There's no economic mastermind

Everyone chooses. Yet, no one chooses the outcome.

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Picture a city’s skyline. Did any single person decide its shape? Of course not. It emerged from countless individual decisions, constrained by geography, economics, and regulation. Yet, when we look at economic outcomes, we often fall into the trap of assuming there must be a master plan or some sinister (or benevolent) motives behind what happens.

Philosophers know this as the “animistic fallacy”—the assumption that observed economic outcomes must be the result of someone’s intentional design. It’s a seductive way of thinking because it mirrors how we explain human behavior in our daily lives.

But this approach frequently misleads us when analyzing social and economic systems. The alternative is what we might call “systemic analysis”—examining how the incentives, constraints, and interactions within a system produce outcomes that may not have been intended by any individual actor.¹

This systemic view has deep roots in economic thought. Adam Smith’s "invisible hand" is perhaps the most famous example. Smith argued that individuals' pursuit of self-interest, given proper institutions, could lead to socially beneficial outcomes, even though no one intended or designed those broader results.

Friedrich Hayek extended this insight with his work on the price system as a mechanism for coordinating dispersed knowledge. In Hayek’s view, prices emerge from the actions of countless market participants, each acting on their own local information. No single entity sets prices or even fully understands why they are what they are. As Hayek put it, this spontaneous order is “the result of human actions, not of human design.”

However, the idea of spontaneous order doesn’t necessarily imply that unplanned systems are always beneficial or just. Mobs are spontaneous orders. Even thinkers who are deeply critical of market outcomes recognize the power of systemic forces. Karl Marx, for instance, saw capitalism as a system driven by underlying economic dynamics rather than the intentions of individual capitalists. His analysis focused on how the internal logic of capital accumulation shaped social and economic outcomes, often in ways no individual actor intended.

More recently, economists like Thomas Schelling have shown how systemic analysis can illuminate social phenomena. Schelling demonstrated how mild individual preferences could lead to stark patterns of segregation without anyone intending that outcome. His models show how system-level patterns can emerge from simple rules followed by individuals.

The key insight of systemic analysis is that social and economic outcomes often emerge from the unintended consequences of individual actions and interactions. No one decided that cities should have ethnic enclaves or that certain technologies would dominate markets. These patterns emerge from countless small decisions made by individuals responding to their own incentives and constraints.

The reason to reject this animistic fallacy is not for any concern about the right way to do economic theory. The problem is the animistic fallacy, again and again, cannot explain the facts of the world around us as well as systemic approaches can.

Inflation Explanations

I’ll give an example of the failures of animistic reasoning.

All the recent discussions about price gouging brought this distinction back into my mind. Many people seem to want to identify particular instances of price gouging (assuming that term has any meaning) and point to that as the cause of inflation. During the ongoing antitrust challenge to the merger of Kroger and Albertsons, a company leader admitted to raising prices above costs, and the usual suspects were quick to take a victory lap around their claims that these companies were the inflation villains.

The contrast between animistic and systemic approaches is particularly stark when we look at explanations for rising prices across the economy. The animistic fallacy leads us to explanations centered on the intentions of powerful actors. We see this in the popular “greedflation” narrative, which attributes price increases primarily to corporate greed or strategic actions by firms in concentrated industries.

Proponents of the greedflation view argue that companies, especially in concentrated industries, are taking advantage of the inflationary environment to raise prices more than necessary and pad their profit margins. They point to record corporate profits as evidence that firms are exploiting consumers rather than simply passing on higher costs.

This explanation has an animistic flavor; it suggests that observed price increases are primarily the result of deliberate choices by business leaders to exploit market conditions. It’s an appealing narrative because it gives us clear villains and seemingly simple solutions: if greedy corporations are to blame, then price controls or windfall profits taxes might solve the problem. There is an “implicit agreement” between firms to raise prices.

However, this view struggles to explain several key features of inflation. Why do prices rise in some industries but not others? Why might they fall again later? If corporate gouging is to blame, why don’t firms always raise prices? The greedflation narrative also doesn’t account for the role of competition in disciplining prices or the web of factors that influence pricing decisions.

A systemic analysis, on the other hand, looks at the broader context in which prices are set. It considers factors like changes in input costs, shifts in consumer demand, technological changes, regulatory environments, and, yes, competitive dynamics. But crucially, it sees the final outcome as emerging from the interaction of all these factors, not as the simple result of any one actor's (or even a few actors’) intentions. After all, the U.S. economy is ridiculously large. No one can move the needle on it.

Let's consider a concrete example: the rise in used car prices during the pandemic. In 2021, used car prices in the U.S. rose by over 40%. In an accounting sense, this was a large part of overall inflation for a while. An animistic explanation might point to car dealers taking advantage of the situation. But a systemic analysis would look at supply and demand:

• Supply chain disruptions reduced the production of new cars, increasing demand for used cars.

