The Undercover Economist Part 6

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It is common to provide goods and services on the private market, but one of the main alternatives-certainly, the main ideological alternative-has been to provide them using a political market instead. Medical goods and services are among the most difficult to distribute. We have tried using political markets, but they have let us down badly, and for obvious reasons.

At first sight, the private market failures, exemplified by the US system, are also obvious. But when we closely examine the market failures, it's the lack of information that is most serious, and the insurance market suffers the most serious consequences. American citizens receive much of their medical care through the intermediation of this badly malfunctioning market.

With some imagination, and some economics, we can step back from the troubles of our current systems and think about how to fix them. In Singapore, the system sketched in the last few pages has been successful for almost two decades. The typical Singa-porean lives to the age of eighty, and the cost of the system (both public and private) is a thousand dollars per person-less than the cost of the bureaucracy alone in the United States. Each year, the typical Singaporean pays about seven hundred dollars privately (the average American pays twenty-five hundred dol-lars privately) and the government spends three hundred dol-lars per person (five times less than the British government and seven times less than the American government). Keyhole eco-nomics works.

The reason why Singapore's success is uncommon is probably that policy debates get stuck with one side claiming that we should rely on the market, and the other side a.s.serting that the govern-ment would do a better job. So, government or market? We've learned that the question doesn't make any sense in isolation. To answer it we need to understand why markets might work, and how and why they fail.

We learned in chapter 3 exactly why markets work: because our choices as consumers between competing producers gives them both the right incentives and the right information to pro-duce the right amount of exactly what we want. And we've also learned that scarcity power, externalities, and inside information can each ruin the way markets do this.

In the case of health care, the market works poorly because while we want the rea.s.surance of knowing they can afford ex-pensive medical bills, inside information eats away at the insur-ance by driving away low-risk customers and forcing premiums to rise. Private companies have developed ways to get around the problem, but they are expensive and bureaucratic. Singapore's government had the power to tackle the problem head on, by using forced saving and catastrophe insurance to make sure costs were manageable but keeping the power of patient choice at the heart of the system. Governments can replace markets, but they will often do better to try to fix them. They are unlikely to suc-ceed unless they appreciate exactly what the problem is in the first place.

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Rational Insanity

"My vision is that in a few years there will only be two or three big Internet portals-everybody will go to one of them to be directed to wherever they want to go on the Internet. That will be worth hundreds of billions of dollars. If you want to succeed, you'll have to be one of those portals."

So spoke Graham Bailey (not his real name) in 1998. Bailey was a partner in a management consulting firm and was making this pa.s.sionate speech to any potential client who would listen. For all I know, he believed it then and believes it now. But when I heard it, I did not. There were not many skeptics at the time. 1998 was the year when the frenzy about the dot-coms was really starting to mount.

One of the most famous dot-coms was the Internet bookshop, Amazon.com. (It was rapidly becoming the vogue to set up com-panies named after website addresses.) Amazon started selling books over the internet in 1995, and in 2003 it sold over $5 bil-lion worth of merchandise. Amazon's rapid growth and its fight to become profitable is remarkable, but not as remarkable as the price of its shares. In 1997 Amazon shares were first sold to the public, at a starting price of $18.

A lot has happened since then. In 1999, Amazon shares soared to over $100. At the time it was said that Amazon.com was valued at more than all the regular bookshops in the world. But throughout 2000, Amazon shares slid back toward $18 and beyond. In the summer of 2001 Amazon shares were trading around $8. In 2002, the company was getting good write-ups in the financial press- but shares were still valued at less than that initial offering of $18. Yet, since then they have recovered to $40 a share. Which price was the mistake: $100, or $8? Or both?

The answer would be useful, not least because Amazon's roller-coaster performance is common. So can the Undercover Econo-mist say anything about why share prices acted the way they did, and how they might behave in the future?

A random walk Economists face a serious problem in trying to say anything sensible about stock prices. Economists work by studying rational behavior, but the more rational the behavior of stock-market investors, the more erratic the behavior of the stock market becomes.

Here's why. Rational people would buy shares today if it was obvious that they would go up tomorrow, and sell them if it was obvious that they would fall. But this means that any forecast that shares will obviously rise tomorrow will be wrong: shares will rise today instead because people will buy them, and keep buying them until they are no longer so cheap that they will ob-viously rise tomorrow. In fact, rational investors should be able to second-guess any predictable movements in the stock market or in the price of any particular share-if it's predictable then, given the money at stake, they will predict it.

