by Maggie Mahar
In the late nineties, the Fed seized upon government reports that productivity was beginning to soar as proof of a structural change in the economy. But then the government began revising its numbers. “The 2.6 percent growth rate in 1999 was cut to 2.3 percent, and the stunning 4.3 percent rate in 2000, which converted many a skeptic to the new-economy cause, was cut to 3 percent,” Madrick reported. “This is hardly a deepening computer revolution.” Madrick, an economist and author of Why Economies Grow: The Forces That Shape Prosperity and How We Can Get Them Working Again, calculated that from 1990—the start of the cycle—to 2000, productivity rose by less than 2 percent a year.3
Indeed, even before the government revised its figures, research by Harvard economist James Medoff, published in Grant’s Interest Rate Observer, suggested that the only real gains in productivity were limited to the computer industry itself. And even there, the industry’s predilection for creative accounting made it difficult to be certain.
In the end, the problem is that it is very difficult to assess the value of the new technology. “Until it is set to profitable employment, a computer is a piece of furniture. Like a piano, its utility depends on the individual at the keyboard,” Grant observed. “He may play ‘The Moonlight Sonata’ or ‘Happy Birthday.’” When the New Economists estimated the value of the computers produced by the New Economy, they assumed, Grant suggested, “that the U.S. workforce studied at Juilliard.”4
PRODUCTIVITY AND PROFITS
But what of the Internet? Throughout the late nineties, the digerati would give the Net much credit as the catalyst for the boom—though again, it was hard to find concrete proof.
This was because, as a study released by McKinsey & Company in 2002 would reveal, total productivity gains after 1995 could be explained by the performance of just six sectors: retail, wholesale, securities, telecom, semiconductors, and computer manufacturing. “The other 70% of the economy contributed a mix of small productivity gains and losses that offset each other,” the study reported.
Moreover, of those six, only one sector benefited from the Internet: brokerages that sold securities to individual investors. Once again, the croupiers were the big winners: By the end of 1999, nearly 40 percent of retail securities trades were performed online—a huge boon to discount brokers such as Charles Schwab.
A close look at how much computers did for banking told another story. Despite generous spending on personal computers and software, retail banks, for instance, saw their productivity rate decline during the late nineties. “Banking was an example of an industry that spent on technology simply because it could,” McKinsey’s James Manyika explained. “It will now spend less.”5
Ultimately, “productivity statistics mistook a spending spree for increased efficiency,” declared Leon Levy, founder of the Oppenheimer Funds, and one of Wall Street’s shrewdest investors, in 2002. “With seemingly insatiable consumers willing to buy higher-priced goods, those selling the goods looked more efficient because their revenues were rising without any increase in their workforce.”6
Sales rose, but what about profits? The proof of productivity gains should be seen in earnings.
1997—A TURNING POINT FOR PROFITS
In fact, 1997 would turn out to be a watershed year for the New Economy, but not in the way that the New Economists expected. Corporate profits hit a wall: “According to government statistics, overall corporate profits grew rapidly between 1992 and 1997,” Princeton economist Paul Krugman observed, “but then stalled; after-tax profits in the third quarter of 2000 were barely higher than they were three years earlier.” Meanwhile, the “operating earnings” of the S&P 500—the profits companies reported to investors—showed 46 percent growth during those three years, thanks, largely, to “accounting gimmicks.”7
In reality, profit margins for the S&P 400 stopped expanding in 1996, according to a study by Sanford Bernstein, one of the few Wall Street firms that did not mix investment research with investment banking. After cleaning up the numbers, Bernstein discovered that from ’76 through 2000, the “exceptional performance” of operating margins in the second half of the nineties “disappear[ed] entirely.”8
How could this be? In theory, the more corporate America spent on information technology, the more efficient its workers would become—leading, inexorably, to higher profits. “Trouble is, productivity can have very little to do with profits,” noted Jeremy Grantham, the Boston-based money manager who pioneered the index fund. In two sentences, Grantham summed up the flaw in the New Economists’ theory: “Imagine what would happen if you lay a lot of cable, and it turns out to have five times more carrying capacity than before. It’s wonderful for productivity, and devastating for profits.”9
EXCESS CAPACITY
While more spending on technology can boost capacity, increased capacity does not necessarily mean higher earnings. To the contrary, when businesses sink billions into technology willy-nilly, more capacity can quickly become excess capacity, and as supply swamps demand, profits plunge.
