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Schmid, E. & Sinabell, F. (2005). Using the Positive Mathematical Programming Method to Calibrate Linear Programming Models. Discussion Paper DP-10-2005, Institute for Sustainable Economic Development, Department of Economics and Social Sciences, University of Natural Resources and Applied Life Sciences, Vienna, Austria (February 2005)
Full text not available from this repository.Abstract
In agricultural economics, several calibration and aggregation approaches have evolved in mathematical programming models. This article combines in a linear programming model features of the Positive Mathematical Programming method with an aggregation approach that is constrained to the production possibility set spanned by a convex combination of observed production activities. The combination is obtained by using a variable separation technique that approximates a non-linear objective function. Therefore, linear programming models can be exactly calibrated to observed production activities. The aggregation of production activities in homogenous production response units assumes that farmers in a region are treated such as they respond in the same way. Both methodologies are embedded in economic reasoning and provide a robust framework to solve large-scale linear programming models in reasonable time.
| Item Type: | Other |
|---|---|
| Uncontrolled Keywords: | Calibration; Aggregation; Linear programming |
| Research Programs: | Forestry (FOR) |
| Bibliographic Reference: | Discussion Paper DP-10-2005, Institute for Sustainable Economic Development, Department of Economics and Social Sciences, University of Natural Resources and Applied Life Sciences, Vienna, Austria (February 2005) |
| Depositing User: | IIASA Import |
| Date Deposited: | 15 Jan 2016 02:18 |
| Last Modified: | 27 Aug 2021 17:37 |
| URI: | https://pure.iiasa.ac.at/7624 |
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