But that means that if investors really are rational, there won't be any predictable share movements at all. All the predictability should be sucked out of the stock market very quickly because all trends will be antic.i.p.ated. The only thing that is left is unpre-dictable news. As a result of the fact that only random news moves share prices, those prices, and the indices measuring the stock market as a whole, should fluctuate completely at random. Math-ematicians call the behavior "a random walk"-equally likely on any day to rise as to fall.

More correctly, the stock market should exhibit a "random walk with a trend," meaning that it should on average edge up as the months go past, so that it is compet.i.tive compared with other potential investments such as money in a savings account, or prop-erty. If it was expected to edge up by more than that trend, it would already have done so, and similarly if it was expected to edge up by less, or to fall, it would already have underperformed. This is the reason people hold shares at all. The trend doesn't alter the basic a.n.a.lysis, though, and on any given day the trend is dwarfed by random movements.

This theory should hold even if not every investor is rational. The ones who are should be enough to force the market into a random walk, providing they are throwing plenty of money into good shares and out of bad ones. Throwing money around shouldn't be too difficult, since presumably the smarter investors make more money.

Should we believe the "random walk" theory? We certainly shouldn't expect it to be absolutely true. If it was, that would be a paradox: perfectly informed investors produce a random market, but a random market doesn't reward anybody for becoming per-fectly informed. It wouldn't be worth anybody's while to invest time and effort to a.n.a.lyze the market or uncover new informa-tion, if everybody else was doing the same. On the other hand, a market full of unexploited opportunities would offer big profits to any investor willing to research them, which would then lead to fewer unexploited opportunities. Somewhere in the middle is a balancing point: a nearly random market with enough quirks to reward the informed investors who keep it nearly random.

You can see the same phenomenon at work at the supermarket checkout. Which line is the quickest? The simple answer is that it's just not worth worrying about. If it was obvious which line was the quickest, people would already have joined it, and it wouldn't be the quickest any more. Stand in any line and don't worry about it. Yet if people really just stood in any line, then there would be predictable patterns that an expert shopper could exploit; for example, if people start at the entrance and work their way across the store, the shortest line should be back near the en-trance. But if enough experts knew that, it wouldn't be the short-est any more. The truth is that busy, smart, agile, and experienced shoppers are a bit better at calling the fastest lines and can prob-ably average a quicker time than the rest of us. But not by much.

Value and price- beyond the random walk a.s.suming that what is true of supermarket lines is also true of stock-market prices, economists should be able to throw some light on the market, but not very much. Many economists do work for investment funds. They are as wrong nearly as often as they are right, but not quite. Our modified random walk theory tells us that this is what we should expect.

So, what do these economists do to provide investment funds with such tiny edges over the market? The starting point is to view stock shares for what they are: a claim on the future profits of a company. Here's an example. Let's say there are 100 shares of timharford.com. If I own one share, I have a right to 1 percent of timharford.com's profits for as long as I hold the share. If timharford.com makes $100 per year, forever, then I get $1 per year, forever. If timharford.com makes $1,000 per year for the next ten years, then nothing, then I get $10 per year for ten years, then nothing.

That's all very simple. A slight complication is that companies do not necessarily return their profits directly to shareholders. Amazon.com earned eight cents per share in 2003, so might have been expected to pay a "dividend" to shareholders of eight cents a share; but Amazon.com didn't pay a dividend in 2003, nor in any of the years before. That doesn't mean that Amazon.com shareholders are being defrauded. The management is using the money for other things, such as paying off Amazon.com's debt or investing to expand the business. If these things are done wisely, profits will rise over time. Instead of being paid a dividend, Amazon.com shareholders would be compensated by a share price higher than it would otherwise have been, in antic.i.p.ation of these later profits. Even if they sell the share before any dividend is paid, they should get a better price for it because of future dividend payments.

If it was easy to tell the future it would be easy to say how much it was worth to own a share in timharford.com. Let's say that everybody knows timharford.com will make $100 per year, forever. Then holding one share will bring in $1 per year, forever. How much is that worth? If I put $10 in a savings account earning 10-percent interest, that will also get me $1 per year, forever. So one share in timharford.com is like $10 in a savings account at 10 percent. At interest rates of 10 percent I should be willing to pay $10 for one share in timharford.com. Interest rates of 5 percent make shares twice as attractive relative to a savings account; in-terest rates of 1 percent make them ten times as attractive. I should be willing to pay $100 for one share in timharford.com with in-terest rates at 1 percent forever, because it would earn me a dol-lar a year, just the same as $100 in a savings account. (This is one of the reasons that stock markets rise when interest rates are ex-pected to fall, and fall when interest rates are expected to rise.) Amazon.com shares were valued at $40 in October of 2004. But with long-term interest rates in the United States of about 4 percent, I needed only $2 in a savings account at that point to earn eight cents a year. Since Amazon.com earned eight cents per share in 2003, the share should have been trading at $2, not $40. Something else must have been justifying those prices.

