An application and comparison of some flexible parametric and semiparametric qualitative-response models with heteroskedasticity

International Journal of Systems Science

Volumn 31, Issue 1, 2000, Pages 27-33

  McDonald, James B ^a   Hansen, James V ^a  

^a BRIGHAM YOUNG UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

MATHEMATICAL MODELS; PARAMETER ESTIMATION; PROBABILITY; RANDOM PROCESSES; STATISTICAL METHODS;

QUALITATIVE-RESPONSE MODELS;

DECISION MAKING;

EID: 0033993156     PISSN: 00207721     EISSN: None     Source Type: Journal    
DOI: 10.1080/002077200291424     Document Type: Article

References (18)

1. Amemiya, T., 1981, Qualitative response models: a survey. Journal of Economic Literature, 19, 1482-1536.
2. Dawes, R., 1979, The robust beauty of improper linear models in decision making. American Psychologist, 34, 502-516.
3. Fischer, G., and Nagin, D., 1981, Random versus fixed coefficient quantal choice models. Structural Analysis of Discrete Data with Econometric Applications, edited by C.F. Manski and D. McFadden (Cambridge, Massachusetts: MIT Press).
4. Hardee, W., and Manski, C., 1993, Non-parametric and semi-parametric approaches to discrete response analysis. Journal of Econometrics, 58, 49-70.
5. Hausman, J., and Wise, D., 1978, A conditional probit model for qualitative choice: discrete decisions recognizing interdependence and heterogeneous preferences. Econometrics, 61, 403-426.
6. Horowitz, J., 1992, A smoothed maximum score estimator for the binary response model, Econometrics, 60, 505-531; 1993, Semi-parametric estimation of a work-trip mode choice model. Journal of Econometrics, 61, 49-70.
7. Horowitz, J., 1992, A smoothed maximum score estimator for the binary response model, Econometrics, 60, 505-531; 1993, Semi-parametric estimation of a work-trip mode choice model. Journal of Econometrics, 61, 49-70.
8. Kearns, M., and Vazirani, U., 1994, An Introduction to Computational Learning Theory (Cambridge, Massachusetts: MIT Press).
9. Klein, R., and Spady, R., 1993, An efficient semi-parametric estimator for binary choice models. Econometrica, 61, 387-421.
10. Libby, R., 1981, Accounting and Human Information Processing: Theory and Applications (Englewood Cliffs, New Jersey: Prentice-Hall).
11. Maddala, G., 1983, Limited-Dependent and Qualitative Variables in Econometrics (Cambridge University Press).
12. Manski, C., 1975, Maximum score estimation of the stochastic utility model of choice. Journal of Econometrics, 3, 205-228; 1985, Semi-parametric analysis of discrete response: asymptotic properties of the maximum score estimator. Journal of Econometrics, 27, 313-334.
13. Manski, C., 1975, Maximum score estimation of the stochastic utility model of choice. Journal of Econometrics, 3, 205-228; 1985, Semi-parametric analysis of discrete response: asymptotic properties of the maximum score estimator. Journal of Econometrics, 27, 313-334.
14. Manski, C., and McFadden, D., 1981, Semi-parametric analysis of discrete response: asymptotic properties of the maximum scope estimator, Journal of Econometrics, 27, 103-334.
15. McDonald, J.B., and White, S.B., 1993, A comparison of some robust, adaptive, and partially adaptive estimators of regression models. Econometric Reviews, 12, 103-124.
16. McDonald, J., and Xu, Y., 1995, A generalization of the beta distrubutions with applications. Journal of Econometrics, 66, 133-152.
17. Payne, J., 1994, Task complexity and contingent processing in decision making: An information search and protocol analysis. Organizational Behaviour and Human Performance, 16, 366-387.
18. Valiant, 1985, Learning disfunctions of confunctions. In Proceedings of the 9th International Joint Conference on Artficial Intelligence, 560-566.