randregret: A command for fitting random regret minimization models using Stata

Alvaro Gutierrez Vargas, Michel Meulders and Martina Vandebroek

No 664773, Working Papers of Department of Decision Sciences and Information Management, Leuven from KU Leuven, Faculty of Economics and Business (FEB), Department of Decision Sciences and Information Management, Leuven

Abstract: In this article, we describe the randregret command, which imple-ments a variety of Random Regret Minimization (RRM) models. The command allows the user to apply the classic RRM model introduced in Chorus (2010, Eu-ropean Journal of Transport and Infrastructure Research 10: 181-196), the Gener-alized RRM model introduced in Chorus (2014, Transportation Research Part B: Methodological 68: 224-238), and also the µRRM and Pure RRM models, both introduced in van Cranenburgh et al. (2015, Transportation Research Part A: Pol-icy and Practice 74: 91-109). We illustrate the usage of the randregret command using stated choice data on route preferences. The command offers robust and cluster standard error correction using analytical expressions of the scores func-tions. It also offers likelihood ratio tests that can be used to assess the relevance of a given model speciï¬cation. Finally, users can obtain the predicted probabilities from each model using the randregretpred command.

Keywords: randregret; randregret pure; randregretpred; discrete choice models; semi-compensatory behavior; random utility maximization; random regret mini-mization (search for similar items in EconPapers)
Date: 2021-09-01
New Economics Papers: this item is included in nep-dcm and nep-upt
Note: paper number KBI_2006
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