Price Decline Influences

There are a number of factors that will influence the timing and the depth of the price decline. There are a number of psychological factors and technical factors in play. [1] These include:

• Smaller Debt-to-Income Ratios
• Increasing Interest Rates and Tightening Credit
• Higher Unemployment
• Foreclosures
• Decrease in Ownership Rates
• Government Intervention

Smaller debt-to-income ratios impact the market because buyers tend to put a smaller percentage of income toward housing payments during price declines. Increasing interest rates decrease the amount borrowers can finance and use to bid on real estate, and tightening credit decreases the size of the borrower pool and thereby lowers demand. A deteriorating economy and higher rates of unemployment means there are fewer buyers with the income to purchase homes, and more homeowners are put in financial distress. High rates of financial distress caused by unemployment or the resetting of adjustable rate mortgages in a higher interest rate environment leads to more foreclosures. Large numbers of foreclosures adds to market inventories and works to push prices lower. The ultimate unknown factor is the meddling of the US Government in the financial markets. A bailout program for homeowners or lenders could radically alter the course of price movement.

Debt-to-Income Ratios

The debt-to-income ratio is a measure of how far buyers are “stretching” to buy real estate. Buyers have historically committed larger sums to purchase real estate when prices are rising in order to capture the appreciation of rising prices. Conversely, buyers have historically committed smaller and smaller percentages of their income toward buying real estate when prices are declining because there is little incentive to overpay. Some may look at this phenomenon as a passive effect of the rise and fall of prices, but since buying is a choice, the fluctuation in debt-to-income ratios is an active force on prices in the market.

Figure 55: National Mortgage Obligation Ratio, 1980-2007

This change in buyer behavior based on the trend in house prices is apparent in the national mortgage origination ratio. This statistic kept by the Federal Reserve Board is a measure of the total national mortgage debt service as a percentage of gross income. Since over 30% of houses in the United States are owned outright, this national percentage is far lower than the debt-to-income ratio of most individuals who have a mortgage. In the coastal bubble rally of the late 80s, people took on larger debts to buy homes, and when prices began their decline, people did not stretch to buy. If people had continued to put a high percentage of their income toward housing, prices would not have fallen as far as they did. The Great Housing Bubble witnessed a 30% increase in the average mortgage debt ratio on a national basis as people bought out of fear and greed in order not to be priced out forever and capture the capital gains of home price appreciation. If history repeats itself, this ratio will decline as house prices decline.

Table 12: National Payments and Prices at Various Debt-to-Income Levels

$ 244,900	National Median Home Price
$ 47,423	National Median Income
$ 3,952	Monthly Median Income
6.0%	Interest Rate
Payment	DTI Ratio	Value	+ 20%
$ 1,107	28.0%	$ 184,561	$ 230,701
$ 1,186	30.0%	$ 197,744	$ 247,180
$ 1,462	37.0%	$ 243,884	$ 304,855

Table 13: Irvine Payments and Prices at Various Debt-to-Income Levels

$ 722,928	Irvine Median Home Price
$ 83,891	Irvine Median Income
$ 6,991	Monthly Median Income
6.0%	Interest Rate
Payment	DTI Ratio	Value	+ 20%
$ 1,957	28.0%	$ 326,487	$ 408,109
$ 3,495	50.0%	$ 583,013	$ 728,766
$ 4,334	62.0%	$ 722,936	$ 903,670

House prices are sensitive to small changes in debt-to-income ratios when interest rates are very low as they were during the Great Housing Bubble. For instance, a 2% increase in the debt-to-income ratio can finance a loan that is 10% larger. Each borrower deciding to put a little more of their income toward housing can bid up prices very quickly. Prior to the bubble rally, lenders would limit DTIs to 28%, but during the bubble rally the only limit to DTIs were the degree to which borrowers were willing to exaggerate their income on their stated-income loan application. The debt-to-income ratio in Irvine, California, in 2007, was 64.4%. Even if it is assumed every buyer was putting 20% down (which they were not), the DTI ratio is 50.1%. This is gross income; as a percentage of take-home pay, the number is much higher. Most financed these sums through some combination of “liar loans” and negative amortization loan terms. Since these two “innovations” have likely been eliminated forever, bubble buyers who used these techniques are not going to be bought out by a future buyer using the same financing methods and thereby using the same debt-to-income ratio.

Higher Interest Rates

Another key factor impacting the fundamental value and thereby the bottom is interest rates. Interest rates went down during the price decline in the early 90s. That softened the impact and made the decline take somewhat longer. When interest rates are declining, bubbles take longer to deflate, and the bottom is at a somewhat higher price point. When interest rates are increasing, bubbles deflate faster, and the bottom is at a lower price point. Mortgage Interest rates during the Great Housing Bubble were at historic lows so a repeat of the steady decline in rates witnessed during the 90s is not very likely. Higher interest rates translate into diminished borrowing, lower prices and a lower bottom.

The lowering of the fed funds rate to 1% during the bubble prompted the lowering of mortgage interest rates to 5.8% by driving down the yield on the 10-year Treasury bill. [ii] The difference between the 10-year Treasury bill and mortgage interest rates is due primarily to the risk premium which was near historic lows during the Great Housing Bubble. As lenders and investors in Mortgage Backed Securities (MBS) lost money during the decline, they demanded higher risk premiums. This increased the spread between the 10-year Treasury bill yield and mortgage interest rates. The spreads for jumbo and subprime both became larger, and the funding for many exotic loan programs dried up.

