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Semiparametric Least Squares (SLS) and Weighted SLS Estimation of Single-Index Models

Ichimura, Hidehiko
1991-12
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https://hdl.handle.net/11299/55563
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Semiparametric Least Squares (SLS) and Weighted SLS Estimation of Single-Index Models

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1991-12

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Center for Economic Research, Department of Economics, University of Minnesota

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Working Paper

Abstract

For the class of single-index models, I construct a semiparametric estimator of coefficients up to a multiplicative constant that exhibits 1/ Vn-consistency and asymptotic normality. This class of models includes censored and truncated Tobit models, binary choice models, and duration models with unobserved individual heterogeneity and random censoring. I also investigate a weighting scheme that achieves the semi parametric efficiency bound.

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Center for Economic Research Discussion Papers

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Discussion Paper
264

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Ichimura, H., (1991), "Semiparametric Least Squares (SLS) and Weighted SLS Estimation of Single-Index Models", Discussion Paper No. 264, Center for Economic Research, Department of Economics, University of Minnesota.

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Ichimura, Hidehiko. (1991). Semiparametric Least Squares (SLS) and Weighted SLS Estimation of Single-Index Models. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/55563.

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