Martin A. Armstrong -Modelo de Confiança Economica

The Business Cycle And the Future

By Martin A. Armstrong

Princeton Economic Institute
© Copyright September 26, 1999

Economic_confidence_model

For many years, I have pursued a field of study that is at best non-traditional. My discovery of a global business cycle during the early 1970's was by no means intentional. As a youth growing up in the 1960's, the atmosphere was anything but stable. I don’t really know if it was Hollywood that captivated my interest in history with an endless series of movies about Roman and Greek history, but whatever it was that drove me, I can only attest to what resulted.

My father had always wanted to return to Europe after serving under General Patton during the war. My mother insisted that she would go only when he could afford to take the whole family. That day finally came and something inside me insisted upon being able to earn my own spending money. I applied for a job despite my age of only 14. It wasn’t much, but on weekends I worked with a coin/bullion dealer. In those days, gold was illegal to buy or sell in bullion form so the industry centered on gold coins issued by Mexico, Hungary and Austria. I soon became familiar with the financial markets as they were starting to emerge. It was this experience that began to conflict with the formal training of school.

One day in a history class, the teacher brought in an old black and white film entitled "Toast of the Town." This film was about Jim Fisk and his attempt to corner the gold market in 1869 that created a major financial panic in which the term "Black Friday" was first coined. In the film was a very young support actor named Cary Grant who stood by the ticker tape machine reading off the latest gold prices. He read the tape and exclaimed that gold had just reached $162 an ounce. I knew from my job that gold was currently selling for $35. At first I thought that the price quote of $162 in the movie must be wrong. After all, Hollywood wasn’t known for truthfulness. Nonetheless, I was compelled to go to the library to check the newspapers of 1869 for myself. This first step in research left me stunned – the New York Times verified $162 was correct.

For the first time in my life, I was faced with a paradox that seemed to conflict with traditional concepts. How could gold be $162 in 1869 and yet be worth only $35 in the 1960's? Surely, inflation was supposed to be linear. If a dollar was a lot of money in 1869, this meant that adjusted for inflation gold must have been the equivalent of several thousand dollars. If value was not linear, then was anything linear?

I began exploring the field of economics on my own and reading the various debates over the existance of a business cycle. Kondratieff was interesting for his vision of great waves of economic activity. Of course, others argued that such oscillations were purely random. Over the years that followed, this nagging question still bothered me. I had poured my heart and soul into history, quickly learning that all civilizations rose and fell and there seemed to be no exception.

I was still not yet convinced that a business cycle was actually definable. Kondratieff’s work was indeed interesting, but there was not enough data to say that it was in fact correct. On the other hand, it seemed that the random theory crowd was somehow threatened by the notion that the business cycle might be definable. After all, if the business cycle could be defined, then perhaps man’s intervention would not be successful. Clearly, there was a large degree of self-interest in discouraging any attempt to define the business cycle. I knew from my study of history that a non-professional German industrialist took Homer and set out to disprove the academics who argued that Homer was merely a story for children. In the end, that untrained believer in Homer discovered Troy and just about every other famous Greek city that was not supposed to have existed beyond fable.

I didn’t know how to go about such a quest to find if the business cycle was definable. Admittedly, I began with the very basic naive approach of simply adding up all the financial panics between 1683 and 1907 and dividing 224 years by the number of panics being 26 yielding 8.6 years. Well, this didn’t seem to be very valid at first, but it did allow for a greater amount of data to be tested compared to merely 3 waves described by Kondratieff.

The more I began to back test this 8.6-year average, the more accurate it seemed to be. I spent countless hours in libraries reading contemporary accounts of events around these dates. It soon became clear that there were issues of intensity and shifts in public confidence. During some periods, society seemed to distrust government and after a good boom bust cycle, sentiment shifted as people ran into the arms of government for solutions. Politics seemed to ebb and flow in harmony with the business cycle. Destroy an economy and someone like Hitler can rise to power very easily. If everyone is fat and happy, they will elect to ignore drastic change preferring not to rock the boat.

The issue of intensity seemed to revolve around periods of 51.6 years, which was in reality a group of 6 individual business cycles of 8.6 years in length. Back testing into ancient history seemed to reveal that the business cycle concept was alive and well during the Greek Empire as well as Rome and all others that followed. It was a natural step to see if one could project into the future and determine if its validity would still hold up. Using 1929.75 as a reference point, major and minor turning points could then be projected forward in time. For the most part, I merely observed and kept to myself this strange way of thinking. In 1976, one of these 8.6-year turning points was quickly approaching (1977.05). For the first time, I began to use this model expecting a significant turn in the economy back toward inflation. My friends thought I was mad. Everyone was talking about how another Great Depression was coming. The stock market had crashed by 50% and OPEC seemed to be undermining everything. I rolled the dice and stuck to it and to my amazement, inflation exploded right on cue as gold rallied from $103 to $875 by January 1980.

As my confidence in this model increased, I began to expand my research testing it against everything I could find. It became clear, that turning points were definable, but the wildcard would always remain as a combination of volatility and intensity. To solve that problem, much more sophisticated modeling became necessary.

As the 51.6-year turning point approached (1981.35), there was no doubt in my mind that the intensity would be monumental. Indeed, interest rates went crazy with prime reaching 22% and the discount rate being pushed up to 17%. The government was attacking inflation so hard, they moved into overkill causing a massive recession into the next half-cycle date of 1985.65. It was at this point in time that the Plaza Accord gave birth of the G5. I tried to warn the US government that manipulating the currency would set in motion a progressive trend toward higher volatility within the capital markets and the global business cycle as a whole. They ignored me and claimed that until someone else had such a model, they did not believe that volatility would be a concern.

The next quarter cycle turning point was arriving 1987.8 and the Crash of 1987 unfolded right on cue. It was at this time that a truly amazing development took place. The target date of 1987.8 was precisely October 19th, 1987 the day of the low. While individual models specifically based upon the stock market were successful in pinpointing the high and low days, I did not think for one moment that a business cycle that was derived from an average could pinpoint a precise day; it simply did not seem logical.

After 1987, I began to explore the possibility that coincidence should not be just assumed. I began researching this model even more with the possibility that precision, no matter how illogical, might possibly exist. I began viewing this business cycle not from a mere economic perspective, but from physics and math. If this business cycle were indeed real, then perhaps other fields of science would hold a clue to this mystery. Physics helped me understand the mechanism that would drive the business cycle but mathematics would perhaps answer the quantitative mystery. I soon began to understand that the circle is a perfect order. Clearly, major historical events that took place in conjunction with this model involved the forces of nature as well. If this business cycle was significant, surely it must encompass something more than the mere economic footprints of mankind throughout the ages.

The Mystery of 8.6

At first, 8.6 seemed to be a rather odd number that just didn’t fit mathematically. In trying to test the validity of October 19th, 1987 being precise or coincidence, I stumbled upon something I never expected. This is the first time I will reveal something that I discovered and kept secret for the last 13 years. The total number of days within an 8.6-year business cycle was 3141. In reality, the 8.6-year cycle was equal to p (Pi) * 1000. Suddenly, there was clearly more at work than mere coincidence. Through extending my studies into physics, it became obvious that randomness was not a possibility. The number of variables involved in projecting the future course of the business cycle was massive, but not completely impossible given sufficient computer power and a truly comprehensive database. The relationship of 8.6 to p (Pi) confirmed that indeed the business cycle was in fact a perfect natural cyclical phenomenon that warranted further investigation. Indeed, the precision to a day appeared numerous times around the world in different markets. Both the 1994.25 and the 1998.55 turning points also produced clear events precisely to the day. The probability of coincidence of so many targets being that precise to the day was well into the billions. Indeed, the relationship of p to the business cycle demonstrated the existence of a perfect cycle that returned to its point of origin where once again it would start anew. The complexity that arose was that while the cycle could be measured and predicted, precisely which sector of the global economy would become the focal point emerged as the new research challenge.

It was also clear that the driving forces behind the business cycle had shifted and intensified due to the introduction of the floating exchange rate system back in 1971. My study into intensity and volatility revealed that whenever the value of money became uncertain, inflation would rise dramatically as money ceased to be a store of wealth. Numerous periods of debasements and floating exchange rate systems had taken place throughout recorded history. The data available from Rome itself was a spectacular resource for determining hard rules as to how capital responded to standard economic events of debasement and inflation. The concept of Adam Smith’s Invisible Hand was valid, but even on a much grander scale involving capital flow movement between competing economies. The overall intensity of the cycle was decisively enhanced creating greater waves as measured by amplitude by the floating exchange system. As currency values began to swing by 40% in 4-year intervals, the cycle intensified even further causing currency swings of 40% within 2-year intervals and finally down to a matter of months following the July 20th, 1998 turning point.

Economic_confidence_86_year_cycle

The Domino Effect

The events that followed 1987 were all too easy to foresee. The G5 talked the dollar down by 40% between 1985 and 1987 essentially telling foreign capital to get out. The Japanese obliged and their own capital contraction led to the next bubble top at the peak of the 8.6-year cycle that was now due 1989.95. As the Japanese took their money home for investment, the value of their currency rose as did their assets thereby attracting global investment as well. Everyone was there in Tokyo in late 1989. Just about every investment fund manager globally was touting the virtues of Japan. As the Japanese bubble peaked, capital had acquired a taste for foreign investment. That now savvy pool of international investment capital turned with an eye towards South East Asia. Right on cue, the capital shifted moving into South East Asia for the duration of the next half-cycle of 4.3 years until it too reached its point of maximum intensity going into 1994.25. At this point, international capital began to shift again turning back to the United States and Europe, thus causing the beginning of a new bull market in a similar manner to what had happened in Japan. In fact, 1994.25 was once again the precise day of the low on the S&P 500 for that year. As American and European investment returned home, the steady outflow of capital from South East Asia finally led to the Asian Crisis in 1997. In both cases, Japan and South East Asia blamed outsiders and sought to impose punitive measures to artificially support their markets. In Japan, these interventions have left the Postal Savings Fund insolvent as public money was used to support the JGB market. Financial institutions were encouraged to hide their losses and even employees from the Minister of Finance were installed in some cases engaging in loss postponing transactions of every kind. Major life companies were told not to hedge their risks for fear that this would make the markets decline even further. Thus, the demise of Japan that would have been complete by 1994 was extended by government intervention that has most likely resulted in a lengthening of the business cycle decline into 2002.85.

The next peak on the 8.6-year business cycle came in at 1998.55, which was precisely July 20th, 1998. While the intensity was defined rather well by the model’s forecast of 6,000 on the Dow by the quarter-cycle target of 1996.4 followed by 10,000 for 1998, the development of highly leveraged hedge funds created a trap that was not fully anticipated. It was clear that the European markets had captured the greatest intensity between 1996 and 1998 and that Russia too had reached our target for maximum intensity. However, the excessive leveraging of funds like Long-Term Capital Management had significantly created the peak in volume as well. Thus, the spread trades were so excessive, that the collapse that was to be expected, took on a virus type of affect. As Russia moved into default, and LTCM moved into default, the degree of leverage caused a cascade of liquidation that was spread around the world. Everything became affected causing the collapse in liquidity and credit to further undermine the global economy as a whole. Despite the new highs in US indices into 1999, the broader market has failed to keep pace and the peak in both liquidity and volume remains clearly that of 1998.55.

The Future

While this business cycle can be calculated on quarter-cycle intervals of 2.15 years into the final peak for this major wave formation of December 24th, 2032. Though this is long beyond my life expectancy, there is so much more behind the true understanding of the driving forces within the business cycle. I have learned that it is easy to claim coincidence and ignore the telltale signs of a hidden order. It is easy to argue that there is no basis for such a model without ever making an effort to test results. If everyone stopped with such criticism, most of ancient Greece would still be buried and Homer would still be considered a book for children. Man would not fly or travel to the moon. A cure for cancer would not be sought and progress would simply not exist. But furthering our understanding is part of humanity. Like law, that when strictly enforced deprives society of justice when circumstances are ignored, it is also the sin of ignorance toward new concepts that deprives mankind of progress and ultimately our posterity.

