This Evaluation Study is concerned with evaluation of foreign aid at the aggregate level. As we explain, for practical purposes, evaluation of the aggregate impact of foreign aid has been synonymous with asking if the inflow of foreign aid, to the poor countries, increases the growth rate of income per capita (economic growth). The focus on economic growth is rooted in two causes. First of all, average income (GDP per capita) is a good indicator of important parts of human development—although most people would agree that it does not capture all aspects. Therefore, it makes sense to look at the impact of aid on average income. Second, economists have a long tradition for analyzing economic growth leading to a rich ‘toolbox’ in terms of theories and in terms of data.
The main purpose of the study is to introduce the reader to the statistical problems researchers encounter in their analyses of aid effectiveness at the aggregate level. The statistical problems are intimately linked to empirical problems in the social sciences and they have mainly been dealt with by the special branch of economists known as econometricians. Therefore, the type of problems and their solutions are not taught at introductory statistical courses in high schools or at universities. Further, within natural sciences (including life sciences), health and
humanities, these special statistical problems are never taught in any course in statistics. This means that most people working with aid ‘on the ground’ are not familiar with the statistical requirements making them unable to judge if a study of aid effectiveness is tackling the
statistical problems in an appropriate way. Frankly, even within the economics profession many lack the necessary skills—leading to unfortunate statements, by economists, about the impact of foreign aid on economic growth.
For years, statistical analyses, using data across many countries have shown that the association between foreign aid and growth of GDP per capita is negative. This has lead some to conclude that aid is, at best, useless and, possibly, even harmful. In most cases, however, the studies forming the basis for such claims cannot be said to have evaluated the causal link from aid to economic growth.
When the statistical problems are used as a yardstick in judging if research studies (and other scholarly writings) of aid effectiveness are ‘trustworthy’ we end up with less than a dozen
published works out of more than one hundred studies written during the past forty-some years. And even among the ‘trustworthy’ studies there is disagreement and ample room for
improvement. In the companion paper (Dalgaard and Hansen, 2009) we present and discuss some of these studies.
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Annexes
The three annexes below present some of the results of the main text using math rather than graphical illustrations. This allows a more formal description of the problems and solutions. More general introductions to the estimation problems can be found in Stock and Watson (2007) or Wooldridge (2008) among many others.
Following standard practice we use Greek letters ( , , and ) to denote unknown
parameters while the letters v and u are used to indicate independent random variables. Further, we focus on ‘large sample results’ in the sense that we illustrate the properties of estimators, not the formulae as they are computed in a software program.