EconPapers    
Economics at your fingertips  
 

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

Claudia Seidel and Wolfgang Britz

Bio-based and Applied Economics Journal, 2019, vol. 08, issue 01

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.

Keywords: Research; Methods/Statistical; Methods (search for similar items in EconPapers)
Date: 2019
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://ageconsearch.umn.edu/record/302123/files/Seidel_Britz_08-01-2019_BAE.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ags:aieabj:302123

DOI: 10.22004/ag.econ.302123

Access Statistics for this article

More articles in Bio-based and Applied Economics Journal from Italian Association of Agricultural and Applied Economics (AIEAA) Contact information at EDIRC.
Bibliographic data for series maintained by AgEcon Search ().

 
Page updated 2025-04-03
Handle: RePEc:ags:aieabj:302123