Paul Goldsmith-Pinkham, Peter Hull, Michal Kolesár
arXiv 9 Jun 2021 · Econometrics · publishedAmerican Economic Review (2024) · 59 citations (OpenAlex)
arXiv:2106.05024 · PDF · DOI · OpenAlex · Extracted main text
We study regressions with multiple treatments and a set of controls that is flexible enough to purge omitted variable bias. We show that these regressions generally fail to estimate convex averages of heterogeneous treatment effects -- instead, estimates of each treatment's effect are contaminated by non-convex averages of the effects of other treatments. We discuss three estimation approaches that avoid such contamination bias, including the targeting of easiest-to-estimate weighted average effects. A re-analysis of nine empirical applications finds economically and statistically meaningful contamination bias in observational studies; contamination bias in experimental studies is more limited due to smaller variability in propensity scores.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Krueger, Alan B (1999) Experimental estimates of education production functions | 1.000 | 8 | 3 | 100% |
| 2 | Angrist, Joshua D (1998) Estimating the Labor Market Impact of Voluntary Military Service Using Social Security Data on Military Applicants | 1.000 | 7 | 5 | 100% |
| 3 | Callaway, Brantly, Sant'Anna, Pedro H.C (2021) Difference-in-differences with multiple time periods | 0.928 | 5 | 4 | 80% |
| 4 | Wooldridge, Jeffrey M (2021) Two-Way Fixed Effects, the Two-Way Mundlak Regression, and Dif\-fer\-ence-in-Dif\-ferences Estimators | 0.928 | 5 | 4 | 80% |
| 5 | De Chaisemartin, Clément (2023) Two-Way Fixed Effects and Differences-in-Differences Estimators with Several Treatments | 0.894 | 7 | 4 | 71% |
| 6 | Sun, Liyang, Abraham, Sarah (2021) Estimating Dynamic Treatment Effects in Event Studies with Heterogeneous Treatment Effects | 0.888 | 10 | 4 | 70% |
| 7 | Crump, Richard K., Hotz, V. Joseph, Imbens, Guido W., Mitnik, Oscar A (2006) Moving the Goalposts: Addressing Limited Overlap in the Estimation of Average Treatment Effects by Changing the Estimand | 0.843 | 4 | 3 | 75% |
| 8 | Hull, Peter D (2018) Estimating Treatment Effects in Mover Designs self | 0.843 | 5 | 3 | 60% |
| 9 | Borusyak, Kirill, Jaravel, Xavier, Spiess, Jann (2024) Revisiting Event-Study Designs: Robust and Efficient Estimation | 0.794 | 10 | 4 | 50% |
| 10 | (2020) Two-Way Fixed Effects Estimators with Heterogeneous Treatment Effects | 0.754 | 7 | 3 | 43% |
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