IDEAS home Printed from https://ideas.repec.org/p/ags/aieacp/124117.html
   My bibliography  Save this paper

Farm production costs estimation trough PMP Models: an application in three Italian Regions

Author

Listed:
  • Arfini, Filippo
  • Donati, Michele
  • Marongiu, Sonia
  • Cesaro, Luca

Abstract

The objective of this paper is to present a Generalised Positive Mathematical Programming model suitable for the estimation of variable cost of production associated with different farm activities. This work present, discuss and demonstrates that the Generalised PMP model is a useful theoretical framework for the representation of farm choice, including for the description of costs related to the production function chosen by each entrepreneur. For this characteristics the model can be used for the farms belonging the FADN sample providing a powerful tools for researcher that would like to know variable costs of production for agricultural activities or estimate the impact of agricultural policy and market reform at regional and sectorial level. The main feature of the generalised PMP model is its independence from any “external” information, included the support value of the GME parameters and the abandon of the “tautology” problem always present in the standard PMP models. The paper also present the results of the cost estimation process and validate it comparing the observed variable cost with the estimated variable cost related to a sample of 738 farms belonging the FADN data base of three Italian regions.

Suggested Citation

  • 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).
    • Handle: RePEc:ags:aieacp:124117
    DOI: 10.22004/ag.econ.124117
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/124117/files/Arfini_Donati_Cesaro%20_Marongiu_Farm%20production%20costs%20estimation%20trough%20PMP%20Models.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.124117?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
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Arriaza, M. & Gomez-Limon, J. A., 2003. "Comparative performance of selected mathematical programming models," Agricultural Systems, Elsevier, vol. 77(2), pages 155-171, August.
    3. Lence, Sergio H & Miller, Douglas J, 1998. "Estimation of Multi-output Production Functions with Incomplete Data: A Generalised Maximum Entropy Approach," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 25(2), pages 188-209.
    4. 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.
    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. Ottmar Röhm & Stephan Dabbert, 2003. "Integrating Agri-Environmental Programs into Regional Production Models: An Extension of Positive Mathematical Programming," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 85(1), pages 254-265.
    7. Richard E. Howitt, 1995. "Positive Mathematical Programming," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 77(2), pages 329-342.
    8. Gocht, Alexander, 2005. "Assessment of Simulation Behavior of Different Mathematical Programming Approaches," 89th Seminar, February 2-5, 2005, Parma, Italy 232598, European Association of Agricultural Economists.
    9. 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.
    10. 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.
    11. Golan, Amos & Judge, George G. & Miller, Douglas, 1996. "Maximum Entropy Econometrics," Staff General Research Papers Archive 1488, Iowa State University, Department of Economics.
    12. 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.
    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.
    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. Henderson, Benjamin & Cacho, Oscar & Thornton, Philip & van Wijk, Mark & Herrero, Mario, 2018. "The economic potential of residue management and fertilizer use to address climate change impacts on mixed smallholder farmers in Burkina Faso," Agricultural Systems, Elsevier, vol. 167(C), pages 195-205.
    2. Christina Moulogianni, 2022. "Comparison of Selected Mathematical Programming Models Used for Sustainable Land and Farm Management," Land, MDPI, vol. 11(8), pages 1-18, August.

    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. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. Cortignani, Raffaele & Severini, Simone, 2010. "The impact of reforming the Common Agricultural Policy on the sustainability of the irrigated area of Central Italy. An empirical assessment by means of a Positive Mathematical Programming model," 120th Seminar, September 2-4, 2010, Chania, Crete 109318, European Association of Agricultural Economists.
    8. 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.
    9. 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).
    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. Msangi, Siwa & Howitt, Richard E., 2006. "Estimating Disaggregate Production Functions: An Application to Northern Mexico," 2006 Annual meeting, July 23-26, Long Beach, CA 21080, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    12. 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.
    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. Frahan, Bruno Henry de, 2005. "PMP, Extensions and Alternative Methods: Introductory Review of the State of the Art," 2005 International Congress, August 23-27, 2005, Copenhagen, Denmark 24537, European Association of Agricultural Economists.
    15. Fragoso, R. & Marques, C. & Lucas, M.R. & Martins, M.B. & Jorge, R., 2011. "The economic effects of common agricultural policy on Mediterranean montado/dehesa ecosystem," Journal of Policy Modeling, Elsevier, vol. 33(2), pages 311-327, March.
    16. Blanco, Maria & Cortignani, Raffaele & Severini, Simone, 2008. "Evaluating Changes in Cropping Patterns due to the 2003 CAP Reform. An Ex-post Analysis of Different PMP Approaches Considering New Activities," 107th Seminar, January 30-February 1, 2008, Sevilla, Spain 6674, European Association of Agricultural Economists.
    17. 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.
    18. Doole, Graeme J. & Marsh, Dan K., 2014. "Methodological limitations in the evaluation of policies to reduce nitrate leaching from New Zealand agriculture," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 58(1), January.
    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. Bulgheroni, Claudia & Sali, Guido, 2008. "Pressure Factors Affecting Lombardy Agricultural System: The Environmental Consequences Of The Fischler Reform," 109th Seminar, November 20-21, 2008, Viterbo, Italy 44827, European Association of Agricultural Economists.

    More about this item

    Keywords

    Production Economics;

    Statistics

    Access and download statistics

    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:ags:aieacp:124117. 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: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/aieaaea.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.