Tag Archives: shadow inventory

Economic Factors That Affect Housing Prices

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photo by TaxRebate.org.uk

S&P has posted a paper on Economic Factors That Affect Housing Prices. This is, of course, an important topic, albeit one that is an art as well as a science. While S&P undertook this analysis more for mortgage-backed securities investors than for anyone else, it certainly is of use to the rest of us. The paper opens,

The U.S. domestic housing market has experienced a 23% price increase since the beginning of the housing recovery in 2011. Many local housing markets are now close to or above their peak levels of 2006, which leads us to investigate whether the pace of home price appreciation (HPA) can continue at its current pace. In this paper, we (1) examine the economic factors that influence HPA and (2) forecast HPA for numerous geographic regions assuming various economic conditions over the next five years. While the aggregate national pattern in housing prices is an important reference, we need to examine housing prices at a more granular geographic level in order to understand regional housing market dynamics and learn how these are affected by local macroeconomic factors. This paper demonstrates that several economic variables are needed to predict average home price movements for each of 48 different U.S. metropolitan statistical areas (MSAs).

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Factors that influence HPA can be difficult to predict. Therefore, residential mortgage backed securities (RMBS) investors frequently use a range of HPA projections to estimate their potential bond returns. With that in mind, for each MSA, we considered five separate hypothetical economic scenarios, ranging from an “Upside” forecast to an extreme “Stress 3” case. Interestingly, our Stress 3 case forecasts a 28% decline in HPI at the national level over the next five years, which corresponds roughly to the decline experienced in the last recession. Our “base case” scenario leads to forecasts at the national level of a 26% increase in HPI over five years. This represents what we believe to be the most likely economic forecast. (1-2)

S&P’s key findings include:

  • Movement in HPA is primarily influenced by up to five variables, depending on the MSA: housing affordability, changes in shadow inventory, the unemployment rate, the TED spread [a measure of distress in the credit markets], and population growth.
  • HPA in many MSAs has momentum, meaning that it depends on its level in the previous quarter of observation.
  • The mortgage rate generally appears to have little predictive power in connection with home prices.
  • Chicago, Houston, Boston, and San Francisco are projected to appreciate at a greater pace (45%, 40%, 27%, and 36%, respectively) than the 26% forecast for the nation as a whole over the next five years, and New York at a slower pace (21%). Columbus led all MSAs with a projected five-year HPA of 50%.
  • Under our most pessimistic (Stress 3) scenario, Chicago is forecast to experience a greater decline in HPI (34%) over the next five years than the nation as a whole (29%), while New York, Boston, Houston, and San Francisco are projected to experience declines that are less severe than that of the nation (19%, 3%, 17%, and 16%, respectively). Markets that have been vulnerable in the past (Las Vegas, Phoenix, and Riverside) are projected to experience the greatest five-year declines under our Stress 3 scenario (66%, 68%, and 68%). The markets that show the greatest movements are the most sensitive to the five factors and frequently show the greatest upside and downside. (2-3, emphasis in the original)

I found the first and third bullet points to be the most interesting, as many pundits weigh in on the factors that affect housing prices. It will be interesting to see if further research confirms S&P’s findings.

Shadowed by the Shadow Inventory

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My former colleague at Seton Hall, Linda Fisher, has posted Shadowed by the Shadow Inventory:  A Newark, New Jersey Case Study of Stalled Foreclosures & Their Consequences on SSRN. The paper presents the findings of a small, but interesting empirical study.  The study “tests the extent to which bank stalling has contributed to foreclosure delays and property vacancies in” one neighborhood in  Newark, New Jersey. (6) Fisher states that this “is the first study to trace the disposition of each property in the sample through both public and private sources, allowing highly accurate conclusions to be drawn.” (6)

Fisher reaches “a similar conclusion to the previous studies with respect to stalling: without legal excuse or ongoing workout efforts, banks frequently cease prosecuting foreclosures.” (7) Fisher also finds that the stalled foreclosures in her study “do not strongly correlate with property vacancies.”(7)  Fisher claims that her findings “are generalizable to similar urban areas in judicial foreclosure states,” but I would like to have seen more support for that claim in the paper. (45)

As a side note, I found her description of foreclosure in New Jersey interesting:

The New Jersey foreclosure system provides a representative example of a judicial foreclosure regime, albeit one with heightened procedural protections for borrowers enacted into the state’s Fair Foreclosure Act. For instance, lenders must file a notice of intention to foreclose containing information about, inter  alia, the lender, servicer and amount required to cure, before filing a foreclosure complaint in court. Once borrowers are served with process, they may file a contesting answer and litigate the matter, as with any civil case. Because ninety-­‐four percent of New Jersey foreclosures in a typical year are not contested, the process is largely administrative and handled through a statewide Office of Foreclosure. Court personnel scrutinize bank evidence in support of default judgments. Borrowers may file late answers, and are responsible only for curing arrears and paying foreclosure fees up until the time of judgment. (14-15, emphasis added, citations omitted)

Because this blog has as one of its main focuses downstream litigation judicial opinions, it is important to remember how few cases actually reach a court room, let alone result in a written opinion by a judge.