Agent-Based Modelling in Economics

Agent-Based Modelling in Economics

Author: Lynne Hamill

Publisher: John Wiley & Sons

Published: 2016-01-19

Total Pages: 256

ISBN-13: 1118456076

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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.


Agent-Based Models in Economics

Agent-Based Models in Economics

Author: Domenico Delli Gatti

Publisher: Cambridge University Press

Published: 2018-03-22

Total Pages: 261

ISBN-13: 1108414990

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The first step-by-step introduction to the methodology of agent-based models in economics, their mathematical and statistical analysis, and real-world applications.


Network Theory and Agent-Based Modeling in Economics and Finance

Network Theory and Agent-Based Modeling in Economics and Finance

Author: Anindya S. Chakrabarti

Publisher: Springer Nature

Published: 2019-10-23

Total Pages: 454

ISBN-13: 9811383197

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This book presents the latest findings on network theory and agent-based modeling of economic and financial phenomena. In this context, the economy is depicted as a complex system consisting of heterogeneous agents that interact through evolving networks; the aggregate behavior of the economy arises out of billions of small-scale interactions that take place via countless economic agents. The book focuses on analytical modeling, and on the econometric and statistical analysis of the properties emerging from microscopic interactions. In particular, it highlights the latest empirical and theoretical advances, helping readers understand economic and financial networks, as well as new work on modeling behavior using rich, agent-based frameworks. Innovatively, the book combines observational and theoretical insights in the form of networks and agent-based models, both of which have proved to be extremely valuable in understanding non-linear and evolving complex systems. Given its scope, the book will capture the interest of graduate students and researchers from various disciplines (e.g. economics, computer science, physics, and applied mathematics) whose work involves the domain of complexity theory.


Economics with Heterogeneous Interacting Agents

Economics with Heterogeneous Interacting Agents

Author: Alessandro Caiani

Publisher: Springer

Published: 2016-09-21

Total Pages: 219

ISBN-13: 3319440586

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This book offers a practical guide to Agent Based economic modeling, adopting a “learning by doing” approach to help the reader master the fundamental tools needed to create and analyze Agent Based models. After providing them with a basic “toolkit” for Agent Based modeling, it present and discusses didactic models of real financial and economic systems in detail. While stressing the main features and advantages of the bottom-up perspective inherent to this approach, the book also highlights the logic and practical steps that characterize the model building procedure. A detailed description of the underlying codes, developed using R and C, is also provided. In addition, each didactic model is accompanied by exercises and applications designed to promote active learning on the part of the reader. Following the same approach, the book also presents several complementary tools required for the analysis and validation of the models, such as sensitivity experiments, calibration exercises, economic network and statistical distributions analysis. By the end of the book, the reader will have gained a deeper understanding of the Agent Based methodology and be prepared to use the fundamental techniques required to start developing their own economic models. Accordingly, “Economics with Heterogeneous Interacting Agents” will be of particular interest to graduate and postgraduate students, as well as to academic institutions and lecturers interested in including an overview of the AB approach to economic modeling in their courses.


Introduction to Agent-Based Economics

Introduction to Agent-Based Economics

Author: Mauro Gallegati

Publisher: Academic Press

Published: 2017-08-03

Total Pages: 276

ISBN-13: 0128039035

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Introduction to Agent-Based Economics describes the principal elements of agent-based computational economics (ACE). It illustrates ACE's theoretical foundations, which are rooted in the application of the concept of complexity to the social sciences, and it depicts its growth and development from a non-linear out-of-equilibrium approach to a state-of-the-art agent-based macroeconomics. The book helps readers gain a better understanding of the limits and perspectives of the ACE models and their capacity to reproduce economic phenomena and empirical patterns. - Reviews the literature of agent-based computational economics - Analyzes approaches to agents' expectations - Covers one of the few large macroeconomic agent-based models, the Modellaccio - Illustrates both analytical and computational methodologies for producing tractable solutions of macro ACE models - Describes diffusion and amplification mechanisms - Depicts macroeconomic experiments related to ACE implementations


Agent-Based Modeling

Agent-Based Modeling

Author: Norman Ehrentreich

Publisher: Springer Science & Business Media

Published: 2007-10-30

Total Pages: 238

ISBN-13: 3540738789

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This book reconciles the existence of technical trading with the Efficient Market Hypothesis. By analyzing a well-known agent-based model, the Santa Fe Institute Artificial Stock Market (SFI-ASM), it finds that when selective forces are weak, financial evolution cannot guarantee that only the fittest trading rules will survive. Its main contribution lies in the application of standard results from population genetics which have widely been neglected in the agent-based community.


