Working Paper: NBER ID: w29787
Authors: James J. Heckman; Rodrigo Pinto
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: Causality; Econometrics; Policy Analysis
JEL Codes: C10; C18
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| econometric causal model (C20) | understanding policy impacts (D78) |
| econometric approach (C51) | handling unobservables and structural relationships (C69) |
| econometric model (C51) | analyze social interactions and peer effects (C92) |
| econometric model (C51) | address functional restrictions and covariance information (C51) |