Nonparametric identification of random coefficients in aggregate demand models for differentiated products

Fabian Dunker, Stefan Hoderlein and Hiroaki Kaido

The Econometrics Journal, 2023, vol. 26, issue 2, 279-306

Abstract: SummaryThis paper studies nonparametric identification in market-level demand models for differentiated products with heterogeneous consumers. We consider a general class of models that allows for the individual-specific coefficients to vary continuously across the population and give conditions under which the density of these coefficients, and hence also functionals such as the fractions of individuals who benefit from a counterfactual intervention, is identified.

Keywords: Random coefficients; aggregate demand; nonparametric identification (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:oup:emjrnl:v:26:y:2023:i:2:p:279-306.

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