Bayesian approaches to the estimation of DSGE models are becoming increasingly popular. Prior knowledge is normally formalized either be information concerning deep parameters’ values (‘microprior’) or some macroeconomic indicator, e.g. moments of observable variables (‘macroprior’)....

Bayesian approaches to the estimation of DSGE models are becoming increasingly popular. Prior knowledge is normally formalized either directly on deep parameters' values (‘microprior’) or indirectly, on macroeconomic indicators, e.g. moments of observable variables (‘macroprior’). We...

Recent empirical literature shows that key macro variables such as GDP and productivity display long memory dynamics. For DSGE models, we propose a �Generalized� Kalman Filter to deal effectively with this problem: our method connects to and innovates upon data-filtering techniques...

We investigate the predictive content of credit and government interest spreads with respect to the Italian GDP growth. Our analysis with Dynamic Model Averaging identifies when interest spreads were more useful predictors of economic activity: these periods are not limited to the Great...

In this paper, we develop financial conditions indices (FCIs) for 3 industrialized (US, Japan, UK) and 5 emerging (China, Brazil, Russia, India, Turkey) economies. The FCIs are formed as the principal component of a range of financial series for each country and are constructed to account for...

We investigate the relationship between macroeconomic conditions and banks' balance sheets by referring to a modified version of the Bank of Italy Quarterly Model (BIQM), regularly used for forecasting and policy analysis. In particular, we examine how regulatory bank capital and private sector...

The paper investigates the impact of US quantitative easing (QE) on global non-financial corporate bond issuance. It distinguishes between two QE instruments, MBS/GSE debt and Treasury bonds, and disentangles between two channels of transmission of QE to global bond markets, namely flow effects...

We evaluate forecasts for the euro area in data-rich and ‘data-lean’ environments by comparing three different approaches: a simple PMI model based on Purchasing Managers’ Indices (PMIs), a dynamic factor model with euro area data, and a dynamic factor model with data from the euro plus...

We evaluate forecasts for the euro area in data-rich and ‘data-lean’ environments by comparing three different approaches: a simple PMI model based on Purchasing Managers’ Indices (PMIs), a dynamic factor model with euro area data, and a dynamic factor model with data from the euro plus...

While the usefulness of factor models has been acknowledged over recent years, little attention has been devoted to the forecasting power of these models for the Japanese economy. In this paper, we aim at assessing the relative performance of factor models over different samples, including the...