Chris Blattman writes:
I joke with my graduate students they need to get as many technical skills as possible as PhD students because the moment they graduate it’s a slow decline into obsolescence. And of course by “joke” I mean “cry on the inside because it’s true”.
Take experiments. Every year the technical bar gets raised. Some days my field feels like an arms race to make each experiment more thorough and technically impressive, with more and more attention to formal theories, structural models, pre-analysis plans, and (most recently) multiple hypothesis testing. The list goes on. In part we push because want to do better work. Plus, how else to get published in the best places and earn the respect of your peers?
It seems to me that all of this is pushing social scientists to produce better quality experiments and more accurate answers. But it’s also raising the size and cost and time of any one experiment.
This should lead to fewer, better experiments. Good, right? I’m not sure. Fewer studies is a problem if you think that the generalizabilty of any one experiment is very small. What you want is many experiments in many places and people, which help triangulate an answer.
The entire post is of interest, and that of course is also probably the biggest problem with RCTs as they are practiced in economics, namely they lead to a greater centralization of knowledge generation and validation. Chris also cites this new and very important piece by Alwyn Young (pdf). You can’t always believe what you read, as my grandmother used to say.