IDEAS home Printed from https://ideas.repec.org/a/oup/erevae/v45y2018i2p205-238..html
   My bibliography  Save this article

Economic impacts of CAP greening: application of an EU-wide individual farm model for CAP analysis (IFM-CAP)

Author

Listed:
  • Kamel Louhichi
  • Pavel Ciaian
  • Maria Espinosa
  • Angel Perni
  • Sergio Gomez y Paloma

Abstract

This paper presents the EU-wide individual farm-level model (IFM-CAP) applied to assess the economic effects of CAP greening. IFM-CAP is a static positive programming model developed to capture the full heterogeneity of EU farms in terms of policy representation and impacts. Simulation results show that, although the proportions of farms and utilised agricultural area (UAA) subject to CAP greening are sizeable (55 per cent of all farms and 86 per cent of UAA) at EU-27 level, the reallocated area caused by CAP greening represents only 4.5 per cent of UAA. Farm income and total production both decrease by 1 and 0.9 per cent, respectively. In total, around 29 per cent of the farm population is affected by CAP greening in the EU-27.

Suggested Citation

  • 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.
    • Handle: RePEc:oup:erevae:v:45:y:2018:i:2:p:205-238.
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1093/erae/jbx029
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

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

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    4. Heckelei, Thomas & Mittelhammer, Ronald C. & Jansson, Torbjorn, 2008. "A Bayesian Alternative To Generalized Cross Entropy Solutions For Underdetermined Econometric Models," Discussion Papers 56973, University of Bonn, Institute for Food and Resource Economics.
    5. Petsakos, Athanasios & Rozakis, Stelios, 2015. "Calibration of agricultural risk programming models," European Journal of Operational Research, Elsevier, vol. 242(2), pages 536-545.
    6. Alexander Gocht & Pavel Ciaian & Maria Bielza & Jean-Michel Terres & Norbert Röder & Mihaly Himics & Guna Salputra, 2017. "EU-wide Economic and Environmental Impacts of CAP Greening with High Spatial and Farm-type Detail," Journal of Agricultural Economics, Wiley Blackwell, vol. 68(3), pages 651-681, September.
    7. Bruno Henry Frahan & Jeroen Buysse & Philippe Polomé & Bruno Fernagut & Olivier Harmignie & Ludwig Lauwers & Guido Huylenbroeck & Jef Meensel, 2007. "Positive Mathematical Programming for Agricultural and Environmental Policy Analysis: Review and Practice," International Series in Operations Research & Management Science, in: Andres Weintraub & Carlos Romero & Trond Bjørndal & Rafael Epstein & Jaime Miranda (ed.), Handbook Of Operations Research In Natural Resources, chapter 0, pages 129-154, Springer.
    8. Brown, Matthew & Jones, James, 2013. "The Predicted Impacts of the Proposed Greening Measures of the 2014 CAP Reform on Farming Businesses in North Cornwall," 87th Annual Conference, April 8-10, 2013, Warwick University, Coventry, UK 158855, Agricultural Economics Society.
    9. Emil Erjavec & Marko Lovec, 2017. "Research of European Union's Common Agricultural Policy: disciplinary boundaries and beyond," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 44(4), pages 732-754.
    10. Heinrich, Barbara, 2012. "Calculating The ‘Greening’ Effect – A Case Study Approach To Estimate The Gross Margin Losses In Different Farm Types In Germany Due To The Reform Of The Cap," 52nd Annual Conference, Stuttgart, Germany, September 26-28, 2012 137155, German Association of Agricultural Economists (GEWISOLA).
    11. Solazzo, Roberto & Pierangeli, Fabio, 2016. "How does greening affect farm behaviour? Trade-off between commitments and sanctions in the Northern Italy," Agricultural Systems, Elsevier, vol. 149(C), pages 88-98.
    12. Cloé Garnache & Pierre Mérel & Richard Howitt & Juhwan Lee, 2017. "Calibration of shadow values in constrained optimisation models of agricultural supply," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 44(3), pages 363-397.
    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. Heckelei, Thomas & Britz, Wolfgang, 2000. "Positive Mathematical Programming with Multiple Data Points: A Cross-Sectional Estimation Procedure," Cahiers d'Economie et de Sociologie Rurales (CESR), Institut National de la Recherche Agronomique (INRA), vol. 57.
    15. Cortignani, Raffaele & Severini, Simone, 2009. "Modeling farm-level adoption of deficit irrigation using Positive Mathematical Programming," Agricultural Water Management, Elsevier, vol. 96(12), pages 1785-1791, December.
    16. Paolo Sckokai & Daniele Moro, 2006. "Modeling the Reforms of the Common Agricultural Policy for Arable Crops under Uncertainty," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 88(1), pages 43-56.
    17. 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.
    18. Heinrich, Barbara, 2012. "Calculating the 'greening' effect: A case study approach to predict the gross margin losses in different farm types in Germany due to the reform of the CAP," DARE Discussion Papers 1205, Georg-August University of Göttingen, Department of Agricultural Economics and Rural Development (DARE).
    19. Heinrich, Barbara, 2012. "Calculating The ‘Greening’ Effect: A Case Study Approach To Predict The Gross Margin Losses In Different Farm Types In Germany Due To The Reform Of The Cap," Department of Agricultural and Rural Development (DARE) Discussion Papers 187445, Georg-August-Universitaet Goettingen, Department of Agricultural Economics and Rural Development (DARE).
    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. Markowitz, Harry, 2014. "Mean–variance approximations to expected utility," European Journal of Operational Research, Elsevier, vol. 234(2), pages 346-355.
    22. repec:oup:erevae:v:44:y:2017:i:4:p:567-589. is not listed on IDEAS
    23. Heinrich, Barbara, 2012. "Calculating The ‘Greening’ Effect: A Case Study Approach To Predict The Gross Margin Losses In Different Farm Types In Germany Due To The Reform Of The Cap," 54th Annual Conference, Goettingen, Germany, September 17-19, 2014 187445, German Association of Agricultural Economists (GEWISOLA).
    24. 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.
    25. Gocht, Alexander & Britz, Wolfgang, 2011. "EU-wide farm type supply models in CAPRI--How to consistently disaggregate sector models into farm type models," Journal of Policy Modeling, Elsevier, vol. 33(1), pages 146-167, January.
    26. Barry T. Coyle, 1999. "Risk Aversion and Yield Uncertainty in Duality Models of Production: A Mean-Variance Approach," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 81(3), pages 553-567.
    27. Paris,Quirino, 2011. "Economic Foundations of Symmetric Programming," Cambridge Books, Cambridge University Press, number 9780521123020.
    28. Vanni, Francesco & Cardillo, Concetta, 2013. "The effects of CAP greening on Italian agriculture," Politica Agricola Internazionale - International Agricultural Policy, Edizioni L'Informatore Agrario, vol. 2013(3), September.
    29. 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.
    30. Lansink, Alfons Oude & Peerlings, Jack, 1996. "Modelling the New EU Cereals and Oilseeds Regime in the Netherlands," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 23(2), pages 161-178.
    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.
    32. Paris,Quirino, 2011. "Economic Foundations of Symmetric Programming," Cambridge Books, Cambridge University Press, number 9780521194723.
    Full references (including those not matched with items on IDEAS)

