IDEAS home Printed from https://ideas.repec.org/p/ags/cfcp15/344256.html
   My bibliography  Save this paper

Competitiveness and resilience dynamics in the Italian olive sector: An in-depth analysis

Author

Listed:
  • Lambarraa-Lehnhardt, Fatima
  • Rosati, Adolfo
  • Hasnain, Syeda Aleena
  • Turchetti, Luca

Abstract

This paper investigates the interaction among potential and revealed resilience capacities, technical efficiency, and total factor productivity (TFP) in Italian olive farms using FADN data from 2013-2019. To achieve this objective, we use principal component analysis for evaluating potential resilience indicators and a stochastic frontier model (SFM) to assess farms' competitiveness and evaluate the impact of resilience measures on farms' efficiency and productivity. Results show that Italian olive farms exhibit higher resilience in transformability, followed by robustness and adaptability. Resilience indicators negatively impact technical efficiency. TFP growth is notably influenced by adaptability. Results suggest that balancing competitiveness and resilience is crucial to achieving a sustainable farming system. To face climate change challenges, policies should facilitate transitions to a climate-resilient farming system by incentivizing investments in climate adaptive technologies and designing careful subsidy programs that emphasize the long-term resilience benefits of sustainable farming practices rather than considering immediate efficiency gains. Farmer support through training and collaborative networks is vital to strengthening farms' adaptability and transformability capacities.

