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This paper studies nonparametric identification in market level demand modelsfor differentiated products with heterogeneous consumers. We consider a generalclass of models that allows for the individual specific coefficients to varycontinuously across the population and give conditions under which the densityof these coefficients, and hence also functionals such as welfare measures, isidentified. A key finding is that two leading models, the BLP-model (Berry,Levinsohn, and Pakes, 1995) and the pure characteristics model (Berry andPakes, 2007), require considerably different conditions on the support of theproduct characteristics.

Nonparametric Identification of Random Coefficients in Endogenous and Heterogeneous Aggregate Demand Models