What is Giving Compass?
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Giving Compass' Take:
• The Great Recession highlighted underlying regulatory issues within the mortgage system. Better understanding these problems can help us avert future crises.
• What goals should regulation seek to achieve? How can competing interests be reconciled?
• Learn more about the liquidity crisis in the mortgage market in the 2000s.
The recent U.S. housing boom saw an unprecedented increase in household mortgage debt. This buildup of mortgage debt, held by vulnerable households, has been party attributed as having importantly contributed to the severity of aftermath. However, the characteristics of borrowers and loans originated prior to the crisis is not the only key factor that affected the severity of the housing downturn during the Great Recession. A series of papers have argued that a number of factors related to rigidity of contract terms, as well as a variety of frictions in design of the mortgage market and the intermediation sector hindered efforts to restructure or refinance household debt, exacerbating the foreclosure crisis.
In response, the central bank altered its monetary policy by lowering interest rates to historic lows. Also, the administration passed two unprecedented large-scale debt relief programs: the Home Affordable Refinancing Program (HARP), aimed to stimulate mortgage refinancing activity of up to eight million heavily indebted borrowers and the Home Affordable Modification Program (HAMP), aimed to stimulate mortgage restructuring effort for up to four million borrowers at risk of foreclosure. Research suggests that the implementation of the low-interest rate policy and these debt relief programs had mixed success.
What can we learn from extant research on the potential design of mortgages and more effective debt relief efforts in the future?
Our discussion highlights an important trade-off that warrants more comprehensive analysis. The indexed mortgage contracts have the advantage of circumventing financial intermediary and other fictions by facilitating a quick (“automatic”) implementation of debt relief during economic downturns. However, for such contracts to be cost-effective, lenders, policymakers, and borrowers may need a good “ex-ante” understanding of the underlying distribution of risk and its relation to indices being used when designing and choosing such contracts.
Given the evidence of significant time-varying regionally heterogeneity, this can be challenging. Moreover, our simple framework illustrates that error in beliefs about the structure of risk can reduce the benefits of such solutions. Given the vast heterogeneity in nature of risk across space and time, such errors are likely, especially as a major change in the nature of mortgage contracts or housing policy can on its own significantly alter relationships between market equilibrium outcomes in potentially hard to quantify way. As a result, one may have to rely on an ex-post debt relief solutions as well.
More broadly, our evidence suggests that effective mortgage design approach to debt relief requires more in-depth analysis of the nature of relevant income and housing risk and its evolution across regions and borrowers. This could include the development of new and sufficiently granular indices on which such contracts could be based. The recent “big-data” revolution is promising in this regard. Such analysis could also identify mortgage designs that effectively implement debt relief across a range of possible environments. Finally, the approach relying on public debt relief programs should focus on alleviating frictions that may hinder the effective implementation of such policies. This should also include development of effective and “easy to verify” set of eligibility criteria regarding debt relief policies.