Race, redlining, and residential mortgage loan performance

By J. Berkovec, Glenn B. Canner, S. Gabriel, Timothy H. Hannan. 1994

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Citations in the corpus

Algorithmic Decision Making and the Cost of Fairness (2017, background): “These examples relate to the historical practice of red-lining , in which lending decisions were intentionally based only on coarse information—usually neighborhood—in order to deny loans to well-qualified minorities [11].”
Cartographies of Race and Class: Mapping the Class‐Monopoly Rents of American Subprime Mortgage Capital (2009, background): “Credit rationing is the dominant neoclassical explanation for the racial redlining and discrimination that plagued American cities for generations, through the 1980s (Stiglitz and Weiss, 1981; Vandell, 1984; Berkovec et al., 1994).”
A multidisciplinary survey on discrimination analysis (2013, methodology): “Berkovec et al. (1994) adopt a linear regression model on a data set of mortgages insured by the US Federal Housing Administration.”
Discrimination in the Credit and Housing Markets: Findings and Challenges (2006, background): “Berkovec et al. (1994), an especially influential study which uses a random sample of FHA loans originated in 1987 and 1988, finds higher minority default rates. Han (2004) uses the Berkovec et al data set and comes to the same empirical conclusion regarding minority default rates.”
Predictably Unequal? The Effects of Machine Learning on Credit Markets (2020, unknown): “In mortgages and housing, see, e.g., Berkovec et al. (1994, 1998), Ladd (1998), Ross and Yinger (2002), Ghent et al. (2014), and Bayer et al. (2017).”