Causality and Econometrics

James Heckman and Rodrigo Pinto ()
Additional contact information
Rodrigo Pinto: University of California, Los Angeles

No 15081, IZA Discussion Papers from IZA Network @ LISER

Abstract: This paper examines the econometric causal model for policy analysis developed by the seminal ideas of Ragnar Frisch and Trygve Haavelmo. We compare the econometric causal model with two popular causal frameworks: Neyman-Holland causal model and the do-calculus. The Neyman-Holland causal model is based on the language of potential outcomes and was largely developed by statisticians. The do-calculus, developed by Judea Pearl and co-authors, relies on Directed Acyclic Graphs (DAGs) and is a popular causal framework in computer science. We make the case that economists who uncritically use these approximating frameworks often discard the substantial benefits of the econometric causal model to the detriment of more informative economic policy analyses. We illustrate the versatility and capabilities of the econometric framework using causal models that are frequently studied by economists.

Keywords: policy analysis; econometric models; causality; identification; causal calculus; directed acyclic graphs; simultaneous treatment effects (search for similar items in EconPapers)
JEL-codes: C10 C18 (search for similar items in EconPapers)
Pages: 81 pages
Date: 2022-02
New Economics Papers: this item is included in nep-ecm, nep-hpe and nep-ltv
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
https://docs.iza.org/dp15081.pdf (application/pdf)

Related works:
Working Paper: Causality and Econometrics (2022)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:iza:izadps:dp15081

Access Statistics for this paper

More papers in IZA Discussion Papers from IZA Network @ LISER Contact information at EDIRC.
Bibliographic data for series maintained by Mark Fallak ().