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Title
Abstract
FAQs
Introduction
Methodology -A Synthetic Approach
Reproducing Empirical Findings
References

Agent-based computational economics-An introduction

Profile image of Charlotte BruunCharlotte Bruun

Department of Economics, Politics and Public …

Abstract

Terming a specific approach to economics agent-based may appear paradoxical. Isn't human behavior the foundation of economics - and shouldn't all economic theory be based on agents behavior in some sense? This, at least, is what conventional economic theory has been ...

FAQs

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What distinguishes agent-based computational economics from traditional microeconomics?add

ACE emphasizes agent interactions as pivotal in understanding economic systems, unlike traditional microeconomics which focuses on isolated agents. This shift allows for emergent phenomena that cannot be predicted from individual behaviors alone.

How does ACE handle the complexity of economic systems compared to conventional methods?add

The synthetic approach of ACE allows for modeling complex adaptive systems, revealing emergent behaviors without restrictive assumptions. This contrasts with conventional methods that rely heavily on simplified, analytical tractable models.

What role does interaction among agents play in agent-based economic modeling?add

The paper highlights that complex dynamics arise from dispersed interactions among heterogeneous agents, essential for capturing emergent phenomena. This interaction model reflects real economic environments better than simulated economies based on aggregate agents.

How does ACE explain macroeconomic movements like business cycles?add

ACE models suggest that business cycles are emergent phenomena resulting from agent interactions, rather than from individual behaviors. This perspective challenges traditional views and promotes the exploration of complex adaptive dynamics.

What methodological challenges does ACE present for empirical testing in economics?add

ACE models' outputs must be reconceptualized for empirical testing, which complicates validation compared to traditional models. There is a need for innovative statistical techniques to interpret simulated data meaningfully.

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