2014
DOI: 10.1016/j.regsciurbeco.2014.07.006
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Differences in subprime loan pricing across races and neighborhoods

Abstract: a b s t r a c t JEL classification: G21 J15 R23 C11We investigate whether race and ethnicity influenced subprime loan pricing during 2005, the peak of the subprime mortgage expansion. We combine loan-level data on the performance of non-prime securitized mortgages with individual-and neighborhood-level data on racial and ethnic characteristics for metropolitan areas in California and Florida. Using a model of rate determination that accounts for predicted loan performance, we evaluate the differences in subpri… Show more

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Cited by 88 publications
(41 citation statements)
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“…While HMDA data are publicly available, the HMDA data used here are restricted because it includes the actual loan number on which the data are merged together, not matched using the variables available in both datasets, as in other published journal articles (see Ghent et al. and Rugh ). Therefore, the data used here are the result of merging unrestricted, public data on loan performance with restricted, public data on borrower demographic information.…”
Section: Datamentioning
confidence: 99%
See 1 more Smart Citation
“…While HMDA data are publicly available, the HMDA data used here are restricted because it includes the actual loan number on which the data are merged together, not matched using the variables available in both datasets, as in other published journal articles (see Ghent et al. and Rugh ). Therefore, the data used here are the result of merging unrestricted, public data on loan performance with restricted, public data on borrower demographic information.…”
Section: Datamentioning
confidence: 99%
“…The CTS data were merged with HMDA data by the San Francisco Federal Reserve Bank using the following variables: loan number, origination date, loan amount, lien status (first or second), and loan purpose (purchase vs. refinancing). While HMDA data are publicly available, the HMDA data used here are restricted because it includes the actual loan number on which the data are merged together, not matched using the variables available in both datasets, as in other published journal articles (see Ghent et al 2014 andRugh 2015). Therefore, the data used here are the result of merging unrestricted, public data on loan performance with restricted, public data on borrower demographic information.…”
Section: Datamentioning
confidence: 99%
“…In our analysis, we focus on the initial contract interest rate rather than the APR or the margin for the ARM because there is little evidence that lenders price the default or prepayment risk of subprime ARMs using the reset rate (see Haughwout, Mayer and Tracy and Ghent, Hernández‐Murillo and Owyang for discussions of this issue). The reason lenders seem to price ARMs using the initial contract rate is that a large fraction of mortgages terminate before they reach the reset date (see, e.g ., Demyanyk ) such that the reset rate that the margin determines is largely a hypothetical interest rate.…”
Section: Datamentioning
confidence: 99%
“…For a review of the literature on race, redlining and mortgage lending, see Ross and Yinger (). More recent contributions to this literature include Haughwout, Mayer and Tracy () and Ghent, Hernández‐Murillo and Owyang ().…”
mentioning
confidence: 99%
“…There are substantial documented differences in lending outcomes between white and minority borrowers. Recent findings show outcome differences for minority borrowers in the form of higher delinquency rates and more foreclosures (Bayer, Ferreira, and Ross 2016a and Bhutta and Canner 2013), the price paid for credit (Ghent, Hernández-Murillo, andOwyang 2014 andRoss 2016b), and higher denial rates (Bhutta and Canner 2013). 1 These studies document the persistence of outcome differences even after conditioning on relevant factors that are typically not available in previous studies, most notably borrower credit scores.…”
Section: Introductionmentioning
confidence: 99%