Nonparametric Identification of Differentiated Products Demand Using Micro Data

Steven Berry () and Philip Haile

Papers from arXiv.org

Abstract: We examine identification of differentiated products demand when one has "micro data" linking individual consumers' characteristics and choices. Our model nests standard specifications featuring rich observed and unobserved consumer heterogeneity as well as product/market-level unobservables that introduce the problem of econometric endogeneity. Previous work establishes identification of such models using market-level data and instruments for all prices and quantities. Micro data provides a panel structure that facilitates richer demand specifications and reduces requirements on both the number and types of instrumental variables. We address identification of demand in the standard case in which non-price product characteristics are assumed exogenous, but also cover identification of demand elasticities and other key features when product characteristics are endogenous. We discuss implications of these results for applied work.

Date: 2022-04, Revised 2022-04
New Economics Papers: this item is included in nep-com
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Citations: View citations in EconPapers (3)

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Related works:
Journal Article: Nonparametric Identification of Differentiated Products Demand Using Micro Data (2024)
Working Paper: Nonparametric Identification of Differentiated Products Demand Using Micro Data (2023)
Working Paper: Nonparametric Identification of Differentiated Products Demand Using Micro Data (2020)
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