IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v242y2015i2p536-545.html
   My bibliography  Save this article

Calibration of agricultural risk programming models

Author

Listed:
  • Petsakos, Athanasios
  • Rozakis, Stelios

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

  • Petsakos, Athanasios & Rozakis, Stelios, 2015. "Calibration of agricultural risk programming models," European Journal of Operational Research, Elsevier, vol. 242(2), pages 536-545.
    • Handle: RePEc:eee:ejores:v:242:y:2015:i:2:p:536-545
    DOI: 10.1016/j.ejor.2014.10.018
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S037722171400839X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ejor.2014.10.018?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
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Kutcher, Gary P. & Norton, Roger D., 1982. "Operations research methods in agricultural policy analysis," European Journal of Operational Research, Elsevier, vol. 10(4), pages 333-345, August.
    2. Torbjörn Jansson & Thomas Heckelei, 2011. "Estimating a Primal Model of Regional Crop Supply in the European Union," Journal of Agricultural Economics, Wiley Blackwell, vol. 62(1), pages 137-152, February.
    3. Thomas Heckelei & Hendrik Wolff, 2003. "Estimation of constrained optimisation models for agricultural supply analysis based on generalised maximum entropy," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 30(1), pages 27-50, March.
    4. 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.
    5. 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, June.
    6. Richard E. Howitt, 1995. "Positive Mathematical Programming," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 77(2), pages 329-342.
    7. Octavio A. Ramirez & Sukant Misra & James Field, 2003. "Crop-Yield Distributions Revisited," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 85(1), pages 108-120.
    8. Levy, Haim & Levy, Moshe, 2014. "The benefits of differential variance-based constraints in portfolio optimization," European Journal of Operational Research, Elsevier, vol. 234(2), pages 372-381.
    9. Sandmo, Agnar, 1971. "On the Theory of the Competitive Firm under Price Uncertainty," American Economic Review, American Economic Association, vol. 61(1), pages 65-73, March.
    10. Teresa Serra & David Zilberman & Barry K. Goodwin & Allen Featherstone, 2006. "Effects of decoupling on the mean and variability of output," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 33(3), pages 269-288, September.
    11. David R. Just & Hikaru Hanawa Peterson, 2010. "Is Expected Utility Theory Applicable? A Revealed Preference Test," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 92(1), pages 16-27.
    12. Alexandre Gohin & Frédéric Chantreuil, 1999. "La programmation mathématique positive dans les modèles d'exploitation agricole : Principes et importance du calibrage," Cahiers d'Economie et Sociologie Rurales, INRA Department of Economics, vol. 52, pages 59-78.
    13. Quirino Paris & Richard E. Howitt, 1998. "An Analysis of Ill-Posed Production Problems Using Maximum Entropy," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 80(1), pages 124-138.
    14. Richard E. Howitt, 1995. "A Calibration Method For Agricultural Economic Production Models," Journal of Agricultural Economics, Wiley Blackwell, vol. 46(2), pages 147-159, May.
    15. John M. Antle, 1983. "Incorporating Risk in Production Analysis," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 65(5), pages 1099-1106.
    16. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
    17. Best, Michael J & Grauer, Robert R, 1991. "On the Sensitivity of Mean-Variance-Efficient Portfolios to Changes in Asset Means: Some Analytical and Computational Results," Review of Financial Studies, Society for Financial Studies, vol. 4(2), pages 315-342.
    18. Tsiang, S C, 1972. "The Rationale of the Mean-Standard Deviation Analysis, Skewness Preference, and the Demand for Money," American Economic Review, American Economic Association, vol. 62(3), pages 354-371, June.
    19. Caputo, Michael R. & Paris, Quirino, 2008. "Comparative statics of the generalized maximum entropy estimator of the general linear model," European Journal of Operational Research, Elsevier, vol. 185(1), pages 195-203, February.
    20. Antle, John M., 1983. "Incorporating Risk In Production Analysis," 1983 Annual Meeting, July 31-August 3, West Lafayette, Indiana 279106, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    21. David A. Hennessy, 1998. "The Production Effects of Agricultural Income Support Policies under Uncertainty," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 80(1), pages 46-57.
    22. Lawrence B. Pulley, 1983. "Mean-Variance Approximations to Expected Logarithmic Utility," Operations Research, INFORMS, vol. 31(4), pages 685-696, August.
    23. Pierre Mérel & Santiago Bucaram, 2010. "Exact calibration of programming models of agricultural supply against exogenous supply elasticities," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 37(3), pages 395-418, September.
    24. Thomas B. Wiens, 1976. "Peasant Risk Aversion and Allocative Behavior: A Quadratic Programming Experiment," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 58(4_Part_1), pages 629-635.
    25. Golan, Amos & Judge, George & Perloff, Jeffrey, 1997. "Estimation and inference with censored and ordered multinomial response data," Journal of Econometrics, Elsevier, vol. 79(1), pages 23-51, July.
    26. Yves Léon & Ludo Peeters & Maurice Quinqu & Yves Surry, 1999. "The use of maximum entropy to estimate input-output coefficients from regional farm accounting data," Post-Print hal-01931589, HAL.
    27. Levy, H & Markowtiz, H M, 1979. "Approximating Expected Utility by a Function of Mean and Variance," American Economic Review, American Economic Association, vol. 69(3), pages 308-317, June.
    28. Yves Léony & Ludo Peeters & Maurice Quinqu & Yves Surry, 1999. "The Use of Maximum Entropy to Estimate Input‐Output Coefficients From Regional Farm Accounting Data," Journal of Agricultural Economics, Wiley Blackwell, vol. 50(3), pages 425-439, September.
    29. Quirino Paris, 1979. "Revenue and Cost Uncertainty, Generalized Mean-Variance, and the Linear Complementarity Problem," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 61(2), pages 268-275.
    30. Gomez-Limon, Jose A. & Arriaza, Manuel & Riesgo, Laura, 2003. "An MCDM analysis of agricultural risk aversion," European Journal of Operational Research, Elsevier, vol. 151(3), pages 569-585, December.
    31. Pierre Mérel & Leo K. Simon & Fujin Yi, 2011. "A Fully Calibrated Generalized Constant-Elasticity-of-Substitution Programming Model of Agricultural Supply," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 93(4), pages 936-948.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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).
    2. 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.
    3. Athanasios Petsakos & Stelios Rozakis, 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(3), pages 713-728, July.
    4. 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.
    5. Ciaian, Pavel & Espinosa, Maria & Louhichi, Kamel & Perni, Angel, 2020. "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), May.
    6. 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.
    7. 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.
    8. 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.
    9. Purola, Tuomo & Lehtonen, Heikki, 2020. "Evaluating profitability of soil-renovation investments under crop rotation constraints in Finland," Agricultural Systems, Elsevier, vol. 180(C).
    10. 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 agricul," Post-Print hal-04195630, HAL.
    11. 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.
    12. 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.
    13. Shyam Kumar Basnet & Torbjörn Jansson & Thomas Heckelei, 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(3), pages 729-759, July.
    14. 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.
    15. 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.
    16. Ciaian, Pavel & Espinosa, Maria & Louhichi, Kamel & Perni, Angel & Gomez y Paloma, Sergio, 2018. "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.
    17. 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.
    18. 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.

