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: [email protected] Haruna Modibbo Usman Department of Economics, Faculty of Arts and Social Sciences, Gombe State University, P.M.B 127, Gombe. Email: [email protected] Abubakar Mohammed Saidu Department of Economics, Faculty of Arts and Social Sciences, Gombe State University, P.M.B 127, Gombe. Email: [email protected] Mohammed Sani Bello Department of Economics, Faculty of Arts and Social Sciences, Gombe State University, P.M.B 127, Gombe. Email: [email protected] 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 IRC-2014 DUBAI-UAE 3 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 5 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 7 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 9 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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