Using observational data, there is no way of identifying a plausible counterfactual without making assumptions that are bound to be debatable, in theory and in practice.
Overall, we believe our approach represents the most carefully developed empirical strategy employed in the aid-growth literature to date.The first quote says that unless you experiment on poor countries, randomly giving aid to some and not others, you have to make arguable assumptions about the world in order to infer anything from country-level data about whether foreign aid causes growth. The second quote might overreach slightly but is true in spirit: this is an impressively careful analysis. The authors work with a data set from a widely cited paper by Raghuram Rajan and my colleague Arvind Subramanian that concludes that there is no clear evidence of a systematic impact of aid on growth. Reanalyzing, AJT conclude that---on the contrary---it is reasonable to believe that aid worth 1% of a country's gross domestic product (GDP) raised economic growth by 0.1%/year on average during 1970--2000. That is a small but helpful impact. While I cannot prove AJT wrong, I remain skeptical. In a new CGD paper, Blunt Instruments, Michael Clemens and Samuel Bazzi powerfully express my main concern. I've explained it less technically on my microfinance open book blog with reference to studies of the impact of microcredit, and will adapt that writing here. A big challenge in the social sciences is to go beyond merely observing correlations to showing causation---e.g., that receiving aid is not merely correlated with economic growth but causes it. AJT employ a common technique for ferreting out causation: the use of instruments, which are factors that are assumed to affect an outcome of interest only through a determinant of interest (caveat for experts: "...after linearly controlling for observed covariates"). To temporarily simplify, AJT set up this picture:
population => foreign aid/capita => economic growthThe first arrow says that how many people live in a country affects how much aid it gets per person. This is true: bigger countries like India get less aid per person than small ones like Madagascar. The second arrow embodies the hope that aid increases economic growth. But by assumption no arrow runs from population directly to economic growth. Population is held to affect growth only through foreign aid. So if we observe in the data that the things on the two ends of the diagram are correlated---moving up and down together---then both the arrows in between must be at work. In particular, foreign aid is making a difference. Here, we say that population "instruments" for aid; and having the first arrow, running from the instrument, lets us study the second arrow. Notice the reasoning here. We assume:
A. Population affects growth only through aid.That plus the data leads to:
B. Aid affects growth.A few comments about this structure:
- Just about all reasoning works this way. You have to assume something to conclude something. Think of Euclid's classic text on geometry, The Elements, which begins with a handful of axioms, such as that for any two points, a straight line can be drawn to connect them.
- AJT understand this. That's what the first quote above is really about.
- It is not clear that we should believe A more readily than B. If I am ready to make one assumption about causal relationships across a diverse set of complex nations over 30 years---population only affected economic growth through aid---why stop there? Why don't I just assume B---that aid raised growth on average? It would save a lot of time. The answer has to be that A is easier to believe than B, just as Euclid's axioms are easier to believe than what Euclid proves with them, such as the Pythagorean Theorem (a2+b2=c2). But is A more credible than B in the case at hand? In Blunt Instruments, Michael and Sami point out that other economic studies have proceeded in a fashion analogous to, yet incompatible with, AJT's, by assuming that population affects growth only through how much foreign trade a country engages in or only through how much foreign investment it receives.
CGD blog posts reflect the views of the authors, drawing on prior research and experience in their areas of expertise. CGD is a nonpartisan, independent organization and does not take institutional positions.