Mean Markets and Lizard Brains

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Mean Markets and Lizard Brains Page 22

by Terry Burnham


  In 1989, Professor Mankiw and David Weil (who was a graduate student at the time, and is now a professor) published an article entitled, “The Baby Boom, the Baby Bust, and the Housing Market.”6 In it, these two esteemed academics concluded, “real housing prices will fall by 47% by the year 2007.” They went on to write, “indeed, real housing prices may well reach lower levels than those experienced at any time in the past forty years.”

  The academic duo speculated on the spillover effects of their predicted housing bust. They write, “Even if the fall in housing prices is only one-half what our equation predicts, it will likely be one of the major economic events over the next two decades.” These professionals predicted that housing prices would decline substantially and seriously harm the economy.

  Not too far away from Harvard University, our young immigrant was facing a decision. Should Fatima and her husband buy a small house or a much larger one? Their family was growing and faced the decision of buying a house for their current needs, or something a bit roomier (and more expensive) to expand into. Fatima urged her husband to buy the biggest house they could afford.

  Fatima anticipated that housing prices would rise (she was fortunate to never have taken an economics course). If prices were to rise, the bigger the investment in real estate, the more profits. Fatima advocated taking a risk, and she convinced her husband to swing for the fences. Accordingly, the young couple took their savings and borrowed as much money as the bank would lend them. They bet big in anticipation that a rising real estate market would make them money.

  So who was right about housing prices? Was it the book-smart academics with their complex mathematical equations, or was it street-smart and gutsy Fatima putting her family fortune on the line? Figure 9.1 shows the answer. U.S. housing prices have soared. The price index is calculated by using repeat sales of the same property. This is a perfect measure as it compares apples to apples and exactly tracks changes in housing prices.

  The professors predicted a 47% fall in housing prices after adjustment for inflation. In reality, housing prices—even after adjusting for inflation—have risen dramatically.

  The professors were exactly wrong.

  Furthermore, the professors predicted that the decline in housing prices would put a drag on the economy. Exactly the opposite has occurred, with rising housing values contributing to rising wealth and supporting the economy during a period when stocks have not risen.

  FIGURE 9.1 U.S. Housing Prices Have Surged

  Source: Office of Federal Housing Enterprise Oversight

  The U.S. housing boom has been nothing short of amazing. Not only have prices risen dramatically since the professors issued their dire predictions, prices have been rising continuously since World War II. Furthermore, U.S. housing prices rose in every single year since at least 1975—no down years for three decades! That is absolutely stunning.

  How did our dueling pair of forecasters perform? Fatima has parlayed her real estate investments into some serious wealth. She put $5,000 down on her first house and borrowed $90,000. She sold the house for $358,000. With the profits, Fatima and her husband bought a house that was three times larger. The new house has appreciated considerably so the couple has accumulated household equity in excess of half a million dollars. In spite of their modest incomes (“jobs that pay shit,” in their words), Fatima and her husband have become rich by aggressively buying real estate.

  Professor Mankiw has also prospered. He became a tenured member of the Harvard economics department at a young age. He has written several economics textbooks and has earned millions from their sale. Professor Mankiw is currently the chairman of President Bush’s Council of Economic Advisors.

  Is Your Home Overvalued?

  Housing has had a great run in the United States for more than 50 years. Is it likely to continue? This question can be answered in three parts: (1) Determine a price-to-earnings ratio (P/E) of your home, (2) estimate a fair P/E for a home, and (3) salt to taste (adjust for local market dynamics).

  What Is the P/E of Your Home?

  A first step is to determine the “fair” value of a property. As with stocks and bonds, this is impossible to do precisely, but easy to approximate. The calculation of fair value relies upon calculating a price to earnings (P/E) ratio.

  A stock’s P/E is calculated by dividing the price of the stock by the earnings for the stock. In the stocks chapter, for example, we looked at Microsoft. The current price of Microsoft (July 2004) is $28, and the predicted earnings for 2004 are $1.27 per share. Thus, Microsoft’s P/E is 22.

  To calculate the P/E of a house or other piece of property, we divide the price of the property by the income it produces. This is easy for a rental property (as long as we are careful to adjust for taxes). For a property that is occupied by the owner, however, there is no rent. In this case, the “earnings” are the estimated rental payments if someone else occupied the property.

  For example, I live with my wife and our new baby in a condominium near Harvard University and Harvard Square. As our place has filled up with cribs and baby toys it has become obvious that we will need to move. Accordingly, I have been getting some estimates for the value of our place. The market price for our condominium is something like $650,000.

  What is the value of our property? Because I don’t assume the market price will stay constant, and I’m not sure when we will sell, I estimate the value independent of the current price. The key is the going rental price for the property. Even though we aren’t currently earning anything on our property, I will use the market rental rate as the “earnings” for my P/E calculation.

