Title: Information Externalities and Residential Mortgage Lending in the Hardest Hit Housing Market: The Case of Detroit
Abstract: AbstractThe flow of credit to the residential sector is a critical issue in the recovery of the housing market after the Great Recession. This study revisited the effect of the from previous transactions on lending decisions during the housing crisis in a hard-hit market of the Detroit metropolitan area. The results of the study suggest that the lack of previous mortgage-financed sales and the concentration of foreclosures in a neighborhood present significant challenges for the access to credit for many mortgage applicants in Detroit. The significant effect of information externality is primarily relevant to the conventional mortgage market and the effect has a relatively low threshold: when the number of mortgage purchases is five or fewer in the previous year, the odds of denial increase 32 percent. More than 30 percent of the neighborhoods in the Detroit metropolitan area have been adversely affected by the lack of accurate information on neighborhood home sales prices. Results from this case study shed light on the systematic process of property valuation and mortgage underwriting during the recent housing crisis.IntroductionTo help explain the disparity observed in residential mortgage lending across neighborhoods, Lang and Nakamura (L-N) (1993) suggest that the level of housing market sales represents an for future lending decisions in the corresponding neighborhood. According to the L-N theory, market activities measured by total loan volume reduce the uncertainty associated with the appraised value of a property and thus affect future loan decisions. A sufficient volume of market sales aids in price discovery, which provides more certainty about home values, enables lenders to distinguish observable risks, and leads to an increased supply of loans. By contrast, an insufficient number of mortgage originations could lead to greater uncertainty in house price appraisals, and as a result mortgage seekers are more likely to be denied because the homes' value cannot be determined accurately. Moreover, because the home sales pricing information generated by a particular lender is publically disclosed and all lenders benefit from it, individual lenders have little incentive to help facilitate loan transactions and gain a better understanding of market values. In other words, the market failure because of information externality could lead to equilibrium with suboptimal lending.In the aftermath of the Great Recession, information externality is an important topic to examine in the residential mortgage market. Two information issues have become evident in many markets. First, many transactions have been sales of distressed properties, which may not provide suitable information for the valuation of a more normal market transaction. The preponderance of distressed home sales in certain neighborhoods may lead valuation estimates to be biased downward when they are used as comparable properties without appropriate adjustments. Second, transaction volume has been low for a variety of reasons. The lack of market sales, especially mortgage-financed home sales, may lead to high degrees of uncertainty in appraisals. Lenders may require a larger downpayment because of the uncertainty in the appraisal to ensure that borrowers have a sizeable equity stake. And when borrowers are unable or unwilling to come up with extra payment, lenders may deny the loan. If loans are not originated, transactions may not occur, and the true value of properties will not be determined. Since the Great Recession, no known research has examined how previous transactions influence future lending decisions through information externalities.This study focuses on one of the hardest hit housing markets in the nation-the Detroit metropolitan area (hereafter, Detroit).2 Having experienced a collapse in its housing sector, Detroit provides a unique opportunity for this empirical study. …
Publication Year: 2014
Publication Date: 2014-01-01
Language: en
Type: article
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Cited By Count: 13
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