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New approach for the assignment of new European agricultural subsidies using scores from data envelopment analysis: Application to olive-growing farms in Andalusia (Spain)

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  • Amores, Antonio F.
  • Contreras, Ignacio

Abstract

More than 60% of olive-growing farms in Andalusia (Spain) would have negative returns without European agricultural subsidies. Agenda 2000 criteria imply that agricultural subsidies currently play the role of enhancing the production quality and the environmental and social values of agriculture. Although the necessity of the modulation of subsidies is stated, the EU regulations do not state which objective criteria should be used or how they should be measured, despite the fact that regulations demand objectivity in this measurement. This paper proposes an allocation system for subsidies which takes the Agenda 2000 criteria into account through their assignment according to Farm Efficiency which is calculated by decomposing overall DEA Scores, by means of internalizing the positive and negative externalities of agricultural activity. The paper analyzes the Type Efficiency of the Andalusian olive-growing sector by using the proposed indexes over a sample of 3000 real farms, taken from the administrative subsidy database.

Suggested Citation

  • Amores, Antonio F. & Contreras, Ignacio, 2009. "New approach for the assignment of new European agricultural subsidies using scores from data envelopment analysis: Application to olive-growing farms in Andalusia (Spain)," European Journal of Operational Research, Elsevier, vol. 193(3), pages 718-729, March.
  • Handle: RePEc:eee:ejores:v:193:y:2009:i:3:p:718-729
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    2. Ligia Alba Melo-Becerra & Antonio José Orozco-Gallo, 2015. "Eficiencia técnica de los hogares con producción agropecuaria en Colombia," Documentos de trabajo sobre Economía Regional y Urbana 227, Banco de la Republica de Colombia.
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    6. Sokol, Ondřej & Frýd, Lukáš, 2023. "DEA efficiency in agriculture: Measurement unit issues," Socio-Economic Planning Sciences, Elsevier, vol. 86(C).
    7. García-Alonso, Carlos R. & Torres-Jiménez, Mercedes & Hervás-Martínez, César, 2010. "Income prediction in the agrarian sector using product unit neural networks," European Journal of Operational Research, Elsevier, vol. 204(2), pages 355-365, July.
    8. Picazo-Tadeo, Andrés J. & Beltrán-Esteve, Mercedes & Gómez-Limón, José A., 2012. "Assessing eco-efficiency with directional distance functions," European Journal of Operational Research, Elsevier, vol. 220(3), pages 798-809.
    9. Vlontzos, G. & Pardalos, P.M., 2017. "Assess and prognosticate green house gas emissions from agricultural production of EU countries, by implementing, DEA Window analysis and artificial neural networks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 155-162.
    10. Kenichi Kashiwagi & Hajime Kamiyama, 2023. "Effect of adoption of organic farming on technical efficiency of olive-growing farms: empirical evidence from West Bank of Palestine," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 11(1), pages 1-28, December.
    11. Beltrán-Esteve, Mercedes, 2013. "Assessing technical efficiency in traditional olive grove systems: a directional metadistance function approach," Economia Agraria y Recursos Naturales, Spanish Association of Agricultural Economists, vol. 13(02), pages 1-24, December.
    12. Peng, Hongjun & Pang, Tao, 2019. "Optimal strategies for a three-level contract-farming supply chain with subsidy," International Journal of Production Economics, Elsevier, vol. 216(C), pages 274-286.
    13. Ligia Alba Melo-Becerra & Antonio José Orozco-Gallo, 2017. "Technical efficiency for Colombian small crop and livestock farmers: A stochastic metafrontier approach for different production systems," Journal of Productivity Analysis, Springer, vol. 47(1), pages 1-16, February.
    14. Carravilla, M. A. & Oliveira, J. F., 2013. "Operations Research in Agriculture: Better Decisions for a Scarce and Uncertain World," AGRIS on-line Papers in Economics and Informatics, Czech University of Life Sciences Prague, Faculty of Economics and Management, vol. 5(2), pages 1-10, June.
    15. Sushil Gupta & Hossein Rikhtehgar Berenji & Manish Shukla & Nagesh N. Murthy, 2023. "Opportunities in farming research from an operations management perspective," Production and Operations Management, Production and Operations Management Society, vol. 32(6), pages 1577-1596, June.
    16. Atici, Kazim Baris & Podinovski, Victor V., 2015. "Using data envelopment analysis for the assessment of technical efficiency of units with different specialisations: An application to agriculture," Omega, Elsevier, vol. 54(C), pages 72-83.
    17. Spyros Niavis & Nikos Tamvakis & Basil Manos & George Vlontzos, 2018. "Assessing and Explaining the Efficiency of Extensive Olive Oil Farmers: The Case of Pelion Peninsula in Greece," Agriculture, MDPI, vol. 8(2), pages 1-13, February.
    18. Apostolos Christopoulos & Ioannis Dokas & Sofia Katsimardou & Eleftherios Spyromitros, 2022. "The Malmquist Productivity measure for UK-listed firms in the aftermath of the global financial crisis," Operational Research, Springer, vol. 22(2), pages 1617-1634, April.
    19. Dios-Palomares, Rafaela & Martínez-Paz, José M., 2011. "Technical, quality and environmental efficiency of the olive oil industry," Food Policy, Elsevier, vol. 36(4), pages 526-534, August.
    20. Vasile Burja, 2011. "Regional Disparities Of Agricultural Performance In Romania," Annales Universitatis Apulensis Series Oeconomica, Faculty of Sciences, "1 Decembrie 1918" University, Alba Iulia, vol. 1(13), pages 1-12.
    21. Zhang, Chunqin & Juan, Zhicai & Xiao, Guangnian, 2015. "Do contractual practices affect technical efficiency? Evidence from public transport operators in China," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 80(C), pages 39-55.

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