The Inverse Product Differentiation Logit Model

55 Pages Posted: 20 Mar 2018 Last revised: 1 Dec 2022

See all articles by Mogens Fosgerau

Mogens Fosgerau

University of Copenhagen

Julien Monardo

University of Bristol

Andre de Palma

University of Cergy-Pontoise - Department of Economics

Date Written: November 29, 2022

Abstract

We introduce the inverse product differentiation logit (IPDL) model, a micro-founded inverse market share model for differentiated products that captures market segmentation according to one or more characteristics. The IPDL model generalizes the nested logit model to allow richer substitution patterns, including complementarity in demand, and can be estimated by linear instrumental variables regression using market-level data. Furthermore, we provide Monte Carlo experiments that compare the IPDL model to the workhorse empirical models of the literature. Lastly, we show the empirical performance of the IPDL model using a well-known dataset on the ready-to-eat cereals market.

Keywords: Demand estimation; Demand invertibility; Differentiated products; Discrete choice; Nested logit; Random utility; Representative consumer

JEL Classification: C26, D11, D12, L

Suggested Citation

Fosgerau, Mogens and Monardo, Julien and De Palma, Andre, The Inverse Product Differentiation Logit Model (November 29, 2022). Available at SSRN: https://ssrn.com/abstract=3141041 or http://dx.doi.org/10.2139/ssrn.3141041

Mogens Fosgerau (Contact Author)

University of Copenhagen ( email )

University of Copenhagen, Building 26
Øster Farimagsgade 5
Copenhagen K., DK-1353
Denmark

Julien Monardo

University of Bristol ( email )

36 Tyndall's Park Road
Bristol, Avon BS8 1TB
United Kingdom

Andre De Palma

University of Cergy-Pontoise - Department of Economics ( email )

Site des Chênes 1
33 boulevard du Port
Cergy-Pontoise, Cédex F-95011
France
33 1 34 25 61 81 (Phone)
33 1 34 25 62 33 (Fax)

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