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Economics and the social sciences are, in fact, the “hard” sciences, as Herbert Simon argued, because the complexity of the problems dealt with cannot simply be reduced to analytically solvable models or decomposed into separate subprocesses. Nevertheless, in recent years, the emerging interdisciplinary “sciences of complexity” have provided new methods and tools for tackling these problems, ranging from complex data analysis to sophisticated computer simulations. In particular, advanced methods developed in the natural sciences have recently also been applied to social and economic problems.The twenty-one chapters of this book reflect this modern development from various modeling perspectives (such as agent-based models, evolutionary game theory, reinforcement learning and neural network techniques, time series analysis, non-equilibrium macroscopic dynamics) and for a broad range of socio-economic applications (market dynamics, technological evolution, spatial dynamics and economic growth, decision processes, and agent societies). They jointly demonstrate a shift of perspective in economics and the social sciences that is allowing a new outlook in this field to emerge.
A new view of the economy as an evolving, complex system has been pioneered at the Santa Fe Institute over the last ten years, This volume is a collection of articles that shape and define this view?a view of the economy as emerging from the interactions of individual agents whose behavior constantly evolves, whose strategies and actions are always adapting.The traditional framework in economics portrays activity within an equilibrium steady state. The interacting agents in the economy are typically homogenous, solve well-defined problems using perfect rationality, and act within given legal and social structures. The complexity approach, by contrast, sees economic activity as continually changing?continually in process. The interacting agents are typically heterogeneous, they must cognitively interpret the problems they face, and together they create the structures?markets, legal and social institutions, price patters, expectations?to which they individually react. Such structures may never settle down. Agents may forever adapt and explore and evolve their behaviors within structures that continually emerge and change and disappear?structures these behaviors co-create. This complexity approach does not replace the equilibrium one?it complements it.The papers here collected originated at a recent conference at the Santa Fe Institute, which was called to follow up the well-known 1987 SFI conference organized by Philip Anderson, Kenneth Arrow, and David Pines. They survey the new study of complexity and the economy. They apply this approach to real economic problems and they show the extent to which the initial vision of the 1987 conference has come to fruition.
How ideas in complexity can be used to develop more effective public policy Complexity science—made possible by modern analytical and computational advances—is changing the way we think about social systems and social theory. Unfortunately, economists' policy models have not kept up and are stuck in either a market fundamentalist or government control narrative. While these standard narratives are useful in some cases, they are damaging in others, directing thinking away from creative, innovative policy solutions. Complexity and the Art of Public Policy outlines a new, more flexible policy narrative, which envisions society as a complex evolving system that is uncontrollable but can be influenced. David Colander and Roland Kupers describe how economists and society became locked into the current policy framework, and lay out fresh alternatives for framing policy questions. Offering original solutions to stubborn problems, the complexity narrative builds on broader philosophical traditions, such as those in the work of John Stuart Mill, to suggest initiatives that the authors call "activist laissez-faire" policies. Colander and Kupers develop innovative bottom-up solutions that, through new institutional structures such as for-benefit corporations, channel individuals’ social instincts into solving societal problems, making profits a tool for change rather than a goal. They argue that a central role for government in this complexity framework is to foster an ecostructure within which diverse forms of social entrepreneurship can emerge and blossom.
There is no term that better describes the essential features of human society than complexity. On various levels, from the decision-making processes of individuals, through to the interactions between individuals leading to the spontaneous formation of groups and social hierarchies, up to the collective, herding processes that reshape whole societies, all these features share the property of irreducibility, i.e., they require a holistic, multi-level approach formed by researchers from different disciplines. This Special Issue aims to collect research studies that, by exploiting the latest advances in physics, economics, complex networks, and data science, make a step towards understanding these economic and social systems. The majority of submissions are devoted to financial market analysis and modeling, including the stock and cryptocurrency markets in the COVID-19 pandemic, systemic risk quantification and control, wealth condensation, the innovation-related performance of companies, and more. Looking more at societies, there are papers that deal with regional development, land speculation, and the-fake news-fighting strategies, the issues which are of central interest in contemporary society. On top of this, one of the contributions proposes a new, improved complexity measure.
