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Measuring input-specific productivity change based on the principle of least action

Author

Listed:
  • Juan Aparicio

    (University Miguel Hernandez)

  • Magdalena Kapelko

    (Wroclaw University of Economics)

  • Bernhard Mahlberg

    () (Institute for Industrial Research
    Vienna University of Economics and Business)

  • Jose L. Sainz-Pardo

    (University Miguel Hernandez)

Abstract

Abstract In for-profit organizations, efficiency and productivity measurement with reference to the potential for input-specific reductions is particularly important and has been the focus of interest in the recent literature. Different approaches can be formulated to measure and decompose input-specific productivity change over time. In this paper, we highlight some problems within existing approaches and propose a new methodology based on the Principle of Least Action. In particular, this model is operationalized in the form of a non-radial Luenberger productivity indicator based on the determination of the least distance to the strongly efficient frontier of the considered production possibility sets, which are estimated by non-parametric techniques based upon Data Envelopment Analysis. In our approach, overall productivity change is the sum of input-specific productivity changes. Overall productivity change and input-specific changes are broken up into indicators of efficiency change and technical change. This decomposition enables the researcher to quantify the contributions of each production factor to productivity change and its components. In this way, the drivers of productivity development are revealed. For illustration purposes the new approach is applied to a recent dataset of Polish dairy processing firms.

Suggested Citation

  • Juan Aparicio & Magdalena Kapelko & Bernhard Mahlberg & Jose L. Sainz-Pardo, 2017. "Measuring input-specific productivity change based on the principle of least action," Journal of Productivity Analysis, Springer, vol. 47(1), pages 17-31, February.
  • Handle: RePEc:kap:jproda:v:47:y:2017:i:1:d:10.1007_s11123-016-0488-9
    DOI: 10.1007/s11123-016-0488-9
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    References listed on IDEAS