  The going rental rate for our apartment is about $2,800 a month. To calculate the P/E we need to factor in all costs including taxes. After our costs, we could generate about $2,000 a month in rental income from our property. So we could earn $24,000 a year in rent, after expenses. So the P/E for our condominium is the price ($650,000) divided by the earnings ($24,000). The P/E for our apartment is 27.

  What Is a Fair P/E for a Home?

  What is the fair P/E for a home? One way to answer this is to compare the P/E of a house to that of stocks and bonds. Table 9.1 makes this comparison and summarizes some key attributes of the different investments.

  The U.S. stock market as measured by the S&P 500 has a P/E of about 18; this calculation uses the estimates for 2004 earnings ($61.50) and the current figure of the S&P 500 (1101).7 The 10-year Treasury bond currently yields 4.4%. This converts to a P/E of 23.

  TABLE 9.1 Key Investment Characteristics of Stocks, Bonds, and Real Estate

  How does a house compare with these two major alternatives? Table 9.1 lists four important investment characteristics and then analyzes the trade-offs between stocks, bonds, and real estate. When comparing two investments, the more favorable the investment attributes, the higher the fair value and the higher the P/E that can be justified. For example, if two investments are identical except for tax treatment, then the investment with the lower tax rate deserves a higher P/E.

  Attribute #1, Risk: An investor in U.S. Treasury bonds is sure to get the original investment returned. Those who own stocks or houses risk losing their investment.

  Attribute #2, Potential for Gain: The U.S. Treasury bond investor can make modest capital gains (if interest rates fall). Both the stock market investor and the home buyer have the potential for substantial gains. Because houses can be bought with very modest down payments, however, they have the highest potential for gain.

  For example, Fatima’s $5,000 investment in real estate became more than $250,000 in just a few years. An investor who bought the Dow Jones Industrial Average in 1927 would have achieved the same 50-fold increase if she or he had held the stocks until 2004.8 So a few years’ investment in housing can provide a lifetime’s worth of gains in the stock market.

  Attribute #3, Tax Treatment: Stocks are treated more favorably than bonds. Both dividends and long-term capital gains have lower tax rates than interest payme
nts on bonds. Houses have the most favorable tax treatment. This ranges from the tax deductibility of interest payments to the exemption of taxes on substantial capital gains from sales.

  Attribute #4, Inflation Protection: Normal U.S. Treasury bonds are not protected against inflation (though some bonds do have such protection). Both stocks and housing are protected against inflation.

  How, then, do housing investments compare with stocks and bonds? The answer is that houses share many characteristics with stocks. Houses offer more potential for gain and better tax treatment than stocks. While the higher potential gain in houses should come with more risk, this has not been the case over the last decades.

  So what is the right P/E for housing? Based on the characteristics of risk, return, taxes, and inflation protection, housing investments look similar to or better than stocks. In addition, the finite supply of land might argue for a bit of a premium. Based on this analysis, housing could command a fair P/E as high as 30. Housing P/Es are categorized in Table 9.2.

  Salt to Taste

  As we all learned in elementary school, the three keys to real estate are location, location, location. While there is a single market for IBM stock, there are many, many different markets for real estate. While we have just made some general conclusions about “fair value” for a house, those P/E categories should obviously be adjusted for local circumstances.

  When people look at real estate at a local level they tend to analyze by city and region. We can read that housing prices have gone up by 15% in Phoenix, but declined in Buffalo. In reality, however, “location” is a much more fined-grained notion than an entire city.

  TABLE 9.2 Is Your Home Overvalued?

  My friend Jon, who lives in Charlotte, North Carolina, learned the importance of location (and timing) over the last several decades. He sent me an e-mail summarizing his real estate experiences. The e-mail, entitled “financial frustration,” said:

  I bought a condo in 1985, when I was single, two blocks from my office [in downtown Charlotte] for convenience for $60,000. The property lost value for years while houses two miles away gained in value. I sold the condo in 1993 after getting married in 1992 for $84,000 and bought a home for $180,000. Seven years and two children later, I sold this home for a small loss after significant improvements. Finally, I bought my current house for $360,000 just as the economy was slowing (June 2001). My original condo is now worth more than $200,000!

  Jon has owned real estate since 1985 in a booming market. Nevertheless, due to family changes he has almost magically missed out on making money; his timing and movements missed the micro trends within his area. So there is much more to location than a city or region. In my own building, for example, the properties on different floors and on different sides of the building have performed differently.

  Accordingly, our valuation ranges should be combined with knowledge of local conditions. Just as an above-average P/E may be appropriate for the stock of a super rapidly growing company, a property in the right location can justify high valuations.

  Is There a Housing Bubble?

  A glance through a bookstore can produce some serious fears about housing prices. Titles such as The Coming Crash in the Housing Market and How to Profit from the Coming Real Estate Bust are likely to get any homeowner’s pulse racing. Are we experiencing a housing bubble and, if so, will the bubble crash?

