We show that two macroeconomic factors have an important predictive content for governmentbond yields and excess returns. These factors are not spanned by the cross-section of yields andare well proxied by economic growth and real interest rates.

We define rank-based estimators (R-estimators) for semiparametric time series models in whichthe conditional location and scale depend on a Euclidean parameter, while the innovation density isan infinite-dimensional nuisance. Applications include linear and nonlinear models, featuring...

Realized volatilities, when observed through time, share the following stylized facts: co–movements, clustering, long–memory, dynamic volatility, skewness and heavy–tails. We propose a simple dynamic factor model that captures these stylized facts and that can be applied to vast panels of...

This paper develops a framework that allows us to combine the tools provided by structural models for economic interpretation and policy analysis with those of reduced-form models designed for nowcasting. We show how to map a quarterly dynamic stochastic general equilibrium (DSGE) model into a...

We propose a class of prior distributions that discipline the long-run predictions of vector autoregressions (VARs). These priors can be naturally elicited using economic theory, which provides guidance on the joint dynamics of macroeconomic time series in the long run. Our priors for the long...

This paper formalizes the process of updating the nowcast and forecast on output and inflation as new releases of data become available. The marginal contribution of a particular release for the value of the signal and its precision is evaluated by computing "news" on the basis of an evolving...

This paper compares the predictive ability of the factor models of Stock and Watson (2002) and Forni, Hallin, Lippi, and Reichlin (2005) using a "large" panel of US macroeconomic variables. We propose a nesting procedure of comparison that clarifies and partially overturns the results of similar...

This paper shows that Vector Autoregression with Bayesian shrinkage is an appropriate tool for large dynamic models. We build on the results by De Mol, Giannone, and Reichlin (2008) and show that, when the degree of shrinkage is set in relation to the cross-sectional dimension, the forecasting...

We analyse the panel of the Greenbook forecasts (sample 1970-96) and a large panel of monthly variables for the US (sample 1970-2003) and show that the bulk of dynamics of both the variables and their forecasts is explained by two shocks. Moreover, a two factor model which exploits, in real...

This paper shows how and when it is possible to obtain a mapping from a quarterly DSGE model to amonthly specification thatmaintains the same economic restrictions and has real coefficients. We use this technique to derive the monthly counterpart of the Gali et al (2011) model. We then augment...