Search Results
Working Paper
Combining Survey Long-Run Forecasts and Nowcasts with BVAR Forecasts Using Relative Entropy
This paper constructs hybrid forecasts that combine both short- and long-term conditioning information from external surveys with forecasts from a standard fixed-coefficient vector autoregression (VAR) model. Specifically, we use relative entropy to tilt one-step ahead and long-horizon VAR forecasts to match the nowcast and long-horizon forecast from the Survey of Professional Forecasters. The results indicate meaningful gains in multi-horizon forecast accuracy relative to model forecasts that do not incorporate long-term survey conditions. The accuracy gains are achieved for a range of ...
Working Paper
Optimal Pooling in Taylor Rule Estimation with Multiple-Horizon Forecast Panels
Multiple-horizon forecast panels are increasingly used to infer perceived monetary policy rules, but inference depends on how coefficients are pooled across forecasters, dates, and horizons. We treat this pooling structure as the object of inference. In a participant-date-horizon Taylor-rule regression model, we compare pooling patterns using Bayesian marginal likelihoods, applying the framework to the Blue Chip Financial Forecasts, Survey of Professional Forecasters, and the Summary of Economic Projections. The preferred specifications place much of the systematic variation in policy-rate ...
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
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 ...
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.
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 ...
Working Paper
Constructing Fan Charts from the Ragged Edge of SPF Forecasts
We develop models that take point forecasts from the Survey of Professional Forecasters (SPF) as inputs and produce estimates of survey-consistent term structures of expectations and uncertainty at arbitrary forecast horizons. Our models combine fixed-horizon and fixed-event forecasts, accommodating time-varying horizons and availability of survey data, as well as potential inefficiencies in survey forecasts. The estimated term structures of SPF-consistent expectations are comparable in quality to the published, widely used short-horizon forecasts. Our estimates of time-varying forecast ...
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 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 ...
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.