Limit Theorems for Estimating the Parameters of Differentiated Product Demand Systems

46 Pages Posted: 21 Jul 2008

See all articles by Steve Berry

Steve Berry

affiliation not provided to SSRN

Oliver B. Linton

University of Cambridge

Ariel Pakes

National Bureau of Economic Research (NBER); Harvard University - Department of Economics

Date Written: July 2000

Abstract

We provide an asymptotic distribution theory for a class of Generalized Method of Moments estimators that arise in the study of differentiated product markets when the number of observations is associated with the number of products within a given market. We allow for three sources of error: the sampling error in estimating market shares, the simulation error in approximating the shares predicted by the model, and the underlying model error. The limiting distribution of the parameter estgimator is normal provided the size of the consumer sample and the number of simulation draws grow at a large enough rate relative to the number of products. The required rates differ for two frequently used demand models, and a small Monte Carlo study shows that the difference in asymptotic properties of the two models are reflected in the models' small sample properties. The differences impact directly on the computational burden of the two models.

JEL Classification: C13, C14

Suggested Citation

Berry, Steve and Linton, Oliver B. and Pakes, Ariel, Limit Theorems for Estimating the Parameters of Differentiated Product Demand Systems (July 2000). LSE STICERD Research Paper No. EM400. Available at SSRN: https://ssrn.com/abstract=1162591

Steve Berry (Contact Author)

affiliation not provided to SSRN

No Address Available

Oliver B. Linton

University of Cambridge ( email )

Faculty of Economics
Cambridge, CB3 9DD
United Kingdom

Ariel Pakes

National Bureau of Economic Research (NBER) ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Harvard University - Department of Economics ( email )

Littauer Center
Room 117
Cambridge, MA 02138
United States
617-495-5320 (Phone)
617-495-8570 (Fax)

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