Gauging the Uncertainty of the Economic Outlook Using Historical Forecasting Errors: The Federal Reserve's Approach

Abstract

Since November 2007, the Federal Open Market Committee (FOMC) of the U.S. Federal Reserve has regularly published participants' qualitative assessments of the uncertainty attending their individual forecasts of real activity and inflation, expressed relative to that seen on average in the past. The benchmarks used for these historical comparisons are the average root mean squared forecast errors (RMSEs) made by various private and government forecasters over the past twenty years. This paper documents how these benchmarks are constructed and discusses some of their properties. We draw several conclusions. First, if past performance is a reasonable guide to future accuracy, considerable uncertainty surrounds all macroeconomic projections, including those of FOMC participants. Second, different forecasters have similar accuracy. Third, estimates of uncertainty about future real activity and interest rates are now considerably greater than prior to the financial crisis; in contrast, estimates of inflation accuracy have changed little. Finally, fan charts-constructed as plus-or-minus one RMSE intervals about the median FOMC forecast, under the expectation that future projection errors will be unbiased and symmetrically distributed, and that the intervals cover about 70 percent of possible outcomes-provide a reasonable approximation to future uncertainty, especially when viewed in conjunction with the FOMC's qualitative assessments. That said, an assumption of symmetry about the interest rate outlook is problematic if the expected path of the federal funds rate is expected to remain low. * Board of Governors of the Federal Reserve System, davidreifschneider@frb.gov. ^ Reserve Bank of Australia, tulipp@rba.gov.au We would like to thank

From Fixed-Event to Fixed-Horizon Density Forecasts: Obtaining Measures of Multi-Horizon Uncertainty From Survey Density Forecasts

“…The Bank of England, for instance, uses a mixture of normal distributions to incorporate asymmetry in the predictive density (see Wallis, 1999 for a discussion, andClements, 2004 andGalbraith andvan Norden, 2012 for an evaluation). As discussed in Reifschneider and Tulip (2017), the SEP predictive densities are based on rolling root mean squared forecast errors of the historical point forecasts of private and government forecasters, over a window of twenty years. The SEP densities, unlike the ones provided by the Bank of England, are constructed under the assumption of symmetry.…”

Forecasting Macroeconomic Risks

“…This figure shows estimated four quarter ahead predictive densities. The solid blue lines represent the predictive densities that condition on both the median SPF forecast and financial conditions, while the dashed orange lines represent the "unconditional" predictive densities computed from the distribution of historical forecast errors (see Reifschneider and Tulip, 2019). The vertical solid gray lines represents the median SPF forecast used in the construction of both the conditional and unconditional densities, while the red dotted lines represent realized values of the target variables.…”

Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors

“…9 Studies such as Faust and Wright (2008) and Reifschneider and Tulip (2017) make use of short-term interest rate forecasts from Greenbook obtained from the Federal Reserve's Board of Governors. However, as discussed in Wright (2008, 2009), for much of the available history, these forecasts have been tied to conditioning assumptions about monetary policy, rather than unconditional forecasts.…”

“…It appears to be commonly recognized that structural changes such as the Great Moderation or unusual periods such as the recent Great Recession can lead to significant shifts in the sizes of forecast errors. For example, in their analysis of historical forecast accuracy (work that underlay the Federal Reserve's initial publication of forecast accuracy measures in the SEP), Reifschneider and Tulip (2007) explicitly chose a sample starting in 1986 to capture accuracy in the period since the start of the Great Moderation. The more recent analysis of Reifschneider and Tulip (2017) discusses some simple evidence of changes in the sizes of forecast errors.…”

“…For example, in their analysis of historical forecast accuracy (work that underlay the Federal Reserve's initial publication of forecast accuracy measures in the SEP), Reifschneider and Tulip (2007) explicitly chose a sample starting in 1986 to capture accuracy in the period since the start of the Great Moderation. The more recent analysis of Reifschneider and Tulip (2017) discusses some simple evidence of changes in the sizes of forecast errors. In practice, the historical accuracy measures published in the Federal Reserve's SEP are based on a 20-year window of forecast errors.…”