Figure 56: Mortgage Interest Rates, 1972-2006

As the FED lowered interest rates, the increased risk premiums demanded by lenders and MBS buyers drove up mortgage interest rates along with the heightened inflation expectation the lower FED funds rate caused during the cycle. Unless the FED wants to start paying people to borrow by lowering rates below 0%, base rates cannot go much lower. If all three parameters that make up mortgage interest rates were at historic lows during the bubble rally, there was little or no hope of mortgage interest rates falling below 5.8% in the bubble’s aftermath. The combination of a higher FED rate, higher inflation expectations and larger risk premiums could easily push interest rates back up to near the 8% historic norm or even much higher. An increase in interest rates from 6% to 8% would reduce buying power 18%, and an increase to 10% would reduce buying power 32%. This would be disastrous for housing prices.

Mortgage interest rates have been on a slow but steady decline since the early 1980s. Interest rates were at historical highs in the early 80s to curb inflation, and the decline from these peaks to the 7% to 9% range was to be expected. This initial decline in interest rates coupled with low inflation caused house prices to begin rising again in the late 80s culminating in the bubble that burst in 1990 leading to six consecutive years of declining prices.

Table 14: Impact of Rising Interest Rates on Prices

$ 244,900	National Median Home Price
$ 47,423	National Median Income
$ 3,952	National Monthly Median Income
28.0%	Debt-To-Income Ratio
$ 1,106.54	Monthly Payment
Interest Rate	Loan Amount	Value	Value Change
4.5%	$ 218,387	$ 272,984	18%
5.0%	$ 206,127	$ 257,659	12%
5.5%	$ 194,885	$ 243,606	6%
6.0%	$ 184,561	$ 230,701	0%
6.4%	$ 177,046	$ 221,307	-4%
7.0%	$ 166,321	$ 207,901	-10%
7.5%	$ 158,254	$ 197,818	-14%
8.0%	$ 150,803	$ 188,503	-18%
8.5%	$ 143,909	$ 179,886	-22%
9.0%	$ 137,522	$ 171,903	-25%
9.5%	$ 131,597	$ 164,496	-29%
10.0%	$ 126,091	$ 157,613	-32%
Note: An increase in interest rates will have a strongly negative impact on house prices.

During the early 90s while prices were declining, interest rates were also declining from 10.6% in 1989 to 7.2% in 1996. These 30% declines in interest rates made housing more affordable and helped limit the price declines in the early 90s. If interest rates had not declined, house prices certainly would have dropped further than they did. It is not very likely that interest rates will decline 30% from the 5.8% they were during the bubble down to an unprecedented 4.1% to match the debt relief of the early 90s. The actions of the FED could not and did not keep house prices from falling.

Figure 57: Mortgage Interest Rates, 1986-2006

Future Loan Terms

One of the primary mechanisms for inflating the Great Housing Bubble was the widespread use of exotic loan terms including interest-only and negative-amortization adjustable rate mortgages. The appeal of interest-only and negative-amortization loans is the lower payments they offer, or their ability to finance larger sums of money with the same payment. Adjustable rate mortgages are very risky; it is a risk that has been forgotten, ignored, or not understood by a great many buyers. In an era of steadily declining interest rates, the risks of adjustable rate mortgages do not become problems and many forget (or never realized) the risks were there. Once prices decline to a point where the loan balance is greater than the value of the property, mortgage holders are unable to refinance when their mortgage reset comes due. Most often this will result in a foreclosure. In fact, this is the primary mechanism of the decline, and it will also prevent any meaningful appreciation for years to come.

Of all the factors that contributed to the inflation of the Great Housing Bubble, the negative amortization loan with its offers of extremely low initial payment rates was the primary factor that pushed prices higher than anyone could previously imagine. Toxic loan products, or as the lending industry likes to call them, affordability products, distort the traditional measure of the debt-to-income ratio. The debt-to-income ratio is calculated with an assumption of a 30-year fixed rate mortgage, when in reality, borrowers were using interest-only and negative amortization loans to keep their debt-to-income ratio to manageable levels.

Table 15: Loan Amounts based on Amortization Method and Debt-to-Income Ratio

$ 722,928	Irvine Median Home Price
$ 83,891	Irvine Median Income
$ 6,991	Monthly Median Income
6.0%	Interest Rate on 30-Year Fixed-Rate Mortgage
5.0%	Interest Rate on 5-Year ARM
3.8%	Payment Rate on Option ARM

Payment	DTI Ratio	30-Year Fixed	Interest Only	Option ARM*
$ 1,957	28.0%	$ 326,487	$ 469,790	$ 618,144
$ 2,289	32.7%	$ 381,831	$ 549,425	$ 722,928
$ 3,012	43.1%	$ 502,410	$ 722,928	$ 951,221
$ 4,334	62.0%	$ 722,928	$ 1,040,236	$ 1,368,732
* Negative Amortization loans (AKA Option ARM)

The table above illustrates the impact of various amortization methods on the debt-to income ratio and the resulting loan amount. The first line shows the typical debt-to-income ratio of 28% prior to the bubble and the amounts this payment would finance using a 30-year fixed, an interest-only and a negative-amortization loan. The fact that this payment amount, even using exotic financing does not reach the median sales price is testament to the high debt-to-income ratios utilized by bubble buyers. Using an Option ARM (negative amortization) it takes 32.7% of a median household’s gross salary to purchase a median home; using interest-only takes 43.1%, and using conventional financing takes an astounding 62% of gross income. The widespread use of Option ARMs in Irvine is not surprising. Irvine, California, is the center of the subprime lending universe, and many mortgage brokers who strongly believed in the viability of this product live and work in Irvine and used them to purchase their primary residences.

