# Is there evidence for the absence of an aid effect, or is there just absence of evidence?

Aid policy was based on the premise that aid raises growth, but …{a major} study of this question was saying that this premise was false.

This quote refers to the Rajan-Subramanian paper (later published in a peer-reviewed journal) that was unable to reject the hypothesis of a zero effect of aid on growth. As I never tire of pointing out, we often get our conditional probabilities mixed up. Based on standard statistical methodology, the (1) probability of failing to reject the zero effect hypothesis is high when the effect is indeed zero. Unfortunately, the author of the quote incorrectly thinks this implies the opposite probability is high -- (2) the likelihood that the effect is indeed zero when you fail to reject the hypothesis of zero. This likelihood can actually be quite low even if the first probability is high. Absence of Evidence does not constitute Evidence for Absence.

Who is this nincompoop?

This 2006 quote is from William Easterly. Oops. Those cognitive biases are even stronger than I thought.

In a desperate bid to save face, there is SOMETHING defensible you can say about the growth effect of aid based on the Rajan and Subramanian paper. They report the standard error of the estimated coefficient of growth regressed on aid (addressing causality), which implies we can say with 95% confidence that the effect lies between -.06 and .18. So we CAN reject the hypothesis that one percentage point of additional aid to GDP raises growth by anything more than 0.18 percentage points.

As it happens, the standard model of aid, investment, and growth (old-fashioned but still in use today in the World Bank, IMF, and UN Millennium Project) implies that aid goes into investment one for one, and then this investment raises growth. With the usual parameters, this would imply an aid effect on growth of 0.2 or higher. THAT model we can reject.

The most honest statement about the modest growth effects is that they are more difficult to discern in the data ONE WAY OR THE OTHER.

Let us all now feel suitably chastened and humbled.