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Structure and Uncertainty in Discrete Choice Models

Published online by Cambridge University Press:  04 January 2017

Curtis S. Signorino
Curtis S. Signorino*
Affiliation:
Department of Political Science, 303 Harkness Hall, University of Rochester, Rochester, NY 14627. e-mail: curt.signorino@rochester.edu
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Abstract

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Social scientists are often confronted with theories in which one or more actors make choices over a discrete set of options. In this article, I generalize a broad class of statistical discrete choice models, with both well-known and new nonstrategic and strategic special cases. I demonstrate how to derive statistical models from theoretical discrete choice models and, in doing so, I address the statistical implications of three sources of uncertainty: agent error, private information about payoffs, and regressor error. For strategic and some nonstrategic choice models, the three types of uncertainty produce different statistical models. In these cases, misspecifying the type of uncertainty leads to biased and inconsistent estimates, and to incorrect inferences based on estimated probabilities.

Information

Type
Research Article
Information
Political Analysis , Volume 11 , Issue 4: Special Issue on Empirical Implications of Theoretical Models , Autumn 2003 , pp. 316 - 344
Copyright
Copyright © Political Methodology Section of the American Political Science Association 2003 

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