Nonparametric and semiparametric estimation with discrete regressors
AbstractThis paper presents and discusses procedures for estimating regression curves when regressors are discrete and applies them to semiparametric inference problems. We show that pointwise root-n-consistency and global consistency of regression curve estimates are achieved without employing any smoothing, even for discrete regressors with unbounded support. These results still hold when smoothers are used, under much weaker conditions than those required with continuous regressors. Such estimates are useful in semiparametric inference problems. We discuss in detail the partially linear regression model and shape-invariant modelling. We also provide some guidance on estimation in semiparametric models where continuous and discrete regressors are present. The paper also includes a Monte Carlo study.
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Nonparametric regression; Semiparametric inference; Discrete regressors; Empirical conditional expectation estimate; Regressograms; Kernels; Nearest neighbours; Partially linear model; Shape-invariant modelling;
Other versions of this item:
- Delgado, Miguel A & Mora, Juan, 1995. "Nonparametric and Semiparametric Estimation with Discrete Regressors," Econometrica, Econometric Society, vol. 63(6), pages 1477-84, November.
- Delgado, Miguel A. & Mora, Juan, . "Nonparametric and Semiparametric Estimation with Discrete Regressors," Open Access publications from Universidad Carlos III de Madrid info:hdl:10016/2421, Universidad Carlos III de Madrid.
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