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CAUSAL ANALYSIS AFTER HAAVELMO

Published online by Cambridge University Press:  10 June 2014

James Heckman
Affiliation:
The University of Chicago
Rodrigo Pinto*
Affiliation:
The University of Chicago
*
*Address correspondence to Rodrigo Pinto, Department of Economics, The University of Chicago, 1155 E. 60th St., Room 215, Chicago, IL 60637, USA; e-mail: [email protected].

Abstract

Haavelmo’s seminal 1943 and 1944 papers are the first rigorous treatment of causality. In them, he distinguished the definition of causal parameters from their identification. He showed that causal parameters are defined using hypothetical models that assign variation to some of the inputs determining outcomes while holding all other inputs fixed. He thus formalized and made operational Marshall’s (1890) ceteris paribus analysis. We embed Haavelmo’s framework into the recursive framework of Directed Acyclic Graphs (DAGs) commonly used in the literature of causality (Pearl, 2000) and Bayesian nets (Lauritzen, 1996). We compare the analysis of causality based on a methodology inspired by Haavelmo’s ideas with other approaches used in the causal literature of DAGs. We discuss the limitations of methods that solely use the information expressed in DAGs for the identification of economic models. We extend our framework to consider models for simultaneous causality, a central contribution of Haavelmo.

Type
ARTICLES
Copyright
Copyright © Cambridge University Press 2014 

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