That "something else" is the future. Real companies do not reliably make a certain profit every year. Investors have to judge their future profitability, in whatever way they can. Perhaps timharford.com will not make $100 a year but $1 billion a year because of a dramatic expansion. Perhaps timharford.com will go bust tomorrow. Because of this uncertainty, most reasonable people will want a discount: one risk-free share at 1 percent interest might have been worth $100, but one risky share, expected to produce the same return of $1 a year (but who can tell?) would be worth less, perhaps $90, $70, or even $30. How much less they are worth depends on how risky the share really is, and on how much the typical investor worries about that risk.

That suggests that investors in Amazon.com don't expect long-term profits of eight cents a share, but something much higher. Instead of buying a share at $40 and making eight cents, they could put $40 in a savings account and make $1.60 (since long-term interest rates are 4 percent). Amazon.com shareholders clearly expect earnings per share to rise to $1.60 and beyond to compensate them for their risk. To do this, Amazon.com profits would have to rise from $35 million to about $1 billion a year.

What I have just described is a view of the stock market based on fundamentals-in other words, on the recognition that in the end, shares are called shares for a reason: they give you a right to have a share in the profits of a real company. In the long run the share price has to reflect that. Economists can help to work out what the fundamental value of the share is, which is what I have just done. If the price of the share is lower than the fundamental value, that tells you that the share is cheap and you should make money buying it. In the long run, share prices have to reflect the funda-mental profits of companies. At the extreme, even if a good-value share stays undervalued forever, you should still make money holding it and pocketing the dividends. In the short run, share prices should also reflect the fundamental prospects of the com-pany, too. After all who would buy a share for $10 when every-body knows it is really worth $1 in the long run? And who would sell a share for $1 when everybody knows it is really worth $10 in the long run? As long as the big investors are sensible, share prices should reflect fundamentals in both the long run and the short run. But are investors sensible?

The most famous economist of the twentieth century, John Maynard Keynes, compared the stock market to a silly newspaper compet.i.tion in which readers were invited to pick several pretty faces from a hundred photographs. The winner was a reader who chose girls closest to the general opinion.

It is not a case of choosing those which, to the best of one's judgment, are really the prettiest, nor even those which aver-age opinion genuinely thinks the prettiest. We have reached the third degree where we devote our intelligences to antici-pating what average opinion expects the average opinion to be. And there are some, I believe, who practice the fourth, fifth, and higher degrees.

A modern day example is the "Grolsch" method of picking shares. I met an investor who told me he had bought lots of shares in the brewer, Grolsch, because he'd been to lots of parties around the City of London and Grolsch beer was being served at all of them. Other beers, which had previously been popular, like Stella Artois or Heineken, seemed to have disappeared from the scene. Naively, I told him that parties in the City weren't necessarily a good indicator of Grolsch's worldwide sales; Grolsch could be doing well in the City but badly everywhere else, in which case the company's long-term profits would fall and buying the shares would have been a mistake. The investor told me that he knew that was true, but it didn't matter. He reckoned that if Grolsch was big in the City, lots of City investors would figure it was made by a successful company and buy the share. The share price would go up-for a while-and he could sell at a profit. The fundamentals only mattered if he planned to hold the share for a long time, long enough for the real picture, whatever it was, to become clear. And what was the real picture? Over the next year, Grolsch shares fell by about a third from 24 to 17.5; they then bounced right back in just a couple of months. At the time of writ-ing in March 2005, they are almost exactly where they were when we first had the conversation.

The Grolsch method is not interested in the value of the share. It's simply an attempt to take advantage of what mistakes you think other investors will make. Yet given what we now know about rational stock markets and the random walk, why would we expect investors to make such easily exploitable mistakes?