    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. Louhichi, Kamel & Ciaian, Pavel & Espinosa, Maria & Colen, Liesbeth & Perni, Angel & Gomez y Paloma, Sergio, 2015. "Farm-level economic impacts of EU-CAP greening measures," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205309, Agricultural and Applied Economics Association.
    2. Louhichi, Kamel & Ciaian, Pavel & Espinosa, Maria & Colen, Liesbeth & Perni, Angel & Gomez y Paloma, Sergio, 2015. "EU-wide individual Farm Model for CAP Analysis (IFM-CAP): Application to Crop Diversification Policy," 2015 Conference, August 9-14, 2015, Milan, Italy 212155, International Association of Agricultural Economists.
    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. 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.
    5. Alexander Gocht & Pavel Ciaian & Maria Bielza & Jean-Michel Terres & Norbert Röder & Mihaly Himics & Guna Salputra, 2017. "EU-wide Economic and Environmental Impacts of CAP Greening with High Spatial and Farm-type Detail," Journal of Agricultural Economics, Wiley Blackwell, vol. 68(3), pages 651-681, September.
    6. 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).
    7. 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.
    8. Petsakos, Athanasios & Rozakis, Stelios, 2015. "Calibration of agricultural risk programming models," European Journal of Operational Research, Elsevier, vol. 242(2), pages 536-545.
    9. 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.
    10. 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.
    11. Kamel Elouhichi & Pascal Tillie & Aymeric Ricome & Sergio Gomez-Y-Paloma, 2020. "Modelling Farm-household Livelihoods in Developing Economies: Insights from three country case studies using LSMS-ISA data," JRC Research Reports JRC118822, Joint Research Centre.
    12. 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.
    13. 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.
    14. Solazzo, Roberto & Pierangeli, Fabio, 2016. "How does greening affect farm behaviour? Trade-off between commitments and sanctions in the Northern Italy," Agricultural Systems, Elsevier, vol. 149(C), pages 88-98.
    15. Kamel Louhichi & Pascal Tillie & Aymeric Ricome & Sergio Gomez y Paloma, 2020. "Modelling Farm-household Livelihoods in Developing Economies Insights from three country case studies using LSMS-ISA data [Modélisation des moyens de subsistance des ménages agricoles dans les écon," Post-Print hal-02544905, HAL.
    16. CARPENTIER, Alain & GOHIN, Alexandre & SCKOKAI, Paolo & THOMAS, Alban, 2015. "Economic modelling of agricultural production: past advances and new challenges," Review of Agricultural and Environmental Studies - Revue d'Etudes en Agriculture et Environnement (RAEStud), Institut National de la Recherche Agronomique (INRA), vol. 96(1), March.
    17. Lee, Hwarang & Eom, Jiyong & Cho, Cheolhung & Koo, Yoonmo, 2019. "A bottom-up model of industrial energy system with positive mathematical programming," Energy, Elsevier, vol. 173(C), pages 679-690.
    18. 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.
    19. Kooten, G. Cornelis van, 2013. "Modeling Forest Trade in Logs and Lumber: Qualitative and Quantitative Analysis," Working Papers 149182, University of Victoria, Resource Economics and Policy.
    20. Espinosa, Maria & Louhichi, Kamel & Perni, Angel & Ciaian, Pavel & Gomez y Paloma, Sergio, 2017. "Impacts of the 2013 CAP reform on the EU farming sector: An assessment using a microeconomic farm model," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258071, Agricultural and Applied Economics Association.

    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:oup:erevae:v:45:y:2018:i:2:p:205-238.. 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: Oxford University Press (email available below). General contact details of provider: https://edirc.repec.org/data/eaaeeea.html .

    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.