STRUCTURAL VECTOR AUTOREGRESSIONS: CHECKING IDENTIFYING LONG‐RUN RESTRICTIONS VIA HETEROSKEDASTICITY

Long‐run restrictions have been used extensively for identifying structural shocks in vector autoregressive (VAR) analysis. Such restrictions are typically just‐identifying but can be checked by utilizing changes in volatility. This paper reviews and contrasts the volatility models that have been used for this purpose. Three main approaches have been used, exogenously generated changes in the unconditional residual covariance matrix, changing volatility modelled by a Markov switching mechanism and multivariate generalized autoregressive conditional heteroskedasticity models. Using changes in volatility for checking long‐run identifying restrictions in structural VAR analysis is illustrated by reconsidering models for identifying fundamental components of stock prices.     

Erstens: ignorieren, zweitens: diffamieren, drittens: umarmen?

Mass media are an essential factor for the success of small parties, for the media can act in a supporting or an inhibiting way towards these parties. This could be observed for the example of the German Green Party: As the Greens were becoming more and more important in the parliaments, the media changed their formerly very critical view of the party to a more factual and positive reporting. Is the party “Die Linke” now experiencing a similar process? The present study analyses the comments of three national German newspapers from 2005 to 2009, using a quantitative content analysis with the aim of bringing to light how the media acted towards “Die Linke”. The results show that commenting has hardly changed since earlier studies were published. Factual issues only play a marginal role, and the party is judged negatively in all newspapers, with the tageszeitung slightly distinct from the other two papers, though.     

Modelling Hospital Admission and Length of Stay by Means of Generalised Count Data Models

For a large heterogeneous group of patients, we analyse probabilities of hospital admission and distributional properties of lengths of hospital stay conditional on individual determinants. Bayesian structured additive regression models for zero‐inflated and overdispersed count data are employed. In addition, the framework is extended towards hurdle specifications, providing an alternative approach to cover particularly large frequencies of zero quotes in count data. As a specific merit, the model class considered embeds linear and nonlinear effects of covariates on all distribution parameters. Linear effects indicate that the quantity and severity of prior illness are positively correlated with the risk of hospital admission, while medical prevention (in the form of general practice visits) and rehabilitation reduce the expected length of future hospital stays. Flexible nonlinear response patterns are diagnosed for age and an indicator of a patients' socioeconomic status. We find that social deprivation exhibits a positive impact on the risk of admission and a negative effect on the expected length of future hospital stays of admitted patients. Copyright © 2015 John Wiley & Sons, Ltd.     

Challenges for land system science

While considerable progress has been made in understanding land use change, land system science continues to face a number of grand challenges. This paper discusses these challenges with a focus on empirical land system studies, land system modelling and the analysis of future visions of land system change. Contemporary landscapes are contingent outcomes of past and present patterns, processes and decisions. Thus, empirical analysis of past and present land-use change has an important role in providing insights into the socio-economic and ecological processes that shape land use transitions. This is especially important with respect to gradual versus rapid land system dynamics and in understanding changes in land use intensity. Combining the strengths of empirical analysis with multi-scale modelling will lead to new insights into the processes driving land system change. New modelling methods that combine complex systems thinking at a local level with macro-level economic analysis of the land system would reconcile the multi-scale dynamics currently encapsulated in bottom-up and top-down modelling approaches. Developments in land use futures analysis could focus on integrating explorative scenarios that reflect possible outcomes with normative visions that identify desired outcomes. Such an approach would benefit from the broad and in-depth involvement of stakeholders in order to link scientific findings to political and societal decision-making culminating in a set of key choices and consequences. Land system models have an important role in supporting future land use policy, but model outputs require scientific interpretation rather than being presented as predictions. The future of land system science is strongly dependent on the research community's capacity to bring together the elements of research discussed in the paper, via empirical data collection and analysis of observed processes, computer simulation across scale levels and futures analysis of alternative, normative visions through stakeholder engagement.     

Network topology of the interbank market

We provide an empirical analysis of the network structure of the Austrian interbank market based on Austrian Central Bank (OeNB) data. The interbank market is interpreted as a network where banks are nodes and the claims and liabilities between banks define the links. This allows us to apply methods from general network theory. We find that the degree distributions of the interbank network follow power laws. Given this result we discuss how the network structure affects the stability of the banking system with respect to the elimination of a node in the network, i.e. the default of a single bank. Further, the interbank liability network shows a community structure that exactly mirrors the regional and sectoral organization of the current Austrian banking system. The banking network has the typical structural features found in numerous other complex real-world networks: a low clustering coefficient and a short average path length. These empirical findings are in marked contrast to the network structures that have been assumed thus far in the theoretical economic and econo-physics literature.     

Book reviews

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Münzunion oder Währungsunion?

Ohne Zusammenfassung     

Zum Problem optimaler Wachstumspfade in mehrsektoralen Modellen

Zusammenfassung Ausgangspunkt bildet ein Produktionsmodell, das durch eine Kombination von zwischensektoraler Prozeßbeschreibung und allgemeinen sektoralen Produktionsfunktionen gewissen empirischen Befunden über input-output-Struktur und Substitutionseffekten theoretisch zu entsprechen versucht. Auf dieser Basis läßt sich eine Reihe von Problemen des optimalen Wachstums (welfaremaximierende Pfade, optimale Beschäftigungspfade, konsummaximierende Pfade) als klassische Variationsprobleme formulieren. Schließlich wurde ein allgemeiner Ausblick auf andere Interpretationen (steuerbare Prozesse) und diesen angemessene Lösungstechniken größerer Leistungsfähigkeit (Maximumprinzip von Pontrjagin) eröffnet.Mit 1 Textabbildung