Rational fools Why indeed? Consider the story of Tony Dye, Chief Invest-ment Officer of Philips & Drew, which manages investments such as pension funds on behalf of large clients. Tony Dye concluded in 1996 that at a level of 4000, the FTSE 100 (the index that reflects the performance of the London Stock Exchange's 100 largest companies) was overvalued, and he moved a chunk of his clients' money into cash, effectively, putting it into a savings ac-count. Having withdrawn 7 billion from the stock market, he was then judged day by day on his decision by his clients, his peers, and the newspapers. He was mocked and nicknamed "Dr. Doom." As the FTSE continued to climb throughout the late 1990s, Dye looked increasingly stupid. In 1999, Philips & Drew lost more clients than any other fund manager. Based on returns to clients, it ranked sixty-six out of sixty-seven compet.i.tors in the final three months of 1999. Dye continued to insist that the stock market was overvalued, shunned Internet and telecom shares, and kept an unusual proportion of his client's investments in cash. The end was inevitable: his early retirement was announced at the beginning of March 2000, and the broad conclusion was that he had been forced out. The Times of London called Philips & Drew "a standing joke," and Dye's successor acknowledged that Dye had suffered: "That's a lonely place. The last few years have not been the easiest in terms of the flak he has had to put up with."

Dye lost his job, but he was right. Before Philips & Drew had time to change its strategy, the stock market turned. Internet, telecom, and technology stocks plummeted. The stock market as a whole slumped. The unfashionable "value" shares, which Dye had been holding, did well, and cash was also better than crashing Internet shares. Philips & Drew soared to the top of the pension fund performance tables, earning its clients 6.4 percent in the three months up to June 2000-the equivalent of more than 28-percent annual return in a sharply falling market. The FTSE fell and fell and fell, from over 6400 at the time of Mr. Dye's departure to under 3300 three years later. Dye had concluded in 1996 that his clients would be better off selling shares with the market at 4000 and putting the money in a savings account. He was eventually proved right seven years later.

Tony Dye was right, but was he sensible? The hundreds of fund managers who were proved disastrously wrong kept their jobs because they were all wrong in a big herd. Tony Dye de-cided to follow his own path. He was vindicated in the end, but not before he had been ridiculed by the press, abandoned by his clients, and forced out by his employer. Fund managers face lop-sided incentives: if they decide to take a different view from the crowd, they will win a few clients if they are successful but lose their jobs if they are not. Much safer to run with the herd.

This isn't to say that share prices are completely out of touch with reality-simply that many major fund managers, who make decisions concerning vast sums of money, are being paid to fol-low fashion instead of pick the right shares. That's bound to mean that the stock market will make mistakes.

Taking the long view It can take many years for those mistakes to become apparent. Who is to say for sure that the Internet bubble really was a bubble? The truth might be that we're making a mistake today when stock prices have fallen so far. There are no definitive answers, but I find that taking a long, long look back certainly raises the right questions. At the peak of the market in 2000, it was fashionable to try to get people to buy into the stock market, or a stock-market related product such as a pension, by showing a graph of stock prices, which looked something like this: Does the stock market do this . . .?

50 45 40 35 30 25 20 15 10 5 0

1980 1990 2000 Source: Shiller 2001.

The idea of this graph is to show you that the stock market (in this case, a much-quoted US stock index, the S&P 500) has climbed very quickly, and if you had invested in the early 1980s you would have done very nicely indeed.

The real message is a little bit more alarming. The numbers up the side of the graph are "historical price/earnings ratios." They show how the price of shares is related to the history of company profits over the previous ten years. So in 1980, the price of typical S&P 500 shares was nine times the typical S&P 500 company's average profit during the 1970s (the graph, and all these figures, are adjusted to remove the effect of inflation). Shares that had brought $100 a year of profits in the 1970s cost $900 to buy in 1980. By 1990, shares that had brought $100 a year of profits during the 1980s would cost $1,800 to buy. This means that investors in 1990 were optimistic that the 1990s would be better than the 1980s, while investors in 1980 were less optimistic that the 1980s would be better than the 1970s.

By 2000, investors were willing to pay $4,500 for shares that had brought $100 of profits throughout the 1990s. If investors in 1990 were optimistic relative to investors in 1980, the investors in 2000 were absolutely delirious. Part of that was a willingness to pay more for shares because people were more familiar with shares and more tolerant of the risks. But mostly it reflected a view-and an unconscious, unquestioned view-that future profitability would be much better than past profitability, in a way that had never happened before.