Since adjustable-rate mortgages of all types performed poorly during the collapse of house prices, and in particular the negative amortization loans, it is likely these loan terms will be curtailed or eliminated in the future. These loans are inherently unstable and prone to high default rates due to the escalating payments that can, and often do, result from their use. The widespread use of these loans destabilizes home prices by detaching them from fundamental valuations. The use of these loans creates the very conditions in which they poorly perform. People who purchased during the bubble rally at inflated prices using these loan terms were risking that these terms would always be available to buyers in the market because without these terms, future buyers would not be able to finance the inflated sums necessary to allow a bubble rally buyer to get out with a profit. Without these exotic loan terms the bubble could not stay inflated.

Unemployment

Figure 58: National Unemployment Rate, 1976-2008

Prior to the Great Housing Bubble, house price declines had only been associated with economic downturns and increases in unemployment. [iii] When the economy softens, wage growth slows down as employers are less able to pay higher wages and the competition for available work makes people less able to demand higher wages from their employers. The economic slowdown is thereby responsible for slower rates of house price appreciation. If the downturn is more severe, rising unemployment serves to push prices lower because the unemployed cannot afford to make their house payments, and their houses often fall into foreclosure. As unemployment increases so does the number of foreclosures, and since there are fewer buyers in a recession, the number of foreclosures cannot be absorbed by the market without a lowering of prices to meet diminished buyer demand.

There is evidence that housing market downturns may actually be the cause of many recessions. [iv] There is a strong correspondence between the times when the country enters and exits a recession and when the times when residential construction spending drops off and picks up. The recession of 2008 was clearly caused by the problems in the credit markets and the resultant slowdown in consumer spending related to the collapse of house prices during the Great Housing Bubble. The result of this recession is unknown as of the time of this writing. If the unemployment rate rises significantly, people are out of work and unable to make their housing payments. This will lead to many more foreclosures even among people who did not take out exotic financing or extract all of their home equity for consumer spending.

Figure 59: California Unemployment Rate. 1976-2008

Many layoffs came to Irvine and Orange County, California, in 2007. New Century Financial went bankrupt along with numerous other subprime lenders based in Orange County. Real Estate related employment went from 15% of the workforce to 18% during the bubble. Most of these workers were laid off when the housing market slowed significantly. Many of the realtors and mortgage brokers in Orange County, California, and Irvine in particular, made hundreds of thousands of dollars a year off real estate transactions during the bubble. Most of these workers were not W-2 employees counted in regular government statistics. Transaction volumes declined 80% from the peak in 2005 to the end of 2007 in Orange County. Prices declined 15% as well. This resulted in a decline in income for realtors and mortgage brokers which put many of them in financial difficulty. Also, many if not most of these members of the real estate industry invested heavily in real estate and acquired multiple properties. Faced with the near elimination of their income, an inability to borrow more money and payments far in excess of any potential rental income, many of these individuals financially imploded and let all of their properties go into foreclosure.

One of the largest contributors to the Irvine, California, economy also does not show up in the unemployment statistics: people’s houses. Median house prices went up in value an amount equal to or greater than the median household income for 5 consecutive years from 2002-2006. It was as if every homeowner had another breadwinner in the family. With home equity withdrawal, this money could be taken out at any time without IRS withholding. On a cash basis, a family’s house was actually contributing more cash to spend than the household wage income. Not everyone took out this money and spent it, but a great many did. When prices fell and credit tightened, the mortgage equity withdrawal spigot was shut off. Imagine the impact on the local economy when half of its “workers” lose their incomes.

With the diminishment of wage income, commission income, and mortgage equity withdrawal, many businesses in Orange County began to suffer. This had ripple effects through the local economy. The lower income began to show up in weakening rents and higher vacancy rates at the major apartment complexes, but the major problem for the housing market was the unemployment. As the unemployment numbers went up, so did the number of foreclosures.

Foreclosures

The wildcard in this analysis is the impact of foreclosures. The number of foreclosures will affect both the timing and the severity of the drop because it is foreclosures that drive prices lower quickly. Foreclosures control the timing of the crash because they directly impact the must-sell inventory numbers: the greater the number of foreclosures, the greater the rate of decline in house prices. By early 2008, the markets in Southern California had already surpassed the peak set in the price decline of the early 90s of Notices of Default and Trustee Sales (foreclosures).

Lenders faced high foreclosure rates in the early 90s because they were too aggressive with their lending practices in the rally of the late 80s: it was their own doing. Lenders overheated the market then, and they got burned. Apparently, they did not learn the lesson of history. One of the problems with the collapse of a financial bubble is the causes get incorrectly identified. When the housing market in California collapsed in the early 90s, the recession and job layoffs were blamed for the problems with the housing market. The recession and layoffs came after the housing market was already in trouble. Unemployment slowed the recovery and added to the foreclosure problem, but it was not the primary cause of the entire pricing downturn. The ultra-aggressive lending practices of the Great Housing Bubble caused a huge spike in foreclosures by early 2008. [v] Just as in the early 90s, the increase in defaults and foreclosures is being caused by the past sins of the lenders: karma on grand scale.

