Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/282773 
Year of Publication: 
2023
Series/Report no.: 
IZA Discussion Papers No. 16646
Publisher: 
Institute of Labor Economics (IZA), Bonn
Abstract: 
This paper examines the econometric causal model and the interpretation of empirical evidence based on thought experiments that was developed by Ragnar Frisch and Trygve Haavelmo. We compare the econometric causal model with two currently popular causal frameworks: the Neyman-Rubin causal model and the Do-Calculus. The Neyman-Rubin causal model is based on the language of potential outcomes and was largely developed by statisticians. Instead of being based on thought experiments, it takes statistical experiments as its foundation. 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 and applied mathematics. We make the case that economists who uncritically use these frameworks often discard the substantial benefits of the econometric causal model to the detriment of more informative analyses. We illustrate the versatility and capabilities of the econometric framework using causal models developed in economics.
Subjects: 
causal inference
causality
structural equation models
Directed Acyclic Graphs
simultaneous causality
JEL: 
C10
C18
Document Type: 
Working Paper

Files in This Item:
File
Size
726.28 kB





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.