The Economic Confidence Model in 2.15-year intervals

1998.55... 07/20/98

2000.7.... 09/13/00

2002.85... 11/08/02

2005.... 01/02/05

2007.15... 02/27/07

2009.3... 04/23/09

2011.45... 06/18/11

2013.6... 08/12/13

2015.75... 10/07/15

2017.9... 12/01/17

2020.05... 01/26/20

2022.2... 03/22/22

2024.35... 05/16/24

2026.5... 07/11/26

2028.65... 09/04/28

2030.8... 10/30/30

2032.95... 12/24/32

In the next issue of the WCMR, the details of this business cycle will be expanded to provide a list of turning points down to the 8.6-month interval. There is a wealth of knowledge that lies ahead if we are not afraid to explore. Regularity of the business cycle does not mean that we lack free will. For it has taken me 30 years of observation to get this far. The peak for one nation may be the low for another. For within the scheme of global capital flows, not everyone can enjoy a boom simultaneously. For every gain in trade, there must be someone who loses. This is simply the nature of the global economy. The greatest booms unfold when capital concentrates in one sector. When that capital shifts, you also find the result of the greatest financial panics in history. An individual will always possess the free will to follow the crowd or strike out with his own independence to buck the trend. There will be those who believe in the business cycle and use it to their advantage just as there will be those who refuse to acknowledge its existence. As long as not everyone believes, the cycle will exist forever. The regularity of the business cycle is not determined by man alone; for within its deep calculations resides the very heart of nature itself. Like the Biblical forecast of Joseph that seven years of plenty will be followed by seven years of famine, understanding the nature of the business cycle can certainly enhance our ability to better manage our affairs rather than constantly add to the intensity of the cycle through our own error of intervention. For now, it is more likely that the politics will continue to act in the opposite direction of the cycle adding to its intensity and enhancing its volatility. Perhaps I have been an evangelist seeking to point out that the economy is like a rain forest – destroy one species and it will ripple through the entire system. The global economy to me is the same delicate system that cannot be viewed in isolation, but only through its collective integration. The failed labor policies of Europe have created perpetually high unemployment and the worst record of economic growth for the past 30 years. Instead of objectively reviewing what has happened, Europe seeks to federalize and strengthen the very controls that already exist. Communism and socialism are all political byproducts of our failure to understand the business cycle. Blaming the rich, your neighbor or a particular race are all vain quests to explain the cause of a cycle that has moved through the boom bust phase. Who knows, perhaps it is possible that if for one moment we truly understood the business cycle and worked in harmony with it, the possibility of reducing the amplitude just might result in a more stable political-economy for all mankind.

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Comentários

1) Este aponta para a Bear Stern , que foi quando o sistema financeiro desmoronou.

I only picked up on the Bear Stearns problems when the press reported the Merrill- BS fight on June 19. It took me the weekend playing with what it meant to realize that was no ordinary run of the mill spat. When I worked the Street, many years ago, no one trashed another' major's collateral but aways tried a work out. I scaled back immediately the following week and reduced to a focused PMs and NAFTA based oil minors.

However, lately the media here in the UK and elsewhere have been attributing the credit crisis start to events in late Feb, rather than the August date usually used. For me these were still masked by the massive LBO nonsense, but I'm told by those in the know that interbank credit began siezing up from the end of Feb and that the Qatar LBO for Sainsburys PLC was amongst the first hit. August is certainly right for the ABCP lockup in Toronto. Dullard me, it took MER nuking BSC collateral and a heightened sense of alert following the May 31 - June3 Bilderberg meetng in Istanbul, to realise that the rules had changed. By then it was already June 25.

If Mr Armstrong is onto something and if it applies to this at all, presumably the credit problem grows until the next date coming up in March 08. Since the end of Feb or early March, I haven't seen any more about Armstrong cycles in the media.

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2) Um pouco de historia e modestia.




I have to say that I thoroughly enjoy your blog. I've been studying cycle theory for some time. I have to say that reading this post was rather eery. I've got a degree in applied mathematics and I find the concept very intriguing. But, I have to say there isn't a whole lot of rigor here. Without relevant data points, I find it hard to believe anyone has been able to highly historical events of significance over for hundred years ago. I'd be inclined to believe some but those would likely be European. What about Asian or other data points which would not be as readily available. China was the world's dominant economy 400 years ago. It is also rather hard to believe how this cycle seems to perfectly fit into Greco-Roman times with a passing commentary. We know so little about many events of that time even the author admits much was considered fable. It is almost as if he is spoofing his own findings.

Yet, I hold out that maybe there is more information available and the information on current events is very interesting. Although, again, it bothers me that this was not published till 1999. I have little doubt there is much that we do not understand. Be it of ourselves, our history, the cosmos, cycles, etc, etc. There is definitely something unexplained about economic cycle theory.

Well, thanks for sharing. I enjoyed it very much.

Posted by: cd | June 26, 2006 at 11:41 PM

CD:

The model was first published a couple of decades ago but was used to forecast the 1980-81 peak in inflation in the late 1970's. It is known as the Princeton Economic's 'Economic Confidence Model' and was a part of Armstrong's 32,000 variable artificial intelligence super-computer model, which Armstrong said had "perhaps the largest economic database in the world, some of which he got from the london museum, including record from ancient Babylon, so I believe him when he says that he backtested the cycles into the ancient world. The CIA and Chinese government tried to aquire the model in 1998 after it forecast the crash of 1998 to the day on July 20. He had forecast the the dow would hit 6000 by 1996 and 10,000 by 1998 in the early 1990's. He also forecast in 1996, that oil would hit minimum $65 and that inflation would heat up after late 2002 going into 2007 and possibly extending into 2012. Armstrong said no to the CIA and Chinese and a few months later ended up in prison where he has now been for 6.5 years on contempt of court.

Armstrong was managing 3-4 billion dollars for the Japanese after he predicted the nikkei would peak in late 1989 and then lose 20,000 points within 10 months. Equity Magazine in Vancouver Canada named Armstrong 'North America's Top Economist' in 1990. All of this research has been around for quite some time, it did not just appear in 1999.
http://princetoneconomics.blogspot.com/

As boomers pull out funds, will they pull down markets?

Robert Powell

Sept. 10, 2009, 12:01 a.m. EDT

As boomers pull out funds, will they pull down markets?

CBO says financial markets won't suffer as millions retire, but some disagree

By Robert Powell, MarketWatch

BOSTON (MarketWatch) -- Many wise men have predicted the stock and bond markets will go into a free fall for decades once baby boomers start withdrawing money from their retirement accounts, but a new report this week by the Congressional Budget Office suggests that won't happen when boomers retire.

"Some economists have warned of the possibility of a dramatic decline in demand as baby boomers sell off their assets to finance their retirement; they assert that the sell-off could cause a dramatic decline in prices," Douglas Elmendorf, director of the CBO, wrote in his report.

Should Lehman Brothers have been saved?

We ask New Yorkers whether the collapse of Lehman Brothers should, or could, have been prevented.

"An evaluation of the evidence, however, indicates that such a dramatic decline in asset demand and prices is unlikely," he said.
If only that were true. But some people disagree with at least some of the CBO's findings.
"The CBO report provides some ideas, but has a long way to go before resolving the question" of whether demand for and prices of assets will fall as boomers retire, said Alan Gustman, a professor at Dartmouth University, and Thomas Steinmeier, a professor at Texas Tech University.

Demand for assets

For its part, the CBO said it makes sense in principle that if more people are selling assets to finance their retirement than are buying assets, then stock and bond prices would decline. But the empirical evidence, the CBO said, doesn't bear that out. Earlier groups of retirees didn't sell their holdings en masse to the fund their retirement.
Several factors probably explain the evidence, Elmendorf said in the report. "First, retirees generally are cautious about selling assets to finance consumption because they might need those assets in the future: They might live longer than expected, and medical costs, which are likely to rise as people age, could be higher than anticipated. Second, rather than spend all of their assets, retirees might intentionally retain some to make bequests.
"Third, wealth in the United States is highly concentrated: One-third of the nation's financial assets is held by the wealthiest 1% of the U.S. population. The wealthiest people do not spend significant portions of their assets during retirement and in most cases die leaving bequests."
What's more, the report said demand for assets will remain high as baby boomers push back the timing of their retirement due to the recent market turmoil. "Some baby boomers who have lost or spent a significant portion of their assets may defer retirement, shortening the duration of retirement and reducing the amount of assets needing to be sold to finance consumption," the report said.

Will prices fall -- or won't they?

The CBO also said it's unlikely stock and bond prices will fall as boomers retire. "Empirical evidence has not revealed much connection between demographic trends and the price changes observed in financial markets."
Some economists agree with at least some of the CBO's findings.
"Couples in particular do not decumulate [spend down their assets] until late in life, so the immediate effect of boomers retiring will be small," said Michael Hurd of the Rand Corporation.
But he and other economists take issue with plenty else in the report. For one, singles do decumulate early in retirement, Hurd said. What's more, he said even though boomers may not decumulate assets, they will no longer be saving after retirement. "Thus a change in asset demand will result from people moving from an accumulate phase to a neutral phase," he said.
To Gustman and Steinmeier the problems with the CBO's view of the world are many. "There are three additional factors that we would like to have seen discussed in the CBO report," they said. "Each of these omitted factors would, in fact, reduce net assets."

First, according to Gustman and Steinmeier, the CBO incorrectly dismisses the presence and importance of defined-benefit plans. According to Gustman's and Steinmeier's forthcoming book "Pensions in the Health and Retirement Study," most people retiring today have a traditional pension plan. In fact, two-thirds of the pension assets of people near retirement age today are in defined-benefit plans.
In plain English, those retiring today won't draw down their stock and bond portfolios because they don't need to. But as more boomers retire without a traditional pension plan, the need for them to draw down their IRAs and 401(k)s will be greater. Thus, the big whooshing sound you hear.
Second, Gustman and Steinmeier say that by focusing only on personal wealth, the study ignores the effects of Social Security's financial problems. "Over 30% of the wealth of those approaching retirement is in Social Security," they said. "As the boomers retire, that wealth will be drawn down throughout the retirement period, creating additional government debt. Of course, under-funded, government-insured health expenditures will add to these liabilities."
Third, the effect of the stock-market decline is only one of the factors affecting baby boomers' retirement picture, Gustman and Steinmeier said. In their paper, "The Retirement Age Population and the Stock Market Decline," the professors said the stock-market decline alone will lead to an average postponement of retirement of no more than a few months.
However, the effects of layoffs of older workers must be factored in as well. "Layoffs reduce total compensation from full-time work even for those who find another job," they said.
"As older workers are laid off as a result of the current recession, many will have a great deal of difficulty in finding new jobs that will pay wages nearly comparable to what they earned in the past. That will lead some to retire earlier than they expected. Should net retirements by older persons be accelerated, they may draw down their pensions and other assets earlier than they had planned."
The net effect of that, Gustman and Steinmeier said, is that there's likely to be a reduction in net assets.
That suggests a bear market, maybe even a two-decade-long bear market.

Read the CBO's report at this Web site.
 
Robert Powell is the editor of Retirement Weekly. Learn more about Retirement Weekly here .

 

Robert Powell has been a journalist covering personal finance issues for more than 20 years, writing and editing for publications such as The Wall Street Journal, the Financial Times, and Mutual Fund Market News.

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Baby boomers may not pull a bunch of money our of their 401Ks/IRAs each year. But I bet some of them, like me, will be transferring more to conservative funds like money market, stable value bond funds as the years pass. We've tried to build those balances the last few decades while we were working and hope we don't start drawing out too soon.

But my theory is that the more you have, the more you can risk (as in stock funds). The less you have, the more conservative you need to be. In the not so distant future, it will start to look like the money we have in those plans will be needed sooner rather than later.