Figure 60: NODs and Trustee Sales as a % of Total Sales,

San Diego, CA, 1990-2007

The importance of the foreclosures cannot be overstated: sellers do not lower their prices voluntarily. Prices do not drop without massive numbers of foreclosures to push them down. The entire “soft landing” argument boils down to one supposition: the number of buyers in the market is able to absorb the must-sell inventory on the market. If this is true, prices do not drop. If this is not true, prices do drop until enough buyers are found to purchase the foreclosures. There are always a number of buyers when prices are declining; some are long-term homeowners who are present in any market, but many are speculators betting on the return of appreciation. These people are few in number, but they buoy the market if there are not many foreclosures. If foreclosure numbers really spike, prices fall until Rent Savers and Cashflow Investors enter the market and absorb the excess. If current trends continue, the number of foreclosures will be too great for long-term owners and speculators to absorb. Foreclosures also control the depth of the decline to some degree. Once prices fall down to their fundamental values, new buyers enter the market and begin to absorb the inventory. If there are not enough buyers at this price level to absorb all the foreclosures, prices could overshoot fundamentals to the downside; in fact, this does tend to happen at the bottom of the real estate cycle.

Figure 61: Projected NODs and Trustee Sales as a % of Total Sales,

San Diego, CA, 1990-2012

Decrease in Home Ownership Rates

There is a strong correspondence to the growth of the subprime lending industry and an increase in home ownership rates. [vi] This is a direct result of lending money to those borrowers previously excluded from the housing market either because the borrower did not have the downpayment, or they lacked good credit. The collapse of the subprime lending industry in 2007 and the subsequent foreclosures on the millions of subprime loans caused a decrease in home ownership rates. Foreclosures are associated with bad credit; those with bad credit are eliminated from the buyer pool until their credit improves. Therefore, people who lose their homes to foreclosure move into a rental, and the previously owner-occupied home often enters the rental pool. (A popular misconception is that rents will go up. The number of rentals will increase along with the number of renters).

Prices fall below rental parity in conditions of decreasing home ownership rates because Rent Savers, who are typically owner occupants, are not numerous enough to absorb the foreclosure inventory, hence the decline in home ownership rates. This means a significant number of the houses due to hit the market due to foreclosure will be purchased as rentals. This is the Cashflow Investor support level. Prices often fall below fundamental valuations at the end of a speculative bubble due to short-term supply and demand imbalances. If this occurs at the bottom of the price cycle of the Great Housing Bubble, the measures of house values may all be lower than the projections and estimates provided herein.

Figure 62: National Home Ownership Rate, 1984-2005

Doomsday Scenario

The analysis presented in this section is intended as a conservative estimate of the magnitude and duration of the decline and recovery following the Great Housing Bubble. Due to the relatively extreme declines contained in the projections, it does not appear as conservative as it really is. When bubbles collapse, they often drop lower and last longer than most can imagine. Few thought the NASDAQ would drop from 5200 to 1200 from 2000-2003, few thought house prices in California would drop from $200K to $177K from 1991-1996 in the deflation of the last coastal real estate bubble, and few thought real estate prices in Japan would drop 64% between 1991 and 2005. [vii] The Doomsday Scenario is an examination of what could happen if all the potential problems for the real estate market negatively impact price levels. It is not likely this scenario will come to pass, but it is certainly a possibility.

Appreciation rates are not fundamental laws of physics. They are dependent upon a solid economy to provide income growth and the willingness of people to put money toward housing payments from their income. If the economy slows and if people choose not to spend large percentages of their incomes toward housing payments (or if people are not permitted to by tighter lending standards,) house prices are not supported. The projection of a worst-case scenario shows the impact of an economic recession and a slow recovery due to tightening credit and a reduced willingness on the part of borrowers to take on new debt.

Figure 63: National Doomsday Scenario

The primary mechanism of the decline is the high rate of foreclosures. This is caused by rising unemployment and the resetting of adjustable rate mortgage payments to much higher amounts due to higher interest rates and the inability of people to refinance into affordable payments, and the inability to make further home equity line of credit withdrawals to make mortgage payments. There are trillions of dollars worth of mortgage obligations in adjustable rate mortgages due to reset by 2011. When many of these borrowers are unable to refinance or make their payments, they will lose their homes to foreclosure. The impact of all these foreclosures will drive prices down quickly, and the depth of the decline may overshoot fundamental valuations due to the temporary imbalance between demand and supply. As each of these borrowers succumbs to the weight of his housing payments, the rate of recovery will be slowed until the bad loans are purged from the financial system. If this scenario becomes reality, on a national basis prices will decline 33% or more from their peak bottoming out at a median price of $165,000 in 2012 or later. The slow recovery at historic appreciation rates will not bring national prices back up to their peak again until 2024.

In Irvine, California, and other extreme bubble markets the forecast is even grimmer. The doomsday scenario would see a 51% decline from peak to trough with prices bottoming at a median price of $351,000 in 2012. Prices will not recover to the previous peak until 2030. Price declines of this magnitude are not likely, but the scenario is not unrealistic. The only requirement is the confluence of all the negative forces working on the market.

Figure 64: Irvine, California, Doomsday Scenario

Lingering Problems

As with any illness, the recovery is often plagued by symptoms of the disease and unwanted side effects. The recovery from the Great Housing Bubble will be no exception. The main problems will be experienced by those who bought at peak prices and did not go through the cleansing foreclosure process. As painful as foreclosure is to those who must endure it, foreclosure is the cure to the disease of the market. After foreclosure, a borrower is no longer burdened by high housing payments, and is free to move to find new work and spend income on consumer goods.

