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Article Excerpt
Conventional wisdom in the mortgage industry holds that loan-to-value (LTV) ratios are positively correlated with mortgage default rates. However, not all empirical studies of mortgage loan performance support this view. This paper offers a theoretical signaling model of why the correlation between LTV ratios and default risk is contingent upon the default costs of the borrower. Specifically, the model proposes that when default costs are high there exists a separating equilibrium in which risky borrowers will self-select into lower LTV loans to reduce the probability of facing a costly default, while safe borrowers will self-select into higher LTV loans as a signal of their enhanced creditworthiness. This adverse selection process gives rise to the possibility of higher default probabilities for lower LTV loans. Conversely, when default costs are low the conventional result, in which risky borrowers select higher LTV loans than safe borrowers, is obtained. Empirical results, based on a sample of 859 single-family residential mortgage loans drawn from the portfolio of a national mortgage lender, are consistent with the separating equilibria predicted by the model.
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Do risky borrowers borrow more? Specifically, does the loan-to-value (LTV) ratio choice of a borrower serve as a signal of that borrower's risk type? (1) The answer to this question is crucial to the mortgage lending industry as it would better enable lenders to screen risky borrowers from safe borrowers and price the default risk of each loan contract correctly.
Mortgage underwriters and academicians have conventionally subscribed to the view that loan-to-value ratios positively influence default rates. The argument usually made is the following: The greater the financial leverage (i.e., the higher the LTV ratio), the greater the debt service requirement, and hence the higher the probability the borrower will ultimately encounter financial distress. Theoretical signaling models, such as those presented by Rothschild and Stiglitz (1976) or Brueckner (2000), lend credibility to this paradigm, while a number of empirical studies, such as Von Furstenberg (1969) or Deng, Quigley and Van Order (2000), provide evidence consistent with the proposition.
Interestingly, however, not all empirical evidence supports this view of the world. Nearly 20 years ago, Campbell and Dietrich (1983) first reported the apparently counterintuitive finding that mortgage loans characterized by high LTV ratios at origination actually exhibit lower default rates over time compared to their low LTV counterparts. They conclude that the pattern of coefficients on the original loan-to-value dummy variables in their model is consistent with the presence of adverse selection in the underwriting process, particularly with respect to mortgages with original LTV ratios below 85%. Recent studies from multifamily and commercial mortgage markets also fail to document any positive relationship between LTV and borrower risk. For example, Archer et al. (1999, 2002) investigate pools of mortgage loans securitized by the Resolution Trust Corporation (RTC) for the Federal Deposit Insurance Corporation (FDIC) during the early to mid-1990s and find no significant relationship between LTV ratios at origination and ultimate loan performance (i.e., the probability of default). Similarly, Ambrose and Sanders (2001) find a lack of significance for LTV in their commercial mortgage performance investigation, and they argue this is entirely consistent with lenders using a compensatory model of credit evaluation, where risky borrowers upon any given dimension are held to more stringent standards along alternative dimensions.
The purpose of the current investigation is to bridge the gap between conventional wisdom and the seemingly counterintuitive empirical results which fail to consistently document a relationship between financial leverage and mortgage loan performance. Specifically, this paper offers both a theoretical explanation and empirical evidence to reconcile the apparently conflicting results with respect to the correlation between LTV ratios and default risk. The theoretical signaling model offered in this paper examines default under asymmetric information and demonstrates that the correlation between LTV ratios and default risk depends on the default costs of the borrower. Specifically, when default costs are high there exists a separating equilibrium in which safe borrowers self-select higher loan-to-value ratios than risky borrowers. This adverse selection problem gives rise to the possibility of a higher default probability for loans with lower LTV ratios. When default costs are low the conventional result, in which safe borrowers self-select lower LTV ratios than risky borrowers, is obtained. This theoretical conclusion is supported by an empirical analysis that distinguishes between borrowers with high default costs and those with low default costs. Our results should be particularly relevant to commercial mortgage market participants, as these lenders do not have access to systematically consistent and reliable default risk indicators such as credit (FICO) scores. (2)
The remainder of this paper is organized as follows. We first provide a brief overview of the existing literature on signaling models and determinants of mortgage default. Then, we present a simple screening model of LTV choice and default. Next, we outline the data used in our analysis and present the empirical results of our investigation. Finally, we summarize the results and offer insight into future research avenues in this area.
