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

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  • Arfini, Filippo
  • Donati, Michele
  • Marongiu, Sonia
  • Cesaro, Luca
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    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.

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    File URL: http://purl.umn.edu/124117
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    Bibliographic Info

    Paper provided by Italian Association of Agricultural and Applied Economics (AIEAA) in its series Congress Papers with number 124117.

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    Date of creation: 2012
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    Handle: RePEc:ags:aieacp:124117

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    Web page: http://www.aieaa.org/
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    Related research

    Keywords: variable cost of production; positive mathematical programming; farm accountancy data network; Production Economics; Q12; C61; Q18; C38;

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    1. 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.
    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. Ottmar R�hm & 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.
    4. 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, Foundation for the European Review of Agricultural Economics, vol. 25(2), pages 188-209.
    5. 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.
    6. Thomas Heckelei & Hendrik Wolff, 2003. "Estimation of constrained optimisation models for agricultural supply analysis based on generalised maximum entropy," European Review of Agricultural Economics, Foundation for the European Review of Agricultural Economics, vol. 30(1), pages 27-50, March.
    7. 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.
    8. 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.
    9. Golan, Amos & Judge, George G. & Miller, Douglas, 1996. "Maximum Entropy Econometrics," Staff General Research Papers 1488, Iowa State University, Department of Economics.
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