Wie viel bringt eine verbesserte Produktionsprogrammplanung auf der Grundlage einer systematischen Auswertung empirischer Zeitreihen? â€“ Die Bedeutung von Prognosemodellen bei der Optimierung unter Unsicherheit
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 farmersâ€™ 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 farmersâ€™ risk tolerance, the variance of the observed programâ€™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.
Volume (Year): 55 (2006)
Issue (Month): 4 ()
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- 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, 07.
- B. Curtis Eaves, 1971. "On Quadratic Programming," Management Science, INFORMS, vol. 17(11), pages 698-711, July.
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