Statistical inference for the Russell measure of technical efficiency

Oleg Badunenko; Pavlo Mozharovskyi

doi:10.1080/01605682.2019.1599778

Statistical inference for the Russell measure of technical efficiency

Oleg Badunenko, Pavlo Mozharovskyi

Université Paris-Saclay

Research output: Contribution to journal › Article › peer-review

116 Downloads (Pure)

Abstract

Data Envelopment Analysis (DEA) has become a popular approach to nonparametric efficiency measurement. The statistical inference using bootstrap methods is readily available for the radial DEA estimator, however it is missing for the Russell measure, the nonradial DEA estimator. We propose a bootstrap based procedure for making statistical inference about the individual Russell measures of technical efficiency. We perform simulations to examine finite sample properties of the proposed estimator. Finally, we present an empirical study using proposed bootstrap procedure.

Original language	English
Number of pages	11
Journal	Journal of the Operational Research Society
Early online date	23 Apr 2019
DOIs	https://doi.org/10.1080/01605682.2019.1599778
Publication status	Early online - 23 Apr 2019

Keywords

Nonradial efficiency
Russell measure
Data envelopment analysis
Frontier Efficiency Models
Statistical inference
Bootstrap

Access to Document

10.1080/01605682.2019.1599778

BADUNENKO_2019_cright_EJOR_Statistical Inference for the Russell Measure of Technical Effciency
This is an Accepted Manuscript of an article published by Taylor & Francis in the Journal of Operational Research Society on 23.04.2019, available online: http://www.tandfonline.com/10.1080/01605682.2019.1599778.
Accepted author manuscript (Post-print), 1.43 MB

https://www.tandfonline.com/doi/full/10.1080/01605682.2019.1599778

Dataset for 'Statistical inference for the Russell measure of technical efficiency'.
Badunenko, O. (Creator) & Mozharovskyi, P. (Creator), Queen's University (Canada), 2011
http://qed.econ.queensu.ca/jae/2011-v26.2/kumbhakar-tsionas/
Dataset

Cite this

@article{ca5c78ea016a49b9a1a35fd8d2d6602f,

title = "Statistical inference for the Russell measure of technical efficiency",

abstract = "Data Envelopment Analysis (DEA) has become a popular approach to nonparametric efficiency measurement. The statistical inference using bootstrap methods is readily available for the radial DEA estimator, however it is missing for the Russell measure, the nonradial DEA estimator. We propose a bootstrap based procedure for making statistical inference about the individual Russell measures of technical efficiency. We perform simulations to examine finite sample properties of the proposed estimator. Finally, we present an empirical study using proposed bootstrap procedure. ",

keywords = "Nonradial efficiency, Russell measure, Data envelopment analysis, Frontier Efficiency Models, Statistical inference, Bootstrap",

author = "Oleg Badunenko and Pavlo Mozharovskyi",

note = "embargo 12 mths This is a post-peer-review, pre-copyedit version of an article published in Journal of the Operational Research Society (JORS). The definitive publisher-authenticated version {"}Statistical Inference for the Russell Measure of Technical Effciency{"}, (2019), DOI: 10.1080/01605682.2019.1599778, is available online at: https://www.tandfonline.com/doi/full/10.1080/01605682.2019.1599778 ",

year = "2019",

month = apr,

day = "23",

doi = "10.1080/01605682.2019.1599778",

language = "English",

journal = "Journal of the Operational Research Society",

issn = "0160-5682",

publisher = "Palgrave Macmillan Ltd.",

}

TY - JOUR

T1 - Statistical inference for the Russell measure of technical efficiency

AU - Badunenko, Oleg

AU - Mozharovskyi, Pavlo

N1 - embargo 12 mths This is a post-peer-review, pre-copyedit version of an article published in Journal of the Operational Research Society (JORS). The definitive publisher-authenticated version "Statistical Inference for the Russell Measure of Technical Effciency", (2019), DOI: 10.1080/01605682.2019.1599778, is available online at: https://www.tandfonline.com/doi/full/10.1080/01605682.2019.1599778

PY - 2019/4/23

Y1 - 2019/4/23

N2 - Data Envelopment Analysis (DEA) has become a popular approach to nonparametric efficiency measurement. The statistical inference using bootstrap methods is readily available for the radial DEA estimator, however it is missing for the Russell measure, the nonradial DEA estimator. We propose a bootstrap based procedure for making statistical inference about the individual Russell measures of technical efficiency. We perform simulations to examine finite sample properties of the proposed estimator. Finally, we present an empirical study using proposed bootstrap procedure.

AB - Data Envelopment Analysis (DEA) has become a popular approach to nonparametric efficiency measurement. The statistical inference using bootstrap methods is readily available for the radial DEA estimator, however it is missing for the Russell measure, the nonradial DEA estimator. We propose a bootstrap based procedure for making statistical inference about the individual Russell measures of technical efficiency. We perform simulations to examine finite sample properties of the proposed estimator. Finally, we present an empirical study using proposed bootstrap procedure.

KW - Nonradial efficiency

KW - Russell measure

KW - Data envelopment analysis

KW - Frontier Efficiency Models

KW - Statistical inference

KW - Bootstrap

U2 - 10.1080/01605682.2019.1599778

DO - 10.1080/01605682.2019.1599778

M3 - Article

SN - 0160-5682

JO - Journal of the Operational Research Society

JF - Journal of the Operational Research Society

ER -

Statistical inference for the Russell measure of technical efficiency

Abstract

Keywords

Access to Document

Fingerprint

Datasets

Dataset for 'Statistical inference for the Russell measure of technical efficiency'.

Cite this