Future House Prices – Part 1

Future House Prices

For all our wisdom and collective experience, none of us knows what the markets will do next. Like an ocean current or a raging river, a financial market charts its own course. It is fickle and feckless and flows without regard to our hopes and dreams. The ebbs and flows of financial markets are meaningful to us, but in reality they are just movements in price; nothing more. Price rallies make homeowners blissful and renters bitter, while price declines make homeowners gloomy and renters gleeful. These feelings and emotions are independent of movements in price. The market just moves, that is all it does. It is benign, yet dangerous; it is indifferent, yet demonstrative; the market is a paradox which we must simply accept.

During the rally of the Great Housing Bubble, buyers did not concern themselves with the day they were going to become sellers. Why would they? There was an endless demand for properties, and buyers were paying whatever was asked. If they wanted a price above current market values to pay off a loan, all they had to do was wait. Once the bubble burst and home prices started to decline, the conditions people were accustomed to during the rally dramatically changed. Anyone considering buying a home in the aftermath of a crash should think about the buyer who is going to buy their home from them at some point in the future, and more specifically, what debt-to-income ratio and loan terms this future buyer will utilize. This is important, because the amount of money this take-out buyer will pay for the home is completely dependent upon these variables. At most, a house is only worth what a buyer can pay for it. In a declining market with few qualified buyers, many of those qualified buyers will only make offers if the deal is exceptional or simply wait for further price declines.

In a market environment where prices are detached from fundamental valuations, bubble buyers face a daunting challenge just to break even on their purchase when the time comes to sell it. A future buyer must have favorable borrowing terms allowing for a high degree of leverage or they may not be able to borrow the prodigious sums borrowers during the bubble rally were able to obtain. If a future buyer is not able to borrow as much with their income as bubble buyers, then wages must increase over time to permit future borrowers to borrow the same sum and allow a bubble buyer to avoid a loss. Unfortunately, it will take many years for wages to catch up to bubble prices. Even when this occurs, and a seller can recover their purchase price, inflation will have diminished the value of those dollars. If the prices are adjusted for inflation, many bubble buyers will never see an inflation adjusted breakeven price.

How Far to Fall

This book was written as the market crash was just beginning, and although there was already significant history to discuss, the price levels where the markets ultimately found stability had not yet been reached. The remainder of this chapter is a projection of what should happen if the residential real estate market responds as history would suggest. There will undoubtedly be unexpected twists and turns that impact the various variables influencing housing prices, and changes to these variables will change the timing and the depth of the crash. The projections and discussion which follows is based on first a return to historic norms and finally a look at what could happen if the crashing market causes an “overshoot” of fundamental valuations as often occurs in the collapse of a financial bubble.

All methods of predicting future price action rely on the same basic premise: prices are tethered to some fundamental value, and although prices may deviate from this value for extended periods of time, prices eventually return to fundamental valuations. This premise has been reinforced by market observation; in fact, many estimates of fundamental value are based on market action. Since many market participants believe in buying and selling based on fundamental values, there is also an element of self-fulfilling prophecy contained therein. The efficient markets theory is based on this idea, and although the behavioral finance theory is needed to explain the wide deviations from fundamentals real-world prices exhibit, both theories share the same notion of an underlying fundamental valuation on which prices are ultimately based. The challenge to market prognosticators is to select a fundamental valuation to which prices will return, and then extrapolate a period of time in which the return of prices to fundamental valuation will take place.

There are a number of ways to project how far and how fast prices will fall. One is to look at the price charts themselves and try to project reasonable trend lines to approximate bottoming valuations. This is not an accurate methodology as it is based on the assumption of a repetition of past performance without examining the reasons for this past performance; however, it does serve as a useful rough estimate. A more accurate and detailed method is to examine the variables that determine market pricing and see how changes in these variables impact resale values. This process involves assessing current fundamental values to make a statement as to where prices should be–and would have been if there had not been a residential real estate bubble–then estimating how long it will take for these variables to return to their historic norms. Also, there are a number of exogenous forces that act on market pricing in an indirect manner. These include debt-to-income ratios, availability of credit and changes in loan terms, mortgage interest rates, unemployment rates, foreclosure rates, home ownership rates, possible government intervention in the markets, and other factors. These forces do not directly impact house prices as changes in these variables do not have strong correlation with house prices; however, these variables can and do impact the variables that do correspond with house prices, therefore an evaluation is provided of the role these factors play in market pricing.

