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Non-parametric efficiency, progress and regress measures for panel data: Methodological aspects

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  • TULKENS, H.
  • VANDEN EECKAUT, P.

Abstract

This purely methodological paper deals with the role of time in non-parametric efficiency analysis. Using both FDH and DEA technologies, it first shows how each observation in a panel can be characterized in efficiency terms vis-a-vis three different kinds of frontiers: (i) "contemporaneous", (ii) "sequential", and (iii) "intertemporal". These are then compared with window analysis. Next, frontier shifts "outward" and "inward", interpreted as progress or regress are considered for the two kinds of technologies, and computational methods are described in detail for evaluating such shifts in either case. These are also contrasted with what is measured by the "Malmquist" productivity index. Finally, an alternative way of identifying progress and regress, independent of the frontier notion and referring instead to some "benchmark" notion, is extended here to panel data.
(This abstract was borrowed from another version of this item.)
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Tulkens, H. & Vanden Eeckaut, P., 1995. "Non-parametric efficiency, progress and regress measures for panel data: Methodological aspects," LIDAM Reprints CORE 1132, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    • Handle: RePEc:cor:louvrp:1132
    DOI: 10.1016/0377-2217(94)00132-V
    Note: In : European Journal of Operational Research, 80, 474-499, 1995
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    1. Dominique Deprins & Léopold Simar & Henry Tulkens, 2006. "Measuring Labor-Efficiency in Post Offices," Springer Books, in: Parkash Chander & Jacques Drèze & C. Knox Lovell & Jack Mintz (ed.), Public goods, environmental externalities and fiscal competition, chapter 0, pages 285-309, Springer.
    2. Fare,Rolf & Grosskopf,Shawna & Lovell,C. A. Knox, 2008. "Production Frontiers," Cambridge Books, Cambridge University Press, number 9780521072069, October.
    3. Robert M. Solow, 1956. "A Contribution to the Theory of Economic Growth," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 70(1), pages 65-94.
    4. Grosskopf, S, 1986. "The Role of the Reference Technology in Measuring Productive Efficiency," Economic Journal, Royal Economic Society, vol. 96(382), pages 499-513, June.
    5. Henry Tulkens, 2006. "On FDH Efficiency Analysis: Some Methodological Issues and Applications to Retail Banking, Courts and Urban Transit," Springer Books, in: Parkash Chander & Jacques Drèze & C. Knox Lovell & Jack Mintz (ed.), Public goods, environmental externalities and fiscal competition, chapter 0, pages 311-342, Springer.
    6. Niels Christian Petersen, 1990. "Data Envelopment Analysis on a Relaxed Set of Assumptions," Management Science, INFORMS, vol. 36(3), pages 305-314, March.
    7. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    8. DEPRINS, Dominique & SIMAR, Léopold, 1983. "On Farrell measures of technical efficiency," LIDAM Reprints CORE 589, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    9. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    10. Tulkens, H. & Vanden Eeckaut, Ph., 1991. "Non-frontier measures of efficiency, progress and regress," LIDAM Discussion Papers CORE 1991055, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
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