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'). In this...

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 already...

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...

We build a model to simulate how the euro-area market-based financial system may function under stressed conditions, such as the COVID-19 turmoil. The core of the model is a set of representative agents reflecting key economic sectors, which interact in asset, funding and derivatives markets and...

The paper proposes a framework for assessing the impact of system-wide and bank-level capital buffers. The assessment rests on a factor-augmented vector autoregression (FAVAR) model that relates individual bank adjustments to macroeconomic dynamics. We estimate FAVAR models individually for...

We build a model to simulate how the euro area market-based financial system may function under stress. The core of the model is a set of representative agents re ecting key economic sectors, which interact in asset, funding, and derivatives markets and face solvency and liquidity constraints on...