Does Aid affect Infant Mortality?

The IMF says;

Health aid has a statistically significant effect on infant mortality: doubling per capita health aid is associated with a 2 percent reduction in the infant mortality rate. For the average country, this implies that increasing per capita health aid by US$1.60 per year is associated with 1.5 fewer infant deaths per thousand births. The estimated effect is small, relative to the targets envisioned by the Millennium Development Goals

Excerpts from the conclusion;

Although past studies have failed to document robust evidence that aid encourages economic growth, there remains hope among academics, policy makers, and the media that aid serves a critical role by saving lives. This hope is consistent with micro-level evidence of the success of specific public health intervention programs. In addition, economic growth plays a limited role in explaining changes in health outcomes, implying that focusing exclusively on the effect of aid on growth may overlook important health benefits from aid.

Despite the vast empirical literature considering the effect of foreign aid on growth, the hope that aid improves health outcomes is backed by surprisingly little systematic evidence. The main contribution of this paper is to present new, systematic and comprehensive cross-country evidence on the effect of health aid on a key health outcome—infant mortality. To the best of our knowledge, this paper is the first empirical study to examine the effect of health aid on health outcomes.

In a sample of 118 countries from 1970–2004, we find that increased health aid is associated with a statistically significant reduction in infant mortality. The estimated effect of doubling health aid is a 2 percent reduction in infant mortality rates, which is small relative to the goals envisioned by the MDGs. In contrast, we fail to find robust evidence for a significant effect of overall aid in reducing infant mortality. The results are consistent with suggestive evidence that unlike overall aid, health aid is associated with a statistically significant rise in health spending.

The estimates of the effect of health aid on health outcomes need to be qualified because the health aid data are likely to suffer from underreporting. However, health aid is reported by donors, and there is no reason to believe that the cost of accurately reporting aid commitments depends on the recipient. Therefore, it is plausible that measurement error due to the underreporting of health aid is not systematically related to the characteristics of the recipient country. In this case, the estimated effect of health aid would be attenuated, and our estimates would understate the true beneficial effect of health aid.

Second, in the GMM estimations, the effect of aid is identified using variation in a country’s aid history, while controlling for several predetermined variables. As with GMM estimates in general, this source of identification is biased if the initial conditions assumed by the model are violated (Bond, 2002). This could occur, for example, if donors’ aid decisions in the initial period partially reflected their expectations of the recipients’ economic and social conditions in the future. This concern is ameliorated to some extent by the failure to reject both the null hypotheses of no second order serial autocorrelation in the residuals, and the validity of over identifying moment conditions.

Finally, the paper takes a cross-country approach to estimate the effect of foreign aid on health similar to the existing literature on aid and growth. Although the effect of aid is identified using within-country changes in aid and health outcomes over time, the estimated effect is nonetheless an average across a very heterogeneous set of countries. The use of cross-country data to address this question should therefore be considered as a first step, to be complemented by detailed case studies of the nature and effects of health aid in individual countries

Related;
Dynamic panel data models: a guide to microdata methods and practice by Stephen Bond

"Ex Ante Evaluation of Social Programs"

Unit roots: identification and testing in micro panels

GMM estimation with persistent panel data: an application to production functions

Determinants and consequences of the mortality and health of infants and children

Infant mortality

The World Health Organization's ranking of the world's health systems

Health Care Intelligence Failure?;

Health care economist David Cutler devotes a chapter in his recent book to the costs and benefits of U.S. treatment of pre-term infants. He points out that "Mortality for the smallest infants...roughly two pounds, fell from 90 percent in 1950 to about 40 percent today." Cutler argues that although saving these infants is very expensive -- he cites a typical cost of $100,000 -- we are getting our money's worth, based on standard economic measures of the value of life.