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Party CompetitionAn Agent-Based Model$
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Michael Laver and Ernest Sergenti

Print publication date: 2011

Print ISBN-13: 9780691139036

Published to Princeton Scholarship Online: October 2017

DOI: 10.23943/princeton/9780691139036.001.0001

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Modeling Multiparty Competition

Modeling Multiparty Competition

(p.3) Chapter One Modeling Multiparty Competition
Party Competition

Michael Laver

Ernest Sergenti

Princeton University Press

This chapter begins with a brief discussion of the need for a new approach to modeling party competition. It then makes a case for the use of agent-based modeling to study multiparty competition in an evolving dynamic party system, given the analytical intractability of the decision-making environment, and the resulting need for real politicians to rely on informal decision rules. Agent-based models (ABMs) are “bottom-up” models that typically assume settings with a fairly large number of autonomous decision-making agents. Each agent uses some well-specified decision rule to choose actions, and there may be considerable diversity in the decision rules used by different agents. Given the analytical intractability of the decision-making environment, the decision rules that are specified and investigated in ABMs are typically based on adaptive learning rather than forward-looking strategic analysis, and agents are assumed to have bounded rather than perfect rationality. An overview of the subsequent chapters is also presented.

Keywords:   political parties, party competition, agent-based modeling, multiparty competition

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