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Human discovery has been driven by a desire to sort and simplify the world. But our ability to navigate the future will be increasingly determined by how we handle its complexity. Adam Smith, the father of economics, described the economy as a complex system.
Yet the study of social science that emerged after Smith wrote his 1776 opus The Wealth of Nations was largely about modelling the decisions of rational actors in simplified settings. That served its purpose, but as our economies have become more complex, parameters that were considered well-defined are no longer so.
We are more interconnected; technological change is exponential; our climate and environment are changing faster than we can adapt. In recent years, complexity economics has risen as a response. Three new books help outline how we can respond.
Fluke by Brian Klaas (John Murray, £20) — an associate professor in global politics at University College London — provides a captivating illustration of the follies of trying to model and forecast the chaotic and unpredictable world we inhabit. He reasserts the importance of geography, historical quirks and timing in shaping societies and economies — from how the tiny island of Britain came to dominate the world to how the sites chosen by the US to drop atomic bombs on Japan during the second world war were partly determined by an official’s vacation there some two decades prior.
Klaas entertainingly reminds us that modern human society is a complex adaptive system, “chock-full of feedback loops, tipping points, reverse causality and [an] endless array of seemingly insignificant ripples — flukes — that turn out to matter enormously”. In this world, he argues, everyone matters. The overriding notion of the book — that we control nothing but influence everything — can leave you feeling mildly helpless, but it is a fascinating hypothesis nonetheless.
That is where We Can Do Better by Maja Göpel (Scribe, £10.99), picks up the baton. In collaboration with journalist Marcus Jauer, Göpel, a political economist at the Leuphana University of Lüneburg, takes the networked and dynamic world as a given and provides a series of actionable chapters on how we ought to rethink and retool as a result of it.
Central to her argument is the need for systems thinking — understanding the world in terms of wholes and relationships, rather than by splitting it into parts. Since laws, institutions, and economic strategies shape (and interact within) complex systems, Göpel argues they must be designed with their ultimate purpose in mind. If we have not clearly established the aim and goals of markets, the state, and society, we cannot expect desired results simply to arise.
Another problem she highlights is how an inability to think about the system as a whole leads society to treat symptoms rather than underlying causes — leading to a dependency on the medicine. Indeed, western liberal democracies are today dominated by short-termist remedies for growth and social malaise, at the expense of long-term solutions (often as a result of political cycles). Instead, Göpel advocates for a fundamental re-evaluation of how we learn, place importance on wealth, use technology and organise. It is a succinct, refreshing and insightful call to action.
Making Sense of Chaos by J. Doyne Farmer (Allen Lane, £25) builds on Klaas’ thesis and Göpel’s framework by arguing that economics is in need of a radical update. Farmer, a complex systems scientist originally from the US, is director of the Complexity Economics programme at the Institute for New Economic Thinking at the Oxford Martin School.
Breaking down the flaws in current economic analyses and assumptions, Farmer illustrates a path forward. At the heart of economics is the idea that systems are shocked, tend towards a balance of supply, and operate within linearly defined economic relationships. It’s an appealingly simple model. Yet it is increasingly lacking when technology and the connected global economy — with complex supply chains, trade, and capital flows — is evolving rapidly, regularly and unpredictably.
Farmer convincingly argues that by using big data and today’s more powerful computers, we can build more realistic models and simulations of the global economy. This does not guarantee forecasts will be more accurate; models are still affected by our judgments. But it does ensure the calculations and processes are more in tune with the reality of complexity. As recent economic shocks — from the Covid pandemic to wars — have demonstrated, simplified models of cause and effect are woefully deficient. Farmer’s vision will undoubtedly be significant in how economics evolves.
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