1The book, edited by Ping Chen, Wolfram Elsner, and Andreas Pyka, is an unprecedented enterprise in complexity economics. Coordinating its creation was challenging, and reading its whole fruit is only slightly more manageable. Writing a just but short review of such an opus magnum might be the most difficult of all, and that’s why this one will limit itself to presenting the structure, methods, aims of the book, and the role it might play in the ongoing debates on the future of economic discipline. In the beginning, it’s worth mentioning the importance of the book goes beyond this field as it makes use of various disciplines together constituting the meta-discipline of the complexity science.
2The Routledge International Handbook of Complexity Economics (RIHCE) comprises thirty-seven contributions, including those from well-established precursors of the discipline and young scholars. Their works, previously published independently, now clearly appear to us as a system of interconnectedness between their research. That might be the most significant advantage of the book. It collects in one place the achievements of various academic and scientific initiatives, helping to realize how their investigations support each other in forming the new research paradigm of complexity economics. It focuses on emergent properties resulting from complex interactions between heterogenous economic agents. Contributors explain the research paradigm step by step within the Handbook’s structure in consecutive parts, presenting its basics (I.1), methods (I.2), domains (II.1), challenges (II.2), politics (III.1), and policies (III.2).
3The chapters W. Brian Arthur, Giovanni Dosi, and Alan Kirman authored are the first to mention because of their long-term experience exploring the possibilities of complexity economics. Arthur, who was there almost forty years ago when physicists and economists sowed the seeds of this perspective on the deserts of New Mexico, comes with “Some Thoughts on Agent‑Based Modeling and the Role of Computation in Economics” (122-128). Agent-Based Modeling (ABM) is a topic frequently recurring in almost eight hundred pages of the Handbook, and it deserves a separate paragraph in this review as well. Dosi and co-authors also focus on modeling when closing the book with their immense presentation of “A Complexity View on the Future of Work.” They discuss it using the “Multi‑sector K+S Agent‑Based Model” (677-725). On the other hand, Kirman and Mauro Gallegati, in the first chapter, “Stairway to Complexity,” tell the story of historical development toward this perspective in economics (22-37). Interest in this path grew with acknowledgment of nonlinearities, emergent properties, and other outcomes of interactions among heterogeneous agents.
4The turn of 2024 and 2025 was full of essential book releases for the research program comprehensively presented in the RIHCE. Among them are Michael Roos’ Principles of Complexity Economics (2024), Jin Chen and James K. Galbraith’s Entropy Economics (2025), and the series “Elements in Complexity and Agent-based Economics,” opened by two books by Giacomo and Mauro Gallegati (Gallegati et al., 2025a; 2025b). Each of these authors is present in the reviewed work. Roos narrows down his contribution to his area of expertise, presenting “Climate Change from the Perspective of Complexity Economics” (486-497). Gallegati supports Kirman in the abovementioned opening. Galbraith and Chen explain “A Biophysical Approach to Production Theory (514-527),” which can be an introduction to their new book. However, for Galbraith, it isn’t the only contribution. Together with editor Ping Chen, Victor M. Yakovenko, and Thomas Berger, he is among the authors who worked on two chapters of the Handbook.
5The landscape of the 21st-century twenties has already seen many raids of complexity economics fighting for a well-deserved recognition as a research program whose applications could significantly improve the effectiveness of our policies and, as a result, our well-being. Compared to these raids, RIHCE is like a massive frontal attack. However, this is where the problem with coordinating such a giant project full of various contributors becomes the most visible. Heterodox economists tend to treat the so-called “mainstream” as a scapegoat, precisely presenting its intellectual shortcomings, but much less often referring in this context to specific works and authors. Here, the problems of coherence appear. Most chapters refer to “neoclassical,” “standard,” or “mainstream” economics, only occasionally attempting to define them. Without a clear definition, we cannot be sure what their authors mean when using this term (Colander, 2000)—and neither they nor the editors mention the relation between various uses of it in particular chapters. This naturally raises several questions: Where runs the boundary between heterodox schools and “mainstream”? Is, e.g., the behavioral school (whose scholars have won the Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel twice) heterodox? Does the “mainstream” already accept some elements of the complexity economics research program? Complexity science confers great importance to the process of evolution in various domains. That’s why, when writing on complexity economics, we should carefully study how alternative approaches penetrate incumbent theories through blurry boundaries between them. Writing about separate “heterodoxy” and “mainstream” isn’t enough.