The timing of the decline is the most difficult parameter to evaluate and estimate. [1] House prices are notoriously “sticky” during price declines because sellers are loath to sell at a loss. The timing of a decline is impacted both by psychological and technical factors. The motivations of sellers based on their personal circumstances and emotional states will determine if there is a heightened sense of urgency to sell which would push prices down quickly. During the price correction of the coastal bubble of the early 90s, prices declined very slowly as unmotivated sellers held on and waited for prices to come back. The market experienced denial and fear, but there was not a stage of capitulatory selling that drove prices down quickly as is typical in the deflation of a speculative bubble. The primary technical factor impacting the rate of price decline is the presence of foreclosures and real estate owned (REO). REOs are a form of must-sell inventory (as are new homes). If there is more inventory of the must-sell variety than the market can absorb, prices are pushed lower. The more of this must-sell inventory there is on the market, the faster prices decline. If the pattern of the early 90s is repeated, the price decline of the Great Housing Bubble may drag out slowly while fundamentals catch up to market pricing. In fact, this is probably what will occur on the national market unless the foreclosure numbers and resultant REOs overwhelm market buyers. In the extreme bubble markets like Irvine, California, the combination of high foreclosure rates and general market panic will likely push prices lower much more quickly. [ii] Even though the percentage decline in house prices is projected to be double the decline witnessed in the coastal bubble of the early 90s, the duration of the decline may be similar as capitulatory selling pushes prices lower at a faster rate.

Price Action

Most market participants focus on price action. The price-to-price feedback mechanism largely responsible for bubble market behavior gathers its strength from an awareness of market pricing, and the widespread belief that short-term, past price performance is predictive of long-term, future price performance. It is a fallacy that is often reinforced in the short-term as irrational exuberance takes over in a market, but over the long term, short-term price movements rarely correspond to long-term price trends, and when they do, it is only by chance.

Predicting future prices based on price action is based on the premise that long-term price trends are reflective of fundamental valuations because they represent the collective wisdom of the market. As with all methods of predicting pricing, deviations from the long-term fundamental valuation almost always result in a return to this value. The weakness in this theory is in its failure to provide a causal mechanism. To note that prices return to long-term valuations without postulating why prices do this provides no mechanism for estimating when prices will return to fundamental value, and it provides no way to determine if there is a significant change to the market’s valuation to establish whether or not prices will return at all. In short, past price action itself is very limited in its ability to predict future price action. Despite the shortcomings of the methodology, predictions based on past price performance are widely used and often woefully inaccurate.

Figure 36: National Projections from Historic Appreciation Rates, 1984-2012

From 1984 through 1998, national house prices appreciated at a rate of 4.5%. There is a strong correlation between this rate of price increase and observed market prices. There is only one deviation from this rate of appreciation during the period. The effect of the coastal bubble of the late 1980s on national prices creates a small rise from the historic appreciation rate and a sideways drift of prices until values resume their 4.5% annual rise. Since prices consistently match this rate of appreciation, and since prices deviate once from this rate in a prior price bubble and return to it, there is a compelling argument that prices will drop to this level of long-term appreciation and begin rising again. If this proves to be true, national home prices will decline 10% from the peak, bottom in 2009, and return to the peak by 2011. This is the market’s best-case scenario.

Figure 37: Irvine, CA, Projections from Historic Appreciation Rates, 1984-2026

The story for the most inflated markets such as Irvine, California, is much the same as the national forecast. If the 4.4% rate of appreciation seen from 1984-1998 is repeated, then prices will decline 45% from the peak, bottom in 2011 and return to the peak in 2023. Since prices peaked in 2006, this method of price projection shows an 18 year peak-to-peak waiting time: not a comforting forecast for Irvine homeowners.

