This paper aims to provide reliable estimates for the COVID-19 contact rate of a Susceptible-Infected-Recovered (SIR) model, From observable data on confirmed, recovered, and deceased cases, a noisy measurement for the contact rate can be constructed, To filter out measurement errors and...

In this paper, we assess the accuracy of macroeconomic forecasts at the regional level using a large data set at quarterly frequency. We forecast gross domestic product (GDP) for two German states (Free State of Saxony and Baden-Württemberg) and Eastern Germany. We overcome the problem of a...

The appropriate design of monetary policy in integrated financial markets is one of the most challenging areas for central banks. One hot topic is whether the rise in liquidity in recent years has contributed to the formation of price bubbles in asset markets. If strong linkages exist, the...

A probabilistic assessment about the set of possible trajectories that a random variable may follow over time is summarized by the simultaneous confidence region generated from its forecast generating distribution. However, if the null model is only approximative or altogether unavailable, one...

We consider a multivariate Markov-switching GARCH model which allows for regime-specific volatility dynamics, leverage effects, and correlation structures. Stationarity conditions are derived, and consistency of the maximum likelihood estimator (MLE) is established under the assumption of...

This paper employs the unrestricted extended constant conditional correlation GARCH specification proposed in Conrad and Karanasos (2010) to examine the intertemporal relationship between the uncertainties of inflation and output growth in the US. We find that inflation uncertainty effects...

This paper analyzes volatility spillovers in multivariate GARCH-type models. We show that the cross-effects between the conditional variances determine the persistence of the transmitted volatility innovations. In particular, the influence of a foreign volatility innovation on a conditional...

We represent the dynamic relation among variables in vector autoregressive (VAR) models as directed graphs. Based on these graphs, we identify so-called strongly connected components (SCCs). Using this graphical representation, we consider the problem of variable selection. We use the relations...