 8 9 10 11 12
Response of RGDP to shock5- M2
-4
-2
0
2
4
6
8
1 2 3 4 5 6 7 8 9 10 11 12
Response of INF to shock5-M2
-10
-5
0
5
10
15
20
25
30
1 2 3 4 5 6 7 8 9 10 11 12
Response of M2 to shock5- M2
-1.0
-0.5
0.0
0.5
1.0
1.5
2.0
2.5
3.0
1 2 3 4 5 6 7 8 9 10 11 12
Response of INTR to shock5 -M2
-.04
-.02
.00
.02
.04
.06
.08
.10
.12
1 2 3 4 5 6 7 8 9 10 11 12
Response of LEXCR to shock5- M2
16
Figure 6: Impulse response to Interest Rate
-4
-2
0
2
4
6
8
10
12
1 2 3 4 5 6 7 8 9 10 11 12
Response of OIL_PRICE to shock6- INTR
-0.4
-0.2
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1 2 3 4 5 6 7 8 9 10 11 12
Response of FFR to shock6- INTR
-2
-1
0
1
2
3
4
1 2 3 4 5 6 7 8 9 10 11 12
Response of RGDP to shock6- INTR
-4
-2
0
2
4
6
8
1 2 3 4 5 6 7 8 9 10 11 12
Response of INF to shock6- INTR
-10
-5
0
5
10
15
20
25
30
1 2 3 4 5 6 7 8 9 10 11 12
Response of M2 to shock6- INTR
-1.0
-0.5
0.0
0.5
1.0
1.5
2.0
2.5
3.0
1 2 3 4 5 6 7 8 9 10 11 12
Response of INTR to shock6- INTR
-.04
-.02
.00
.02
.04
.06
.08
.10
.12
1 2 3 4 5 6 7 8 9 10 11 12
Response of LEXCR to shock6- INTR
Figure 7 depicts the impact of one standard deviation in Exchange rate to other variables of the
monetary transmission mechanism in Ecowas. The response of the Inflation and interest rates
appears to be positive and significant, while others have been insignificant.
Table 7: Impulse Response exchange rate shock
-4
-2
0
2
4
6
8
10
12
1 2 3 4 5 6 7 8 9 10 11 12
Response of OIL_PRICE to shock7- LEXCR
-0.4
-0.2
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1 2 3 4 5 6 7 8 9 10 11 12
Response of FFR to shock7- LEXCR
-2
-1
0
1
2
3
4
1 2 3 4 5 6 7 8 9 10 11 12
Response of RGDP to shock7- LEXCR
-4
-2
0
2
4
6
8
1 2 3 4 5 6 7 8 9 10 11 12
Response of INF to shock7- LEXCR
-10
-5
0
5
10
15
20
25
30
1 2 3 4 5 6 7 8 9 10 11 12
Response of M2 to Shoc7- LEXCR
-1.0
-0.5
0.0
0.5
1.0
1.5
2.0
2.5
3.0
1 2 3 4 5 6 7 8 9 10 11 12
Response of INTR to shock7- LEXCR
-.04
-.02
.00
.02
.04
.06
.08
.10
.12
1 2 3 4 5 6 7 8 9 10 11 12
Response of LEXCR to shock7- LEXCR
6.0 Periodic Analysis of the Variance decomposition
The variance decomposition estimates the proportion of each shock effect resulting from the
variance of each of the endogenous variables and also from the shock of the variable itself over a
period of time. In our findings, the shock has been broken down to four quarterly periods, variable
by variable, as contained in Tables 8-10. Table 8 gives the variance decomposition of the Oil price
where the oil price contemporaneously responses to shock of itself in the first quarter as 99.84%.
Thus, out of the remaining 0.16% other variables, the FFR accounts for 0.11%. This implies that
99.95% is captured by the external influence, while other variables are relatively insignificant.
17
However, successively, on quarterly basis, the contributions of these variables are on the increase,
except that of the oil price, which decreases subsequently.
Table 8: Variance Decomposition of Oil Price
Period Oil Price FFR RGDP Inflation Money
supply
Interest
rate
Exchange
Rate
3 99.84402 0.108992 0.033877 0.000290 0.010947 0.001178 0.000693
6 99.45324 0.450964 0.076904 0.002484 0.013184 0.001604 0.001622
9 98.49965 1.343896 0.122260 0.013574 0.016802 0.002302 0.001520
12 97.25997 2.545298 0.141565 0.028678 0.020255 0.002657 0.001574
The Variance decomposition of the FFR in Table 9 is similar to what is obtained in oil price
variance. The variations in the dominated by the oil price and the FFR from the 1st quarter to the
4th quarter. Whereas the contribution of other variables are relatively less important. The
contribution of FFR is at a decreasing level, ranging from 99.32 to 97.41 of the 1st quarter and the
4th quarter respectively.
