The Best Way to Forecast Real Estate Demand

    The problem with using old metrics based on the past is that the housing market was severely distorted in a way that is impossible for economists to deconstruct and reverse engineer so as to correctly predict future housing prices. The problem was that from 1984 to 2009 “Easy Qualifier” mortgages aka “Liar’s Loans” were offered by banks and this allowed a significant number of people to get homes they should not have been able to buy. Thus the data during that era is not useable for forecasting because Easy Qualifier loans are no longer allowed.

      To fix this corrupted data economists would need to get the power of subpoena and get hold of a large random sample of old loan applications and then somehow get the IRS to release the borrowers’ tax returns and compare that to the incorrect income data on the loan application. This won’t happen because the IRS won’t release the data and because economists have no legal standing in court to go on a fishing expedition and subpoena old financial documents. So the amount of excessive lending that was facilitated by Easy Qualifier loans is unknowable. Then, even if this was known, the next problem an economist would face is that it is impossible to assess the impact when a group of rouge bidders are allowed into a crowded auction room. Will the rouge borrowers make prices go up in proportion to the number of rouge borrowers or will prices increase geometrically in a panic? For example if 80 people with money go into a crowded auction room and then 20 additional buyers get in who were not qualified to bid then this extra group of people could create a bidding war and push prices far higher than if the rouge group had been kept out of the marketplace auction room. By rouge buyers I mean those who got a loan that was more than they should have gotten because they used an Easy Qualifier loan to exaggerate their income.

    The most important thing in lending and in investment valuation is the income analysis, so when lenders offered Easy Qualifiers they ruined the most important part of the loan process. Thus trying to compare home sales prices during the Easy Qualifier era to today is very difficult.

   Anecdotal evidence suggests that lenders kept the worst excesses of Easy Qualifiers in check until 1997, after which time home prices exploded. By coincidence the real inflation adjusted personal income in the U.S. has been stagnant since 1998. Since homes bought by the bottom 99% of the population (unless a buyer is retired) are financed with a loan which is supposed to be qualified by income then it seems that home prices should be close to the 1997 (inflation adjusted) level to be fairly priced. This is because the last known era before Easy Qualifiers became extreme was in 1997 and from 1990-1997 prices dipped and then recovered thus 1997 was a time when prices could be deemed to be reasonable. Any appreciation since 1997 should be roughly in line with CPI of roughly 2% annually, so prices today should be only about 1.33 times 1997 prices.

     I have seen a chart showing inflation adjusted home prices shows we are getting close to the 1997 real price level but still need to go down a little more. For a century on a “real” basis houses don’t go up faster than CPI.


   Housing bulls say that there is a lot of pent up demand for housing and that the existing stock of housing is getting old. However “demand” must include the ability to buy something. Because many people are trapped in careers with stagnant or declining wages they can’t afford to buy a home that cost more than what they now own. Many young people are saddled with huge student loans, more so than in previous eras. Most importantly a large number of potential buyers can’t qualify for a loan because Easy Qualifiers are not available, except in rare and very high interest rate B paper loans. Thus the alleged “demand” for housing based on household formation or the need to move to a nicer property is not real. All the starving people in South Sudan want to buy a Mercedes and fill their grocery cart at Safeway but they can’t afford to, so that type of demand is not true demand. Another example of a misunderstanding about demand is population growth. Most of it is with moderate to lower income people, while the upper middle class continue to have only one or no children per family. But moderate income people are suffering from a decline in “real” wages and excessive unemployment, so they are less able to participate in buying a house than upper middle class professionals with “new economy” skills.

    The key mistake investors make is to look at high water marks in asset prices as a target for something that is going to repeat. That is an incorrect reference point, because a high water mark from a previous bubble could have been a false data point generated by a bubble, or a buying panic or it was caused by false perceptions about an investment. A more reliable benchmark is to use the income method of lending, which in real estate for homes owned by the bottom 99% is ultimately based on the earned income of the general population. The bottom 50% to 90% of the population has been stuck in a rut of no real personal income growth since 1998. So that means they can’t engage in a bidding war to buy a home even if there is the appearance of demand in the form of more household formation or a greater desire to move to a house in better condition.

   The qualitative nature of earned income has degraded over the past 30 years. In the old days people got a base salary and that was it. Now people may earn a living as an independent contractor but due to fluctuations in income their income is shaky and thus it is too risky for the bank to loan money to them. This problem was fixed with the use of Easy Qualifiers but since 2009 these loans have not been available so many potential borrows can’t qualify. The shaky nature of their income means that they really should not be allowed to buy; the bank is doing them a favor to decline their loan request. The real problem is that personal income is more volatile and less reliable than 30 years ago so people are actually poorer than they think. It is like the Sharpe ratio for investments. When an investment is extremely volatile then on a risk adjusted basis it really was not that profitable, according to the Sharpe ratio.  The increasingly less reliable nature of U.S. residents’ personal income means that (when using the income method of lending) less people qualify for a loan, which has been exacerbated by the end of “Easy Qualifier” lending.

    Another inhibitor of demand is that the public needs to spend the next several years deleveraging by paying down debt. This means the public needs to either avoid buying a more expensive home or may even need to downsize and buy a less costly home.

Some exceptions apply

   The exception to this article would be the upper middle class neighborhoods in coastal California where there is pent up demand where some people with excess liquid assets could use liquid assets to buy a more expensive home and where the desire to move into a Mediterranean climate is so great that people from all over the world are interested in moving to coastal California. A rough guess is that the desirable affluent areas with a Mediterranean climate are only about 3% of the U.S. housing stock, so this area is not reflective of the rest of the country. Another exception would be for the top 1% of the population who often live off of passive investments which have gone up due to the phony stock market bubble caused by the Fed’s Quantitative Easing. These people were hurt the least by the development of the “new economy” and have plenty of liquid assets so that they can buy a home without a mortgage.

Most of the recent appreciation in homes recently was concentrated in the top 5% of home prices with the rest showing much more modest gains.

Investors need independent financial advice about the risk of hidden bubbles caused by looking at assets instead of income data.


About the author

Don Martin, CFP®

Leave a Reply

Your email address will not be published.

You may use these HTML tags and attributes: <a href="" title=""> <abbr title=""> <acronym title=""> <b> <blockquote cite=""> <cite> <code> <del datetime=""> <em> <i> <q cite=""> <s> <strike> <strong>

Copyright 2014   About Us   Contact Us   Our Advisors       Login