In this Paper we concentrate on the hypothesis that the empirical rejections of the Expectations Theory (ET) of the term structure of interest rates can be caused by improper modeling of expectations. Our starting point is an interesting anomaly found by Campbell-Shiller (1987), when by taking a...

This paper brings together two strands of the empirical macro literature: the reduced-form evidence that the yield spread helps in forecasting output and the structural evidence on the difficulties of estimating the effect of monetary policy on output in an intertemporal Euler equation. We show...

Models based on economic theory have serious problems at forecasting exchange rates better than simple univariate driftless random walk models, especially at short horizons. Multivariate time series models suffer from the same problem. In this paper, we propose to forecast exchange rates with a...

We propose a new approach to forecasting the term structure of interest rates, which allows to efficiently extract the information contained in a large panel of yields. In particular, we use a large Bayesian Vector Autoregression (BVAR) with an optimal amount of shrinkage towards univariate AR...

The paper addresses the issue of forecasting a large set of variables using multivariate models. In particular, we propose three alternative reduced rank forecasting models and compare their predictive performance for US time series with the most promising existing alternatives, namely, factor...

The estimation of large Vector Autoregressions with stochastic volatility using standard methods is computationally very demanding. In this paper we propose to model conditional volatilities as driven by a single common unobserved factor. This is justified by the observation that the pattern of...

We propose a method to produce density forecasts of the term structure of government bond yields that accounts for (i) the possible mispecification of an underlying Gaussian Affine Term Structure Model (GATSM) and (ii) the time varying volatility of interest rates. For this, we derive a Bayesian...

This paper develops a method for producing current-quarter forecasts of GDP growth with a (possibly large) range of available within-the-quarter monthly observations of economic indicators, such as employment and industrial production, and financial indicators, such as stock prices and interest...

In this paper we discuss how the forecasting performance of Bayesian VARs is affected by a number of specification choices. In the baseline case, we use a Normal-Inverted Wishart (N-IW) prior that, when combined with a (pseudo-) iterated approach, makes the analytical computation of h-step ahead...

We use the time series of shifts in U.S. Federal tax liabilities constructed by Romer and Romer to estimate tax multipliers. Differently from the single-equation approach adopted by Romer and Romer, our estimation strategy (a Var that includes output, government spending and revenues, inflation...