We document the impact of COVID-19 on frequently employed time series models, with a focus on euro area in ation. We show that for both single equation models (Phillips curves) and Vector Autoregressions (VARs) estimated parameters change notably with the pandemic. In a VAR, allowing the errors...

We propose a framework to identify a rich set of structural drivers of inflation in order to understand the role of the multiple and concomitant sources of the post-pandemic inflation surge. We specify a medium-sized structural Bayesian VAR on a comprehensive set of variables for the euro area...

We document the impact of COVID-19 on frequently employed time series models, with a focus on euro area inflation. We show that for both single equation models (Phillips curves) and Vector Autoregressions (VARs) estimated parameters change notably with the pandemic. In a VAR, allowing the errors...

This paper investigates how the ordering of variables affects properties of the time-varying covariance matrix in the Cholesky multivariate stochastic volatility model.It establishes that systematically different dynamic restrictions are imposed whenthe ratio of volatilities is time-varying....

This paper investigates how the ordering of variables affects properties of the time-varying covariance matrix in the Cholesky multivariate stochastic volatility model. It establishes that systematically different dynamic restrictions are imposed when the ratio of volatilities is time-varying....