Heterogeneity in general multinomial choice models

Ingrid Mauerer () and Gerhard Tutz ()
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Ingrid Mauerer: University of Málaga
Gerhard Tutz: LMU Munich

Statistical Methods & Applications, 2023, vol. 32, issue 1, No 6, 129-148

Abstract: Abstract Different voters behave differently at the polls, different students make different university choices, or different countries choose different health care systems. Many research questions important to social scientists concern choice behavior, which involves dealing with nominal dependent variables. Drawing on the principle of maximum random utility, we propose applying a flexible and general heterogeneous multinomial logit model to study differences in choice behavior. The model systematically accounts for heterogeneity that classical models do not capture, indicates the strength of heterogeneity, and permits examining which explanatory variables cause heterogeneity. As the proposed approach allows incorporating theoretical expectations about heterogeneity into the analysis of nominal dependent variables, it can be applied to a wide range of research problems. Our empirical example uses individual-level survey data to demonstrate the benefits of the model in studying heterogeneity in electoral decisions.

Keywords: Categorical dependent variable; Heterogeneity; Multinomial logit model; Discrete choice analysis; Random utility maximization; Electoral decisions (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10260-022-00642-5

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