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When it comes to the boomers' effects on the economy, their investments are just one part of the equation - you also have to look at their spending. If they don't take much money out of the equity markets to live on (a good thing for the markets), they won't be spending like they used to either, which was another driver of the economy. There aren't as many of the next generation to pick up their spending on durables, household items, clothes, etc. at retail which the retirees no longer need anyway since they are no longer in acquisition mode but downsizing. And, in the perfect storm, this recession is going to make several generations more cautious about spending the way the boomers did. So there will still be a depressing effect on the equities markets and the economy as businesses cut back with less consumer demand.

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As a boomer who finds himself in the middle of my age group, here is what I am pursuing. After being a biochemist for 29 years, raising four great kids, and paying all those taxes along the way, I have been laid off by my corporation. Seeing this coming 1-2 years ago, my wife (who also works full-time) and I began buying properties here in Upstate NY in 2008, fixed them, and are renting them out to graduate students and many who work in the Health and Education fields.

We now have a quarter million dollar business (gross) and still growing. We need a property manager to handle the increase in tenants, repairs, etc.. Too bad Obama conveniently forgot the small business person, which everyone knows makes up 50% of this country's employment. I would have proposed at least a $15,000 tax credit to small business (1-200 person company) for each person hired full-time plus I could add $10,000. 1 million business's hiring 1 person equals 1million people off unemployment at annual cost to U.S. gov't of 15 billion dollars, NOT THE BUDGET BUSTING NUMBER OF 798 BILLION FOR JOBS THAT ARE TEMPORARY!

Housing prices in Onondaga Count, NY have only fallen -1% from 2008 to 2009, according to recent statistics. Even if they fall more, so what, my properties are basically Income Funds, paying a monthly "dividend" (minus bank mortgages, repairs, personal Income Tax). There are many more people out there that have to rent because of the tougher bank lending standards, which should have been in place in the first case, anyway, rents are stable if not increasing since 2008.

I am not investing in stock equities, for now, rather I am buying and selling in the bond market; plowing my profits into such bond funds as BND, AGG, and EGF. In 10-20 years I will sell everything (houses), and even if I price in an Armageddon figure of 40-50 cents on the dollar for each property, I still will have invested and diversified my rent profits, get my 20% down payment back, and now the banks are almost paid off with some equity left, maybe (worse case).

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Boomers still have more money than any other age group in spite of the recent markets' swoon. Follow the money people!

Marketers wastefully spend their time and companies' money targeting 18-35 yo's when the majority of stored wealth and purchasing power lies in the 50+ range. Unless these 50+-somethings part with their money, there will be no pick up in economic activity. But, eventually, at some point, Boomers will de-cumulate or dis-invest to fund their lifestyles sans income from employment. Those same 50-somethings will at some point sell assets i.e. stocks, bonds, and real estate, the question is: To whom will they sell, who will buy and at what price? In order for them to de-cumulate or dis-invest, they will need to sell to those who are younger and hopefully have rising incomes to support their purchases. Otherwise, asset prices will decline. How Boomers decide to spend or save and how younger generations fare in regard to their incomes and investments will determine the future course of the economy and our collective futures.

There is a fallacious assumption made by many financial wonks, pundits and talking heads who believe that retirees will need to live on the same income or more, adjusted for inflation, than they earn during their working lives. They fail to realize that many will in fact downsize their lifestyle and with that their need for the same amount of pre-retirement income. Those who can afford to retire, do so because they had the discipline to live below their means during their working lives while they were accumulating assets and wealth. Those who chose to live aspirational lifestyles did so at their own financial peril; as they are now realizing that they cannot sustain or support that lifestyle ad infinitum without sacrificing their retirement. The same profligate spenders will realize that even if they continue to work they will not earn the same amount of money as the labor supply exceeds its demand and hence lowers the price -income- of labor, and therefore, once again they will learn that there is no free lunch when it comes to economics. It's truly a zero sum game where a dollar spent is a minus to the spender and a plus to the saver. Money is not lost it is merely redirected to the saver and invester, redistributed from weak hands to strong.

For those who have accumulated wealth and have been downsized or chose to retire early, and who did not lose money in the recent market meltdown, they will shift to a neutral spending pattern, simply maintaining what they have. That will not bode well for the economy. The unknowns for retirees are still: taxes, inflation rate, longevity and health care costs; obviously too many variables to know with certainty and therefore requiring the prudent to be financially conservative and spend much less than they once did in order to prepare for an unknowable financial future.

For those boomers who are unemployed, but, still have plenty of assets, should they be re-employed, they will continue to save as they always have, but, most importantly, they will spend more than they would in an unemployed status, thus, goosing economic growth. The choice is up to the G and the companies who are smart enough to realize this and the fact that they could rehire those boomers in the 50+ range for less than they think. The re-employment of this group would allow for a smoother economic transition that would benefit Boomers and the younger workers who are destined to replace them as the Boomers transfer their corporate knowledge, life's wisdom and work habits to the next generation. This would also be a plus for the companies who employ this strategy and for the country as a whole.
Just MHO.

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As one of those so called retiring baby boomers (6 years now), my fear is that my dollars are becoming worthless. I'm putting them into the market, into gold, and into copper to protect against the coming inflation and devalued dollar. If everyone is thinking like me, then the market will rise but the dollar will crash. It is survival in the coming galloping inflation.

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This CBO report is another example of "looking backwards", ignoring demographics, and ignoring the programs they know are coming THEY KNOW they Medicare is in warning status. They know SS has no future COLA adjustments like the past. They know the state of the dollar. It is just silly to use what people "use to do" before the crisis and IGNORE the changes that the CBO KNOWS are coming. Compared to prior generations, this generation is looking at cuts in Government benefits that will equal their net worth (on the average) at the date of their retirement.

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Cyclone and MrMoney

You are both ignoring the 800 pound gorilla in the room, and that is the fact that population growth is no longer a problem, and 6 billion is likely about all the people that will populate the earth at one time. A shrinking population in most of the developed world will be the larger issue for our economies. Immigration will cease to be an issue here, and will become a necessity, as more and more workers are needed to pay the taxes required to support our aging population with the entitlement programs we have promised them.

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"Empirical evidence has not revealed much connection between demographic trends and the price changes observed in financial markets." - WHAT?

This article smells like propaganda giving you cause not to panic about the inevitable!
I guess giving them a little more time to squeeze $ out of the baby boomers.
But possibly not.
Maybe just naive state workers pushing for an economic comeback (which ain't gonna happen for the USA)
Any way - Sounds like you can bet on the exact opposite happening to what these guys say!

Harry Dent Author of The Great Depression Ahead is my expert on demographics:

http://www.hsdent.com/ny_times_bestseller_the_great_depression_ahead_book_tour/

I agree with him on 90%
But I feel:
1. The Great Depression is already started = Effects will not be as bad as the Mort. crises has already taken us so far down.
2. The masses of population in Brazil, Russia, India and China will save America from the greatest impact. (World population has more than doubled since 1950)
3. And lucky for you. America has imported almost 20% more population in ages between 30 to 40 years. Their positive contribution to the economy will support the masses moving into retirement.

Something for you guys to think about.
I strongly recommend the link supplied if you want to survive what IS coming.

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One simple forecasting tool predicts, with uncanny accuracy, the health of the economy and the stock markets over many decades to come: the (demographic) Spending Wave.

Mr. Dent first used the Spending Wave in 1988 to predict the raging bull market of the nineties long before it became obvious. At that time, he stated that the Dow would reach 10,000 or higher and that this boom period, characterized by high domestic productivity and falling interest rates, would last until approximately 2010. By adding immigration data to my original model and making a few other adjustments, he raised his Dow forecast much higher. This fine-tuning increased the accuracy of the Spending Wave without changing its fundamental reliability.

The Spending Wave predicts the health of our economy by lagging the birth index forward 46.5 years. Why this number? That’s how old each of us is when we reach our predictable peak in spending today. By our mid-forties,the average American family has purchased the largest home we’ll own and all the furnishings to go with it, and we spend money on clothing, food and education for our teenage children. Once the children leave the nest, the fixed costs remain the same but variable costs suddenly start dropping. Though this frees capital for discretionary spending, it marks the end of the necessary family spending that drives the economy.

http://www.hsdent.com/spending-wave/

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What Mr. Dent’s discussion fails to include is the US workforce reductions created by the population declines of the 1960s and 1970s. Without increasing immigration, the GDP would likely fall due to the reduced purchasing power of my children and that of my retiring or death. Now that my kids are entering their prime purchasing age, we as a nation are experiencing the lack in their purchasing power. The younger generations cannot match the purchasing power of their baby boomer parents. As a result, we have the housing bubble that started in 2005 and the younger generation’s inability to acquire all the homes inspired by the housing explosion of the past. Now factor in the reduced baby boomer purchasing power resulting from the present economic crisis, the loss of value in their homes and their fading from the scene.

As Dent’s chart shows, the birth rate will fall until the population increases of the 1980s kick in between 2020 and 2025 and will likely not reach the levels of 2006 until away past 2056. As a result, the GDP should suffer without a heavy dose of immigrants.

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The author of this story omitted several key factors.

First, its not like the U.S. baby boomers only own U.S. equities.

Some own international equities.
Some own bonds.
Some own real estate
Some own CD's.

So it is not like they will suddenly pull the trigger and sell equities only to raise cash.

Second, all U.S. equities are not owned by old U.S. investors.
Foreign investors own a lot of U.S. stocks and may not sell any time soon.
Many equities are owned by sovereign wealth who have no plans on selling.

And while it may be true that aging baby boomers may scale down their investment purchases, we do have a younger generation that will need to save like never before.
They don't have the luxury of appreciating real estate that boomers had.
They can't count on social security like boomers have.
There are far less pension plans offered to the younger generations.

So younger people have no choice but to invest heavily in stocks and bonds for their own future.

So bottom line is that boomers do not make up all the demand for US investments- far from it.
Demand will be there from younger generations and foreign investors.
And many boomers have pensions, social security and won't have to sell- they will leave an estate for their children to spend/invest.

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It has long been forecast that boomers would significantly impact every facet of society much like a pig moving through a python.
Consider if you will:
1) The number one fear of the elderly is outliving their money. As people age they become increasingly more conservative in their expenditures.
2) Life expectancy is rapidly increasing and will continue to rise. Today average life expectancy is 78. At the turn of the last century it was but 52.
3) This market has yet to experience a major correction. We face more problems than we have resolved (energy dependence, unaffordable entitlements, a disproportionate percentage of society retired, unwinnable wars, falling dollar, declining standard of living, etc). That drop in value will either further erode equity assets or scare boomers to more conservative and income certain investments with what is left.
4) Boomers are historically POOR savers. They have been big spenders, heavy borrowers, known for their need to consume, not save. As a result they are unprepared for retirement, will be likely to defer retirement and possibly work until physically unable. This group is heavily leveraged compared to their parents.
5) Typically, marketing does NOT target seniors because they are atypical spenders, certainly not reflective of the historic perception the American consumer has insatiable appetite to consume. Right now boomers are in their peak earning years.
6) Given the onset of boomers attaining retirement age I fully expect them to seek smaller and less costly housing. Some is attributable to lower income, an attempt to wring some equity out of their existing home, but also to bring operating expense in line with lower income.
7) If, as I expect, we will be decades digging out from this economic malaise, boomers, even with investments, will be shifting out of stocks that have or will reduce dividends.

Just imagine the huge shift as boomers migrate from consuming, paying taxes, investing, etc to becoming an economic drag on our society. And yes, I am a boomer.

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I can only respond by citing my personal situation and many of those that I know which includes people that are millionaires to those with almost nothing.

The stock market decline took at least 30-40 percent of the wealth away from middle American on up. Many have decided lately because of increased cc minimum payments to reduce or eliminate any further 401k contributions. If companies do not contribute the incentive is almost entirely gone to continue putting money into 401Ks that often are rather limiting with their selections. Our 401 has been with several investment groups that we had nothing to do with deciding that fact. Often there are only handful of funds that we are qualified to invest in. Both my bank and company have switched funds this year due to poor performance this past year. Again, we have zero control over this. We once were invested in a company pension plan that was easier to decide when to get in and when to sit it out. Back in the 80s when the market crashed, everybody I knew that worked for this mega company contributed the most they could knowing that the price of the stock was ridiculously low. We even took our private money and bought more stock outside the 401K contributions. I wish I had bet everything I owned at that time because we knew the company very well and knew our investment was very safe. 401 investing today is like throwing darts. I hate it. I would do so many things differently if I had to do it all over again. We all got conned.

