Predicting Financial Crises: The (Statistical) Significance of the Signals Approach
Makram El-Shagi, Tobias Knedlik, Gregor von Schweinitz
Abstract
The signals approach as an early warning system has been fairly successful in detecting crises, but it has so far failed to gain popularity in the scientific community because it does not distinguish between randomly achieved in-sample fit and true predictive power. To overcome this obstacle, we test the null hypothesis of no correlation between indicators and crisis probability in three applications of the signals approach to different crisis types. To that end, we propose bootstraps specifically tailored to the characteristics of the respective datasets. We find (1) that previous applications of the signals approach yield economically meaningful and statistically significant results and (2) that composite
indicators aggregating information contained in individual indicators add value to the signals approach, even where most individual indicators are not statistically significant on their own.
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The Causal Effect of Watching TV on Material Aspirations: Evidence from the “Valley of the Innocent”
Walter Hyll, Lutz Schneider
Abstract
The paper addresses the question of whether TV consumption has an impact on material aspirations. We exploit a natural experiment that took place during the period in which Germany was divided. Owing to geographical reasons, TV programs from the Federal Republic of Germany could not be received in all parts of the German Democratic Republic. Therefore, a natural variation occurred in exposure to West German television. We find robust evidence that watching TV is positively correlated with aspirations. Our identification strategy implies a causal relationship running from TV to aspirations. This conclusion resists various sets of alternative specifications and samples.
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Qual VAR Revisited: Good Forecast, Bad Story
Makram El-Shagi, Gregor von Schweinitz
Abstract
Due to the recent financial crisis, the interest in econometric models that allow to incorporate binary variables (such as the occurrence of a crisis) experienced a huge surge. This paper evaluates the performance of the Qual VAR, i.e. a VAR model including a latent variable that governs the behavior of an observable binary variable. While we find that the Qual VAR performs reasonably well in forecasting (outperforming a probit benchmark), there are substantial identification problems. Therefore, when the economic interpretation of the dynamic behavior of the latent variable and the chain of causality matter, the Qual VAR is inadvisable.
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Effects of Incorrect Specification on the Finite Sample Properties of Full and Limited Information Estimators in DSGE Models
Sebastian Giesen, Rolf Scheufele
Abstract
In this paper we analyze the small sample properties of full information and limited information estimators in a potentially misspecified DSGE model. Therefore, we conduct a simulation study based on a standard New Keynesian model including price and wage rigidities. We then study the effects of omitted variable problems on the structural parameters estimates of the model. We find that FIML performs superior when the model is correctly specified. In cases where some of the model characteristics are omitted, the performance of FIML is highly unreliable, whereas GMM estimates remain approximately unbiased and significance tests are mostly reliable.
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Real Effective Exchange Rate Misalignment in the Euro Area: A Counterfactual Analysis
Makram El-Shagi, Axel Lindner, Gregor von Schweinitz
Abstract
Were real effective exchange rates (REER) of Euro area member countries drastically misaligned at the outbreak of the global financial crisis? The answer is difficult to determine because economic theory gives no simple guideline for determining the equilibrium values of real exchange rates, and the determinants of those values might have been distorted as well. To overcome these limitations, we use synthetic matching to construct a counterfactual economy for each member as a linear combination of a large set of non-Euro area countries. We find that Euro area crisis countries are best described by a mixture of advanced and emerging economies. Comparing the actual REER with those of the counterfactuals gives sensible estimates of the misalignments at the start of the crisis: All peripheral countries were strongly overvalued, while high undervaluation is only observed for Finland.
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Plant-based Bioeconomy in Central Germany - Mapping of Actors, Industries and Places
Wilfried Ehrenfeld, Frieder Kropfhäußer
Abstract
The challenges facing the 21st century, presented by a growing global population, range from food security to sustainable energy supplies to the diminishing availability of fossil raw materials. An attempt to solve these problems is made by using the concept of bioeconomy. Plants, in particular, possess an important function in this context - they can be used either as a source of food or, in the form of biomass, for industrial or energy purposes. Linking industrial and agricultural research and production, bioeconomy provides growth potential, in particular in rural areas.
The aim of this article is therefore to outline the status of plant-based bioeconomy
in three states of Central Germany - Saxony, Saxony-Anhalt and Thuringia - and to compare this to German plant-based bioeconomy. We take an in-depth look at the different sectors and outline the industries involved, the location and age of the enterprises as well as the distribution of important NACE codes. In conclusion, we highlight the significant number of new or small enterprises and the high research and innovation rate of Central Germany. We also stress the future potential of Central German plant-based bioeconomy as well as the importance of a more plant-focusedview of the technology sector.
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The Structure and Evolution of Intersectoral Technological Complementarity in R&D in Germany from 1990 to 2011
Matthias Brachert, T. Broekel
Abstract
Technological complementarity is argued to be a crucial element for effective Research and Development (R&D) collaboration. The real structure is, however, still largely unknown. Based on the argument that organizations’ knowledge resources must fit for enabling collective learning and innovation, we use the co-occurrence of firms in collaborative R&D projects in Germany to assess inter-sectoral technological complementarity between 129 sectors. The results are mapped as complementarity space for the Germany economy. The space and its dynamics from 1990 to 2011 are analyzed by means of social network analysis.
The results illustrate sectors being complements both from a dyadic and portfolio/ network perspective. This latter is important, as complementarities may only become fully effective when integrated in a complete set of different knowledge resources from multiple sectors. The dynamic perspective moreover reveals the shifting demand for knowledge resources among sectors at different time periods.
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