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

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  • Fabian Dunker
  • Stefan Hoderlein
  • Hiroaki Kaido

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.

Suggested Citation

  • Fabian Dunker & Stefan Hoderlein & Hiroaki Kaido, 2023. "Nonparametric identification of random coefficients in aggregate demand models for differentiated products," The Econometrics Journal, Royal Economic Society, vol. 26(2), pages 279-306.
    • Handle: RePEc:oup:emjrnl:v:26:y:2023:i:2:p:279-306.
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    References listed on IDEAS

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