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Efficiency of two-step estimators for censored systems of equations: Shonkwiler and Yen reconsidered

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  • Harald Tauchmann

Abstract

This study analyses a parametric estimator for a system of equations with limited dependent variables that was recently proposed. Its performance is compared with those of alternative estimation procedures using Monte Carlo methods. The comparison shows that this new estimator is less efficient for a wide range of parameter regions than multivariate generalizations of the classical Heckman model. This result can be explained by its variance depending on the squared conditional mean of the dependent variables. Additionally, it turns out that within the class of generalized Heckman estimators, rather simple ones display the best performance.

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  • Harald Tauchmann, 2005. "Efficiency of two-step estimators for censored systems of equations: Shonkwiler and Yen reconsidered," Applied Economics, Taylor & Francis Journals, vol. 37(4), pages 367-374.
    • Handle: RePEc:taf:applec:v:37:y:2005:i:4:p:367-374
    DOI: 10.1080/0003684042000306987
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    References listed on IDEAS

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    1. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 31(3), pages 129-137.
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    3. J. Scott Shonkwiler & Steven T. Yen, 1999. "Two-Step Estimation of a Censored System of Equations," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 81(4), pages 972-982.
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    5. Steven Yen & Kamhon Kan & Shew-Jiuan Su, 2002. "Household demand for fats and oils: two-step estimation of a censored demand system," Applied Economics, Taylor & Francis Journals, vol. 34(14), pages 1799-1806.
    6. Heien, Dale & Wessells, Cathy Roheim, 1990. "Demand Systems Estimation with Microdata: A Censored Regression Approach," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(3), pages 365-371, July.
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