Efficient estimation in conditional single-index regression

Michel Delecroix, Wolfgang Härdle and Marian Hristache

Journal of Multivariate Analysis, 2003, vol. 86, issue 2, 213-226

Abstract: Semiparametric single-index regression involves an unknown finite-dimensional parameter and an unknown (link) function. We consider estimation of the parameter via the pseudo-maximum likelihood method. For this purpose we estimate the conditional density of the response given a candidate index and maximize the obtained likelihood. We show that this technique of adaptation yields an asymptotically efficient estimator: it has minimal variance among all estimators.

Keywords: Single-index; model; Pseudo-maximum; likelihood; Semiparametric; efficiency; bound (search for similar items in EconPapers)
Date: 2003
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Citations: View citations in EconPapers (33)

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