. . . in my opinion. . . readers. . . should find in this book both several remarkable insights concerning basic statements of evolutionary theorising and concrete results that can be acquired by applying such basic statements in computer simulation models and in various fields of analysis. Mauro Lombardi, The Journal of Artificial Societies and Social Simulation Complexity theory first emerged three decades or so ago, but only recently has its potential relevance for the study of social and economic phenomena really begun to be recognised. This timely collection of essays clearly demonstrates, both conceptually and empirically, how complexity theory ideas can provide considerable insight into how socio-economic systems cities, societies, industries, technologies and economies evolve and adapt over time. It is essential reading for anyone interested in how order and evolution emerge out of the seemingly chaotic socio-economic world around us. Ron Martin, University of Cambridge, UK I read Complexity and Co-Evolution with real pleasure. These authors have done the near impossible they have made the concepts of a new and evolving science accessible to people who can apply it in practical ways. The clarity of writing reflects the sort of confidence only the truly informed can muster, for they need no jargon to cover confusions. Their mastery allows them to present the essentials in simple, unadorned forms and through genuinely illustrative examples. Any manager or director trying to navigate dynamic markets can use this book to learn new ways of thinking, explore new possibilities, and study historical experiences. Robert Artigiani, United States Naval Academy Current thinking about evolutionary dynamics increasingly relies on co-evolution, and co-evolution increasingly implies complex dynamics of one sort or another. This volume brings together a capable and well-balanced group of thinkers on these topics who explore these deeply related concepts with up-to-date and advanced tools and concepts. For anyone wishing to learn about the latest developments in these rapidly developing areas, this book is highly recommended. J. Barkley Rosser Jr., James Madison University, US This book applies ideas and methods from the complexity perspective to key concerns in the social sciences, exploring co-evolutionary processes that have not yet been addressed in the technical or popular literature on complexity. Authorities in a variety of fields including evolutionary economics, innovation and regeneration studies, urban modelling and history re-evaluate their disciplines within this framework. The book explores the complex dynamic processes that give rise to socio-economic change over space and time, with reference to empirical cases including the emergence of knowledge-intensive industries and decline of mature regions, the operation of innovative networks and the evolution of localities and cities. Sustainability is a persistent theme and the practicability of intervention is examined in the light of these perspectives. Specialists in disciplines that include economics, evolutionary theory, innovation, industrial manufacturing, technology change, and archaeology will find much to interest them in this book. In addition, the strong interdisciplinary emphasis of the book will attract a non-specialist audience interested in keeping abreast of current theoretical and methodological approaches through evidence-based and practical examples.
This book presents a survey of the aspects of economic complexity, with a focus on foundational, interdisciplinary ideas. The long-awaited follow up to his 2011 volume Complex Evolutionary Dynamics in Urban-Regional and Ecologic-Economic Systems: From Catastrophe to Chaos and Beyond, this volume draws together the threads of Rosser’s earlier work on complexity theory and its wide applications in economics and an expanded list of related disciplines. The book begins with a full account of the broader categories of complexity in economics--dynamic, computational, hierarchical, and structural--before shifting to more detailed analysis. The next two chapters address problems associated with computational complexity, especially those of computability, and discuss the Godel Incompleteness Theorem with a focus on reflexivity. The middle chapters discuss the relationship between entropy, econophysics, evolution, and economic complexity, respectively, with applications in urban and regional dynamics, ecological economics, general equilibrium theory, as well as financial market dynamics. The final chapter works to bring together these themes into a broader framework and expose some of the limits concerning analysis of deeper foundational issues. With applications in all disciplines characterized by interconnected nonlinear adaptive systems, this book is appropriate for graduate students, professors and practitioners in economics and related disciplines such as regional science, mathematics, physics, biology, environmental sciences, philosophy, and psychology.
