IDEAS home Printed from https://ideas.repec.org/a/wly/agribz/v40y2024i2p349-370.html
   My bibliography  Save this article

Analysing determinate components of an approximated Luenberger–Hicks–Moorsteen productivity indicator: An application to German dairy‐processing firms

Author

Listed:
  • Frederic Ang
  • Stephen J. Ramsden

Abstract

The Luenberger–Hicks–Moorsteen (LHM) total factor productivity (TFP) indicator has sound theoretical properties, but its decomposition yields indeterminate components of technical change and scale efficiency change that can become infeasible. The current paper decomposes the approximating Bennet indicator, which results in determinate components of technical change, technical efficiency change, scale efficiency change and mix efficiency change that are always feasible. The application focuses on the German dairy‐processing sector, an important postfarm supply chain actor. We compute 558 growth rates for the period 2011–2020. The results show that the LHM‐approximating Bennet indicator decreases by on average 1.14% p.a., with substantial annual fluctuations. The underlying components of output‐ and input‐oriented technical change also fluctuate substantially, and often conflict. Moreover, output‐ and input‐oriented TFP efficiency change fluctuate moderately on average, which is mainly driven by scale efficiency change and mix efficiency change. The components of technical efficiency change remain relatively stable on average. Indeterminateness is a relevant problem when decomposing the original LHM indicator for the current sample: depending on the specification, the proportion of infeasibilities when decomposing the original LHM indicator ranges between 6.09% and 15.95%. Our proposed determinate decomposition is thus a valuable complement. [EconLit Citations: D24, D25, Q13].

