TESTING THE FOREIGN AID-LEDGROWTH HYPOTHESIS IN

Transcription

TESTING THE FOREIGN AID-LEDGROWTH HYPOTHESIS IN
Journal of Contemporary Management Sciences
Volume 3 (2) 55- 64
JCMS Publication, 2014
Journal of
Contemporary
Management
Sciences
TESTING THE FOREIGN AID-LEDGROWTH HYPOTHESIS IN
NIGERIA
Inuwa Nasiru
Department of Economics, Faculty of Arts and Social Sciences,
Gombe State University, P.M.B 127, Gombe.
Email: ninuwa@yahoo.comm
Haruna Modibbo Usman
Department of Economics, Faculty of Arts and Social Sciences,
Gombe State University, P.M.B 127, Gombe.
Email: haroongombe@yahoo.com
Abubakar Mohammed Saidu
Department of Economics, Faculty of Arts and Social Sciences,
Gombe State University, P.M.B 127, Gombe.
Email: abubakarmsaidu@yahoo.com
Mohammed Sani Bello
Department of Economics, Faculty of Arts and Social Sciences,
Gombe State University, P.M.B 127, Gombe.
Email: mohammedbellosani@gmail.com
Abstract
The relationship between foreign aid and economic growth has been the subject of much controversy. Therefore,
this paper aims at investigating the foreign aid-growth relationship by applying the Dickey-Fuller Generalized Least
Square (DF-GLS) unit root test and autoregressive distributed lag (ARDL) bound test approach to co-integration
during the period 1960-2012. The results revealed that foreign aid has positive and statistically significant in both
the short- and long run justifying aid-growth hypothesis. The study therefore recommends that aid supporting
institutions should put policy measures that would monitor the maximum effective utilization of foreign aid in order
to avoid mis utilization and mismanagement
KEYWORDS: Foreign Aid, Economic Growth, ARDL, Nigeria
.
1. INTRODUCTION
Foreign aid has been transferred from developed countries to developing countries in the form of project aid,
commodity aid, technical assistance and program aid. In fact, over the past 60 years, donor’s countries have invested
more than $2.3 trillion in foreign aid. Despite, this significant investment, 3 billion people still live on less than $2 a
day; 840 million are hungry; 10 million children die from preventable disease; and 1 billion adults are illiterate
(Easterly, 2006). In 2007, net overseas development assistance (ODA) to Africa amounted to USD 38.7 billion,
representing 37% of total aid. This corresponds to a fall of 18% in real terms, mostly due to exceptional debt relief
especially for Nigeria in2006. If debt relief grants are excluded, then ODA to Africa rose by 12% in real terms.
The total net aid flows from all donors that Nigeria received was US$ 152 million in 1999. In 2000, aid flows
increased slightly to $185 million and by 2004, it reached $573 million (Okon, 2012). These increased might not be
unconnected with the Nigeria’s economic reform program, but its benefits have recently been under severe scrutiny.
Some observers argue that a large portion of foreign aid flowing into the country is wasted and only increases
unproductive public consumption, corruption and inefficiencies (OECD, 2007).
Although, foreign aid to developing countries has been a subject of heated discussions among economists. Some
argue that foreign aid has no effect on growth and may sometimes even undermine growth in aid recipient countries
(Feeny, 2005; Fatima, 2014). Others suggest that foreign aid positively influences economic growth (Fasanya &
Onakoya, 2012; Kargbo, 2012). Still others suggest that foreign aid has a negative impact on economic growth
(Okon, 2012; Bakare, 2011).
The departure from earlier studies of the role of foreign aid flows on economic growth is in the methodology used to
examine the interaction between variables. Here the study makes use of autoregressive distributed lag (ARDL)
bounds test approach to co-integration. The ARDL has numerous advantages. Firstly, the ARDL approach is able to
examine the presence of short run as well as long run relationship between the independent variables and the
dependent variable. Secondly, the ARDL model takes a sufficient numbers of lags to capture the data generating
process in a general to specific modeling framework. Thirdly, the ARDL approach to co integration can be applied
irrespective of whether the variables are I(0), I(1) or fractionally co integrated Finally, the ARDL approach provides
robust result in a small sample size.
The rest of the paper is structured as follows: Section two presents the literature review and theoretical framework,
as section three discusses the methodology. Empirical results are presented in section four, while section five
concludes the paper.
