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Weekly UpdatesHistorical trends in foreclosure activity are a function of both prevailing underwriting quality and economic conditions. This look back at foreclosures from 1979 through the present reveals how economic conditions and underwriting quality were about equally responsible for the spike in defaults from 2005 onward. A move away from fully documented loans was a key factor in the portion of defaults due to underwriting during that spike.
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For lenders, investors and regulators, an important risk-management exercise is to understand possible worst-case scenarios. A worst-case scenario enables decision-makers to quantify the downside risk and prepare mitigation strategies if prudent. * Decision-makers can monitor the indicators (for example, house prices), determine ways to limit the worst risks and maybe even know when they are seeing the light at the end of the tunnel. * In this article, we will consider historical trends in mortgage foreclosures and house price values, and link those particular trends to trends in the economic environment--including local economic conditions at time of origination and developments in underwriting quality. * All of these factors can shed light on how the current crisis developed, and help us understand our worst-case scenario.
Are the worst quality-adjusted vintages behind us?
Each quarter, University Financial Associates LLC (UFA) calculates its Default Risk Index, which tracks the impact of local and national economic conditions on expected life-of-loan mortgage defaults by vintage. By holding borrower credit and loan terms constant, the index is able to isolate the effects of local and national economic conditions from the myriad other variables that affect loan performance.
The Default Risk Index is one of the simulations that UFA runs to help risk managers understand future economic risks. A simulation is a model of real economic conditions, in which key measures of the economic environment, such as gross domestic product (GDP), unemployment or house prices, are treated as variables whose interaction can be expressed in mathematical equations. With these tools, an economist can model what might occur if GDP growth falls to -5 percent, or if unemployment climbs to 15 percent in a given time period. Hypothetical numbers for GDP or unemployment are the input for the equation, and predictions--such as house prices or mortgage default levels--are the output. In a worst-case scenario, economists estimate what values the variables might reach if everything were to go wrong with the economy. A baseline scenario is business-as-usual; the variables are given values close to trends.
In UFA's worst-case scenario, GDP will decline 5 percent for two years, followed by two more years of positive 1 percent growth before returning to trend growth. The worst-case scenario is much worse than any of the post-war recessions, but far better than the 1930s.
In such a worst-case scenario, the UFA Default Risk Index peaks at 376 in first-quarter 2009, while in the baseline scenario it peaks in fourth-quarter 2008 at 279 (see Figure 1). The index reading represents a comparison with the average of the 1990s (1990s = 100). For the worst vintage, first-quarter 2009, it is estimating the worst-case risk of default on newly originated nonprime mortgages at 2.76 times higher than the average of the 1990s. Compare this number for the baseline scenario, which peaks one quarter earlier at 2.79 times higher than the 1990s average. The index is telling us that the loans originated in fourth-quarter 2008 and first-quarter 2009 are likely to default at the highest rates after controlling for other risk factors such as loan-to-value (LTV) ratio and credit scores. In either scenario, the worst vintages are already behind us, in fourth-quarter 2008 and first-quarter 2009. This is an important result of our scenario experiment. It means that very likely we have already seen the worst economic environment for originating loans that this credit cycle has in store for us.
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To understand the UFA Risk Index and the worst-case scenario results in a broader context, let us turn to an examination of trends in loan performance, collateral performance, economic conditions, underwriting quality and the relationships among these factors.
The long-run trend in foreclosures
Figure 2 shows the foreclosures started as a percent of outstanding number of loans from 1979 through 2008. There is a rising trend with an occasional leveling off. Between 1979 and 2002, foreclosure rates quadrupled, going from 0.48 percent to 1.96 percent annually. In an impressive surge from 2006 to 2008, foreclosure rates more than doubled again, jumping from 1.88 percent to 4.32 percent.
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Figure 2 includes a linear trend line. The actual rate of foreclosures rises above the trend line just after the recessions of 1981-1982, 1990-1991 and 2001. During the intervals of economic expansion, the rate dips below the trend line.