  There are some compelling clues that allow us to make a judgment as to the existence of a housing bubble.

  Clue #1: Housing Prices Have Risen Far Faster Than Rents There is no nationwide housing P/E. While we don’t know the absolute value of the P/E, we know that it has risen by 43% since 1982. Figure 9.2 graphs the rate of increase in housing prices divided by the rate of increase in rents.

  Since 1982, housing prices have risen 43% more than rents. My wife and I have had a similar experience with our property. The market price of our condominium has almost doubled in just the last five years. In the same period, rents in our building have increased by about 20%.

  So housing prices have risen faster than rents. Does this mean that current housing prices are too high? No. It could be that housing prices were too low back in 1982. What is unavoidable, however, is that relative to rents, real estate is less attractive today than it has been at any time over the last several decades.

  FIGURE 9.2 U.S. Housing Prices Have Risen Faster Than Rents

  Source: Office of Federal Housing Enterprise Oversight, Bureau of Labor Statistics

  Clue #2: Housing Supply Has Grown Faster Than Housing Demand

  Economists are odd people in many ways. In addition to using the words “supply and demand” far more frequently than normal humans, we also spend a lot of time thinking about elasticity. As I found out in college, the abstract concept of elasticity can make the difference between wealth and poverty.

  Once a house has been built, it is not particularly easy to convert it to something else. Thus, the supply of real estate is relatively inelastic. That means that the supply of housing changes only slowly. In contrast, something that is elastic can respond quickly to changes.

  What about housing demand? Barring some sort of tragedy, the number of people who need housing is also unlikely to change quickly. Does this mean that the demand for housing is also inelastic? No. Housing demand fluctuates far more rapidly than population.

  In tough times, people are remarkably flexible in their living arrangements. A recent college graduate, for example, with a good job can’t imagine living at home. If unemployed, however, the same person becomes much more tolerant of her or his parents. In good times, therefore, demand for housing rises far more than population growth, and in bad times, people find ways to economize.

  Thus, the housing market is characterized by inelastic supply and relatively elastic demand. So what? These sorts of markets have the interesting characteristic that price can change very rapidly.

  I learned this lesson when I was in college at the University of Michigan. Doug, the millionaire surfer, made a good living each Saturday scalping tickets at football games. My friend Scott and I decided to get some of this easy money. We hit upon the following strategy. Go to the student dormitories farthest from the stadium. Find students groggy from Friday night drinking and offer to buy their tickets for $1. Then ride our bicycles down to the stadium, sell the tickets for more, and collect our profits.

  We did this one bright Saturday morning and managed to make about $100 in a couple of hours. I remember our first sale. A couple was walking away from a BMW. I approached the man and asked if he needed tickets. He asked, “How much?” Scott responded with “face value” of $12. The man instantly agreed, and we had $22 in profit!

  The following Saturday, Scott and I were up early aggressively buying tickets. Buoyed by our success, we purchased more than 60 tickets, each for $1. As we rode our bikes to the stadium, however, we saw people offering to sell huge batches of tickets. We soon began selling tickets as fast as possible. The going prices started low and then plummeted. One buyer wanted six tickets. I offered six for $0.25 each. A competing scalper undercut me by offering all six tickets for a total of $1. Scott and I lost almost all of our investment.

  What happened? We learned that, like housing, football games have inelastic supply and elastic demand. While both games that we worked were against similar quality opponents, the forecast predicted rain on the second Saturday. The supply of tickets was a constant of just more than 100,000 seats (the University of Michigan’s stadium is known as the “big house”), but demand was slightly lower the second week.

  In markets with inelastic supply and elastic demand, prices can move very rapidly. As game time approaches there are either more buyers or more sellers. A relatively small shift in demand makes the difference between too many buyers and too few. This translates into the difference between high ticket prices and almost free tickets. On our second weekend of ticket scalping, Scott and I ended up throwing away dozens of tickets.

  T
he housing market has inelastic supply and relatively elastic demand. There is no equivalent of kickoff time when supply becomes worthless so the rental effects are not as extreme. Nevertheless, the real estate market is subject to relatively large changes in rents for relatively small changes in demand.

  Importantly, the supply of U.S. housing has been growing far more rapidly than the population. Figure 9.3 shows the relative growth between the 1970 and 2000 census.

  FIGURE 9.3 U.S. Housing Supply Has Grown Faster Than the Population

  Source: U.S. Census Bureau

  Over the last three decades, the growth in housing units in the United States has exceeded the growth in population. As discussed, this does not imply disaster. Over this time period, the United States has become far richer. As we have become richer, it is reasonable to expect that we would have more houses. Nevertheless, the fact that supply has grown so much more than population is a clue. If times get tougher, it is possible that demand for housing could drop enough to put significant pressure on prices.

 

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