The Impact of Second Loans on Subprime Mortgage Defaults

An estimated 12.6% of primary mortgage loans were simultaneously originated with a second loan from 2004 until 2008, although relatively little is known about how the presence of such subordinate loans affects the default decisions of borrowers. We use a novel data series of loan servicing records from 2002 until 2010 to identify such borrowers and find evidence that the default behavior of these borrowers significantly differs from borrowers without second loans. Estimating a discrete‐time proportional odds hazard model, we find borrowers with a second loan were 62.7% more likely to default each month on their primary loan when conditioning alone on the attributes of the primary loan. However, borrowers of second loans were 58.3% less likely to default on their primary loan as compared to single‐loan borrowers with equivalent current combined attributes (i.e., loan‐to‐value, balance and interest rate). We hypothesize and provide empirical evidence that this occurs because borrowers with second loans have the option to sequentially default on each loan since subordinate lenders will not pursue foreclosure if borrowers have insufficient equity. Lenders of defaulted subordinate debt may revisit their decision to foreclose in the future after housing markets start to recover, thus prompting a new round of foreclosures.     

Mortgage Lending Discrimination and the Decision to Apply: A Methodological Note

Previous studies of lenders' decisions to accept or reject loan applications have not accounted for the possibility that lenders discourage written applications from members of protected classes, i.e., prescreening. This paper discusses how prescreening and self-selection may bias the measurement of discrimination. Estimation techniques are developed that test and correct for such bias whether or not information is available on non-applicants.     

Mortgage Lending, Sample Selection and Default

Traditional models of mortgage default suffer from sample-selection bias because they do not control for the loan approval process. This paper estimates a sample-selection-corrected default model using the 1990 Boston Federal Reserve loan application sample and the 1992 Federal Housing Authority (FHA) foreclosure sample. A single-equation FHA default model appears to suffer from substantial selection bias, but the bias primarily arises from the omission of credit history and other variables that are only in the application sample. Therefore, default models that contain detailed information on applicants may not suffer from substantial selection bias. Finally, a test for prejudice-based discrimination is developed and conducted, but the findings are inconclusive.     

Self-Selection and Discrimination in Credit Markets

In this article we make two contributions toward a better understanding of the causes and consequences of discrimination in credit markets. First, we develop an explicit theoretical model of loan underwriting in which lenders use a simple Bayesian updating process to evaluate applicant creditworthiness. Using a signal correlated with an applicant's true creditworthiness and their prior beliefs about the distribution of credit risk in the applicant pool, lenders are able to evaluate an applicant's expected or "inferred" creditworthiness to determine which loans to approve and which to deny. Second, we explicitly model the self-selection behavior of individuals. Because these decisions shape lenders' prior beliefs about the distribution of credit risk, they also affect the Bayesian posterior from which lenders compute an applicant's inferred creditworthiness, implying that statistical discrimination can arise endogenously. As an example, we show that in a market in which only some lenders have Beckerian tastes for discrimination there are conditions under which lenders without racial animus will also discriminate. Our model's flexibility makes it ideal for analyzing a wide variety of empirical and policy questions.     

Search Cost and Price Dispersion in Vertically Related Markets: The Case of Bank Loans and Deposits

Using data on marginal interest rates of loan and deposit products by Spanish banks, we find that the level of interest rates on loans (deposits) across geographic markets decrease (increase) with the number of banks in each market, and that the level of interest rates on loans increases with the level of interest rates of deposits. We also find that the dispersion of interest rates of both loans and deposits increase with the number of banks. This evidence is interpreted as evidence of customer’s search costs in retail banking, consistent with predictions from the Carlson and McAfee (J Polit Econ 91:480–493, 1983) model of market competition with search costs.     

Does Local Competition Impact Interest Rates Charged on Small Business Loans? Empirical Evidence from Canada

Using a unique survey database of Canadian small business loans,we find a negative and statistically significant relation between the number of localcompetitors and small business loan rates. This result is robust to the presence of a wide varietyof covariates intended to proxy the effects of both loan specific details and individualcharacteristics. These findings further suggest that the local markets definition applied to small businessloans is still relevant, despite recent technological innovation such as internet banking.     

A Model of the Asset Disposition Decision of the RTC

The purpose of this paper is to develop a model of the asset disposition decision for the Resolution Trust Corporation (RTC). In this paper, we focus on the primary goal of the RTC—to maximize the net present value of the cash flows generated through holding and selling the assets it acquires. A major decision it faces is whether to hold or sell assets. This decision ultimately depends on the RTC's discount rate versus that of the marginal buyer. A second question relates to the decision of which assets to sell first and which ones to delay sale. The model developed in this paper characterizes the asset disposition decision process of the RTC for different types of assets. We develop a set of optimal disposition rules based on the simple premise of a multi-period cash flow maximization. In addition, we test some of these rules by analyzing RTC disposition performance. Through this exercise, we hope to provide some guidance to the RTC in implementing its enormous task as well as to policy makers in charting the progress of the RTC. The main results of this analysis indicate that liquid assets and retail deposit franchises should be sold as quickly as possible. Illiquid assets that are performing and do not have high servicing costs are good candidates to finance through senior/subordinated securities or sale with seller financing by the RTC. Illiquid non-performing assets are good candidates for equity participation financing by the RTC. The sales proceeds obtained by the RTC will be increased if buyers have greater certainty with respect to expected cash flows and RTC sales policies.     

