Tag Archives: forecast

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.

Homeowner Nation or Renter Nation?

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Andreas Praefcke

Arthur Acolin, Laurie Goodman and Susan Wachter have posted a forthcoming Cityscape article to SSRN, A Renter or Homeowner Nation? The abstract reads,

This article performs an exercise in which we identify the potential impact of key drivers of home ownership rates on home ownership outcomes by 2050. We take no position on whether these key determinants in fact will come about. Rather we perform an exercise in which we test for their impact. We demonstrate the result of shifts in three key drivers for home ownership forecasts: demographics (projected from the census), credit conditions (reflected in the fast and slow scenarios), and rents and housing cost increases (based on California). Our base case average scenario forecasts a decrease in home ownership to 57.9 percent by 2050, but alternate simulations show that it is possible for the home ownership rate to decline from current levels of around 64 percent to around 50 percent by 2050, 20 percentage points less than at its peak in 2004. Projected declines in home ownership are about equally due to demographic shifts, continuation of recent credit conditions, and potential rent and house price increases over the long term. The current and post WW II normal of two out of three households owning may also be in our future: if credit conditions improve, if (as we move to a majority-minority nation) minorities’ economic endowments move toward replicating those of majority households, and if recent rent growth relative to income stabilizes.

This article performs a very helpful exercise to help understand the importance of the homeownership rate.  This article continues some of the earlier work of the authors (here, for instance). I had thought that that earlier paper should have given give more consideration to how we should think about the socially optimal homeownership rate. Clearly, a higher rate, like the all-time high of 69% that we had right before the financial crisis, is not always better. But just as clearly, the projected low of 50% seems way too low, given long term trends. But that leaves a lot of room in between.

This article presents a model which can help us think about the socially optimal rate instead of just bemoaning a drop from the all-time high. It states that

Equilibrium in the housing market is reached when the marginal household is indifferent between owning and renting, requiring the cost of obtaining housing services through either tenure to be equal. In addition, for households, the decision to own or rent is affected by household characteristics and, importantly, expected mobility, because moving and transaction costs are higher for owners than for renters.  Borrowing constraints also affect tenure outcomes if they delay or prevent access to homeownership. (4-5)

This short article does not answer all of the questions we have about the homeownership rate, but it does answer some of them. For those of us trying to understand how federal homeownership policy should be designed, it undertakes a very useful exercise indeed.

Exotic Mortgage Increase

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DepositAccounts.com quoted me in 10 Things You Might See From Your Bank in 2016. It reads, in part,

It’s that time of year when experts pull out the crystal ball and start talking about “what they see”. Banking pros are no exception. When it comes to 2016, they expect plenty; change is on the horizon. Here’s a look at some of them.

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4. Exotic mortgages increase

David Reiss, a professor at Brooklyn Law School, specializing in real estate believes that banks are going to get more comfortable with originating more exotic mortgages as they have more experience with the mortgage lending rules that were prescribed in Dodd-Frank. These rules, such as the Qualified Mortgage Rule and Ability To Repay Rule, encourages lenders to make “plain vanilla” mortgages. But there are opportunities to expand non-Qualified Mortgages, so “2016 may be the year where it really takes off,” says Reiss. The bottom line? “This means consumers who have been rejected for plain vanilla mortgages, may be able to get a non-traditional mortgage. This is a two-edge[d] sword. Access to credit is great, but consumers will need to ensure that the credit they get is sustainable credit that they can manage year in, year out.”