By Bryon Robidoux
This article explores, as demographic patterns grow more complex, how integrating complexity theory into actuarial science and deeper engagement with heterodox economic perspectives can help actuaries build more resilient, adaptive models for the future.
In layman’s terms, demographics is the study of the characteristics of people in a population-such as their age, gender, race/ethnicity, income, and where they live-to understand how groups change and grow over time. This article doesn’t look into evolving demographic statistics, but instead will examine the impact of those statistics on global politics and the economy, especially how they cause stability or instability. I will begin at a high level and gradually delve deeper, focusing on the complexity of interactions. The exploration will review how interactions and complexity impact actuarial and economic models. Finally, I will provide some suggestions on moving forward.
Globalization
In his book, The End of the World Is Just the Beginning: Mapping the Collapse of Globalization-The Collapse of Globalization and Its Aftermath, geopolitical strategist Peter Zeihan defines deglobalization as the unraveling of the interconnected global economic system that has existed since the end of World War II. The U.S. built the foundation of globalization by providing global security, cheap energy, stable supply chains, and open international trade. This system enabled unprecedented economic growth, stability, efficiency, and innovation worldwide. Still, it was always fragile-dependent on U.S. willingness to guarantee the safety of global trade routes and maintain international order.
Zeihan argues that the pillars supporting globalization are now collapsing. The U.S. is retreating from its role as a global protector, making international shipping and trade riskier and less reliable. At the same time, demographic decline (aging and shrinking populations in many countries), resource scarcity, and rising geopolitical tensions undermine the foundations of global supply chains. As these trends accelerate, the world will fragment into regional economies, where goods become more expensive and lower in quality, and countries increasingly compete-sometimes militarily-for access to resources and secure trade routes. Deglobalization marks the end of the world as we know it: A shift from an era of global cooperation and abundance to one of regional fragmentation, scarcity, and instability, driven by the breakdown of the systems that made globalization possible.[1]
Another way to reconcile Zeihan’s concerns on deglobalization is by understanding network science. University of Pennsylvania Professor Damon Centola’s book, Change: How to Make Big Things Happen teaches how large networks with strong ties foster immunity to change and contagions. Weak network ties are fragile because contagions can spread rapidly, causing frequent instability. Therefore, as global supply chain connections atrophy and weaken, we should expect amplified global variability due to less immunity to contagious events.[2]
Demographics and the Complex World
In his book, Demographics Unravelled: How Demographics Affect and Influence Every Aspect of Economics, Finance and Policy, global macro researcher Amlan Roy says, “People influence social change and policies. The environment that they live in conditions their behavior. The environment determines the interaction of various systems (health, education, labor, social welfare, legal, political, etc.) and the institutional framework. Policies have a role to play, and the role of government influences the environment within which consumers and workers reside.”[3]
Furthermore, the age distribution of a country impacts the speed at which the economy is growing and its fundamental properties. As people age, their consumption versus savings habits morph.[1,3] Young people have families and buy houses, which makes them heavy consumers taking on debt because incomes are low in their 20s and 30s. A young population will have a rapidly growing, debt-driven economy. As people age, they pay down the debt and mature in their careers until the kids move out or go to college. Once the kids are gone, consumption decreases, and savings increase as they prepare for retirement. In retirement, they draw down their savings and consumption levels for everything but health care.[1] These savings and consumption habits impact politics, too.
For instance, we now have countries such as China, Germany, and Italy, with more people over 40 than under 40. In these countries, health and social welfare have become massive issues. There could likely not be enough workers to take care of the aging population. This distribution of ages can have radical repercussions on the cost of capital and a country’s various institutions and politics.[1]
Understanding Governmental Institutions and Their Roles
2024 Nobel laureates Daron Acemoglu and James A. Robinson, in their tome, Why Nations Fail: The Origins of Power, Prosperity, and Poverty, clearly illustrate that politics and economics are inseparable. Politics is the operating system in which the economy runs, much like Microsoft Windows is to Excel.[4] Institutions can either be extractive or inclusive and pluralistic.
