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

Ichimura, Hidehiko
1991-12

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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.

Suggested citation

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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