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The authors thank for comments Alberto Alesina, Ernesto Hernández-Catá, and participants at the IMF conference on Macroeconomics and Poverty, held on March 14-15, 2002 and an IMF seminar. Ivetta Hakobyan and Siba Das provided expert research assistance. Views expressed are those of the authors and do not necessarily represent the official view of the International Monetary Fund.
The first fact—that industrial countries presently devote only about one-quarter of 1 percentage, significantly less than the goal of 0.7 percent, of GNP to foreign aid—has received more attention than the second fact that aid has hardly declined in importance to the countries that continue to receive it. In recent years, donors seem to have become more selective vis-á-vis economic policies pursued by recipient countries, and an increasing share of aid is being distributed based on economic and social considerations (World Bank, 2002) as opposed to geopolitical and historical considerations (Alesina and Dollar, 2000). Easterly (2002) challenged, however, the World Bank’s findings and claimed that up to 1999 no link between economic performance and aid disbursements can be observed.
Discussions of the role of aid in fiscal policy have, at times, been overshadowed by the question of how to measure the fiscal deficit: with or without grants? There is a strong case for using the definition that includes grants, provided that grants are measured accurately (and projected realistically), since grants by definition do not generate an obligation to repay. A second issue is whether the grant element of concessional borrowing should be included as revenues. To avoid double counting, this would need to be offset on the expenditure side by imputing the costs of servicing outstanding concessional debt at market rates. But imputing the entire net present value of interest subsidy when the loan is received while spreading the interest costs paid with the subsidy over the life of the loan would seem to reduce, rather than enhance, the clarity of the accounts. Moreover, the imputation of the implicit grant element would depend heavily on assumptions regarding future exchange rates and interest rates.
Some economists have argued that aid is an inefficient instrument for spurring development in low-income countries and that it played a significantly negative role in those countries by encouraging waste and corruption (Bauer, 1979).
Given that the bulk of nontradables comprises services and construction, they both can be seen as “luxuries.” In any case, changing the elasticity to one or even to less than one does not effect the results substantially.
This is, of course, a result of the Stolper-Samuelson theorem: a change in relative prices benefits the factor used intensively in the industry that expands (Stolper and Samuelson, 1941).
In practice, the upward pressure on the real exchange rate will be greater (i) the greater is the marginal propensity to spend on nontradable goods, (ii) the lower is their supply responsiveness, (iii) the higher the demand responsiveness to price changes, and (iv) the lower the policy coordination to sterilize aid inflows.
Another class of models dealing with the impact of aid looks at the political economy impact of aid flows and these models are mostly skeptical about any positive aid effects. The most prominent are: (i) “the war of attrition” models (Bulow and Klemperer, 1999), where aid results in bad policies, because individual factions in the recipient country cannot agree on how aid should be allocated and spent and (ii) “the voracity effect” models (Tornell and Lane, 1999), where weak institutional structure combined with fractionalization of the governing elite produce wasteful spending of aid inflows. Empirical support for these models was provided by Casella and Eichengreen (1996) and Alesina and Weder (2002), respectively.
Dutch disease models—see Edwards and van Wijnbergen (1989) for a model and White (1992) for a review—were originally formulated for countries with sudden discoveries of natural resources, but were eve1ntually extended to the effects of aid inflows in developing countries and even foreign direct investment surges in transition and emerging economies (Frait and Komárek, 1999).
From a technical point of view, the single-country studies are vulnerable to sample changes aid regime switching: most of these countries have had alternating periods of very low and very high periods of aid inflows, casting doubts on the stability of the estimated parameters. Moreover, those models invariably use short time series only.
These channels also seem to imply that the traditional thinking about private investment crowding out through higher real interest rates is less relevant in developing economies.
This may not be an easy assumption to make. Even in relatively well-run countries, diversion of public funds may reach staggering proportions. For example, Reinikka and Svensson (2002) report that in Uganda “… on average, during the period 1991-95, schools received only 13 percent of what the central government contributed to the schools’ nonwage expenditures. The bulk of the allocated spending was either used by public officials for purposes unrelated to education or captured for private gain.”