Extractive Institutions
The more extractive government institutions the more power is concentrated in a small, fortunate few who are incredibly wealthy while the population suffers in poverty. Even if extractive governments appear extremely prosperous, history has shown that the prosperity will likely reverse,[4] much like Argentina in the 20th century.[1] An increase in economic power leads to a rise in political power, and vice versa, through a vicious cycle. This cycle forces extractive countries to become more extractive, poorer, and less stable.[4]
Inclusive and Pluralistic Institutions
The wealth and prosperity of a nation depend on the inclusiveness and plurality of the institutions, which create a healthy friction between groups, ensuring the stabilization of power among them. As diversity, equity, and inclusion increase, the friction becomes healthier, magnifying the stability of the institutions. As long as the political and economic powers stay balanced, everyone will work together to create more inclusive and pluralistic societies through the virtuous cycle.4
In Power and Progress: Our Thousand-Year Struggle Over Technology and Prosperity, Nobel laureates Acemoglu and Simon Johnson explain that when smaller, innovative, competitive companies exist, they fight for the best people, giving laborers more bargaining power and a larger share of productivity gains. Consumers win because they can purchase cheaper, more innovative products. The governed win because power is balanced, and institutions stay inclusive and pluralistic. Healthy competition produces creative destruction, which causes older, less competitive organizations to die and younger, more innovative companies to take their place. Therefore, establishing well-functioning antitrust laws is paramount for keeping economic and political power contained and keeping the government secure, stable, long-lasting, and prosperous.[5]
Coming Full Circle
Currently, the stability of the global economy ultimately rests on the stability of the U.S. institutions. In The Myth of Capitalism: Monopolies and the Death of Competition, authors Jonathan Tepper and Denise Hearn illuminate how, as companies merge, competition suffers, innovation decreases, labor has less bargaining power, and political and economic dominance increases. As political dominance swells, unhealthy conformity follows, allowing more extractive institutions. Over the last 50 years, this process has occurred in the U.S. due to its evolving antitrust definition, increasing enforcement difficulty. As organizations and institutions become more extractive, the government loses stability due to infighting and unhealthy friction, leading to our current political environment.[6]
Demographics and Complexity
As I have tried to demonstrate, our world is a complex adaptive system (CAS). A CAS is a dynamic network of interacting, heterogeneous agents (people, firms, and institutions) that adapt and evolve in response to environmental changes, leading to emergent behaviors that cannot be predicted by analyzing individual components alone. These systems exhibit self-organization, nonlinear interactions, and feedback loops, enabling them to maintain resilience and functionality despite external perturbations. This stability happens with no centralized control.[7]
Redefining Demographics
When studied through the lens of CAS, demographics emphasizes the dynamic interplay of individuals, environmental factors, and social structures that drive population changes. Furthermore, it explores how diverse individuals and groups adapt to their circumstances and respond to changing environments, producing unpredictable, emergent patterns in population size, structure, and distribution over time. By framing demographics as a CAS, researchers can better capture the unpredictability and interdependence inherent in population systems, moving beyond simplistic linear equilibrium models, which ignore essential interactions.
How Does Complexity Impact Models and the Work of Actuaries?
Static equilibrium analysis is the bedrock of actuarial science, financial mathematics, and economics. Static equilibrium in economics refers to a market condition where supply equals demand at a particular price and quantity, and there are no inherent forces causing change-meaning there is no incentive for buyers or sellers to alter their behavior. Economists typically analyze this state as a snapshot without considering how the market reached this point or how it might evolve.
The limitation of static equilibrium analysis is that it ignores how markets move toward equilibrium and how long it takes.[8] Furthermore, it does not capture the effects of unexpected events or the adjustment process-dynamic models address these. But in the podcast “Ninety-Eight Years of Economic Wisdom” on Freakonomics Radio Network, economist Robert Solow states that economists design current models more as mathematical exercises than as tools to explain how the economy works largely because they rely on dynamic stochastic general equilibrium (DSGE) models. Solow does not take DGSE seriously because it assumes a single-person economy conforming to her whims.
You Can’t Unfry an Egg
Nobel Laureate Ilya Prigogine’s The End of Certainty: Time, Chaos and the New Laws of Nature explains that complexity scientists would describe static equilibrium models as Newtonian, suitable for mechanical, linear systems. The results are predictable from their starting parameters. If given a couple of points along the path of an object, their future path is predictable. More astonishingly, the path before the starting point can be determined by reversing time, much like the planets orbiting in the heavens. This time invariability gives great power for reducing systems to their fundamental components to describe their behavior. You can re-create the process by running a single entity.[9]
CAS vastly differs because thousands, millions, or billions of agents work simultaneously. The properties of the system emerge from the aggregate behavior of the individual agents, so you cannot analyze the pieces to understand the big picture.[7] As you add more energy to the system, new, unexpected behaviors and properties manifest, causing a bifurcation. At the bifurcation or tipping point, time is no longer reversible. You won’t be able to get back to what you had. For instance, you cannot unfry an egg by cooling it! Bifurcation is where risk becomes uncertain and significantly diminishes or loses predictability.[9]
Predicting and Managing Instability
Static equilibrium models vastly overstate the predictability of the world and future events. Bank of England economist Sir Mervyn King’s Radical Uncertainty: Decision-Making Beyond the Numbers, clarified that during the 2008 Global Financial Crisis (GFC), banks could not make sense of their equilibrium model results. During the worst days of the crisis, they had to abandon their models when they needed them the most. They had to go back to basics. Furthermore, it says there is little information and use of applying random jumps to fatten the tails when creating economic scenarios if there is an inability to explain why the jumps occur.[10]
Compare and Contrast Models
To understand the revolution happening in economics, read Steve Keen’s book, The New Economics: A Manifesto, especially the chapters “Why the Manifesto” and “Neoclassical Disease.” He argues that equilibrium analysis assumes that the sum of the parts equals the whole, whereas a CAS assumes the whole equals the sum of its parts and all the interactions between them.[8] In extremely adverse scenarios, we provide insurance where the interactions’ risk will overwhelm the parts’ risk.
