Two Sigma: Economic Forecasters’ Uncertainty vs. Disagreement

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Economic Forecasters’ Uncertainty vs. Disagreement by written by JEFFREY N. SARET & GERARDO MANZO of  Two Sigma  and reflects their views, not necessarily the firm’s  – please see important legal disclaimer at bottom of post

Executive Summary

Polls of economic forecasters can reveal much more than point estimates. Data from the Federal Reserve and European Central Bank show that the level of disagreement across forecasters today is within the historical norm, but uncertainty appears higher than ever, particularly in Europe. Asset allocators might want to incorporate that uncertainty when hedging their economic risk.

Economic Forecasters’ Uncertainty vs. Disagreement

Even though economists do not have a reputation for their sense of humor, they generate a lot of jokes. One joke describes three economists playing darts in a bar. The first misses the board entirely, throwing a dart one foot to the left and leaving a small hole in the wall. The second economist misses the board as well, breaking a mirror one foot to the right. The annoyed bartender glares when the third economist cheers loudly and earnestly, “We averaged a bullseye!”1


Some asset allocators might take as a moral of this story that they ought to ignore entirely polls of economists on topics like GDP growth. Recent data releases for Q2 2016 GDP growth, which fell short of expectations in the US (1.2 percent actual versus Bloomberg estimate of 2.5 percent expected)2 and other major markets, might further that belief. However, rather than ignoring polling data because of dubious point forecasts, allocators might delve deeper into other characteristics of the data. For example, does the data imply a high degree of dispersion or disagreement across forecasters? Do individual forecasters have a high degree of confidence or certainty in their own views?

By disentangling disagreement from uncertainty in polls of forecasters, asset allocators can draw a much clearer picture of what the data says and potentially hedge their exposures accordingly. For example, if half of polled experts believe with high conviction that one outcome appears likely, and the other half believe equally firmly that the opposite outcome appears likely, an asset allocator might want to hedge against two discrete scenarios. Alternatively, if all forecasters share a common expected outcome, but each feels highly uncertain of that outcome, an asset allocator might want to hedge against a broader range of scenarios.

For GDP and inflation forecasts, data from the US Federal Reserve and the European Central Bank (ECB) reveal two interesting findings.3 First, both US and European forecasters currently disagree among themselves about as much as usual on growth and inflation. However, the level of uncertainty for each forecaster appears higher today than at any other time during the past 15 years, particularly in Europe. Asset allocators might want to account for that uncertainty when hedging their economic risk.

Comparing Uncertainty To Disagreement In Forecasts

When the Federal Reserve and the ECB survey professional forecasters for their economic outlooks, the respondents do not simply input point estimates for the mean. Instead, each forecaster enters a probability that an economic outcome (e.g., GDP growth) will fall within a pre-specified band (e.g., 1.0–1.9 percent). The Fed and ECB generate these surveys quarterly.

One can infer more than just the means from the surveys of professional forecasters by studying both the disagreement and the uncertainty of the forecasts. Consistent with academic research, disagreement equals the inter-quartile range (75th minus 25th percentile) of point forecasts, whereas uncertainty equals the average of the individual variances from each forecaster’s probability distribution of outcomes.4 Figure 1 depicts these two measures.

Figure 1 plots the level of disagreement and uncertainty in the Fed and ECB surveys of professional forecasters. For both growth and inflation, the data (mostly) start in 1999.

Economic Forecasters

The figure highlights two main points. First, disagreement in growth and inflation vary over time (e.g., peaks during periods of financial stress such as 2001 and 2009), but the most recent surveys (Q3 2016) show that the current level does not differ significantly from the long-term mean. Forecasters seem as split today as usual.

Second, and more interestingly, the level of uncertainty today appears higher than usual, particularly in Europe. European forecasters appear 20 percent less confident in both their growth and inflation predictions than in March 2009 (trough of global equity markets) and 15 percent less confident than in March 2012 (Greek sovereign default).

Potential Implications

Asset allocators feeling befuddled while trying to hedge the macroeconomic risks in their portfolios should not feel alone. Professional forecasters also appear to suffer from a degree of uncertainty today that exceeds recent memory, including during the global financial crisis. The policy uncertainty from Brexit and the ongoing refugee crises likely contribute to the economic uncertainty. Asset allocators might also feel some relief that forecasters at least agree amongst themselves, both within and across the US and Europe. Then again, it might feel like a good time to go back to throwing darts.


  • G. Boero, J. Smith and K. F. Wallis, 2015. “The measurement and characteristics of professional forecasters’ uncertainty.” Journal of Applied Econometrics, 30, 1029-1046.
  • Lahiri, Kajal, and Xuguang Sheng, 2010, “Measuring forecast uncertainty by disagreement: The missing link.” Journal of Applied Econometrics 25.4: 514-538.
  • Rich, Robert, and Joseph Tracy, 2010, “The relationships among expected inflation, disagreement, and uncertainty: evidence from matched point and density forecasts.” The Review of Economics and Statistics 92.1: 200-207.

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