This is what I know. I have lived in many regions of the country and for personal reasons I have always been rather drawn to the greatest generation. I found my generation, baby boomers to be spoiled and self serving. The greatest generation mostly lived frugally and also was guaranteed a company pension. That combination is a winner. The retirees I knew and spent a great deal of time with took very nice trips every year until they couldn't, but they lived in very modest homes. I think baby boomers would balk at such modest homes. Those retirees had long ago paid off their homes and cars and settled into a life pretty much devoid of stress. They just plain didn't want much. My mother was one of them. At the time of her death, which was 83, she may have had about 90,000 left in the bank. Nursing homes prior to that ate up much of her wealth. My mother-in-law the same situation. She lived in a very nice condo complex in Fla and barely spent any money. Everybody living in that large community had just a bit of SS and some savings that might have amounted to 50,000. My aunt that uncle the same.

The baby boomers are relying mostly on SS and a touch of those with a pension, but mostly that up and down 401 plan. After this year's slaughter many of us are just trying to preserve what we have and pay off any debt we have and learn to live with a lot less. We have flat run out of time. The thousand of lake communities in this part of the country have all their second homes for sale. The boomers are cleaning house. Those privately investing have ceased to do so. They don't trust the market and have turned into those loathing the government. Many still have high school kids to get through school.

The baby boomers may find some part-time jobs to supplement their drastically reduced income stream. I know millionaires that have ceased investing but can't find investment instruments with security and a decent return. So if you retired with 1,000,000 thinking you could get a 5 percent return and now can only get a 2.5 return that is a huge income stream reduced. Prior to this crisis many thought 7 or 8 percent was doable, but now.... The more time they have now to understand the markets the less they like what they hear. Ignorance is often bliss.

At the time of Biden's nomination, his financial records were revealed. He had few investments and in fact a 770,000 mortgage on his home that is probably worth a lot less today. He is at retirement age currently. He of course was counting on his much younger wife and her pension and his government pension and so he apparently didn't investment much at all according to records released.

Less than 8 years ago when we bought a farm, we looked at many large pieces of property. What I found out with this long property search was how many baby boomers that lived large and looked like they were very rich were highly leveraged. They owned multiple properties but at closing frequently had to pay to close. They had long ago borrowed that money.

Things are rarely as they appear. The CBO in this case is WAY TO OPTIMISTIC.

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The Gustman and Steinmeier analysis while adding somewhat to this debate falls well short of the mark in its myopic focus on the "big selloff". They simply did not look at the asset most likely to bear the brunt of the Great Retirement--housing.

While defined benefit pension plans will see withdrawals, those plans that are not in "closed" status (think state teacher retirement, large corporate plans, state and federal plans) are set up to service a population that is assumed to go on in the future; that is, just because some members are retired doesn't mean that the company or governmental entity will cease employing additional people, new teachers not be hired, etc., etc.

Their concern over asset drawdowns on financial valuations is misplaced. Rather they should look at the effect on housing, as many Boomers have stated in surveys that they expect their homes to provide the funding for their retirement. Unlike financial assets, residential housing assets are very broadly held, and unless buyers can be found for the properties being sold to fund the Great Retirement, housing prices might not only never come back to 2002-2004 levels over the next 15 years, these prices might actually slip another 20-33% as wave upon wave of Boomers search for money.

All this is further compounded by the fact that I can sell my financial assets to someone in India, China, or Brazil without difficulty. However, that cannot be said to be true of my house. Stock is fungible, but my house needs to be sold to someone else who wants to live at that precise geographic location. Those in SMSAs with growing elderly demographics better take note and sell early (before 2018) if they will be able to sell at all.

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"There is no means of avoiding the final collapse of a boom brought about by credit expansion.

The alternative is only whether the crisis should come sooner as a result of a voluntary abandonment of further credit expansion, or later as a final and total catastrophe of the currency system involved."

-Ludwig Von Mises

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Look back to the time when we had balanced Trade , and a Recovering deficit from a Time of Inflation , and what was making those wheels turn in that direction ........then look to when those wheels were changed to reverse mode ..... and argue to the fact that while there were contracting deficit spending balance in Government , in the late 1990s , the Real Growth in Markets was declining and lead to the tech bubble crash in 2000-1 because of the devaluation that was taking place in the relocation of Jobs/ wealth creation from the change in Trade law , BUT , If we would have kept the dollar sound through our Reagan / GATT Tariff Trade rules in the 1980s would we have kept our Capitalists system solvent and leading the world economies to better quality of life achievements , like it has done forever , so that the rise of Social Justice would not be rising up in the debate on Equality ???? I believe the Change of Tariff Law back in 1994-95 was the beginning of this demise we see today , and the Giant Sucking Sound Ross Perot talked about in the 1992 Presidential Campaign , http://www.thenation.com/doc/20011231/greider

Subject: Please read this ; The Road to Socialism USA http://www.cpusa.org/article/articleview/994/1/154/


Please read this , and ask if America would have built all that we have consumed over the past 15 years of Tariff Free Imports , the very Tariffs that would have been paid to offset the losses to Medicare and Social Security , for the loss of wage deductions that by relocating jobs out of the USA has caused , which everyone keeps forgetting to talk about , that maybe we wouldn't need Socialism ???

The High Cost of the China-WTO Deal
Administration's own analysis suggests spiraling deficits, job losses
by Robert E. Scott http://www.epi.org/publications/entry/issuebriefs_ib137/


Or was it all planned ???

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I work for a large Japanese multinational. Before that I worked for a Swedish multinational. I have known and worked with many Europeans and Asians of several different cultures. The standard line is "It's a great system as long as you don't get sick." I also hear a lot of "It's free but you get what you pay for." I know two Dutch who received absolutely NO TREATMENT for cancer after they were diagnosed. Their doctors basically said, "Get your affairs in order." as soon as they made the diagnosis. Each one died less than a year after diagnosis although they did give them plenty of morphine to dull the pain.
If you really want to know how good the French and other European "free" systems are, then I suggest you take a look at the recovery rates for prostate cancer. In the US we have a recovery rate of close to 90% because we treat prostate cancer. In Europe, the recovery rate hovers around 40% because they do not treat prostate cancer. It is a painful and lingering death when untreated.
The Euro systems are actually a self fulfilling method of murder. The doctors know they don't have the funds to treat serious illnesses, so they don't, then they tell the sick patients; "See, your chances of recovery are slim, so we can't throw money away treating your illnesses."
To answer your question, yes, I have been out of the country so often I'm on my third passport. That is precisiely why I do not want a European or Japanese health care system. I look at healthcare as a luxury item which I am able to afford. I do not want to turn my healthcare decisions over to a doctor whose only incentive is not to spend my own money not treating me.
And the reason why the French may seem healthier than us is because as soon as they get sick, they die. You don't see many old, obese, or infirmed French hanging out at sidewalk cafes. The faster they die, the less money is drawn from the system.
I understand that car wreck victims and women delivering babies get speedy service, though.

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Aging Baby Boomers and the Housing Bubble: Epic Transition

Aging Baby Boomers and the Generational Housing Bubble: Foresight and Mitigation of an Epic Transition

Authors: Dowell Myers ^a; SungHo Ryu ^b (Show Biographies)

Affiliations:	a School of Policy, Planning, and Development, University of Southern California,
	b Southern California Association of Governments,

DOI: 10.1080/01944360701802006

Publication Frequency: 4 issues per year

Published in: Journal of the American Planning Association, Volume 74, Issue 1 December 2008 , pages 17 - 33

First Published on: 31 December 2007

Previously published as: Journal of the American Institute of Planners (0002-8991) until 1979

Previously published as: Planners' Journal until 1943

Abstract

Problem: The 78 million baby boomers have driven up housing demand and prices for three decades since beginning to buy homes in 1970 and continuing up the housing ladder. What will happen when boomers begin to sell off their high-priced homes to relatively smaller and less-advantaged generations?

Purpose: This article presents a long-run projection of annual home buying and selling by age groups in the 50 states and considers implications for communities of the anticipated downturn in demand.

Methods: We propose a method for estimating average annual age-specific buying and selling rates, weighting these by population projections to identify states whose growing proportions of seniors may cause an excess of home selling sooner than others. We also analyze the likely supplier responses to diminished demand, and recommend strategies for local planners.

Results and conclusions: Sellers of existing homes provide 85% of the annual supply of homes sold, and home sales are driven by the aging of the population since seniors are net home sellers. The ratio of seniors to working-age residents will increase by 67% over the next two decades; thus we anticipate the end of a generational housing bubble. We also find that younger generations face an affordability barrier created by the recent housing price boom. With proper foresight, planners could mitigate what otherwise could be significant consequences of these projections.

Takeaway for practice: The retirement of the baby boomers could signal the end of the postwar era for planning, and reverse several longstanding trends, leading decline to exceed gentrification, demand for lowdensity housing to diminish, and new emphasis on compact development. Such developments call planners to undertake new activities, including actively marketing to retain elderly residents and cultivating new immigrant residents to replace them.

Research support: The Fannie Mae Foundation.

Keywords: baby boomers; aging; housing bubble

Introduction

The giant baby boom generation born between 1946 and 1964 has been a dominant force in the housing market for decades. This group has always provided the largest age cohorts, and has created a surge in demand as it passed through each stage of the life cycle. As its members entered into home buying in the 1970s, gentrification in cities and construction of starter homes in suburbs increased. Their subsequent march into middle age was accompanied by rising earnings and larger expenditures for move-up housing. Looking ahead to the coming decade, the boomers will retire, relocate, and eventually withdraw from the housing market. Given the potential effects of so many of these changes happening in a limited period of time, communities should consider how best to plan this transition.
Communities in the United States face an historic tipping point. After decades of stability, we expect the ratio of seniors to working-age residents to grow abruptly, increasing by roughly 30% in each of the next two decades. We also expect that this change will make many more homes available for sale than there are buyers for them. The exit of the baby boomers from homeownership could have effects as significant as their entry, though with different consequences.
Recent discussion of the housing market has focused on price escalation and the creation of a housing “bubble” (Case & Shiller, 2003). During the extraordinary run-up in housing prices from 2000 to 2005, the business pages were filled with concern that this supposed real estate bubble might burst. The meltdown of mortgage markets in 2007, led by the subprime sector, has heightened anxiety about foreclosures and price reductions. Certainly this set of recent developments is cause for concern, but a larger and longer-lasting generational correction looms ahead. The changes in the housing market following the retirement of the baby boom generation could provide a context for local planning and development in the next quarter century that is very different from the last.
Urban planners have special responsibility for championing the longer view, as underscored by Hopkins and Zapata (2007). “As planners we want to work with constituencies to engage and shape futures, not merely stumble upon these futures as they emerge. To shape futures, we must imagine them in advance and understand how they might emerge” (p. 1). Most plans have time horizons of 5 to 20 years. Nelson (2006) recently called for planners to take the lead in adopting a longer view, asserting that the built environment will be wholly remade in the next half century, and urging planners to place their incremental decisions in this longer perspective. Such a long-term outlook is very different from that of business forecasting, which typically informs real estate market analysis. Such forecasting rarely looks beyond 1 year.¹
Analyzing the implications of demographic trends driven by human aging can help planners envision the changes ahead (Masnick, 2002; Myers & Menifee, 2000). The aging of the baby boomers has been foreseen for decades, but was for many years too distant to cause much concern except about its possible consequences for Social Security. The passage of time has brought the issues closer, and it may now be appropriate for urban planners to emphasize the broader implications of this major demographic change. Only a few planners have considered what an aging society might mean for transportation, land use, or other planning concerns (Giuliano, 2004; Rosenbloom, 2004). The first wave of baby boomers will reach age 65 (the dividing point between what we term “elderly” or “seniors” and working-age adults) in 2011, with the last of this generation scheduled to cross that threshold in 2029. Meanwhile the ratio of seniors to younger adults will surge to unprecedented levels, affecting all aspects of community life in which these two groups are systematically different.
We consider the implications of this transition by viewing it through the lens of homeownership. One key question is whether the growing numbers of seniors will generate more home sales than the housing market is able to absorb. Specifically, we aim to identify the point at which boomers will begin to offer more homes for sale than they buy, with potentially serious consequences for the housing market. We project when this will occur in all 50 states, taking into account each state's age specific population growth and prevailing patterns of home buying and selling.
We begin by discussing the recent boom in housing prices and the growing gap between an older generation with high housing equity and a younger generation who find housing increasingly unaffordable. We review the notion of a housing price bubble and consider whether a generational housing bubble might exist. We present the age-specific annual rates of buying and selling homes in each state, and use them to create long-term projections. Finally, we discuss the planning implications of these possible futures.

