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Identifying Heterogeneity in Economic Choice Models

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Author Info
Jeremy T. Fox
Amit Gandhi

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Abstract

We show how to nonparametrically identify the distribution that characterizes heterogeneity among agents in a general class of structural choice models. We introduce an axiom that we term separability and prove that separability of a structural model ensures identification. The main strength of separability is that it makes verifying the identification of nonadditive models a tractable task because it is a condition that is stated directly in terms of the choice behavior of agents in the model. We use separability to prove several new results. We prove the identification of the distribution of random functions and marginal effects in a nonadditive regression model. We also identify the distribution of utility functions in the multinomial choice model. Finally, we extend 2SLS to have random functions in both the first and second stages. This instrumental variables strategy applies equally to multinomial choice models with endogeneity.

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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 15147.

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Date of creation: Jul 2009
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Handle: RePEc:nbr:nberwo:15147

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Find related papers by JEL classification:
C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Semiparametric and Nonparametric Methods
C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models
L0 - Industrial Organization - - General

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This page was last updated on 2009-11-25.

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