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Inference on semiparametric models with discrete regressors

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  • Delgado, Miguel A.
  • Mora, Juan

Abstract

We study statistical properties of coefficient estimates of the partially linear regression model when some or all regressors, in the unknown part of the model, are discrete. The method does not require smoothing in the discrete variables. Unlike when there are continuous regressors. when all regressors are discrete independence between regressors and regression errors is not required. We also give some guidance on how to implement the estimate when there are both continuous and discrete regressors in the unknown part of the model. Weights employed in this paper seem straightforwardly applicable to other semiparametric problems.

Suggested Citation

  • Delgado, Miguel A. & Mora, Juan, 1993. "Inference on semiparametric models with discrete regressors," DES - Working Papers. Statistics and Econometrics. WS 3700, Universidad Carlos III de Madrid. Departamento de Estadística.
    • Handle: RePEc:cte:wsrepe:3700
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    References listed on IDEAS

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    1. Newey, Whitney K, 1990. "Efficient Instrumental Variables Estimation of Nonlinear Models," Econometrica, Econometric Society, vol. 58(4), pages 809-837, July.
    2. Chamberlain, Gary, 1992. "Efficiency Bounds for Semiparametric Regression," Econometrica, Econometric Society, vol. 60(3), pages 567-596, May.
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    Keywords

    Semiparametric partially linear model;

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