大连市小额担保贷款模式的探索

小额担保贷款主要是根据国家有关促进就业政策,针对符合贷款条件的创业人员在自谋职业、自主创业或合伙经营与组织起来就业过程中面临的资金困难,由各级政府设立小额贷款担保基金,经指定担保机构承诺担保,通过银行发放并由政府给予一定贴息扶持的政策性贷款。本文通过探索政策性小额担保贷款模式,促进大连市小额担保贷款工作有序进行,以创业带动就业,有利于发挥创业的就业倍增效应,调动劳动者创业的积极性和主动性,同时也为劳动密集型小企业扩大生产、增加就业岗位创造条件,对缓解就业压力具有重要的现实意义。     

Recourse as shadow equity: Evidence from commercial real estate loans

We study the role that recourse plays in the commercial real estate loan contracts of the largest U.S. banks. We find that recourse is valued by lenders as a substitute for conventional equity. At origination, recourse loans have rate spreads that are about 20 basis points lower and loan-to-value ratios that are almost 3 percentage points higher than nonrecourse loans. Dynamically, recourse affects loan modification negotiations by providing additional bargaining power to the lender. Recourse loans were half as likely to receive accommodation during the COVID-19 pandemic, and the modifications that did occur entailed a relatively smaller reduction in payments.     

Evaluation of USDA's Broadband Loan Program: Impacts on broadband provision

Since 2002 the USDA's Broadband Loan Program has directed more than $1.8 billion in subsidized loans to help expand broadband access in under-served rural communities. Program eligibility criteria included having a population of 20,000 or fewer, having no prior access to broadband, and providing a minimum matching contribution of 15% by recipients of the loan. Loans were extended mainly to small telecommunications services firms at varying (subsidized) interest rates. We evaluate on the effectiveness of the Loan Program in increasing broadband availability in target locations. Specifically, we analyze whether loan receipt increases the number of broadband providers in a particular location, using various count panel methods. Our analysis is conducted at the ZIP code level over the period 1999–2008; it uses broadband provider data from the FCC's Form 477, and loan data from the Rural Utility Service (the implementing agency for the Broadband Loan Program). Results indicate that ZIP codes receiving broadband loans did in fact experience modest, statistically significant increases in the number of broadband providers vis-à-vis non-recipient locations; that average marginal effects on treated ZIP codes were approximately 0.092 additional broadband providers annually; and that these benefits accrued more towards rural locations than urban locations, in conformance with the intent of the program.     

Spatial Price Discrimination with Heterogeneous Firms

In this paper we aim to explain intuitively heterogeneous firms’ optimal location decisions in a simple spatial market. To do so, we present and solve a four‐stage game of entry, location, pricing and consumption in a spatial price discrimination framework with arbitrarily many heterogeneous firms. We provide a unique equilibrium outcome without imposing restrictions on the distribution of marginal costs across firms.     

Explaining Refinancing Decisions Using Microdata

This paper develops a model which explains how mortgage-rate movements, transactions costs, changes in borrower income and house value, personal financial opportunities and the prepayment option embedded in fixed-rate mortgages affect a financially flexible borrower's decision to refinance an existing loan while retaining the underlying home. Broadening the focus of previous analytical work, the model explains why households with similar mortgage loans may react differently as financial market conditions change. It contains definitive empirical predictions that are supported by an analysis of a choice-based sample of individual loan transactions. Results suggest that refinancings are motivated both by movements in the level of interest rates and by borrowers' desires to alter their capital structures in the face of changing income and housing wealth.     

The Impact of Homeowners' Housing Wealth Misestimation on Consumption and Saving Decisions

Using a unique data set of 81,943 house value estimates by the homeowners and their financial institution, I find that homeowners overestimate their house value by 3.1%. After controlling for homeowners' socioeconomic characteristics, I find that ex ante homeowners who rate (cash-out) refinance an existing loan to increase savings (consumption) are significantly more likely to underestimate (overestimate) their house value. Moreover, overestimators (underestimators) are more likely to increase (reduce) their spending ex post . Finally, I also find that underestimators are more likely to prepay their loans and overestimators are more likely to default on their loans.     

