Behavioral Foundations of Nested Stochastic Choice and Nested Logit

40 Pages Posted: 17 Aug 2019 Last revised: 27 Nov 2019

See all articles by Matthew Kovach

Matthew Kovach

Mitchell E. Daniels, Jr School of Business, Purdue University

Gerelt Tserenjigmid

Virginia Tech

Date Written: November 24, 2019

Abstract

We provide the first behavioral characterization of nested logit, a foundational and widely applied model in discrete choice. We take a revealed preference approach to identify the underlying notion of similarity and use it to characterize a non-parametric version of nested logit we call Nested Stochastic Choice(NSC). We characterize NSC with a single axiom that weakens Independence of Irrelevant Alternatives(IIA) based on revealed similarity to allow for the similarity effect. Nested logit is then characterized by one additional axiom that imposes a weak form of menu-independence. We show that a widely applied generalization, cross-nested logit, lacks testable implications.

Keywords: Nested Stochastic Choice, Luce Model, Nested Logit, IIA, Similarity Effect, Regularity, Revealed Similarity

JEL Classification: D01, D81, D9

Suggested Citation

Kovach, Matthew and Tserenjigmid, Gerelt, Behavioral Foundations of Nested Stochastic Choice and Nested Logit (November 24, 2019). Available at SSRN: https://ssrn.com/abstract=3437165 or http://dx.doi.org/10.2139/ssrn.3437165

Matthew Kovach (Contact Author)

Mitchell E. Daniels, Jr School of Business, Purdue University ( email )

403 Mitch Daniels Blvd.
West Lafayette, IN 47907
United States

Gerelt Tserenjigmid

Virginia Tech ( email )

250 Drillfield Drive
Blacksburg, VA 24061
United States

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
136
Abstract Views
650
Rank
417,931
PlumX Metrics