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Assessing the Forecasting Performance of a Generic Bio-Economic Farm Model Calibrated With Two Different PMP Variants

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  • Argyris Kanellopoulos
  • Paul Berentsen
  • Thomas Heckelei
  • Martin van Ittersum
  • Alfons Oude Lansink

Abstract

"Using linear programming in bio-economic farm modelling often results in overspecialised model solutions. The positive mathematical programming (PMP) approach guarantees exact calibration to base year data but the forecasting capacity of the model is affected by necessary but arbitrary assumptions imposed during calibration. In this article, a new PMP variant is presented which is based on less arbitrary assumptions that, from a theoretical point of view, are closer to the actual decision making of the farmer. The PMP variant is evaluated according to the predictions of the bio-economic farm model, developed within the framework for integrated assessment of agricultural systems in Europe (SEAMLESS). The forecasting capacity of the model calibrated with the standard PMP approach and the alternative PMP variant, respectively, is tested in ex-post experiments for the arable farm types of Flevoland (the Netherlands) and Midi-Pyrenees (France). The results of the ex-post experiments, in which we try to simulate farm responses in 2003 using a model calibrated to 1999 data, show that the alternative PMP variant improves the forecasting capacity of the model in all tested cases." Copyright (c) 2010 The Authors. Journal compilation (c) 2010 The Agricultural Economics Society.

Suggested Citation

  • Argyris Kanellopoulos & Paul Berentsen & Thomas Heckelei & Martin van Ittersum & Alfons Oude Lansink, 2010. "Assessing the Forecasting Performance of a Generic Bio-Economic Farm Model Calibrated With Two Different PMP Variants," Journal of Agricultural Economics, Wiley Blackwell, vol. 61(2), pages 274-294.
    • Handle: RePEc:bla:jageco:v:61:y:2010:i:2:p:274-294
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    References listed on IDEAS

