Testing Productivity Change, Frontier Shift, and Efficiency Change

Research output: Working paperResearch

Abstract

Inference about productivity change over time based on data envelopment (DEA) has focused primarily on the Malmquist index and is based on asymptotic properties of the index. In this paper we propose a novel set of significance tests for DEA based productivity change measures based on permutations and accounting for the inherent correlations when panel data are observed. The tests are easily implementable and give exact significance probabilities as they are not based on asymptotic properties. Tests are formulated both for the geometric means of the Malmquist index, and also of its components, i.e. the frontier shift index and the efficiency change index, which together enable analysis of not only the presence of differences, but also gives an indication of whether the productivity change is due to shifts in the frontiers and/or changes in the efficiency distributions. Simulation results show the power of, and suggest how to interpret the results of, the proposed tests. Finally, the tests are illustrated using a data set from the literature.
Original languageEnglish
Place of PublicationFrederiksberg
PublisherKøbenhavns Universitet
Number of pages23
Publication statusPublished - Jun 2018
SeriesIFRO Working Paper
Number2018/7

Bibliographical note

CBS Library does not have access to the material

Keywords

  • Malmquist index
  • Frontier shift
  • Efficiency change
  • Data Envelopment Analysis (DEA)
  • Panel data
  • Permutation tests
  • Inference

Cite this

Asmild, M., Kronborg, D., & Rønn-Nielsen, A. (2018). Testing Productivity Change, Frontier Shift, and Efficiency Change. Frederiksberg: Københavns Universitet. IFRO Working Paper, No. 2018/7
Asmild, Mette ; Kronborg, Dorte ; Rønn-Nielsen, Anders . / Testing Productivity Change, Frontier Shift, and Efficiency Change. Frederiksberg : Københavns Universitet, 2018. (IFRO Working Paper; No. 2018/7).
@techreport{5dea352686b9424e9d5f76bbd9d8c08a,
title = "Testing Productivity Change, Frontier Shift, and Efficiency Change",
abstract = "Inference about productivity change over time based on data envelopment (DEA) has focused primarily on the Malmquist index and is based on asymptotic properties of the index. In this paper we propose a novel set of significance tests for DEA based productivity change measures based on permutations and accounting for the inherent correlations when panel data are observed. The tests are easily implementable and give exact significance probabilities as they are not based on asymptotic properties. Tests are formulated both for the geometric means of the Malmquist index, and also of its components, i.e. the frontier shift index and the efficiency change index, which together enable analysis of not only the presence of differences, but also gives an indication of whether the productivity change is due to shifts in the frontiers and/or changes in the efficiency distributions. Simulation results show the power of, and suggest how to interpret the results of, the proposed tests. Finally, the tests are illustrated using a data set from the literature.",
keywords = "Malmquist index, Frontier shift, Efficiency change, Data Envelopment Analysis (DEA), Panel data, Permutation tests, Inference, Malmquist index, Frontier shift, Efficiency change, Data Envelopment Analysis (DEA), Panel data, Permutation tests, Inference",
author = "Mette Asmild and Dorte Kronborg and Anders R{\o}nn-Nielsen",
note = "CBS Library does not have access to the material",
year = "2018",
month = "6",
language = "English",
publisher = "K{\o}benhavns Universitet",
address = "Denmark",
type = "WorkingPaper",
institution = "K{\o}benhavns Universitet",

}

Testing Productivity Change, Frontier Shift, and Efficiency Change. / Asmild, Mette; Kronborg, Dorte; Rønn-Nielsen, Anders .

Frederiksberg : Københavns Universitet, 2018.

Research output: Working paperResearch

TY - UNPB

T1 - Testing Productivity Change, Frontier Shift, and Efficiency Change

AU - Asmild, Mette

AU - Kronborg, Dorte

AU - Rønn-Nielsen, Anders

N1 - CBS Library does not have access to the material

PY - 2018/6

Y1 - 2018/6

N2 - Inference about productivity change over time based on data envelopment (DEA) has focused primarily on the Malmquist index and is based on asymptotic properties of the index. In this paper we propose a novel set of significance tests for DEA based productivity change measures based on permutations and accounting for the inherent correlations when panel data are observed. The tests are easily implementable and give exact significance probabilities as they are not based on asymptotic properties. Tests are formulated both for the geometric means of the Malmquist index, and also of its components, i.e. the frontier shift index and the efficiency change index, which together enable analysis of not only the presence of differences, but also gives an indication of whether the productivity change is due to shifts in the frontiers and/or changes in the efficiency distributions. Simulation results show the power of, and suggest how to interpret the results of, the proposed tests. Finally, the tests are illustrated using a data set from the literature.

AB - Inference about productivity change over time based on data envelopment (DEA) has focused primarily on the Malmquist index and is based on asymptotic properties of the index. In this paper we propose a novel set of significance tests for DEA based productivity change measures based on permutations and accounting for the inherent correlations when panel data are observed. The tests are easily implementable and give exact significance probabilities as they are not based on asymptotic properties. Tests are formulated both for the geometric means of the Malmquist index, and also of its components, i.e. the frontier shift index and the efficiency change index, which together enable analysis of not only the presence of differences, but also gives an indication of whether the productivity change is due to shifts in the frontiers and/or changes in the efficiency distributions. Simulation results show the power of, and suggest how to interpret the results of, the proposed tests. Finally, the tests are illustrated using a data set from the literature.

KW - Malmquist index

KW - Frontier shift

KW - Efficiency change

KW - Data Envelopment Analysis (DEA)

KW - Panel data

KW - Permutation tests

KW - Inference

KW - Malmquist index

KW - Frontier shift

KW - Efficiency change

KW - Data Envelopment Analysis (DEA)

KW - Panel data

KW - Permutation tests

KW - Inference

M3 - Working paper

BT - Testing Productivity Change, Frontier Shift, and Efficiency Change

PB - Københavns Universitet

CY - Frederiksberg

ER -