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Category: Econometrics

Published September 18, 2012

LATE with Multiple Instrumental Variables

(If you are a new reader, this post is a bit more technical in nature and follows up on a three-part series published over the past few weeks. Click the following links for parts 1, 2, and 3.)

A colleague writes:

I have been enjoying your posts on the LATE. It got me thinking, as the number of instruments increases, does the LATE approach the ATE? Put another way, as the R2 of the instrumenting equation approaches 1, does the LATE converge to the ATE?

Continue readingLATE with Multiple Instrumental Variables

Published September 10, 2012

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.

Continue readingNever Too LATE, Part 3: Observational Data
Published September 6, 2012

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:

Continue readingNever Too LATE, Part 2