6Science’s progress is not only about blurring the line between the old, well-recognized, incumbent research program and a toolkit of new, promising insights within one discipline. Complexity economics, born in the 1987 Santa Fe Institute discussion between physicists and economists (Beinhocker, 2006, 46-48), knows about it extraordinarily well. RIHCE not only reaches for standard methods in this area adapted from physics and biology but also attempts to learn from studies on human development, like agriculture or urbanism. Special attention is devoted to an area of study in-between—epidemiology. The chapter by Torsten Heinrich starts with one of the best short explanations of the beginning of the Covid-19 pandemic (498-499). Heinrich is not alone in his research interest. “Why did no one see it coming?” That was the question Queen Elizabeth famously posed to economists in November 2008, six weeks into the financial crisis (Martin, 2023). Complexity economists in the Handbook ask the same question about the pandemic. Their observations on communication issues caused by fake news and anti-science movements in these dark days can lead to an interesting conclusion. Complexity economics might be one of the biggest victims of modern-day anti-intellectualism. Scientists, who indicate how our small irresponsible customs and habits, when widespread, might cumulate into a catastrophe, rarely raise the sympathy of the crowds.
7Despite what one might expect from its forward-looking nature, complexity economics is not a movement that shows insufficient respect for its discipline’s intellectual roots. A few authors, not only those whose chapters we’ll find at the beginning of the book, use the history of economic thought perspective. It makes RIHCE intergenerational in more than just one meaning of this term. Not only does it collect contributions from various contemporary generations of scholars, but it also underlines the progress made by economics from one generation to another, leading to the emergence of complexity economics. The journey begins with Adam Smith and his vision of spontaneous order, a concept essential for the research program (Farmer et al., 2012). The path leads to the greatest minds of the 20th century, Keynes and Schumpeter, who also gained their well-deserved place in consideration of the complex economy and the uncertainty it caused. What’s interesting is that Marx doesn’t appear as much as a forerunner of complexity economics, but his modern understanding is juxtaposed with the research program in a sizeable chapter by Frank Beckenbach (592-630). However, when it comes to dialogue with different schools, complexity economists aren’t only looking backward but also around themselves. It leads to plural references to institutionalist Nobel Prize winners. Not only those established as well as Douglass North or Elinor Ostrom but often to the most recent laureate, Daron Acemoglu. This promising dialogue will for sure develop in the Handbook on Institutions and Complexity (Alston et al., 2025).
8If, due to the size of this review, it is necessary to limit explanations to only one of the tools considered in the RIHCE, it should be Agent-Based Modeling. Agent-Based Models appears in the vast majority of the chapters discussing challenges as various as the threat of natural hazards and the future of the labor market. Its ubiquitousness in the book is not a matter of accident. Agent-Based Models has already achieved recognition as a tool that might revolutionize the way we model interactions between heterogeneous actors and is one of the most significant achievements of complexity economics so far. Agent-Based Models are computational models in which individuals are represented as unique and autonomous entities interacting with each other and exogenous environments (Railsback and Grimm, 2019). These interactions lead to emergent effects that differ from the effects of individual agents’ activities. The tool counters traditional, regression-based methods in that, like systems dynamics modeling, it allows for exploring complex systems that display non-independence of individuals and feedback loops in causal mechanisms. There is a growing conviction that these models better match the realities of the complex 21st-century economy, and some already out-predict traditional methods (Farmer, 2024, XVIII). Every day, their potential is studied in new areas, such as competition law enforcement (Schrepel and Schuler, 2024).
9After reading this concise review of the giant book, one could assume that this monography abandons the mathematical foundations of economics to follow the wisdom of the natural sciences and look back into the intellectual history of the discipline. Nothing is less accurate. As for a work made of so many individual contributions, RIHCE shows a surprising dominance of chapters focused on quantitative analyses. Their analytical character isn’t limited to numbers and formulas. The book contains hundreds of tables and graphs explaining and illustrating everything from basics to ambitions of complexity economics. It makes this informative monography a sound starting point for a wide discussion on what kind of perspective and tools we need to confront the coming challenges of the modern economy.