The Impact of Foreign Aid on Economic Growth in Morocco: Econometric Analysis Using VECM

The present work aims to contribute to the empirical literature on the effectiveness of Foreign aid in Morocco. We use the Vector Error Correction Model (VECM) to jointly capture the long-run relationship and short-run dynamics between Official Development Assistance and economic growth. Other variables such as investment, exports, and government consumption are also included in the model. The results indicate that the foreign aid promotes growth through government consumption in the short term. However, the impact of aid on economic growth becomes negative in the long term.


Introduction
International aid acts as an income transfer.This transfer may or may not produce economic growth for the recipient countries.Official Development Assistance (Note 1) as defined by the OECD's Development Assistance Committee (DAC), includes all resource inflows that are provided to countries and territories on the ODA recipient list, or Multilateral institutions, and which must emanate from public bodies, including States and local authorities, or bodies acting on behalf of public bodies, with the aim of promoting economic development and improving the standard of living of developing countries.
For more than 50 years, the effectiveness of foreign aid has been a subject of controversy among researchers.Numerous theoretical and empirical studies have been carried out to analyze the impact of aid on economic growth.Nevertheless, very few empirical studies have been carried out on Morocco.
Morocco, an emerging country with a population of nearly 34 million, is a major beneficiary of international financial cooperation.From 1981 to 2014, the international community has devoted about $ 30 billion of official development assistance to Morocco (Note 2).ODA to Morocco has more than quadrupled since 2000, when the Millennium Development Goals were set, to reach an unprecedented record of US $ 2.25 billion in 2014 wich represent 2.1% of Morocco's GNI (WDI, 2016).
Although ODA flows to Morocco have not always evolved constantly, they are now reaching a considerable level, which inevitably means questioning their effectiveness.In this perspective, the central problem of the relationship between aid and growth is to know specifically whether foreign aid affects positively and significantly economic growth in Morocco.that aid does not help, and has no impact on economic growth.

Aid-Growth: Positive Relationship
The work of Burnside andDollar (1997, 2000) is at the heart of the debate on aid effectiveness in terms of growth.According to these authors, international aid is only effective in terms of growth when the recipient countries adopt a good economic and social policy.Their results showed that countries with good fiscal, monetary and trade "policy" are best suited to converting aid into economic growth.In this case, good economic policy leads to controlled inflation, a low budget deficit and the implementation of a policy of open trade.However, this definition of good policy is not the subject of unanimity.Thus, the World Bank has defended this idea in the 1998 Assessing Aid report which summarizes the principle in the form of "if commitment, money -if not, ideas" (Note 3).Karuna Gomanee, Sourafel Girma and Oliver Morrissey (2005) highlight the indirect effect of international aid on economic growth through transmission mechanisms such as investment or government spending.Indeed, they identify investment as the most important transmission mechanism by examining the relationship between aid and growth on a panel of 25 countries in sub-Saharan Africa during the period 1970-1997.The results of the estimation show a significant and positive effect of foreign aid on economic growth.Everything being equal, on average, a one percentage point increase in aid as a percentage of GDP contributes to a quarter-percentage-point increase in the growth rate.This result supports what Hansen and Tarp (2001) have demonstrated.They found that aid is likely to increase the rate of growth, and this result is not conditioned by "good policy".This is in line with the result of Guillaumont and Chauvet (2001) that the return on aid is higher in countries vulnerable to macroeconomic shocks.Moreira (2005) conducted a cross-country study, using OLS and GMM, and concluded that aid has less effect on growth in the short-run than in the long-run.This study suggests that the work of the previous generation is consistent with the new generation of aid effectiveness studies and that less importance should be attributed to the "micro-macro paradox" as an overall appraisal of aid effectiveness.Another study carried out by Camelia Minoiu and Sanjay G. Reddy (2009) indicates that aid promotes growth in the long-run; the effect is significantly large and robust.Kurihara (2014) through an impulse response function of various aid recipient countries, assumes that in general, the impact of foreign aid on economic growth is short, at best one or two years.However, too much dependence on foreign aid should be avoided for sound and sustainable economic growth.

Negative Relationship Between Aid and Growth
Unlike the above studies, the anti-aid studies found that there is a negative relationship between aid and growth in recipient countries for a number of reasons, including governance issues (Papanek (1972), Brautigam and Knack (2004), Malik (2008)).
Among the first authors to question the effectiveness of foreing aid included Griffen and Enos (1970) who found, from an empirical study, a simple negative correlation between aid and growth in 27 countries, showing even a negative impact of aid on domestic savings.Peter Bauer (1972) argues that aid is ineffective and detrimental to the private sector and hinders development because it acts as a disincentive to investment.However, his thesis has not been the subject of an empirical study.
For a category of researchers, large amounts of aid also affect the real exchange rate of the recipient country and hinder the competitiveness of its export sector.This event is often referred to as "Dutch Disease" (Rajan & Subramanian, 2005).As the study by Rajan and Subramanian shows, in countries that received more aid during the 1980s and 1990s, not only the export sectors with high degree of labor intensity have developed less rapidly than the others, but the development of the manufacturing sector as a whole has also slowed (Note 4).Boone (1994Boone ( , 1996) ) in his most cited work in this field concludes that there is no relationship between aid and growth.Indeed, the author found no significant or positive impact of the aid on growth or investment or on poverty reduction.As for Henri Schwalbenberg (1998), even with the inclusion of "bad" economic policies, did not find significant results to affirm either a positive or negative relationship between aid and economic growth.

