Structural vector-autoregressive models are potentially very useful tools for guiding both macro- and microeconomic policy. In this paper, we present a recently developed method for exploiting non-Gaussianity in the data for estimating such models, with the aim of capturing the causal structure...

Work and life satisfaction depends on a number of pecuniary and nonpecuniary factors at the workplace and determines these in turn. We analyze these causal linkages using a structural vector autoregression approach for a sample of the German working populace collected from 1984 to 2008, finding...

Work and life satisfaction depend on a number of pecuniary and non-pecuniary factors at the workplace and determine these in turn. We analyze these causal linkages using a structural vector autoregression approach for a German sample of the working populace from 1984-2008.

Work and life satisfaction depends on a number of pecuniary and nonpecuniary factors at the workplace and determines these in turn. We analyze these causal linkages using a structural vector autoregression approach for a sample of the German working populace collected from 1984 to 2008, finding...

Structural vector-autoregressive models are potentially very useful tools for guiding both macro- and microeconomic policy. In this paper, we present a recently developed method for exploiting non-Gaussianity in the data for estimating such models, with the aim of capturing the causal structure...

The identification of a VAR requires differentiating between correlation and causation. This paper presents a method to deal with this problem. Graphical models, which provide a rigorous language to analyze the statistical and logical properties of causal relations, associate a particular set of...