By 1997, this is precisely what happened in some of the hottest sectors. Investors eager to buy technology stocks financed the boom in capital spending, and the Fed did its part by keeping interest rates low. Borrowing to build another factory seemed a bargain. “Presented with the financial means to build the extra semiconductor fabricating plant or the marginal personal-computer manufacturing plant, the world’s high-tech manufacturers have not hesitated,” Jim Grant noted in October of 1997. “A huge expansion of manufacturing capacity is under way—in chemicals, paper, aircraft, autos, commercial banking and high technology…. The result is a boom in productive capacity—and a collapse in the prices of memory chips and personal computers, the most basic commodities of the information age. Even Intel has lately been forced to cut the prices of its microprocessors. And the hottest new computers are the ones that sell for less than $1000.”10
Meanwhile, tech shares headed for heaven. In 1996, semiconductor shares rose 80 percent, computer hardware makers climbed 41 percent, and software companies rose 36 percent. Ten of technology’s blue chips—IBM, Oracle, Cisco Systems, Motorola, Hewlett-Packard, Sun Microsystems, Intel, Texas Instruments, Micron Technology, and Microsoft—boasted a combined market value of nearly $500 billion at the beginning of 1997, up a staggering $196 billion in fifteen months.
At the same time, industry fundamentals deteriorated. “Memory chip prices are in free fall,” Forbes reported early in 1997. “Spot price for the commodity 16-megabyte DRAM is currently around $6, down from $50 last year.” Meanwhile, 20 new chip plants were planned or under construction in Taiwan. Hyundai and LG Semicon in Korea were putting some 80 percent of their semiconductor sales into capital spending. “This fresh supply could drive chip prices down to $3 or $4. Bad news for Micron Technology, Texas Instruments, Atmel and others.”
PC makers benefited from falling chip prices and were still reporting impressive profits. But as competition heated up, the PC price wars began, with some computers marked down by as much as 40 percent in the weeks before Christmas of ’96.
Even with prices slashed, computers sat on the shelves. At the end of 1996, Wal-Mart announced that it would no longer sell PCs in 700 of its 1,600 stores.11
THE ASIAN CRISIS
By the summer of 1997, excess capacity was rearing its ugly head, not just at Wal-Mart but in Asia. Go-go growth in Southeast Asia had spurred the building of countless factories, and the result was a glut in virtually every sector: cars, chips, ships, clothing, cement, plastic, petrochemicals, and steel. Meanwhile, China was flooding its neighbors in Southeast Asia with cheap, well-made goods—crimping their export-led economies.
In the first half of 1997, China exported 25 percent more goods than it had a year earlier. In Malaysia, Thailand, the Philippines, and Indonesia, export prices sank, real estate prices sagged, and trade deficits grew. Countries throughout the region faced pressure to devalue their currencies in order to make their exports cheaper, the better
to compete with each other, and with China.12
And, ultimately, that is exactly what happened. In July, the Thai baht fell 12 percent against the dollar. Devaluations in the Philippines, Malaysia, and Indonesia followed, creating a domino effect that triggered stock market declines across the region.
Hong Kong held the line—but at a price. In October, the Hang Seng index plunged more than 16 percent in just two days. Within hours, what the media called “the Asian flu” spread to the United States. Fearing that the earnings of large U.S. companies exposed to Asia would suffer, investors headed for the exits.
On Monday, October 27, the Dow dropped 554 points—the largest one-day plunge in the market’s history. Still, in percentage terms, the Dow’s 12 percent drop from its August 6 peak paled in comparison with the 22.6 percent one-day plunge in 1987. And within days, the index bounced back, leading to the largest one-day gain in the market’s history.