No Aid-Growth Relationship
A 2001 study on the impact of aid on growth concludes that once outliers are removed from the population sample, aid has no impact on economic growth (Dalgaard & Hansen, 2001).A follow-up study carried out three years later adds a variable to account for the climate of the geographical location of developing countries.The results showed that the relationship between aid and growth in countries in the tropics is non-existent (Dalgaard, Hansen, & Tarp, 2004).Nevertheless, some scholars still argue that the lack of a link between international aid and economic growth does not deny the possibility of such an existence.They believe that the institutional and political reform of host countries has the capacity to foster a positive aid-growth relationship (Barro 1991;2000).

Methodology
In most of works cited above, the authors use either a panel data model or a general linear model for the methodological approach.Also, determining the channels of transmission is essential in order to guide policies aimed at optimizing the effect of ODA on economic growth.To do this, the use of the multi-variant approach of cointegration is essential.The methodological approach will first be to define the variables involved in the study, then to explain the instrument of analysis linked to the verification of the link empirical relationship between foreign aid and economic growth in Morocco.

Data and Variables
The choice of variables is based on existing literature (works of Karuna Gomanee, Sourafel Girma and Oliver Morrissey (2005), and Pahlaj Moolio, (2015)).Ultimately, four variables are defined for examining the empirical link between international aid and economic growth: -Gross Domestic Product:  2016) and the moroccan High Commission for Planning (HCP) database.The data used is annual and covers the period from 1981 to 2014.The tool used to process this data is Eviews 6.0, a statistical software package used mainly for time series.

Model
Our econometric study consists in testing a VECM model linking aid to economic growth.This method allows to reveal jointly the long run and short run relationships between variables.Therefore, the VECM representation of this model is illustrated: Where L represents the lag operator,  is the difference operator, E t-1 is the error term, ε t is a white noise.In fact, the first step in this analysis is to examine the stationarity tests of the time series, a prerequisite for each cointegration test to avoid spurious regressions.Then, we will test the existence of cointegration relations before examining causality between variables.

Unit Root Test
The examination of stationarity remains an inevitable step before any treatment of the time series in order to avoid spurious regressions.It is therefore necessary to determine the order of integration of the time series using the Augmented Dickey Fuller test (ADF).This test is carried out under three possible model specifications, with constant and trend, with constant, and with no constant nor trend.We obtain the results summarized in the following table: As shown in Table 1, the results imply that the variables in the model represent DS processes at the level.The tests applied to the first differences reject the null hypothesis of the unit root with the threshold of 5% (t-statistic > critical value).Since the first differences are stationary, the variables are integrated to the same order (I (1)), which means we can proceed to the Johansen's co integration.

Lag Selection
The number of lags depends on the size of the selected sample.It significantly influences the estimation.The number of lags to be used for applying the Johansen test is determined by calculating the Akaike (AIC) and Schwarz (SC) information criteria for lags ranging from 1 to 3.There are other criteria to determine the optimal number of lags like the Hannan-Quin criterion and the Final Prediction Error, which are based on the same principle.The results are shown in the following table: We find that the minimum of the Akaike criterion corresponds to p = 2 while the Schwarz criterion corresponds to p = 1.In order to complete our test, we will compare the FPE criteria, and HQ and the Log-Liklelihood.The results obtained in table 2 indicate that the number of lags to be retained is 1.

Johansen Co-Integration Test
After determining the optimum lags (1 lag), we can then establish the number of equilibrium relations existing between the four variables.The Johansen co-integration test is performed on a system of five variables ( The results of the trace and Maximum Eigenvalue tests show that there is indeed a cointegration between variables because the null hypothesis of absence of cointegration is rejected at the 5% level.Table 3 shows that the Max-Eigen test indicates 1 cointegration equation at the 5% threshold (21.58434<27.58434)while the trace test indicates 2 cointegration equations (27.5361<29.79707).We will therefore admit that there is one cointegration relation.

Model Estimation
The estimation of the VECM gives negative and significant coefficients of the error correction terms of the co-integration equations (CointEq1).This coefficient represents the speed of adjustment to long-run equilibrium.

