The global financial crisis has reignited interest in models of crisis prediction. It has also raised the question whether financial connectedness-a possible source of systemic riskcan serve as an early warning indicator of crises. In this paper we examine the ability of connectedness in the global network of financial linkages to predict systemic banking crises. Our results indicate that increases in a country's financial interconnectedness and decreases in its neighbors' connectedness are associated with a higher probability of banking crises after controlling for macroeconomic fundamentals.

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The global financial crisis has reignited interest in models of crisis prediction. It has also raised the question whether financial interconnectedness-a possible source of systemic risk-can serve as an early warning indicator of crises. In this paper, we examine the ability of connectedness in the global network of financial linkages to predict systemic banking crises during the 1978-2010 period. Our results indicate that increases in a country's own connectedness and decreases in its neighbours' connectedness are associated with a higher probability of banking crises after controlling for macroeconomic fundamentals. Our findings suggest that financial interconnectedness has early warning potential, especially for the 2007-2010 wave of systemic banking crises.

The global financial crisis has reignited interest in models of crisis prediction. It has also raised the question whether financial connectedness-a possible source of systemic riskcan serve as an early warning indicator of crises. In this paper we examine the ability of connectedness in the global network of financial linkages to predict systemic banking crises. Our results indicate that increases in a country's financial interconnectedness and decreases in its neighbors' connectedness are associated with a higher probability of banking crises after controlling for macroeconomic fundamentals.

Individual achievement in college has been closely tied to dropout and graduation rates and these indices of completion have been considered the most important measures for gauging achievement in undergraduate education. In this study, we both define and examine a new concept of thriving in college. Both the literature and the data suggest that a multidimensional concept of thriving is better suited for predicting student achievement. We base our data analysis on the data we collected from a nationwide survey conducted in 2013-2014. The survey data show that student achievement in college does not depend solely on academic performance, and that there is no single factor that predicts thriving in college, in general, for an individual student. We show that in a heterogeneous population of students and a heterogeneous set of colleges, there is no unique pattern or factor for all students to thrive in the same college. We define and quantify the concepts of multidimensional thriving, personal traits and college ecosystems and build an algorithm that shows which is the best college ecosystem for a unique student. Furthermore, we show which traits of this individual are most responsible for the subsequent thriving in this specific college and which other traits s/he should learn or acquire in order to increase these chances of thriving.