arXiv 12 Nov 2021 · Econometrics
arXiv:2111.06573 · PDF · DOI · OpenAlex · Extracted main text
In program evaluations, units can often anticipate the implementation of a new policy before it occurs. Such anticipatory behavior can lead to units' outcomes becoming dependent on their future treatment assignments. In this paper, I employ a potential-outcomes framework to analyze the treatment effect with anticipation. I start with a classical difference-in-differences model with two time periods and provide identified sets with easy-to-implement estimation and inference strategies for causal parameters. Empirical applications and generalizations are provided. I illustrate my results by analyzing the effect of an early retirement incentive program for teachers, which the target units were likely to anticipate, on student achievement. The empirical results show the result can be overestimated by up to 30% in the worst case and demonstrate the potential pitfalls of failing to consider anticipation in policy evaluation.
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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 | Imbens, G. W. and C. F. Manski (2004) Confidence intervals for partially identified parameters | 0.894 | 7 | 3 | 71% |
| 2 | Fitzpatrick, M. D. and M. F. Lovenheim (2014) Early retirement incentives and student achievement | 0.822 | 6 | 2 | 83% |
| 3 | Stoye, J (2009) More on confidence intervals for partially identified parameters | 0.737 | 5 | 2 | 60% |
| 4 | Malani, A. and J. Reif (2015) Interpreting pre-trends as anticipation: Impact on estimated treatment effects from tort reform | 0.511 | 2 | 1 | 100% |
| 5 | Sun, L. and S. Abraham (2020) Estimating dynamic treatment effects in event studies with heterogeneous treatment effects | 0.481 | 6 | 2 | 17% |
| 6 | Abadie, A. and M. D. Cattaneo (2018) Econometric methods for program evaluation | 0.405 | 1 | 1 | 100% |
| 7 | Athey, S. and G. W. Imbens (2017) The econometrics of randomized experiments | 0.405 | 1 | 1 | 100% |
| 8 | Borusyak, K. and X. Jaravel (2017) Revisiting event study designs | 0.405 | 1 | 1 | 100% |
| 9 | Bosković, B. and L. Nstbakken (2018) How much does anticipation matter? evidence from anticipated regulation and land prices | 0.405 | 1 | 1 | 100% |
| 10 | De Chaisemartin, C. and X. d'Haultfoeuille (2020) Two-way fixed effects estimators with heterogeneous treatment effects | 0.405 | 1 | 1 | 100% |
Showing the top 10 of 24 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Refining the Notion of No Anticipation in Difference-in-Differences Studies | 0.737 | 3 | 2 |
| 2 | A Joint Analysis of Sensitivity to Anticipation and Parallel Trends Violations | 0.737 | 3 | 2 |