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Category: Impact Evaluation

Never Too LATE, Part 3: Observational Data

Last week I wrote two posts about the local average treatment effect (LATE). Click here for part 1, and here for part 2, in which I respectively discuss the difference between the ATE and the LATE, and the difficulty of comparing results across studies if different studies rely on different instrumental variables (IV).

This brings me to the topic of this post. After I posted part 2 last week, a reader — an economist who has been out of school for some time — emailed me with the following:

I can’t recall learning about this while in grad school. Surely it was mentioned and it’s just receded into a dark corner of my memory? It seems like a pretty important concept to consider, although I guess it’s a bigger concern for experimental economics?

The emphasis is mine. An equally emphatic answer would be: “No, it’s actually a huge problem with nonexperimental data.”

Wages, Education, and the Vietnam War

To see this, consider the classic IV example — Angrist’s (1990) study of the impact of education on wages. Because wages and education are jointly determined — if anything, there is reverse causality because people choose to go to spend time in school based on the expectation of a higher wage — Angrist used a respondent’s Vietnam draft lottery number as an IV for the respondent’s education.

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:

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.