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...

This paper investigates why the slope of the yield curve predicts future economic activity in Germany and the United States. A structural VAR is used to identify aggregate supply, aggregate demand, monetary policy and inflation scare shocks and to analyse their effects on the real, nominal and...

A unifying framework for inference is developed in predictive regressions where the predictor has unknown integration properties and may be stationary or nonstationary. Two easily implemented nonparametric F-tests are proposed. The test statistics are related to those of Kasparis and Phillips...

This paper analyses the use of factor analysis for instrumental variable estimation when the number of instruments tends to infinity. In particular, we focus on situations where many weak instruments exist and/or the factor structure is weak. Theoretical results, simulation experiments and...

Imperfect information has played a prominent role in modern business cycle theory. This paper assesses its importance by estimating the New Keynesian (NK) model under alternative informational assumptions. One version focuses on confusion between temporary and persistent disturbances. Another,...

The work presented in this paper falls into two parts. First, using a simple model and within the context of the central bank’s objective of price stability, it is shown that the optimal monetary response to unexpected changes in asset prices depends on how these changes affect the central...

The estimation of dynamic factor models for large sets of variables has attracted considerable attention recently, due to the increased availability of large datasets. In this paper we propose a new parametric methodology for estimating factors from large datasets based on state space models and...

The estimation of structural dynamic factor models (DFMs) for large sets of variables is attracting considerable attention. In this paper we briefly review the underlying theory and then compare the impulse response functions resulting from two alternative estimation methods for the DFM....