Predicting Financial Crises: The (Statistical) Significance of the Signals Approach
Makram El-Shagi, Tobias Knedlik, Gregor von Schweinitz
Journal of International Money and Finance,
No. 35,
2013
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 cannot 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 results; (2) that composite indicators aggregating information contained in individual indicators add value to the signals approach; and (3) that indicators which are found to be significant in-sample usually perform similarly well out-of-sample.
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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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Intra-industry trade between European Union and Transition Economies. Does income distribution matter?
Hubert Gabrisch, Maria Luigia Segnana
IWH Discussion Papers,
No. 155,
2002
Abstract
EU-TE trade is increasingly characterised by intra-industry trade. For some countries (Czech Republic), the share of intra-industry trade in total trade with the EU approaches 60 percent. The decomposition of intra-industry trade into horizontal and vertical shares reveals overwhelming vertical structures with strong quality advantages for the EU and shrinking quality advantages for TE countries wherever trade has been liberalised. Empirical research on factors determining this structure in an EU-TE framework has lagged theoretical and empirical research on horizontal trade and vertical trade in other regions of the world. The main objective of this paper is, therefore, to contribute to the ongoing debate over EU-TE trade structures, by offering an explanation of intra-industry trade. We utilize a cross-country approach in which relative wage differences and country size play a leading role. In addition, as implied by a model of the productquality
cycle, we examine income distribution factors as determinates of the emerging
EU-TE structure of trade flows. Using OLS regressions, we find first, that relative
differences in wages (per capita income) and country size explain intra-industry trade, when trade is vertical and completely liberalized and second, that cross country differences in income distribution play no explanatory role. We conclude that if increasing wage differences resulted from an increasing productivity gap between highquality and low-quality industries, then vertical structures will, over the long-term create significant barriers for the increase in TE incomes and lowering EU-TE income differentials.
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