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An Introductory Guide to Event Study Models

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  • Douglas L. Miller

Abstract

The event study model is a powerful econometric tool used for the purpose of estimating dynamic treatment effects. One of its most appealing features is that it provides a built-in graphical summary of results, which can reveal rich patterns of behavior. Another value of the picture is the estimated pre-event pseudo-"effects", which provide a type of placebo test. In this essay I aim to provide a framework for a shared understanding of these models. There are several (sometimes subtle) decisions and choices faced by users of these models, and I offer guidance for these decisions.

Suggested Citation

  • Douglas L. Miller, 2023. "An Introductory Guide to Event Study Models," Journal of Economic Perspectives, American Economic Association, vol. 37(2), pages 203-230, Spring.
    • Handle: RePEc:aea:jecper:v:37:y:2023:i:2:p:203-30
    DOI: 10.1257/jep.37.2.203
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    Cited by:

    1. Robert Kaestner, 2023. "A Critique of " The Birth of a Nation : Media and Racial Hate"," Econ Journal Watch, Econ Journal Watch, vol. 20(2), pages 214–233-2, September.
    2. Laura Argys & Thomas Mroz & M. Melinda Pitts, 2023. "Modeling Event Studies with Heterogeneous Treatment Effects," FRB Atlanta Working Paper 2023-11, Federal Reserve Bank of Atlanta.
    3. Matthieu Bunel & Dominique Meurs & Élisabeth Tovar, 2024. "Moving apart: job-driven residential mobility and the gender pay gap Evidence from a large industrial firm," EconomiX Working Papers 2024-6, University of Paris Nanterre, EconomiX.
    4. Hudde, Ansgar & Jacob, Marita, 2022. "There’s More in the Data! Using Month-Specific Information to Estimate Changes Before and After Major Life Events," SocArXiv vueas, Center for Open Science.
    5. Julia Mink, 2023. "Broken Homes and Empty Pantries: French Households Suffer Substantial Loss of Standard Living, Reduce Food Consumption and Lose Weight Following Separation," CRC TR 224 Discussion Paper Series crctr224_2023_469, University of Bonn and University of Mannheim, Germany.

    More about this item

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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