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Creation of climate‐smart and energy‐efficient agriculture in the European Union: Pathways based on the frontier analysis

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  • Justas Streimikis
  • Zhuang Miao
  • Tomas Balezentis

Abstract

Creation of the climate‐smart agriculture requires efficient resource use and mitigation of the environmental pressures among other objectives. Therefore, it is important to assess the energy efficiency and productivity growth in the European Union's agriculture. This paper analyses the sample of the selected European Union member states. The productive technology including the energy consumption and the resulting greenhouse gas (GHG) emission is constructed. The measurement of the energy efficiency and productivity change relies on the slacks‐based measure and Luenberger productivity indicator. The productivity growth was decomposed with respect to the input/output variables and the sources of growth (i.e., efficiency change and technical progress). The average annual productivity growth of 0.79% was obtained for the selected countries during 1995–2016. The highest productivity gains were observed in Lithuania, Denmark, Belgium and Romania (1.27%–1.94% per year). The productivity growth related to GHG emission dominated the contributions by the input/output variables in Lithuania, Denmark, Belgium, Romania, Poland, Austria, France, the Netherlands, Hungary and Estonia.

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  • Justas Streimikis & Zhuang Miao & Tomas Balezentis, 2021. "Creation of climate‐smart and energy‐efficient agriculture in the European Union: Pathways based on the frontier analysis," Business Strategy and the Environment, Wiley Blackwell, vol. 30(1), pages 576-589, January.
    • Handle: RePEc:bla:bstrat:v:30:y:2021:i:1:p:576-589
    DOI: 10.1002/bse.2640
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    as
    1. Kerstens, Kristiaan & O’Donnell, Christopher & Van de Woestyne, Ignace, 2019. "Metatechnology frontier and convexity: A restatement," European Journal of Operational Research, Elsevier, vol. 275(2), pages 780-792.
    2. Vlontzos, George & Niavis, Spyros & Manos, Basil, 2014. "A DEA approach for estimating the agricultural energy and environmental efficiency of EU countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 40(C), pages 91-96.
    3. Lajos Baráth & Imre Fertő, 2017. "Productivity and Convergence in European Agriculture," Journal of Agricultural Economics, Wiley Blackwell, vol. 68(1), pages 228-248, February.
    4. Lajos Baráth & Imre Fertő & Štefan Bojnec, 2020. "The Effect of Investment, LFA and Agri‐environmental Subsidies on the Components of Total Factor Productivity: The Case of Slovenian Farms," Journal of Agricultural Economics, Wiley Blackwell, vol. 71(3), pages 853-876, September.
    5. 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.
    6. Sueyoshi, Toshiyuki & Yuan, Yan & Goto, Mika, 2017. "A literature study for DEA applied to energy and environment," Energy Economics, Elsevier, vol. 62(C), pages 104-124.
    7. Boussemart, Jean-Philippe & Ferrier, Gary D. & Leleu, Hervé & Shen, Zhiyang, 2020. "An expanded decomposition of the Luenberger productivity indicator with an application to the Chinese healthcare sector," Omega, Elsevier, vol. 91(C).
    8. Wang, Xue-Chao & Klemeš, Jiří Jaromír & Wang, Yutao & Dong, Xiaobin & Wei, Hejie & Xu, Zihan & Varbanov, Petar Sabev, 2020. "Water-Energy-Carbon Emissions nexus analysis of China: An environmental input-output model-based approach," Applied Energy, Elsevier, vol. 261(C).
    9. Wang, Ke & Wei, Yi-Ming, 2016. "Sources of energy productivity change in China during 1997–2012: A decomposition analysis based on the Luenberger productivity indicator," Energy Economics, Elsevier, vol. 54(C), pages 50-59.
    10. 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.
    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. Pastor, Jesus T. & Lovell, C.A. Knox, 2005. "A global Malmquist productivity index," Economics Letters, Elsevier, vol. 88(2), pages 266-271, August.
    13. Fang, Lei, 2020. "Opening the “black box” of environmental production technology in a nonparametric analysis," European Journal of Operational Research, Elsevier, vol. 286(2), pages 769-780.
