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August 13, 2019

Uncertainty dominates today’s policy landscape. Just last week it figured prominently and explicitly in the U.S. Federal Open Market Committee’s news release and press conference announcing its controversial interest rate cut.

Recognizing the nature and extent of the uncertainty facing us today is not hard. We have trade war uncertainty and associated uncertainty about the future of the global trading system, uncertainty about a changing world order, uncertainty about global governance and rules of the game, uncertainty related to technological disruptions, and climate change uncertainty.

But what exactly do we mean by uncertainty? How is it different from risk? And what does the rise in uncertainty mean from a monetary policy perspective?

Too often, economists talk about risks and uncertainty as if they were the same thing. Yet as long ago as 1921 the University of Chicago’s Frank Knight explained how they are different. Risk involves situations whose outcomes are not known, but where we can with some confidence measure the probability or odds of different events happening. Uncertainty, by contrast, applies to situations where we do not have and cannot know all we need to know in order to estimate probabilities in the first place. In other words, Knightian, or radical, uncertainty is a lack of any quantifiable knowledge about some possible occurrence.

U.S. Defense Secretary Donald Rumsfeld was famous for saying: “There are known knowns. These are things we know that we know. There are known unknowns. That is to say, there are things that we know we don’t know. But there are also unknown unknowns. These are things we don’t know we don’t know.” Knightian, or radical uncertainty involves both of these unknowns.

The best policy decisions require a single judgment about the economic outlook. But the existence of uncertainty can mean a single judgment is difficult, even impossible.

What can policymakers do in the face of uncertainty that seems to be increasing without bounds? Central banks need to expand their toolkits in several important ways.

First and foremost, they need to consider how best to convey that the future is unpredictable. They will have to construct narratives — that is, they will have to integrate information in a way that both acknowledges the infinite uncertainties facing us and also tells a story to assist economic agents to understand the world confronting them. Narratives offer central banks a potentially powerful tool for explaining true uncertainty. Consider the following two examples of radical uncertainty currently facing the world, Canada included.

The first is Brexit. Since the 2016 referendum, uncertainty about the ultimate outcome, as well as about the economic consequences associated with any of the several possible outcomes, has made it near-impossible to quantify Brexit risks with any confidence. That is not to say various scenarios cannot be analyzed. Just that basing policy on any one scenario would be both difficult and unwise. Even today, as the Oct. 31 deadline looms, is the most likely outcome a no-deal Brexit, the Theresa May deal, a revised deal, or a second referendum? In such a situation, far better for policy makers to be upfront about the extent of uncertainty and share a narrative that acknowledges it and relays a story that helps economic agents understand what they are confronting.

A second current case of radical uncertainty involves the implications of U.S.-China trade tensions. The Trump administration has been extremely volatile on the nature and extent of a possible escalation of its trade war with China, and China could counter with several different actions of its own. Again, we do not have enough information to calculate the probabilities that would guide us toward a firm, fully informed policy decision.

A good outcome from this use of narratives would be that all stakeholders took more responsibility for their own decision-making. This stands in contrast to a long-lasting concern of central banks that economic agents, especially financial market participants, take what are typically conditional statements from central banks as commitments to act in a particular way.

The Bank of Canada seems dialled-in to this reality. In a recent speech governor Stephen Poloz cited “a significant increase in uncertainty around the future of the global trading system,” adding that “the global economy has been dealing with heightened uncertainty over trade policy for an extended period now.” There are serious concerns the global trading system could experience a prolonged period of radical uncertainty.

Central banks could also supplement their modelling to include “agent-based models,” in which non-economic motives, or “animal spirits,” lead economic agents to exhibit the sorts of complex behaviour seen in the real world. Though not a replacement for macro-forecasting tools, these models, which can get very complex, may bring us closer to understanding the possible consequences of uncertain environments in which these interactions could result in unpredictable behaviour. As seen through this agent-based model prism, the 2008-2009 global financial crisis can be characterized as driven by irrational behaviour, by markets that failed to clear, and by conditions that were far from economists’ usual assumption of equilibrium.

Central bankers need to integrate uncertainty into their institutions’ communications and modelling strategy. Their challenge will be to acknowledge and communicate uncertainty while still making educated assessments of risk in order to guide policy. No central banker should pretend we know with any precision what the future holds.

Paul Jenkins, former senior deputy governor of the Bank of Canada, is a senior fellow at the C.D. Howe Institute and author of “Into the Unknown: Reflections on Risk, Uncertainty and Monetary Policy Decision-making."

Published in the National Post