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Tobit regression model with parameters of increasing dimensions

Author

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  • Ding, Hao
  • Wang, Zhanfeng
  • Wu, Yaohua

Abstract

A Tobit regression model is studied with covariates of increasing dimensions. Asymptotic properties of the parameter estimator, such as consistency and normality, are obtained. Numerical studies including simulation results and an application to a women’s labor supply dataset show that the proposed estimator performs well.

Suggested Citation

  • Ding, Hao & Wang, Zhanfeng & Wu, Yaohua, 2017. "Tobit regression model with parameters of increasing dimensions," Statistics & Probability Letters, Elsevier, vol. 120(C), pages 1-7.
    • Handle: RePEc:eee:stapro:v:120:y:2017:i:c:p:1-7
    DOI: 10.1016/j.spl.2016.09.006
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    References listed on IDEAS

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    1. Powell, James L., 1984. "Least absolute deviations estimation for the censored regression model," Journal of Econometrics, Elsevier, vol. 25(3), pages 303-325, July.
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    4. He, Xuming & Shao, Qi-Man, 2000. "On Parameters of Increasing Dimensions," Journal of Multivariate Analysis, Elsevier, vol. 73(1), pages 120-135, April.
    5. Michelli Barros & Manuel Galea & Manuel González & Víctor Leiva, 2010. "Influence diagnostics in the tobit censored response model," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 19(3), pages 379-397, August.
    6. Liu, Xianhui & Wang, Zhanfeng & Wu, Yaohua, 2013. "Group variable selection and estimation in the tobit censored response model," Computational Statistics & Data Analysis, Elsevier, vol. 60(C), pages 80-89.
    7. Bai, Z. D. & Wu, Y., 1994. "Limiting Behavior of M-Estimators of Regression Coefficients in High Dimensional Linear Models I. Scale Dependent Case," Journal of Multivariate Analysis, Elsevier, vol. 51(2), pages 211-239, November.
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