To most people, uncertainty simply means not knowing: not knowing what next year’s vacation plans are, who their next client will be, or how long their savings will last.
But to economists, uncertainty is paradoxically knowable. It can be measured, indexed, modeled, and correlated with other elements in the business cycle. One such element is economic growth—uncertainty is lower during booms and higher during busts.
The association makes intuitive sense. But economists have struggled to define a cause-and-effect link between uncertainty and growth. “Which direction is this relationship going?” says Scott R. Baker, an assistant professor of finance at the Kellogg School of Management.
In two recent research studies, Baker and his collaborators examined how uncertainty at the macroeconomic and government-policy levels is not merely a reaction to sluggish growth, but can also act as an inhibiting influence on growth itself.
“The government needs to be cognizant of action that they take or statements they make about uncertainty.”
In other words, economic uncertainty is not just a reaction to market forces—it appears to be a force unto itself. And it is a force that should be understood by economists and hopefully mitigated by policymakers so that it causes less economic stress.
Knowing What We Do Not Know
Baker defines uncertainty not as an inability to forecast the outcome of events, but as a measure of the variance between many such forecasts. Specifically, he wants to know how large a spread there is around a mean.
For example, he says, “If you ask ten economists what GDP growth is going to be next year, and five say it’s going to be 1% and five say it’s going to be 2%, that’s a mean of 1.5%, and everybody’s within a half point of each other. But if five people say 0% and five say 3%, there’s more uncertainty around that same mean value of 1.5% because the range of potential outcomes has increased.”
When the mean of these forecasts is low, meaning “people are more pessimistic about economic fundamentals or business conditions in the next year,” the spread between individual forecasted values tends to be greater, Baker says.
To determine whether this uncertainty was a cause or effect of the initial pessimism, Baker studied the GDP growth of sixty countries that endured either a large-scale natural disaster, terrorist attack, or period of political strife between 1970 and the present day. These shocks to various nations’ economic growth allowed Baker and coauthor Nicholas Bloom of Stanford University to “disentangle” the effects of economic uncertainty from those of the shocks that precipitated them.
“If an earthquake occurs, it causes economic losses, so it has a negative effect on mean stock returns in the next quarter. But it doesn’t have as large of an effect in terms of uncertainty about future productivity,” Baker explains. “In contrast, something like a political revolution can also lower the forecast mean of business conditions for the next year, but there’s also a lot more uncertainty about what’s going to happen. Maybe the new leader isn’t a known quantity so nobody knows what economic policies he’s going to take; maybe there’s going to be a reverse coup.”
When Bad Things Happen to Good Markets
Baker used both “first moment” economic shocks (the short-term effects on the level of productivity or on business conditions) and “second moment” shocks (things affecting the uncertainty and volatility of forecasted business conditions, as measured by stock market volatility) to neatly separate the ensuing effects on economic growth.
“We used natural disasters and political conflicts in our model because these are national-scale events that affect macroeconomic growth in a way that is actually measurable,” he says. “They’re also very concrete and fairly random at a high frequency level.”
This allows Baker and Bloom to isolate changes in uncertainty that stem from external forces, not from macroeconomic growth itself, leading to a clearer analysis of whether uncertainty impacts growth or only the other way around.
The results of the experiment were “definitive,” Baker says.
GDP growth was reduced by up to 1.6% in the first financial quarter following one of these major events, and up to 7% the following year—and the uncertainty the event caused was responsible for at least half of that change in growth.
The reason, Baker says, is because adjusting to changing business conditions incurs costs that cannot easily be recouped. If firms cannot reasonably predict what those changes are likely to look like, “they just tend to sit still for as long as possible to wait for the uncertainty to resolve.” When businesses sit still—freezing their hiring and curtailing their capital investments—economic growth stalls.
Governments can mount a powerful policy response to such slowdowns in growth. But uncertainty around these policies can itself be a drag on the very growth they are designed to stimulate.
“From 2010 to 2012, there was a lot of discussion about whether the amount of uncertainty about government policy was one of the things that had been driving the depth of the Great Recession and the sluggishness of the recovery,” Baker says. “The government was taking all kinds of unprecedented action, so there was uncertainty about new regulations, new taxes, new Federal Reserve policy. People wondered whether that was having some negative effects on consumers, households, or businesses.”
In a second research study, Baker, Bloom, and Steven J. Davis of the University of Chicago devised an “economic policy uncertainty index” to track and model this effect. Baker acknowledges that uncertainty in government policy is “a somewhat nebulous concept,” but his team quantified it in much the same way as they did with macroeconomic uncertainty in their other work.
Between 1985 and 2014, the more variance that the researchers could gather in predictions about U.S. economic policy—from newspaper articles and government spending forecasts to tax code changes and election results—the higher was the uncertainty, as measured on the index they created.
Baker found that while policy uncertainty generally increased in the wake of the 2008 recession, determining its effect on the economy was a challenge. Still, the researchers found a “tight linkage” between increased levels of policy uncertainty and decreased investment in firms that are highly dependent on government spending, such as defense contractors, healthcare companies, and hospitals.
Uncertainty as a Market Force
Both research projects, Baker says, strongly suggest that uncertainty is a macroeconomic force to be reckoned with in its own right—both by the economists who model and forecast business conditions and the policymakers who influence and respond to those conditions. Certain first-moment economic shocks are inherently unpredictable, but by understanding the second-moment effects that uncertainty can have, additional reductions in growth can be mitigated.
“The government needs to be cognizant of action that they take or statements they make about uncertainty,” Baker explains. “For example, there are lots of taxes now that are on perpetual one-year renewal cycles. Our research suggests that things like that tend to depress investment because firms are going to wait and see what the government does, rather than maintain some steady level of investment over time.”Baker maintains that uncertainty analysis is also a crucial method for economists’ own basic understanding of the business cycle.
“Businesses are already taking uncertainty and its potential effects into account,” he says. “That’s why we can see these ‘second moment’ effects on growth. When we’re building models of macroeconomic behavior, it’s very important not to assume that businesses are making decisions based on the mean of what they expect to happen next year, but also in terms of the uncertainty around that mean. We think this is not just a characteristic of these very concrete shocks, like earthquakes and political revolutions, but of the evolution of business conditions in general.”
In other words, a little knowledge—even if it is about what we do not know—can go a long way.