A Small-Sample Estimator for the Sample-Selection Model

Econometric Reviews

Volumn 23, Issue 1, 2004, Pages 71-91

  Golan, Amos ^a   Moretti, Enrico ^b   Perloff, Jeffrey M ^c  

^a AMERICAN UNIVERSITY   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

^c UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Maximum entropy; Monte Carlo experiments; Sample selection

Indexed keywords

EID: 1642314309     PISSN: 07474938     EISSN: None     Source Type: Journal    
DOI: 10.1081/ETC-120028837     Document Type: Review

References (33)

1. Ahn, H., Powell, J. L. (1993). Semiparametric estimation of censored selection models with a nonparametric selection mechanism. J. Econometrics 58:3-29.
2. Chen, S. (1999). Distribution-free estimation of the random coefficient dummy endogenous variable model. J. Econometrics 91:171-199.
3. Cosslett, S. R. (1981). Distribution-free maximum likelihood estimator of the binary choice model. Econometrica 51:765-782.
4. Csiszár, I. (1991). Why least squares and maximum entropy? An axiomatic approach to inference for linear inverse problems. Ann. Statist. 19:2032-2066.
5. Golan, A., Judge, G. (1996). A Maximum Entropy Approach to Empirical Likelihood Estimation and Inference. University of California, Berkeley. Working paper.
6. Golan, A., Judge, G., Miller, D. (1996). Maximum Entropy Econometrics: Robust Estimation with Limited Data. New York: John Wiley & Sons.
7. Golan, A., Judge, G., Perloff, J. M. (1997). Recovering information from censored and ordered multinomial response data. J. Econ. 79:23-51.
8. Golan, A., Gzyl, H. (2002). A generalized maxentropic inversion procedure for noisy data. Appl. Math. Comput. 127:249-260.
9. Golan, A., Perloff, J. M., Shen, E. Z. (2001). Estimating a demand system with nonnegativity constraints: mexican meat demand. Rev. Econ. Statist. 83: 541-550.
10. Han, A. K. (1987). Non-parametric analysis of a generalized regression model: The maximum rank correlation estimator. J. Econometrics 35:303-316.
11. Hartman, R. S. (1991). A Monte Carlo analysis of alternative estimators in models involving selectivity. J. Bus. Econ. Statist. 9:41-49.
12. Hay, J., Leu, R., Rohrer, P. (1987). Ordinary least squares and sample-selection models of health-care demand. J. Bus. Econ. Statist. 5:499-506.
13. Heckman, J. J. (1979). Sample selection bias as a specification error. Econometrica 47:153-161.
14. Jaynes, E. T. (1957a). Information theory and statistical mechanics. Phys. Rev. 106:620-630.
15. Jaynes, E. T. (1957b). Information theory and statistical mechanics II. Phys. Rev. 108:171-190.
16. Jaynes, E. T. (1984). Prior information and ambiguity in inverse problems. In: McLaughin, D. W., ed. Inverse Problems. Vol. 14. Providence, Rhode Island: American Mathematical Society, pp. 151-166.
17. Kullback, J. (1959). Information Theory and Statistics. New York: John Wiley & Sons.
18. Leung, S. F., Yu, S. (1996). On the choice between sample selection and two-part models. J. Econometrics 72:197-229.
19. Levine, R. D. (1980). An information theoretical approach to inversion problems. J. Phys. 13:91-108.
20. Maddala, G. S. (1983). Limited-Dependent and Qualitative Variables in Econometrics. Cambridge: Cambridge University Press.
21. Manning, W., Duan, N., Rogers, W. (1987). Monte Carlo evidence on the choice between sample selection and two-part models. J. Econometrics 35:59-82.
22. Manski, C. F. (1975). Maximum score estimation of the stochastic utility model of choice. J. Econometrics 3:205-228.
23. Manski, C. F. (1985). Semiparametric analysis of discrete response: Asymptotic properties of the maximum score estimator. J. Econometrics 27:313-333.
24. Mittelhammer, R., Cardell, S. (1996). On the Consistency and Asymptotic Normality of the Data Constrained GME Estimator of the GML. Washington State University, Pullman, WA. Working paper.
25. Nawata, K., Nagase, N. (1996). Estimation of Sample Selection Bias Models. Econometric Rev. 15:387-400.
26. Owen, A. B. (1990). Empirical likelihood ratio confidence regions. Ann. Statist. 18:90-120.
27. Owen, A. B. (1991). Empirical likelihood for linear models. Ann. Statist. 19: 1725-1745.
28. Powell, J. L., Stoker, T. M. (1996). Optimal bandwidth choice for choice for density-weighted averages. J. Econometrics 75:291-316.
29. Qin, J., Lawless, J. (1994). Empirical likelihood and general estimating equations. Ann. Statist. 22:300-325.
30. Shannon, C. E. (1948). A mathematical theory of communication. Bell Syst. Tech. J. 27:379-423.
31. Shore, J. E., Johnson, R. W. (1980). Axiomatic derivation of the principle of maximum entropy and the principle of minimum cross-entropy. IEEE Trans. Inf. Theory IT-26: 26-37.
32. Silverman, B. W. (1986). Density Estimation for Statistics and Data Analysis. Chapman and Hall.
33. Skilling, J. (1989). The axioms of maximum entropy. In: Skilling, J., ed. Maximum Entropy and Bayesian Methods in Science and Engineering. Dordrecht: Kluwer Academic, pp. 173-187.