We assess the stability of the unemployment gap parameter using linear dynamic Phillips curve models for the United States. In this study, we allow the unemployment gap parameter to be time-varying such that we can monitor the importance of the Phillips curve over time. We consider different...

In this paper we investigate whether the dynamic properties of the U.S. business cycle have changed in the last fifty years. For this purpose we develop a flexible business cycle indicator that is constructed from a moderate set of macroeconomic time series. The coincident economic indicator is...

We propose a new class of observation-driven time-varying parameter models for dynamic volatilities and correlations to handle time series from heavy-tailed distributions. The model adopts generalized autoregressive score dynamics to obtain a time-varying covariance matrix of the multivariate...

We adopt an unobserved components time series model to extract financial cycles for the United States and the five largest euro area countries over the period 1970 to 2014. We find that credit, the credit-to-GDP ratio and house prices have medium-term cycles which share a few common statistical...

This paper has been accepted for publication in the 'Review of Economics and Statistics'.We propose a dynamic factor model for mixed-measurement and mixed-frequency panel data. In this framework time series observations may come from a range of families of parametric distributions, may be...

We propose a new model for dynamic volatilities and correlations of skewed and heavy-tailed data. Our model endows the Generalized Hyperbolic distribution with time-varying parameters driven by the score of the observation density function. The key novelty in our approach is the fact that the...