Elbadawi (1998) estimated the relative role of endowment, transaction costs, and exchange rates for manufacturing exports in a sample of African countries. He found that high transaction costs and exchange rates misalignment explain the bulk of Africa’s export underperformance vis-á-vis East Asia.
We approximate the share of traded goods by the share of agriculture (including fishing), mining, and manufacturing. We show results for those countries from Table 1 where the appropriate data were available. Our results are similar to those reported by Laplagne (1997), who reported the share of tradable goods for a sample of small South Pacific economies.
See Hadjimichael et al (1995), Burnside and Dollar (2000), and Collier and Dehn (2001) for the good policies-aid-growth nexus and the critique by Lensink and White (2000), Guillaumont and Chauvet (2001), Dalgaard and Hansen (2001), Hansen and Tarp (2001b), and Easterly (2002). In contrast, Easterly (2001) argues that neither good policies nor exogenous shocks can explain much of the poor growth performance in developing countries and finds a strong link to the rate of growth in OECD countries in the context of a leader-follower model.
The most frequently cited reason for low foreign direct investment are negative investors’ perceptions about poor countries economic and political stability, inadequate infrastructure, and a weak legal framework, particularly for the enforcement of contracts.
See Guillaumont and Chauvet (2001) for a similar argument in the context of the Dollar-Burnside regression: once “structural vulnerability” is taken into account, the aid- policy interactive term becomes insignificant.
Past attempts at formulating such long-term paths, such as the 25-year, UNDP- funded Vision 2020 that were formulated for a number of developing countries in the mid 1990s, failed to gamer support both from the authorities and key donors.
It is not difficult to imagine situation when the domestic authorities bargain with the donor agencies about interpretation of outcomes in the same way they presently bargain about the thrust of future policies.
For example, IMF-supported programs during 1993-96 contained somewhat more structural measures in aid-dependent countries than in those where the role of aid has been negligible. The estimated parameter in regression of the number of structural conditions on aid in percent of GDP is statistically significant at the 90 percent level.
One widely-cited and influential paper reports the opposite result (Collier, 1999), but this is mainly a reflection of some particular features of the empirical methodology used, including the failure to de-trend the data and the exclusive focus on U.S. dollar measures of aid and tax revenues (discussed below). For a discussion of empirical issues in estimating the volatility of aid, see Bulíř and Hamann, 2001.
Collier (1999) reported that aid was negatively correlated with revenue in a sample of African countries; however, his estimated covariance term incorporates the same empirical features as in the previous footnote, and moreover it is not significantly different from zero.
Aid was found to be countercyclical mostly in countries with large, short-lived shocks and post-conflict countries. From the donor perspective, French-speaking countries were more likely to receive aid in a countercyclical pattern, but as before, the results do not seem to be robust.
These results do not necessarily mean that aid-financed budgets are more variable than budgets financed by the same level of tax revenues. This is because the variance of total revenues equals the sum of the variances of aid and non-aid revenues plus their covariance— an effect analogous to portfolio diversification. But this will be true in most cases, given that aid is several times as volatile as tax revenues and the covariance term is either zero or positive in most countries.
Project (“tied”) aid constitutes payments for investment projects agreed between the donor and recipient and its fungibility depends on whether the authorities intended to finance these projects themselves, prior to the aid commitment (White, 1992). In contrast, program aid (also called balance of payment support or “untied” aid) generally comes in a “cash” form and is perfectly fungible—the authorities have complete control over the use of these resources.
Program interruption occurs if either: (i) the last scheduled program review was not completed; or (ii) all scheduled reviews were completed but the subsequent annual arrangement was not approved in ESAF/PRGF arrangements.
To some extent, this may reflect the strategic behavior by the IMF, given its role in giving a “seal of approval” as the basis for other external assistance.
The majority of IMF-supported programs include adjusters to ensure that quarterly spending plans can continue even if aid falls short of projected levels. See International Monetary Fund (2002), Annex I for a discussion.
As a related issue, empirical evidence on a direct impact of aid in the monetary area is rather scanty and outdated (see White, 1992 for a review). Recently, Fanizza (2001) illustrated, in the case of Malawi, inflationary pressures resulting from the government’s inability to sell sufficient amount of foreign exchange, owing to the country’s small and isolated foreign exchange market.