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Modeling farmer participation to a revenue insurance scheme by means of Positive Mathematical Programming

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  • Severini, Simone
  • Cortignani, Raffaele

Abstract

European farmers face increasing income uncertainty and the debate is growing on the role of insurance schemes and of public support in this field. This debate is further stimulated by the perspective of introducing instruments to cope with risk also in the Common Agricultural Policy. Therefore, there is a need for empirical analysis and tools aimed at providing empirical evidences on this subject. This paper applies a PMP modelling approach that takes into explicit consideration risk aversion behaviour to test the possibility to use it to assess the implications of participating in a insurance scheme. This is done by introducing a revenue insurance scheme into a model developed on a small group of crop farms in Italy. In particular, a quadratic mix integer programming approach has been developed in order to model the choice of participating or not in the proposed insurance scheme. The model has been than used to conduct simulations considering changes in the level of the insurance premium. The paper tries to assess the soundness of the proposed approach and to identify its limitations. The obtained results suggest that this could be a useful tool to investigate the impact of participating in insurance schemes on production patterns and farm profitability and the role of public support in this field.

Suggested Citation

  • Severini, Simone & Cortignani, Raffaele, 2011. "Modeling farmer participation to a revenue insurance scheme by means of Positive Mathematical Programming," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 116001, European Association of Agricultural Economists.
    • Handle: RePEc:ags:eaae11:116001
    DOI: 10.22004/ag.econ.116001
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    References listed on IDEAS

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    1. Severini, Simone & Cortignani, Raffaele, 2011. "An attempt to modelling revenue insurance schemes at the farm level by means of Positive Mathematical Programming," 122nd Seminar, February 17-18, 2011, Ancona, Italy 99431, European Association of Agricultural Economists.
    2. Moschini, Giancarlo & Hennessy, David A., 2001. "Uncertainty, risk aversion, and risk management for agricultural producers," Handbook of Agricultural Economics, in: B. L. Gardner & G. C. Rausser (ed.), Handbook of Agricultural Economics, edition 1, volume 1, chapter 2, pages 88-153, Elsevier.
    3. Hansen, Kristiana & Frahan, Bruno Henry de, 2010. "Risk in Agriculture: Modeling Revenue Insurance for Crop Farms in Belgium," 2010 Annual Meeting, July 25-27, 2010, Denver, Colorado 61535, Agricultural and Applied Economics Association.
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    Cited by:

    1. Basnet, Shyam Kumar & Jansson , Torbjorn & Heckelei, Thomas, 2021. "A Bayesian econometrics and risk programming approach for analysing the impact of decoupled payments in the European Union," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 65(03), January.
    2. Wolfgang Britz & Linda Arata, 2019. "Econometric mathematical programming: an application to the estimation of costs and risk preferences at farm level," Agricultural Economics, International Association of Agricultural Economists, vol. 50(2), pages 191-206, March.
    3. Britz, Wolfgang & Linda, Arata, "undated". "How Important Are Crop Shares In Managing Risk For Specialized Arable Farms? A Panel Estimation Of A Programming Model For Three European Regions," 56th Annual Conference, Bonn, Germany, September 28-30, 2016 244801, German Association of Agricultural Economists (GEWISOLA).
    4. Zgajnar, Jaka, 2014. "Simulation model for income risk analyses at the sector level, case of Slovenia," 2014 International Congress, August 26-29, 2014, Ljubljana, Slovenia 186381, European Association of Agricultural Economists.
    5. Jansson, Torbjörn & Heckelei, Thomas & Gocht, Alexander & Basnet, Shyam Kumar & Zhang, Yinan & Neuenfeldt, Sebastian, 2014. "Analysing impacts of changing price variability with estimated farm risk-programming models," 2014 International Congress, August 26-29, 2014, Ljubljana, Slovenia 182665, European Association of Agricultural Economists.
    6. Liu, Xuan & van Kooten, Gerrit Cornelis & Duan, Jun, 2020. "Calibration of agricultural risk programming models using positive mathematical programming," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 64(3), July.
    7. Heckelei, Thomas & Britz, Wolfgang & Zhang, Yinan, 2012. "Positive Mathematical Programming Approaches – Recent Developments in Literature and Applied Modelling," Bio-based and Applied Economics Journal, Italian Association of Agricultural and Applied Economics (AIEAA), vol. 1(1), pages 1-16, April.
    8. Arfini, Filippo & Donati, Michele & Marongiu, Sonia & Cesaro, Luca, 2012. "Farm production costs estimation trough PMP Models: an application in three Italian Regions," 2012 First Congress, June 4-5, 2012, Trento, Italy 124117, Italian Association of Agricultural and Applied Economics (AIEAA).
    9. Kamel Elouhichi & Maria Espinosa Goded & Pavel Ciaian & Angel Perni Llorente & Bouda Vosough Ahmadi & Liesbeth Colen & Sergio Gomez Y Paloma, 2018. "The EU-Wide Individual Farm Model for Common Agricultural Policy Analysis (IFM-CAP v.1): Economic Impacts of CAP Greening," JRC Research Reports JRC108693, Joint Research Centre.

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    Keywords

    Farm Management; Risk and Uncertainty;

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