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The Hicks-Moorsteen productivity index satisfies the determinateness axiom

Author

Listed:
  • Walter Briec

    (IAE Perpignan - Institut d'Administration des Entreprises - Perpignan - UPVD - Université de Perpignan Via Domitia)

  • K. Kerstens

    (LEM - Lille - Economie et Management - Université de Lille, Sciences et Technologies - CNRS - Centre National de la Recherche Scientifique)

Abstract

There are two total factor productivity indices available in the literature based on a primal notion of the technology. In a ratio tradition, these are the Malmquist and the HicksMoorsteen productivity indices. In a difference perspective, the Luenberger and Luenberger-Hicks-Moorsteen productivity indicators are based upon a sightly different concept. The purpose of this note is to establish that -in contrast to the Malmquist index- the Hicks-Moorsteen type of productivity index (as well as its difference-based counterpart) is well-defined and satisfies the determinateness property, since the underlying distance functions are always feasible.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Walter Briec & K. Kerstens, 2011. "The Hicks-Moorsteen productivity index satisfies the determinateness axiom," Post-Print hal-00656580, HAL.
  • Handle: RePEc:hal:journl:hal-00656580
    DOI: 10.1111/j.1467-9957.2010.02169.x
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    Cited by:

    1. Diogo Cunha Ferreira & Rui Cunha Marques, 2016. "Malmquist and Hicks–Moorsteen Productivity Indexes for Clusters Performance Evaluation," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 15(05), pages 1015-1053, September.
    2. Aparicio, Juan & López-Torres, Laura & Santín, Daniel, 2018. "Economic crisis and public education. A productivity analysis using a Hicks-Moorsteen index," Economic Modelling, Elsevier, vol. 71(C), pages 34-44.
    3. Briec, Walter & Kerstens, Kristiaan & Prior, Diego & Van de Woestyne, Ignace, 2018. "Testing general and special Färe-Primont indices: A proposal for public and private sector synthetic indices of European regional expenditures and tourism," European Journal of Operational Research, Elsevier, vol. 271(2), pages 756-768.
    4. Kerstens, Kristiaan & Van de Woestyne, Ignace, 2014. "Comparing Malmquist and Hicks–Moorsteen productivity indices: Exploring the impact of unbalanced vs. balanced panel data," European Journal of Operational Research, Elsevier, vol. 233(3), pages 749-758.
    5. 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.
    6. Abad, A. & Ravelojaona, P., 2025. "An unified framework for measuring environmentally-adjusted productivity change: Theoretical basis and empirical illustration," European Journal of Operational Research, Elsevier, vol. 320(3), pages 642-654.
    7. Diewert, Erwin & Fox, Kevin J., 2014. "Decomposing Bjurek Productivity Indexes into Explanatory Factors," Economics working papers erwin_diewert-2014-32, Vancouver School of Economics, revised 30 Jun 2014.
    8. repec:rza:wpaper:328 is not listed on IDEAS
    9. Tomas Balezentis & Kristiaan Kerstens & Zhiyang Shen, 2022. "Economic and Environmental Decomposition of Luenberger-Hicks-Moorsteen Total Factor Productivity Indicator: Empirical Analysis of Chinese Textile Firms With a Focus on Reporting Infeasibilities and Qu," Post-Print hal-03833245, HAL.
    10. Mocholi-Arce, Manuel & Sala-Garrido, Ramon & Molinos-Senante, Maria & Maziotis, Alexandros, 2023. "Profit productivity change in the English and Welsh water sector: Impact of the price reviews," Utilities Policy, Elsevier, vol. 82(C).
    11. Enrique Gilles & Javier Deaza & Alejandro Vivas, 2016. "Productivity measurements for three countries of the Pacific Alliance and South Korea, 2008-2012," Documentos de Trabajo EAN 15236, Universidad EAN.
    12. Jin, Qianying & Kerstens, Kristiaan & Van de Woestyne, Ignace, 2020. "Metafrontier productivity indices: Questioning the common convexification strategy," European Journal of Operational Research, Elsevier, vol. 283(2), pages 737-747.
    13. Zhiyang Shen & Kristiaan Kerstens & Tomas Baležentis, 2025. "An environmental Luenberger–Hicks–Moorsteen total factor productivity indicator: empirical analysis considering undesirable outputs either as inputs or outputs, and attention for infeasibilities," Annals of Operations Research, Springer, vol. 347(1), pages 241-263, April.
    14. Christian Stetter & Johannes Sauer, 2022. "Greenhouse Gas Emissions and Eco-Performance at Farm Level: A Parametric Approach," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 81(3), pages 617-647, March.
    15. Mocholi-Arce, Manuel & Sala-Garrido, Ramon & Molinos-Senante, Maria & Maziotis, Alexandros, 2021. "Water company productivity change: A disaggregated approach accounting for changes in inputs and outputs," Utilities Policy, Elsevier, vol. 70(C).
    16. Briec, Walter & Dumas, Audrey & Stenger, Agathe, 2013. "On the standard achievement and well-being indexes and their relation to the Hicks–Moorsteen productivity index," Economic Modelling, Elsevier, vol. 35(C), pages 900-909.
    17. C.J. O'Donnell, 2011. "The Sources of Productivity Change in the Manufacturing Sectors of the U.S. Economy," CEPA Working Papers Series WP072011, School of Economics, University of Queensland, Australia.

    More about this item

    JEL classification:

    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • D21 - Microeconomics - - Production and Organizations - - - Firm Behavior: Theory
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity

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