Mostly Harmless!

DON'T PANIC! The core methods in today's econometric toolkit are linear regression for statistical control, instrumental variables methods for the analysis of natural experiments, and differences-in-differences methods that exploit policy changes.

This is the refrain of Joshua Angrist and Steve Pischke in the preface to their new book: "Mostly Harmless Econometrics". We mentioned it on the blog before here. In advance of Professor Angrist's visit to Geary on Friday, people might be interested in a preview of the Mostly Harmless book that is available here. For anyone who doesn't have a copy of the book (or even if you do), it's worth looking at the paper by Angrist and Krueger on "Empirical Strategies in Labour Economics". This is more a primer than a paper; it featured here (takes less time to to load up) in the 1999 Handbook of Labour Economics.

Abstract below:

This chapter provides an overview of the methodological and practical issues that arise when estimating causal relationships that are of interest to labor economists. The subject matter includes identification, data collection, and measurement problems. Four identification strategies are discussed, and five empirical examples -- the effects of schooling, unions, immigration, military service, and class size -- illustrate the methodological points. In discussing each example, we adopt an experimentalist perspective that emphasizes the distinction between variables that have causal effects, control variables, and outcome variables. The chapter also discusses secondary datasets, primary data collection strategies, and administrative data. The section on measurement issues focuses on recent empirical examples, presents a summary of empirical findings on the reliability of key labor market data, and briefly reviews the role of survey sampling weights and the allocation of missing values in empirical research.

Finally, there is also a range of "Mostly Harmless" t-shirts for sale; see below for a sample!