Causality and Econometrics
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.
This research was supported in part by NIH grant NICHD R37HD065072. The views expressed in this paper are solely those of the authors and do not necessarily represent those of the funders or the official views of the National Institutes of Health. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.
James J. Heckman, 2008. "Econometric Causality," International Statistical Review, vol 76(1), pages 1-27.