Nonparametric Identification of Differentiated Products Demand Using Micro Data / Steven T. Berry, Philip A. Haile.

Format:

Book

Author/Creator:

Berry, Steven T.

Contributor:

National Bureau of Economic Research.

Haile, Philip A.

Series:

Working Paper Series (National Bureau of Economic Research) no. w27704.

NBER working paper series no. w27704

Language:

English

Physical Description:

1 online resource: illustrations (black and white);

Place of Publication:

Cambridge, Mass. National Bureau of Economic Research 2020.

Summary:

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.

Notes:

Print version record

August 2020.