IDEAS home Printed from https://ideas.repec.org/a/taf/jecmet/v29y2022i4p326-334.html
   My bibliography  Save this article

Pearl before economists: the book of why and empirical economics

Author

Listed:
  • Nick Huntington-Klein

Abstract

Structural Causal Modeling (SCM) is an approach to causal inference closely associated with Judea Pearl and given an accessible instroduction in [Pearl, J., & Mackenzie, D. (2018). The book of why: The new science of cause and effect. Basic Books]. It is highly popular outside of economics, but has seen relatively little application within it. This paper briefly introduces the main concepts of SCM through the lens of whether applied economists are likely to find marginal benefit in these methods beyond standard economic approaches to causal inference. The most promising areas are those where SCM's causal diagrams alone offer significant value: covariate selection, the development of placebo tests, causal discovery, and identification in complex models.

Suggested Citation

  • Nick Huntington-Klein, 2022. "Pearl before economists: the book of why and empirical economics," Journal of Economic Methodology, Taylor & Francis Journals, vol. 29(4), pages 326-334, October.
  • Handle: RePEc:taf:jecmet:v:29:y:2022:i:4:p:326-334
    DOI: 10.1080/1350178X.2022.2088085
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/1350178X.2022.2088085
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/1350178X.2022.2088085?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

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

    More about this item

    Statistics

    Access and download statistics

    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:taf:jecmet:v:29:y:2022:i:4:p:326-334. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/RJEC20 .

    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.