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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Article provided by Taylor and Francis Journals in its journal Applied Economics.
Volume (Year): 37 (2005) Issue (Month): 4 (March) Pages: 367-374 Download reference. The following formats are available: HTML
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