Robust Data-Driven Inference for Density-Weighted Average Derivatives

Matias Cattaneo, Richard Crump and Michael Jansson

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

Abstract: This paper presents a new data-driven bandwidth selector compatible with the small bandwidth asymptotics developed in Cattaneo, Crump, and Jansson (2009) for density-weighted average derivatives. The new bandwidth selector is of the plug-in variety, and is obtained based on a mean squared error expansion of the estimator of interest. An extensive Monte Carlo experiment shows a remarkable improvement in performance when the bandwidth-dependent robust inference procedure proposed by Cattaneo, Crump, and Jansson (2009) is coupled with this new data-driven bandwidth selector. The resulting robust data-driven confidence intervals compare favorably to the alternative procedures available in the literature.

Keywords: Average derivatives; Bandwidth selection; Robust inference; Small bandwidth asymptotics (search for similar items in EconPapers)
JEL-codes: C12 C14 C21 C24 (search for similar items in EconPapers)
Pages: 36
Date: 2009-09-28
New Economics Papers: this item is included in nep-ecm and nep-ets
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Citations: View citations in EconPapers (3)

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Journal Article: Robust Data-Driven Inference for Density-Weighted Average Derivatives (2010)
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Persistent link: https://EconPapers.repec.org/RePEc:aah:create:2009-46

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