Fitting mixed random regret minimization models using maximum simulated likelihood

Ziyue Zhu, Álvaro A. Gutiérrez-Vargas () and Martina Vandebroek ()
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Álvaro A. Gutiérrez-Vargas: KU Leuven
Martina Vandebroek: KU Leuven

Stata Journal, 2024, vol. 24, issue 2, 250-272

Abstract: In this article, we describe the mixrandregret command, which ex- tends the randregret command introduced in Gutiérrez-Vargas, Meulders, and Vandebroek (2021, Stata Journal 21: 626–658) by allowing random coefficients in random regret minimization models. The newly developed mixrandregret com- mand allows the user to specify a combination of fixed and random coefficients in the regret function of the classical random regret minimization model introduced in Chorus (2010, European Journal of Transport and Infrastructure Research 10: 181–196). In addition, the user can specify normal and lognormal distributions for the random coefficients using the appropriate command’s options. The models are fit by maximum simulated likelihood estimation using numerical integration to approximate the choice probabilities.

Keywords: mixrandregret; mixrpred; mixrbeta; discrete choice models; random regret model; logit model; random coefficients (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1177/1536867X241257802

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