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Semiparametic Nonlinear Least-Squares Estimation of Truncated Regression Models

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  • Lee, Lung-Fei

Abstract

This article provides a semiparametric method for the estimation of truncated regression models where the disturbances are independent of the regressors before truncation. This independence property provides useful information on model identification and estimation. Our estimate is shown to be null-consistent and asymptotically normal. A consistent estimate of the asymptotic covariance matrix of the estimator is provided. Monte Carlo experiments are performed to investigate some finite sample properties of the estimator.

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  • Lee, Lung-Fei, 1992. "Semiparametic Nonlinear Least-Squares Estimation of Truncated Regression Models," Econometric Theory, Cambridge University Press, vol. 8(01), pages 52-94, March.
  • Handle: RePEc:cup:etheor:v:8:y:1992:i:01:p:52-94_01
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    Cited by:

    1. Chen, Songnian & Zhou, Xianbo, 2011. "Semiparametric estimation of a bivariate Tobit model," Journal of Econometrics, Elsevier, vol. 165(2), pages 266-274.
    2. Honore, Bo E. & Kyriazidou, Ekaterini & Udry, Christopher, 1997. "Estimation of Type 3 Tobit models using symmetric trimming and pairwise comparisons," Journal of Econometrics, Elsevier, vol. 76(1-2), pages 107-128.
    3. Lee, Lung-fei, 1995. "Semiparametric maximum likelihood estimation of polychotomous and sequential choice models," Journal of Econometrics, Elsevier, vol. 65(2), pages 381-428, February.
    4. Chen, Songnian, 1997. "Semiparametric estimation of the Type-3 Tobit model," Journal of Econometrics, Elsevier, vol. 80(1), pages 1-34, September.
    5. Chen, Songnian & Zhou, Xianbo, 2012. "Semiparametric estimation of a truncated regression model," Journal of Econometrics, Elsevier, vol. 167(2), pages 297-304.

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