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Ebook Segregation and the Subprime Lending Crisis

The growth in subprime lending, coupled with rising defaults and record-level foreclosure rates, has gripped the nation since 2008. Blame is being directed at ill-informed consumers, lax underwriting by loan originators, failure of regulatory agencies, predatory lending practices, greedy investors, misguided appraisers and credit rating agencies, job loss in economically distressed regions, and a range of other institutional and individual factors (Baily, Elmendorf, and Litan 2008; Gramlich 2007). Virtually ignored in this debate is the role of structural and contextual forces, most notably various trajectories of inequality, uneven metropolitan development, and racial segregation. While there is widespread recognition that lower income households and communities, racial minorities, women and other vulnerable populations are hardest hit, the context of racial segregation as a driver of subprime lending, and as an explanation for the variance in such lending across cities and communities, has not received serious consideration. Yet there are theoretically plausible reasons why the segregation of minorities may establish a context in which these lending practices would flourish (Squires 2008a).

It is plausible that in highly segregated cities, minority populations are more susceptible, for at least three reasons, to high-cost financial products. One explanation is that in segregated cities, minority communities are more isolated, and may be less experienced with purchasing financial products. Consequently, subprime lenders might more effectively target those areas in their marketing strategy and exploit differences in financial education. There is some evidence that some financial institutions have targeted low-income and minority neighborhoods for subprime products (Avery, Brevoort, and Canner 2006; Bocian, Ernst, and Li 2008; Squires 2008a). Second, mainstream, prime lenders might avoid segregated, low-income areas and there may be less competition among lenders, leaving borrowers, regardless of their financial education level, little choice other than high-cost products. Finally, lenders may place a higher risk-based premium for those living in low-income, segregated areas. In more segregated cities, there may be more at-risk areas (or at least the perception of greater risk) and people in these communities, and this might affect the city’s overall proportion of high-cost loans. These mechanisms may explain why segregation might contribute to variation in subprime lending across cities.

Ebook How do contracts adapt to an increase in free cash flow?

In this paper, I examine the evolution of firm contracts as the firm’s environment changes. While there has been extensive cross-sectional research documenting associations between contract choices (financing, monitoring, and compensation policies) and economic determinants, there is much less work corroborating these results with evidence that firms adapt to changes in their environment. I contribute to the literature on contracting by examining three research questions. First, I examine if contracts change in a manner predicted by economic theory in the years surrounding a change in the firm’s environment. Second, I study whether firms that can anticipate the change in the firm’s environment adjust contracts differently. Finally, I examine if the changes in contracts are associated with different managerial actions.

To address these research questions, I select a sample of firms that provides a powerful setting to study how contracts adapt to a change in the firm’s environment. I focus on firms experiencing a large and persistent increase in internally generated cash flow in excess of available investment opportunities (free cash flow). Multiple theories predict that an increase in free cash flow is an important event in the life of the firm affecting various firm contracts. Theories based on agency costs suggest that an increase in free cash flow provides managers with additional opportunities to engage in wasteful expenditures unless the appropriate contracts are present (e.g., Jensen, 1986; Lamont, 1997; and Titman, Wei and Xie, 2003). Theories based on market imperfections suggest that if it is costly to write contracts with external capital providers (due to information asymmetry) then an increase in internally generated cash flow will be associated with a concurrent increase in the feasible investment opportunity set (e.g., Fazzari, Hubbard, and Petersen, 1988).

Ebook Internal Liquidity Risk in Corporate Bond Credit Spreads

With the emergence of the rapidly growing credit and credit derivative markets, the issue of understanding the determinants of corporate yield spreads is of increasing importance in credit risk management. Considerable empirical efforts have been devoted to this fundamental issue. Most of them base on structural models which contain comprehensible economic intuitions and are able to study the effects of macroeconomic conditions and firm specific features on credit spreads. Although most of them support that the Merton type structural models are capable of explaining credit spreads to some extent, few conclude that the cross-sectional behaviors or dynamics of credit spreads could be captured largely by them.

Among those empirical efforts, Collin-Dufresne, Goldstein, and Martin (2001) found traditional credit models explain only about 25% of the variation in credit spreads and the unexplained portion is mostly driven by an unknown common factor. Eom, Helwege, and Huang (2004) find that the predicted spreads of the original Merton model are too low while most of the others over-predict spreads on average. They also find the newer models still suffer from underestimation problem on credit spreads of safer bonds. Campbell and Taksler (2003) utilize panel data of the late 1990s to explore the effect of equity volatility on corporate bond yields and find that idiosyncratic firm-level volatility can explain as much cross-sectional variation in yields as credit ratings can. Covitz and Downing (2002) use a simple liquidity indicator, current ratio, to explain yield spreads. They find that it can explain very short-term spreads while the explanatory power for long-term spreads is rather weak. Several recent studies lay stress on the non-default components in corporate bond yield spreads. Longstaff, Mithal, and Neis (2005), using credit default swaps data, find that the default component represents the majority of yield spreads though the non-default components, such as bond-specific illiquidity and overall liquidity of fixed income markets, do exist. Delianedis and Geske (2001) attribute the discrepancy between the observed credit spreads and Merton’s option based estimates of default spreads to external liquidity effect and market risk factors.

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