Bootstrapping Kernel-Based Semiparametric Estimators

Matias Cattaneo and Michael Jansson

CREATES Research Papers from Department of Economics and Business Economics, Aarhus University

Abstract: This paper develops alternative asymptotic results for a large class of two-step semiparametric estimators. The first main result is an asymptotic distribution result for such estimators and differs from those obtained in earlier work on classes of semiparametric two-step estimators by accommodating a non-negligible bias. A noteworthy feature of the assumptions under which the result is obtained is that reliance on a commonly employed stochastic equicontinuity condition is avoided. The second main result shows that the bootstrap provides an automatic method of correcting for the bias even when it is non-negligible.

Keywords: Semiparametric estimation; bootstrapping; asymptotic separability. (search for similar items in EconPapers)
JEL-codes: C14 C15 (search for similar items in EconPapers)
Pages: 83
Date: 2014-07-30
New Economics Papers: this item is included in nep-ecm and nep-ore
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Citations: View citations in EconPapers (4)

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