• Stimulus checks and low interest rates boosted consumer purchasing power.

• Changes in travel patterns due to the pandemic increased demand for personal vehicles.

These factors interacted to create a situation where demand for used cars far outstripped supply, driving up prices. No single actor “caused” this price change, and no single company could have prevented it. It emerged from the system. We can then look for the other empirical implications of these systemic changes. What other prices will change? Will it revert?

The systemic view also helps us understand why inflation can persist even in highly competitive industries where no firm has significant market power. It explains how well-intentioned policies, like stimulus checks or low interest rates, can contribute to inflationary pressures without anyone intending that outcome.

This approach has important implications for policy. If we believe that economic outcomes are primarily the result of intentional actions by powerful actors, we might focus on punishing “bad behavior” or directly controlling prices and wages. Just ban price gouging.

If we recognize the systemic nature of these phenomena, we’re more likely to focus on shaping incentives, improving market structures, and addressing underlying economic forces. What sorts of things shift out the supply curve? That’s a question about the system.

Are microfoundations animistic?

There’s a tension in this, between the economic focus on individual decision-making and our understanding of systemic outcomes. On one hand, much of modern economics is built on the foundation of methodological individualism - the idea that economic phenomena should be explained by the actions and motivations of individual agents. We construct models where consumers maximize utility, firms maximize profits, and we derive market outcomes from these individual choices. The push for microfoundations in macroeconomics stems from this desire to ground our understanding of aggregate phenomena in individual choices. That helps us make better predictions in light of the Lucas critique.

However, this focus on individual maximization often leads to the paradoxical conclusion that individuals don't determine the outcomes we care about most. In a competitive market, for instance, no individual firm sets the price - “the market” as a system determines the price. Firms are "price takers," not "price makers."

This tension becomes even more apparent when we consider phenomena like business cycles, long-run growth, or inflation. We might model these using representative agents making optimal choices, but we understand that the real causal factors are systemic—the interactions between different sectors of the economy, the dynamics of money and credit, and the cumulative effects of technological change.

The standard neoclassical approach tries to reconcile these views through the concept of equilibrium. In a Walrasian general equilibrium model, for instance, individuals make optimizing choices taking prices as given, while the interaction of all these choices determines the equilibrium prices. It’s a clever theoretical trick that connects individual behavior to systemic outcomes.

But the Walrasian approach, in its purest form, abstracts too far from the process of price formation. In these models, prices spring into existence fully formed, as if summoned by an invisible auctioneer. No one really “sets” prices; they just are. This is clearly at odds with our everyday experience of markets, where we see firms actively grappling with pricing decisions and consumers haggling or comparison shopping.

A more nuanced view recognizes that while individuals and firms do make pricing decisions, they do so within a system that constrains and shapes those choices. Prices emerge from a process of trial and error, of competition and coordination, that no single actor fully controls or understands.

This perspective aligns with broader notions of equilibrium developed by economists like Hayek. In Hayek's view, the market is a discovery process. Prices emerge as market participants act on their local knowledge, gradually coordinating their plans through a process of mutual adjustment. No one chooses the resulting equilibrium, but neither does it appear magically. It evolves through a decentralized process of social learning.

This middle ground – recognizing both individual agency and systemic constraints – offers a richer understanding of economic phenomena. It allows us to see how individual choices matter while also appreciating the often unintended consequences of those choices as they play out in a system.

Economists must navigate this tension—to build models that respect the importance of individual decision-making while also capturing the emergent, systemic properties that often drive the outcomes we care about. This isn’t easy, but it’s necessary if we want to develop a truly comprehensive understanding of economic phenomena.

In practice, this often means using different approaches for different questions. When we’re thinking about how a specific policy might affect behavior, individual-level models can be incredibly useful. We can ignore equilibrium for a sec and just think about changing prices. But when we’re trying to understand broader trends or design macro-level policies, we need to think more in terms of systems.

This doesn’t mean intentional actions never matter. Policy choices and corporate strategies can certainly influence economic outcomes. But even then, the ultimate results often differ from what anyone intended. A regulation meant to protect workers might inadvertently reduce employment. A corporate strategy to increase market share might end up shrinking the overall market.

Systemic analysis requires us to look beyond surface-level explanations and dig into the incentives, feedback loops, and emergent properties of economic systems. It’s more challenging than the animistic fallacy, but ultimately more illuminating. The proof of the pudding is in the eating, and the systemic approach of supply and demand continues to outperform the other approaches.

1. I’m taking this distinction between animistic and systemic from Sowell’s Knowledge and Decision.