Department of Economics and Business Economics

Bootstrapping Kernel-Based Semiparametric Estimators

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  • rp14_25

    Submitted manuscript, 617 KB, PDF document

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.
Original languageEnglish
Place of publicationAarhus
PublisherInstitut for Økonomi, Aarhus Universitet
Number of pages83
Publication statusPublished - 25 Aug 2014
SeriesCREATES Research Papers
Number2014-25

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