Party Competition
An Agent-Based Model
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"Laver and Sergenti argue that politics is best viewed as a complex dynamical system that is neither random nor in equilibrium. Their use of agent-based modeling to better understand the flux of politics will be of great interest to the next generation of modelers seeking to make sense of the wide variety of political systems in the real world."--Norman Schofield, Washington University in St. Louis "Laver and Sergenti present a bold and rigorous new approach to interparty electoral competition. Their results are remarkable and often puzzling, offering plentiful food for thought for modelers, a...
"Laver and Sergenti argue that politics is best viewed as a complex dynamical system that is neither random nor in equilibrium. Their use of agent-based modeling to better understand the flux of politics will be of great interest to the next generation of modelers seeking to make sense of the wide variety of political systems in the real world."--Norman Schofield, Washington University in St. Louis "Laver and Sergenti present a bold and rigorous new approach to interparty electoral competition. Their results are remarkable and often puzzling, offering plentiful food for thought for modelers, analytical theorists, and empiricists alike. Ignore this book at your peril, or better, read it and become an admirer."--Kaare Strøm, University of California, San Diego "Party Competition is an ambitious and pioneering work. Laver and Sergenti present a new methodology for the study of a quite central and traditional problem in political science. This is to my knowledge the first book-length treatise on the evolutionary modeling of party competition."--Hannu Nurmi, author of Models of Political Economy "Distinct and important. The tools that Laver and Sergenti bring to bear on computational modeling will start a debate that is long overdue in the social sciences. This is another step forward in developing the methods needed to solve real-world problems that have so far resisted our best efforts."--Scott de Marchi, Duke University
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