Previous Literature
Given the importance of discerning default risk in the multitrillion dollar mortgage industry, it is not surprising that a rich theoretical and empirical literature has emerged on pricing this risk and determining the factors that contribute to a borrower's decision to default. The most relevant theoretical study for the current paper is Brueckner (2000), which addresses the signaling role of a borrower's loan-to-value ratio choice with respect to that borrower's default risk. In Brueckner's model, default occurs when the value of the asset plus the borrower's default cost falls below the loan balance. Risky borrowers are defined as those who have lower default costs, and thus are more likely to exercise the default option. Similar to the result of Rothschild and Stiglitz (1976), the unique equilibrium in Brueckner is a separating equilibrium in which risky borrowers obtain a larger loan than safe borrowers. This is in contrast to the equilibrium results of the current paper where risky borrowers may obtain a larger or smaller loan depending on the default costs. The difference is due to the fact that the current investigation analyzes an alternative source of default, one in which default is triggered by a sufficient decline in the borrower's future income and risky borrowers are defined as those with a higher probability of a decline in future income.
The work of Leland and Pyle (1977), which examines the problem of a firm investing in a project and the market portfolio, is also relevant to the current investigation. Under their framework, the objective of the firm is to maximize the value of the project and market portfolio. In their model, there are no default costs and the risk level of the project is known to the firm but not to lenders and investors in the market. The authors show that the firm's willingness to invest in its own project serves as a signal of the project quality. In equilibrium, firms with safer projects will invest more in their own project, and they will be able to borrow more. The current model differs from that proposed by Leland and Pyle in a number of ways. First, Leland and Pyle present a signaling model in which the informed party (firm) moves first and makes an equity investment in the project. The current model is a screening model in which the uninformed party (the lender) moves first and offers a menu of mortgage contracts. Second, the total amount the borrower needs to raise in the current model is fixed by the purchase price of the asset. Thus, a higher down payment means a smaller loan, not a larger one. As mentioned earlier, the current model also shows that default costs are critical in that different default costs lead to different equilibrium outcomes. Therefore, the equilibrium offered by Leland and Pyle is only one of the three equilibrium outcomes of the current model.
In addition to the loan-to-value ratio, the existing literature identifies an array of other risk factors that lenders might utilize to screen risky borrowers from safe borrowers. For example, in Titman (1992) firms have private information about their production efficiency. He shows that, under certain parameter conditions, "good risk" firms choose short-term financing while "bad risk" firms choose long-term financing. Similarly, Guedes and Thompson (1995) offer empirical evidence for a signaling model where firms issue either fixed- or adjustable-rate debt to finance a project and obtain support for a separating equilibrium where high-quality firms issue high-default-risk debt and low-quality firms issue low-default-risk debt. (3) Milde and Riley (1988) use a production economy to show that a firm with a less risky investment project may choose larger or smaller debt financing depending upon the firm's production function.
Another line of research studies the prepayment risk of the borrower (e.g., Dunn and Spatt 1988) and analyzes such instruments as ARMs (Brueckner 1992, Rosenthal and Zorn 1993, Posey and Yavas 1999), coupon rates and points on FRMs (Yang 1992, Brueckner 1994a, LeRoy 1996, Stanton and Wallace 1998), and prepayment penalties and due-on-sale clauses (Dunn and Spatt 1985, Chari and Jagannathan 1989) to separate high-prepayment-risk and low-prepayment-risk borrowers.
Although the setup and focus are different, it is also worth mentioning that there is a considerable literature on both the relationship between the borrower's risk type and his/her choice of a collateral requirement under asymmetric information (e.g., Barro 1976, Wette 1983, Bester 1985, Chan and Kanatas 1985, Besanko and Thakor 1987, Mester 1994), as well as the determinants of mortgage demand (e.g., Brueckner 1994b, Follain and Dunsky 1996, Ling and McGill 1998). (4)
With the exception of the studies discussed earlier (Campbell and Dietrich 1983, Archer et al....
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