Econometric Measures of Connectedness and Systemic Risk in the Finance and Insurance Sectors

We propose several econometric measures of connectedness based on principal-components analysis and Granger-causality networks, and apply them to the monthly returns of hedge funds, banks, broker/dealers, and insurance companies. We find that all four sectors have become highly interrelated over the past decade, likely increasing the level of systemic risk in the finance and insurance industries through a complex and time-varying network of relationships. These measures can also identify and quantify financial crisis periods, and seem to contain predictive power in out-of-sample tests. Our results show an asymmetry in the degree of connectedness among the four sectors, with banks playing a much more important role in transmitting shocks than other financial institutions.Systemic Risk; Financial Institutions; Liquidity; Financial Crises

Understanding Organized Crime Networks: Evidence Based on Federal Bureau of Narcotics Secret Files on American Mafia

Using unique data on criminal profiles of 800 US Mafia members active in the 50s and 60s and on their connections within the Cosa Nostra network we analyze how the geometry of criminal ties between mobsters depends on family ties, community roots and ties, legal and illegal activities. We contrast our evidence with historical and sociological views about the functioning of the Mafia. Much of our findings are remarkably in line with these views, with interesting qualifications. We interpret some of our results in light of a model of optimal vertical and horizontal connections where more connections mean more profits but also a higher risk of defection. We find that variables that lower the risk of defection, among others, kinship, violence, and mafia culture increase the number of connections. Moreover, there is evidence of strategic endogamy: female children are as valuable as male ones, and being married to a "connected" wife is a strong predictor of leadership within the Mafia ranks. A very parsimonious regression model explains one third of the variability in the criminal ranking of the "men of honor," suggesting that these variables could be used to detect criminal leaders. An additional prediction of our simple model is a right-skewed distribution of the number of connections, which is remarkably in line with the evidence of an extremely hierarchical organization.Mafia; Networks; Intermarriage; Assortative Matching; Crime