Volume I: An Alternative Way of Understanding Societies and their Economies
Volume II: Computational Models, Validation, and Applications

Gonzalo Castañeda

With the recent developments in computing technologies and the thriving research scene in Complexity Science, economists and other social scientists have become aware of a more flexible and promising alternative for modelling socioeconomic systems; one that, in contrast with neoclassical economics, advocates for the realism of the assumptions, the importance of context and culture, the heterogeneity of agents (individuals or organisations), and the bounded rationality of individuals who behave and learn in multifaceted ways in uncertain environments. The book synthesises an extensive body of work in the field of social complexity and constructs a unifying framework that allows developing concrete applications to important socioeconomic problems. This one-of-a-kind textbook provides a comprehensive panorama for advanced undergraduates and graduate students who want to become familiar with a wide range of issues related to social complexity. It is also a pioneering text that can support professors who wish to learn techniques and produce research in this novel field.
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After reviewing the main concepts, premises and implications of complexity theory, the book frames this vision within the history of economic thought. Then, it articulates a meta-theory in which interdependent agents are embedded in a social context and whose collective and decentralised behaviour generates socio-economic phenomena. Such a framework builds on theories from evolutionary, institutional and behavioural economics, as well as analytical sociology. The book then reviews different computational tools for modelling complex adaptive systems, such as cellular automata, networks, and agent-based models. It elaborates on their analytical advantages in comparison to equation-based models, and how they can be calibrated/estimated and validated with empirical data. Finally, the book advocates for the practical use of these computational tools and makes a case for policy applications and the study of causal mechanisms.

More at: www.social-complexity.com

More at: complexnetworks.org

Euan Mearns and Didier Sornette

From 1966 to 1976, four large earthquakes shook the Bohai Bay rift basin of Northeast China. This prompted the Chinese to launch one of the world’s largest social and science experiments into earthquake prediction that would engage tens of thousands of common people. The climax of this came in February 1975 where a prediction was made hours before the Haicheng earthquake struck. Evacuation of the city of Yingkou and some rural districts saved thousands of lives. The Chinese were jubilant, believing they had cracked the earthquake prediction conundrum. Eighteen months later, however, on the 28th July, 1976, jubilation turned to despair when a great earthquake flattened the large industrial city of Tangshan resulting in 250,000 to 650,000 casualties. This book describes the geological, technical, political and sociological backgrounds to the Haicheng prediction success and the Tangshan prediction failure.
Ahead of the Tangshan earthquake, Chinese seismologists had accumulated significant information that suggested an earthquake was imminent and came close to making a prediction. With improved knowledge and vastly improved ability to accumulate, consolidate and analyse data, this book suggests that Tangshan could have been predicted today using techniques developed in China in that epic decade of discovery. Building on these insights, it also offers a viable future pathway towards earthquake predictions that combines the insights and organisation of the 1966-1976 Chinese prediction program with modern technologies, in order to facilitate data gathering, interpretation and sharing.

More at: www.cambridgescholars.com

COVID-19 is the virus that proved the fragility of the world. It took only the simplest form of life to shake the connectivity and dependency of society. This book is a real-time record and recommendation from a community of complexity scientists reacting to the pandemic. Through nontechnical articles, interviews, and discussions spanning the early days of the pandemic through the fall of 2021, researchers seek ways to stay responsive to complexity when every force conspires toward simplicity. The Complex Alternative encompasses immunology, epidemiology, psychology, inequality, and collapse. It is an effort to preserve perspective at a time when partiality seeks dominion.

Edited by David C. Krakauer and Geoffrey West, this book features the thoughts of more than sixty members of the Santa Fe Institute’s research community on the future of complexity science and the broader significance of science in the twenty-first century.

More at: www.sfipress.org

Presents current theoretical, empirical, and operational efforts tackling corruption studies.
Introduces the relevance of evidence-based and network approaches to anticorruption.
Discusses the best ways to convert the obtained knowledge into public policy.

More at: link.springer.com