Background

Aging Baby Boomers and the New Dominance of the Elderly

  Since it began, the giant baby boom generation has been a dominant factor shaping housing markets. Frequently described as resembling a pig passing through a python, this large bulge of population surged slowly through the age structure. We focus on the adults most likely to own homes by excluding all those age 24 and younger.² After 1970, the leading edge of the baby boomers turned 25 and entered the market for homeownership. Figure 1 shows growth in the U.S. population over seven decades, both overall and partitioned into those between ages 25 to 64 and those 65 and older. Figure 1 shows that in all decades save the 1960s, a single age group, the leading edge of the baby boomers, accounts for half or more of U.S. population growth.
Between 1970 and 1980, as the baby boom children came of age, the population age 25 and older increased by 22.9 million, more than twice the growth of 10.6 million witnessed between 1960 and 1970. Whereas the largest adult growth in the 1960s was in the group aged between 55 and 64, growth in the 1970s in the 25 to 34 age group was four times greater, and many of these individuals were forming new households and buying homes. This sudden surge in demand drove several housing market trends, spurring new apartment construction, gentrification in cities where young adults congregated, and escalation in house prices in metropolitan areas where increased supply was limited by topography or regulatory constraints. In subsequent decades the leading edge of the baby boom advanced to progressively older age groups, each time contributing half or more of the total population growth in that decade. As the cohort grew older and achieved their peak earnings, they increased demand for move-up housing for families with older children and higher amenity housing for empty nesters with mature tastes.
 

[Enlarge Image]

Figure 1. Growth in United States population age 25 and over for each decade from 1960 to 2030 (in millions): Source: U.S. Census Bureau, 2003b, Tables 12 and HS-3. After 2010 the leading edge of the boomers will pass age 65 and growth among the elderly population will substantially exceed that of younger adults, an unprecedented social and economic development. This is best seen in the ratio of those aged 65 and older to working-age adults (aged 25 to 64). After decades of relative stability, this ratio will surge 30% in the 2010s and a further 29% in the 2020s (Myers, 2007), altering the balance to which we have long been accustomed. Here, we emphasize how this surging ratio will increase the number of older home sellers relative to younger home buyers, and focus on deciphering what this age shift implies for trends in homeownership, and what responses are possible for planners. Although the phenomenon affects every state (Frey, 2007), its effects will vary somewhat across the nation. For example, from 2010 to 2030, the ratio of seniors to younger adults is expected to rise 59.0% in New Jersey, 64.0% in Ohio, 66.4% in California, and 82.4% in Arizona, a magnet for retirement migration. (For details on every state see the Appendix.)

Demographics and Housing

  Relations between age and housing demand are central to studies of demographics and housing (Myers, 1990). Housing demographers focus especially on age because mobility declines sharply with age, and because different age groups typically occupy different types of housing (Clark & Dieleman, 1996; Gober, 1992; Masnick, 2002). Of greatest relevance to this analysis are the interactions between age and homeownership (Chevan, 1989). Homeownership rates rise with age, and do not generally peak until after age 65. John Pitkin's (1990) study of elderly homeownership was especially notable for showing how most variation in homeownership among older age cohorts over time is explained by demographic factors and inertia from prior decades, while current economic factors add small but significant effects at the margin.
The experience of two Harvard economists, one who later became chair of the Council of Economic Advisers, suggests it is dangerous to attempt to predict long-term trends in housing, unless the demographics are well handled. Mankiw and Weil (1989) predicted a 47% decline in house prices during the 1990s, based largely on their modeling of declining demand as baby boomers aged. Instead, we have seen baby boomer demand for housing grow and prices double. Housing economist Karl Case recently called the Mankiw-Weil prophecy “one of the worst forecasts in the history of mankind” (Carmichael, 2007, p. 2). Their approach used cross-sectional analysis improperly to predict trends for age cohorts.³ Although economists have avoided long-term forecasts since Mankiw and Weil's experience, longitudinal inferences about housing demand can still be made with cross-sectional data if we are careful (Myers, 1999). Indeed, planners should attempt careful, forward-oriented analysis so as not to make major policy errors and to avoid either undue pessimism or unwarranted optimism (Krainer, 2005).

Short-Term Correction and a Generational Housing Bubble

  We argue that the United States is currently experiencing a short-term housing market bubble that is nested within a longer-term, generational housing bubble of greater magnitude. The recent housing price boom has been remarkably strong. From 2000 to 2005, the median sales price reported by the National Association of Realtors rose 48.6% nationwide, and in some areas, such as California, the median sales price rose 117.1%. Only in 2007 did prices begin to slip in particular metropolitan areas and nationwide. This price run-up had a two-edged effect that substantially increased the home equity of existing homeowners while at the same time making housing less affordable for would-be home buyers. The result is a sharply increased generation gap, with the baby boomers largely gaining, while members of younger generations face higher affordability hurdles.

Short-Term Housing Cycles

  According to Case and Shiller (2003), the term housing bubble “refers to a situation in which excessive public expectations of future price increases cause prices to be temporarily elevated” (p. 299). In a housing bubble, expectations of price appreciation feed further escalation of prices; people buy houses for “future price increases rather than simply for the pleasure of occupying the home. And it is this motive that is thought to lend instability to bubbles, a tendency to crash when the investment motive weakens” (Case & Shiller, 2003, p. 321).
Underlying the increases are changes in market fundamentals, or what Shiller (2005) calls “precipitating factors”: increases in employment or income in the area, increases in population, reductions in financing costs, or reductions in land permitted for development. Over the long run, housing construction is closely linked to growth in population, though it can be constrained by recession or by regulatory constraints. There are also substantial lag effects, and the age group experiencing the most growth disproportionately influences the type of housing constructed (Campbell, 1966).

Regulatory Effects

  A number of economists have recently addressed the price effects of regulations that restrict new construction (Glaeser, Gyourko, & Saks, 2005; Green, Malpezzi, & Mayo, 2005; Quigley & Raphael, 2005). Local activism to protect the environment and protect local livability has caused many communities to add development restrictions since 1970 (Fulton, Shigley, Harrison, & Sezzi, 2000). This was especially true in California, where population grew rapidly in large metropolitan areas, but surrounding water and mountains set physical limits to urban expansion and were protected as resources.
Over the years, both demographic pressure for more housing construction and regulatory restrictions increased. When demand increased during expansionary phases of the business cycle and was not met quickly by increases in supply, housing prices surged. The corrections that followed were rarely as large as the price surges, amounting most often to a few years of price stagnation, not sizable busts, and thus prices have ratcheted upward over the long term.⁴

Role of Young Adults

  The numbers of young adults in the population and their home-buying behavior are especially important in driving these price trends. They make up the principal reservoir of new demand in the marketplace, a pool of first-time home buyers poised to enter the market or not, depending on perceived conditions. When market fundamentals drive housing prices up, word of mouth and the fear that rising prices will make future purchases unaffordable amplify the trend. As a result, the number of buyers in the market increases to include both speculators ⁵ and young adults accelerating their entry into homeownership. Thus, paradoxically, because of the investment incentive, homeownership generally rises when housing prices are rising rather than when housing is becoming more affordable. A study of changing homeownership rates among young adults in the 1980s and 1990s found that in states where prices had increased substantially, homeownership rates declined very little or even rose, whereas in states where prices had declined markedly, homeownership rates plunged by 10 to 20% (Myers, 2001).⁶ Potential buyers in declining markets had an incentive to wait for prices to bottom, while those in booming markets felt pressure to accelerate their purchases, to get on board before the train left the station. Thus the housing market's volatility is amplified by buyers' responses to trends in market fundamentals.
Housing markets depend on the ability of the young to buy homes, but they face greater challenges in some parts of the nation. Figure 2 shows, for each of the states, the ratio of the median value of all owner-occupied homes to the median income of households with heads between the ages of 30 and 34 in 2000 and 2005.⁷ This ratio allows us to compare housing prices in different places and over time, and focuses attention on the potential buying power of the generation entering the housing market. House prices in New Jersey nearly doubled, for example, going from 2.89 times the median household income of this group of young adults in 2000 to 5.00 times their income in 2005. Although prices increased in virtually every state between 2000 and 2005, the spikes in some states are clearly evident. The already high-cost states of California and Hawaii became nearly twice as expensive between 2000 and 2005, with median housing value increasing to roughly 9 times the median income of young adults. A second tier of expensive states, with ratios of 5 or greater, includes Nevada in the West and Massachusetts, Rhode Island, and New Jersey in the Northeast. A third grouping has ratios greater than 4 in 2005: Arizona, Colorado, Oregon, and Washington in the West, Florida and Maryland in theSouth, and Connecticut and New York in the East. Much of the nation, however, still had low ratios of housing prices to incomes, even after the boom years.
 

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Figure 2. Ratios of median home values to median incomes of household heads aged 30 to 34 in 2000 and 2005, by state: Sources: U.S. Census Bureau (2003a, 2005a).

The Generational Housing Bubble

  The current gap between generations has grown unsustainable, and the risk of a generational housing bubble now compounds the risk of a shorter-term housing bubble. The recent upsurge in prices is so extreme in many states, and has been so abrupt, that many real estate observers fear a sharp downward correction.⁸ Not only do increased housing prices pose a particular challenge to young households entering the market, but also financing terms became much less favorable after 2005. What have not been recognized to date are the grave impacts of the growing age imbalance in the housing market. If the elderly are more often home sellers, and are more numerous than the young who are buyers, a market shift could come on quickly after 2010, causing housing prices to fall. Even if prices remain flat, without the investment incentive young households will likely slow their entry into homeownership, worsening the imbalance between sellers and buyers. Once past the tipping point, market adjustments will cascade in virtually every community, as the ratio of seniors to working age adults will increase for the greater part of two decades.