Suggested Citation

  • Frederic Ang & Stephen J. Ramsden, 2024. "Analysing determinate components of an approximated Luenberger–Hicks–Moorsteen productivity indicator: An application to German dairy‐processing firms," Agribusiness, John Wiley & Sons, Ltd., vol. 40(2), pages 349-370, April.
    • Handle: RePEc:wly:agribz:v:40:y:2024:i:2:p:349-370
    DOI: 10.1002/agr.21895
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/agr.21895
    Download Restriction: no
    File URL: https://libkey.io/10.1002/agr.21895?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Pardey, Philip G. & Alston, Julian M., 2021. "Unpacking the Agricultural Black Box: The Rise and Fall of American Farm Productivity Growth," The Journal of Economic History, Cambridge University Press, vol. 81(1), pages 114-155, March.
    2. Frederic Ang & Pieter Jan Kerstens, 2023. "Robust nonparametric analysis of dynamic profits, prices and productivity: An application to French meat-processing firms," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 50(2), pages 771-809.
    3. Bert Balk & Rolf Färe & Shawna Grosskopf, 2003. "The theory of economic price and quantity indicators," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 23(1), pages 149-164, December.
    4. Kristiaan Kerstens & Jafar Sadeghi & Ignace Van de Woestyne & Linjia Zhang, 2022. "Malmquist productivity indices and plant capacity utilisation: new proposals and empirical application," Annals of Operations Research, Springer, vol. 315(1), pages 221-250, August.
    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. Awudu Abdulai & Hendrik Tietje, 2007. "Estimating technical efficiency under unobserved heterogeneity with stochastic frontier models: application to northern German dairy farms," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 34(3), pages 393-416, September.
    7. W. Briec & K. Kerstens, 2009. "Infeasibility and Directional Distance Functions with Application to the Determinateness of the Luenberger Productivity Indicator," Journal of Optimization Theory and Applications, Springer, vol. 141(1), pages 55-73, April.
    8. Valentin Zelenyuk, 2014. "Scale efficiency and homotheticity: equivalence of primal and dual measures," Journal of Productivity Analysis, Springer, vol. 42(1), pages 15-24, August.
    9. Ioannis Skevas & Grigorios Emvalomatis & Bernhard Brümmer, 2018. "Heterogeneity of Long†run Technical Efficiency of German Dairy Farms: A Bayesian Approach," Journal of Agricultural Economics, Wiley Blackwell, vol. 69(1), pages 58-75, February.
    10. Ang, Frederic & Kerstens, Pieter Jan, 2020. "A superlative indicator for the Luenberger-Hicks-Moorsteen productivity indicator: Theory and application," European Journal of Operational Research, Elsevier, vol. 285(3), pages 1161-1173.
    11. Kerstens, Kristiaan & Shen, Zhiyang & Van de Woestyne, Ignace, 2018. "Comparing Luenberger and Luenberger-Hicks-Moorsteen productivity indicators: How well is total factor productivity approximated?," International Journal of Production Economics, Elsevier, vol. 195(C), pages 311-318.
    12. Kristiaan Kerstens & Ignace Van de Woestyne, 2021. "Cost functions are nonconvex in the outputs when the technology is nonconvex: convexification is not harmless," Annals of Operations Research, Springer, vol. 305(1), pages 81-106, October.
    13. Walter Briec & Kristiaan Kerstens, 2004. "A Luenberger-Hicks-Moorsteen productivity indicator: its relation to the Hicks-Moorsteen productivity index and the Luenberger productivity indicator," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 23(4), pages 925-939, May.
    14. Lukáš Čechura & Zdeňka Žáková Kroupová, 2021. "Technical Efficiency in the European Dairy Industry: Can We Observe Systematic Failures in the Efficiency of Input Use?," Sustainability, MDPI, vol. 13(4), pages 1-19, February.
    15. R. G. Chambers & Y. Chung & R. Färe, 1998. "Profit, Directional Distance Functions, and Nerlovian Efficiency," Journal of Optimization Theory and Applications, Springer, vol. 98(2), pages 351-364, August.
    16. C. A. K. Lovell, 2016. "Recent Developments in Productivity Analysis," Pacific Economic Review, Wiley Blackwell, vol. 21(4), pages 417-444, October.
    17. Robert G. Chambers, 2002. "Exact nonradial input, output, and productivity measurement," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 20(4), pages 751-765.
    18. Frederic Ang & Kristiaan Kerstens & Jafar Sadeghi, 2023. "Energy productivity and greenhouse gas emission intensity in Dutch dairy farms: A Hicks–Moorsteen by‐production approach under non‐convexity and convexity with equivalence results," Journal of Agricultural Economics, Wiley Blackwell, vol. 74(2), pages 492-509, June.
    19. Léopold Simar & Paul W. Wilson, 1998. "Sensitivity Analysis of Efficiency Scores: How to Bootstrap in Nonparametric Frontier Models," Management Science, INFORMS, vol. 44(1), pages 49-61, January.
    20. 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.
    21. Lukáš Čechura & Zdeňka Žáková Kroupová & Irena Benešová, 2021. "Productivity and Efficiency in European Milk Production: Can We Observe the Effects of Abolishing Milk Quotas?," Agriculture, MDPI, vol. 11(9), pages 1-21, August.
    22. Csaba Jansik & Xavier Irz, 2015. "Competitiveness Makes a Difference in the European Dairy Sector," EuroChoices, The Agricultural Economics Society, vol. 14(3), pages 12-19, December.
    23. Frederic Ang, 2019. "Analyzing Components of Productivity Growth Using the Bennet-Lowe Indicator: An Application to Welsh Sheep Farms," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 101(4), pages 1262-1276.
    24. Frederic Ang & Simon M. Mortimer & Francisco J. Areal & Richard Tiffin, 2018. "On the Opportunity Cost of Crop Diversification," Journal of Agricultural Economics, Wiley Blackwell, vol. 69(3), pages 794-814, September.
