1993
DOI: 10.1006/juec.1993.1014
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A Model of Redlining

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Cited by 135 publications
(76 citation statements)
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“…Lank and Nakamura [11,12] suggest that assessment risk may play an important role in explaining redlining. Property assessments may be inaccurate in neighborhoods with low loan volumes leading to lower willingness of lenders to approve mortgages in these neighborhoods.…”
Section: Discussionmentioning
confidence: 99%
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“…Lank and Nakamura [11,12] suggest that assessment risk may play an important role in explaining redlining. Property assessments may be inaccurate in neighborhoods with low loan volumes leading to lower willingness of lenders to approve mortgages in these neighborhoods.…”
Section: Discussionmentioning
confidence: 99%
“…12 Finally, the specification controls for detailed loan and borrower characteristics. The loan variables include whether a gift was provided for the downpayment, whether the loan was cosigned, whether the interest rate was adjustable, 13 and whether private mortgage insurance was obtained.…”
Section: Data and Model Specificationmentioning
confidence: 99%
“…In the urban literature, geographic redlining (see e.g. Ladd [11] and Lang and Nakamura [12]) involves di¤erentials in mortgage loan supply across neighborhoods or space. In other words, mortgage lenders discriminate on the basis of the location of the property so that people living in redlined areas …nd di¢culties in obtaining loans.…”
Section: Introductionmentioning
confidence: 99%
“…Relatively greater volatility in minority property prices arises from several sources, including relatively greater effects of the business cycle on labor income of minorities and disparities in the availability of mortgage credit and/or federal loan guarantees to low-income and minority borrowers (Grinstein-Weiss, Clinton, & Carrillo, 2015); a significantly higher rate of default arising from the concentration of alternative mortgage products and high LTV loans in minority neighborhoods (Brueckner, Calem, & Nakamura (2016); externalities on local home prices from the high incidence of default in such neighborhoods (Immergluck & Smith (2006); and cycles in the degree of appraisal bias toward properties in minority neighborhoods (Lang & Nakamura, 1993;Calem, Firestone, & Wachter, 2010).…”
mentioning
confidence: 99%