randregret: A command for fitting Random Regret Minimization Models

Álvaro A. Gutiérrez Vargas, Michel Meulders and Martina Vandebroek
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Álvaro A. Gutiérrez Vargas: Centre for Research Operation and Statistics (ORSTAT), KU Leuven, Belgium
Michel Meulders: Centre for Research Operation and Statistics (ORSTAT), KU Leuven, Belgium
Martina Vandebroek: Centre for Research Operation and Statistics (ORSTAT), KU Leuven, Belgium

London Stata Conference 2020 from Stata Users Group

Abstract: In this article, we describe the randregret command which implements a variety of Random Regret Minimization (RRM) models. The command allows the user to apply the classic RRM model (Chorus, 2010), the Generalized RRM model (Chorus, 2014), and also the mu-RRM and Pure RRM models (Van Cranenburgh, Guevara and Chorus, 2015). 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 score functions. It also offers likelihood ratio tests which can be used to assess the relevance of a given model specification. Finally, predicted probabilities from each model can be easily computed using the randregretpred postestimation command.

Date: 2020-09-11
New Economics Papers: this item is included in nep-dcm
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Persistent link: https://EconPapers.repec.org/RePEc:boc:usug20:13

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