New Data on Buying and Selling by Age Groups

  Those aiming to anticipate the future of housing markets commonly extrapolate trends obtained by comparing homeownership rates and numbers of homeowners at two different times. Yet these indicators compare housing stocks at different times rather than flows of annual activity. The stock of housing would adjust only gradually even if the annual flows changed abruptly, and thus is not a very sensitive indicator. In fact, even if the number of homeowners remained constant over time, demand would exist for trading up and trading places. Thus, homeownership rates are insufficient for understanding the future of housing markets, and could be misleading.
Instead, we use annual per capita rates at which people of differing ages sell and buy homes, to allow us to project what will happen to the housing market as the demographic profile of the nation changes. These rates are estimated for the period 1995 to 2000, under the assumption that this period yields an expression of more normal market behavior that can be expected to prevail in future years than behavior in the boom years of 2000 to 2005 or the recession years of 1990 to 1995. Sales rates are difficult to know because sellers relocate after they sell and cannot be surveyed. As a result, far more is known about recent buyers. But to understand the market, we need comparable information about both buying and selling. Thus we employed a new method.
We began by assembling 2000 Census sample data for individuals. Our data represented the complete Census sample for each 5-year cohort between the ages of 15 and 85 and older, in each state. We also knew whether these individuals were householders (the persons owning or renting the unit where the household lives), their housing tenure in 2000, the length of time they had lived at their 2000 residence, and the state where they had lived 5 years earlier. We estimated the number of home purchases between 1995 and 2000 in each age cohort, for each state, as the number of householders who were also homeowners and had occupied their homes for less than 5 years, adjusting for those who purchased more than one home for occupancy in this interval. We estimated the number of home sales, again for each age cohort, for each state, in two ways. First we assumed that home buyers were also previous home sellers, after adjusting for the estimated share that are first-time homebuyers (as derived from the American Housing Survey). We assigned their sales to the states where they had reported residing 5 years earlier, whether or not that was where they had purchased a new home. In addition, for those over age 60, we compared the number of homeowners in 2000 to the number of homeowners in the same cohort when it was 10 years younger in 1990. We considered this difference to be a measure of all the home sales that were not followed by purchasing another home, but by renting, moving to a retirement home, or death.
To use these rates of purchase and sale with population projections, they must be estimated on a per capita, not per household, basis. Thus we divided the purchases and sales in each age group for each state over the decade⁹ by the average size of the cohort during the decade, and then converted this to average annual rates of buying and selling.¹⁰
Figure 3 displays the annualized, age-specific rates of buying and selling homes per 100 people we calculated for the nation as a whole. The highest buying rate (3.6 purchases per year per 100 persons) occurs between ages 30 and 34. From this peak, rates of buying homes gradually decline at later ages. Readers may find it surprising that the per capita rate of home buying remains as high as it does among the elderly. Over 1% of people aged 75 to 79 buy new principal residences in any given year. Nonetheless, the likelihood that a person in this age group will sell an owner-occupied home is more than three times higher than the likelihood that they will buy a home. At age 80 and above the annual rate escalates to nearly 9 home sales per 100 people.¹¹ However, until age 70 the annual sell rate remains at about 2% per year for a remarkably broad range of ages.
For most of the modern American lifespan the rates of buying and selling are closely related, because most of those who sell a home then replace it by buying another. However, below age 50, buying is more common than selling, and net homeownership rates rise to this point. When people enter their late-50s and early-60s, as the leading edge of the baby boom generation has now done, buying and selling are in balance. Among individuals in their mid-60s sellers come to outnumber buyers before selling dominates among those in their 70s and beyond. Among people of the same age, sellers come to exceed buyers at about age 65 nationwide, but this varies markedly by state, as shown below.
 

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Figure 3. Average annual percent of persons buying and selling homes in each age group, for the United States, 1995 to 2000: Note: On average, 8.8% of persons 80 and older sold homes each year.

Projections of Future Numbers of Buyers and Sellers in the 50 States

  We now apply our estimates of buy and sell rates in each age group to projected state populations in the same age groups to anticipate the future of home buying in each state. This approach assumes that the age-specific home selling and buying rates of the late 1990s reflect long-run average behavior.¹² Although metropolitan regions are generally regarded as the best geographic units for representing housing markets, data limitations lead us to focus on states. Below, we review variations among the states that reflect many of the same differences that we can observe among metropolitan areas and regions in the nation. We then compare projected numbers of home buyers to sellers for the 50 states.

State Variations in Annual Buy and Sell Rates

  It is reasonable to expect that rates of buying and selling would not be the same across all states. States with higher overall homeownership rates surely have higher rates of home buying and, later, greater home sales. Also, states with more affordable housing might be expected to have higher rates of home buying among young people.
Although growth in the population of seniors in most states results mostly from people aging in place (Frey, 2007), a few states are retirement destinations, likely causing them to have higher rates of home buying among older age groups than other states. Conversely, states with cold climates or more congested living environments may find their elderly residents selling homes at earlier ages to escape unpleasant living conditions.
We compare buying and selling in the following states (each shown with its 2005 ratio of median housing prices to median household income among adults ages 30-34 from Figure 2): Arizona, a retirement state (4.13); Ohio, a midwestern state, low-cost but cold (2.75); New Jersey, a high-cost eastern state (5.00); and California, a western, very-high-cost state (8.65). As predicted above, Arizona stands out for its exceptionally high buy rates, especially at older ages, which reflect its rapid population growth and high retirement in-migration (see Figure 4). In the other three states home buying rates peak when people are in their 30s and fall as individuals approach their retirement years. However, Ohio, the low-cost state, has home buying rates that are substantially higher among residents in their 20s and early-30s. California, by contrast, has very low home buying rates among its young adults. This is not surprising given that California's extremely high housing prices require young adults to save longer for larger down payments, and advance further in their careers until they earn the higher incomes required to support large mortgage payments. California's buying rates in middle and older ages are somewhat higher than New Jersey's or Ohio's, likely because buying has been delayed. New Jersey has home buying rates among young adults midway between those of Ohio and California, reflecting its intermediate housing prices, but has the lowest rates of home buying among older residents.
 

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Figure 4. Average annual percent of persons buying homes in each age group, for selected states, 1995 to 2000. Turning to home selling (see Figure 5), Arizona's high rates stand out among middle-aged persons. Since sales by those from outside the state are counted in their previous state of residence, these represent sales by repeat buyers in Arizona.¹³Arizona has long had some of the highest residential mobility rates in the nation, and so this pattern of high rates of selling and buying is not surprising.
The patterns in the other three states are even more similar than they were for buying rates. In middle age, about 2% of people sell their homes each year, although the rate is a bit lower in New Jersey, just as it was for home buying in this age range. California's lower sales among young adults follow because they also have lower buying rates. After age 60 or 70, all four states exhibit rising home selling rates that appear roughly similar.
To understand the future home selling of the giant baby boom generation as they reach age 65, we compare net rates of buying or selling at ages 65 to 69 across the states. Figure 6 displays these rates in a bar graph ranking states within four regions. The states range from Nevada, with a net buying rate of 1.56% per year, to Connecticut with a net selling rate of 1.02% per year.
In general, very substantial net selling prevails among people of this age across the states of the Northeast and Midwest. In the South, only Maryland and Louisiana have similar rates of net selling, while Florida has very substantial net home buying at ages 65 to 69, far ahead of its closest southern rival, South Carolina. In the West, only California and Alaska have substantial net home selling among people aged 65 to 69. Most of the other western states, led by Nevada and Arizona, have net home buying among people of these ages.

Crossover Point: The Age at Which Selling Surpasses Buying

  We begin our analysis of the timing of the baby boomers' impact on the housing market by finding the age at which selling typically begins to exceed buying in each state, shown in Figure 7. In some states the elderly are such active buyers that their growing numbers will not lead to an excess of sellers. In others states, however, the buyers fall behind the sellers at an early age. In six states, the number of sellers begins to exceed buyers at ages 55 to 59, while in seven states sellers exceed buyers at ages 60 to 64. Five of the states that reach this point before age 65 are located in the Northeast and five are in the Midwest, with Alaska, California, and Maryland rounding out the group. Thus, it is a mix of the coldest, most congested, and most expensive states, rather than high-growth states of the South or West, which we expect to lose older homeowners most rapidly. The northeastern states lead the way, and are shaded for emphasis.
 

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Figure 5. Average annual percent of persons selling homes in each age group, for selected states, 1995 to 2000: Note: On average, between 8 and 9% of persons 80 and older sold homes each year in all these states. In 22 states crossover occurs when people are between 65 and 69. Another 15 states, all in the South or West, have crossover points after age 70, occurring latest in Arizona, Florida, and Nevada. This reflects the historically higher rates of migration toward the South and West, and historically higher retirement out-migration from the Northeast and Midwest. If the baby boomers behave similarly at these ages, their effects on the housing market should exhibit strong regional differences.

Net Excess of Sellers Over Buyers in the 50 States

  The ultimate number of sales and home purchases by owner occupiers in a given time period is the product of each state's unique profile of buying and selling rates per capita and the forecasted population for each age group at that point. Some states may have high rates but few people in the relevant age groups. Of greatest importance is whether a state has a growing or static population of young adults to absorb the homes its senior population will sell. The worst case would occur where the older population is numerous and sells its homes at an early age, but the young adult population is growing slowly or not at all, and has a low rate of home buying.
We used population projections for future periods to calculate when we expect home sellers to begin to exceed home buyers in each state, and Figure 8 summarizes the results. Six states have already entered long-term buyer shortages, withseven more to follow in the next decade. However, for 30 states, we do not expect the number of buyers to fall below the number of sellers until well after 2025.

Construction and Market Response

  The foregoing analysis centers on the magnitude of the sell-off among owner-occupants who are baby boomers. In fact, buyers will likely appear for every house because the price will be lowered until the market clears. If prices fall low enough, home buying rates may rise, sellers who are able to remain in their homes may decide to keep them, and investors may step in to claim some properties. If rices fall we also expect home builders to scale back on onstruction, reducing the growth in supply. The questionis whether these adjustments will be sufficient to cushion the baby boomer sell-off.
Reasonable observers might view the problem thus:

…in the long run at least, contraction in the real estate industry may mitigate any impacts of overall decreases in housing demand. The question appears to be whether the impacts of the demographics will result more in industry contraction or in declines in value.¹⁴

 

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Figure 6. Net annual percent of persons aged 65-69 buying or selling homes, by state and region. Shiller (2007) stresses the importance of supplier responses in ending housing booms. Though past failures to appreciate the competition from other new construction have often led to oversupply, he asserts that large development companies today possesses better information and behave more rationally than in prior decades, as McCue and Belsky (2007) agree. In fact, in the post-2005 housing market, when sales fell and inventories grew, builders exhibited a disciplined response, scaling back production only 6 months behind the decline in sales (Harvard Joint Center for Housing Studies, 2007). Unfortunately, that decline was so precipitous that many home builders were caught with greater debt than cash flow.
It is often overlooked that existing homeowners supply five or six times as many homes for sale as do builders of new homes.¹⁵ Existing homeowners' decisions to sell are not professionally managed, but are driven by personal financial, community, and aging-related life-cycle decisions. The many baby boomers facing these same issues in the future could flood the market with excess supply without regard to declining demand.
Undesirable effects could be magnified by the duration of the baby boomer sell-off. Homebuilders are more likely to survive a short-term pullback than a prolonged contraction that requires them to lay off core staff, abandon land contracts, and sell assets. Firms in the construction industry will attempt to keep building homes at some minimal level just to stay in business. For example, after 2 years of job losses totaling 313,000 in the long recession of the 1990s, production in California only fell to 83,341 new units in 1993, still roughly half the previous volume.
Finally, construction is likely to continue because home builders are in the business of serving buyers whose needs cannot be met by the existing inventory. The fact that older people outnumber younger people nationally (see Figure 1 and Appendix Table A-1) ensures that most builders will try to serve the former by building housing better suited to their needs than what is already on the market. Although the older population will be selling more homes than they buy, better than 1% of them will still buy homes each year. And younger people will still buy homes at three times this rate. People may demand new construction in order to get novel design or to locate in growing areas where supply is insufficient, or in locations with better access to jobs and transit.
 

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Figure 7. Crossover points: ages at which selling exceeds buying for each state: Note: Shaded states are in the Northeast. Buyers and sellers are owneroccupants, and do not include investors or those buying or selling second homes. In sum, supply will be dominated by the actions of aging homeowners who have little ability to postpone decisions, and home builders who cut back as little as possible. Large builders will shift to markets with good growth prospects and scale back their operations elsewhere. Other builders will find niches of underserved demand, particularly among the elderly, even in stagnant or declining markets. Thus we expect the number of properties for sale to grow ever larger, creating a buyer's market, and vacancies to accumulate in less desirable neighborhoods and parts of the nation.

Consequences of a Generational Housing Price Correction

  There will be winners and losers in the correction to the generational housing bubble. Many young adults will wait for downward price adjustments to make home purchases more affordable. However the baby boomers were born over an 18-year period, and their housing sell-off could stretch over two decades instead of the typical 3 to 7 years for a housing market correction. Few young adults are likely to wait that long for prices to bottom out before purchasing.
 