Houses will become America’s new debtor’s prisons. By the end of 2008, anyone who purchased between 2004 and 2007 will be underwater. Everyone who is underwater and making crushing home payments will be stuck in their homes until values climb back above their purchase price. Since there are a great many people in these circumstances and since each of these people are in at a different price point, each one will have a different term in debtor’s prison, but when their sentence is up, many will opt to sell to get out from under the crushing payments. Each of these people selling their homes keep prices from rising. This is the impact of overhead supply. It is also why the market will not see meaningful appreciation without capitulatory selling. People trapped in their homes cannot move to accept promotions or advancements in their careers, and people who are making large debt service payments have less discretionary income to spend. In an economy heavily dependent upon consumer spending, the impact of this loss of spending power will serve as a drag on economic growth. [viii] Aside from the broader economic ramifications, the heavily indebted will need to adjust to a lifestyle within their available after-tax and after-debt income. This will be a disheartening adjustment to many, particularly those who had become dependent upon mortgage equity withdrawal to sustain their lifestyles.

Summary

During the decline of house prices in the deflation of the Great Housing Bubble, price levels will fall to fundamental valuations of historic levels of appreciation, price-to-rent ratios, and price-to-income ratios. The nominal price declines may be impacted by inflation and monetary policy of the Federal Reserve, but inflation adjusted prices will fall precipitously. As people put less money toward housing payments either by choice or by tightening lender standards, prices will not be supported at inflated levels. The combination of unemployment, higher interest rates and the elimination or severe curtailment of exotic financing terms will make refinancing more difficult and the resulting unaffordable mortgage payments will put many borrowers into foreclosures adding large amounts of must-sell supply to the market, driving prices lower. If prices follow their historical pattern, they will fall down to their fundamental valuations by 2011. There are a number of variables which will influence the depth and timing of the decline, and most of the risks are to the downside. There will likely be an overshoot of fundamental valuations at the bottom. Despite all the nuance and analysis, everything comes down to one simple indicator: to paraphrase James Carville and Bill Clinton, “It’s the Foreclosures, Stupid!”

So what implication does all of this have on a future buying decision? Buyers should not count on appreciation. If a buyer needs to factor in appreciation to make the math work on a home purchase, she will buy too early, and she will pay too much. When the cost of ownership is equal to the cost of rental it is safe to buy. Even if prices drop further–which they might–buyers will not be hurt because they will be saving money versus renting. If buyers are counting on increasing rents or house price appreciation to get to breakeven sometime later, they will probably get burned.

Buyers should think about what terms and conditions a future buyer will face. During the bubble prices were bid up to unsustainable heights. Prospective buyers should not purchase when conditions are not favorable. If interest rates are low, debt-to-income ratios are high, and exotic financing is the norm, it is a bad time to buy. It seems counter-intuitive, but a wise buyer wants to purchase when credit is tight and values are depressed. Buyers should be patient and wait for the conditions to be right because a future buyer can pay more when credit is loose and prices are inflated. A house is only worth what a buyer will pay for it.

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[1] One of the factors not included on the list of those that may negatively impact the housing market during the decline of the Great Housing Bubble was the potential problems created by the aging of baby boomers. In the study Aging Baby Boomers and the Generational Housing Bubble (Myers & Ryu, 2008), the authors explore the potential impacts of baby boomers selling their homes and downsizing from their McMansions. The impact of this group, though potentially significant, is very difficult to model and understand. There is no way to know what this generation will do and when they will do it. To speculate that this group would undergo a massive change in their habitation during the collapse of a major housing bubble does not seem plausible, although it is possible. It seems more likely that the baby boomers will not start retiring and potentially downsizing until the crash is past, and any changes in their housing situation will be spread out over many years rather than being concentrated in a short timeframe. The retirement of the baby boomers could serve to depress appreciation in those areas the baby boomers move out of, but it may also stimulate another construction boom in the areas they move in to.

[ii] The Federal Reserve has very little control over long-term interest rates. In an unpublished paper from the University of Washington, the authors examined the correlation between the 10-year Treasury Note and long term mortgage rates. They found the correlation to be greater than 95%. However, when they checked for correlation between the Federal Funds Rate and long-term mortgage rates, the correlation dropped to 35%. The most recent example occurred when the Federal Funds Rate when from 2% in June 2004 to 6.25% in October 2006, and the contract mortgage rate barely budged moving from 6.29% to 6.36%.

[iii] Karl Case and Robert Shiller concluded price declines could only come through an economic downturn (Case & Shiller, The Behavior of Home Buyers in Boom and Post-Boom Markets, 1988). This theory was disproven by the Great Housing Bubble. There has also been research suggesting that housing downturns are actually the cause of economic downturns (Leamer, Housing Is the Business Cycle, 2007).

[iv] A paper by Edward Leamer (Leamer, Housing Is the Business Cycle, 2007) draws strong parallels between residential construction spending and the beginning and ending of economic recessions.

[v] The foreclosure chart was drawn by taking the notices of trustee sales and the notices of default and dividing these figures by the monthly sales rate. Since there is considerable variability in these numbers from month to month, the figures have been averaged to smooth out the noise in the data and reveal the underlying trends.

