What Randomization Can and Cannot Do: The 2019 Nobel Prize

“A PhD student of ours on the market this year, Carlos Inoue, examined the effect of random allocation of a new coronary intervention in Brazilian hospitals. Following the arrival of this technology, good doctors moved to hospitals with the “randomized” technology. The estimated effect is therefore nothing like what would have been found had all hospitals adopted the intervention. This issue can be stated simply: randomizing treatment does not in practice hold all relevant covariates constant, and if your response is just “control for the covariates you worry about”, then we are back to the old setting of observational studies where we need a priori arguments about what these covariates are if we are to talk about the effects of a policy.”

A Fine Theorem

It is Nobel Prize season once again, a grand opportunity to dive into some of our field’s most influential papers and to consider their legacy. This year’s prize was inevitable, an award to Abhijit Banerjee, Esther Duflo, and Michael Kremer for popularizing the hugely influential experimental approach to development. It is only fitting that my writeup this year has been delayed due to the anti-government road blockades here in Ecuador which delayed my return to the internet-enabled world – developing countries face many barriers to reaching prosperity, and rarely have I been so personally aware of the effects of place on productivity as I was this week!

The reason for the prize is straightforward: an entire branch of economics, development, looks absolutely different from what it looked like thirty years ago. Development economists used to be essentially a branch of economic growth. Researchers studied topics like the productivity of large…

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