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Discussion Paper
What Drives Forecaster Disagreement about Monetary Policy?
What can disagreement teach us about how private forecasters perceive the conduct of monetary policy? In a previous post, we showed that private forecasters disagree about both the short-term and the long-term evolution of key macroeconomic variables but that the shape of this disagreement differs across variables. In contrast to their views on other macroeconomic variables, private forecasters disagree substantially about the level of the federal funds rate that will prevail in the medium to long term but very little on the rate at shorter horizons. In this post, we explore the possible ...
Report
Fundamental Disagreement about Monetary Policy and the Term Structure of Interest Rates
Using a unique data set of individual professional forecasts, we document disagreement about the future path of monetary policy, particularly at longer horizons. The stark differences in short rate forecasts imply strong disagreement about the risk-return trade-off of longer-term bonds. Longer-horizon short rate disagreement co-moves with term premiums. We estimate an affine term structure model in which investors hold heterogeneous beliefs about the long-run level of rates. Our model fits Treasury yields and the short rate paths predicted by different groups of investors and thus matches the ...
Report
The Term Structure of Expectations
Economic theory predicts that intertemporal decisions depend critically on expectations about future outcomes. Using the universe of professional survey forecasts for the United States, we document the behavior of the entire term structure of expectations for output growth, inflation, and the policy rate. We show that a simple unobserved components model of the trend and cycle explains the joint behavior of both consensus measures of expectations and the observed disagreement among individual forecasters. Importantly, univariate models of each variable are outperformed by a multivariate model ...
Working Paper
Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors
We develop uncertainty measures for point forecasts from surveys such as the Survey of Professional Forecasters, Blue Chip, or the Federal Open Market Committee?s Summary of Economic Projections. At a given point of time, these surveys provide forecasts for macroeconomic variables at multiple horizons. To track time-varying uncertainty in the associated forecast errors, we derive a multiple-horizon specification of stochastic volatility. Compared to constant-variance approaches, our stochastic-volatility model improves the accuracy of uncertainty measures for survey forecasts.
Report
Fundamental disagreement
We use the term structure of disagreement of professional forecasters to document a novel set of facts: (1) forecasters disagree at all horizons, including the long run; (2) the term structure of disagreement differs markedly across variables: it is downward sloping for real output growth, relatively flat for inflation, and upward sloping for the federal funds rate; (3) disagreement is time-varying at all horizons, including the long run. These new facts present a challenge to benchmark models of expectation formation based on informational frictions. We show that these models require two ...
Report
The term structure of expectations and bond yields
Bond yields can be decomposed into expected short rates and term premiums. We directly measure the former using all available U.S. professional forecasts and obtain the latter as the difference between bond yields and survey-based expected short rates. While the behavior of nominal and real short rate expectations is consistent with standard macroeconomic theory, term premiums account for the bulk of the cross-sectional and time series variation in yields. They also largely explain the yield curve's reaction to a host of structural economic shocks. This dramatic failure of the expectations ...
Working Paper
On the Aggregation of Probability Assessments: Regularized Mixtures of Predictive Densities for Eurozone Inflation and Real Interest Rates
We propose methods for constructing regularized mixtures of density forecasts. We explore a variety of objectives and regularization penalties, and we use them in a substantive exploration of Eurozone inflation and real interest rate density forecasts. All individual inflation forecasters (even the ex post best forecaster) are outperformed by our regularized mixtures. From the Great Recession onward, the optimal regularization tends to move density forecasts’ probability mass from the centers to the tails, correcting for overconfidence.
Working Paper
Macroeconomic Uncertainty Through the Lens of Professional Forecasters
We analyze the evolution of macroeconomic uncertainty in the United States, based on the forecast errors of consensus survey forecasts of various economic indicators. Comprehensive information contained in the survey forecasts enables us to capture a real-time subjective measure of uncertainty in a simple framework. We jointly model and estimate macroeconomic (common) and indicator-specific uncertainties of four indicators, using a factor stochastic volatility model. Our macroeconomic uncertainty has three major spikes aligned with the 1973?75, 1980, and 2007?09 recessions, while other ...
Discussion Paper
Why Do Forecasters Disagree about Their Monetary Policy Expectations?
While forecasters generally disagree about the expected path of monetary policy, the level of disagreement as measured in the New York Fed’s Survey of Primary Dealers (SPD) has increased substantially since 2022. For instance, the dispersion of expectations about the future path of the target federal funds rate (FFR) has widened significantly. What explains the current elevated disagreement in FFR forecasts?
Working Paper
Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors
We estimate uncertainty measures for point forecasts obtained from survey data, pooling information embedded in observed forecast errors for different forecast horizons. To track time-varying uncertainty in the associated forecast errors, we derive a multiple-horizon specification of stochastic volatility. We apply our method to forecasts for various macroeconomic variables from the Survey of Professional Forecasters. Compared to constant variance approaches, our stochastic volatility model improves the accuracy of uncertainty measures for survey forecasts. Our method can also be applied to ...