[vi] In the paper Accounting for Changes in the Homeownership Rate (Chambers, Garriga, & Schlagenhauf, 2007), the authors concluded 56% to 70% of the increase in home ownership rates was due to “innovations” in the lending industry, in particular the lowering of downpayment requirements. Much of the remainder they attributed to demographic factors. The increase in home ownership among younger households was almost entirely driven by new financing terms, while changes among older households were much more to do with increasing income.

[vii] One of the issues not discussed in this writing is the potential impact of generational shifts in housing. A model for generational changes presented in The Baby Boom: Predictability in House Prices and Interest Rates (Martin, 2005) resurrects the early theories of Mankiw and Weil (Mankiw & Weil, The Baby Boom, the Baby Bust and the Housing Market, 1989)in which they predicted the collapse of housing prices in Japan in 1990 and the ongoing disruption in their housing market caused by the decline in population from the Baby Boom demographic bubble. In their 1988 paper Mankiw and Weil famously and incorrectly predicted the same phenomenon would occur in the United States. Instead, the United States witnessed the Great Housing Bubble. It is the author’s opinion that the differing impacts in the Japanese market and the United States market has far more to do with the degree of asset inflation and other macroeconomic impacts than it does with generational demographic factors. While it is certainly possible that the aging of baby boomers will have a negative impact on the United States housing market, it is not clear what impact baby boomers will have. It is assumed they will downsize their accommodations, but this may not be the case. Many may chose to retire and live out their lives in the houses where they lived pre-retirement. If this occurs there will be no mass selloff of homes depressing housing prices.

[viii] In the paper Housing and the Business Cycle (Davis & Heathcote, 2003), the authors document the strong relationship between residential investment and the general economy. Residential investment is much more volatile than the swings in the general economy, but it moves in the same direction. In a later paper obviously drawing for this paper’s title (Leamer, Housing Is the Business Cycle, 2007) the author goes a step further and postulates that the housing market is a driving force in the economy. Previously, conventional wisdom was that housing followed economic cycles and did not drive them. These findings are also bolstered by a report for the Federal Reserve Bank of San Francisco (Krainer, Residential Investment over the Real Estate Cycle, 2006). All the reports reach the same conclusion: residential investment is closely linked to the economic cycle. In another related study on the fallout of financial bubbles, (Helbling, Conover, & Terrones, 2003) Chapter II: When Bubbles Burst. The authors note the financial drag caused by the decline in asset prices.

Price-to-Income Ratio

Since incomes and rents are closely related, evidence for the Great Housing Bubble that appears in the price-to-rent ratio also appears in the price-to-income ratio. National price-to-income ratios are quite stable. There has been a slight upward drift with the decline of interest rates since the early 1980s peak, but from the period from 1987 to 2001, this ratio remained in a tight range from 3.9 to 4.2. The increase from 4.1 to 4.5 witnessed from 2001 to 2003 can be explained by the lowering of interest rates; however, the increase from 4.5 to 5.2 from 2003 to 2006 can only be explained by exotic financing and irrational exuberance.

Figure 46: Projected National Price-to-Income Ratio, 1988-2015

If national price-to-income ratios decline to their historic norm of 4.0, prices nationally will fall 9% peak-to-trough, bottom in 2011 and return to peak pricing in 2014. A 10% decline and a nine year waiting period would be difficult on homeowners nationally, but the magnitude and the duration will not be nearly as severe for most as it will be for homeowners in the extreme bubble markets like Irvine, California.

Figure 47: National Projections based on Price-to-Income Ratio, 1986-2015

The volatility in price-to-income ratios caused by bubble behavior is clearly visible in the historic price-to-income ratios from Irvine, California. During the coastal bubble of the late 80s, in which Irvine participated, the price-to-income ratio increased from 3.7 to 4.6, a 25% increase. In the decline of the early 90s, price-to-income ratios dropped to a range from 4.0 to 4.1 and stabilized there from 1994 to 1999 before rocketing up to an unprecedented 8.6–a 115% increase. This new ratio was achieved by the extensive use of exotic financing, in particular negative amortization loans that rendered the new ratio inherently unstable.

Figure 48: Projected Irvine, California Price-to-Income Ratio, 1986-2030

If house prices in Irvine decline to the point where the price-to-income ratio reaches its average of 4.2–a ratio higher above this historic range of stability between 4.0 and 4.1–prices will decline 43% peak-to-trough, bottom in 2011 and return to the peak in 2029. The magnitude of this decline would be catastrophic to homeowners who purchased during the bubble. Twenty-four years is a long time to wait for peak buyers hoping to get out at breakeven.

Figure 49: Irvine, California Projections from Price-to-Income Ratio, 1986-2030

Hyperinflation

The Federal Reserve under Ben Bernanke began aggressively lowering interest rates at the end of 2007 in response to the severe economic downturn caused by the collapse of house prices and the related difficulties falling house prices had on the banks and other institutions that made loans using houses as collateral. [1] Bernanke, prior to taking the position as the chairman of the Federal Reserve, was an academic who studied the Great Depression and wrote extensively on the failures of monetary policy by the Federal Reserve at the time. He also wrote about the crisis of deflation Japan faced when their combined stock market and real estate bubbles deflated throughout the 1990s. [ii] Bernanke believed that quick and decisive action on the part of the Federal Reserve was necessary to prevent a destructive deflationary spiral as was witnessed in the United States during the Great Depression and in Japan during the 1990s. [iii] By lowering interest rates and creating price inflation, Bernanke hoped to devalue the currency and provide market liquidity through both domestic and foreign investment. Once the real rate of interest was below the level of inflation, borrowing would be strongly encouraged as the value of the currency was falling faster than the interest rate being charged. The increased borrowing would stimulate business growth and the general economy minimizing the deflationary impact of falling home prices. In theory, the lower interest rates would also serve to blunt the decline in housing prices as borrowers would again be able to finance large sums to support inflated prices.

