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Productivity, technical efficiency and technological change in French agriculture during 2002-2015: a Färe-Primont index decomposition using group frontiers and meta-frontier

Author

Listed:
  • K Hervé Dakpo

    (ECO-PUB - Economie Publique - INRA - Institut National de la Recherche Agronomique - AgroParisTech)

  • Yann Desjeux

    (SMART-LERECO - Structures et Marché Agricoles, Ressources et Territoires - INRA - Institut National de la Recherche Agronomique - AGROCAMPUS OUEST)

  • Philippe Jeanneaux

    (Territoires - Territoires - INRA - Institut National de la Recherche Agronomique - AgroParisTech - VAS - VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement - IRSTEA - Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture - UCA [2017-2020] - Université Clermont Auvergne [2017-2020])

  • Laure Latruffe

    (SMART-LERECO - Structures et Marché Agricoles, Ressources et Territoires - INRA - Institut National de la Recherche Agronomique - AGROCAMPUS OUEST)

Abstract

The objective of the article is to assess productivity change in French agriculture during 2002–2015; namely, total factor productivity (TFP) change and its components – technological change and efficiency change. For this, we use the Färe-Primont index which verifies the multiplicatively completeness property and is also transitive, allowing for multi-temporal and -lateral comparisons. We investigate the extent of heterogeneity within each type of farming sub-sample in terms of TFP change, with the help of the Herfindahl-Hirschman index (HHI). In addition, to compare the technologies among the five types of farming considered, we extend our analysis to the meta-frontier framework. Results indicate that during 2002–2015, all farms experienced TFP progress. The smallest average increase was experienced by the dairy farms and the largest by the field crop farms and the beef farms. The latter had the strongest technological progress but a deterioration in efficiency, while the opposite was found for field crop farms. The analysis of HHI reveals that sheep or goat farms are the most homogenous in terms of the direction of TFP change experienced over the period 2002–2015. The meta-frontier analysis shows that field crop farms' technology is the most productive of all the types of farming.

Suggested Citation

  • K Hervé Dakpo & Yann Desjeux & Philippe Jeanneaux & Laure Latruffe, 2019. "Productivity, technical efficiency and technological change in French agriculture during 2002-2015: a Färe-Primont index decomposition using group frontiers and meta-frontier," Post-Print hal-01901487, HAL.
  • Handle: RePEc:hal:journl:hal-01901487
    DOI: 10.1080/00036846.2018.1524982
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    Cited by:

    1. Tomas Baležentis & Alfons Oude Lansink, 2020. "Measuring dynamic biased technical change in Lithuanian cereal farms," Agribusiness, John Wiley & Sons, Ltd., vol. 36(2), pages 208-225, April.
    2. 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.
    3. Lajos Baráth & Imre Fertő & Jakub Staniszewski, 2021. "Technological Heterogeneity in Pig Farming: A Metafrontier Approach—Perspectives from Hungary and Poland," Agriculture, MDPI, vol. 11(10), pages 1-13, October.
    4. K Hervé Dakpo & Laure Latruffe & Yann Desjeux & Philippe Jeanneaux, 2021. "Latent Class Modelling for a Robust Assessment of Productivity: Application to French Grazing Livestock Farms," Journal of Agricultural Economics, Wiley Blackwell, vol. 72(3), pages 760-781, September.
    5. Xin Janet Ge & Xiaoxia Liu, 2021. "Urban Land Use Efficiency under Resource-Based Economic Transformation—A Case Study of Shanxi Province," Land, MDPI, vol. 10(8), pages 1-20, August.
    6. Fu, Tsu-Tan & See, Kok Fong, 2022. "An integrated analysis of quality and productivity growth in China’s and Taiwan’s higher education institutions," Economic Analysis and Policy, Elsevier, vol. 74(C), pages 234-249.
    7. Reziti, Ioanna, 2019. "Total factor productivity change of agriculture in five Southern European countries," Agricultural Economics Review, Greek Association of Agricultural Economists, vol. 0(Issue 2).
    8. Danilo Đokić & Bojan Matkovski & Marija Jeremić & Ivan Đurić, 2022. "Land Productivity and Agri-Environmental Indicators: A Case Study of Western Balkans," Land, MDPI, vol. 11(12), pages 1-13, December.
    9. Anna Nowak & Renata Kubik, 2019. "Changes in Agricultural Productivity in New and Old Member States of the European Union," European Research Studies Journal, European Research Studies Journal, vol. 0(4), pages 101-114.
    10. Yuko Akune & Nobuhiro Hosoe, 2021. "Microdata analysis of Japanese farmers’ productivity: Estimating farm heterogeneity and elasticity of substitution among varieties," Agricultural Economics, International Association of Agricultural Economists, vol. 52(4), pages 633-644, July.
    11. Đokić, Danilo & Matkovski, Bojan & Jeremić, Marija & Đurić, Ivan, 2022. "Land productivity and agri-environmental indicators: A case study of Western Balkans," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 11(12), pages 1-13.

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