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Exploration of model performances in the presence of heterogeneous preferences and random effects utilities awareness

Nikita Gusarov (), Amirreza Talebijamalabad and Iragaël Joly ()
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Nikita Gusarov: GAEL - Laboratoire d'Economie Appliquée de Grenoble - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology - UGA - Université Grenoble Alpes - CNRS - Centre National de la Recherche Scientifique - UGA - Université Grenoble Alpes
Amirreza Talebijamalabad: Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology - UGA - Université Grenoble Alpes
Iragaël Joly: GAEL - Laboratoire d'Economie Appliquée de Grenoble - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology - UGA - Université Grenoble Alpes - CNRS - Centre National de la Recherche Scientifique - UGA - Université Grenoble Alpes

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Abstract: This work is a cross-disciplinary study of econometrics and machine learning (ML) models applied to consumer choice preference modelling. To bridge the interdisciplinary gap, a simulation and theorytesting framework is proposed. It incorporates all essential steps from hypothetical setting generation to the comparison of various performance metrics. The flexibility of the framework in theory-testing and models comparison over economics and statistical indicators is illustrated based on the work of Michaud, Llerena and Joly (2012). Two datasets are generated using the predefined utility functions simulating the presence of homogeneous and heterogeneous individual preferences for alternatives' attributes. Then, three models issued from econometrics and ML disciplines are estimated and compared. The study demonstrates the proposed methodological approach's efficiency, successfully capturing the differences between the models issued from different fields given the homogeneous or heterogeneous consumer preferences.

Keywords: Discrete choice models; Neural network analysis; Performance comparison; Heterogeneous preferences (search for similar items in EconPapers)
Date: 2020-10
New Economics Papers: this item is included in nep-big, nep-cmp, nep-dcm and nep-upt
Note: View the original document on HAL open archive server: https://hal.archives-ouvertes.fr/hal-03019739
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