Policy shouldn't rely on economic theory, but on data about actual human behavior

Policy shouldn't rely on economic theory, but on data about actual human behavior
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The tax overhaul bill before Congress has a professed rationale that rests on economic theory. As neuroscientists who study decision making, we would like to raise a very serious objection to this rationale; namely, that a bill based on economic theory is informed by ideas, not data. Traditional economic theory, you might be surprised to hear, demands no evidence.

Our field, neuro-economics, involves the study of human decision making. We therefore naturally assumed that the classical economic theories so deeply ingrained in our public life are similarly rooted in data about actual economic decisions. But that’s not the case. We each discovered this when, as part of our own research, we asked economist colleagues for the data underlying some influential economic theory. In each case, we were told that data for or against the theory have not been collected. At all.

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It turns out that classical economics, like philosophy, is a theoretical field. It considers behavior under abstract, idealized conditions. Those conditions, and even the behavior being theorized about, need never have been shown to exist.  

 

In this way, classical economics differs from neuroscience and other experimental disciplines. In neuro-economics, a branch of neuroscience, we model how the brain makes decisions. Models are evaluated by their ability to predict real behavior, as measured through experiments, rather than behavior that should be true because it makes sense.

At this historical moment, it is acutely important to distinguish between theoretical and experimental fields. Economics includes both: The subfields of behavioral and applied economics rely on experimental data.

However, it is classical economics — the theoretical subfield — that has been the dominant influence on U.S. public policy for a century or more. It isn’t hard to understand why. Classical economics has the intuitive appeal of aiming at rational use of resources. Unfortunately, it’s “rational” ideas are completely unmoored from facts.

There are numerous examples of economic theories that never even purported to be grounded in data, yet shaped decades of legislation and individual energy. This week, the idea of “trickle-down” economics as a rationale for massive changes in the flow of resources is the most obvious example. Traditional economics similarly invokes rationality to assume that people want to work as little as possible. Yet humans love to make things hard on purpose and they work when they don’t have to (while Home Depot thrives).

The most tragic of the traditional economic assumptions, promoted by economist James McGill Buchanan among others, may be the idea that people are completely, rationally, selfish. This premise is now deeply ingrained in the American popular imagination and it has motivated a political movement seeking to restrict democratic participation and create an oligarchy.

In actuality, people are not rationally selfish. Instead, the data show that people are hyper-altruistic. They will pay more to keep someone else from getting hurt than they would to protect themselves, even when no one can see their actions.

In fact, almost all of the premises about rational self-interest from classical economics are decisively wrong, debunked by a wealth of data accumulated by experimental science from many fields. Our behavior is not selfish and rational, but rather consistently irrational.

The Nobel prize in economics has twice recognized the importance of understanding irrational human biases to predict decision-making, once this year, to behavioral economist Richard Thaler, and previously to psychologist Daniel Kahneman, for his work with Amos Tversky.

We don’t mean to suggest that non-experimental fields are without value. Theoretical physics in ideal (unrealistic) conditions has propelled progress in engineering. Similarly, classical economic theory can, ultimately, offer tools for understanding human behavior. Knowing the rational solution to a decision-making problem can help pinpoint where behavior deviates from optimum, and inform testable hypotheses about the sources of the observed biases. 

But basing policy on classical economic theory is like basing a contract on philosophy. Effective policy cannot be built from idealized conjectures; it demands realism, and actual facts.

Lawmakers have at their disposal a growing repertoire of evidence-based tools for supporting optimum behavior in realistic, complex and uncertain situations. These tools have been identified, and tested, by scientists of behavior. Importantly, much of this work has been funded by federal taxes.

We are eager to see the neuroscience of motivations and decisions benefit the people who paid for it. We can think of no better payback than to support truly rational policy, accountable to evidence.

Alison Adcock is an associate professor of Psychiatry and Behavioral Sciences at Duke University and associate director of the Center for Cognitive Neuroscience. Yael Niv is an associate Professor of Neuroscience and Psychology at Princeton University and Co-Director of the Rutgers-Princeton Center for Computational Cognitive Neuropsychiatry.