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Nadaraya’s Estimates for Large Quantiles and Free Disposal Support Curves Read chapter Read first chapter

2012 | OriginalPaper | Chapter

3. Nonparametric Frontier Estimation from Noisy Data

Authors : Maik Schwarz, Sébastien Van Bellegem, Jean-Pierre Florens

Published in: Exploring Research Frontiers in Contemporary Statistics and Econometrics

Publisher: Physica-Verlag HD

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Abstract

A new nonparametric estimator of production frontiers is defined and studied when the data set of production units is contaminated by measurement error. The measurement error is assumed to be an additive normal random variable on the input variable, but its variance is unknown. The estimator is a modification of the m-frontier, which necessitates the computation of a consistent estimator of the conditional survival function of the input variable given the output variable. In this paper, the identification and the consistency of a new estimator of the survival function is proved in the presence of additive noise with unknown variance. The performance of the estimator is also studied using simulated data.

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previous chapter Production Efficiency versus Ownership: The Case of China
next chapter Estimating Frontier Cost Models Using Extremiles
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Metadata
Title
Nonparametric Frontier Estimation from Noisy Data
Authors
Maik Schwarz
Sébastien Van Bellegem
Jean-Pierre Florens
Copyright Year
2012
Publisher
Physica-Verlag HD
Book
Exploring Research Frontiers in Contemporary Statistics and Econometrics

Print ISBN: 978-3-7908-2348-6

Electronic ISBN: 978-3-7908-2349-3

Copyright Year: 2012

DOI
https://doi.org/10.1007/978-3-7908-2349-3_3

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