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Quarterly Journal of Economics Vol. 140 No. 3 2025

Structural Estimation Under Misspecification: Theory and Implications for Practice

Isaiah Andrews1; Nano Barahona2; Matthew Gentzkow3; Ashesh Rambachan4; Jesse M. Shapiro5

1 Massachusetts Institute of Technology and National Bureau of Economic Research , · 2 University of California, Berkeley, and National Bureau of Economic Research · 3 Stanford University and National Bureau of Economic Research · 4 Massachusetts Institute of Technology · 5 Harvard University and National Bureau of Economic Research

Abstract

A researcher can use a tightly parameterized structural model to obtain internally consistent estimates of a wide range of economically interesting targets. We ask how reliable these estimates are when the researcher’s model may be misspecified. We focus on the case of multivariate, potentially nonlinear models where the causal variable of interest is endogenous. Reliable estimates require that the researcher’s model is flexible enough to describe the effects of the endogenous variable approximately correctly. Reliable estimates do not require that the researcher has correctly specified the role of the exogenous controls in the model. However, if the role of the controls is misspecified, reliable estimates require a property we call strong exclusion. Strong exclusion depends on having sufficiently many instruments that are unrelated to the controls. We discuss how practitioners can achieve strong exclusion, and illustrate our findings with an application to a differentiated goods model of demand for beer.

DOI
10.1093/qje/qjaf018
Volume
140
Issue
3
Pages
1801-1855
Language
en
Sources
bibtex:phds-export.bib crossref

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