2. LITERATURE REVIEW
There seems to be extensive literature examining the relationship between foreign aid and economic growth. As
earlier mentioned, the results from these various studies are mixed. While some studies suggest a positive
relationship, others suggest a negative association as well as absent of any relationship between the variables. For
instance, Fasanya & Onakoya (2012) applied Johansen maximum likelihood co integration test and parsimonious
error correction model to examine the effect of foreign aid on economic growth in Nigeria during the period 19702010. The results revealed that foreign aid has a positive and significant impact on economic growth. The results of
ECM showed that economic growth in Nigeria has an automatic mechanism and responds to deviations from
equilibrium in a balancing manner. Therefore, the study recommends that donor governments should be aware of the
political situations in recipient countries, and work with international bodies to ensure as much stability as possible.
Giles (1994) applied Engle-Granger two-step residual based test to co integration and Granger causality test to
examine the relationship between foreign aid and economic growth for Cameroon during the period 1971-1990. The
results showed that there is no evidence of long run equilibrium relationship between foreign aid and economic
growth. Granger causality test revealed a unidirectional causality running from foreign aid loans to economic
growth. Another recent study by Kargbo (2012) applied autoregressive distributed lag (ARDL) bound test and
Johansen maximum likelihood test to co integration techniques to examine the relationship between foreign aid and
economic growth for Sierra Leone during the period 1970-2007. The results revealed a long run equilibrium
relationship among the variables. The results also showed that foreign aid has positive and significant impact on
economic growth in both the short and long run.
Okon (2012) applied two-stage lease squares (2SLS) to examine the effect of foreign aid on economic growth in
Nigeria during the period 1960-2010. The author found that foreign aid has negative and significant impact on
human development. The results also revealed a negative effect of foreign aid on economic growth. The study,
therefore recommends that government should put policy measures that would monitor the maximum effective
utilization of foreign aid. Moreover, Javid & Qayyum (2011) applied autoregressive distributed lag (ARDL) bound
test approach to co integration to examine the relationship between foreign aid and economic growth in Pakistan
during the period 1960-2008. The results revealed that there exists a long run equilibrium relationship among the
variables. The results also revealed that foreign aid has a negative effect on economic growth. However, both the
effect of inflation and trade openness has significant effect on economic growth in Pakistan.
In addition, Bakare (2011) applied vector autoregressive model (VAR) and variance decomposition analysis to
examine the relationship between foreign aid and economic growth in Nigeria during the period 1988-2010. The
results showed a negative relationship between foreign aid and economic growth, which imply that foreign aid tend
to worsen economic growth in Nigeria rather than improving it. The results also evidenced a negative relationship
between foreign aid and capital formation. Thus, the study recommends an appropriate policy measures that would
monitor the maximum and effective utilization of aid.
Kolawale (2013) applied augmented Dickey-Fuller (ADF) test, Johansen maximum likelihood test, error correction
model (ECM) and Granger causality test to examine the relationship between foreign aid and foreign assistance on
economic growth for Nigeria during the period 1980-2011. The results revealed that there is long run equilibrium
relationship among the variables. The results also showed that neither economic growth nor foreign aid granger
caused each other. Similarly, Fatima (2014) applied descriptive statistic and ordinary least square (OLS) to examine
the effect of foreign aid and economic growth for Pakistan during the period 1980-2012. The results revealed that
foreign aid neither at aggregate nor disaggregate level influenced economic growth in Pakistan. The results revealed
that investment has a positive and significant effect on economic growth.
Feeny (2005) applied autoregressive distributed lag (ARDL) bound test approach to co integration to examine the
relationship between foreign aid and economic growth in Papua New Guinea (PNG) during the period 1965-1999.
The results revealed that total foreign aid has no impact on economic growth. The results also showed that neither
aid grants nor aid loans have impact on economic growth in PNG.
On the basis of cross-country studies, Jones (2013) applied Pedroni residual co integration tests, error correction
model and Johansen Fisher panel co integration test to examine the relationship between foreign aid and economic
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growth for the panel of 16 West African countries during the period 1960-1990. The results revealed a long run
equilibrium relationship between foreign aid and economic growth for the whole panel. The results of Granger
causality test showed a unidirectional causality running from foreign aid to economic growth justifying aid-growth
hypothesis.
Durbarry, Gemmel, & Greenaway (1998) applied two-way fixed effect model to examine the aid-growth nexus for
the panel of 68 developing countries during the period 1970-1993. The results revealed that foreign aid has a
positive and significant impact on economic growth. The study also suggests that these results vary according to
income level, level of aid allocation and geographical location. Furthermore, Hatemi-J &Irandoust (2005) applied
panel unit root test and panel co integration test based on Pedroni to examine the relationship between foreign aid
and economic growth for the panel of 6 developing countries during period 1974-1996. The findings revealed that
foreign aid has a positive and significant impact on economic growth for each country in the sample.