Table 9: Variance Decomposition of FFR
Period Oil Price FFR RGDP Inflation Money
supply
Interest
rate
Exchange
Rate
3 0.526060 99.32158 0.081928 0.001173 0.014226 0.008063 0.046967
6 0.529566 99.21368 0.072558 0.006334 0.020621 0.011697 0.145543
9 1.186113 98.49118 0.056130 0.011189 0.036661 0.015223 0.203503
12 2.203027 97.41401 0.049231 0.014518 0.075244 0.020170 0.223797
The RGDP shocks accounts for almost all the variations of the period. From Table10, the variance
depicts that the money supply (M2), in ECOWAS countries, takes dominance of the shock effect
to output growth (Real GDP), apart from the variable’s own shock. This follows Irfan et al (2011)
and Cambazoglu (2012) that money supply stands out as it greatly affected GDP positively. The
rate of contribution of M2 was also at an increasing rate through the periods, of 1.23%, 10.08%,
14.79% and 15.25% from 1st quarter to 4th quarter, respectively. This depicts the evidence that
broad money plays a major role in the monetary transmission mechanism in ECOWAS. Next to it
is the Exchange rate and the FFR respectively. The lowest percentage shock effect is from the oil
price shock. Generally, there is an inverse relationship between the real growth rate and the
monetary policy.
18
Table 10: Variance Decomposition of RGDP
Period Oil Price FFR RGDP Inflation Money
supply
Interest
rate
Exchange
Rate
3 0.000920 0.127228 97.69132 0.003779 1.287944 0.028929 0.859881
6 0.011412 0.395574 82.75179 0.007729 10.08204 0.061789 6.689667
9 0.023812 0.644922 75.02551 0.011828 14.79458 0.069866 9.429484
12 0.032988 0.834753 74.24810 0.028434 15.25857 0.069675 9.527475
In summary, the external shocks, particularly, FFR significantly impact economic growth and
inflation rate in ECOWAS economy. Also, the exchange rate is significantly affected by the shock
of the oil price, which produces a reciprocatively effect on the economic growth and stability,
being an open economy. Other variables had insignificant impact of the oil price shock.
6. Conclusion and Summary of Results
This study employs panel structural VAR (PSVAR) model to examine the monetary policy shocks
effect to economic growth is the sub region of ECOWAS economies. Due to availability of data,
this study covers 14 out of 15 countries in the sub region, covering the period 1980(1) to 2017(4).
This sample period was chosen after 5 years of the existence of the economic integration. We
conducted the preliminary diagnosis of the data to affirm the suitability of the data, which include
the unit root test to confirm the stationarity of the monetary variables. Hence, the PSVAR provides
significant results ECOWAS economy. The results suggest that both the internal shocks and the
external shocks have significant effects on the economic growth and stability of ECOWAS, but
the internal shocks have greater effects that the external. The impact of the external shock of the
FFR is more pronounced. The shock of FFR significantly impacts economic growth and inflation
rate in ECOWAS economy. Also, the exchange rate is significantly affected by the shock of the
oil price, which produces a reciprocatively effect on the economic growth and stability, being an
open economy. Other variables had insignificant impact of the oil price shock.
Furthermore, Money supply has the prime impact on the economic growth, inflation rate and
interest rate. The monetary policy shocks had positive and significant effects on economic growth,
which is in line with the findings of Vera Ogeh-Lassev Fiado (2015). It further suggests a positive
and significant effect on the inflation rate, which is in line with the Monetarist school of thought
that inflation is a monetary phenomenon. This therefore implies that monetary policy instruments
play an important role in the output growth and other macroeconomic policies in ECOWAS.
Similarly, shocks of the interest and the exchange rate are positive and significant on the inflation
19
rate. It was also discovered that the inflation rate majorly contributes to money supply. The
economic implication of this suggests that any policy decision to reduce inflation through negative
money supply will lead to output decline. Therefore, policies on money supply should be guided
jealously.
Our findings further suggest that there are idiosyncratic evidences found in the robustness check.
Price puzzle and Exchange rate puzzle were evident within the horizon. Therefore, monetary
policy and more particularly money supply and FFR, are an important variable to be considered
and should be guided jealously during monetary integration of the Ecowas sub-region and other
monetary policy decisions. This therefore implies that monetary policy instruments play an
important role in the economic growth of Ecowas, especially the money supply.
Our future research shall be focusing on other areas of monetary policy shocks to economic
growth. This shall give room for better comparative analysis and policy formulation of the
monetary authorities in ECOWAS sub region.
20
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