Limit theorems for estimating the parameters of differentiated product demand systems

Berry, Steve, Linton, Oliver and Pakes, Ariel (2000) Limit theorems for estimating the parameters of differentiated product demand systems. Econometrics; EM/2000/400 (EM/00/400). Suntory and Toyota International Centres for Economics and Related Disciplines, London, UK.

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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 estimator 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.

Item Type:	Monograph (Discussion Paper)
Official URL:	http://sticerd.lse.ac.uk
Additional Information:	© 2000 the authors
Divisions:	Financial Markets Group Economics STICERD
Subjects:	H Social Sciences > HB Economic Theory
JEL classification:	L - Industrial Organization > L1 - Market Structure, Firm Strategy, and Market Performance > L13 - Oligopoly and Other Imperfect Markets C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods: General > C13 - Estimation C - Mathematical and Quantitative Methods > C3 - Econometric Methods: Multiple; Simultaneous Equation Models; Multiple Variables; Endogenous Regressors > C35 - Discrete Regression and Qualitative Choice Models C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods: General > C15 - Statistical Simulation Methods; Monte Carlo Methods; Bootstrap Methods
Date Deposited:	27 Apr 2007
Last Modified:	15 Sep 2023 22:47
URI:	http://eprints.lse.ac.uk/id/eprint/2032

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