Figure 38: Growth in Income and House Prices, 1981-2006

The key assumption in this analysis is that market prices will resume the rate of appreciation seen from 1984 to 1998. This rate of house price appreciation is 1.4% above the rate of inflation, 1.2% above the rate of wage growth, and 0.7% above the very long-term rate of house price appreciation. House appreciation cannot exceed wage growth forever: trees cannot grow to the sky. People have to earn money to buy a home (unless of course we become a nation of the landed gentry in which real estate is only transferred through inheritance). Over the last 25 years, house appreciation in Orange County has outpaced wage growth. Wage growth has averaged 3.4% while house price appreciation has averaged 6.9%. The coastal bubble years (1986-1989) where house prices outpaced income growth were followed by bust years (1990-1995) where wage growth made modest recoveries.

House prices outpaced wage growth for two reasons: first, debt-to-income ratios rose as people put higher percentages of their income toward making payments; second, interest rates declined allowing people to finance larger sums with less money. Much of the reason house prices appreciated at a rate in excess of its normal relationship to inflation is due to the gradual decline of interest rates during the period. As interest rates decline, the amount people can borrow increases. If people can borrow more, they can bid prices higher. House prices appreciated at a rate greater than its long-term average due to declining interest rates. If interest rates stop declining (which is likely), or if interest rates begin a cycle of long-term incline, the rate of house price appreciation will be impacted negatively; the drop of prices from the deflating bubble will be deeper, and the date of ultimate price recovery will be much later.

Figure 39: Declining Interest Rates, 1984-2006

The median sales price measures the general price levels at which buyers are active in the market, but it does not reflect the quality of what is purchased and it does not reflect the price changes of individual properties. The S&P/Case-Shiller indices measure price changes in individual properties through its use of repeat sales in calculation of the index. Market participants are primarily concerned with how their property is changing in price rather than some aggregate measure of the market. The S&P/Case-Shiller index is the best market measure for approximating the price change on individual properties.

Figure 40: National Projections based on S&P/Case-Shiller Indices

It is more difficult to use an aggregate appreciation rate on the S&P/Case-Shiller indices because there is no single period where a particular average correlates well with market pricing, plus small changes in the rate of appreciation can make large differences in where the bottom is found. There are two issues to be addressed with any projection of appreciation when there is low correlation to the data: the starting point, and the rate of increase. The S&P/Case-Shiller indices did not start collecting data until 1987, but this date is arbitrary. The most recent market low was in 1984, and by 1987, there was some detachment from fundamental valuations. The point of origin for the projection of appreciation may more appropriately be below the first data point in 1987; however, to simplify the analysis, the 1987 data point was used as the origin. The 3.3% rate used in the projections was the historic rate of wage growth from 1987 to 2006. Since people finance house purchases with payments made from wages, this is a reasonable rate to use. Another method that can be used is to assume the very long-term rate of appreciation of 0.7% over inflation. The question then is what rate of inflation should be used. The average rate of inflation from 1987 to 2007 has been just over 3%, but inflation rates have been much higher and more volatile prior to this time. So an argument can be made that 3.7% is a more appropriate number. If this rate is used with the lower origin point to allow for the small degree of house price inflation already evident in 1987, the two support curves differ slightly, but the difference between the two is not significant to the outcome.

Figure 41: Los Angeles Projections based on S&P/Case-Shiller Indices

Based on projections from S&P/Case-Shiller indices using a 3.3% rate of wage growth as a support level, prices of individual properties will decline 27% from their peak valuations in 2006, finding a bottom in 2011 and reaching the previous peak in 2025. This is arguably the market prediction of most concern to homeowners that purchased during the bubble because it reflects the price change of individual properties like theirs. There is very little comfort in the thought of a 27% decline and a 19 year waiting period until prices regain their previous peak.

The degree of detachment from fundamental valuations in the extreme bubble markets like those in California is truly remarkable, and the decline in house prices will be as unprecedented as the rally that preceded it. Based on projections from S&P/Case-Shiller indices using a 3.3% rate of wage growth as a support level, prices of individual properties will decline 53% from their peak valuations in 2006, finding a bottom in 2011 and reaching the previous peak in 2033. Twenty-Eight years is a long time to wait for peak buyers to get their money back.

