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Productivity growth measurement and decomposition under a dynamic inefficiency specification: The case of German dairy farms

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  • Skevas, Ioannis
  • Emvalomatis, Grigorios
  • Brümmer, Bernhard

Abstract

Standard parametric models for efficiency and total factor productivity growth measurement either impose strict structures on the time-evolution of efficiency scores or no structure at all. When the data capture a sector in turbulent periods both specifications may be inappropriate. The dynamic stochastic frontier model takes a middle way in terms of the time-structure it imposes on efficiency scores. We apply the dynamic stochastic frontier model to the case of German dairy farms in a period that is characterized by high milk price volatility. The model is able to capture time-specific efficiency and total factor productivity growth shocks that may have been induced by this high volatility. Furthermore, the dynamic stochastic frontier model is favored by the data when compared to a model that imposes a very restrictive time structure on efficiency and two models that do not impose any time structure at all.

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  • Skevas, Ioannis & Emvalomatis, Grigorios & Brümmer, Bernhard, 2018. "Productivity growth measurement and decomposition under a dynamic inefficiency specification: The case of German dairy farms," European Journal of Operational Research, Elsevier, vol. 271(1), pages 250-261.
    • Handle: RePEc:eee:ejores:v:271:y:2018:i:1:p:250-261
    DOI: 10.1016/j.ejor.2018.04.050
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    Cited by:

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    2. Tsionas, Mike G. & Malikov, Emir & Kumbhakar, Subal C., 2020. "Endogenous dynamic efficiency in the intertemporal optimization models of firm behavior," European Journal of Operational Research, Elsevier, vol. 284(1), pages 313-324.
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    4. Baños-Pino, José F. & Boto-García, David & Zapico, Emma, 2021. "Persistence and dynamics in the efficiency of toll motorways: The Spanish case," Efficiency Series Papers 2021/03, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    5. Caetano Luiz Beber & Sebastian Lakner & Ioannis Skevas, 2021. "Organizational forms and technical efficiency of the dairy processing industry in Southern Brazil," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 9(1), pages 1-22, December.
    6. Ali, Beshir M. & de Mey, Yann & Oude Lansink, Alfons G.J.M., 2021. "The effect of farm genetics expenses on dynamic productivity growth," European Journal of Operational Research, Elsevier, vol. 290(2), pages 701-717.
    7. Huang, Minjie & Zhao, Shunan & Kumbhakar, Subal C., 2022. "Decomposition of Output, Productivity and Market Structure Changes," European Journal of Operational Research, Elsevier, vol. 303(1), pages 422-437.
    8. Ioannis Skevas, 2023. "A novel modeling framework for quantifying spatial spillovers on total factor productivity growth and its components," American Journal of Agricultural Economics, John Wiley & Sons, vol. 105(4), pages 1221-1247, August.
    9. Baležentis, Tomas & Sun, Kai, 2020. "Measurement of technical inefficiency and total factor productivity growth: A semiparametric stochastic input distance frontier approach and the case of Lithuanian dairy farms," European Journal of Operational Research, Elsevier, vol. 285(3), pages 1174-1188.
    10. Liyun Zhu & Alfons Oude Lansink, 2022. "Dynamic sustainable productivity growth of Dutch dairy farming," PLOS ONE, Public Library of Science, vol. 17(2), pages 1-19, February.
    11. Baños-Pino, José F. & Boto-García, David & Zapico, Emma, 2022. "Persistence and dynamics in the efficiency of toll motorways: The Spanish case," Economics of Transportation, Elsevier, vol. 31(C).
    12. Skevas, Ioannis, 2020. "Inference in the spatial autoregressive efficiency model with an application to Dutch dairy farms," European Journal of Operational Research, Elsevier, vol. 283(1), pages 356-364.
    13. Jerzy Marzec & Andrzej Pisulewski, 2021. "Measurement of technical efficiency in the case of heterogeneity of technologies used between firms - Based on evidence from Polish crop farms," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 67(4), pages 152-161.
    14. Alessandro Magrini, 2021. "A Stochastic Frontier Model to Assess Agricultural Eco-efficiency of European Countries in 1990–2019," International Journal of Statistics and Probability, Canadian Center of Science and Education, vol. 10(4), pages 138-138, July.
    15. Polemis, Michael L. & Tzeremes, Nickolaos G., 2019. "Competitive conditions and sectors’ productive efficiency: A conditional non-parametric frontier analysis," European Journal of Operational Research, Elsevier, vol. 276(3), pages 1104-1118.
    16. Zetian Yu & Hao Liu & Hua Peng & Qiantong Xia & Xiaoxia Dong, 2023. "Production Efficiency of Raw Milk and Its Determinants: Application of Combining Data Envelopment Analysis and Stochastic Frontier Analysis," Agriculture, MDPI, vol. 13(2), pages 1-25, February.
    17. Kumbhakar, Subal C. & Li, Mingyang & Lien, Gudbrand, 2023. "Do subsidies matter in productivity and profitability changes?," Economic Modelling, Elsevier, vol. 123(C).

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    More about this item

    Keywords

    OR in agriculture; Productivity growth; German dairy farms; Dynamic stochastic frontier;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • Q12 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets

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