Data-driven Nests in Nested Logit Models

26.05.2025 14:15 – 15:30

INSTITUTE OF ECONOMICS AND ECONOMETRICS SEMINAR

Jointly with: Milena Almagro and Kenneth Lai

Abstract:

Within discrete choice models of random utility, nested logit has been proposed as a parsimonious model that also allows for relatively flexible substitution patterns across products. However, assuming knowledge of the nest structure has proven problematic in some applications. We propose a method that estimates both the nest structure as well as the structural parameters using product share data. We consider empirical settings with longitudinal observations of products across several markets and potential price endogeneity. We develop an estimator to recover the nest structure and the parameters and analyze its statistical properties. We propose an easy-to-implement two-step estimation strategy, where in the first step, we estimate the nesting structure following Bonhomme and Manresa (2015), and in the second step, we estimate the preference parameters conditional on the estimated nest structure of the first step. We showcase the good performance of our method through a Monte Carlo experiment, and we apply it to the U.S. automobile market data.

Lieu

Bâtiment: Uni Mail

Boulevard du Pont-d'Arve 40
1205 Geneva
Room M 3250, 3rd floor

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