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...

To enact effective policies and spend resources efficiently, firms, policymakers, and markets need accurate economic forecasts. But even though economists generally work with similar models and data, their projections often range widely. To better understand why, Keith Sill explores what the...

When setting monetary policy, should policymakers target variables such as commodity prices or interest rate spreads, which are sensitive to the market's expectations of inflation? Or are variables such as money growth, which are tied to the underlying causes of inflation and economic growth,...

Do professional forecasters distort their reported forecasts in a way that compromises accuracy? New research in the theory of forecasting suggests such a possibility. In a recent paper, Owen Lamont finds that forecasters in the Business Week survey make more radical forecasts as they gain...

This paper presents new evidence on the benefits of conditioning quarterly model forecasts on monthly current-quarter data. On the basis of a quarterly Bayesian vector error corrections model, the findings indicate that such conditioning produces economically relevant and statistically...

The authors propose methods for evaluating and improving density forecasts. They focus primarily on methods that are applicable regardless of the particular user's loss function, though they take explicit account of the relationships between density forecasts, action choices, and the...

Broadly defined, macroeconomic forecasting is alive and well. Nonstructural forecasting, which is based largely on reduced-form correlations, has always been well and continues to improve. Structural forecasting, which aligns itself with economic theory and, hence, rises and falls with theory,...

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...