Mallik (2008) applied Johansen maximum likelihood test and vector error correction model (VECM) to examine the
effect of foreign aid on economic growth for the panel of 6 poorest countries during 1965-2005. The results showed
the existence of long run equilibrium relationship among the variables for all the countries. The results also revealed
that in 5 out of 6 countries, foreign aid has a significant but negative impact economic growth in the long run.
While, the mixed results between foreign aid and economic growth in the short run was reported. Also, Liew,
Mohamed, & Mzee, (2012) applied pooled ordinary least square, random effects and fixed effects to examine the
effects of foreign aid on economic growth for the panel of 5 East African countries during the period 1985-2010.
The results revealed that foreign aid has a negative and significant effect on economic growth for these countries.
This implies that foreign aid led hypothesis is rejected.
THEORETICAL FRAMEWORK
A simplified variant of the Two-Gap model is used to estimate the impact of aid and economic growth. This Model
was popularized by Chenery and Strout (1966) ages ago is still in use in projecting the macroeconomic impact of
foreign aid. This model has two components hence it is also commonly referred to as the Two-Gap Model. The first
component is the relationship between investment and growth, wherein the level of growth is assumed to be
dependent on the level of investment. The second component is the relationship between savings, which is assumed
as a critical factor for investment expansion, and growth. With this model, analysts are able to determine the
necessary level of investment to achieve a desired level of economic growth. Gaps occur if the investment is below
the desired level and these gaps can be ascribed as either a savings gap or as a foreign exchange(or trade) gap. If a
country is unable to fill this gap through imports, exports or production, foreign aid inflows or foreign capital
inflows are needed so that it can grow more rapidly than its internal resources would otherwise allow. Hence an
inflow of foreign aid should move a country’s economy upwards (McMillan, 2011).
3. DATA AND METHODOLOGY
In order to examine the relationship between foreign aid and economic growth in Nigeria, this study employs the
Nigeria annual time series from 1960-2012. These variables are real GDP per capita (as a proxy for economic
growth) and net overseas development assistance ( as a proxy for foreign aid). The variables employed are sourced
from World Development Indicator (WDI, 2013).
The time series analysis of the relationship between natural foreign aid and economic growth in Nigeria follows the
technique of co integration, which is employed to estimate the long run relationship between the variables. Having
determined the co integration relationship, then, an error correction model which provides estimates for the shortrun and the adjustment coefficient is estimated.This is specifically achieved by employing Autoregressive
Distributed Lag (ARDL) bounds testing procedure to test the long run equilibrium relationship between natural gas
consumption and economic growth. The ARDL has several advantages over other conventional techniques of co
integration (such as Engle and Granger 1987; Johansen 1988; Johansen and Jeselius 1990; Gregory and Hansen
1996). First, it can be applied irrespective of whether the underlying variables are I(0), I(1) or a combination of both.
Second, the model takes a sufficient number of lags to capture the data generating process in general to specific
modeling frameworks. Third, the error correction model (ECM) can be derived from ARDL through a simple linear
transformation, which integrates short run adjustments with long run equilibrium without losing long run
information. Fourth, the small sample properties of the ARDL approach are far superior to that of Johensen and
Juselius co integration technique (Dantama, Abdullahi, & Inuwa, 2012).
The ARDL approach to co integration is estimated using the following Unrestricted Error Correction Model
(UECM) equations:
q
p
i 1
q
i 1
p
i 1
i 1
 ln RGDPt   0   1 ln RGDPt  1   2 ln NODAt  1   3 lnRGDPt  1   4 ln NODAt  1  t1    (1)
 ln NODAt   0   1 ln NODAt  1   2 ln RGDPt  1    3 lnNODAt  1    4 ln RGDPt  1  t 2    (2)
From equation (1) and (2), ∆ represents the difference notation, while lnRGDP is the natural logarithm of RGDP and
ln NODA is the natural logarithm of the natural gas consumption.
The null hypothesis for each of the equation is:
Ho: α1= α2=0,
H0: β1=β2=0
H1: α1≠α2≠0
H1:β1≠ β2≠0
From Eqs. (1)–(2), the F-test can be used to examine whether along-run equilibrium relationship exists between the
variables, by testing the significance of the lagged level variable. The computed F-statistics for co integration are
denoted as FRGDP(RGDP/NODA) and FNODA (NODA/RGDP) for each equation, respectively. Pesaran,
Shin,
&Smith (2001) tabulated two sets of critical values. The first set of critical values is called lower-bounds critical
IRC-2014 DUBAI-UAE
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values, and the second set of critical values is known as upper bound scritical values. According to Pesaran, Shin,
&Smith (2001), the null hypothesis of no co integration is rejected if the calculated F-statistics more than the upperbound critical values. On the other hand, if the calculated F-statistic is less than the lower-bound critical values, we
cannot reject the null hypothesis and hence the variables are not co integrated. Finally, the decision about co
integration is inconclusive if the calculated F-statistic falls between the lower and upper-bound critical values.
