To continue with the theme of debating development, over at NYU's Development Research Institute, Abhijit Banerjee debates Angus Deaton:
Banerjee described the surprising result of a recent experiment in Hyderabad, India. Even with access to small loans, small business owners did not invest in growing their own businesses. This is surprising because other RCTs have shown that such investments would reap returns of 60-100 percent a year.
Banerjee suggested several explanations. Perhaps the scale is simply too small. Perhaps lack of education constrains the potential of these businesses. But the most convincing explanation according to Banerjee is that for the poor, the returns are huge incrementally, but small in absolute terms. The owners of these very small businesses think that whatever profits they might earn are unlikely to dramatically change their lives.
The larger point is that the whole intellectual journey of finding a surprising research result and formulating and testing hypotheses to explain the puzzle would not be possible without RCTs:
“We Need Experiments”
►Angus Deaton responded that RCTs are of limited value since they focus on very small interventions that by definition only work in certain contexts. It’s like designing a better lawnmower—and who wouldn’t want that? —unless you’re in a country with no grass, or where the government dumps waste on your lawn. RCTs can help to design a perfect program for a specific context, but there’s no guarantee it will work in any other context.
RCTs are so highly regarded because people assume that the randomness of the selection eliminates bias. What people don’t talk about is that there are actually two stages of selection. The first stage, in which researchers start with the entire population, and choose a group which will in the second stage be randomly divided into the study and control groups, is NOT random. Selection in the first stage may be determined by convenience or politics, and therefore may not be representative of the entire population.
