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On Event Study Designs and Distributed-Lag Models: Equivalence, Generalization and Practical Implications
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On Event Study Designs and Distributed-Lag Models: Equivalence, Generalization and Practical Implications

Author

Listed:
  • Schmidheiny, Kurt

    (University of Basel)

  • Siegloch, Sebastian

    (University of Cologne)

Abstract

We discuss important features and pitfalls of panel-data event study designs. We derive the following main results: First, event study designs and distributed-lag models are numerically identical leading to the same parameter estimates after correct reparametrization. Second, binning of effect window endpoints allows identification of dynamic treatment effects even when no never-treated units are present. Third, classic dummy variable event study designs can be naturally generalized to models that account for multiple events of different sign and intensity of the treatment, which are particularly interesting for research in labor economics and public finance.

Suggested Citation

  • Schmidheiny, Kurt & Siegloch, Sebastian, 2019. "On Event Study Designs and Distributed-Lag Models: Equivalence, Generalization and Practical Implications," IZA Discussion Papers 12079, Institute of Labor Economics (IZA).
    • Handle: RePEc:iza:izadps:dp12079
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    More about this item

    Keywords

    applied microeconomics; distributed-lag; event study; credibility revolution;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • H00 - Public Economics - - General - - - General
    • J08 - Labor and Demographic Economics - - General - - - Labor Economics Policies

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