Universität Bonn

Department of Economics

Francesca Molinari - Cornell University

"Identification and Inference for Pure Random Coefficients Models with Limited Consideration", together w/ Levon Barseghyan

Abstract

This paper proposes a discrete choice model where decision makers differ both in their preferences as well as in the products they consider -- their consideration sets. The paper shows how to point identify both the preference distribution and the consideration set formation mechanism under a wide range of assumptions and consideration set formation mechanisms, using cross-sectional data on choices and attributes. In particular, we show that point identification can be attained even when consideration depends on preferences as well as on (many of the) product characteristics, without the need of panel data or menu variation. We propose a sieve-likelihood estimator for the nonparametric distribution of preferences and consideration set, and obtain its asymptotic properties. We compare our model with models in the Logit family. We illustrate the properties of our approach and its computational advantages in large scale simulations and an empirical application.

Additional information:

  • Speaker: Francesca Molinari
  • Time: Thursday, 05.12.2024, 14:15 - 15:30
  • Location: Conference Room at IZA (Schaumburg-Lippe-Straße 9)
  • Further links:
  • Organizer: Statistics Group
  • Contact: