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An exogenous expansion in mortgage credit has significant effects on house prices. This finding is established using US branching deregulations between 1994 and 2005 as instruments for credit. Credit increases for deregulated banks, but not in placebo samples. Such differential responses rule out demand-based explanations, and identify an exogenous credit supply shock. Because of geographic diversification, treated banks expand credit: housing demand increases, house prices rise, but to a lesser extent in areas with elastic housing supply, where the housing stock increases instead. In an instrumental variable sense, house prices are well explained by the credit expansion induced by deregulation.

Nonbanks originated about half of all mortgages in 2016, and 75 percent of the mortgages insured by the FHA and the VA. Both shares are much higher than those observed at any point in the 2000s. In this paper, we describe how nonbank mortgage companies are vulnerable to liquidity pressures in both their loan origination and servicing activities, and we document that this sector in the aggregate appears to have minimal resources to bring to bear in an adverse scenario. We show how the same liquidity issues unfolded during the financial crisis, leading to the failure of many nonbank companies, requests for government assistance, and harm to consumers. The high share of nonbank lenders in FHA and VA lending suggests that the government has significant exposure to the vulnerabilities of nonbank lenders, but this issue has received very little attention in the housing reform debate.

The imposition of federal conservatorships on September 6, 2008, at the Federal National Mortgage Association and the Federal Home Loan Mortgage Corporation—commonly known as Fannie Mae and Freddie Mac—was one of the most dramatic events of the financial crisis. These two government-sponsored enterprises play a central role in the US housing finance system, and at the start of their conservatorships held or guaranteed about $5.2 trillion of home mortgage debt. The two firms were often cited as shining examples of public-private partnerships—that is, the harnessing of private capital to advance the social goal of expanding homeownership. But in reality, the hybrid structures of Fannie Mae and Freddie Mac were destined to fail at some point, owing to their singular exposure to residential real estate and moral hazard incentives emanating from the implicit guarantee of their liabilities. We describe the financial distress experienced by the two firms, the events that led the federal government to take dramatic action in an effort to stabilize housing and financial markets, and the various resolution options available to US policymakers at the time; and we evaluate the success of the choice of conservatorship in terms of its effects on financial markets and financial stability, on mortgage supply, and on the financial position of the two firms themselves. Conservatorship achieved its key short-run goals of stabilizing mortgage markets and promoting financial stability during a period of extreme stress. However, conservatorship was intended to be a temporary fix, not a long-term solution, and more than six years later, Fannie Mae and Freddie Mac still remain in conservatorship.

This paper provides novel estimates of the interest rate elasticity of mortgage demand by measuring the degree of bunching in response to a discrete jump in interest rates at the conforming loan limit—the maximum loan size eligible for purchase by Fannie Mae and Freddie Mac. The estimates indicate that a 1 percentage point increase in the rate on a 30-year fixed-rate mortgage reduces first mortgage demand by between 2 and 3 percent. One-third of this response is driven by borrowers who take out second mortgages, which implies that total mortgage debt only declines by 1.5 to 2 percent.

I empirically analyze credit market outcomes when competing lenders are differentially informed about the expected return from making a loan. I study the residential mortgage market, where property developers often cooperate with vertically integrated mortgage lenders to offer financing to buyers of new homes. I show that these integrated lenders have superior information about the construction quality of individual homes and exploit this information to lend against higher quality collateral, decreasing foreclosures by up to 40%. To compensate for this adverse selection on collateral quality, nonintegrated lenders charge higher interest rates when competing against a better-informed integrated lender.

Purpose Policy issues associated with the regulation of the unlisted debenture market have been highlighted in recent times with the collapse of a number of regionally based mortgage companies. The purpose of this paper is to analyse the decline and demise of the unlisted debenture market between 2007-2013 with particular reference to the effectiveness of the regulatory regime in stabilising the industry and protecting investors’ interests. Design/methodology/approach A database was constructed which reflected the total population of unlisted mortgage companies in the financial sector. A snapshot approach was used to assess the extent to which these companies complied with regulatory provisions. Findings Findings suggest the regulatory process allowed these companies to continue operating despite not complying with the relevant Australian Securities and Investments Commission benchmarks. In the light of the current inquiry into the financial system, the research suggests that a re-evaluation of the regulatory approach is timely. Research limitations/implications This research is restricted to a study of one category of debenture issuers (issuers of mortgage finance). It is based on reports required by regulatory authorities. It does not provide an analysis of the motivations of investors in these companies. Practical/implications This research has implications for the implementation of regulatory change in respect to oversight of shadow banking activities. It suggested that a passive approach to regulation is not sufficient to ensure that the interests of investors are fully protected. Originality/value No prior research has systematically examined the unlisted mortgage and analysed the borrowing and lending activities of companies that have failed and those that have survived.

During the first half of 2020, the difference in savings from mortgage refinancing between high- and low-income borrowers was 10 times higher than before. This was the result of two factors: high-income borrowers increased their refinancing activity more than otherwise comparable low-income borrowers and, conditional on refinancing, they captured slightly larger improvements in interest rates. Refinancing inequality increases with the severity of the COVID-19 pandemic and is characterized by an underrepresentation of low-income borrowers in the pool of applications. We estimate a difference of $5 billion in savings between the top income quintile and the rest of the market.

Purpose The purpose of this paper is to examine the antecedents of customer satisfaction during mortgage purchases. Mortgage demand in the USA has reached an all-time high because of an increase in housing demand after COVID-19. Nonetheless, several customers are dissatisfied with their service providers. Customers who actively search the market gain more information about mortgage providers and use this information to define expectations for lenders. The only way there will be customer satisfaction is if lenders meet these expectations. Therefore, it is economically significant for mortgage lenders to discover the antecedents of mortgage satisfaction. Design/methodology/approach In this study, the partial least squares approach was used to test the hypothesis that satisfaction was influenced by objective knowledge, familiarity and search intensity among a sample of customers (n = 4,512) from the National Survey of Mortgage Originations who had purchased a mortgage in the USA between 2019 and 2020. Findings The results of structural modelling showed that familiarity (β = 0.23 and p = 0.01) with and knowledge (β = 0.16 and p = 0.01) of mortgages significantly affected consumer satisfaction during mortgage purchase. Search intensity (p = 0.01) mediated the relationship between knowledge, familiarity and satisfaction. Research limitations/implications The primary implication is that mortgage service providers should prioritise educating customers about the mortgage buying process on their websites and in person. So managers must actively assist clients in having realistic expectations. Second, mortgage companies should establish a presence on third-party mortgage comparison websites to ensure that customers actively consider alternatives, thereby increasing customer satisfaction. Originality/value This study is unique in being an exploratory study to examine the antecedents of mortgage satisfaction using a public data set. This study uniquely examines the National Survey of Mortgage Originations data set with partial least squares approach to examine underlying customer attitudes.

Mortgage data is often skewed, has missing information, and is contaminated by outliers. When mortgage companies or banks make prediction of note rates for new applicants, robust regression models are usually selected to deal with outliers. In this paper, we utilize deep neural network to predict the loan rate and compare its performance with three classical robust regression models. Two real mortgage data sets are used in this comparison. The results show that deep neural network has the best performance and therefore is recommended.