VECM Long Run Estimates
As LGDP, LAID, LCG, LINV, LEX are cointegrated, the long-run relationship may have the following form: LGDP = -0.18* LAID -0.38 * LCG + 0.62 * LINV + 0.44 * LEX + 6. 93 (2) In the long term, aid has a negative impact on economic growth.Indeed, an increase of 1% of Official Development Assistance leads to a loss of approximately 0.18% of GDP.Similarly, government consumption has a negative effect on growth in the long run.On the other hand, the results of our model show that investment and exports have a positive impact on economic growth.

VECM Short Run Estimates
The multivariate analysis reveals a positive and significant causal relationship between aid and economic growth in the short run and with one-year delay.The table below shows that the Gross Domestic Product depends on its past value as well as that of aid and government consumption.According to the results above, the value of the coefficient of determination R 2 shows that almost 66% of fluctuations in economic growth are explained by the four variables defined above.Therefore, the explanatory power and the overall significance of the model are good.
The VECM short run estimates show that the coefficient associated with the aid variable is positive and significant (0.053) in the regression at the 5% level.It means that an increase of 1% of foreign aid is equivalent to an improvement of 0.05% of GDP.Similarly, government consumption (CG) has a positive and significant short run effect on economic growth at the 5% level, so an increase of 1% of CG generates an increase of almost 0.23% of GDP.Other significant results of this model show that aid also has a positive impact on government consumption in the short run.Indeed, an increase of 1% of aid causes an increase of 0.08% of public consumption.

Model Diagnostics
In summary, all tests of the diagnostics demonstrate that the model is stable and has no signs of autocorrelation, normality, or heteroskedasticity problems.The results of residual normality test are significant.The residues follow a normal distribution, which is favorable for our model."The stability condition test" reveals that none of the pointslies outside the circle, suggesting that the VECM model is stable."The serial correlation" test gives a probability greater than 5% (level of significance) so the errors are serially uncorrelated."The heteroskedasticity test" reveals an absence of heteroskedasticity in the model as shown by the probability value.

Discussion
The results of our study suggest that foreign aid has a mixed impact on economic growth in Morocco.Indeed, in the short run, ODA has a relatively positive effect on economic growth.However, this effect becomes negative in the long run.
The analysis of the short-term parameters of our model shows that the impact of aid on economic growth is positive.Indeed, an increase of 1% of aid is equivalent to an improvement of 0.05% of GDP.We also note that ODA has a positive impact on government consumption in the short run.Also, government consumption contributes to an improvement in economic growth (Table 4), which may justify the presence of a positive relationship between aid and economic growth.We can then conclude that through the channel of government consumption that aid influences economic growth.Thus, the error correction term is significantly negative and equal to -0.27, indicating that GDP adjusts at a rate of 27% relative to its equilibrium level following any shock from exogenous variables, and the shock is entirely reabsorbed after one year.
However, the impact of aid on economic growth is negative in the long term.In this case, the results show that an increase of 1% of ODA contributes to a decrease of 0.18% of GDP.The long-run result is consistent with the findings of Boone (1995) (Note 8) which considers that the aid contributes to an increase in government spending rather than capital accumulation.There is therefore no tax reduction allowed by the allocation of aid, and therefore no increase in household consumption and more generally no increase in production.Mallik (2008) also found a negative impact of aid on long-term economic growth.The empirical results of the study shows that in five of the six countries entering the model (Note 9), the natural logarithm of foreign aid as a percentage of real GDP has a significant negative long-term effect on the natural logarithm of real GDP per capita.Moreover, our model shows that foreign has no impact on investment and exports in Morocco.This should lead to a reflection on the need to reorient aid in order to optimize its impact on economic growth.

Conclusion
The purpose of this study is to highlight the nature of the effect of aid on economic growth in Morocco.We suggest a reasoning which consists in making the dynamic regression, to settle the problem of the stationarity of the variables, consequently, to integrate a vector error correction model (VECM).It must be noted that raising the level of foreign aid increases economic growth in the short-run via government consumption, but this impact becomes negative in the long-run.
The negative impact of aid in the long-term will raise the question of the quality of transmission channels.This leads us to reflect on the presence of other variables as transmission channels.We could still assume that investment in education and health would probably play a role in channeling aid effectiveness.
All variables are transformed into logarithms.The data are extracted from the World Development Indicator (WDI) of the World Bank database ( t LEX ;

Table 1 .
ADF unit root test results *Indicates that the coefficient is significant at 5% probability level.Source: authors' calculations.

Table 2 .
Selecting the number of lags * indicates lag order selected by the criterion.

Table 3 .
In order to carry out the test it is necessary to perform the Trace and the Maximum Eigenvalue tests synthesized in the following table: Johansen Co-integration test results t LGDP , t LAID , t LCG , t LINV , t LEX ).

Table 4 .
Estimate of the model