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Water governance matters: Self-supplied versus collective irrigation services and their impact on technical efficiency and production in olive oil farming

Author

Listed:
  • Russo, S.
  • Mirra, L.
  • Caracciolo, F.
  • Giannoccaro, G.

Abstract

This study examines the impact of irrigation water services in shaping the economic performance of olive farms, with particular attention to their effects on production variability and technical efficiency. Employing a stochastic frontier analysis, we evaluate how different modes of irrigation service provision (self-supplied versus collective) affect farm-level outcomes. The empirical analysis is based on 954 observations from the Farm Accountancy Data Network, covering olive farms in Apulia, Italy’s principal olive-producing region, over the 2016–2019 period. The findings point out that self-supplied irrigation is associated with lower variability in both output and technical efficiency, reflecting greater reliability of water service. Conversely, farms relying on collective irrigation services experience higher variability in technical efficiency. These results highlight the importance of targeted policy interventions aimed at enhancing the reliability of collective irrigation services, also integrating current water allocation mechanisms with pricing differentiation policy.

Suggested Citation

  • Russo, S. & Mirra, L. & Caracciolo, F. & Giannoccaro, G., 2026. "Water governance matters: Self-supplied versus collective irrigation services and their impact on technical efficiency and production in olive oil farming," Agricultural Water Management, Elsevier, vol. 324(C).
    • Handle: RePEc:eee:agiwat:v:324:y:2026:i:c:s0378377426000296
    DOI: 10.1016/j.agwat.2026.110148
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    1. Zema, Demetrio Antonio & Nicotra, Angelo & Mateos, Luciano & Zimbone, Santo Marcello, 2018. "Improvement of the irrigation performance in Water Users Associations integrating data envelopment analysis and multi-regression models," Agricultural Water Management, Elsevier, vol. 205(C), pages 38-49.
    2. Ali, M.H. & Talukder, M.S.U., 2008. "Increasing water productivity in crop production--A synthesis," Agricultural Water Management, Elsevier, vol. 95(11), pages 1201-1213, November.
    3. 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.
    4. Giacomo Giannoccaro & Laura Mirra & Simone Russo & Luigi Roselli & Bernardo C. Gennaro, 2024. "Valuing Cost of Groundwater Overexploitation: Evidences from Apulian Land Values," Springer Proceedings in Business and Economics, in: Alessio Cavicchi & Francesco Caracciolo & Maria Crescimanno & Maria De Salvo & Antonino Galati & Ant (ed.), Innovation and Knowledge in Agri-food and Environmental Systems, pages 53-57, Springer.
    5. Ivan Portoghese & Raffaella Matarrese & Laura Mirra & Giacomo Giannoccaro, 2025. "Assimilating Farmers’ Behaviour in the Development of an ET-Based Irrigation Water-Accounting Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 39(14), pages 7749-7774, November.
    6. Gebru, Menasbo & Tadesse, Tewodros & Berhe, Melaku, 2025. "Reliability of irrigation water and farm-level productivity: Evidence from semi-arid farming systems in northern Ethiopia," Agricultural Systems, Elsevier, vol. 223(C).
    7. Subal Kumbhakar & Gudbrand Lien & J. Hardaker, 2014. "Technical efficiency in competing panel data models: a study of Norwegian grain farming," Journal of Productivity Analysis, Springer, vol. 41(2), pages 321-337, April.
    8. Fernández, J.E. & Alcon, F. & Diaz-Espejo, A. & Hernandez-Santana, V. & Cuevas, M.V., 2020. "Water use indicators and economic analysis for on-farm irrigation decision: A case study of a super high density olive tree orchard," Agricultural Water Management, Elsevier, vol. 237(C).
    9. Sébastien Foudi & Katrin Erdlenbruch, 2012. "The role of irrigation in farmers’ risk management strategies in France," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 39(3), pages 439-457, July.
    10. Caudill, Steven B. & Ford, Jon M., 1993. "Biases in frontier estimation due to heteroscedasticity," Economics Letters, Elsevier, vol. 41(1), pages 17-20.
    11. Federico Belotti & Silvio Daidone & Giuseppe Ilardi & Vincenzo Atella, 2013. "Stochastic frontier analysis using Stata," Stata Journal, StataCorp LLC, vol. 13(4), pages 718-758, December.
    12. Bruce A. Babcock & David A. Hennessy, 1996. "Input Demand under Yield and Revenue Insurance," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 78(2), pages 416-427.
