I propose a method identification of structural vector autoregressions (SVARs) and simultaneous equations models (SEMs) with orthogonal structural shocks using testable identification restrictions. If some sparsity conditions are satisfied, the method produces a set of testable inclusions and...

Systemic risk modelling concerns the estimation of the interrelationships between financial institutions, with the aim of establishing which of them are more central and, therefore, more contagious/subject to contagion. The aim of this paper is to develop a novel systemic risk model. A model...

We propose an objective Bayesian method for the comparison of all Gaussian directed acyclic graphical models defined on a given set of variables. The method, which is based on the notion of fractional Bayes factor, requires a single default (typically improper) prior on the space of...

We propose an objective Bayesian method for the comparison of all Gaussian directed acyclic graphical models defined on a given set of variables. The method, which is based on the notion of fractional Bayes factor, requires a single default (typically improper) prior on the space of...

We propose an objective Bayesian method for the comparison of all Gaussian directed acyclic graphical models defined on a given set of variables. The method, which is based on the notion of fractional Bayes factor, requires a single default (typically improper) prior on the space of...

Im Rahmen des DFG-Forschungsprojektes "Wertschöpfungstheorie betrieblicher Entsorgungsprozesse" soll die bestehende Produktionstheorie am Beispiel kommunaler Restmüllentsorgungsprozesse um entscheidungsorientierte Elemente erweitert werden. Dazu ist zunächst eine IST-Aufnahme der Prozesse...

We propose a new method for the objective comparison of two nested models based on non-local priors. More specifically, starting with a default prior under each of the two models, we construct a moment prior under the larger model, and then use the fractional Bayes factor for a comparison....

We propose a new method for the objective comparison of two nested models based on non-local priors. More specifically, starting with a default prior under each of the two models, we construct a moment prior under the larger model, and then use the fractional Bayes factor for a comparison....