Let's be clear about what a ma.s.sive a.s.sumption that was. It wasn't a question about whether company profits were increasing. On average, over the medium term, they always have increased in a b.u.mpy uphill ride as the economy expands. But price/earnings ra-tios like those shown in the graph have always taken into account the fact that because the economy is growing, tomorrow's profits will probably be larger than today's profits. Investors in 2000 were betting on more than that. They were betting that tomorrow's profits would be much, much larger than today's profits-in a way that had never been seen in the history of the stock markets, not when the railroads came, nor when America was electrified, nor in the great expansion of the 1950s and 1960s.

The graph of price/earnings shouldn't rise like the north face of the Eiger. It should be fairly flat, bouncing up and down a bit perhaps, but over the long term never really changing much. A stable ratio of 16 says that I am willing to pay $16 for a share that has in the past given profits of $1 a year, $1,600 for a portfolio that has in the past given profits of $100 a year, or $16 billion for a company that has in the past given profits of $1 billion a year. As the companies on the stock market grow, profits may grow from $10 million to $100 million to $1billion, but the ratio shouldn't usually change over time. (It does change with interest rates and att.i.tudes to risk, but these effects aren't nearly enough to explain what happened in the late 1990s.) . . . or this? The long view.


"A new and permanently high plateau" 45 40 35 30 25 20 15 10 5 0 Source: Shiller 2001.

When pension salesmen showed me graphs like this in 2000, what they hoped they were telling me was that the stock market was going to keep soaring. But what I saw was a message that it was bound to crash. Historically, long-term price-earnings ra-tios have always been around 16. They have often drifted away from 16 but have always returned to that figure. Yale economist Robert Shiller has devoted some effort to establishing this pat-tern of always drifting back to a P/E ratio of 16, and he has col-lected price/earnings ratios back to 1881. (Robert Shiller's data is used in the graphs for both figures. In fact, the first figure is just an extract from the second. The impression the two graphs give is rather different.) What comes out very clearly from Shiller's data is that a ratio over 30 is not normal. It only happened once before the 1990s, in 1928. As in 2000, people in 1928 came up with many rationalizations for the high share prices at the time. Irving Fisher, one of Shiller's predecessors as a noted Yale econo-mist, famously declared that shares had reached "a new and per-manently high plateau." Fisher was no fool; a very influential thinker in monetary economics, he wrote a book called The Wall Street Crash-And After, giving what must at the time have seemed like excellent reasons for expecting share prices to stay high.

After the initial dramatic swing down in the stock market at the end of the 1920s, the start of the Wall Street Crash, Fisher argued that future profits would be excellent, due to efficiencies resulting from recent large mergers, the application of new tech-nology, the improvement of management expertise, and the ex-pertise of the Federal Reserve. The a.n.a.lysis seems reasonable . . . and strangely familiar.

Unfortunately, despite the t.i.tle, Fisher's book was not published after the Wall Street Crash. It was published just after the first act of what turned out to be a much longer drama. Further dramatic falls in share prices followed. So, too, did the Great Depression.

Thinking sensibly about scarcity We are probably not on the verge of another depression. Some die-hard optimists would even claim that the stock market will bounce to justify its bubble valuations. James Gla.s.sman and Kevin Ha.s.sett, the authors of Dow 36,000, a book that made the epony-mous prediction, were unrepentant in August 2002 after the Dow had slumped to around 8000 and have continued to defend their book. They point out, correctly, that n.o.body could call the market in the short term; they predict a rebound for the market over time. (They are no longer emphasizing the fact that in Dow 36,000 they predicted that the market might take "three or five years" to soar . . . that is, until the end of 2004.) Gla.s.sman and Ha.s.sett argue that the stock market has been undervalued for a hundred years, so the historical data produced by Robert Shiller does not prove that in-vestors in the future will make the same mistake. Perhaps inves-tors have indeed been wrong for the past century. As we've already discovered, once economists abandon the view that people are act-ing sensibly, it is very hard for us to say very much at all.

A more productive line of inquiry is to ask whether, as bubble valuations suggested, company profits will really be so dramati-cally much higher in the next few years. It's tempting to think that this is an argument about the power of the internet, cell phones, computers, and other recent technological advances. Many Internet fans did indeed argue that it was reasonable to pay an enormous amount of money for a company like Amazon because the internet was "transforming everything."

Unfortunately, that is not the point. Maybe the Internet really is a transformational technology like electricity, ma.s.s chemical production, or the railroads. The answer will emerge over time, but that answer does not actually matter much for the stock mar-ket. The hidden premise is that if we are in an economic revolu-tion, shares should be very valuable. This premise is wrong. Shares should rise in price only if there's good reason to think that fu-ture profits will be high. As we know, profits derive from scar-city; for instance, ownership of scarce land (protected by legal t.i.tle), a scarce brand (protected by trademark), or an organiza-tion with unique capabilities (protected by nothing more than the fact that most effective organizations are hard to copy). So share prices should rise only if economic transformation increases the degree to which organizations control scarce resources.

