Causality and Econometrics

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

No 15081, IZA Discussion Papers from Institute of Labor Economics (IZA)

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
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Citations: View citations in EconPapers (5)

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Working Paper: Causality and Econometrics (2022)
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