The Oxford Handbook of Computational Economics and Finance

The Oxford Handbook of Computational Economics and Finance

Author: Shu-Heng Chen

Publisher: Oxford University Press

Published: 2018-01-12

Total Pages: 785

ISBN-13: 0190877502

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The Oxford Handbook of Computational Economics and Finance provides a survey of both the foundations of and recent advances in the frontiers of analysis and action. It is both historically and interdisciplinarily rich and also tightly connected to the rise of digital society. It begins with the conventional view of computational economics, including recent algorithmic development in computing rational expectations, volatility, and general equilibrium. It then moves from traditional computing in economics and finance to recent developments in natural computing, including applications of nature-inspired intelligence, genetic programming, swarm intelligence, and fuzzy logic. Also examined are recent developments of network and agent-based computing in economics. How these approaches are applied is examined in chapters on such subjects as trading robots and automated markets. The last part deals with the epistemology of simulation in its trinity form with the integration of simulation, computation, and dynamics. Distinctive is the focus on natural computationalism and the examination of the implications of intelligent machines for the future of computational economics and finance. Not merely individual robots, but whole integrated systems are extending their "immigration" to the world of Homo sapiens, or symbiogenesis.


Agent-Based Computational Modelling

Agent-Based Computational Modelling

Author: Francesco C. Billari

Publisher: Taylor & Francis

Published: 2006-03-13

Total Pages: 684

ISBN-13: 9783790816402

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The present book describes the methodology to set up agent-based models and to study emerging patterns in complex adaptive systems resulting from multi-agent interaction. It offers the application of agent-based models in demography, social and economic sciences and environmental sciences. Examples include population dynamics, evolution of social norms, communication structures, patterns in eco-systems and socio-biology, natural resource management, spread of diseases and development processes. It presents and combines different approaches how to implement agent-based computational models and tools in an integrative manner that can be extended to other cases.


Agent-Based Modeling for Archaeology

Agent-Based Modeling for Archaeology

Author: Iza Romanowska

Publisher: SFI Press

Published: 2021-08-02

Total Pages: 442

ISBN-13: 1947864386

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To fully understand not only the past, but also the trajectories, of human societies, we need a more dynamic view of human social systems. Agent-based modeling (ABM), which can create fine-scale models of behavior over time and space, may reveal important, general patterns of human activity. Agent-Based Modeling for Archaeology is the first ABM textbook designed for researchers studying the human past. Appropriate for scholars from archaeology, the digital humanities, and other social sciences, this book offers novices and more experienced ABM researchers a modular approach to learning ABM and using it effectively. Readers will find the necessary background, discussion of modeling techniques and traps, references, and algorithms to use ABM in their own work. They will also find engaging examples of how other scholars have applied ABM, ranging from the study of the intercontinental migration pathways of early hominins, to the weather–crop–population cycles of the American Southwest, to the trade networks of Ancient Rome. This textbook provides the foundations needed to simulate the complexity of past human societies, offering researchers a richer understanding of the past—and likely future—of our species.


Empirical Agent-Based Modelling - Challenges and Solutions

Empirical Agent-Based Modelling - Challenges and Solutions

Author: Alexander Smajgl

Publisher: Springer Science & Business Media

Published: 2013-09-12

Total Pages: 254

ISBN-13: 1461461340

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This instructional book showcases techniques to parameterise human agents in empirical agent-based models (ABM). In doing so, it provides a timely overview of key ABM methodologies and the most innovative approaches through a variety of empirical applications. It features cutting-edge research from leading academics and practitioners, and will provide a guide for characterising and parameterising human agents in empirical ABM. In order to facilitate learning, this text shares the valuable experiences of other modellers in particular modelling situations. Very little has been published in the area of empirical ABM, and this contributed volume will appeal to graduate-level students and researchers studying simulation modeling in economics, sociology, ecology, and trans-disciplinary studies, such as topics related to sustainability. In a similar vein to the instruction found in a cookbook, this text provides the empirical modeller with a set of 'recipes' ready to be implemented. Agent-based modeling (ABM) is a powerful, simulation-modeling technique that has seen a dramatic increase in real-world applications in recent years. In ABM, a system is modeled as a collection of autonomous decision-making entities called “agents.” Each agent individually assesses its situation and makes decisions on the basis of a set of rules. Agents may execute various behaviors appropriate for the system they represent—for example, producing, consuming, or selling. ABM is increasingly used for simulating real-world systems, such as natural resource use, transportation, public health, and conflict. Decision makers increasingly demand support that covers a multitude of indicators that can be effectively addressed using ABM. This is especially the case in situations where human behavior is identified as a critical element. As a result, ABM will only continue its rapid growth. This is the first volume in a series of books that aims to contribute to a cultural change in the community of empirical agent-based modelling. This series will bring together representational experiences and solutions in empirical agent-based modelling. Creating a platform to exchange such experiences allows comparison of solutions and facilitates learning in the empirical agent-based modelling community. Ultimately, the community requires such exchange and learning to test approaches and, thereby, to develop a robust set of techniques within the domain of empirical agent-based modelling. Based on robust and defendable methods, agent-based modelling will become a critical tool for research agencies, decision making and decision supporting agencies, and funding agencies. This series will contribute to more robust and defendable empirical agent-based modelling.