IDEAS home Printed from https://ideas.repec.org/a/oup/emjrnl/v27y2024i3pc1-c61..html
   My bibliography  Save this article

Causal models for longitudinal and panel data: a survey

Author

Listed:
  • Dmitry Arkhangelsky
  • Guido Imbens

Abstract

SummaryIn this survey we discuss the recent causal panel data literature. This recent literature has focused on credibly estimating causal effects of binary interventions in settings with longitudinal data, emphasising practical advice for empirical researchers. It pays particular attention to heterogeneity in the causal effects, often in situations where few units are treated and with particular structures on the assignment pattern. The literature has extended earlier work on difference-in-differences or two-way fixed effect estimators. It has more generally incorporated factor models or interactive fixed effects. It has also developed novel methods using synthetic control approaches.

Suggested Citation

  • Dmitry Arkhangelsky & Guido Imbens, 2024. "Causal models for longitudinal and panel data: a survey," The Econometrics Journal, Royal Economic Society, vol. 27(3), pages 1-61.
  • Handle: RePEc:oup:emjrnl:v:27:y:2024:i:3:p:c1-c61.
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1093/ectj/utae014
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:oup:emjrnl:v:27:y:2024:i:3:p:c1-c61.. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Oxford University Press (email available below). General contact details of provider: https://edirc.repec.org/data/resssea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.