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Finite sample properties for the semiparametric estimation of the intercept of a censored regression model

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  • Marcia M. A. Schafgans

Abstract

Financial support for this paper was provided by a C.A. Anderson Fellowship of the Cowles Foundation. I wish to thank Donald Andrews, Moshe Buchinsky, Oliver Linton, and Peter Robinson for helpful discussions. I also wish to thank three anonymous referees for their comments and suggestions. I am, of course, responsible for any remaining errors. A popular two‐step estimator of the intercept of a censored regression model is compared with consistent asymptotically normal semiparametric alternatives. Using a root mean squared error criterion, the semiparametric estimators perform better for a range of bandwidth parameter choices for a variety of distributions of the errors and regressors. For error distributions that are close to the normal, however, the two‐step parametric estimator performs better.

Suggested Citation

  • Marcia M. A. Schafgans, 2004. "Finite sample properties for the semiparametric estimation of the intercept of a censored regression model," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 58(1), pages 35-56, February.
    • Handle: RePEc:bla:stanee:v:58:y:2004:i:1:p:35-56
    DOI: 10.1046/j.0039-0402.2003.00107.x
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    References listed on IDEAS

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    1. Schafgans, Marcia M.A. & Zinde-Walsh, Victoria, 2002. "On Intercept Estimation In The Sample Selection Model," Econometric Theory, Cambridge University Press, vol. 18(1), pages 40-50, February.
    2. Marcia M. A. Schafgans, 2000. "On Intercept Estimation in the Sample Selection Model," Econometric Society World Congress 2000 Contributed Papers 0730, Econometric Society.
    3. Marcia M Schafgans, 1997. "Semiparametric Estimation of a Sample Selection Model: A Simulation Study," STICERD - Econometrics Paper Series 326, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
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    1. Femenia, Fabienne, 2019. "A Meta-Analysis of the Price and Income Elasticities of Food Demand," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 68(2), June.

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