For more than half a century, Manfred Deistler has been contributing to the construction of the rigorous theoretical foundations of the statistical analysis of time series and more general stochastic processes. Half a century of unremitting activity is not easily summarized in a few pages. In...

A survey is provided dealing with the formulation of modelling problems for dynamic factor models, and the various algorithm possibilities for solving these modelling problems. Emphasis is placed on understanding requirements for the handling of errors, noting the relevance of the proposed...

Financial shocks represent a major driver of fluctuations in tail risk, defined as the 5th percentile of the forecast distributions of output and inflation. Since the variance and the asymmetry of the forecast distributions are largely driven by the left tail, financial shocks turn out to play a...

We use a dynamic factor model to provide a semi-structural representation for 101 quarterly US macroeconomic series. We find that (i) the US economy is well described by a number of structural shocks between two and five. Focusing on the four-shock specification, we identify, using sign...

Financial shocks generate a protracted and quantitatively important effect on real economic activity and financial markets only if the shocks are both negative and large. Otherwise, their role is quite modest. Financial shocks have become more important for economic fluctuations after the 2000...

The authors replicate and extend the Monte Carlo experiment presented in Doz, Giannone and Reichlin (A Quasi-Maximum Likelihood Approach For Large, Approximate Dynamic Factor Models, Review of Economics and Statistics, 2012) on alternative (time-domain based) methods for extracting dynamic...