It's easy to see that there might be a link between economic transformation and the control of scarcity. It's far less easy to see what it is, and it seems unlikely that it is as straightforward as "new technologies will increase corporate control of scarce resources." Some companies will gain; others will lose. Histori-cally, there has been no clear link between economic transfor-mation and high profits for the average company. In fact, the reverse is often true: economic transformation destroys the prof-itability of old firms (by replacing or duplicating their scarce as-sets), while the new firms that replace them often face a high failure rate and very large costs of building their businesses. The advantages are enjoyed by workers who are paid higher wages on average and by customers who pay lower prices or get new and better goods and services. For example, Amazon's profits of $30 million in 2003 should be weighed against the fall in global mu-sic industry profits of around $2.5 billion in the same year, a drop that industry executives blame on Internet music down-loads and easy piracy. The Internet can destroy profits as well as enable them.

This has always been the case with previous revolutionary tech-nologies such as railroads or electricity. Because I didn't under-stand the point well enough at the time, I once made the mistake of entering into a sportsman's bet with the economist John Kay. He wondered what would have happened if you had bought shares in the Great Western Railway, the most famous of all the rail companies in Britain, the birthplace of train travel. He specu-lated that even had you bought them on the first day they were available, and held them for the long term, your returns would have been quite modest, say, less than 10 percent a year. I couldn't conceive that one of the most successful companies of the rail-road revolution could have possibly returned such a modest sum to shareholders. Off I went to flick through dusty nineteenth-century editions of The Economist and find out the answer. Of course, Kay was right. Not long after the Great Western Rail-way shares were put on sale for 100 a share in 1835, there was a tremendous burst of speculation in rail shares. Great Western shares peaked at 224 in 1845, ten years after the company was formed. Then they crashed and never reached that level again in the century-long life of the company. The long-term investor would have received dividend payments and would have made a respectable but unremarkable 5-percent annual return on his ini-tial 100 investment. Somebody buying at the peak of the frenzy would have lost money but would have done far better than the backers of countless rail companies, which simply went bankrupt without completing their lines.

So, even the best rail companies weren't great investments, and the worst were financial disasters. But n.o.body disputes the fact that the railroads completely transformed developed econo-mies. Conservative estimates are that they added 515 percent to the total value of the US economy by 1890-a staggering amount, when you think about it. But compet.i.tion to build and operate rail lines kept profits modest. As long as compet.i.tion is strong, the railroads had little scarcity power.

Scarcity and technology In the case of the dot-coms and other high technology compa-nies, the case for scarcity is even harder to make. A few have done well, it's true; for instance, IBM, Microsoft, and Intel. IBM was an enormously successful company: at the end of the 1970s it was the most profitable company ever. But at the beginning of the 1980s, it nearly went bankrupt and has only recovered by radically and painfully transforming itself into a completely dif-ferent business. Intel has not suffered the same disintegration, although operating profits did fall by over three quarters in 2001. But Intel is famous for its incessant drive to keep innovating to stay ahead of the compet.i.tion. (The chairman, Andy Grove, wrote a book t.i.tled Only the Paranoid Survive.) Only Microsoft, which replaced IBM as the t.i.tan of the computer industry, seems to have had a comfortable time. Perhaps it is the great success of Microsoft, which has helped to fuel the frenzy to find the "next Microsoft." Most companies are not Microsoft and never will be. In truth, as far as the share price is concerned, even Microsoft is not Microsoft, because its share price at the end of the 1990s reflected not its current situation but an expectation of what Microsoft could eventually become. The view of investors, perhaps correctly, is that by controlling a number of important industry standards, Microsoft really does have genuine, lasting scarcity power, which will generate ma.s.sive profits for many years to come.

For the gaggle of dot-com pretenders, the contrast could not have been greater. Many of them had businesses that could have been duplicated at minimal cost in a matter of months, and it was that fact alone that should have made it clear that their shares were really worth next to nothing. It did not matter whether the economy was changing, because the economy will never change so much that companies with no scarcity power become highly profitable.

