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Instrument-free identification and estimation of differentiated products models

By David Byrne, Susumu Imai, Vasilis Sarafidis and Masayuki Hirukawa


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, but does not require instruments for identification. We establish non-parametric 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

Topics: ddc:330
Publisher: Kingston, Ont.: Queen's Economics Dep., Queen's Univ.
Year: 2015
OAI identifier:
Provided by: EconStor

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