Figure 50: CPI Adjusted Median Home Prices, 1986-2006

At the time of this writing, the results of the policies of the Federal Reserve have not become history so the consequences cannot be fully evaluated. The primary foreseeable consequence of Federal Reserve policy is rampant price inflation. An economy that relies for 70% of its value on the spending of consumers will be strongly impacted by price inflation. When a country knowingly devalues its currency, it causes a severe recession as the prices of imported goods and raw materials increase significantly. Perhaps a severe recession and price inflation is preferable to an economic depression like the one of the 1930s in America, but it is certainly not desirable. Since stagflation of the 70’s, the FED has shown a willingness to push the economy into recession before it allows inflation to get out of control. When the FED started lowering interest rates at the end of 2007, it appeared as if they may be moving down the path of hyperinflation; however, it seems unlikely they would take it to extreme. One of the primary functions of the FED is to provide a stable financial system. Once the Federal Reserve begins to see economic growth and liquidity in the debt markets, interest rates may rise as quickly as they fell in order to stop hyperinflation from occurring.

Figure 51: National Inflation Rate, 1961-2007

There will be some benefits to a devalued currency. A less valuable currency is a boon to exporters. The United States has run a chronic trade deficit for many years, and much of the recent deficit has come from inexpensive goods imported from China. The trade imbalance may correct itself with currency devaluation. Of course, this rebalancing of trade will come at the cost of more expensive imported foreign goods and a commensurate decline in spending power from US consumers. Also, prior to currency devaluation, wages in the United States were so high that jobs were being outsourced to foreign countries where people can be paid much less. Wages could not rise significantly from where they were without devaluing the dollar to prevent wage arbitrage from moving jobs overseas. [iv] The devalued currency provided some room for wage increases, and these wage increases could theoretically provide additional support for housing prices.

Figure 52: Inflation-Adjusted Projections for Los Angeles, 1987-2012

Currency devaluation and inflation eats away at the buying power of money. Although this may support house prices at marginally higher nominal price levels, real price levels, the price level adjusted for inflation, will remain unchanged. Imagine if the Federal Reserve allowed inflation to cut the spending power of the dollar in half by 2011, and imagine if this level of inflation allowed house prices to remain stable at 2006 price levels for those 5 years. Many homeowners would feel relieved their homes did not decline in value, but this relief would be an illusion as the buying power of their money tied up in the value of their houses was cut in half. Irrespective of the nominal decline in prices, the inflation adjusted prices will decline significantly going forward. In the Los Angeles market as measured by the S&P/Case-Shiller index, a decline in prices to levels of historic rates of appreciation as previously described will result in a 66% decline in inflation adjusted terms. [v] On an inflation adjusted basis, buyers during the bubble will never get back to breakeven unless there is another real estate bubble similar to the Great Housing Bubble.

An Educated Guess

Each of the four methods of house price valuation described previously makes an independent prediction of how far prices will fall, and when they will recover. Some of these will prove more reliable and accurate than others, but an average of the results of these four methods makes it possible to make an educated guess as to the percentage decline in house prices and when prices will get back to peak levels. Unfortunately, there is no reliable method for projecting the rate of this decline, but if the experience of the coastal bubble of the early 90s is a good guide, then prices should fall for 6 to 7 years before reaching a bottom. This puts the bottom of prices sometime in or around 2011 based on the peak in various markets occurring in 2005 or 2006. Prices will flatten at the bottom because it will take time to absorb the inventory of foreclosures resulting from the drop. Market psychology and the rate of foreclosures will largely determine the rate of price decline, and these forces are difficult if not impossible to model. It is possible to construct a graph that illustrates the path of house prices over time based on the methods of price valuation and assumptions about the timing of the decline.

Table 10: Summary of Predictions for National Home Prices

Method	Total Decline	Appreciation Rate	Recovery Year
S&P/Case-Shiller Inflation Support	33%	3.3%	2025
Median House Price and Historic Appreciation	10%	4.5%	2011
Price-To-Rent Ratio	27%	3.6%	2020
Price-To-Income Ratio	9%	3.3%	2014
	20%	3.7%	2018

The range of predictions for the decline of national home prices is from 9% to 27% with an average of 20%. The predicted time of peak-to-peak recovery ranges from 2011 to 2021 with an average of 2018. Some will argue price drops of this magnitude are not likely, and these would be unprecedented declines; however, the increases were unprecedented as well. The Great Housing Bubble was a unique and unprecedented event.

Figure 53: National Median House Price Prediction, 2004-2019

The predictions for national prices are based on a 3.7% rate of fundamental appreciation for some combination of wage growth, rental increases and other factors. The origin point for the graph is based on the last period in which fundamentals were aligned in the 1986-1999 period (not shown on the figure). The amount of the decline, 20%, is based on the average prediction of the four methods. The rate of decline was interpolated from the date of the peak to the date of the predicted bottom based on the experience of the coastal bubble of the 1990s. National prices peaked at an approximate value of $246,000 in 2006; they should bottom out at around $196,000 in 2011, and if fundamental appreciation rates hold, they will reach the previous peak in 2018.

