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Estimation of generalised regression models by the grouping method

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  • Nawata, K.

Abstract

Nawata [8–10] proposed a new estimator for the standard regression, censored regression, and binary choice models, based on grouping of observations. This paper shows that Nawata's grouping method can be generalised to various types of estimation problems and represents a new class of estimation methods.

Suggested Citation

  • Nawata, K., 1997. "Estimation of generalised regression models by the grouping method," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 43(3), pages 503-510.
    • Handle: RePEc:eee:matcom:v:43:y:1997:i:3:p:503-510
    DOI: 10.1016/S0378-4754(97)00038-4
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    References listed on IDEAS

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    1. Powell, James L, 1986. "Symmetrically Trimmed Least Squares Estimation for Tobit Models," Econometrica, Econometric Society, vol. 54(6), pages 1435-1460, November.
    2. Powell, James L., 1986. "Censored regression quantiles," Journal of Econometrics, Elsevier, vol. 32(1), pages 143-155, June.
    3. Manski, Charles F., 1985. "Semiparametric analysis of discrete response : Asymptotic properties of the maximum score estimator," Journal of Econometrics, Elsevier, vol. 27(3), pages 313-333, March.
    4. Nawata, Kazumitsu, 1990. "Robust estimation based on grouped-adjusted data in censored regression models," Journal of Econometrics, Elsevier, vol. 43(3), pages 337-362, March.
    5. Nawata, Kazumitsu, 1990. "Robust estimation based on grouped-adjusted data in linear regression models," Journal of Econometrics, Elsevier, vol. 43(3), pages 317-336, March.
    6. Manski, Charles F., 1975. "Maximum score estimation of the stochastic utility model of choice," Journal of Econometrics, Elsevier, vol. 3(3), pages 205-228, August.
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