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Nonparametric Identification of Differentiated Products Demand Using Micro Data

Steven Berry () and Philip Haile

No 27704, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: A recent literature considers the identification of heterogeneous demand and supply models via "quasi-experimental'' variation, as from instrumental variables. In this paper we establish nonparametric identification of differentiated products demand when one has "micro data'' linking characteristics of individual consumers to their choices. Micro data provide a panel structure allowing one to exploit variation across consumers within each market, where latent demand shocks are fixed. This facilitates richer demand specifications while substantially softening the reliance on instrumental variables, reducing both the number and types of instruments required. Our results require neither the structure of a "special regressor'' nor a "full support'' assumption on consumer-level observables.

JEL-codes: C14 C26 C3 D12 L0 (search for similar items in EconPapers)
Date: 2020-08
New Economics Papers: this item is included in nep-com
Note: IO
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Citations: View citations in EconPapers (9)

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Related works:
Journal Article: Nonparametric Identification of Differentiated Products Demand Using Micro Data (2024) Downloads
Working Paper: Nonparametric Identification of Differentiated Products Demand Using Micro Data (2023) Downloads
Working Paper: Nonparametric Identification of Differentiated Products Demand Using Micro Data (2022) Downloads
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