Agent-Based Models in Economics: A Toolkit

by Domenico Delli Gatti (Editor), Giorgio Fagiolo (Editor), Mauro Gallegati (Editor), Matteo Richiardi (Editor), Alberto Russo (Editor)

In contrast to mainstream economics, complexity theory conceives the economy as a complex system of heterogeneous interacting agents characterised by limited information and bounded rationality. Agent Based Models (ABMs) are the analytical and computational tools developed by the proponents of this emerging methodology. Aimed at students and scholars of contemporary economics, this book includes a comprehensive toolkit for agent-based computational economics, now quickly becoming the new way to study evolving economic systems. Leading scholars in the field explain how ABMs can be applied fruitfully to many real-world economic examples and represent a great advancement over mainstream approaches. The essays discuss the methodological bases of agent-based approaches and demonstrate step-by-step how to build, simulate and analyse ABMs and how to validate their outputs empirically using the data. They also present a wide set of applications of these models to key economic topics, including the business cycle, labour markets, and economic growth

Review
'Some 25 years ago, Frank Hahn a leading economic theorist said, '… wildly complex systems need simulating … while there will be work for the computer scientist, I very much doubt that economists will be able to establish general propositions in any but very special examples'. Economists have reacted by saying 'show us an alternative'. This book does just that. It provides the elements of an alternative computational approach in which aggregate phenomena such as crises do not appear from the blue, but emerge from the interaction between simple but heterogeneous agents.' Alan Kirman, University of Aix-Marseille III

'The authors conceive of economies as complex systems of heterogeneous interacting agents with bounded rationality and limited information, and they view agent-based modeling as a necessary tool for the exploration of such systems. In this book the authors provide a comprehensive introduction to agent-based modeling. Although macroeconomic applications are stressed, the coverage of topics such as rationality, behavior, expectations, and learning will be of value for many other applications as well. A particularly welcome aspect of the book is its attention to historical antecedents and its inclusion of chapters devoted to empirical validation and estimation issues.' Leigh Tesfatsion, Iowa State University



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