4. EMPLIRICAL RESULTS
Adhering to the standard practice in time series econometrics, the estimation process starts by testing the time series
properties of data using the Dickey-Fuller Generalized Least Square (DF-GLS) test. Although the bounds test
procedure allows regressors to be either I(0) or I(1), it is still necessary to ensure that the level of the dependent
variable is I(1) and exclude the possibility that any of the regressors are I(2) or higher. The DF-GLS test is applied
and the results are presented in Table 1.
Table 1: Unit Root Tests
Variable
DF-GLS test at Level
DF-GLS at first Difference
LRGDP
-1.066441
-5.218917***
LNODA
-1.577352
-6.908712***
Source: authors’ computations *** indicates level of significance at 1%
Based on the test for stationary of the variables using the DF-GLS unit roots test in Table 1. The results showed that
all the variables are stationary at first differenced I(1),with none being I(2). Thus, the study can proceed with the use
of the ARDL technique to co integration, which is applicable when the regressors used in the model are either I (0)
or I (1) or a mixture of both.
Table 2: ARDL Bound Test Results
F-Statistic
Critical Values at 5%
FLRGDP (LRGDP/LNODA)= 4.6754
Lower bound
Upper bound
3.3009
4.1490
FLNODA (LNODA/LRGDP)= 0.64237
Source: authors’ computations.
Based on the results of co integration test presented in Table 2, the findings suggest that there exist along run
equilibrium relationship, when real GDP is the dependent variable because the calculated F-statistics(4.6754) is
greater than the upper bound critical value(4.1490) at 5% level. Thus, the null hypothesis of no co integration is
rejected, implying long-run co integration relationship between the variables. However, absence of co integration is
apparent when natural overseas development assistance is taken as dependent variable because the calculated F
statistics(0.64237) is lower than the lower bound critical value (3.3009) at 5% level. Since the long run relationship
between the aid-growth nexus is established, the short run and the long run estimate of ARDL will be conducted
Table 3: Results of Estimated long-run Coefficients
Regressor
Coefficient
Standard error
T-ratio [p-value]
0.33589
.0073219
45.8751 [0.000]
Dependent variable; LRGDP
LNODA
Source; authors’ computations
The results of the estimated long run coefficient are presented in Table 3. The estimated coefficients of the long-run
relationship evidenced that foreign aid has a positive and statistically significant impact on real GDP proxies for
economic growth. Therefore, A 1% increase in aid will leads to approximately 33.5% increase in real GDP in
Nigeria.
Table 4: Error Correction Representation for the Selected ARDL Model
Regressor
Coefficient
Standard Error
T-ratio
P-value
∆LNODA
0.027207
.0099247
2.7414
0.008
ECM(-1)
-0.081000
.030261
-2.6767
0.010
Dependent variable: ∆LRGDP
Ecm=LRGDP-.33589* LNODA Source: authors’ computations.
The results of the short-run dynamic coefficients associated with the long-run relationship obtained from the ECM
equation are reported in Table 4. Similar to the result of obtained in long run estimated equation; foreign aid has a
positive and significant effect on economic growth in Nigeria. The error correction coefficient estimated -0.0810
(0.010) is highly significant, has the correct sign and imply a fair speed of adjustment to equilibrium after a shock.
Approximately 8.1% of disequilibria from the previous year’s shock converge back to the long-run equilibrium in
the current year.
Table 5: Diagnostics Test
Test Statistics
LM test
Serial Correlation
CHSQ(1) = 1.8085
Functional Form
CHSQ(1) = .027718 [0.868]
Normality
CHSQ(2) = 5.7504
[0.056]
Heteroscedasticity
CHSQ(1) = .84539
[0.358]
[0.179]
Source: authors’ computations.
IRC-2014 DUBAI-UAE
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Table 5 present diagnostics test of the estimated ARDL model. The model passes all diagnostic tests. There is no
evidence of serial correlation and the model is well specified based on their probability value. Similarly, the battery
of diagnostic tests for heteroscedasticity and normality of the residuals did not find any significant evidence of
departures from standard assumptions.
