This paper develops and illustrates a simple method to generate a DSGE model-based forecast for variables that do not explicitly appear in the model (non-core variables). The authors use auxiliary regressions that resemble measurement equations in a dynamic factor model to link the non-core...

The surge in fiscal deficits since 2008 has put a renewed focus on the authors’ understanding of fiscal policy. The interaction of fiscal and monetary policy during this period has also been the subject of much discussion and analysis. This paper gives new insight into past fiscal policy and...

This paper proposes new methodologies for evaluating out-of-sample forecasting performance that are robust to the choice of the estimation window size. The methodologies involve evaluating the predictive ability of forecasting models over a wide range of window sizes. The authors show that the...

Economists have tried to uncover stylized facts about people’s expectations, testing whether such expectations are rational. Tests in the early 1980s suggested that expectations were biased, and some economists took irrational expectations as a stylized fact. But, over time, the results of...

This paper illustrates the use of a real-time data set for forecasting. The data set consists of vintages, or snapshots, of the major macroeconomic data available at quarterly intervals in real time. The paper explains the construction of the data set, examines the properties of several of the...

The authors propose a measure of predictability based on the ratio of the expected loss of a short-run forecast to the expected loss of a long-run forecast. This predictability measure can be tailored to the forecast horizons of interest, and it allows for general loss functions, univariate or...

We provide a new way to filter US inflation into trend and cycle components, based on extracting long-run forecasts from the Survey of Professional Forecasters. We operate the Kalman filter in reverse, beginning with observed forecasts, then estimating parameters, and then extracting the...

This paper presents a small-scale macroeconometric time-series model that can be used to generate short-term forecasts for U.S. output, inflation, and the rate of unemployment. Drawing on both the Bayesian VAR and vector error corrections (VEC) literature, the author specifies the baseline model...

This paper presents the concept and uses of a real-time data set that can be used by economists for testing the robustness of published econometric results, for analyzing policy, and for forecasting. The data set consists of vintages, or snapshots, of the major macroeconomic data available at...

Vector-autoregression (VAR) forecast models have been developed for many state economies, including the three states in the Third Federal Reserve District--Pennsylvania, New Jersey, and Delaware. This paper extends that work by developing a Bayesian VAR forecast model for the Philadelphia...