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Student-t censored regression model: properties and inference

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Abstract

In statistical analysis, particularly in econometrics, it is usual to consider regression models where the dependent variable is censored (limited). In particular, a censoring scheme to the left of zero is considered here. In this article, an extension of the classical normal censored model is developed by considering independent disturbances with identical Student-t distribution. In the context of maximum likelihood estimation, an expression for the expected information matrix is provided, and an efficient EM-type algorithm for the estimation of the model parameters is developed. In order to know what type of variables affect the income of housewives, the results and methods are applied to a real data set. A brief review on the normal censored regression model or Tobit model is also presented.

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Authors and Affiliations

  1. Departamento de Estadística, Facultad de Matemática, Pontificia Universidad Católica de Chile, Santiago 22, Chile

    Reinaldo B. Arellano-Valle & Karla A. Muñoz-Gajardo

  2. Departamento de Estadística, Facultad de Ciencias Físicas y Matemáticas, Universidad de Concepción, Concepción, Chile

    Luis M. Castro

  3. Research Center in Mathematics, CIDICS, Campus de la Salud, UANL Ave. Carlos Canseco s/n con Ave. Gonzalitos, 64460, Col Mitras Centro Monterrey, NL, México

    Graciela González-Farías

Authors
  1. Reinaldo B. Arellano-Valle
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  2. Luis M. Castro
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  3. Graciela González-Farías
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  4. Karla A. Muñoz-Gajardo
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Corresponding author

Correspondence to Luis M. Castro.

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Arellano-Valle, R.B., Castro, L.M., González-Farías, G. et al. Student-t censored regression model: properties and inference. Stat Methods Appl 21, 453–473 (2012). https://doi.org/10.1007/s10260-012-0199-y

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  • DOI: https://doi.org/10.1007/s10260-012-0199-y

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