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Parallel Trends and Dynamic Choices

Philip Marx, Elie Tamer, Xun Tang

arXiv 14 Jul 2022 · Econometrics · publishedJournal of Political Economy Microeconomics (2023) · 13 citations (OpenAlex)

arXiv:2207.06564 · PDF · DOI · OpenAlex · Extracted main text

Abstract

Difference-in-differences is a common method for estimating treatment effects, and the parallel trends condition is its main identifying assumption: the trend in mean untreated outcomes is independent of the observed treatment status. In observational settings, treatment is often a dynamic choice made or influenced by rational actors, such as policy-makers, firms, or individual agents. This paper relates parallel trends to economic models of dynamic choice. We clarify the implications of parallel trends on agent behavior and study when dynamic selection motives lead to violations of parallel trends. Finally, we consider identification under alternative assumptions that accommodate features of dynamic choice.

Citation extraction

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Most heavily cited references

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.

ReferenceIntensityMentionsSectionsMain text
1De Chaisemartin and d'Haultfoeuille (2020) Two-way fixed effects estimators with heterogeneous treatment effects1.00053100%
2Sun and Abraham (2021) Estimating dynamic treatment effects in event studies with heterogeneous treatment effects0.92844100%
3Callaway and Sant’Anna (2021) Difference-in-differences with multiple time periods0.92843100%
4De Chaisemartin and d'Haultfoeuille (2018) Fuzzy differences-in-differences0.92843100%
5Ashenfelter and Card (1985) Using the Longitudinal Structure of Earnings to Estimate the Effect of Training Programs0.8434375%
6Malani and Reif (2015) Interpreting pre-trends as anticipation: Impact on estimated treatment effects from tort reform0.7373367%
7Abadie (2005) Semiparametric Difference-in-Differences Estimators0.73732100%
8Manski and Pepper (2018) How do right-to-carry laws affect crime rates? Coping with ambiguity using bounded-variation assumptions0.73732100%
9Rambachan and Roth (2019) An honest approach to parallel trends0.73732100%
10Athey and Imbens (2022) Design-based analysis in difference-in-differences settings with staggered adoption0.64422100%

Showing the top 10 of 59 scored citations.

Cited by, within the corpus

arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.

Citing paperIntensityMentionsSections
1Selection and parallel trends1.00083
2Dynamic covariate balancing: estimating treatment effects over time with potential local projections0.73733
3Dynamic Biases of Static Panel Data Estimators0.64422
4Heterogeneous Treatment Effects via Linear Dynamic Panel Data Models0.64422
5Back to Feedback Dynamics and Heterogeneity in Panel Data0.64422
6Causal Graphs for Conditional Parallel Trends0.64422
7Forecasted Treatment Effects with Short Panels0.51122
8Difference-in-Differences Designs: A Practitioner's Guide0.51121
9A Joint Analysis of Sensitivity to Anticipation and Parallel Trends Violations0.51121
10Policy Evaluation during a Pandemic0.40511