Table 11: Summary of Predictions for Irvine, California Home Prices

Method	Total Decline	Appreciation Rate	Recovery Year
S&P/Case-Shiller Inflation Support	55%	3.3%	2039
Median House Price and Historic Appreciation	45%	4.4%	2023
Price-To-Rent Ratio	22%	4.7%	2019
Price-To-Income Ratio	43%	3.2%	2029
	41%	3.9%	2028
* The appreciation rate of 3.9% moved up the recovery year to 2025

The range of predictions for the decline of home prices in Irvine, California, is from 22% to 53% with an average of 41%. The predicted time of peak-to-peak recovery ranges from 2019 to 2033 with an average of 2028. Of course, since Irvine is in the heart of a bubble-prone market, recovery may happen more quickly, but then again, that would mean prices have entered another unsustainable price bubble.

Figure 54: Irvine, California, Median House Price Prediction, 2004-2025

Predictions for Irvine, California, are based on a 3.9% rate of fundamental appreciation as wage growth and rental rate growth have consistently outpaced national averages. The origin point is the intersection of the last two stable bottoming periods in 1984-1987 and 1995-1999. The 41% decline is the average of the four analysis methods, and the rate of decline is projected in the same manner as the national statistics. In Irvine, California, prices peaked around $723,000 in 2006, and they should bottom out in 2011 along with the rest of the country. If the fundamental appreciation rate of 3.9% is accurate, the previous peak will be reached in 2025–a 19 year span from peak to peak.

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[1] Adam Posen wrote Why Central Banks Should Not Burst Bubbles. (Posen A. , 2006) His conclusions are as follows, “Central banks should not be in the business of trying to prick asset price bubbles. Bubbles generally arise out of some combination of irrational exuberance, technological jumps, and financial deregulation (with more of the second in equity price bubbles and more of the third in real estate booms). Accordingly, the connection between monetary conditions and the rise of bubbles is rather tenuous, and anything short of inducing a recession by tightening credit conditions prohibitively is unlikely to stem their rise. Even if a central bank were willing to take that one-in-three or less shot at cutting off a bubble, the cost-benefit analysis hardly justifies such preemptive action. The macroeconomic harm from a bubble bursting is generally a function of the financial system’s structure and stability – in modern economies with satisfactory bank supervision, the transmission of a negative shock from an asset price bust is relatively limited, as was seen in the United States in 2002. However, where financial fragility does exist, as in Japan in the 1990s, the costs of inducing a recession go up significantly, so the relative disadvantages of monetary preemption over letting the bubble run its course mount. In the end, there is no monetary substitute for financial stability, and no market substitute for monetary ease during severe credit crunch. These two realities imply that the central bank should not take asset prices directly into account in monetary policymaking but should be anything but laissez-faire in responding to sharp movements in inflation and output, even if asset price swings are their source.” His argument is sound, but he does point out that if bubbles get too large, the fallout can be even more disastrous than attempts to restrain them. This argues against his central point, and the Japanese example does show what can happen if bubbles are allowed to get too large. Ben Bernanke also wrote a paper titled Should Central Banks Respond to Movements in Asset Prices? (Bernanke & Gertler, Should Central Banks Respond to Movements in Asset Prices?, 2000). He professes a belief that the activities of the Central Bank should not target asset prices, although his behavior as FED chairman has been interpreted as an attempt to bolster market prices. In a later paper (Bernanke & Boivin, Monetary Policy in a Data-Rich Environment, 2002) Bernanke also explored the uses and aggregation of data by the Federal Reserve. He seemed to be preparing himself for the job of FED Chairman. The focus of policy debate and academic research in the wake of the Great Housing Bubble is likely to be the issue of asset bubbles in general. Central Banks around the world learned how to control inflation in the 1980s and 1990s, but their policies have tended to create excess liquidity which has resulted in financial bubbles.

[ii] (Bernanke B. S., Japanese Monetary Policy: A Case of Self-Induced Paralysis, 1999)

[iii] Adam Posen in his paper It Takes more than a Bubble to Become Japan (Posen A. S., 2003), outlines the causes of the prolonged recession after the bursting of the stock and real estate bubbles in Japan. He agrees with Ben Bernanke’s conclusion that aggressive monetary easing is the solution to the problem, “Central bankers should learn from Japan’s bubble the benefits of a more thoughtful approach to assessing potential growth and of easing rapidly in the face of asset price declines and not be concerned with targeting asset prices or pricking bubbles per se.” In a related paper Passive Savers and Fiscal Policy Effectiveness in Japan (Kuttner & Posen, 2001) by Kenneth N. Kuttner; Adam S. Posen, the authors reaffirm their conclusions on the mistakes of the Japanese Central Bank in handling their asset bubbles. The authors note that despite excessive borrowing of the central government, Japanese citizens continue to by government debt at very low cost and in effect subsidize their own borrowing.

[iv] In the paper Offshoring, Economic Insecurity, and the Demand for Social Insurance (Anderson & Gascon, 2008), Richard G. Anderson and Charles S. Gascon describe the problems associated with offshoring, in particular the increased demand of social services caused by the fear of offshoring.

[v] The inflation adjusted chart for the S&P/Case-Shiller index was drawn by the following method. The index value was then divided by the consumer price index date from the U.S. Department of Labor Bureau of Labor Statistics. The resulting number was converted to a baseline value of 1 so the data could be represented as a percentage change.