Sallie Mae, through its wholly owned subsidiary Nellie Mae, has published at regular intervals, since 1998, its analysis of credit card usage among college students at both the undergraduate and graduate levels. With today’s economic environment, information in this study continues to be relevant to students, educators, lenders and families. Particularly because college students generally produce a modicum of income, it is important to understand how they use credit, how much they are using, and the factors both attitudinal and situational that contribute to their decisions to use credit.
The primary data used for the study to assess how much credit students are using comes from credit bureau reports of students who have applied for credit based “alternative” or “private” student loans. In the early versions of the study, we analyzed only this credit bureau data for a randomly selected group of students at the start of the academic year. Beginning in 2004, we added a survey component to help uncover student attitudes about credit and the types of goods and services for which they are using credit.
Corporate managers in the US and Europe claim that maintaining "financial flexibility" is the primary objective of their firms' financial policies (see Graham and Harvey (2001) and Banceland Mittoo (2002)). Their stated policies are consistent with the goal of ensuring funding for present and future investment undertakings in a world where financing frictions force fir ms to pas sup profitable opportunities. In spite of those assertions, empirical work on capital structure often ignores much of the interplay between corporate investment and financing decisions.
Quantifying extremal dependence is a central problem of multivariate extreme value theory and its statistical applications. Two forms of extremal dependence are possible: extremes are either asymptotically independent or asymptotically dependent.
Theoretical examples of the two limiting behaviours are the bivariate Normal distribution, for asymptotic independence, and the bivariate t distribution, for asymptotic dependence (see, for example, Ledford and Tawn, 1996, and Demarta and McNeil, 2005). In this work, we focus on the tail dependence of skewed extensions of these basic models, namely the bivariate skew-Normal and skew-t distributions (Azzalini and Capitanio, 1999 and 2003).
