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Wie viel bringt eine verbesserte Produktionsprogrammplanung auf der Grundlage einer systematischen Auswertung empirischer Zeitreihen? – Die Bedeutung von Prognosemodellen bei der Optimierung unter Unsicherheit

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  • Musshoff, Oliver
  • Hirschauer, Norbert

Abstract

In this paper we examine whether there is room for improvement in farm program decisions through the integration of formal mathematical optimisation into the planning process. Probing the potential for improvement, we investigate the cases of four Brandenburg cash crop farms over the last six years. We find that their total gross margins could have been increased significantly through a more sophisticated program planning. However, we also find that the superiority of formalised planning approaches depends on the quality of the data. The superior formal planning approach includes, in contrast to farmers’ ad hoc planning, a systematic time series analysis of gross margins and a stochastic optimisation model. For each of the six years, the formal planning approach provides optimised alternative programs based on the information available to the farmers at the respective time of planning. In order to avoid solutions that exceed the farmers’ risk tolerance, the variance of the observed program’s total gross margin which implicitly reflects the risk attitude of the individual farmer is used as an upper bound in the optimisation. Using the yields and prices realised at the end of each planning period, the total gross margins that could have been realized through the formally optimised programs in each year are then compared to those that were actually realised.

Suggested Citation

  • Musshoff, Oliver & Hirschauer, Norbert, 2006. "Wie viel bringt eine verbesserte Produktionsprogrammplanung auf der Grundlage einer systematischen Auswertung empirischer Zeitreihen? – Die Bedeutung von Prognosemodellen bei der Optimierung unter Uns," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 55(04), pages 1-13.
  • Handle: RePEc:ags:gjagec:97196
    DOI: 10.22004/ag.econ.97196
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    References listed on IDEAS

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    1. P. B. R. Hazell, 1971. "A Linear Alternative to Quadratic and Semivariance Programming for Farm Planning under Uncertainty: Reply," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 53(4), pages 664-665.
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    3. Darren Hudson & Keith Coble & Jayson Lusk, 2005. "Consistency of risk premium measures," Agricultural Economics, International Association of Agricultural Economists, vol. 33(1), pages 41-49, July.
    4. P. B. R. Hazell, 1971. "A Linear Alternative to Quadratic and Semivariance Programming for Farm Planning under Uncertainty," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 53(1), pages 53-62.
    5. B. Curtis Eaves, 1971. "On Quadratic Programming," Management Science, INFORMS, vol. 17(11), pages 698-711, July.
    6. Doppler, W. & März, U., 1989. "Die Behandlung von Verteilungen in stochastischen Methoden der Betriebsplanung," Proceedings “Schriften der Gesellschaft für Wirtschafts- und Sozialwissenschaften des Landbaues e.V.”, German Association of Agricultural Economists (GEWISOLA), vol. 25.
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    Cited by:

    1. Heidelbach, Olaf, 2007. "Efficiency of selected risk management instruments: An empirical analysis of risk reduction in Kazakhstani crop production," Studies on the Agricultural and Food Sector in Transition Economies, Leibniz Institute of Agricultural Development in Transition Economies (IAMO), volume 40, number 92323.

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