In Making Sense of Chaos: A Better Economics for a Better World, Doyne Farmer of the Santa Fe Institute outlines a framework of complexity economics grounded in CAS, contrasting it with traditional neoclassical, equilibrium-based models. He illustrates this distinction through the example of Basel II banking regulations during the GFC. Under a static equilibrium framework, Basel II regulators assumed that the banking industry could minimize systemic risk if each bank independently minimized its risk-implying that industry-wide risk was merely the sum of its parts. However, this assumption proved dangerously flawed. In practice, Basel II amplified risk rather than reducing it. During the market downturn, regulatory guidelines prompted banks to behave similarly. As institutions sold off assets to manage their portfolio risks, asset prices declined, triggering further sell-offs across the system. This sell-off created a positive feedback loop in which the interactions among banks overwhelmed individual risk management strategies, exacerbating the severity of the crisis.[11]
The Potential Solution
Suppose Zeihan is correct that deglobalization marks a shift to regional fragmentation, scarcity, and instability, driven by the breakdown of the systems that made globalization possible. In that case, we need more dynamic modeling techniques such as simulations, nonlinear mathematics, and agent-based models to capture adaptation and feedback. Furthermore, we must look at heterodox versions of economics, such as complexity, evolutionary, quantum, and others, to acquire diverse perspectives and solutions to our problems. Treating one flavor of economics as dogma is risky, as banks discovered during the GFC.
I am learning the open-source agent-based simulation software Minsky, written and maintained by Steve Keen and his team. Its advantage is that it is built explicitly for financial modeling because it allows for double-entry accounting. It can model large-scale macro economies of money supply and capital and smaller-scale models of the internal workings of insurance assets and liabilities. It can create alternative scenarios, complement our current models, and give new insights.[8]
The Bottom Line
The world is a dynamic system marked by complexity and constant interaction. Demographic analysis offers one lens through which we can make sense of its emergent behaviors. World War II was a critical bifurcation point, ushering in the baby boom and the era of globalization. Globalization delivered the growth and stability that shaped the past 80 years. But that era is ending: globalization is retreating, and the baby boomers are retiring. These shifts will profoundly affect the global economy, politics, and society.
Equilibrium-based financial models presuppose a stable environment, which globalization luckily provided, yet they offer no account of how such stability arises-or collapses. This omission becomes critical as the global system retracts and breaks current strong economic ties. As seen in previous crises, components’ nature and degree of interaction are central to identifying failure points, bifurcations, and evolving relationships between variables. As the Global Financial Crisis made clear, models grounded in equilibrium assumptions systematically overlook these dynamics, rendering them increasingly inadequate for understanding and managing systemic risk in a deglobalizing world.
Even without factoring in climate change-which this article has not addressed-the potential for instability is substantial. This article advocates for integrating complexity theory into actuarial science and a deeper engagement with heterodox economic perspectives. These tools and frameworks may prove essential for navigating the demographic and systemic shifts likely to define the decades ahead.
Bryon Robidoux, MAAA, FSA, CERA, is an assistant vice president of Product Development at Constellation Insurance.
Endnotes
- Zeihan, Peter, The End of the World Is Just the Beginning: Mapping the Collapse of Globalization, Harper Business, an Imprint of HarperCollinsPublishers, 2022.
- Centola, Damon, Change: How to Make Big Things Happen, John Murray, 2022.
- Roy, Amlan, Demographics Unravelled: How Demographics Affect and Influence Every Aspect of Economics, Finance and Policy, John Wiley & Sons, Ltd, 2022.
- Acemoglu, Daron, Why Nations Fail: The Origins of Power, Prosperity, and Poverty, Crown Currency, 2013.
- Acemoglu, Daron, and Simon Johnson, Power and Progress: Our Thousand-Year Struggle over Technology and Prosperity, Public Affairs, 2024.
- Tepper, Jonathan, The Myth of Capitalism: Monopolies and the Death of Competition, John Wiley & Sons, Inc., 2023.
- Miller, John H., and Scott E. Page, Complex Adaptive Systems: An Introduction to Computational Models of Social Life, Princeton University Press, 2007.
- Keen, Steve, The New Economics: A Manifesto, Polity Press, 2022.
- Prigogine, I., and Isabelle Stengers, The End of Certainty: Time, Chaos, and the New Laws of Nature, Free Press, 1997.
- Kay, John, and Mervyn A. King, Radical Uncertainty: Decision-Making beyond the Numbers, W.W. Norton & Company, 2021.
- Farmer, J. Doyne, Making Sense of Chaos: A Better Economics for a Better World, Yale University Press, 2024.