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Uniform confidence bands in deconvolution with unknown error distribution

Kengo Kato and Yuya Sasaki

Journal of Econometrics, 2018, vol. 207, issue 1, 129-161

Abstract: This paper develops a method to construct uniform confidence bands in deconvolution when the error distribution is unknown. Simulation studies demonstrate the performance of the multiplier bootstrap confidence band in the finite sample. We apply our method to the Outer Continental Shelf (OCS) Auction Data and draw confidence bands for the density of common values of mineral rights on oil and gas tracts. We also present an application of our main theoretical result specifically to additive fixed-effect panel data models, and we draw confidence bands for the density of the total factor productivity in a manufacturing industry in Chile.

Keywords: Deconvolution; Measurement error; Multiplier bootstrap; Uniform confidence bands (search for similar items in EconPapers)
JEL-codes: C14 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (26)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:207:y:2018:i:1:p:129-161

DOI: 10.1016/j.jeconom.2018.07.001

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Journal of Econometrics is currently edited by T. Amemiya, A. R. Gallant, J. F. Geweke, C. Hsiao and P. M. Robinson

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