Pompeu Fabra University (UPF)
May 25, 2022, 11:00, Room GC B1 10 (click here for the map)
We develop a nonparametric model of discrete choice from a limited number of choice observations from different individuals. Choice elements have a multiattribute representation from the analyst perspective. However, preferences are not constructed from utility functions. Instead, we regard preferences as strict linear orders over the choice elements, paired with probability distributions that represent inferential uncertainty due to limited observations. While utility distributions are not identifiable from observed choices, the treatment of preferences in our model considerably alleviates the identification concern. Moreover, it allows capturing complex substitution patterns among options without making any specification assumption. We proceed by a robust formulation of heterogeneity and construct a high-dimensional joint distribution over the individual-level preference orders. Finally, an approximation method for the estimation's computational tractability is discussed.
Moha Ghaderi is an Assistant Professor at Pompeu Fabra University and a BSE Affiliated Professor. He obtained his PhD (cum laude) from ESADE in 2017. His doctoral dissertation has received the ESADE best thesis award and the URL Extraordinary Doctoral Dissertation Award, Doctoral Dissertation Award from the European Doctoral Association in Management and Business Administration, and has been named among the top 3 doctoral dissertations for the biennial award by the MCDM International Society. His publications have appeared in several journals, including EJOR, Omega, and Computers & OR, and received Omega best paper award and INFORMS junior researcher best paper award. His research focuses on quantitative methods, marketing analytics, and decision sciences.