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Calibration of agricultural risk programming models

Author

Listed:
  • Athanasios Petsakos

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

  • Stelios Rozakis

    (Department of Agricultural Economics and Rural Development - Agricultural University of Athens)

Abstract

Positive Mathematical Programming (PMP) is one of the most commonly used methods for calibrating activity programming models. In this article we consider PMP as a calibration method for risk programming models with a mean-variance (E-V) specification. We argue that the restrictive theoretical assumptions employed by typical linear E-V models limit their applicability in analyzing the effects of decoupled payments on agricultural production decisions. Furthermore, the requirement for eliciting a risk aversion coefficient renders such models incompatible with the PMP method. For this reason we propose a nonlinear E-V specification and develop a PMP-based procedure for its calibration which does not aim at introducing (further) nonlinearities in the objective function, but at recovering the "true" distribution of wealth that will allow the final model to reproduce base year observations. We also examine how our approach relates to the recent PMP developments on calibration against elasticity priors and we show how such priors can be used for the calibration of the nonlinear E-V model.

Suggested Citation

  • Athanasios Petsakos & Stelios Rozakis, 2015. "Calibration of agricultural risk programming models," Post-Print hal-01173062, HAL.
    • Handle: RePEc:hal:journl:hal-01173062
    DOI: 10.1016/j.ejor.2014.10.018
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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. Britz, Wolfgang & Arata, Linda, 2016. "How important are crop shares in managing risk for specialized arable farms? A panel estimation of a programming model for three European regions," 2016 Fifth AIEAA Congress, June 16-17, 2016, Bologna, Italy 242316, Italian Association of Agricultural and Applied Economics (AIEAA).
    3. Francisco Fernández & Roberto Ponce & Maria Blanco & Diego Rivera & Felipe Vásquez, 2016. "Water Variability and the Economic Impacts on Small-Scale Farmers. A Farm Risk-Based Integrated Modelling Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(4), pages 1357-1373, March.
    4. Xuan Liu & Gerrit Cornelis van Kooten & Jun Duan, 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), pages 795-817, July.
    5. Ciaian, Pavel & Espinosa, Maria & Louhichi, Kamel & Perni, Angel, . "Farm Level Impacts of Trade Liberalisation and CAP Removal Across EU: An Assessment using the IFM-CAP Model," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 69(2).
    6. Liu, Xuan & Duan, Jun & van Kooten, G. Cornelis, 2015. "An Evaluation of the Effects of Changes in the AgriStability Program on Producers’ Crop Activities: A Farm Modeling Approach," Working Papers 201654, University of Victoria, Resource Economics and Policy.
    7. Petsakos, Athanasios & Rozakis, Stelios, 2022. "Models and muddles: comment on ‘Calibration of agricultural risk programming models using positive mathematical programming’," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 66(03), January.
    8. de Frutos Cachorro, Julia & Gobin, Anne & Buysse, Jeroen, 2018. "Farm-level adaptation to climate change: The case of the Loam region in Belgium," Agricultural Systems, Elsevier, vol. 165(C), pages 164-176.
    9. Ciaian, Pavel & Espinosa, Maria & Louhichi, Kamel & Perni, Angel & Gomez y Paloma, Sergio, "undated". "Farm level impacts of abolishing the CAP direct payments: An assessment using the IFM-CAP model," 162nd Seminar, April 26-27, 2018, Budapest, Hungary 272087, European Association of Agricultural Economists.
    10. Robert, Marion & Bergez, Jacques-Eric & Thomas, Alban, 2018. "A stochastic dynamic programming approach to analyze adaptation to climate change – Application to groundwater irrigation in India," European Journal of Operational Research, Elsevier, vol. 265(3), pages 1033-1045.
    11. Parisa Aghajanzadeh-Darzi & Pierre-Alain Jayet & Athanasios Petsakos, 2017. "Improvement of a Bio-Economic Mathematical Programming Model in the Case of On-Farm Source Inputs and Outputs," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 15(3), pages 489-508, September.
    12. 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.
    13. Xuan Liu & Jun Duan & G. Cornelis van Kooten, 2018. "The impact of changes in the AgriStability program on crop activities: A farm modeling approach," Agribusiness, John Wiley & Sons, Ltd., vol. 34(3), pages 650-667, June.
    14. Gómez-Limón, José A. & Gutiérrez-Martín, Carlos & Riesgo, Laura, 2016. "Modeling at farm level: Positive Multi-Attribute Utility Programming," Omega, Elsevier, vol. 65(C), pages 17-27.
    15. Esther Boere & G. Cornelis van Kooten, 2015. "Reforming the Common Agricultural Policy: Decoupling Agricultural Payments from Production and Promoting the Environment," Working Papers 2015-01, University of Victoria, Department of Economics, Resource Economics and Policy Analysis Research Group.
    16. Purola, Tuomo & Lehtonen, Heikki, 2020. "Evaluating profitability of soil-renovation investments under crop rotation constraints in Finland," Agricultural Systems, Elsevier, vol. 180(C).
    17. Kamel Louhichi & Daël Merisier, 2023. "Potential impacts of the Income Stabilisation Tool on farmers' income and crop diversity: a French case study [Impacts potentiels de l'outil de stabilisation des revenus sur les revenus des agriculteurs et la diversité des cultures : une étude de ," Post-Print hal-04195630, HAL.
    18. Kamel Louhichi & Daël Merisier, 2024. "Potential impacts of the Common Agricultural Policy's Income Stabilisation Tool on farmers' incomes and crop diversity: A French case study," Journal of Agricultural Economics, Wiley Blackwell, vol. 75(2), pages 716-739, June.
    19. Qiuzhuo Ma & Krishna P Paudel & Liting Gu & Xiaowei Wen, 2018. "An application of a cardinality-constrained multiple benchmark tracking error model on a plant enterprise selection problem," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 45(5), pages 677-721.
    20. Kamel Louhichi & Pavel Ciaian & Maria Espinosa & Angel Perni & Sergio Gomez y Paloma, 2018. "Economic impacts of CAP greening: application of an EU-wide individual farm model for CAP analysis (IFM-CAP)," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 45(2), pages 205-238.

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