Which brings us back to Graham Bailey and management consulting in late 1998. The implicit idea behind his story was this: it doesn't matter whether you have any scarcity power. It doesn't matter if anyone in the world can do what you do. What matters is that you get there first. It's a gold-rush vision-the first claim has priority. If somehow Internet companies could stake out "terri-tory" on the Internet, other companies would find it impossible to move in and dislodge them.

When you make that implicit idea explicit you can see that it appeals to the great American myths, but doesn't really have a lot behind it. Settlers and prospectors had a set of property rights, admittedly rough-and-ready ones, to defend their claim. But Internet companies do not-they have a domain name and maybe some brand recognition. But easy come, easy go: why on earth should the first company to set up an Internet business face no effective compet.i.tion? It is quite easy for customers to find out about new businesses. It is effortless for them to visit their websites-much easier than it is to visit a new store. In fact, the advantage to businesses who move first looks smaller than it has ever been in the past. As Bailey was speaking, a tiny company was being established in a garage in California. It provided Internet search technology but was performing just a few hundred searches an hour. The company's name was Google.

Google is the living proof that moving first counts for nothing on the Internet. What counts is being best. Google came to the game late, at a time when Yahoo! appeared to have established itself as the king of all search engines, but has become synony-mous with Web searching itself. The question for Google is whether a new company, sitting in a garage somewhere, is about to do to them what they did to their rivals. On the Internet, ev-ery company is vulnerable to compet.i.tion. The Web eats into scarcity power.

The lessons for your own stock market investment are clear enough. First, remembering the struggle to find the fastest line at a supermarket, bear in mind that all stock prices incorporate tremendous expert knowledge. If you plan to try to make serious money, better have a clear idea what you think you know, and what market insiders are ignoring. Second, remember that long-lasting profitability for a company comes from having some capability that others cannot match: a powerful brand in a con-servative market-think of Trojan condoms; control of a stan-dard like Microsoft's; or simple superior expertise, like General Electric. Perhaps eBay has such a capability, drawn from its locked-in base of loyal buyers and sellers. Very few other Internet companies do, and if you looked inside Graham Bailey's story thoughtfully you would have found it very unconvincing in 1998. His consulting firm went bankrupt in April 2001.


The Men Who Knew the Value of Nothing

Someone who knows the price of everything and the value of nothing. Oscar Wilde's definition of a cynic, now commonly applied to economists.

Imagine hiring an economist to sell your house. He designs a clever-looking kind of auction, which he a.s.sures you should raise the $300,000 you think your house is worth. The bids come in, and to your horror and the economist's embarra.s.sment you some-how end up with less than $3,000. You're left homeless and nearly penniless, your wife divorces you, and you spend the rest of your days in a dank bas.e.m.e.nt.

Meanwhile, your next-door neighbor also decides to sell his house and engages a different economist, who also designs a clever-looking kind of auction. Your neighbor also expects $300,000, but the bidding just keeps on going up and he ends up with $2.3 million.

Far-fetched? Not at all. Something very similar actually happened, not to homeowners but to governments. The real estate in this situation was const.i.tuted not of bricks and mortar but of thin air, wavelengths of radio spectrum, to be exact, which cell-phone companies use to operate their networks. Over the past few years, governments across the world have been selling the rights to use this spectrum to telecom companies. There is a limited amount of the spectrum available, and as we have learned, where there is scarcity there is money to be made. Unfortu-nately, not all of the economists who were hired as consultants knew how to set up the auction so that it was likely to produce a good price. One auction really did raise less than 1 percent of what was hoped for, while another raised ten times as much as expected.

This wasn't down to luck but to cleverness in some cases and blundering in others. Auctioning air, like playing poker, is a game of great skill-and one that was played for very high stakes indeed.

Love, war, and poker Many of those who knew the mathematician John von Neumann regarded him as the "best brain in the world," and they had a chance to compare him with some stiff compet.i.tion, given that one of von Neumann's colleagues at Princeton was Albert Einstein. Von Neumann was a genius around whom grew a my-thology of almost superhuman intelligence. According to one story, Von Neumann was asked to a.s.sist with the design of a new supercomputer, required to solve a new and important math-ematical problem, which was beyond the capacities of existing supercomputers. He asked to have the problem explained to him, solved it in moments with pen and paper, and then turned down the request.

Von Neumann made dramatic strides in logic, set theory, geometry, meteorology, and other fields of mathematics, and he took a central role in developing quantum mechanics, nuclear weapons, and the computer. But it's his role as the founder of game theory that interests us here.