    13. Ruggiero Sardaro & Piermichele La Sala, 2020. "The technical efficiency of the Apulian winegrowing farms with different irrigation water supply systems," Economia agro-alimentare, FrancoAngeli Editore, vol. 22(2), pages 1-24.
    14. Dolores Rey & Carlos Dionisio Pérez-Blanco & Alvar Escriva-Bou & Corentin Girard & Ted I. E. Veldkamp, 2019. "Role of economic instruments in water allocation reform: lessons from Europe," International Journal of Water Resources Development, Taylor & Francis Journals, vol. 35(2), pages 206-239, March.
    15. Richard Damania, 2020. "The economics of water scarcity and variability," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 36(1), pages 24-44.
    16. Hadri, Kaddour, 1999. "Estimation of a Doubly Heteroscedastic Stochastic Frontier Cost Function," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(3), pages 359-363, July.
    17. Raushan Bokusheva & Lukáš Čechura & Subal C. Kumbhakar, 2023. "Estimating persistent and transient technical efficiency and their determinants in the presence of heterogeneity and endogeneity," Journal of Agricultural Economics, Wiley Blackwell, vol. 74(2), pages 450-472, June.
    18. Caudill, Steven B & Ford, Jon M & Gropper, Daniel M, 1995. "Frontier Estimation and Firm-Specific Inefficiency Measures in the Presence of Heteroscedasticity," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(1), pages 105-111, January.
    19. Salam, Md. Abdus & Rahman, Sanzidur & Anik, Asif Reza & Sharna, Shaima Chowdhury, 2023. "Exploring competitiveness of surface water versus ground water irrigation and their impacts on rice productivity and efficiency: An empirical analysis from Bangladesh," Agricultural Water Management, Elsevier, vol. 283(C).
    20. Hung-Jen Wang, 2002. "Heteroscedasticity and Non-Monotonic Efficiency Effects of a Stochastic Frontier Model," Journal of Productivity Analysis, Springer, vol. 18(3), pages 241-253, November.
    21. Hung-jen Wang & Peter Schmidt, 2002. "One-Step and Two-Step Estimation of the Effects of Exogenous Variables on Technical Efficiency Levels," Journal of Productivity Analysis, Springer, vol. 18(2), pages 129-144, September.
    22. Portoghese, Ivan & Giannoccaro, Giacomo & Giordano, Raffaele & Pagano, Alessandro, 2021. "Modeling the impacts of volumetric water pricing in irrigation districts with conjunctive use of surface and groundwater resources," Agricultural Water Management, Elsevier, vol. 244(C).
    23. Pereira, Helga & Marques, Rui Cunha, 2017. "An analytical review of irrigation efficiency measured using deterministic and stochastic models," Agricultural Water Management, Elsevier, vol. 184(C), pages 28-35.
    24. Laura Mirra & Bernardo Corrado de Gennaro & Giacomo Giannoccaro, 2021. "Farmer Evaluation of Irrigation Services. Collective or Self-Supplied?," Land, MDPI, vol. 10(4), pages 1-15, April.
    25. 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.
    26. Marta Ellena & Roberta Padulano & Paola Mercogliano, 2025. "Influence of climate change on irrigation demand: insights from one of the most agricultural regions in Italy (Puglia)," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 121(9), pages 10043-10058, May.
    27. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
    28. 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.
    29. Dan Rigby & Francisco Alcon & Michael Burton, 2010. "Supply uncertainty and the economic value of irrigation water," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 37(1), pages 97-117, March.
    30. Goutam Konapala & Ashok K. Mishra & Yoshihide Wada & Michael E. Mann, 2020. "Climate change will affect global water availability through compounding changes in seasonal precipitation and evaporation," Nature Communications, Nature, vol. 11(1), pages 1-10, December.
    31. Simone Russo & Francesco Caracciolo & Cristina Salvioni, 2022. "Effects of Insurance Adoption and Risk Aversion on Agricultural Production and Technical Efficiency: A Panel Analysis for Italian Grape Growers," Economies, MDPI, vol. 10(1), pages 1-17, January.
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    Keywords

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    JEL classification:

    • 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
    • Q25 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Water
    • Q28 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Government Policy

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