Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/122184
Authors: 
Dunker, Fabian
Hoderlein, Stefan
Kaido, Hiroaki
Year of Publication: 
2014
Series/Report no.: 
Reihe Ökonomie / Economics Series, Institut für Höhere Studien (IHS) 307
Abstract: 
This paper studies nonparametric identification in market level demand models for differentiated 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 identified. 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.
Document Type: 
Working Paper

Files in This Item:
File
Size
662.33 kB





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.