This dissertation focuses on describing and explaining business cycle dynamics. Motivated by the extraordinary strong economic downturn in 2008/2009, it emphasis the importance of modeling nonlinearities. This thesis should be regarded as a contribution to applied econometrics and can be...

This chapter uses an application to explore the utility of Bayesian quantile regression (BQR) methods in producing density nowcasts. Our quantile regression modeling strategy is designed to reflect important nowcasting features, namely the use of mixed-frequency data, the ragged-edge, and large...

The authors introduce a new approach to estimate high-dimensional factor-augmented vector autoregressive models (FAVAR) where the loadings are subject to idiosyncratic regime-switching dynamics. Our Bayesian estimation method alleviates computational challenges and makes the estimation of...