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Semiparametric Estimation of Consumer Demand Systems with Micro Data

Abdoul G. Sam and Yi Zheng

American Journal of Agricultural Economics, 2010, vol. 92, issue 1, 246-257

Abstract: Maximum likelihood and two-step estimators of censored demand systems yield biased and inconsistent parameter estimates when the assumed joint distribution of disturbances is incorrect. This paper proposes a semiparametric estimator that retains the computational advantage of the two-step approach but is immune to distributional misspecification. The key difference between the proposed estimator and the two-step estimator is that the parameters of the binary censoring equations are estimated using a distribution-free single-index model. We implement the proposed estimator using household-level data obtained from the Hainan province in China. specification test lends support to our approach. Copyright 2010, Oxford University Press.

Date: 2010
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American Journal of Agricultural Economics is currently edited by Madhu Khanna, Brian E. Roe, James Vercammen and JunJie Wu

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