    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. 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.
    2. Viaggi, Davide & Raggi, Meri & Gomez y Paloma, Sergio, 2011. "Farm-household investment behaviour and the CAP decoupling: Methodological issues in assessing policy impacts," Journal of Policy Modeling, Elsevier, vol. 33(1), pages 127-145, January.
    3. 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.
    4. 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).
    5. Petsakos, Athanasios & Rozakis, Stelios, 2011. "Integrating risk and uncertainty in PMP models," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 114762, European Association of Agricultural Economists.
    6. Thomas Heckelei & Wolfgang Britz, 2000. "Positive Mathematical Programming with Multiple Data Points: A Cross-Sectional Estimation Procedure," Cahiers d'Economie et Sociologie Rurales, INRA Department of Economics, vol. 57, pages 27-50.
    7. Umed Temurshoev & Marian Mraz & Luis Delgado Sancho & Peter Eder, 2015. "EU Petroleum Refining Fitness Check: OURSE Modelling and Results," JRC Research Reports JRC96207, Joint Research Centre.
    8. 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.
    9. Arfini, Filippo & Donati, Michele & Paris, Quirino, 2008. "Innovation in Estimation of Revenue and Cost Functions in PMP Using FADN Information at Regional Level," 2008 International Congress, August 26-29, 2008, Ghent, Belgium 44008, European Association of Agricultural Economists.
    10. Siwa Msangi & Sarah Ann Cline, 2016. "Improving Groundwater Management for Indian Agriculture: Assessing Tradeoffs Across Policy Instruments," Water Economics and Policy (WEP), World Scientific Publishing Co. Pte. Ltd., vol. 2(03), pages 1-33, September.
    11. 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.
    12. Umed Temurshoev & Fréderic Lantz, 2016. "Long-term petroleum product supply analysis through a robust modelling approach," Working Papers 2016-003, Universidad Loyola Andalucía, Department of Economics.
    13. Louhichi, Kamel & Flichman, Guillermo & Blanco Fonseca, Maria, 2009. "A generic template for FSSIM," Reports 57463, Wageningen University, SEAMLESS: System for Environmental and Agricultural Modelling; Linking European Science and Society.
    14. Pierre-Alain Jayet & Athanasios Petsakos & Raja Chakir & Anna Lungarska & Stéphane De Cara & Elvire Petel & Pierre Humblot & Caroline Godard & David Leclère & Pierre Cantelaube & Cyril Bourgeois & Mél, 2023. "The European agro-economic model AROPAj," Working Papers hal-04109872, HAL.
    15. Heckelei, Thomas & Britz, Wolfgang, 2005. "Models Based on Positive Mathematical Programming: State of the Art and Further Extensions," 89th Seminar, February 2-5, 2005, Parma, Italy 234607, European Association of Agricultural Economists.
    16. Pascal Tillie & Kamel Louhichi & Sergio Gomez-Y-Paloma, 2018. "La culture attelée dans le bassin cotonnier en Côte d'Ivoire. Analyse et modélisation des impacts d'un programme de relance de la culture attelée," JRC Research Reports JRC111027, Joint Research Centre.
    17. 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.
    18. Arfini, Filippo & Donati, Michele & Grossi, L. & Paris, Quirino, 2008. "Revenue and Cost Functions in PMP: a Methodological Integration for a Territorial Analysis of CAP," 107th Seminar, January 30-February 1, 2008, Sevilla, Spain 6636, European Association of Agricultural Economists.
    19. 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.
    20. Louhichi, Kamel & Ciaian, Pavel & Espinosa, Maria & Colen, Liesbeth & Perni, Angel & Paloma, Sergio, 2015. "The Impact of Crop Diversification Measure: EU-wide Evidence Based on IFM-CAP Model," 2015 Conference, August 9-14, 2015, Milan, Italy 211542, International Association of Agricultural Economists.

    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:eee:ejores:v:242:y:2015:i:2:p:536-545. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    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.