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    1. Chambers, Robert G. & Fare, Rolf & Grosskopf, Shawna, 1996. "Productivity Growth in APEC Countries," Working Papers 197843, University of Maryland, Department of Agricultural and Resource Economics.
    2. Tarja Joro & Pekka Korhonen & Jyrki Wallenius, 1998. "Structural Comparison of Data Envelopment Analysis and Multiple Objective Linear Programming," Management Science, INFORMS, vol. 44(7), pages 962-970, July.
    3. Alfons Lansink & Elvira Silva, 2003. "CO 2 and Energy Efficiency of Different Heating Technologies in the Dutch Glasshouse Industry," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 24(4), pages 395-407, April.
    4. Wrzesińska-Kowal, Joanna & Drabarczyk, Katarzyna, 2014. "Food production in Poland, compared to selected European Union Member States," Problems of World Agriculture / Problemy Rolnictwa Światowego, Warsaw University of Life Sciences, vol. 14(29), pages 1-10, December.
    5. Mikulas Luptacik & Bernhard Mahlberg, 2016. "Productivity change in a multisectoral economic system," Economic Systems Research, Taylor & Francis Journals, vol. 28(3), pages 344-361, September.
    6. Mahlberg, Bernhard & Sahoo, Biresh K., 2011. "Radial and non-radial decompositions of Luenberger productivity indicator with an illustrative application," International Journal of Production Economics, Elsevier, vol. 131(2), pages 721-726, June.
    7. Leopold Simar & Valentin Zelenyuk, 2006. "On Testing Equality of Distributions of Technical Efficiency Scores," Econometric Reviews, Taylor & Francis Journals, vol. 25(4), pages 497-522.
    8. William Cooper & Kyung Park & Jesus Pastor, 1999. "RAM: A Range Adjusted Measure of Inefficiency for Use with Additive Models, and Relations to Other Models and Measures in DEA," Journal of Productivity Analysis, Springer, vol. 11(1), pages 5-42, February.
    9. Maria Silva Portela & Pedro Borges & Emmanuel Thanassoulis, 2003. "Finding Closest Targets in Non-Oriented DEA Models: The Case of Convex and Non-Convex Technologies," Journal of Productivity Analysis, Springer, vol. 19(2), pages 251-269, April.
    10. Aparicio, Juan & Pastor, Jesus T., 2014. "Closest targets and strong monotonicity on the strongly efficient frontier in DEA," Omega, Elsevier, vol. 44(C), pages 51-57.
    11. Mahlberg, Bernhard & Luptacik, Mikulas & Sahoo, Biresh K., 2011. "Examining the drivers of total factor productivity change with an illustrative example of 14 EU countries," Ecological Economics, Elsevier, vol. 72(C), pages 60-69.
    12. Léopold Simar, 2003. "Detecting Outliers in Frontier Models: A Simple Approach," Journal of Productivity Analysis, Springer, vol. 20(3), pages 391-424, November.
    13. Walter Briec & K. Kerstens, 2009. "Infeasibilities and directional distance functions: with application to the determinateness of the luenberger productivity indicator," Post-Print hal-00372560, HAL.
    14. Gonzalez, Eduardo & Alvarez, Antonio, 2001. "From efficiency measurement to efficiency improvement: The choice of a relevant benchmark," European Journal of Operational Research, Elsevier, vol. 133(3), pages 512-520, September.
    15. Fukuyama, Hirofumi & Weber, William L., 2009. "A directional slacks-based measure of technical inefficiency," Socio-Economic Planning Sciences, Elsevier, vol. 43(4), pages 274-287, December.
    16. Kapelko, M. & Horta, I.M. & Camanho, A.S. & Oude Lansink, A., 2015. "Measurement of input-specific productivity growth with an application to the construction industry in Spain and Portugal," International Journal of Production Economics, Elsevier, vol. 166(C), pages 64-71.
    17. 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.
    18. Aparicio, Juan & Mahlberg, Bernhard & Pastor, Jesus T. & Sahoo, Biresh K., 2014. "Decomposing technical inefficiency using the principle of least action," European Journal of Operational Research, Elsevier, vol. 239(3), pages 776-785.
    19. Hirofumi Fukuyama & Hiroya Masaki & Kazuyuki Sekitani & Jianming Shi, 2014. "Distance optimization approach to ratio-form efficiency measures in data envelopment analysis," Journal of Productivity Analysis, Springer, vol. 42(2), pages 175-186, October.
    20. Pastor, Jesús T. & Aparicio, Juan, 2010. "A note on "A directional slacks-based measure of technical inefficiency"," Socio-Economic Planning Sciences, Elsevier, vol. 44(3), pages 174-175, September.
    21. Rafat Soboh & Alfons Oude Lansink & Gert Van Dijk, 2012. "Efficiency of Cooperatives and Investor Owned Firms Revisited," Journal of Agricultural Economics, Wiley Blackwell, vol. 63(1), pages 142-157, February.
    22. Mahlberg, Bernhard & Luptacik, Mikulas, 2014. "Eco-efficiency and eco-productivity change over time in a multisectoral economic system," European Journal of Operational Research, Elsevier, vol. 234(3), pages 885-897.
    23. Magdalena Kapelko & Alfons Oude Lansink & Spiro E. Stefanou, 2016. "Investment Age and Dynamic Productivity Growth in the Spanish Food Processing Industry," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 98(3), pages 946-961.
    24. 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.
    25. Cazals, Catherine & Florens, Jean-Pierre & Simar, Leopold, 2002. "Nonparametric frontier estimation: a robust approach," Journal of Econometrics, Elsevier, vol. 106(1), pages 1-25, January.
    26. Juan Aparicio & José Ruiz & Inmaculada Sirvent, 2007. "Closest targets and minimum distance to the Pareto-efficient frontier in DEA," Journal of Productivity Analysis, Springer, vol. 28(3), pages 209-218, December.
    27. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
    28. Chang, Tzu-Pu & Hu, Jin-Li & Chou, Ray Yeutien & Sun, Lei, 2012. "The sources of bank productivity growth in China during 2002–2009: A disaggregation view," Journal of Banking & Finance, Elsevier, vol. 36(7), pages 1997-2006.
    29. Fukuyama, Hirofumi & Maeda, Yasunobu & Sekitani, Kazuyuki & Shi, Jianming, 2014. "Input–output substitutability and strongly monotonic p-norm least distance DEA measures," European Journal of Operational Research, Elsevier, vol. 237(3), pages 997-1007.
    30. Pastor, J. T. & Ruiz, J. L. & Sirvent, I., 1999. "An enhanced DEA Russell graph efficiency measure," European Journal of Operational Research, Elsevier, vol. 115(3), pages 596-607, June.
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    Cited by:

    1. Magdalena Kapelko & Alfons Oude Lansink & Spiro E. Stefanou, 2017. "Input-Specific Dynamic Productivity Change: Measurement and Application to European Dairy Manufacturing Firms," Journal of Agricultural Economics, Wiley Blackwell, vol. 68(2), pages 579-599, June.
    2. Zhu, Qingyuan & Wu, Jie & Ji, Xiang & Li, Feng, 2018. "A simple MILP to determine closest targets in non-oriented DEA model satisfying strong monotonicity," Omega, Elsevier, vol. 79(C), pages 1-8.

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