Authors:
Sarah Wolf
1
;
Steffen Fürst
1
;
Sophie Knell
2
;
Wiebke Lass
2
;
Daniel Lincke
1
;
Antoine Mandel
3
;
Jonas Teitge
2
and
Carlo Jaeger
4
Affiliations:
1
Global Climate Forum and Potsdam Institute for Climate Impact Research, Germany
;
2
Potsdam Institute for Climate Impact Research, Germany
;
3
Université Paris 1 Panthéon-Sorbonne, France
;
4
Global Climate Forum, Germany
Keyword(s):
Economic Agent-based Models, Scheduling, Climate Policy, Win-win Strategies.
Related
Ontology
Subjects/Areas/Topics:
Agent Based Modeling and Simulation
;
Complex Systems Modeling and Simulation
;
Sensor Networks
;
Simulation and Modeling
;
Simulation Tools and Platforms
;
Social Systems Simulation
;
Software and Architectures
Abstract:
Agent-based models (ABMs), and with them simulation, are gaining importance in economics. As they allow to study coordination problems in a dynamic setting, they can be helpful tools for identifying win-win strategies for climate policy. This paper argues that strongly simplified models can support a better understanding of economic ABMs. We present work in progress on an example case: while in economic systems in the real world many actions and interactions by various agents take place in parallel, often ABMs use sequential computation. With a simple economic agent-based model of firms that trade and produce goods, we explore and discuss two alternative modes of scheduling: the timetable model, where all agents complete one step after the other, and the heliotropic model, where one agent after the other completes steps. We find that the timetable model is better suited for working with data from national statistics, while the heliotropic model dispenses with random shuffling that is
often introduced to guarantee symmetric expectations for agents. The latter can be used in a completely deterministic fashion, providing a baseline case for studying the system’s dynamics.
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