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The paper develops an easy-to-apply test for contagion. In order to address the main challenge of any contagion test, that of endogeneity, the testing is conducted in the structural vector autoregression (SVAR) framework where we assume the reduced form errors follow a mixed-normal distribution. This distributional assumption enables us to use a recently developed SVAR model identification method with no need to restrict any of the instantaneous linkages between the variables. In the empirical part of the paper, we apply our test to the eurozone's ten years government bond spreads over Germany. In this maturity, the bond spreads mainly reflect governments' default risk. The years we consider are 2005--2010, and we find evidence of contagion in the spreads. Furthermore, it appears that, during the beginning of the euro debt crisis, there was transmission of government default risk from Greece to the other countries. However, Greece was not the only source country of contagion.JEL Classification: C1, C3, E4, F3, G1

The paper develops an easy-to-apply test for contagion. In order to address the main challenge of any contagion test, that of endogeneity, the testing is conducted in the structural vector autoregression (SVAR) framework where we assume the reduced form errors follow a mixed-normal distribution. This distributional assumption enables us to use a recently developed SVAR model identification method with no need to restrict any of the instantaneous linkages between the variables. In the empirical part of the paper, we apply our test to the eurozone's ten years government bond spreads over Germany. In this maturity, the bond spreads mainly reflect governments' default risk. The years we consider are 2005--2010, and we find evidence of contagion in the spreads. Furthermore, it appears that, during the beginning of the euro debt crisis, there was transmission of government default risk from Greece to the other countries. However, Greece was not the only source country of contagion.JEL Classification: C1, C3, E4, F3, G1

Empirical research confirms the existence of volatility spillovers across national stock markets. However, the models in use are mostly statistical ones. Much less is known about the actual transmission mechanisms; theoretical literature is scarce, and so is empirical work trying to estimate specific theoretical models. Some economic theory founded tests for such spillovers have been developed for non-overlapping markets; this institutional set up provides a way around the problems of estimating a system of simultaneous equations. However, volatility spillovers across overlapping markets might be as important a phenomenon as across non-overlapping markets. Building on recent advances in econometrics of identifying structural vector autoregressive models, this paper proposes a way to estimate an existing signal-extraction model that explains volatility spillovers across simultaneously open stock markets. Furthermore, a new empirical test for detection of such spillovers is derived. As an empirical application, the theoretical model is fitted to daily data of eurozone stock markets in years 2010--2011. Evidence of volatility spillovers across the countries is found.JEL Classification: C12, C30, D82, G14, G15