A few months ago, Princeton economist Angus Deaton offered his vision for development economics.
In his piece, he rails against the movement toward relatively atheoretical, randomized experiments, calling for closer ties between theory and empirics.
“The great economists should be trying to do something that is harder.”
Now, in an excellent new paper, Harvard economist Guido Imbens fires back.
Imbens argues that Deaton is too dismissive of the special value that randomized experiments have in assessing causality, and that natural experiments, while not as good as randomized experiments, are far better than Deaton gives them credit for.
While it might seem difficult to mostly agree with both Deaton and Imbens, given that they espouse polar opposite views, strangely enough that is where I stand in this debate.
On the points Imbens makes, I think he is exactly right. However, what Imbens minimizes, in my opinion, is the importance of models and theory for motivating empirical research, including randomized experiments.
Given a question, of course you want a randomized experiment to give you the best answer possible. What I think has happened too much in economics recently is that the availability of experiments has trumped the asking of good questions. Or, put another way, anyone can do program evaluations based on true randomization, so why should some of the world’s best economists be devoting so much of their time to such exercises?
The great economists should be trying to do something that is harder.