Seasoned market watchers found the one-day gain almost as spooky as the one-day loss: such volatility confirmed Gail Dudack’s intuition that this was a market that had lost its rudder—a market driven by blind emotion.
Nevertheless, within a week many on Wall Street were shrugging off fears that the U.S. market would be affected by the “Asian contagion.”
“Wall Street: Too Healthy Right Now to Succumb to a Case of ‘Asian Flu,’” declared the headline in The International Herald Tribune, noting that “even the usually cautious Alan Greenspan last week characterized economic growth as ‘robust’ and inflation as ‘low.’”13
The Fed chairman was right. Inflation was not a problem. The greater threat was deflation—falling prices that could, in turn, squeeze profit margins. A fundamental imbalance between supply and demand was keeping prices low. Desperate to boost earnings and bring in dollars, Asia’s Newly Industrialized Countries slashed prices even further, and global competition intensified.
The U.S. economy avoided deflation, but in many areas prices remained flat. Overinvestment had created excess capacity at home and abroad, and as a result, U.S. corporations had lost “pricing power”—consumers would not accept price increases. Meanwhile, export opportunities for U.S. companies shrank as the dollar soared against most major currencies, making U.S. products more expensive abroad.
No wonder corporate earnings stalled in ’97.
NO MIRACLE FOR THE CHICKENS
The ultimate consequence of “Greenspan’s productivity bubble” would be unemployment. In a piece published on David Tice’s Prudentbear.com, Donald Perry used a parable to make the point. Dr. Perry was not an economist, nor was he a Wall Street strategist. He was, in fact, an ecologist—an outside observer with common sense—and he compared the New Economy to a chicken farm:
“Basically, productivity in the coop increases when chickens lay more eggs per day,” Perry wrote. “Early on farmers noted that hens could produce more eggs when confined to a cage, instead of running around searching for food, being chased by cocks, or having to evade predators. To understand productivity as it relates to the economy substitute the word ‘chicken’ for ‘worker.’”
If chickens are laying more eggs—but the price of eggs is falling—the egg business is at best “treading water,” Perry explained. Too many eggs, like too many cell phones or too many computers, leaves the chicken farmer with little power to raise prices. “What Greenspan fails to acknowledge,” Perry observed, “is that while American business may be producing more eggs, the bottom is dropping out from under the price of eggs.” The solution, for the egg farmer, is “to send some of the chickens to Campbell’s [where they would wind up, quite literally, in the soup]. The farmer then has fewer chickens to feed, gets the highest average output per chicken, and makes a little extra money in the process.
“But human chickens aren’t sent to Campbell’s,” he pointed out, “they get unemployment and buy fewer goods.” And, “since there are fewer buyers the glut of eggs becomes even greater.
“Another complication is that while it is plain to see that putting chickens in sweat shops all over the planet produces huge numbers of eggs, who will buy these eggs? Obviously, the market must correct itself by ‘wringing out the excesses.’ Ultimately many egg producers are going to go out of business. So when you hear Greenspan touting productivity gains you should be thinking ‘Who will be going out of business next?’ Hint: Asian chickens produce more eggs on less food.”
Before deciding that rising productivity is a boon, one needs to ask why it is rising, Perry suggested. Rising productivity “makes economic sense when production rises faster than ‘hours worked,’ but it makes little or no sense when—as in recent years—hours worked fall faster than rising production.”14
Or, as Gail Dudack put it: “When productivity gains are linked to jobs vanishing, we see no miracle.”15
1997: A TURNING POINT FOR THE MARKET
Gail Dudack had been a bull since she first appeared on Wall $treet Week with Louis Rukeyser at the tender age of 25. But by the beginning of 1997, she was convinced that share prices no longer reflected fundamental values. At the time, Dudack was chief market strategist at UBS Warburg, and she warned her clients: “By our measure, the equity market was fairly valued until October 1996.” After that, in Dudack’s view, stocks were overvalued.