Price-to-Rent Ratio

Comparative rent is the primary method of evaluating the fundamental value of any property. The price-to-rent ratio links the cost of ownership with the cost of rental. This link is direct because possession of property can be obtained by either method. The cost of ownership encapsulates all of the financing terms and other variables associated with possession of real estate as does the cost of rental. Price-to-rent ratio fluctuates over time as changes in the cost of ownership and terms of financing makes financing amounts vary and house prices vary as well.

Figure 42: Projected National Price-to-Rent Ratio, 1988-2021

Figure 43: National Projections based on Price-to-Rent Ratio, 1988-2021

One of the major components of any projection using price-to-rent ratios is the projection of future rents. On a national level rents have been rising at a 3.6% rate from 1988 to 2007. [iii] This is 0.6% greater than the rate of inflation and 0.3% greater than the rate of wage growth. In Orange County, California, rents have been rising at the rate of 4.7% from 1983 to 2007. This is 1.7% greater than the rate of inflation and 1.3% greater than the rate of wage growth. Any difference between the rate of rental growth and the rate of wage growth cannot be sustained forever; however, the differential on the national level is small, and it can be attributed to changing customer behavior as people demonstrate an increased willingness to spend more on housing related costs. The rate of rent growth over wage growth in Orange County is a bit more troubling. Orange County is second only to Honolulu, Hawaii as the most expensive place to rent in the United States and the continued growth of rents in excess of wages is not sustainable.

The unprecedented spike in the national price-to-rent ratio is clear evidence of a massive, national real estate bubble. As the ratio demonstrates, there was no increase in rents justifying market pricing. The only other explanation which would deny a market bubble would be a dramatic lowering of ownership costs through other means. Although lower interest rates did lower ownership costs somewhat, the resulting savings due to lower interest rates only explains about one-third to one-half of the increase in prices. The remainder is caused by the use of exotic financing and irrational exuberance. Predictions based on the price-to-rent ratio are arguably the most robust because the ratio has been stable over long periods of time, and for good reason; the comparative cost of ownership to rental is a logical basis for valuation. If house prices return to their historic average of the 1988 to 2004 period of 181, then national prices will fall 27% peak-to-trough, bottom in 2011 and return to the peak in 2020.

Figure 44: Projected Orange County, CA Price-to-Rent Ratio, 1983-2020

The ratio of price-to-rent in Orange County, California, where the city of Irvine is located, has shown more variability than national figures. There was a coastal bubble taking off in the late 80s and collapsing in the early 1990s. The premise of prices reverting to fundamental valuations can be clearly seen in the changes in the price-to-rent ratio in Orange County. In the mid 1980s, the market was bottoming out from the first coastal residential real estate bubble associated with the inflationary times of the late 1970s. From 1983 to 1987, the price-to-rent ratio stabilized between 176 and 185, a range of about 6%. After the coastal bubble, prices stabilized in 1994 to 1996 in a range from 175 to 178. Projections using the price-to-rent ratio assume prices will fall again to the range from 175 to 185 before stabilizing. The reason prices stabilize in this range is because it is here that the cost of ownership approximates the cost of rental, and Rent Savers buy real estate and form a support bottom. If house prices in Orange County return to their historic price-to-rent stability range, prices will fall 22% peak-to-trough, bottom in 2013, and return to the previous peak by 2019; however, if rental increases do not sustain their 4.7% historic rate, the bottom may be somewhat lower, and the return to the previous peak would be delayed.

Figure 45: Orange County Projections based on Price-to-Rent Ratio, 1988-2020

[1] Since real estate is associated with high transaction costs, heterogeneity and illiquidity, there is little opportunity for arbitrage (Black, Fraser, & Hoesli, 2006) (An investor cannot sell a house short.) These factors cause house prices to correct slowly without large numbers of foreclosures.

[ii] Large variations in regional markets suggests the markets will deteriorate at different rates and at different times. (Baker D. , 2002) The extreme bubble markets of the coasts will deteriorate the most, and they may deteriorate the fastest due to the profusion of exotic financing.

[iii] Rental data is from U.S. Department of Labor Bureau of Labor Statistics.