Numerical Comparison of the Asymptotic Efficiency of the Semiparametric Estimators of the Sample Selection Model

• 영문명: Numerical Comparison of the Asymptotic Efficiency of the Semiparametric Estimators of the Sample Selection Model
• 발행기관: 인하대학교 산업경제연구소
• 저자명: 이상원
• 간행물 정보: 『경상논집』경상논집 제13집 제1호, 163~190쪽, 전체 28쪽
• 주제분류: 경제경영 > 경제학
• 파일형태: PDF
• 발행일자: 1999.04.01

영문 초록

In this paper, efficiency of the estimators of the simultaneous limited dependent variable model of binary choice and censored regression is investigated. Considering the non-robustness of the parametric estimators to the distributional specification of the model, efficiencies of both the parametric Gaussian MLE and three semiparametric estimators are compared each other. Efficiency comparison is carried out by comparing the asymptotic efficiency(asymptotic variances or asymptotic MSE) of these estimators. Based upon the specific designs of the model and the distributional assumptions, the comparison is done through the numerical evaluation of the asymptotic efficiencies of the estimators.

목차

1. Introduction

2. Asymptotic efficiency of the estimators of the sample selection model

3. Design of experiments

4. The results

5. Conclusion

Tables

Appendix

References

Abstract