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Selection and parallel trends

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arxiv 2203.09001 v15 pith:YJMGT7TE submitted 2022-03-17 econ.EM

classification econ.EM
keywords selectionconditionsparalleltrendsassumptionsbenchmarkingbiaseffect
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We study the role of selection into treatment in difference-in-differences (DiD) designs. We derive necessary and sufficient conditions for parallel trends assumptions under general classes of selection mechanisms. These conditions characterize the empirical content of parallel trends and clarify the trade-offs between assumptions about selection into treatment and restrictions on the time series properties of the potential outcomes required for DiD methods. We use the necessary and sufficient conditions to provide a selection-based decomposition of the bias of DiD and provide easy-to-implement strategies for benchmarking its components. We also provide templates for justifying DiD in applications with and without covariates. Reanalyses of the causal effect of NSW training programs and the effect of the Medicaid expansion demonstrate the usefulness of our selection-based approach to benchmarking the bias of DiD.

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Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Moment Restrictions for Nonlinear Panel Data Models with Feedback

    econ.EM 2025-06 accept novelty 8.0 of 10

    A complete characterization of feedback and heterogeneity robust moment functions for nonlinear panel data, with efficiency bounds and closed-form moments for mixed proportional hazards models.

  2. Learning What to Learn: Experimental Design when Combining Experimental with Observational Evidence

    econ.EM 2025-10 conditional novelty 7.0 of 10

    Designing experiments that will be combined with observational evidence reduces to balancing a normalized variance regret against a normalized bias regret.

  3. Difference-in-Differences in the Presence of Unknown Interference

    econ.EM 2025-12 conditional novelty 4.0 of 10

    Under unknown interference, the two-group two-period DiD estimand equals the total effect on the treated minus the spillover effect on the control, and identifies neither separately without additional assumptions.

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