“Back then, you had to be careful about using the word ‘bubble,’” she recalled six years later. “But in October of 1997, on the 10-year anniversary of the ’87 crash, I saw an opportunity to sound a warning, and I published a report that was, essentially, a review of Charles Kindleberger’s Manias, Panics and Crashes: A History of Financial Crisis. Those who believe that the ’90s are unique,” Dudack told her clients, “should read this book.”16
An economics professor at MIT writing in the late seventies, Kindleberger had outlined both the ingredients necessary to produce market manias and the role that central bankers like Alan Greenspan can play in fueling financial euphoria.
The first stage of a mania, according to Kindleberger, is usually an exogenous shock to the financial system: “This could be the beginning or end of a war, a bumper harvest or a new investment. Whatever the source it is sufficiently large and pervasive that it alters the economic outlook by changing profit opportunities in at least one important sector of the economy.”
In this case, Dudack told her clients, “We believe that the end of the Cold War and the birth of the Internet both qualify.”
“Easy money” (what Kindleberger called mismanagement of credit) is a second prerequisite for euphoria. Here, Dudack pointed out that the lending environment in the mid-nineties fit the scenario: “Credit cards are ubiquitous, sub-prime lending (to borrowers who ordinarily do not qualify for a loan) has been phenomenal and mortgages are available for 105% of the value of a home.”
A third ingredient: the con men. “Chapter titles such as ‘Fraud and the Cycle,’ ‘Bubbles and Swindlers,’ ‘Noble Gamblers,’ ‘Venal Journalism,’ ‘Dubious Practices,’ ‘The Temptation of Bankers’ and ‘The Wages of Sin’ tell it all,” Dudack noted. “But,” she warned, “many times these signs do not appear until after the crash. Japan would be a perfect example of this, where fraud in the brokerage industry and ties to the Mafia were identified after the Nikkei fell from 39,000 to 14,300.”
Finally, Kindleberger argued that during a financial mania “faith in the central banker” (in this case the Fed chairman) feeds complacency. Investors believe that if things fall apart, he will rescue them, and as a result, “the mania is likely to go on much longer and much further since there is little perception of risk by investors.”
Kindleberger made it clear that he did not believe central bankers have the power to eliminate financial manias. But he suggested that “the weight of the historical evidence strongly favors the case” that monetary policy (in this case, Fed policy) might “moderate” a boom that leads to a bust.
Greenspan’s critics would charge that, as the bubble grew, he did not even try. “When the Fed sends a s
ignal, it speaks to the world,” said Morgan Stanley’s Roach. “Greenspan condoned the bubble—and then concocted a theory as to why it was rational.”17
RETIREMENT ROULETTE
As belief in “Alan Greenspan’s Brave New World” blanketed the nation, wise-heads in Washington began to suggest that the government should begin gambling the Social Security Trust Fund’s assets on stocks. Early in 1997, the Advisory Council on Social Security issued a 752-page report that outlined three plans for “rescuing” Social Security.
As usual, Newsweek’s Allan Sloan pulled no punches. “What all three proposals have in common,” he observed, is that they “would throw us willy-nilly into a high-stakes game of retirement roulette, betting the nation’s financial future (or the futures of millions of individual retirees) on the stock market.”
“The council didn’t start out to do this,” Sloan pointed out. “Initially its members tried to agree on a cuts-and-taxes fix.”18 But some members feared that sharp tax increases and benefit cutbacks represented a politically unpalatable solution.
This is when they came up with the idea of betting 40 percent of the fund on stocks. (By law, the Social Security fund is required to invest only in Treasury bonds.) “How did the council’s biggest faction—six of 13 members—decide to put 40 percent of the fund in stocks?” Sloan asked. “‘That’s the amount that makes things come out,’ says panel member Robert Ball, the former Social Security commissioner who’s pushing this plan hard.”
Once again, Washington was working backward from high concept to empirical evidence. In what could be called the wish-fulfillment method of budgeting, the Advisory Council started with the amount that they guessed the Security Trust Fund would need, then determined that if 40 percent of Social Security savings were invested in equities, the fund would meet their goal—assuming, of course, that stocks returned an average of 11.28 percent a year.
