Limit Theorems for Estimating the Parameters of Differentiated Product Demand Systems

Steven Berry (), Oliver Linton and Ariel Pakes

STICERD - Econometrics Paper Series from Suntory and Toyota International Centres for Economics and Related Disciplines, LSE

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.

Keywords: Choice models; Method of Moments; Multinominal; Random Coefficients; Vertical Model (search for similar items in EconPapers)
Date: 2000-07
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Related works:
Journal Article: Limit Theorems for Estimating the Parameters of Differentiated Product Demand Systems (2004)
Working Paper: Limit Theorems for Estimating the Parameters of Differentiated Product Demand Systems (2002)
Working Paper: Limit Theorems for Estimating the Parameters of Differentiated Product Demand Systems (2002)
Working Paper: Limit theorems for estimating the parameters of differentiated product demand systems (2000)
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Persistent link: https://EconPapers.repec.org/RePEc:cep:stiecm:400

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