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Figure 8. Period in which sellers exceed buyers in each state: Note: Shaded states are in the Northeast. Buyers and sellers are owneroccupants, and do not include investors or those buying or selling second homes. Members of the baby boom generation themselves who are homeowners could be losers. As home values decline, so will home equity, shrinking retirement savings. For example, Nothaft and Chang (2004) recently reported that

home equity—the difference between the home value and the amount of mortgage debt on the property—comprised at least 50% of net wealth for one-half of all households. Home equity is not only the single largest component of net wealth for most families, but it is also held by a broader cross section of families when compared with other assets. (p. 2)

Home equity is less important for high-income households, because they hold a disproportionate share of stocks and other investments, but it is especially important for working- and middle-class households. Moreover, equity may be more vulnerable to downturns than in prior decades. The ease of refinancing or obtaining home equity loans has led many middle-class homeowners to already use up substantial portions of their equity. Analysis of recent trends indicates that many more of the soon-to-be-elderly will be heavily encumbered with debt late in life than has been the case in the recent past (Masnick, Di, & Belsky, 2006). A 25% reduction in home values could erase half the equity of homeowners with large mortgages.¹⁶ Even among those who do not sell their homes, downward reappraisal will erode the equity that would otherwise have supported reverse mortgages or home equity loans (Edmunds & Keene, 2006). People who intend to retire using these means of extracting income from their wealth must maintain or increase the value of their homes.

Implications for Local Planning

  Communities where home sellers are highly concentrated could be adversely affected by the developments we describe. Our analysis compared the 50 states, and yet we know that substantial variation exists within states, with important differences among cities, suburbs, and rural areas. Given that all housing markets are local, we make the following observations about the potential local impacts and their implications for planners.
Where demand falls short of housing supply, property value assessments could fall after increasing for many years, creating municipal budget deficits and playing havoc with fiscal planning. Although it seems wise for states and localities to use current fiscal surpluses to pay down debt and save for later, this is often difficult for local governments to do. In addition, shifts that abruptly make formerly high-priced properties more affordable will create a different set of problems that could destabilize middle-class neighborhoods. We already know that aging homeowners do less to maintain their homes (Galster, 1987; Myers, 1984), and under the scenario we anticipate there may be many more such homeowners who are unable to sell. If they rent their homes or sell them to investors at a discount, neighborhoods once largely owner-occupied will have more renters. During the adjustment process many homes could stand empty for long periods, creating neighborhood nuisances. Beleaguered homeowners will put pressure on local officials to protect their former quality of life. Yet there are a number of ways to plan in advance both to mitigate symptoms and to address the root of the problem.

Plan Housing Construction

  Anticipating the consequences of an aging baby boom generation should help planners manage the supply of new construction to meet future housing needs and balance the demands of competing interests.

Recognize New Housing and Locational Preferences

  After decades of neglect, apartment construction is resurgent in many central cities (Birch, 2002), meeting preferences for housing that is higher density and more centrally located. Fishman (2005) has declared this a new “fifth migration” that will focus residential growth in coming decades toward the centers, not peripheries, of metropolitan areas. To date, however, there is little evidence of any net shift of total or elderly population toward central cities (Englehardt, 2006; Frey, 2007).
Nelson (2006) called for analyzing both housing preferences and the location of existing inventory to determine needs for new construction. Our analysis provides the demographic driver for these needs and preferences in the aging of the baby boom. Our projections support Nelson's conclusion that the existing supply of large-lot homes, largely located in the suburbs, may be sufficient to meet needs through 2025, at least in many parts of the nation. New construction should remedy the current undersupply of units in the more compact central city and suburban environments shown to be in growing demand, especially for aging boomers (Myers & Gearin, 2001).

Regulate Overall Supply

  If the aging baby boomers sell one type of housing and buy another, this could stimulate substantial construction. Since decisions about new construction are generally decentralized, this could lead to oversupplies of housing in many metropolitan areas. The excess vacancies would likely be clustered in localities with older and less-preferred housing. This could reverse the post-WWII pattern in which new construction in the suburbs left vacancies and abandonment concentrated in older central city neighborhoods.¹⁷ Some are already warning of decline in early post-WWII suburbs (Lucy & Phillips, 2006), but planners should monitor supply and demand conditions in outer suburbs as well. Planners in the near future may contend simultaneously with neglected low-density single-family districts, dwellings left vacant by waves of exiting baby boomers, and controversial proposals for redevelopment at higher densities.
In the past, development restrictions have protected against oversupply, although they have also led to housing price escalation and decreased affordability. A growing movement aims to relax those restrictions in order to facilitate denser development and make housing more affordable. Although these objectives have merit, planners should evaluate the consequences of making such changes in the context of the long-term decline in housing demand predicted here. How ironic would it be if, after years of price run-ups, development restrictions were suddenly loosened in many states just in time for baby boomers' big sell-off? Local and regional planners should manage additions to the supply of housing to avoid a glut as baby boomers age.

Fight the Rising Ratio

  In addition to managing the construction of new housing, local planners should work on managing the ratio of seniors to working-age residents directly. Planners should aim to alleviate the potential impacts of large numbers of elderly home sellers while stimulating demand among younger adults.

Plan to Retain Elderly Residents

  Frey (2007) has emphasized that most people will age in the same state or metropolitan area where they have lived, though not necessarily in the same community or house. Communities should retain their elderly residents as long as possible to slow the flow of houses for sale. This makes it imperative to develop elderly friendly, vital communities (Achenbaum, 2005). Rather than encouraging segregation of the elderly in separate retirement institutions, urban designers should foster their social integration into more lively communities, whose essential features include community activity centers for seniors, close-by retail services, and small, easy-access parks for midday socializing. The new movement toward planning healthy cities for active living can also help planners attract and retain elderly homeowners (Frank & Engelke, 2001), as can homeowner maintenance programs, dial-a-ride transportation services, and mobile meals services (Gilderbloom & Rosentraub, 1990).

Attract the Young

  Planners should also aim to attract younger home buyers by increasing local employment growth, marketing to the “creative class,” (Florida, 2003) and building a cultural economy (Currid, 2007; Markusen & Schrock, 2006). Strategies to improve amenities and urban livability may appeal to some, but families also need practical help with convenient day care, afterschool programs, and better local schools. Workforce housing programs can help young people absorb more of the homes for sale in a community by providing counseling and purchase assistance. It would be more effective to institute such programs early, before an excess of homes for sale tarnishes the community reputation and deters middle-class buyers.

Attract New Immigrants

  Fostering the settlement of new immigrants can also stimulate home buying. Immigrants are typically drawn to concentrations of job growth, but have also taken root in places experiencing average job growth or worse (like the populations of Somalis in Lewiston, Maine, and Hmong in Fresno, California). Once a group is established, it may pull in more residents of the same ethnicity. Thus, community development strategies to promote immigrant settlement can help build a base of young residents. Per capita rates of homeownership rise dramatically as immigrants reside longer in the United States, and immigrant populations are growing faster than native-born populations (Myers & Liu, 2005). As a result, the foreign-born share of the increase in homeowners has roughly doubled each decade since 1980, rising from 10.5% in the 1980s, to 20.7% in the 1990s, and 40.0% in the period 2000 to 2006 (Myers & Liu, 2005, Table 2).¹⁸ These shares are even higher in several states, exceeding 60% in California, New York, New Jersey, Massachusetts, and Illinois, and they will climb much higher after the baby boomer sell-off commences. It is immigrants who will lead many markets out of the current downturn inhome sales and prices.

Invest in the Young

  The foregoing strategies merely help one community compete against others for a fixed number of potential home buyers. A longer-term strategy would expand the numbers of home buyers among the younger generation by investing in their human capital development. A state that invests more in higher education not only trains a workforce with greater earnings potential, but also cultivates the next generation of taxpayers and home buyers. Tax dollars invested today in higher education are reported to return benefits two or three times greater than the original investment, in the form of future tax collections on higher earnings (Myers, 2007). College graduates can also afford substantially higher priced homes. Upgrading human capital among young adults will be especially crucial as the ratio of seniors to working-age adults grows. Previously neglected minority youth will benefit, as will the rest of society, if state and local governments enhance the productivity of all their human resources.

Conclusion: On the Precipice of a New Era

  Our analysis depicts a coming generational transition in the housing market that will upset the historic balance of buyers and sellers. Residents in most states are net buyers of homes well into their 50s. The resulting upward pressure on demand by the large baby boom generation will soon peak, and after age 70 they will be net sellers in all except three states. Mankiw and Weil (1989) may have miscalculated the timing of decline, predicting its beginning 20 years or more prematurely, but the baby boomers will finally start retiring from the housing market. Their demand for housing will begin to contract, and then will decline at an accelerating rate. Boomers will dominate the housing market, as they have through their entire adult lives, when the ratio of seniors to working-age adults soars by 67% in the next two decades. This tilt toward age groups that are net sellers of housing is historically unprecedented, and it challenges planners to foresee and forestall adverse impacts.
The baby boom generation was born over a period of 18 years, and once its sell-off commences, it could dominate the housing market for up to two decades. Planners could lessen the negative consequences of the deflating generational housing bubble by anticipating these long-term trends and initiating pre-emptive programs to retain elderly homeowners, attract young home buyers, and closely monitor additions to the housing inventory to forestall overbuilding.
Planners must adjust their thinking for a new era that reverses many longstanding assumptions. Though planners in many urban areas have been struggling against gentrification, they may now need to stave off urban decline. Whereas decline once occurred in the central city, it may now be concentrated in suburbs with surpluses of large-lot single-family housing. Whereas residential development once focused on single-family homes, many states may swing toward denser developments clustered near amenities. Whereas the major housing problem was once affordability, it could now be homeowners' dashed expectations after lifelong investment in home equity. The new challenge may be how to encourage buyers in distressed environments and how to sustain municipal services in the face of declining property values. All of these reversals result from the aging of the baby boomers. By using foresight, planners have a better chance of leading their communities through the difficult transition ahead.

Appendix

  Ratios of seniors to working-age adults, and percent change, by state, 2000 through 2030.

	Seniors (aged 65 and up), per 1000 working-age adults (aged 25-64) in each year				Percent change each period
	2000	2010	2020	2030	2000-2010	2010-2020	2020-2030	2010-2030
Source: U.S. Census Bureau, 2005b.
Alabama	252	267	352	450	6.0	32.1	27.8	68.8
Alaska	104	152	248	316	46.2	62.8	27.5	107.6
Arizona	259	274	374	499	5.8	36.6	33.6	82.4
Arkansas	276	275	348	432	-0.3	26.7	24.0	57.1
California	204	219	284	365	7.7	29.7	28.2	66.4
Colorado	177	196	277	342	11.0	41.5	23.3	74.4
Connecticut	258	269	335	444	4.1	24.7	32.6	65.4
Delaware	247	262	355	499	6.2	35.3	40.7	90.3
District of Columbia	222	211	239	265	-5.0	13.3	10.9	25.7
Florida	342	340	437	600	-0.8	28.6	37.5	76.8
Georgia	179	191	254	329	7.0	33.0	29.6	72.3
Hawaii	251	276	387	493	10.1	40.1	27.6	78.7
Idaho	228	227	306	377	-0.3	34.5	23.3	65.8
Illinois	232	234	292	369	0.7	25.0	26.4	58.0
Indiana	240	241	304	378	0.5	26.1	24.5	56.9
Iowa	299	286	368	480	-4.4	28.8	30.4	67.9
Kansas	265	258	334	433	-2.7	29.4	29.7	67.8
Kentucky	236	242	318	407	2.6	31.6	27.7	68.1
Louisiana	229	243	324	418	6.2	33.1	29.1	71.8
Maine	267	279	389	540	4.2	39.6	38.8	93.7
Maryland	207	226	284	360	9.0	25.7	26.6	59.1
Massachusetts	252	253	324	431	0.4	27.7	33.3	70.3
Michigan	235	239	306	394	1.6	28.3	28.7	65.1
Minnesota	231	229	296	390	-1.0	29.3	31.6	70.1
Mississippi	243	244	324	430	0.7	32.5	32.6	75.8
Missouri	263	264	332	425	0.4	25.9	28.1	61.2
Montana	260	275	405	549	5.6	47.5	35.6	100.0
Nebraska	272	267	353	459	-1.6	32.2	29.8	71.6
Nevada	201	227	299	386	12.7	31.7	29.4	70.4
New Hampshire	219	229	318	430	4.6	38.6	35.4	87.6
New Jersey	245	250	308	398	2.0	23.1	29.2	59.0
New Mexico	231	271	412	601	17.5	51.9	46.1	121.9
New York	243	255	317	411	4.9	24.4	29.5	61.0
North Carolina	225	234	299	376	4.2	27.7	25.7	60.5
North Dakota	301	295	403	566	-1.9	36.4	40.3	91.4
Ohio	256	258	331	423	1.0	28.4	27.7	64.0
Oklahoma	261	267	341	420	2.3	27.6	23.2	57.3
Oregon	242	237	318	365	-2.0	33.7	15.0	53.7
Pennsylvania	302	292	365	474	-3.3	24.8	29.9	62.2
Rhode Island	281	266	331	446	-5.3	24.2	34.8	67.4
South Carolina	230	256	355	470	11.3	38.5	32.4	83.4
South Dakota	295	282	379	524	-4.3	34.2	38.2	85.5
Tennessee	231	249	326	405	7.7	31.0	24.2	62.6
Texas	194	203	264	328	4.5	30.1	24.5	62.0
Utah	189	190	249	296	0.8	30.7	19.2	55.7
Vermont	237	259	374	506	9.3	44.4	35.2	95.2
Virginia	205	231	307	391	12.9	32.8	27.5	69.3
Washington	210	222	297	362	5.7	34.0	21.7	63.1
West Virginia	289	290	396	505	0.3	36.6	27.4	74.0
Wisconsin	253	250	328	443	-1.5	31.4	34.9	77.3
Wyoming	224	255	404	562	13.5	58.8	39.1	120.9
U.S. Total	238	246	318	411	3.2	29.6	29.0	67.2

