Corporate finance analysis: hypothesis and case study examination

¶ … mortgage default (Elul, Souleles and Chomsisenghept). This model suggests that home owners should only ever default if they have negative equity in their residence. If there is negative equity, then there would be an incentive for the borrower to walk away from the property. However this also does not consider subsidiary effects such as the impact upon the person's credit or the possibility that the property could regain equity in the medium or long-term. Furthermore, other researchers have also proposed that other factors such as being illiquid would also provide a motive for someone to default on their mortgage. A combination of these two variables would also act to amplify the incentive to voluntarily default; and of course being so illiquid that there is no possibility to make a mortgage payment virtually guarantees that a default will occur.

Although this research paper does not necessarily define its hypothesis directly, it can be inferred that the authors are not quite content with the option model. Even though there is no economic incentive for borrowers to walk away from a property if it has equity, there are other variables that can also have an impact on this decision. Furthermore, it should also be noted that not all mortgage holders necessarily act rationally. Therefore, there could theoretically be decisions to default upon a mortgage based upon emotional or psychological criteria. However, these factors are difficult to study and this article seems to attempting to broaden the model for default beyond that of the comprehensiveness of the option model.

Data, Model and Statistical Tests

The purpose of this paper is to access the relative importance of two factors associated with mortgage defaults; negative equity and liquidity. To gather mortgage data, the researchers focused on loans that originated during the years of 2005 and 2006. Since these loans were originated shortly before the real estate bubble exploded, these two years are the most likely to produce a sample of individuals with negative equity. The exact figures for these mortgages are supplied from Lender Processing Services (LPS). However, supplementary data is also generated from the individual's credit report which was consequently supplied by Equifax. This allowed the researchers the ability to construct a more accurate picture of the total amount owed; especially when a second mortgage existed. Furthermore, to find the current (estimated) value of the home, the researchers used the estimated value of the home during origination and then multiplied this figure by the overall trend in the local market given the price index.

For an individual's liquidity data, the researchers had to construct a proxy for the liquidity values. They chose to use the figures from the credit bureau to determine the utilization levels of their unsecured credit since it was previously shown that individuals with high utilization are often liquidity strained. From this data set the researchers compiled a baseline default rate that separated the variables. The dummy variable was the dependent variable and represented a threshold in which mortgages go into default (60+ days). The independent variables included standard mortgage and borrower characteristics from the LPS dataset. Other variables included the county's unemployment rate and the change in the local house price index which were used to determine a shock value and the amount of equity respectively.

Results and Conclusions

The major results include that the researchers found that both illiquidity and negative equity are both statistically and economically significantly correlated with mortgage default and both variables were also monotonic in their function characteristics. The study also compares high utilization of unsecured credit lines with the total negative equity in a property and finds that the two variables high significant effect when the ratio of loan to value is higher. Unemployment was found to high little effect when there was a relatively low ratio (below 50). However, when the loan to value ratio increased then unemployment had a rather dramatic effect upon the default rate. Furthermore, the study also compared the presence of a second mortgage and its effects upon the default rate. When the loan to value ratio was low (below 50) then the second mortgage had little impact. However, when it was higher it had a substantial impact, similar to the impact unemployment had.

The major contribution to the field that this paper makes is that it widens the lens of what factors can contribute to a mortgage default. Previous models merely made provisions for negative equity as well as some other related factors such as the cost to move and some proxy for reputation costs. However, the effects of illiquidity in this study were found to be nearly on par with the negative equity variable. Therefore these two factors should be further researched to verify this trend. Furthermore, it is also important because of potential policy initiatives. For example, if illiquidity is one of the driving forces then in some cases it might be more beneficial to lower monthly payments than to focus on the total equity amount.

Analysis

The research article takes a significant step towards delineating the variables that represent individual's motivations for defaulting on a property. However, this seems to be only a first step and there is undoubtedly much work to be done in this field before it can provide an accurate account of the default environment. The model will undoubtedly have to be further developed to become more comprehensive. That being said, just adding a liquidity variable to the negative equity model was actually a pretty large step in the right direction.