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Abstract

We propose a new methodology for estimating the demand and cost functions of differentiated products models when demand and cost data are available. The method deals with the endogeneity of prices to demand shocks and the endogeneity of outputs to cost shocks, by using variation in market size that does not need to be exogenous, and cost data. We establish nonparametric identification, consistency and asymptotic normality of our estimator. Using Monte-Carlo experiments, we show our method works well in contexts where instruments are correlated with demand and cost shocks, and where commonly-used instrumental variables estimators are biased and numerically unstable.

Publication Type:	Monograph (Discussion Paper)
Additional Information:	This is an updated version of the Discussion Paper "Identification and Estimation of Differentiated Products Models using Cost Data" first published in August 2015. This updated version was first published in February 2020.
Subjects:	H Social Sciences > HB Economic Theory
Departments:	School of Policy & Global Affairs > Economics > Discussion Paper Series

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