David Roodman over at the CGD recently posted a great article about the new aid-growth paper published by WIDER, of which he remains a skeptic. Scroll down to the comments, and you’ll see Owen Barder making some very good points in response.
I also posted a comment on the piece. My concern was rather different and probably not best suited for that blog. Among various ramblings, I wrote:
At what point did finding universal answers become the only legitimate basis of economic study? Development has looked and proceeded differently in different places…
Statistics is just one type of evidence. Why have economists apparently forgotten this?
My plea was for an approach to development that took in far more specific case study analysis. By this I mean not the Duflo/Banerjee approach of randomized trials, but a holistic approach to development that focuses more on the actual historical process of development in specific places over real time than abstractions with pretense to universality based on cross section data or studies dealing with specific interventions.
The rationale behind this is simple to me: firstly, a disinterested analysis of what we know about successful development processes emphasises their diversity more than their similarities, though these exist and are important. There is little reason to assume that imagined future development processes will have more uniformity. Secondly, understanding of real development successes and real development failures (however they are defined) demonstrate that they are typically the result of a range of complex interacting factors. In most cases, causal mechanisms have shown inconstancy, with the same phenomenon having markedly different effects depending on context and time, even within the same country.
Of course, this kind of method is messy; it won’t ever give us unambiguous answers as to what works and to what extent. It requires that we formulate policy based on our understanding of the historical circumstances that led to the current state in a country, bearing in mind that the interplay between factors cannot always be modeled as there are concurrent effects on multiple levels (individual interactions, social interactions between groups and state-subject/citizen relations for example) and different effects in different regions or time periods. It will mean that we have to rely on what we know from other countries and other times, trying to tease out the central relevant lessons.
It’s an approach that is anathema to modern economics. The majority of our current work tends towards universality of analysis and conclusion. It seeks to pose theoretical relationships that hold under specific assumptions (which are often implicitly further assumed to hold everywhere if they hold anywhere) and then test them. If the tests work (and for the cynical, even if they don’t), they seek to tell us of a ‘robust’ concrete relationship: each unit of factor X contributes 0.1 units of GDP growth. Paradoxically, this often leads to just as much messiness and uncertainty as a historical analysis. The aid regressions Roodman looks at are a classic example: the exact same data produces opposite results depending on model specification. Neither result is unambiguous even on its own terms.
Economics was not always like this though. Early economists were multidisciplinary creatures by nature. They studied history, social relationships and the economy as interlinked phenomena, using a holistic method that took in historical evidence, theoretical abstractions from this evidence and some further statistical evidence to support their ideas. Statistics was necessarily a smaller part of their work, for their data and the sophistry of their statistical techniques was still quite basic. This period still produced what to my mind remain the two greatest works of economic thought: The Wealth of Nations and Capital.