Comparing the Mixed Logit Estimates and True Parameters under Informative and Uninformative Heterogeneity: A Simulated Discrete Choice Experiment

Maksat Jumamyradov (), Benjamin M. Craig, William H. Greene and Murat Munkin

Computational Economics, 2025, vol. 65, issue 6, No 8, 3295-3324

Abstract: Abstract In discrete choice experiments (DCEs), differences between respondents’ preferences may be associated with observable or unobservable factors. Unobservable heterogeneity, related to latent factors associated with the choices of individuals, may be modelled using correlated (i.e. informative heterogeneity) or uncorrelated (i.e. uninformative heterogeneity) individual-specific parameters of a logit model. In this study, we simulated unobservable heterogeneity among DCE respondents and compared the results of the maximum simulated likelihood (MSL) estimation of the mixed logit model when correctly specified and mis-specified. These results show that the MSL estimates are biased and can differ greatly from the true parameters, even when correctly specified. Before estimating a mixed logit model, we highly recommend that choice modellers conduct simulation analyses to assess the potential extent of biases before relying on the MSL estimates, particularly their variances and correlations, and then ultimately determine which model specification produces the least bias.

Keywords: Mixed logit; Unobservable heterogeneity; Maximum Simulated Likelihood (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s10614-024-10637-x

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