Revisited the role of foreign aid in capital formation: experience of South Asian countries

Developing countries often rely on foreign capital, including foreign aid, to address investment-savings gaps. While the role of foreign aid has diminished recently, it remains crucial for achieving Sustainable Development Goals (SDGs), particularly in low-income countries like those in South Asia. The theoretical literature suggests that foreign aid can boost economic growth by increasing domestic capital, improving trade, transferring technology, and enhancing infrastructure. However, empirical evidence is mixed, with some studies suggesting aid crowds out domestic investment due to factors like consumption, corruption, and balance-of-payments issues. Previous research on the aid-investment link lacks consensus on the role of conditional factors, and often focuses on growth effects rather than the direct investment impact. This study addresses this gap by analyzing the role of six conditioning factors (financial development, trade, FDI, human development, government expenditure, and external debt) in the relationship between foreign aid and investment in South Asia, a region that has received substantial foreign aid but lacks comprehensive research on this specific topic. The study's contributions include re-examining aid's impact on investment in South Asia, examining six conditioning factors, addressing methodological limitations (cross-section dependency and structural breaks), and determining the direction of causality to inform effective policy interventions.

The theoretical literature presents conflicting views on the aid-investment relationship. Some argue that aid complements domestic savings, relaxes foreign exchange constraints, and boosts investment. Others suggest that aid might deter investment by promoting unproductive activities, corruption, or exchange rate appreciation. Empirical studies also yield mixed results. Early studies often found negative impacts, neglecting endogeneity and heterogeneity. Later studies incorporated more sophisticated methodologies but still reached inconclusive results, some finding crowding-out effects while others found crowding-in effects. Some studies emphasized the role of conditioning factors like institutions and policies. Research specifically focusing on South Asia is limited, mainly focusing on the growth effect of aid rather than its direct impact on investment. This study aims to fill these gaps by examining the conditional effect of aid on investment in South Asia.

The study uses panel data from six South Asian countries (1990-2019). A multi-step procedure is employed. First, second-generation panel unit root tests (CIPS and KT, accounting for structural breaks) are used to assess the stationarity of the variables. Second, panel cointegration tests (Westerlund, 2007 and Westerlund & Edgerton, 2008, accounting for cross-section dependency and structural breaks) are applied to investigate long-run relationships. Third, the Pooled Mean Group (PMG) estimator in an ARDL framework is used to estimate short-run and long-run effects of foreign aid on investment, accounting for the six conditioning factors. A robustness check is performed using the Common Correlated Effect Pooled Mean Group (CCEPMG) estimator, which accommodates cross-sectional effects and structural breaks. Finally, a dynamic heterogeneous panel causality test (Juodis et al., 2021) is implemented to determine the causal relationship between aid and investment.

The study finds evidence of a long-run relationship between foreign aid and domestic investment. Using both PMG and CCEPMG estimations, the long-run coefficient of foreign aid is negative and significant, indicating that foreign aid directly crowds out domestic investment in South Asia. A 1% increase in foreign aid (as a percentage of GDP) reduces domestic investment by approximately 0.78% (PMG) and 0.71% (CCEPMG). However, the net effects considering the interaction between aid and the six conditioning factors reveal a more nuanced picture. The net effect of aid is positive when considered alongside financial development, trade, FDI, and human development. This suggests that aid complements investment through these channels. Conversely, the net effect is negative when considering the interaction of aid with external debt and government expenditure, indicating that aid substitutes investment in these cases. The causality test shows bidirectional causality between foreign aid and domestic investment, further supporting the crowding-out hypothesis.

The findings address the research question by demonstrating the complex relationship between foreign aid and domestic investment in South Asia. The direct negative impact of aid on investment highlights potential inefficiencies in aid utilization and governance challenges. The positive net effects through specific channels emphasize the importance of considering the contextual factors that shape aid effectiveness. The results challenge the assumption that aid automatically complements investment and underscore the need for targeted interventions to improve aid effectiveness. The bidirectional causality reinforces the notion that the negative impact of aid on investment can create a feedback loop that perpetuates lower investment levels.

This study contributes to the aid-development literature by demonstrating the direct negative impact of foreign aid on domestic investment in South Asia, while simultaneously showing that aid can positively influence investment through specific channels. Policy implications include reviewing aid policies to align with national development priorities, strengthening aid management systems, enhancing complementarities between aid and trade, human capital, FDI, and financial development, and improving the efficiency of government expenditure. Future research could explore country-specific factors in greater detail and analyze the effectiveness of various aid modalities.

The study is limited to six South Asian countries and the period 1990-2019. The generalizability of the findings to other regions or time periods might be limited. The study relies on aggregate data, which may obscure variations at the firm or sectoral levels. While the methodology addresses several methodological challenges, potential omitted variables or unobserved heterogeneity could influence the results.