Investors: The Missing Piece in the Foreclosure Racial Gap Debate

Abstract

Foreclosures have become one of the most important problems facing cities and the U.S. economy. However, not all communities are affected equally. Our goal is to better understand factors that affect variation in neighborhood foreclosures in a typical, mid‐sized U.S. city—Louisville, Kentucky. While previous findings indicate that a key explanatory variable leading to rising neighborhood foreclosures is the proportion of racial minorities, our analysis finds that in a fully specified model, race does not predict differences between black and white homeowners. On the other hand, an analysis of investors predicts high foreclosure rates in African‐American neighborhoods. The effect of percent nonwhite is caused by several key intervening variables, including the presence of investor foreclosures, the absence of neighborhood walkability, and the prevalence of high‐cost loans. In the past, walkability and investor behavior have largely been ignored by social scientists studying neighborhood variation in foreclosures and the role of race in rising foreclosures. In this article, we examine how speculation by investors in majority African‐American neighborhoods along with degree of walkability and the concentration of high‐priced loans have contributed to recent increases in foreclosures and variation across neighborhoods. Together, the findings demonstrate that these three factors help to better explain the contemporary causes of greater foreclosures in African‐American neighborhoods.

Race, Space, and Cumulative Disadvantage: A Case Study of the Subprime Lending Collapse

“…Yet the remaining sample statistics reveal other important differences between black and white borrowers that might plausibly account for racial disparities in lending terms and foreclosure rates. For example, blacks evince a greater likelihood of borrowing at the housing bubble's peak in 2006 as well as lower incomes, credit scores, and rates of neighborhood educational attainment, all factors that prior studies have shown to undermine loan performance and raise the odds of default and foreclosure (e.g., Anacker and Carr 2011; Chan et al 2013; Ding et al 2011; Gilderbloom et al 2012; Pennington-Cross and Ho 2010). …”

“…Whereas 79% of whites lived in tracts that were less than 50% black, 81% of blacks lived in tracts that were at least 50% black. Although 21% of white borrowers appeared to live in black neighborhoods, close inspection of these cases revealed many to be investors who likely lived elsewhere (see Gilderbloom et al 2012). While rising gentrification partly fueled by the subprime mortgage boom may have integrated black and white households in resurgent cities such as Washington, DC, black-white segregation may have been exacerbated in cities such as Baltimore (Bond and Williams 2007; Fischer 2013; Friedman et al 2012; Friedman, Tsao, and Chen 2013; Hyra and Rugh forthcoming; Lichtenstein and Weber 2014).…”

“…Third, we quantify the serial displacement of capital experienced by African Americans in urban areas to move beyond simple ecological associations between residential segregation and socioeconomic disadvantage and demonstrate exactly how institutionalized discrimination widens economic disparities between individuals and neighborhoods on the basis of race (Kochhar, Fry, and Taylor 2011; Lipsitz and Oliver 2010; Molina 2012; Shapiro, Meschede, and Osoro 2013; Wolff 2012). Finally, we link previously discrete steps in the causal cycle of racial disinvestment by connecting the racial segmentation of mortgage capital in space (Ashton 2008; Crossney 2012; Fisher 2009; Hernández 2009; Wyly et al 2006, 2012) to individual disparities in high risk/high cost lending (Ashton 2008; Barr, Dokko, and Keys 2011; Bocian, Reid, Li, and Quercia 2011) and then link both to neighborhood disparities in predatory lending (Apgar and Calder 2005; Bunce et al 2002; Been, Ellen, and Madar 2009; Crossney 2012; Ding et al 2008; Gilderbloom et al 2012). …”

Blue City …RedCity? A Comparison of Competing Theories of Core County Outcomes in U.S. Presidential Elections, 2000–2012

“…It is possible that this effect is a fluke created by the interactions of the variables in the model or that it is capturing the effect of an omitted independent variable. Another possible explanation might be that this variable is in part capturing the presence of investor foreclosures-a driving force behind higher urban foreclosure rates (Gilderbloom, Ambrosius, Squires, Hanka, & Kenitzer, 2012).…”

Challenging conventional wisdom : section 8 housing and the real impact on neighborhood values in Louisville, Kentucky.

“…however, its moderate size and mid-western location make Louisville representative of the average US city (Gilderbloom, Ambrosius, Squires, Hanka, & Kenitzer, 2012;Savitch & Vogel, 2004).…”