We propose a new measure of underlying inflation that informs, in real time, about asymmetric risks on the outlook of inflationary pressures. The asymmetries are generated through nonlinearities induced by economic activity. The new indicator is based on a multivariate regime-switching framework...

This paper describes the set of Bayesian vector autoregression (BVAR) models that Banco de España uses to project GDP growth rates and to simulate macrofinancial risk scenarios for Brazil and Mexico. The toolkit consists of large benchmark models to produce baseline projections and various...

The ongoing trend of high inflation across much of the world has reignited interest in inflation volatility with varying foci and methods. In this paper, we employ a Bayesian framework to estimate inflation volatility using a sample of G20 countries. Estimation results suggest persistent...

We propose efficient Bayesian Hamiltonian Monte Carlo method for estimation of systemic risk measures, LRMES, SRISK and ∆CoVaR, and apply it for thirty global systemically important banks and for eighteen largest US financial institutions over the period of 2000-2020. The advantage of the...

When agents' information is imperfect and dispersed, existing measures of macroeconomic uncertainty based on the forecast error variance have two distinct drivers: the variance of the economic shock and the variance of the information dispersion. The former driver increases uncertainty and...