    14. Ioannis Skevas, 2020. "Measurement of production inefficiency in a technology and inefficiency heterogeneity setting," Applied Economics, Taylor & Francis Journals, vol. 52(42), pages 4594-4604, September.
    15. Jiang, Zhiqiang & Ji, Changming & Qin, Hui & Feng, Zhongkai, 2018. "Multi-stage progressive optimality algorithm and its application in energy storage operation chart optimization of cascade reservoirs," Energy, Elsevier, vol. 148(C), pages 309-323.
    16. Atakelty Hailu & Terrence S. Veeman, 2001. "Non-parametric Productivity Analysis with Undesirable Outputs: An Application to the Canadian Pulp and Paper Industry," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 83(3), pages 605-616.
    17. María Pérez Urdiales & Alfons Oude Lansink & Alan Wall, 2016. "Eco-efficiency Among Dairy Farmers: The Importance of Socio-economic Characteristics and Farmer Attitudes," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 64(4), pages 559-574, August.
    18. Eric Njuki & Boris E. Bravo-Ureta & Christopher J. O’Donnell, 2019. "Decomposing agricultural productivity growth using a random-parameters stochastic production frontier," Empirical Economics, Springer, vol. 57(3), pages 839-860, September.
    19. Jiandong Chen & Ming Gao & Ke Ma & Malin Song, 2020. "Different effects of technological progress on China's carbon emissions based on sustainable development," Business Strategy and the Environment, Wiley Blackwell, vol. 29(2), pages 481-492, February.
    20. Fan, Xing & Zhang, Wen & Chen, Weiwei & Chen, Bin, 2020. "Land–water–energy nexus in agricultural management for greenhouse gas mitigation," Applied Energy, Elsevier, vol. 265(C).
    21. William W. Cooper & Lawrence M. Seiford & Kaoru Tone, 2007. "Undesirable Outputs Models," Springer Books, in: Data Envelopment Analysis, edition 0, chapter 13, pages 367-379, Springer.
    22. Ke Wang & Yujiao Xian & Yi-Ming Wei & Zhimin Huang, 2016. "Sources of carbon productivity change: A decomposition and disaggregation analysis based on global Luenberger productivity indicator and endogenous directional distance function," CEEP-BIT Working Papers 91, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    23. Eric Njuki & Boris E. Bravo-Ureta, 2019. "Examining irrigation productivity in U.S. agriculture using a single-factor approach," Journal of Productivity Analysis, Springer, vol. 51(2), pages 125-136, June.
    24. 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.
    25. Zhou, P. & Ang, B.W. & Wang, H., 2012. "Energy and CO2 emission performance in electricity generation: A non-radial directional distance function approach," European Journal of Operational Research, Elsevier, vol. 221(3), pages 625-635.
    26. 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.
    27. Miao, Zhuang & Baležentis, Tomas & Shao, Shuai & Chang, Dongfeng, 2019. "Energy use, industrial soot and vehicle exhaust pollution—China's regional air pollution recognition, performance decomposition and governance," Energy Economics, Elsevier, vol. 83(C), pages 501-514.
    28. William W. Cooper & Lawrence M. Seiford & Kaoru Tone, 2007. "Data Envelopment Analysis," Springer Books, Springer, edition 0, number 978-0-387-45283-8, April.
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    4. Huang, Hongyun & Mo, Renbian & Chen, Xingquan, 2021. "New patterns in China's regional green development: An interval Malmquist–Luenberger productivity analysis," Structural Change and Economic Dynamics, Elsevier, vol. 58(C), pages 161-173.
    5. Leonidas Sotirios Kyrgiakos & Georgios Kleftodimos & George Vlontzos & Panos M. Pardalos, 2023. "A systematic literature review of data envelopment analysis implementation in agriculture under the prism of sustainability," Operational Research, Springer, vol. 23(1), pages 1-38, March.
    6. Zhang, Dongyang, 2021. "Marketization, environmental regulation, and eco-friendly productivity: A Malmquist–Luenberger index for pollution emissions of large Chinese firms," Journal of Asian Economics, Elsevier, vol. 76(C).
    7. Barnes, A.P. & McMillan, J. & Sutherland, L.-A. & Hopkins, J. & Thomson, S.G., 2022. "Farmer intentional pathways for net zero carbon: Exploring the lock-in effects of forestry and renewables," Land Use Policy, Elsevier, vol. 112(C).

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