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Nonparametric Identification of Random Coefficients in Endogenous and Heterogeneous Aggregate Demand

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  • Fabian Dunker
  • Stefan Hoderlein
  • Hiroaki Kaido
Abstract
This 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 welfare measures, is identified. Building on earlier work by Berry and Haile (2013), 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) the variation of the product characteristics across markets that is exogenous to the individual heterogeneity. We further show that two leading models, the BLP-model (Berry, Levinsohn, and Pakes, 1995) and the pure characteristics model (Berry and Pakes, 2007), require considerably different conditions on the support of the product characteristics.

Suggested Citation

  • Fabian Dunker & Stefan Hoderlein & Hiroaki Kaido, 2017. "Nonparametric Identification of Random Coefficients in Endogenous and Heterogeneous Aggregate Demand," Courant Research Centre: Poverty, Equity and Growth - Discussion Papers 224, Courant Research Centre PEG.
    • Handle: RePEc:got:gotcrc:224
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    File URL: http://www2.vwl.wiso.uni-goettingen.de/courant-papers/CRC-PEG_DP_224.pdf
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    Cited by:

    1. Wang, Ao, 2021. "A BLP Demand Model of Product-Level Market Shares with Complementarity," The Warwick Economics Research Paper Series (TWERPS) 1351, University of Warwick, Department of Economics.

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