    25. Diewert, W. E., 1976. "Exact and superlative index numbers," Journal of Econometrics, Elsevier, vol. 4(2), pages 115-145, May.
    26. Nishimizu, Mieko & Page, John M, Jr, 1982. "Total Factor Productivity Growth, Technological Progress and Technical Efficiency Change: Dimensions of Productivity Change in Yugoslavia, 1965-78," Economic Journal, Royal Economic Society, vol. 92(368), pages 920-936, December.
    27. 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.
    28. Simar, Léopold & Wilson, Paul W., 2020. "Technical, allocative and overall efficiency: Estimation and inference," European Journal of Operational Research, Elsevier, vol. 282(3), pages 1164-1176.
    29. Johannes Sauer & Uwe Latacz-Lohmann, 2015. "Investment, technical change and efficiency: empirical evidence from German dairy production," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 42(1), pages 151-175.
    30. Shen, Zhiyang & Baležentis, Tomas & Ferrier, Gary D., 2019. "Agricultural productivity evolution in China: A generalized decomposition of the Luenberger-Hicks-Moorsteen productivity indicator," China Economic Review, Elsevier, vol. 57(C).
    31. Chambers, Robert G. & Chung, Yangho & Fare, Rolf, 1996. "Benefit and Distance Functions," Journal of Economic Theory, Elsevier, vol. 70(2), pages 407-419, August.
    32. Ang, Frederic & Kerstens, Pieter Jan, 2017. "Decomposing the Luenberger–Hicks–Moorsteen Total Factor Productivity indicator: An application to U.S. agriculture," European Journal of Operational Research, Elsevier, vol. 260(1), pages 359-375.
    33. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Frederic Ang & Pieter Jan Kerstens, 2023. "Robust nonparametric analysis of dynamic profits, prices and productivity: An application to French meat-processing firms," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 50(2), pages 771-809.
    2. Frederic Ang & Kristiaan Kerstens & Jafar Sadeghi, 2023. "Energy productivity and greenhouse gas emission intensity in Dutch dairy farms: A Hicks–Moorsteen by‐production approach under non‐convexity and convexity with equivalence results," Journal of Agricultural Economics, Wiley Blackwell, vol. 74(2), pages 492-509, June.
    3. Ang, Frederic & Kerstens, Pieter Jan, 2020. "A superlative indicator for the Luenberger-Hicks-Moorsteen productivity indicator: Theory and application," European Journal of Operational Research, Elsevier, vol. 285(3), pages 1161-1173.
    4. Stefano NASINI & Rabia NESSAH, 2021. "Endogenous Learning in Multi-Sector Economies," Working Papers 2021-EQM-08, IESEG School of Management, revised Oct 2023.
    5. 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.
    6. Cherchye, L. & Post, G.T., 2001. "Methodological Advances in Dea," ERIM Report Series Research in Management ERS-2001-53-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    7. Haiyan Deng & Ge Bai & Kristiaan Kerstens & Zhiyang Shen, 2023. "Comparing green productivity under convex and nonconvex technologies: Which is a robust approach consistent with energy structure?," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 44(8), pages 4377-4394, December.
    8. Briec, Walter & Dumas, Audrey & Kerstens, Kristiaan & Stenger, Agathe, 2022. "Generalised commensurability properties of efficiency measures: Implications for productivity indicators," European Journal of Operational Research, Elsevier, vol. 303(3), pages 1481-1492.
    9. Valentin Zelenyuk, 2023. "Productivity analysis: roots, foundations, trends and perspectives," Journal of Productivity Analysis, Springer, vol. 60(3), pages 229-247, December.
    10. A. Abad & P. Ravelojaona, 2017. "Exponential environmental productivity index and indicators," Journal of Productivity Analysis, Springer, vol. 48(2), pages 147-166, December.
    11. Ang, Frederic & Kerstens, Pieter Jan, 2017. "Decomposing the Luenberger–Hicks–Moorsteen Total Factor Productivity indicator: An application to U.S. agriculture," European Journal of Operational Research, Elsevier, vol. 260(1), pages 359-375.
    12. Ravelojaona, Paola, 2019. "On constant elasticity of substitution – Constant elasticity of transformation Directional Distance Functions," European Journal of Operational Research, Elsevier, vol. 272(2), pages 780-791.
    13. Pastor, Jesus T. & Lovell, C.A. Knox & Aparicio, Juan, 2020. "Defining a new graph inefficiency measure for the proportional directional distance function and introducing a new Malmquist productivity index," European Journal of Operational Research, Elsevier, vol. 281(1), pages 222-230.
    14. Zhensheng Chen & Xueli Chen & Tomas Baležentis & Xiaoqing Gan & Vivian Valdmanis, 2020. "Productivity change and its driving forces in Chinese healthcare sector," PLOS ONE, Public Library of Science, vol. 15(12), pages 1-16, December.
    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. Chen, Xiaoqing & Kerstens, Kristiaan & Tsionas, Mike, 2024. "Does productivity change at all in Swedish district courts? Empirical analysis focusing on horizontal mergers," Socio-Economic Planning Sciences, Elsevier, vol. 91(C).
    17. 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.
    18. Arnaud Abad & Rabaozafy Louisa Andriamasy & Walter Briec, 2018. "Surplus measures and luenberger Hicks–Moorsteen productivity indicator," Journal of Economics, Springer, vol. 125(3), pages 279-308, November.
    19. Rafael Benítez & Vicente Coll-Serrano & Vicente J. Bolós, 2021. "deaR-Shiny: An Interactive Web App for Data Envelopment Analysis," Sustainability, MDPI, vol. 13(12), pages 1-19, June.
    20. Tomas Balezentis & Zhiyang Shen, 2017. "An environmental Luenberger-Hicks-Moorsteen. Total Factor Productivityindicator for OECD Countries," Working Papers 2017-EQM-02, IESEG School of Management.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wly:agribz:v:40:y:2024:i:2:p:349-370. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1520-6297 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.