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Revenue and Cost Functions in PMP: a Methodological Integration for a Territorial Analysis of CAP

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  • Arfini, Filippo
  • Donati, Michele
  • Grossi, L.
  • Paris, Quirino

Abstract

An integrated policy evaluation tool is proposed for assessing the effects of agricultural policy measures using all the information available at farm level. The tool combines the positive mathematical programming methodology with the cluster analysis technique by using the same panel of data. The PMP model proposed here allows to measure the effects of policy in term of agricultural supply responses including output market price variations. The novel procedure by which the PMP model is articulated permits to recover the set of farm level demand functions for agricultural products and the cost function characterizing the given sample of farms. Cluster analysis is useful for better appreciating the behaviour of farms before and after the policy scenario analysis by considering the transfers of farms among clusters. A decoupling scenario assessment presents the responses that the integrated tool can provide for evaluating agricultural policy instruments.

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File URL: http://purl.umn.edu/6636
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Bibliographic Info

Paper provided by European Association of Agricultural Economists in its series 107th Seminar, January 30-February 1, 2008, Sevilla, Spain with number 6636.

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Date of creation: 2008
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Handle: RePEc:ags:eaa107:6636

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Keywords: Positive mathematical programming; Cluster analysis; Integrated tool; Agricultural policies; Policy evaluation; Agricultural and Food Policy; Research Methods/ Statistical Methods;

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  1. Miller, Douglas & Lence, Sergio H., 1998. "Estimation of Multi-Output Production Functions with Incomplete Data: A Generalized Maximum Entropy Approach," Staff General Research Papers 1219, Iowa State University, Department of Economics.
  2. 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.
  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, Foundation for the European Review of Agricultural Economics, vol. 30(1), pages 27-50, March.
  4. Golan, Amos & Judge, George G. & Miller, Douglas, 1996. "Maximum Entropy Econometrics," Staff General Research Papers 1488, Iowa State University, Department of Economics.
  5. 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.
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Cited by:
  1. Arfini, Filippo & Donati, Michele, 2011. "Organic Productions and Capacity to Respond to Market Signals and Policies: An Empirical Analysis of a Sample of FADN Farms," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 114229, European Association of Agricultural Economists.
  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), issue 1, April.

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