A 'Non-Toxic' Intermediate Textbook 'Here, at last, we have the ideal textbook for microeconomics from an evolutionary and institutional perspective. Wolfram Elsner does nothing less than reconstruct the principles of microeconomics for a world of interactive business networks, change and innovation, crisis and uncertainty, as well as coordination problems and cooperative joint ventures. The publication of this book is a landmark event in microeconomics.' – Phillip A. O'Hara, Curtin University of Technology, Perth, Australia and President-Elect of AFEE, 2012 'This microeconomics textbook by Wolfram Elsner provides a timely alternative for understanding the micro roots of uncertainty, complexity and crisis. The evolutionary and institutional perspective sheds new light on contemporary issues such as clusters, networks, innovation and coordination. By reading this textbook, teachers, students and practitioners will open their minds to new economic thinking.' – Ping Chen, Peking University, Beijing, Fudan University, Shanghai, China and author of Economic Complexity and Equilibrium Illusion This thorough reconstruction of microeconomics 'post-2008' provides economic students with a new way of real-world understanding and strategic qualification that will be better appreciated by their future employers and any professional practice. It will prove essential for economic students and other social science programs at a graduate level. This accessible and engaging textbook includes: • A survey of the most famous core models of modern microeconomics including the neoclassical approach and its heterodox critiques – Sraffian, Institutionalist, Post-Keynesian and Mirowskian • An introduction to complexity thinking in economics • An introduction to game theory • An introduction to the methods of complex computer simulation • An introduction to strategic behavior • An newly integrated approach to real-world and complexity economics, rather than focusing on neoclassical ('perfect') market equilibrium 'plus a thousand recent extra things on top'. See the companion website – www.microeconomics.us – for teaching material, readings, exams and as a general guide to explore issues raised in the book.
A collection of previous published papers by the author on the subject of complexity economics, appearing from the 1980s to the present.
This book now has something new to say about innovation analysing it in complex social systems while making innovation understandable and tractable using tools such as computational network analysis and agent-based simulation.
Social systems are among the most complex known. This poses particular problems for those who wish to understand them. The complexity often makes analytic approaches infeasible and natural language approaches inadequate for relating intricate cause and effect. However, individual- and agent-based computational approaches hold out the possibility of new and deeper understanding of such systems. Simulating Social Complexity examines all aspects of using agent- or individual-based simulation. This approach represents systems as individual elements having each their own set of differing states and internal processes. The interactions between elements in the simulation represent interactions in the target systems. What makes these elements "social" is that they are usefully interpretable as interacting elements of an observed society. In this, the focus is on human society, but can be extended to include social animals or artificial agents where such work enhances our understanding of human society. The phenomena of interest then result (emerge) from the dynamics of the interaction of social actors in an essential way and are usually not easily simplifiable by, for example, considering only representative actors. The introduction of accessible agent-based modelling allows the representation of social complexity in a more natural and direct manner than previous techniques. In particular, it is no longer necessary to distort a model with the introduction of overly strong assumptions simply in order to obtain analytic tractability. This makes agent-based modelling relatively accessible to a range of scientists. The outcomes of such models can be displayed and animated in ways that also make them more interpretable by experts and stakeholders. This handbook is intended to help in the process of maturation of this new field. It brings together, through the collaborative effort of many leading researchers, summaries of the best thinking and practice in this area and constitutes a reference point for standards against which future methodological advances are judged. This book will help those entering into the field to avoid "reinventing the wheel" each time, but it will also help those already in the field by providing accessible overviews of current thought. The material is divided into four sections: Introductory, Methodology, Mechanisms, and Applications. Each chapter starts with a very brief section called ‘Why read this chapter?’ followed by an abstract, which summarizes the content of the chapter. Each chapter also ends with a section of ‘Further Reading’ briefly describing three to eight items that a newcomer might read next.