Most of the quantitative studies of optimal monetary policy have also assumed that the shocks hitting the economy have a time-invariant Gaussian distribution, that is, a classical bell curve with symmetric and well-behaved tails. In reality, however, the distribution of shocks hitting the economy is more complex. In some instances, the uncertainty facing the economy is clearly skewed in one direction or another; again, this is likely when there are significant financial disruptions. The Federal Reserve often reports on our judgments regarding the degree of skewness and the associated economic costs by giving assessments of the “Balance of Risks” in the press releases that are issued following FOMC meetings.
In addition, at least in some circumstances, the shocks hitting the economy may exhibit excess kurtosis, commonly referred to as tail risk because the probability of relatively large disturbances is higher than would be implied by a Gaussian distribution. In that light, one element of the recent enhancements to the Federal Reserve’s communication strategy is that FOMC participants now provide assessments of the relative degree of uncertainty. For example, in the “Summary of Economic Projections”issued in late November, FOMC participants indicated that the degree of uncertainty regarding the economic growth outlook was relatively high compared to the average degree of uncertainty over the past two decades. This account could be interpreted as a statement that the Committee perceived the tail risk as unusually large.
With a nonquadratic objective function (consistent with the importance of uncertainty for the course of monetary policy) as well as nonlinear dynamics and non-Gaussian shocks, optimal monetary policy will also be nonlinear and will tend to focus on risk management.