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Integrating risk and uncertainty in PMP models

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  • Petsakos, Athanasios
  • Rozakis, Stelios

Abstract

Positive Mathematical Programming (PMP) is one of the most commonly used methods of calibrating activity linear programming (LP) models in agriculture. PMP applications published thus far focus on the estimation of a farm’s nonlinear cost or profit function and rely on the recovery of unobserved or implicit information that can explain the initial model’s inability to calibrate. In this paper we use the PMP procedure to calibrate an expected utility model under the assumption that this implicit information can reveal a farmer’s profit expectations and risk attitude. The perfect calibration shows that PMP can be applied not only to LP models, but also to models that incorporate risk and this provides an interesting alternative to the traditional PMP methodology.

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File URL: http://purl.umn.edu/114762
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Bibliographic Info

Paper provided by European Association of Agricultural Economists in its series 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland with number 114762.

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Date of creation: 2011
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Handle: RePEc:ags:eaae11:114762

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Keywords: E-V analysis; expected utility; farm model; Positive Mathematical Programming; risk.; Risk and Uncertainty;

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  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, Foundation for the European Review of Agricultural Economics, vol. 30(1), pages 27-50, March.
  2. Golan, Amos & Judge, George G. & Miller, Douglas, 1996. "Maximum Entropy Econometrics," Staff General Research Papers 1488, Iowa State University, Department of Economics.
  3. Torres-Rojo, J. M., 2001. "Risk management in the design of a feeding ration: a portfolio theory approach," Agricultural Systems, Elsevier, vol. 68(1), pages 1-20, April.
  4. 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 308-17, June.
  5. Meyer, Jack, 1987. "Two-moment Decision Models and Expected Utility Maximization," American Economic Review, American Economic Association, vol. 77(3), pages 421-30, June.
  6. Xiaobo Zhang & Shenggen Fan, 2001. "Estimating Crop-Specific Production Technologies in Chinese Agriculture: A Generalized Maximum Entropy Approach," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 83(2), pages 378-388.
  7. Richard E. Howitt, 1995. "A Calibration Method For Agricultural Economic Production Models," Journal of Agricultural Economics, Wiley Blackwell, vol. 46(2), pages 147-159.
  8. 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. 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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