Our economy today has been described variously as “weird,” “really weird” and “very, very weird.”
Weird because this is a yo-yo economy where gas prices shot up to more than $5 a gallon and then settled back down. The inflation rate for used cars dropped, then accelerated at a 40 percent rate before deflating at a record rate. Housing has gone from boom to bust, then to boom again. Economic indicators have been described as “a Jackson Pollock painting of data points and trends.”
Economists can’t figure it out. Economic models are only getting us as far as separating top-flight economists into Team Stagflation and Team Soft Landing. Alan Blinder, the Princeton economist, talks about the prospects of the Federal Reserve nailing a soft landing like he is handicapping a team’s Super Bowl prospects: “I think they still have a chance, but it’s a tougher chance than it was.”
Economists tried to deal with the twin stresses of inflation and recession in the 1970s without success, and now here we are, 50 years and 50-plus economics Nobel Prizes later, with little ground gained. The Fed and the Treasury Department buttressed the banking structure in the aftermath of the 2008 crisis. Fifteen years later, we are seeing it breeched.
There’s weirdness yet to come, and a lot more than run-of-the-mill weirdness. We are entering a new epoch of crisis, a slow-motion tidal wave of risks that will wash over our economy in the next decades — namely climate change, demographics, deglobalization and artificial intelligence. Their effects will range somewhere between economic regime shift and existential threat to civilization. The risks to the economy, to the stability of our society and to civilization are enormous if we don’t get the economic models right for what’s coming.
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For climate, we already are seeing a glimpse of what is to come: drought, floods and far more extreme storms than in the recent past. We saw some of the implications over the past year, with supply chains broken because rivers were too dry for shipping and hydroelectric and nuclear power impaired.
For demographics, birthrates are on the decline in the developed countries. China’s population is in decline, for instance, and South Korea just set a mark for the lowest birthrate in the developed world. As with climate change, demographic shifts determine societal ones, like straining the social contract between the working and the aged.
We are reversing the globalization of the past 40 years, with the links in our geopolitical and economic network fraying. “Friendshoring,” or moving production to friendly countries, is a new term. The geopolitical forces behind deglobalization will amplify the stresses from climate change and demographics to lead to a frenzied competition for resources and consumers.
We can see the impacts of climate change, demographics and deglobalization coming. The fourth, artificial intelligence, is a wild card. But we already are seeing risks for work and privacy, and for frightening advances in warfare.
These risks are going to accelerate and affect us for decades. If our economic models can only get as far as Team Stagflation versus Team Soft Landing — if we can’t get a firm hold on pedestrian economic issues like inflation and recession — the prospects are not bright for getting our forecasts right for these existential forces.
The problem here is not that our economic models don’t work at all. The models seem serviceable when things are simple and stable, when we are in a steady state with tons of past data to draw on. The problem is that the models don’t work when our economy is weird. And that’s precisely when we most need them to work.
Economists have admitted as much. At the height of the 2008 financial crisis, Queen Elizabeth II asked the question that no doubt was on the minds of many of her subjects: “Why did nobody see it coming?” The response, some months later, by the Nobel laureate economist Robert Lucas, was blunt: Economics failed with the 2008 crisis because economic theory has established that it cannot predict such crises.
A key reason these models fail in times of crisis is that they can’t deal with a world filled with complexity or with surprising twists and turns. For example, the mathematical models of economics analyze a representative agent — be that an individual or a firm — and assume the overall economy will behave the way that this one agent behaves. The problem here, and a problem broadly with complex and dynamic systems, is that the whole doesn’t look like the sum of the parts. If you have a lot of people running around, the overall picture can look different than what any one of those people is doing. Maybe in aggregate their actions jam the doorway; maybe in aggregate they create a stampede.
Economists fancy themselves as the physicists of the social sciences, wielding mathematical models to bring solutions to the economic world. But we are not a mechanical system. We are humans who innovate, change with our experiences, and at times game the system. Reflecting on the 1987 market crash, the brilliant physicist Richard Feynman remarked on the difficulty facing economists by noting that subatomic particles don’t act based on what they think other subatomic particles are planning — but people do that.
What if economists can’t turn things around? This is a possibility because we are walking into a world unlike any we have seen. We can’t anticipate all the ways climate change might affect us or where our creativity will take us with A.I. Which brings us to what is called radical uncertainty, where we simply have no clue — where we are caught unaware by things we haven’t even thought of.
This possibility is not much on the minds of economists. Charting Fed policy or forecasting consumer demand might have surprises here and there, but operate with a well-worn vocabulary. It’s with the longer term risks that “unknowable” has force.
How do we deal with risks we cannot even define? A good start is to move away from the economist’s palette of efficiency and rationality and instead look at examples of survival in worlds of radical uncertainty. Take the cockroach: It has survived for hundreds of millions of years as rainforests turned to savannas and savannas turned to deserts. And it has done this with a coarse escape system, simply running from puffs of air on its cercal hairs. Not very elegant. It will never win the Insect of the Year award but has done well enough to survive a world of radical change.
In our time savannas are turning to deserts. The alternative to the economist’s model is to take a coarse approach, to be more adaptable — leave some short-term fine tuning and optimization by the wayside. Our long term might look brighter if we act like cockroaches. An insect fine tuned for a jungle may dominate the cockroach in that environment. But once the world changes and the jungle disappears, it will as well.
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