Analysts often use financial variables to help predict real activity and inflation. One of the most popular of these variables is the spread between yields on long-term and short-term government instruments, also known as the yield spread. Researchers have shown the spread is a good predictor of...

Forecasts by rational agents contain embedded initial and terminal boundary conditions. Standard time series models generate two types of long-run "endpoints"---fixed endpoints and moving average endpoints. Neither can explain the shifting endpoints implied by postwar movements in the...

This note extends the analysis in Stark and Croushore (2001) with an emphasis on the importance of data vintage for survey forecasts and modeling expectations. For both of these types of empirical exercises, results suggest that the choice of latest available or real-time data is critical for...

Forecasts by rational agents contain embedded initial and terminal boundary conditions. Standard time series models generate two types of long-run "endpoints"--fixed endpoints and moving average endpoints. Neither can explain the shifting endpoints implied by postwar movements in the...

It is tempting to interpret empirical evidence in a number of recent studies as suggesting that term structure spreads help predict future inflation over moderate horizons of 3 to 5 years. This paper argues that common measures of the predictive power of the term structure spread for future...

We propose a new algorithm which allows easy estimation of Vector Autoregressions (VARs) featuring asymmetric priors and time varying volatilities, even when the cross sectional dimension of the system N is particularly large. The algorithm is based on a simple triangularisation which allows to...

This study examines the problem of forecasting an aggregate of cointegrated disaggregates. It first establishes conditions under which forecasts of an aggregate variable obtained from a disaggregate VECM will be equal to those from an aggregate, univariate time series model, and develops a...

This paper examines the asymptotic and finite-sample properties of tests of equal forecast accuracy applied to direct, multi-step predictions from both non-nested and nested linear regression models. In contrast to earlier work -- including West (1996), Clark and McCracken (2001, 2005),and...

Motivated by the common finding that linear autoregressive models forecast better than models that incorporate additional information, this paper presents analytical, Monte Carlo, and empirical evidence on the effectiveness of combining forecasts from nested models. In our analytics, the...

This paper uses Monte Carlo experiments to examine the small-sample properties of some commonly used tests of equal forecast accuracy. The study pays particular attention to test power, evaluated using both asymptotic and empirical critical values. In addition to evaluating different tests, this...