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Nonparametric identification of endogenous and heterogeneous aggregate demand models: complements, bundles and the market level

Authors: Fabian Dunker , Stefan Hoderlein and Hiroaki Kaido
Date: 19 May 2014
Type: cemmap Working Paper, CWP23/14
DOI: 10.1920/wp.cem.2014.2314

Abstract

This paper studies nonparametric identi fication in market level demand models for di fferentiated products. We generalize common models by allowing for the distribution of heterogeneity parameters (random coefficients) to have a nonparametric distribution across the population and give conditions under which the density of the random coefficients is identi fied. 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) an integral transform (Radon transform) that maps the random coefficient density to the aggregate demand. This feature is shown to be common across a wide class of models, and we illustrate this by studying leading demand models. Our examples include demand models based on the multinomial choice (Berry, Levinsohn, Pakes, 1995), the choice of bundles of goods that can be substitutes or complements, and the choice of goods consumed in multiple units.

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New version:
Fabian Dunker, Stefan Hoderlein and Hiroaki Kaido February 2017, Nonparametric identification of random coefficients in endogenous and heterogeneous aggregate demand models, cemmap Working Paper, CWP11/17, The IFS
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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