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    2. Britz, Wolfgang & van Ittersum, Martin K. & Oude Lansink, Alfons G.J.M. & Heckelei, Thomas, 2012. "Tools for Integrated Assessment in Agriculture. State of the Art and Challenges," Bio-based and Applied Economics Journal, Italian Association of Agricultural and Applied Economics (AIEAA), issue 2, August.
    3. Egbendewe-Mondzozo, Aklesso & Swinton, Scott M. & Izaurralde, R. Cesar & Manowitz, David H. & Zhang, Xuesong, 2012. "Maintaining Environmental Quality while Expanding Energy Biomass Production: Policy Simulations from Michigan, USA," 2012 Conference, August 18-24, 2012, Foz do Iguacu, Brazil 126749, International Association of Agricultural Economists.
    4. Egbendewe-Mondzozo, Aklesso & Swinton, Scott M. & Izaurralde, R. Cesar & Manowitz, David H. & Zhang, Xuesong, 2010. "Biomass Supply from Alternative Cellulosic Crops and Crop Residues: A Preliminary Spatial Bioeconomic Modeling Approach," Staff Papers 98277, Michigan State University, Department of Agricultural, Food, and Resource Economics.
    5. Garnache, Cloe & Merel, Pierre R., 2011. "Calibrating a regional PMP model of agricultural supply under multiple constraints: a set of matryoshka doll conditions," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 114630, European Association of Agricultural Economists.
    6. Louhichi, Kamel & Flichman, Guillermo & Blanco Fonseca, Maria, 2009. "A generic template for FSSIM," Reports 57463, SEAMLESS: System for Environmental and Agricultural Modelling, Linking European Science and Society.
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    8. He, Lixia & Horbulyk, Theodore M. & Ali, Md. Kamar & Le Roy, Danny G. & Klein, K.K., 2012. "Proportional water sharing vs. seniority-based allocation in the Bow River basin of Southern Alberta," Agricultural Water Management, Elsevier, vol. 104(C), pages 21-31.
    9. Jeder, Houcine & Sghaier, Mongi & Louhichi, Kamel & Reidsma, Pytrik, 2014. "Bio-economic modelling to assess the impact of water pricing policies at the farm level in the Oum Zessar watershed, southern Tunisia," Agricultural Economics Review, Greek Association of Agricultural Economists, vol. 15(2), June.
    10. Louhichi, Kamel & Kanellopoulos, Argyris & Janssen, Sander & Flichman, Guillermo & Blanco, Maria & Hengsdijk, Huib & Heckelei, Thomas & Berentsen, Paul & Lansink, Alfons Oude & Ittersum, Martin Van, 2010. "FSSIM, a bio-economic farm model for simulating the response of EU farming systems to agricultural and environmental policies," Agricultural Systems, Elsevier, vol. 103(8), pages 585-597, October.
    11. Petsakos, Athanasios & Rozakis, Stelios, 2015. "Calibration of agricultural risk programming models," European Journal of Operational Research, Elsevier, vol. 242(2), pages 536-545.
    12. 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), issue 1, April.
    13. Egbendewe-Mondzozo, Aklesso & Swinton, Scott M. & Izaurralde, R. César & Manowitz, David H. & Zhang, Xuesong, 2013. "Maintaining environmental quality while expanding biomass production: Sub-regional U.S. policy simulations," Energy Policy, Elsevier, vol. 57(C), pages 518-531.
    14. Chopin, Pierre & Doré, Thierry & Guindé, Loïc & Blazy, Jean-Marc, 2015. "MOSAICA: A multi-scale bioeconomic model for the design and ex ante assessment of cropping system mosaics," Agricultural Systems, Elsevier, vol. 140(C), pages 26-39.
    15. Gunter, Allison & Goemans, Chris & Pritchett, James G. & Thilmany, Dawn D., 2012. "Linking an Equilibrium Displacement Mathematical Programming Model and an Input-Output Model to Estimate the Impacts of Drought: An Application to Southeast Colorado," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 124930, Agricultural and Applied Economics Association.
    16. Skevas, T. & Swinton, S.M. & Meehan, T.D. & Kim, T.N. & Gratton, C. & Egbendewe-Mondzozo, A., 2014. "Integrating agricultural pest biocontrol into forecasts of energy biomass production," Ecological Economics, Elsevier, vol. 106(C), pages 195-203.
    17. Arfini, Filippo & Donati, Michele & Marongiu, Sonia & Cesaro, Luca, 2012. "Farm production costs estimation trough PMP Models: an application in three Italian Regions," Congress Papers 124117, Italian Association of Agricultural and Applied Economics (AIEAA).
    18. Christian Schader & Jürn Sanders & Thomas Nemecek & Nic Lampkin & Matthias Stolze, 2008. "A Modelling Approach for Evaluating Agri-Environmental Policies at Sector Level," Journal of Socio-Economics in Agriculture (Until 2015: Yearbook of Socioeconomics in Agriculture), Swiss Society for Agricultural Economics and Rural Sociology, vol. 1(1), pages 93-132.
    19. Mack, Gabriele & Ferjani, Ali & Mohring, Anke & Zimmerman, Albert & Mann, Stefan, 2015. "How did farmers act? An ex-post validation of normative and positive mathematical programming for an agent-based sector model," 2015 Conference, August 9-14, 2015, Milan, Italy 212201, International Association of Agricultural Economists.
    20. Leite, João Guilherme Dal Belo & Silva, João Vasco & van Ittersum, Martin K., 2014. "Integrated assessment of biodiesel policies aimed at family farms in Brazil," Agricultural Systems, Elsevier, vol. 131(C), pages 64-76.
    21. Aurbacher, Joachim & Parker, Phillip S. & Calberto Sánchez, Germán A. & Steinbach, Jennifer & Reinmuth, Evelyn & Ingwersen, Joachim & Dabbert, Stephan, 2013. "Influence of climate change on short term management of field crops – A modelling approach," Agricultural Systems, Elsevier, vol. 119(C), pages 44-57.

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