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Agent‐based Modelling of Climate Adaptation and Mitigation Options in Agriculture
Author(s) -
Berger Thomas,
Troost Christian
Publication year - 2014
Publication title -
journal of agricultural economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.157
H-Index - 61
eISSN - 1477-9552
pISSN - 0021-857X
DOI - 10.1111/1477-9552.12045
Subject(s) - computable general equilibrium , agriculture , adaptation (eye) , climate change , natural resource economics , land use , complement (music) , environmental resource management , environmental economics , partial equilibrium , policy analysis , computer science , economics , general equilibrium theory , microeconomics , ecology , political science , biochemistry , chemistry , physics , phenotype , complementation , gene , optics , biology , law
Computer simulation models can provide valuable insights for climate‐related analysis and help streamline policy interventions for improved adaptation and mitigation in agriculture. Computable general equilibrium ( CGE ) and partial equilibrium ( PE ) models are currently being expanded to include land‐use change and energy markets so that the effects of various policy measures on agricultural production can be assessed. Agent‐based modelling ( ABM ) or multi‐agent systems ( MAS ) have been suggested as a complementary tool for assessing farmer responses to climate change in agriculture and how these are affected by policies. MAS applied to agricultural systems draw on techniques used for R ecursive F arm P rogramming, but include models of all individual farms, their spatial interactions and the natural environment. In this article, we discuss the specific insights MAS provide for developing robust policies and land‐use strategies in response to climate change. We show that MAS are well‐suited for uncertainty analysis and can thereby complement existing simulation approaches to advance the understanding and implementation of effective climate‐related policies in agriculture.