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Nonparametric identification of random coefficients in endogenous and heterogeneous aggregate demand models

Authors: Fabian Dunker , Stefan Hoderlein and Hiroaki Kaido
Date: 22 February 2017
Type: cemmap Working Paper, CWP11/17

Abstract

This paper studies nonparametric identi fication in market level demand models for differentiated products with heterogeneous consumers. We consider a general class of models that allows for the individual speci fic coefficients to vary continuously across the population and give conditions under which the density of these coefficients, and hence also functionals such as welfare measures, is identified. Building on earlier work by Berry and Haile (2013), we show that key identifying restrictions are provided by (i) a set of moment conditions generated by instrumental variables together with an inversion of aggregate demand in unobserved product characteristics; and (ii) the variation of the product characteristics across markets that is exogenous to the individual heterogeneity. We further show that two leading models, the BLP-model (Berry, Levinsohn, and Pakes,1995) and the pure characteristics model (Berry and Pakes, 2007), require considerably different conditions on the support of the product characteristics.

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Previous version:
Fabian Dunker, Stefan Hoderlein and Hiroaki Kaido May 2014, Nonparametric identification of endogenous and heterogeneous aggregate demand models: complements, bundles and the market level, cemmap Working Paper, CWP23/14, Institute for Fiscal Studies
Fabian Dunker, Stefan Hoderlein and Hiroaki Kaido September 2015, Nonparametric identification of endogenous and heterogeneous aggregate demand models: complements, bundles and the market level, cemmap Working Paper, CWP51/15, Institute for Fiscal Studies

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