Notes

  1. Occasionally housing industry analysts will take a 10-year view. For example, in a recent special effort, a consortium of leading housing trade organizations forecasted the market for a full decade, from 2004 to 2013 (Berson, Lereah, Merski, Nothaft, & Seiders, 2006). Unfortunately, a 10-year forecast horizon was not long enough for this group, the Bureau of Labor Statistics, or the Economic Development Administration to anticipate the effects of the retirement of the baby boom generation. A 10-year forecast launched from 2007 might now begin to detect these consequences.
  2. According to the 2000 Census, only 1.4% of owner-occupied households in the United States were headed by a person under age 25. Age 25 is also generally regarded as the lower boundary of prime working age, when individuals are most likely to hold secure employment.
  3. In 1980, the highest per capita spending on housing occurred at age 45; accordingly, Mankiw and Weil (1989) concluded that once the baby boomers passed age 45 they would begin to spend less on housing, reducing housing demand and lowering prices as the boomers aged. But it turned out that lower spending on housing after age 45 was not a result of older adults cutting back. Rather, members of the generation that was over 65 in 1980 were unlike their younger counterparts in that they had never spent much housing. The fallacy of Mankiw and Weil's reasoning was revealed once researchers followed individual cohorts' behaviors as they grew older (Pitkin & Myers, 1994).
  4. A recent study by the Federal Deposit Insurance Corporation (Angell & Williams, 2005) reviewed historical housing booms in all U.S. metropolitan areas for which data were available and concluded: “In over 80% of the metro-area price booms we examined between 1978 and 1998, the boom ended in a period of stagnation that allowed household incomes to catch up with local home prices.”
  5. Those buying for investment purposes increase their market activity when prices are rising most rapidly and withdraw when prices flatten or decline. For example, between 2002 and 2005, when the recent boom began to crest, the investor share of mortgage originations grew from 6.8 to 10.9% in Los Angeles, from 5.8 to 13.8% in Austin, and from 8.1 to 15.8% in Miami (Harvard Joint Center for Housing Studies, 2007, Appendix W-4).
  6. There was a very strong positive correlation between changes in homeownership rates among heads of households aged 25 to 34 and changes in median house values for states, with r = 0.75 in the 1980s and r = 0.65 in the 1990s (Myers, 2001).
  7. This ratio is not a representation of the purchase calculation of actual households, but a relative index. In fact, the median income pertains to both renters and owners, and many young buyers are likely to purchase homes below the median price.
  8. This is certainly the conclusion of Robert Shiller (2005, 2006), who plots house prices against other asset classes and shows that the recent run-up in house prices is unprecedented.
  9. We converted data for the 5-year interval preceding the census to its equivalent for a full decade by summing the experience of adjacent 5-year cohorts. For example, we aggregated 5-year rates for persons aged 35 to 39 in 1995 to 1999 with those for persons aged 30 to 34 in the same time period, synthetically estimating the experience of a full decade.
  10. Complete data on estimated buy and sell rates for all 50 states for each of 13 age groups are available from the authors on request.
  11. Death rates climb markedly after ages 55 to 64. Averaged between men and women (weighted for the population at risk), the annual probability of death rises to 2.4% between the ages of 65 to 74, 5.7% between 75 and 84, and 15.5% at 85 and older (U.S. Census Bureau, 2003b). Considering that elderly persons also face higher risks of severe illness or physical incapacity, it is not surprising that they would be two to three times more likely to sell their homes than younger homeowners.
  12. The choice of calibration period is important, because the estimated rates of behavior are intended to represent underlying demographically based demand and will be held constant in future periods. For this purpose, we judged the period of 1995 to 2000 to be much better for estimating normal market behavior than the boom years of 2000 to 2005, or the recession years included in 1990 to 1995. Although we expect the annual rates will likely rise and fall in the future, we assume that they will fluctuate around the rates we estimated from the age schedule in the baseline period. Thus we feel our result properly depicts the changes in underlying demographically based demand likely to prevail in future periods.
  13. In Arizona, the sell rate without correcting for those who sold before migrating to the state is 4.2 per 100 among those aged 55 to 59, and 2.9 per 100 after making this adjustment.
  14. This comment is by an anonymous reviewer of the article.
  15. In 2005, the year of peak sales of newly built homes, 1.28 million newly built units were sold and 7.08 million existing homes were sold, a ratio of 5.5 to 1. In the low point of the 1991 recession, 0.51 million newly built homes were sold and 3.22 million existing homes were sold, a ratio of 6.3 to 1 (Harvard Joint Center for Housing Studies, 2007, Table A-1).
  16. For example, among homeowners ages 50 to 54 in 2004, the median equity was $92,000 and mortgage debt $85,000 (Englehardt, 2006, Table 1).
  17. As an example, during the 1980s the number of households in the Cleveland metropolitan area grew by only 18,000, but 46,700 new housing units were constructed, mostly in suburban areas, and unneeded dwellings were left empty in the central city and older suburbs (Bier & Howe, 1998).
  18. We estimated growth after 2000 by comparing data from the 2006 American Community Survey to the 2000 Census.

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List of Figures

 

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Figure 1. Growth in United States population age 25 and over for each decade from 1960 to 2030 (in millions): Source: U.S. Census Bureau, 2003b, Tables 12 and HS-3.

 

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Figure 2. Ratios of median home values to median incomes of household heads aged 30 to 34 in 2000 and 2005, by state: Sources: U.S. Census Bureau (2003a, 2005a).

 

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Figure 3. Average annual percent of persons buying and selling homes in each age group, for the United States, 1995 to 2000: Note: On average, 8.8% of persons 80 and older sold homes each year.

 

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Figure 4. Average annual percent of persons buying homes in each age group, for selected states, 1995 to 2000.

 

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Figure 5. Average annual percent of persons selling homes in each age group, for selected states, 1995 to 2000: Note: On average, between 8 and 9% of persons 80 and older sold homes each year in all these states.

 

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Figure 6. Net annual percent of persons aged 65-69 buying or selling homes, by state and region.

 

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Figure 7. Crossover points: ages at which selling exceeds buying for each state: Note: Shaded states are in the Northeast. Buyers and sellers are owneroccupants, and do not include investors or those buying or selling second homes.

 

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Figure 8. Period in which sellers exceed buyers in each state: Note: Shaded states are in the Northeast. Buyers and sellers are owneroccupants, and do not include investors or those buying or selling second homes.

List of Tables

	Seniors (aged 65 and up), per 1000 working-age adults (aged 25-64) in each year				Percent change each period
	2000	2010	2020	2030	2000-2010	2010-2020	2020-2030	2010-2030
Source: U.S. Census Bureau, 2005b.
Alabama	252	267	352	450	6.0	32.1	27.8	68.8
Alaska	104	152	248	316	46.2	62.8	27.5	107.6
Arizona	259	274	374	499	5.8	36.6	33.6	82.4
Arkansas	276	275	348	432	-0.3	26.7	24.0	57.1
California	204	219	284	365	7.7	29.7	28.2	66.4
Colorado	177	196	277	342	11.0	41.5	23.3	74.4
Connecticut	258	269	335	444	4.1	24.7	32.6	65.4
Delaware	247	262	355	499	6.2	35.3	40.7	90.3
District of Columbia	222	211	239	265	-5.0	13.3	10.9	25.7
Florida	342	340	437	600	-0.8	28.6	37.5	76.8
Georgia	179	191	254	329	7.0	33.0	29.6	72.3
Hawaii	251	276	387	493	10.1	40.1	27.6	78.7
Idaho	228	227	306	377	-0.3	34.5	23.3	65.8
Illinois	232	234	292	369	0.7	25.0	26.4	58.0
Indiana	240	241	304	378	0.5	26.1	24.5	56.9
Iowa	299	286	368	480	-4.4	28.8	30.4	67.9
Kansas	265	258	334	433	-2.7	29.4	29.7	67.8
Kentucky	236	242	318	407	2.6	31.6	27.7	68.1
Louisiana	229	243	324	418	6.2	33.1	29.1	71.8
Maine	267	279	389	540	4.2	39.6	38.8	93.7
Maryland	207	226	284	360	9.0	25.7	26.6	59.1
Massachusetts	252	253	324	431	0.4	27.7	33.3	70.3
Michigan	235	239	306	394	1.6	28.3	28.7	65.1
Minnesota	231	229	296	390	-1.0	29.3	31.6	70.1
Mississippi	243	244	324	430	0.7	32.5	32.6	75.8
Missouri	263	264	332	425	0.4	25.9	28.1	61.2
Montana	260	275	405	549	5.6	47.5	35.6	100.0
Nebraska	272	267	353	459	-1.6	32.2	29.8	71.6
Nevada	201	227	299	386	12.7	31.7	29.4	70.4
New Hampshire	219	229	318	430	4.6	38.6	35.4	87.6
New Jersey	245	250	308	398	2.0	23.1	29.2	59.0
New Mexico	231	271	412	601	17.5	51.9	46.1	121.9
New York	243	255	317	411	4.9	24.4	29.5	61.0
North Carolina	225	234	299	376	4.2	27.7	25.7	60.5
North Dakota	301	295	403	566	-1.9	36.4	40.3	91.4
Ohio	256	258	331	423	1.0	28.4	27.7	64.0
Oklahoma	261	267	341	420	2.3	27.6	23.2	57.3
Oregon	242	237	318	365	-2.0	33.7	15.0	53.7
Pennsylvania	302	292	365	474	-3.3	24.8	29.9	62.2
Rhode Island	281	266	331	446	-5.3	24.2	34.8	67.4
South Carolina	230	256	355	470	11.3	38.5	32.4	83.4
South Dakota	295	282	379	524	-4.3	34.2	38.2	85.5
Tennessee	231	249	326	405	7.7	31.0	24.2	62.6
Texas	194	203	264	328	4.5	30.1	24.5	62.0
Utah	189	190	249	296	0.8	30.7	19.2	55.7
Vermont	237	259	374	506	9.3	44.4	35.2	95.2
Virginia	205	231	307	391	12.9	32.8	27.5	69.3
Washington	210	222	297	362	5.7	34.0	21.7	63.1
West Virginia	289	290	396	505	0.3	36.6	27.4	74.0
Wisconsin	253	250	328	443	-1.5	31.4	34.9	77.3
Wyoming	224	255	404	562	13.5	58.8	39.1	120.9
U.S. Total	238	246	318	411	3.2	29.6	29.0	67.2