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Non-frontier measures of efficiency, progress and regress for time series data

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  • Tulkens, Henry
  • Vanden Eeckaut, Philippe

Abstract

We deal in this paper wih efficiency, progress and regress without using the frontier concept. For describing the relation between inputs and outputs in production, we introduce a notion that we call “benchmark production correspondence” with which to measure progress and regress without running into the problems of distinguishing between efficiency gains and progress, or between efficiency losses and regress. An illustration with a monthly time series covering almost 15 years of the activities of an urban transit company is presented and contrasted with DEA and FDH nonparametric frontier approaches.
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  • Tulkens, Henry & Vanden Eeckaut, Philippe, 1995. "Non-frontier measures of efficiency, progress and regress for time series data," International Journal of Production Economics, Elsevier, vol. 39(1-2), pages 83-97, April.
    • Handle: RePEc:eee:proeco:v:39:y:1995:i:1-2:p:83-97
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    1. 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.
    2. Henry Tulkens & Philippe Eeckaut, 2006. "Nonparametric Efficiency, Progress and Regress Measures For Panel Data: Methodological Aspects," Springer Books, in: Parkash Chander & Jacques Drèze & C. Knox Lovell & Jack Mintz (ed.), Public goods, environmental externalities and fiscal competition, chapter 0, pages 395-429, Springer.
    3. 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.
    4. 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.
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    3. Cooper, W. W. & Seiford, Lawrence M. & Thanassoulis, Emmanuel & Zanakis, Stelios H., 2004. "DEA and its uses in different countries," European Journal of Operational Research, Elsevier, vol. 154(2), pages 337-344, April.
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    6. Requillart, Vincent & Nauges, Celine & Simioni, Michel & Bontemps, Christophe, 2012. "Food Safety Regulation and Firm Productivity: Evidence from the French Food Industry," 2012 First Congress, June 4-5, 2012, Trento, Italy 124378, Italian Association of Agricultural and Applied Economics (AIEAA).
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    9. Triantis, Konstantinos & Sarangi, Sudipta & Kuchta, Dorota, 2003. "Fuzzy pair-wise dominance and fuzzy indices: An evaluation of productive performance," European Journal of Operational Research, Elsevier, vol. 144(2), pages 412-428, January.
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    11. Diewert, W. Erwin & Fox, Kevin J., 2017. "Decomposing productivity indexes into explanatory factors," European Journal of Operational Research, Elsevier, vol. 256(1), pages 275-291.
    12. Chambers, Robert G. & Fare, Rolf & Jaenicke, Edward & Lichtenberg, Erik, 1998. "Using dominance in forming bounds on DEA models: The case of experimental agricultural data," Journal of Econometrics, Elsevier, vol. 85(1), pages 189-203, July.
    13. Maria Alberta Oliveira & Carlos Santos, 2005. "Assessing school efficiency in Portugal using FDH and bootstrapping," Applied Economics, Taylor & Francis Journals, vol. 37(8), pages 957-968.
    14. Forsund, Finn R. & Sarafoglou, Nikias, 2005. "The tale of two research communities: The diffusion of research on productive efficiency," International Journal of Production Economics, Elsevier, vol. 98(1), pages 17-40, October.
    15. Mukherjee, Kankana, 2010. "Measuring energy efficiency in the context of an emerging economy: The case of indian manufacturing," European Journal of Operational Research, Elsevier, vol. 201(3), pages 933-941, March.
    16. Riccardi, R. & Oggioni, G. & Toninelli, R., 2012. "Efficiency analysis of world cement industry in presence of undesirable output: Application of data envelopment analysis and directional distance function," Energy Policy, Elsevier, vol. 44(C), pages 140-152.
    17. Kittelsen,S.A.C., 1999. "Monte Carlo simulations of DEA efficiency measures and hypothesis tests," Memorandum 09/1999, Oslo University, Department of Economics.
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    19. Barros, Carlos P. & Liang, Qi Bin & Peypoch, Nicolas, 2013. "The technical efficiency of US Airlines," Transportation Research Part A: Policy and Practice, Elsevier, vol. 50(C), pages 139-148.

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