The biennial Malmquist productivity change index

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The biennial Malmquist productivity change index. / Pastor, Jesús T.; Asmild, Mette; Lovell, C. A.Knox.

In: Socio-Economic Planning Sciences, Vol. 45, No. 1, 03.2011, p. 10-15.

Research output: Contribution to journal › Journal article › Research › peer-review

Harvard

Pastor, JT, Asmild, M & Lovell, CAK 2011, 'The biennial Malmquist productivity change index', Socio-Economic Planning Sciences, vol. 45, no. 1, pp. 10-15. https://doi.org/10.1016/j.seps.2010.09.001

APA

Pastor, J. T., Asmild, M., & Lovell, C. A. K. (2011). The biennial Malmquist productivity change index. Socio-Economic Planning Sciences, 45(1), 10-15. https://doi.org/10.1016/j.seps.2010.09.001

Vancouver

Pastor JT, Asmild M, Lovell CAK. The biennial Malmquist productivity change index. Socio-Economic Planning Sciences. 2011 Mar;45(1):10-15. https://doi.org/10.1016/j.seps.2010.09.001

Author

Pastor, Jesús T. ; Asmild, Mette ; Lovell, C. A.Knox. / The biennial Malmquist productivity change index. In: Socio-Economic Planning Sciences. 2011 ; Vol. 45, No. 1. pp. 10-15.

Bibtex

@article{bd910023aa9d4c50aa878e47c45f756b,
title = "The biennial Malmquist productivity change index",
abstract = "In this paper we introduce a new Malmquist productivity index that has three attractive features: it avoids linear programming infeasibilities under variable returns to scale, it allows for technical regress, and it does not need to be recomputed when a new time period is added to the data set. The proposed index is compared to both the adjacent Malmquist index and the global Malmquist index in an empirical example, which highlights the drawbacks of the existing indexes compared to the proposed biennial Malmquist index.Our results show that 13% of the observations in the data set may have to be ignored due to infeasibilities when decomposing the adjacent Malmquist index. Using only this reduced data set does at times lead to quite different results than those generated by applying the proposed biennial Malmquist index to the entire data set. The empirical example also shows that productivity change estimated between two time periods using the global Malmquist index change substantially when a third time period is added to the data set, whereas the proposed biennial Malmquist index is immune to this problem.",
keywords = "Infeasibilities, Malmquist productivity indices, Productivity change decompositions, Technical regress",
author = "Pastor, {Jes{\'u}s T.} and Mette Asmild and Lovell, {C. A.Knox}",
year = "2011",
month = mar,
doi = "10.1016/j.seps.2010.09.001",
language = "English",
volume = "45",
pages = "10--15",
journal = "Socio-Economic Planning Sciences",
issn = "0038-0121",
publisher = "Pergamon Press",
number = "1",

}

RIS

TY - JOUR

T1 - The biennial Malmquist productivity change index

AU - Pastor, Jesús T.

AU - Asmild, Mette

AU - Lovell, C. A.Knox

PY - 2011/3

Y1 - 2011/3

N2 - In this paper we introduce a new Malmquist productivity index that has three attractive features: it avoids linear programming infeasibilities under variable returns to scale, it allows for technical regress, and it does not need to be recomputed when a new time period is added to the data set. The proposed index is compared to both the adjacent Malmquist index and the global Malmquist index in an empirical example, which highlights the drawbacks of the existing indexes compared to the proposed biennial Malmquist index.Our results show that 13% of the observations in the data set may have to be ignored due to infeasibilities when decomposing the adjacent Malmquist index. Using only this reduced data set does at times lead to quite different results than those generated by applying the proposed biennial Malmquist index to the entire data set. The empirical example also shows that productivity change estimated between two time periods using the global Malmquist index change substantially when a third time period is added to the data set, whereas the proposed biennial Malmquist index is immune to this problem.

AB - In this paper we introduce a new Malmquist productivity index that has three attractive features: it avoids linear programming infeasibilities under variable returns to scale, it allows for technical regress, and it does not need to be recomputed when a new time period is added to the data set. The proposed index is compared to both the adjacent Malmquist index and the global Malmquist index in an empirical example, which highlights the drawbacks of the existing indexes compared to the proposed biennial Malmquist index.Our results show that 13% of the observations in the data set may have to be ignored due to infeasibilities when decomposing the adjacent Malmquist index. Using only this reduced data set does at times lead to quite different results than those generated by applying the proposed biennial Malmquist index to the entire data set. The empirical example also shows that productivity change estimated between two time periods using the global Malmquist index change substantially when a third time period is added to the data set, whereas the proposed biennial Malmquist index is immune to this problem.

KW - Infeasibilities

KW - Malmquist productivity indices

KW - Productivity change decompositions

KW - Technical regress

U2 - 10.1016/j.seps.2010.09.001

DO - 10.1016/j.seps.2010.09.001

M3 - Journal article

AN - SCOPUS:78649905188

VL - 45

SP - 10

EP - 15

JO - Socio-Economic Planning Sciences

JF - Socio-Economic Planning Sciences

SN - 0038-0121

IS - 1

ER -

ID: 225670473