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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Technology Clubs, R&D and Growth Patterns: Evidence from EU Manufacturing
Claire Economidou, J. W. B. Bos, Michael Koetter
European Economic Review,
Nr. 1,
2010
Abstract
This paper investigates the forces driving output change in a panel of EU manufacturing industries. A flexible modeling strategy is adopted that accounts for: (i) inefficient use of resources and (ii) differences in the production technology across industries. With our model we are able to identify technical, efficiency, and input growth for endogenously determined technology clubs. Technology club membership is modeled as a function of R&D intensity. This framework allows us to explore the components of output growth in each club, technology spillovers and catch-up issues across industries and countries.
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