Green Buildings in Commercial Mortgage‐Backed Securities: The Effects of LEED and Energy Star Certification on Default Risk and Loan Terms

We study the impact of green building on loans in the CMBS market. A hazard model shows green buildings carry 34% less default risk, all else equal. A matched‐sample analysis gives similar results. We attribute the effect to a loan‐to‐value channel, where risk is lowered by a green price premium. The benefit comes at least partly from the level of green achievement, not only the label itself. Loans on buildings that were green at loan origination have slightly better terms than loans on nongreen buildings. That difference is growing over time, but the effect is economically small compared to default risk.     

Lender Steering in Residential Mortgage Markets

In this article, we examine the incentives for lenders to steer borrowers into piggyback loan structures to circumvent regulations requiring primary mortgage insurance (PMI) for loans with loan‐to‐value ratios (LTV) above 80%. Our empirical analysis focuses on propensity score‐matched portfolios of piggyback and single‐lien loans having the same combined LTV based on a full set of observed risk characteristics. Our results confirm that mortgages originated with the piggyback structure have much lower ex post default rates and faster prepayment speeds than corresponding PMI loans. We also find a significant causal effect of interstate banking deregulation on the growth of piggybacks in these years, confirming that the ex post performance gap is primarily driven by lender steering on the supply side and not by borrower self‐selection. We then perform a number of tests to explore different origination and execution channels of mortgage steering.     

The Influence of Fannie and Freddie on Mortgage Loan Terms

This article uses a novel instrumental variables approach to quantify the effect that government‐sponsored enterprise (GSE) purchase eligibility had on equilibrium mortgage loan terms in the period from 2003 to 2007. The technique is designed to eliminate sources of bias that may have affected previous studies. GSE eligibility appears to have lowered interest rates by about ten basis points, encouraged fixed‐rate loans over ARMs and discouraged low documentation and brokered loans. There is no measurable effect on loan performance or on the prevalence of certain types of “exotic” mortgages. The overall picture suggests that GSE purchases had only a modest impact on loan terms during this period.     

Lenders’ pricing strategy: Do neighborhood risks matter?

This article explores the different pricing strategies of lenders who originate both government-sponsored enterprise (GSE) and non-GSE loans. We find that conditional on loan and borrower characteristics and some observable local economic factors, mortgage rates on GSE loans vary significantly across regions. However, we observe no sizable regional variation in loan amounts or default risk. By contrast, the mortgage rates on non-GSE loans depend almost entirely on borrowers and loan characteristics. In addition, we find that spatial variations in GSE mortgage rates are highly responsive to regional prepayment risk. Our results are robust to various controls for neighborhood characteristics, including regional-level bank competition, borrower accessibility to mortgages, and household income levels. Overall, the findings offer a novel insight into how lenders adjust pricing strategies in response to a changing lending environment. The results provide implications relating to the present and imminent dangers of housing bubbles and the intensified refinancing wave following the COVID-19 pandemic.     

A Note on Equivalent Fixed Rate and Variable Rate Loans; Borrower's Perspective

A common situation is where a borrower is offered the choice of two types of loans—a fixed interest rate loan for a fixed period or a variable interest (floating interest) rate loan. Usual wisdom and advice is that the borrower opts for the fixed rate loan if interest rates are anticipated to rise in the future or opts for the variable rate loan if interest rates are anticipated to fall. However, depending on the magnitude of the rates offered, and the rate uncertainty in the market, such wisdom may not always be well founded. This note demonstrates why this might be. It derives a readily usable, low-mathematical-background expression showing, for borrowers, when fixed and variable rate loans are equivalent and when one rate type is better/worse than the other.     

Analysis, ranking and selection of R&D projects in a portfolio

A method for the analysis, ranking and selection of R&D projects from a portfolio is outlined and demonstrated. It is proposed that an objective multi-criteria decision making method, Data Envelopment Analysis (DEA), be used to split a portfolio of projects into accept, consider further and reject sub-groups. Next, the 'consider further' group is examined using a subjective method, the Value Creation Model. Such an approach allows for obvious decisions to be automated and complex decisions to be given careful consideration, an approach that is more consistent with how practising managers actually make select/reject decisions. DEA allows for comparison of variables without requiring weights or conversion factors. The relation between research strategy and consideration of categorical data is considered in relation to the research portfolio of the Advanced Technology Division of Bell Laboratories.     

Mortgage Default and Prepayment Risks among Moderate‐ and Low‐Income Households

Using a unique sample of community reinvestment loans, we study the propensity of very low‐income households to terminate a mortgage and compare it to the outcomes for low‐income and moderate‐income households. The results indicate that, even within moderate‐ and low‐income segments, lower or very low income is associated with higher default and lower prepayment probabilities. In addition, depending on how low the borrower's income is, classic determinants of loan termination such as credit scores, the amount of equity in the home and local labor market conditions can have different impacts on default and prepayment probabilities.