A game, to a game theorist, is any activity in which your prediction of what another person will do affects what you decide to do. Such games include poker, nuclear war, love, or bidding for thin air in an auction. Game theory can seem deceptively simple: for instance, the game "driving" is thoroughly straightforward.

In "driving," I receive an acceptable payoff if I drive on the right and so do you. I also receive an acceptable payoff if I drive on the left side, and you do too. If one of us chooses to behave other-wise, I receive a very bad payoff-a ride in an ambulance. (You also receive a bad payoff if we have a head-on collision, but in game theory I don't usually care about your payoff for its own sake. I care about your payoffs only because they help me predict your behavior.) Games are often described in just that way, using little stories or anecdotes, but these stories conceal the fact that for a game theorist, games are mathematical objects. The great game theo-rists are brilliant mathematicians, such as Von Neumann him-self, or n.o.bel Prize winner John Nash, the subject of A Beautiful Mind. As in the case of all game theory, Nash's revolutionary new way to predict a game's outcome was an inspired application of well-understood mathematics.

Von Neumann was fascinated by poker, and as he turned his mind to the game he developed mathematical tools that are not only handy for economists but for people trying to understand everything from dating to evolutionary biology or the cold war.

The fundamentals of poker are simple: players conceal their cards until the final showdown, when the player with the best cards wins the pot, full of all the acc.u.mulated bets. Each player has to keep betting to stay in the game, but some will give up along the way, preferring to forfeit a little money rather than risk losing much more in the showdown. If all the other players give up, you can win the pot without ever showing your cards.

If you were playing poker, your basic challenge would be to work out whether it was worth paying to stay in the game. Prob-ability theory won't get you very far. It is not enough to calculate the odds that the hand you hold is better than the other hands hidden around the table. You need to a.n.a.lyze your opponents' moves. Is a small bet a sign of weakness, or a trick to tempt you to raise the stakes against hidden strength? And do big bets mean a big hand-or a bluff? At the same time you must recognize that your opponents will be trying to interpret your own bets, and you must be careful not to be predictable.

Poker is full of spirals of second-guessing: "If he thinks that I think that he thinks that I have four kings, then. . . ." Poker is a game both of luck and of skill, and most importantly, it is a game of secrets: each player has access to information hidden to the others. In chess, a game of pure skill, the battle takes place in plain sight of everyone. In poker, no player can see the whole truth.

This is where game theory comes in. Von Neumann believed that if he could a.n.a.lyze poker using mathematics, he could shine a spotlight onto all kinds of human interactions. Poker is a game where a small number of players try to outwit each other in an environment of luck, secrets, and skilled calculation. But poker is not the only situation to fit that description. Think of generals fighting a war, or even-if you're a cynic like me-men and women playing the great game of love itself. Many human inter-actions can be interpreted as battles of wits, like poker. All these interactions came to be described by theorists as "games" and explored using game theory.

Economic life is no exception. Von Neumann teamed up with the economist Oskar Morgenstern to write the bible of game theory, Theory of Games and Economic Behavior, which was pub-lished just before the end of World War II. Ever since, game theory and economics have had a close relationship: game theory is taught to most students studying economics, and several game theorists have been awarded the n.o.bel Prize for Economic Sciences.

If you want examples of real-life "economic games," think of bargaining between landlord and tenant, between government and trade union, between used-car salesman and used-car buyer. Think of oil producing nations deciding whether to adhere to OPEC rules to help drive up oil prices, or produce flat out and take advantage of the high prices that others have created.

Or, to take the example we'll explore in most depth in this chapter, think of a collection of eager telecom corporations trying to acquire radio-spectrum licenses from a government with a limited number to offer. Every bidder has some idea of how prof-itable it would be to own a license (and so how valuable a license is), but n.o.body knows precisely how profitable. The government's challenge is to find out some secrets: to determine which of the telecom companies can best use the licenses, and how much the licenses are worth to them. Ideally the government would want to a.s.sign the licenses to the firms who will use them best. Since the government is to be divvying up a valuable public a.s.set, they also want to get the best value for the taxpayer.

Poker and the spectrum license problem are both games in Von Neumann's sense. There is an even closer similarity: in both cases, it's important to put large sums of money at the heart of the process. Without stakes, poker makes no sense. To a gam-bler, any game may be regarded as "more interesting" if there is money riding on it, but in poker, money is central to the play of the game. This is because bets communicate strength and weak-ness in poker-if players are not betting with real money, the "communication" is meaningless. As we know well by now, talk is cheap. Bluffing only has consequences if real money is at stake.

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