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Estimating a Dual Value Function as a Meta-Model of a Detailed Dynamic Mathematical Programming Model

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  • Seidel, Claudia
  • Britz, Wolfgang

Abstract

Mathematical programming (MP) is a widespread approach to depict production and investment decisions of agents in agent-based models (ABM) related to agriculture. However, introducing dynamics and indivisibilities in MP models renders their solution computing time intensive. We present a meta-modeling approach as an alternative to directly integrating MP in an ABM. Specifically, we estimate a dual symmetric normalized quadratic (SNQ) value function from a set of MP solutions. The approach allows us to depict relationships between key attributes, like the farm endowment with (quasi-) fixed factors and discounted farm household incomes, without modeling the technology in detail. The estimated functions are integrated in the ABM to derive agents’ decisions. The meta-modeling approach relaxes computational restrictions such that spatial interactions in large regions can be simulated improving our understanding of structural change in agriculture. It can also be used to extrapolate to farming populations where data availability might be restricted.

Suggested Citation

  • Seidel, Claudia & Britz, Wolfgang, 2019. "Estimating a Dual Value Function as a Meta-Model of a Detailed Dynamic Mathematical Programming Model," Bio-based and Applied Economics Journal, Italian Association of Agricultural and Applied Economics (AIEAA), vol. 8(1), April.
    • Handle: RePEc:ags:aieabj:302123
    DOI: 10.22004/ag.econ.302123
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    Cited by:

    1. Schaefer, David & Britz, Wolfgang & Kuhn, Till, 2020. "Modelling policy induced manure transports at large scale using an agent-based simulation model," Discussion Papers 305270, University of Bonn, Institute for Food and Resource Economics.

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    Research Methods/ Statistical Methods;

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