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Category: Economics

Never Too LATE, Part 2

I began this discussion on Tuesday with an example in order to define the concept of local average treatment effect (LATE).

In the words of Imbens and Wooldridge (2007), LATEs are “average effects for subpopulations that are induced by the instrument to change the value of the endogenous regressors.”

What prompted my wanting to write about LATE is a post on Tom Pepinsky’s blog, where Tom discusses the frequent lack of discussion of local average treatment effects (LATEs) in the political science literature:

Kaushik Basu Is the New Chief Economist of the World Bank

I had heard a very credible rumor about this a few weeks ago, but here is the official announcement on the World Bank’s website. If you don’t know who he is, here is the Wiki entry for Kaushik Basu, and here is his Cornell webpage.

I was lucky enough to take Kaushik’s graduate level development class in the early years of my Ph.D. As you might expect, the course was mostly about theory, and we used Kaushik’s Analytical Development Economics as our textbook. I also really liked his 2003 book on political economy.

Kaushik is one of the most interesting lecturers I have had a chance to learn from in the ten years I spent as a student at various universities doing my B.Sc., M.Sc., and Ph.D. degrees. He is also one of my favorite writers in economics because of his clear, congenial style.

Never Too LATE, Part 1

In a post on his blog, Cornell’s Tom Pepinsky discusses the frequent lack of discussion of local average treatment effects (LATEs) in the political science literature:

On two separate occasions I have been told by reviewers to “remove the discussion of the local average treatment effect” from a manuscript under review. One reviewer did not seem to understand what the LATE is. The other wrote something along the lines of “everyone knows what the LATE is, so get on with it.”

What’s a LATE? Suppose you wanted to test the claim that “breakfast is the most important meal.” You would randomly select, say, 50 subjects and randomly assign them to the treatment and control groups.