5. CONCLUSION
Foreign aid remains an important source of public expenditure in most developing countries,
including Nigeria. This study applied the Dickey- Fuller Generalized Least Square (DF- GLS) unit root test and
autoregressive distributed lag (ARDL) bound test approach to co integration to examine the impact of foreign aid on
economic growth in Nigeria during the period 1960-2012.The study found that foreign aid is positive and
statistically significant in promoting economic growth in Nigeria validating the aid led-growth hypothesis. The
results further revealed that the error correction coefficient estimated -0.0810 (0.010) is highly significant, has the
correct sign and imply a fair speed of adjustment to equilibrium after a shock. Approximately 8.1% of disequilibria
from the previous year’s shock converge back to the long-run equilibrium in the current year. The study therefore
recommends that aid supporting institutions should put policy measures that would monitor the maximum effective
utilization of foreign aid in order to avoid misutilization and mismanagement.
REFERENCES
1-
Bakare, A.S. (2011). “The Macroeconomic Impact of Aid in Sub-Sahara Africa: The Case of Nigeria.” Business and Management
Review, 1(5), 24-32.
2-
Chenery, H. and Strout. A. (1966). “Foreign assistanceand economic development”. American EconomicReview, 56, 679-733.
3-
Durbarry, R., Gemmel, N., and Greenaway, D. (1998). “New Evidence on the Impact of Foreign Aid on Economic Growth.” Credit
Research Paper 8, 1-32.
4-
Dantama, Y.U., Abdullahi, Y.Z., and Inuwa, N. (2012). “Energy Consumption-Economic Growth Nexus in Nigeria: An Empirical
Assessment Based on ARDL Bound Tests Approach.” European Scientific Journal, 8(12), 141-157.
5-
Easterly, W.(2006). The white man’s burden: Why the West’s efforts to aid the rest havedone so much ill and so little good. New
York: Oxford University Press.
6-
Fasanya, I.O. and Onakoya, A.B.O. (2012). “Does Foreign Aid Accelerate Economic Growth? An Empirical Analysis for Nigeria.”
International Journal of Economics and Financial Issues, 2(4), 423-431.
7-
Feeny, S. (2005). “The Impact of Foreign Aid on Economic Growth in Papua New Guinea.” The Journal of Development Studies,
41(6), 1092-1117.
8-
Fatima, F. (2014). “Foreign Aid and Economic Growth.” Open Access Library Journal, 1, 1-7.
9-
Giles, J.A. (1994). “Another Look at the Evidence on Foreign Aid Led Economic Growth.” Applied Economics Letter, 1, 194-199.
10-
Hatemi-J and Irandoust, M. (2005). “Foreign Aid and Economic Growth: New Evidence from Panel Cointegration.” Journal of
Economic Development, 30(1), 71-80.
11-
Javid, M. & Qayyum, A. (2011). “Foreign Aid and Growth Nexus in Pakistan: The Role of Macroeconomic Policies.” PIDE Working
Paper 72.
12-
Jones, Y.M. (2013). “Testing the Foreign Aid-Led Growth Hypothesis in West Africa.” Working Papers Management BWPMA,
1303.
13-
Kolawale, B.O. (2013). “Foreign Assistance and Economic Growth in Nigeria: The Two-Gap Model Framework.” American
International Journal of Contemporary Research, 3(10), 153-160.
14-
Kargbo, P.M. (2012). “Impact of Foreign Aid on Economic Growth in Sierra Leon.” Working Paper No 07, 1-42.
15-
Liew, C.Y., Mohamed, M.R. and Mzee, S.S. (2012). “The Impact of Foreign Aid on Economic Growth of East African Countries.”
Journal of Economics and Sustainable Development, 3(2), 129-138.
16-
McMillan, L. (2011). “Foreign Aid and Economic Development.” School of Doctoral Studies (European Union) Journal, 158-165.
IRC-2014 DUBAI-UAE
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17-
Mallik, G. (2008). “Foreign Aid and Economic Growth: A Cointegration Analysis of the Six Poorest African Countries.” Economic
Analysis and Policy, 38(2), 251-260.
18-
Okon, E.O. (2012). “Five Decades of Development Aid to Nigeria: The Impact on Human Development.” Journal of Economics and
Sustainable Development, 3(1), 32-42.
19-
OECD (2007). Is it ODA? OECD Factsheet. May, Paris.
20-
Pesaran, M. H., Shin, Y., and Smith, R.J. (2001).“Bounds Testing Approaches to the Analysis of Level Relationships.”Journal of
Applied Econometrics, 16, 289–326.

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