Twenty-two Years of the NBER-ASA Quarterly Economic Outlook Surveys: Aspects and Comparisons of Forecasting Performance

Abstract

The National Bureau of Economic Research, in cooperation with the American Statistical Association, conducted a regular quarterly survey of professional macroeconomic forecasters for 22 years beginning in 1968. The survey produced a mass of information about characteristics and results of the forecasting process. Many studies have already used some of this material, but this is the first comprehensive examination of all of it. This report addresses several subjects and produces findings on each, as follows: (1) The distributions of error statistics across the forecasters: the dispersion among the individual predictions is often large and it typically increases with forecast horizon, as do the mean absolute (or squared) errors. (2) The role of the time-series properties of the target data: the more volatile the time series, the larger as a rule are the errors of the forecasts. (3) The role of revisions in "actual" data: forecast errors tend to be larger the greater the extent of the revisions. (4) Differences by subpcriod: there is little evidence of an overall improvement or deterioration in forecasts between the l970s and the 1980s. (5) Combining the individual forecasts into group mean or 'consensus" forecasts: this generally results in large gains in accuracy. (6) Comparisons with a well-known macroeconometric model: the group forecasts are more accurate for most but not all variables and spanS. (7) Comparisons with state-of-the-art time series models: the group forecasts and at least half of the individual forecasts tend to outperform Bayesian vector autoregressive models in most (but not all) cases. The univariate ARIMA forecasts arc generally the weakest.

Bias in Federal Reserve Inflation Forecasts: Is the Federal Reserve Irrational or Just Cautious?

“…The Survey of Professional Forecasters contains not only the consensus forecast, the variable that has been used so far in this paper, but information about the forecast of each of the forecasters that answered the survey. The number of forecasters change with each survey, but a measure of the dispersion of the forecasts has been used in the past as a measure of the variance of inflation (Zarnowitz and Braun (1992)) and as a measure of heterogeneity in inflation expectations (Mankiw, Reis, and Wolfers (2003)). 52 For this paper the interquartile range across forecasters is calculated, and the regression: e t+h,t = βinqr t+h,t + ε t+h (24) is estimated for each horizon using OLS and Newey-West standard errors.…”

“…The moment conditions arise from different forecast horizons and different instruments. 62 For each moment condition, an estimate of the asymmetry parameter is obtained. This estimate is answering the question: What asymmetry parameter rationalizes the observed sequence of forecasts?…”

Macroeconomic Uncertainty Through the Lens of Professional Forecasters

“…Professional forecasters base their forecasts on various econometric models, leading indicators and surveys, as well as a large number of available macroeconomic and financial data, encompassing information from a wide range of sources (see Zarnowitz and Braun 1993). Therefore, survey forecasts provide an effective way of removing expected variation 1 See, for example, Bloom (2009), Arellano et al (2012), Caggiano et al (2014), Aastveit et al (2013), and Mumtaz and Surico (2013), among many others.…”

Accounting-based downside risk, cost of capital, and the macroeconomy

“…We obtain time-series macroeconomic data of mean and median consensus expectations for future real GDP growth from the SPF available from the Federal Reserve Bank of Philadelphia, Real-Time Data Research Center. The SPF has been widely used in prior research to proxy for macroeconomic expectations (e.g., Zarnowitz and Braun 1993;Sims 2002;Ang et al 2007;Ulrich 2013;Konchitchki 2013;Konchitchki and Patatoukas 2014a, b). We also use the SPF to obtain realization data of GDP growth.…”