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’)....

We seek to quantify the impact on euro area GDP of the European Economic Recovery Plan (EERP) enacted in response to the financial crisis of 2008-09. To do so, we estimate an extended version of the ECB's New Area-Wide Model with a richly specified fiscal sector. The estimation results point to...

In this paper we review the methodology of forecasting with log-linearised DSGE models using Bayesian methods. We focus on the estimation of their predictive distributions, with special attention being paid to the mean and the covariance matrix of h-step ahead forecasts. In the empirical...

We introduce frictional financial intermediation into a HANK model. Households are subject to idiosyncratic and aggregate risk and smooth consumption through savings and consumer loans intermediated by banks. The banking friction introduces an endogenous countercyclical spread between the...

We explore the dynamic effects of news about a future technology improvement which turns out ex post to be overoptimistic. We find that it is difficult to generate a boom-bust cycle (a period in which stock prices, consumption, investment and employment all rise and then crash) in response to...

We explore the dynamic effects of news about a future technology improvement which turns out ex post to be overoptimistic. We find that it is difficult to generate a boom-bust cycle (a period in which stock prices, consumption, investment and employment all rise and then crash) in response to...

We seek to quantify the impact on euro area GDP of the European Economic Recovery Plan (EERP) enacted in response to the financial crisis of 2008-09. To do so, we estimate an extended version of the ECB’s New Area-Wide Model with a richly specified fiscal sector. The estimation results point...

This paper illustrates how to handle a sequence of extreme observations-such as those recorded during the COVID-19 pandemic-when estimating a Vector Autoregression, which is the most popular time-series model in macroeconomics. Our results show that the ad-hoc strategy of dropping these...

Dynamic stochastic general equilibrium models have recently become standard tools for policy-oriented analyses. Nevertheless, their forecasting properties are still barely explored. We fill this gap by comparing the quality of real-time forecasts from a richly-specified DSGE model to those from...

This paper shows how to compute the h-step-ahead predictive likelihood for any subset of the observed variables in parametric discrete time series models estimated with Bayesian methods. The subset of variables may vary across forecast horizons and the problem thereby covers marginal and joint...