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Keywords:survey forecasts 

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 Papers , Paper 21-06

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 ...
Staff Reports , Paper 655

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 ...
Staff Reports , Paper 992

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.
Working Papers , Paper 2017-026

Report
The FRBNY staff underlying inflation gauge: UIG

Monetary policymakers and long-term investors would benefit greatly from a measure of underlying inflation that uses all relevant information, is available in real time, and forecasts inflation better than traditional underlying inflation measures such as core inflation measures. This paper presents the ?FRBNY Staff Underlying Inflation Gauge (UIG)? for CPI and PCE. Using a dynamic factor model approach, the UIG is derived from a broad data set that extends beyond price series to include a wide range of nominal, real, and financial variables. It also considers the specific and time-varying ...
Staff Reports , Paper 672

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.
Working Papers (Old Series) , Paper 1715

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 ...
Staff Reports , Paper 775

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?
Liberty Street Economics , Paper 20230802

Report
Is There Hope for the Expectations Hypothesis?

Most macroeconomic models impose a tight link between expected future short rates and the term structure of interest rates via the expectations hypothesis (EH). While the EH has been systematically rejected in the data, existing work evaluating the EH generally assumes either full-information rational expectations or stationarity of beliefs, or both. As such, these analyses are ill-equipped to refute the EH when these assumptions fail to hold, fueling hopes for a “resurrection” of the EH. We introduce a model of expectations formation which features time-varying means and accommodates ...
Staff Reports , Paper 1098

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 Papers (Old Series) , Paper 1809

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