This evidence highlights the role of national and local economic conditions in the rate of foreclosures, which we discuss in more detail later. To the extent that increases in foreclosure rates are recession-induced, the spike from 2006 onward points to a very severe recession.
The trend in house prices
Modern theories of mortgage valuation treat the borrower's financial position in the mortgage contract as analogous to that of a buyer of a put option on a stock, where the house is the underlying asset instead of the stock. Like a put option, the buyer has the right, but not the obligation, to default and surrender the underlying asset (the house) at an agreed-upon price (the loan balance) within a specified time period (the mortgage term). One implication of this approach is that the put option should be sensitive to the value of the collateral.
When collateral prices are rising, a financially stressed borrower with equity will rationally choose to sell his or her house rather than default. Correspondingly, when house prices are falling and equity becomes negative, stressed borrowers are more likely to rationally choose default. Therefore, it is important to understand both collateral prices and financial stress as they relate to foreclosures.
Figure 3 plots real and nominal house prices since 1975. There is a cyclical pattern to real house prices from 1975 to 1997 within a narrow range. However, during the boom years from 1997 to 2007, real house prices rose about 40 percent above what had been the long-run level until that time.
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Such steep increases should be expected to greatly reduce the need for stressed borrowers to default. Because many lenders develop underwriting models by evaluating recent loan performance data, looking back only two to three years, any underwriting models created using data from this boom period would underestimate the risks to lenders in more average times.
Separating underwriting from economic conditions
Figures 2 and 3 highlight the historical effects of economic conditions on foreclosures. One of the goals of our recent research has been to decompose the rate of foreclosures started in the national serviced portfolio, as reported by the Mortgage Bankers Association (MBA), into an underwriting component (both observable and unobservable) and a component arising from economic conditions.
For a detailed technical discussion of how we separated the effects of economic conditions from the effects of underwriting quality in the data, and how we fitted the forward-looking (predictive) Default Risk Index to the backward-looking (reported) rates of foreclosure in the MBA data, see the May 2009 research paper co-authored with Charles Anderson, Deconstructing a Mortgage Meltdown: A Methodology for Decomposing Underwriting Quality, pages 12-17, available at www.ufanet.com.
Figure 4 presents results of our data analysis for all loans. In Figure 4, one can see that defaults due to underwriting (i.e., of default rates after controlling for economic conditions) went up as defaults due to local economic conditions went down; in other words, a strong economy was covering for poor underwriting quality.
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The estimated variations by prime and subprime tell a similar story. For this story we focus on "All" foreclosures started, which have the longest time series and deepest data.
The line labeled "Actual Defaults" in Figure 4 gives actual foreclosures started relative to the 1999 baseline. The line labeled "Local Economics" identifies the part played by economic conditions (how foreclosures would have moved had underwriting not changed), which promoted declining foreclosures until 2004. And the line labeled "Underwriting" shows the contribution of underwriting quality to foreclosures started (or how foreclosures would have changed had economic conditions not changed). The contribution of underwriting quality was positive (more defaults) early in the period, negative later and sharply positive in 2006 to 2007.
For example, in 2004 the line labeled "Underwriting" shows the curve for underwriting is 1 while actual defaults are 0.25 and the economic conditions index is -0.75. This means that while actual default rates rose 25 percent from 1990 to 2004, if economic conditions had not been so favorable, foreclosures started would have risen by 100 percent instead of 25 percent. Underwriting quality eroded enough to double the level of foreclosures started by 2004; but only a 25 percent increase was realized because favorable economic conditions offset three-fourths of the potential increase. During this period, house prices appreciated steadily in most of the country.
The recessions of the early 1990s and of 2001-2002, when unemployment was rising, are visible in the line showing local economic conditions curves of Figure 4, but they are dominated by the other very favorable economic effects such as rising house prices. Both recessions were accompanied by brief periods when underwriting standards tightened, as reflected by declines in the line showing underwriting curves, confirming that lenders do respond to recent loan performance by adjusting underwriting standards.
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