Evaluation of the Aid-Growth Relationship Presented by Ghassan Baliki and Emiko Nishii Development Workshop

Outline Empirical Framework of Rajan and Subramanian (2005) Potential drawbacks How can we understand the Aid-Growth relationship better? Aid Effectiveness Literature (AEL): A Meta-Study Main Findings and Concluding Remarks

Rajan and Subramanian (2005): What Does the Cross-Country Evidence Really Show? Endogeneity issues – Aid may depend on level of income (i.e. donors increase aid inflows based on recipients’ needs) >> Aid can’t be exogenous with respect to growth Constructing instruments for Aid is necessary Alesina & Dollar (1998) >> Aid is often allocated based on historical & diplomatic reasons

Rajan and Subramanian (2005): Cont’d Constructing IV for Aid: 1) Find the share of donor d’s aid allocated to recipient r in year t. 2) Use the predicted share to compute aid to GDP ratio received by country r in year t.

Rajan and Subramanian (2005): Cont’d Dependent variable: average annual growth rate of per capita GDP ( , , , ) The results suggest that with exclusion of outliers, 3 out of 5 cases, the coefficient of Aid is negative, and significant in none. >> decomposition of Aid is necessary to understand the Aid-Growth relationship better

Rajan and Subramanian (2005): Cont’d Disaggregate Aid by: 1) Sectors (social, economic and food) 2) Timing of impact (short, and long impact) e.g. whereas food aid should not be expected to affect long-run growth, social & economic aid should 3) Type of donor (multilateral vs. bilateral) i.e. multilateral aid is less ‘political’ than bilateral aid >> the results show that no sub-categories have any significant impact

Rajan and Subramanian (2005): Cont’d Non-linear & conditional effects of Aid on growth. - Aid effectiveness depends on policy environments? “aid effectiveness depends on the institutions that restrict appropriation of public funds by rent seeking agents” Hodler (2007) >> inclusion of policy measures (e.g. CPIA by the World Bank) - Diminishing return of aid? >> inclusion of aid squared Results suggest that in no case, the coefficients are significant. >> potentially driven by endogeneity and country-specific characteristics

Rajan and Subramanian (2005):Cont’d - the first-difference GMM - the system GMM >> the results are fragile (e.g. depends on the # of lags or independent variables included, the results change) First-difference GMM system GMM Total aid- and significant- and insignificant Short-impact aid- and significant- and insignificant Economic aid+ and significant

Rajan and Subramanian (2005): Cont’d Quantitative Impact of Aid Assumption: Mainly, Aid influences growth through increasing public investment. α=0.35, Y/K=0.45, and β=1 give a suggested coefficient of >> the coefficients for many existing literature are overestimated.

Rajan and Subramanian (2005): Cont’d We must pay attention to the potential importance of a previously neglected factors. The importance of understanding ‘Aid influences growth through which channels exactly?’: >> In this context, investigating ‘What’s preventing aid from having a positive impact on growth?’ may be helpful. Related Literature: - Lensink and Morrissey (1999) “Uncertainty of Aid Inflows and the Aid-Growth Relationship” - Rajan and Subramanian (2005) “What Undermines Aid’s Impact on Growth?”

Lensink and Morrissey (1999): “Uncertainty of Aid Inflows and the Aid-Growth Relationship” Aim: The paper seeks to find whether uncertainty associated with (volatility of) the level of aid inflows affects the impact of aid on growth. Potential impact of Aid on growth with the presence of Uncertainty: - investors may postpone/cancel investment decisions - Aid is an important component of government revenues >>volatility of receipts may impact on fiscal behavior, thus growth Policies/Institutions may be conditional on aid inflows.

Financial Resources Inflows from DAC to Developing Countries

Lensink and Morrissey (1999) Cont’d Dependent variable: avg. growth rate of GDP per capita Aid=level of Aid Construct proxy for uncertainty 1) a forecasting equation is estimated (as a first or second-order autoregressive process, extended with a time trend) 2) calculate the standard deviation of the residuals from the forecasting equation >> The coefficients on uncertainty are negative and significant. >> When the uncertainty measure is included Aid becomes significant and positive

Lensink and Morrissey (1999): Cont’d Still some drawbacks……… By using the cross-country approach, there are possibilities that exogenous factors leading to a bias estimator. Almost any explanatory variable could be found to have a significant effect whereas the ‘truth’ is that apparent significance is due to common causalities or spurious regressions >> omitted variable bias still remains. Is “growth” a good variable to capture the effectiveness of aid?

Rajan and Subramanian (2005): “What Undermines Aid’s Impact on Growth?” What’s preventing Aid from having a positive impact on growth? - The Aid-Competitiveness Approach Best way to check aid-effectiveness is to compare ‘fact’ and ‘counter- fact’ >> not possible. Instead, check whether labor-intensive industries grow relatively slower in countries with high aid-inflow compare to non-labor- intensive industries. This approach allows us to capture 1) within-country differential effects, and 2) country treatment effect to understand the effect of aid.

Rajan and Subramanian (2005): “What Undermines Aid’s Impact on Growth?” How Aid can influence growth through ‘competitiveness’ channel? Under the fixed exchange rate: Aid spent on domestic goods pushes up the price of recourses that are in limited supply domestically (e.g. skilled worker). Under the flexible exchange rate: Aid inflows increase nominal exchange rate, thus reducing competitiveness.

Rajan and Subramanian (2005): “What Undermines Aid’s Impact on Growth?” Strong evidence consistent with aid undermining the competitiveness of the labor-intensive or exporting sectors. In countries that receive more aid, labor-intensive and exportable sectors grow slower relative to capital-intensive and non-exportable sectors. Aid inflows do cause overvaluation Are the results compelling? Major exports sector for all recipient counties is labor-intensive? on balance, whether these adverse competitiveness effects offset any beneficial effects of aid is unclear.

AEL – Doucouliagos and Paldam (2006, 2007a, 2008) ▫Do the estimates of the AEL converge to something we might term 'truth'? ▫Can we identify the main innovations which cause (prevent) convergence? ▫Do biases exist while uncovering the 'truth' about aid effectiveness ?

Three Perennial Problems ▫1) Priors ▫2) Data Mining ▫3)Incentives - Innovation with skepticism - Reliance on independent replication - and the Reluctance Hypothesis

Absolute Aid Ineffectiveness

Why is it Puzzling? ▫“Why would they” vs. “If it is, it must be rational” → Aid fatigue ▫Marginal Project vs. Financed Project ▫Always via accumulation? ▫No repay means no crowding out

Meta-Analysis Priors and Biases: ▫Polishing ▫Ideology ▫Goodness Meta Analysis Methodologies: ▫Meta-Significance Test (MST) ▫Precision-Effect Testing (PET) ▫Funnel Asymmetry Test (FAT)

The Three Family Models of AEL

Does Aid Cause Increasing Accumulation? Large but probably not full crowding effect

A Large Crowding Out

Does Aid Cause Increasing Growth? Neoclassical Model: Results: ▫Decline in variation over time and with sample size ▫More Extreme points ▫Average decreasing ▫Non-symmetrical funnel around horizontal axis

Funnel Plot, No Economic Significance!

Aid Growth Effects: Reluctance Trends

Is the Effect of Aid on Growth Conditional? Good Policy Model (Burnside and Dollar, 2000): The Medicine Model (Lensink and White, 2001):

Conclusion of the Three Meta-Studies