ESRI Discussion Paper Series No.223
Analysis on correlations and causal relations between ODA disbursement
and economic indicators including GDP among DAC countries :
How much can GDP explain ODA disbursement?

Masahiro OMURA
Senior Research Fellow, Economic and Social Research Institute, Cabinet Office

The full text is written in Japanese.

Abstract

ODA disbursements of donor countries have been examined and compared at international fora including DAC. Mostly attention has been paid to ODA/GDP ratio. International target of 0.7% ODA/GDP ratio has been maintained since the 1970s. The premise is that GDP determines ODA. Other economic indicators such as fiscal and international balances might explain ODA disbursement to some extent. So far attention has been centered on GDP. This paper analyzes relations between ODA disbursement and economic indicators including GDP and shows how much GDP can explain ODA. It uses cross-section, time series and panel data analyses.

Cross-section analysis examined the data between 1991 and 2006 covering the period after the end of the Cold War. ODA disbursement was regressed against eight variables including GDP, GDP growth rate, fiscal balance, government debt, current account balance, international reserves, total tax rate, and unemployment rate. Backward elimination method was employed to identify more relevant variables - GDP, tax rate, current account balance, unemployment rate and government debt in that order. Simple linear regression between ODA and GDP reveals a downward trend in the coefficient of GDP between 1992 and 1997 and an upward trend between 2002 and 2005. These trends respectively coincide with uncertainty about aid motives in the early 1990s and renewed motivation in the early 2000s exemplified by the Monterrey consensus.

Panel data analysis was conducted using four variables including GDP, government debt, fiscal balance and current account balance after an elimination of four less relevant variables in an eight variable model. A single variable model with GDP was found to have slightly higher overall R-squared than a four variable model. The coefficient of GDP was 0.2077 in the former, indicating ODA increase of 20.77 million dollars was realized by GDP increase of 10 billion dollars by the DAC countries. In the four models examined the coefficients of GDP were found to have the highest t-scores. The government debt, fiscal balance and current account balance were also found to have an explanatory power in that order.

In the time series analysis, ODA was regressed against GDP together with the first time lag of ODA. The result showed that ten DAC member countries had a long term dynamic multiplier of more than 0.7 per cent. A multi-variable regression was conducted with logarithm conversion as well as with the backward elimination. The variable most heavily selected was GDP followed by tax rate, current account balance, unemployment rate and government debt in that order. The serial correlation was mostly not confirmed. Impulse reaction analyses were conducted based on VAR models between real ODA and real GDP using differences to eliminate a unit root. In most cases the accumulative effect of GDP to ODA was positive, and that of ODA to GDP was the same in many cases, though Granger causality was not confirmed in many cases. ECM analysis was conducted in the cases of two countries which were found to have cointegration relations.

The results of multi-variable regressions as well as panel data analyses showed that GDP has the strongest explanatory power among economic indicators regarding ODA disbursements. It seems adequate that international fora including the DAC focus their attention to the relations between ODA and GDP and monitor ODA/GDP ratios. It would be appropriate, however, due attention be also paid to other economic indicators (according to panel data analyses, governmental debt, fiscal balance and current account balance, and according to cross-section and time series regression analyses, tax rate, current account balance, unemployment rate and government debt) in the analysis of ODA disbursements as they also have relatively strong explanatory power regarding ODA disbursements.

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