Suggested Citation

  • Lambarraa-Lehnhardt, Fatima & Rosati, Adolfo & Hasnain, Syeda Aleena & Turchetti, Luca, 2024. "Competitiveness and resilience dynamics in the Italian olive sector: An in-depth analysis," IAAE 2024 Conference, August 2-7, 2024, New Delhi, India 344256, International Association of Agricultural Economists (IAAE).
  • Handle: RePEc:ags:cfcp15:344256
    DOI: 10.22004/ag.econ.344256
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/344256/files/21495.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.22004/ag.econ.344256?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. Jeffrey M. Wooldridge, 2015. "Control Function Methods in Applied Econometrics," Journal of Human Resources, University of Wisconsin Press, vol. 50(2), pages 420-445.
    2. Willam Greene, 2005. "Fixed and Random Effects in Stochastic Frontier Models," Journal of Productivity Analysis, Springer, vol. 23(1), pages 7-32, January.
    3. Papke, Leslie E. & Wooldridge, Jeffrey M., 2008. "Panel data methods for fractional response variables with an application to test pass rates," Journal of Econometrics, Elsevier, vol. 145(1-2), pages 121-133, July.
    4. Meuwissen, Miranda P.M. & Feindt, Peter H. & Spiegel, Alisa & Termeer, Catrien J.A.M. & Mathijs, Erik & Mey, Yann de & Finger, Robert & Balmann, Alfons & Wauters, Erwin & Urquhart, Julie & Vigani, Mau, 2019. "A framework to assess the resilience of farming systems," Agricultural Systems, Elsevier, vol. 176(C).
    5. Thomas Slijper & Yann de Mey & P Marijn Poortvliet & Miranda P M Meuwissen, 2022. "Quantifying the resilience of European farms using FADN," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 49(1), pages 121-150.
    6. Fatima Lambarraa & Spiro Stefanou & Teresa Serra & José M. Gil, 2009. "The impact of the 1999 CAP reforms on the efficiency of the COP sector in Spain," Agricultural Economics, International Association of Agricultural Economists, vol. 40(3), pages 355-364, May.
    7. Timothy J. Coelli & D.S. Prasada Rao & Christopher J. O’Donnell & George E. Battese, 2005. "An Introduction to Efficiency and Productivity Analysis," Springer Books, Springer, edition 0, number 978-0-387-25895-9, December.
    8. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-332.
    9. Kumbhakar, Subal C. & Li, Mingyang & Lien, Gudbrand, 2023. "Do subsidies matter in productivity and profitability changes?," Economic Modelling, Elsevier, vol. 123(C).
    10. Yangseon Kim & Peter Schmidt, 2000. "A Review and Empirical Comparison of Bayesian and Classical Approaches to Inference on Efficiency Levels in Stochastic Frontier Models with Panel Data," Journal of Productivity Analysis, Springer, vol. 14(2), pages 91-118, September.
    11. 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.
    12. Maria Raimondo & Francesco Caracciolo & Concetta Nazzaro & Giuseppe Marotta, 2021. "Organic Farming Increases the Technical Efficiency of Olive Farms in Italy," Agriculture, MDPI, vol. 11(3), pages 1-15, March.
    13. Mark Brady & Konrad Kellermann & Christoph Sahrbacher & Ladislav Jelinek, 2009. "Impacts of Decoupled Agricultural Support on Farm Structure, Biodiversity and Landscape Mosaic: Some EU Results," Journal of Agricultural Economics, Wiley Blackwell, vol. 60(3), pages 563-585, September.
    14. Henry Kaiser, 1974. "An index of factorial simplicity," Psychometrika, Springer;The Psychometric Society, vol. 39(1), pages 31-36, March.
    15. Sneessens, Inès & Sauvée, Loïc & Randrianasolo-Rakotobe, Hanitra & Ingrand, Stéphane, 2019. "A framework to assess the economic vulnerability of farming systems: Application to mixed crop-livestock systems," Agricultural Systems, Elsevier, vol. 176(C).
    16. 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.
    17. Anna Gaviglio & Rosalia Filippini & Fabio Albino Madau & Maria Elena Marescotti & Eugenio Demartini, 2021. "Technical efficiency and productivity of farms: a periurban case study analysis," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 9(1), pages 1-18, December.
    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. Thomas Slijper & Yann de Mey & P Marijn Poortvliet & Miranda P M Meuwissen, 2022. "Quantifying the resilience of European farms using FADN," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 49(1), pages 121-150.
    2. William Griffiths & Xiaohui Zhang & Xueyan Zhao, 2010. "A Stochastic Frontier Model for Discrete Ordinal Outcomes: A Health Production Function," Department of Economics - Working Papers Series 1092, The University of Melbourne.
    3. William Griffiths & Xiaohui Zhang & Xueyan Zhao, 2014. "Estimation and efficiency measurement in stochastic production frontiers with ordinal outcomes," Journal of Productivity Analysis, Springer, vol. 42(1), pages 67-84, August.
    4. Lundgren, Tommy & Marklund, Per-Olov & Zhang, Shanshan, 2016. "Industrial energy demand and energy efficiency – Evidence from Sweden," Resource and Energy Economics, Elsevier, vol. 43(C), pages 130-152.
    5. Hanousek, Jan & Kočenda, Evžen & Shamshur, Anastasiya, 2015. "Corporate efficiency in Europe," Journal of Corporate Finance, Elsevier, vol. 32(C), pages 24-40.
    6. Deng, Yaguo, 2024. "A Bayesian semi-parametric approach to stochastic frontier models with inefficiency heterogeneity," DES - Working Papers. Statistics and Econometrics. WS 43837, Universidad Carlos III de Madrid. Departamento de Estadística.
    7. Stefano Mainardi, 2021. "Parametric and Semiparametric Efficiency Frontiers in Fishery Analysis: Overview and Case Study on the Falkland Islands," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 79(2), pages 169-210, June.
    8. Radha R. Ashrit, 2023. "Estimation of technical efficiency of Indian farms for major crops during 2013–2014 and 2017–2018: a stochastic Frontier production approach," SN Business & Economics, Springer, vol. 3(2), pages 1-32, February.
    9. Xie, Bai-Chen & Ni, Kang-Kang & O'Neill, Eoghan & Li, Hong-Zhou, 2021. "The scale effect in China's power grid sector from the perspective of malmquist total factor productivity analysis," Utilities Policy, Elsevier, vol. 69(C).
    10. Astrid Cullmann & Christian von Hirschhausen, 2007. "From Transition to Competition: Dynamic Efficiency Analysis of Polish Electricity Distribution Companies," Discussion Papers of DIW Berlin 716, DIW Berlin, German Institute for Economic Research.
    11. Liu, Fengqin & Sim, Jae-yeon & Sun, Huaping & Edziah, Bless Kofi & Adom, Philip Kofi & Song, Shunfeng, 2023. "Assessing the role of economic globalization on energy efficiency: Evidence from a global perspective," China Economic Review, Elsevier, vol. 77(C).
    12. Honma, Satoshi & Ushifusa, Yoshiaki & Okamura, Soyoka & Vandercamme, Lilu, 2023. "Measuring carbon emissions performance of Japan's metal industry: Energy inputs, agglomeration, and the potential for green recovery reduction," Resources Policy, Elsevier, vol. 82(C).
    13. Alejandro Arvelo-Martín & Juan José Díaz-Hernández & Ignacio Abásolo-Alessón, 2019. "Hospital productivity bias when not adjusting for cost heterogeneity: The case of Spain," PLOS ONE, Public Library of Science, vol. 14(6), pages 1-17, June.
    14. Birara Endalew & Adugnaw Anteneh & Kassahun Tasie, 2022. "Technical Efficiency of Teff Production Among Smallholder Farmers: Beta Regression Approach," The European Journal of Development Research, Palgrave Macmillan;European Association of Development Research and Training Institutes (EADI), vol. 34(2), pages 1076-1096, April.
    15. Graziella Bonanno & Annalisa Ferrando & Stefania Patrizia Sonia Rossi, 2023. "Do innovation and financial constraints affect the profit efficiency of European enterprises?," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 13(1), pages 57-86, March.
    16. Liu, Rui & Lopez Barrera, Emiliano, 2024. "Socioeconomic Drivers of Food Waste Over Time: A Comparative Evaluation of Panel Stochastic Frontier Models for Indirect Quantification in Chinese Households," 2024 Annual Meeting, July 28-30, New Orleans, LA 343852, Agricultural and Applied Economics Association.
    17. Barros, Carlos Pestana & Williams, Jonathan, 2013. "The random parameters stochastic frontier cost function and the effectiveness of public policy: Evidence from bank restructuring in Mexico," International Review of Financial Analysis, Elsevier, vol. 30(C), pages 98-108.
    18. López-Bermúdez, Beatriz & Freire-Seoane, María Jesús & Nieves-Martínez, Diego José, 2019. "Port efficiency in Argentina from 2012 to 2017: An ally for sustained economic growth," Utilities Policy, Elsevier, vol. 61(C).
    19. Ceyhun Elgin & Selman Çakır, 2015. "Technological progress and scientific indicators: a panel data analysis," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 24(3), pages 263-281, April.
    20. Goddard, John & Molyneux, Philip & Williams, Jonathan, 2014. "Dealing with cross-firm heterogeneity in bank efficiency estimates: Some evidence from Latin America," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 130-142.

    More about this item

    Keywords

    Production Economics; Productivity Analysis; Research Methods/ Statistical Methods;
    All these keywords.

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:ags:cfcp15:344256. 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: AgEcon Search (email available below). General contact details of provider: https://iaae-agecon.org/ .

    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.