Using the Positive Mathematical Programming Method to Calibrate Linear Programming Models

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)

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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: 17 Feb 2016 12:28
URI: http://pure.iiasa.ac.at/7624

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