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Agent-Based Modelling in Economics (Inglés) Pasta dura – 19 enero 2016

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Agent-based modelling in economics

Lynne Hamill and Nigel Gilbert, Centre for Research in Social Simulation (CRESS), University of Surrey, UK

New methods of economic modelling have been sought as a result of the global economic downturn in 2008.This unique book highlights the benefits of an agent-based modelling (ABM) approach. It demonstrates how ABM can easily handle complexity: heterogeneous people, households and firms interacting dynamically. Unlike traditional methods, ABM does not require people or firms to optimise or economic systems to reach equilibrium. ABM offers a way to link micro foundations directly to the macro situation.

Key features

  • Introduces the concept of agent-based modelling and shows how it differs from existing approaches.
  • Provides a theoretical and methodological rationale for using ABM in economics, along with practical advice on how to design and create the models.
  • Each chapter starts with a short summary of the relevant economic theory and then shows how to apply ABM.
  • Explores both topics covered in basic economics textbooks and current important policy themes; unemployment, exchange rates, banking and environmental issues.
  • Describes the models in pseudocode, enabling the reader to develop programs in their chosen language.
  • Supported by a website featuring the NetLogo models described in the book.

Agent-based Modelling in Economics provides students and researchers with the skills to design, implement, and analyze agent-based models. Third year undergraduate, master and doctoral students, faculty and professional economists will find this book an invaluable resource.

Biografía del autor

Nigel Gilbert, Professor of Sociology and Director of CRESS, University of Surrey, UK.

Lynne Hamill, Centre of Research in Social Simulation (CRESS), University of Surrey, UK.

Opiniones de clientes

4.2 de 5 estrellas
4.2 de 5
3 calificaciones de clientes
5 estrellas 62% (62%) 62%
4 estrellas 0% (0%) 0%
3 estrellas 38% (38%) 38%
2 estrellas 0% (0%) 0%
1 estrella 0% (0%) 0%
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Principales opiniones internacionales

ratfink
5.0 de 5 estrellas Excellent intro to translating theory to ABM models in Netlogo
Revisado en el Reino Unido el 19 de mayo de 2017
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Pietro Terna
5.0 de 5 estrellas Excellent book
Revisado en Italia el 11 de febrero de 2016
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John L. Mauer
3.0 de 5 estrellas Three Stars
Reseñado en los Estados Unidos el 16 de diciembre de 2016
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