The fuzzy logic of the "New Economy."

A couple of years ago the editor of Business Week had a problem with his car: Whenever he went too fast--whenever the needle on his speedometer went above 40--the car developed a dangerous shimmy. So he carefully drove to the repair shop, never letting the needle go past 39. Alas, after looking at the car, the mechanic declared that he couldn't fix the shimmy. Moreover, he had found another problem: The speedometer was defective. In fact, when the needle was pointing to 40, the car was actually going 55. And he couldn't fix that problem, either.

To the mechanic's surprise, the editor was pleased with this news. "So what you're telling me is that the car doesn't shimmy until I go 55 miles per hour. That means I can drive home 15 miles an hour faster than I drove here!"

OK, OK, I made that story up. I have never met Stephen Shepard, editor in chief of Business Week, but I'm sure that he would never make that kind of mistake in ordinary life. It would not be necessary for the mechanic to explain pedantically that, while it was true that the news about the speedometer implied that the car could go faster than previously thought, it did not change the speedometer reading at which the car shimmied.

But he is apparently not so clearheaded when it comes to economics. Indeed, the whole "New Economy" doctrine--a doctrine relentlessly espoused by his magazine for the last few years and vociferously defended in a recent signed essay by Shepard himself--is based on a misunderstanding of the relationship between measurement and reality that is conceptually identical to the garbled thinking of the imaginary editor retrieving his car.

The New Economy doctrine, sometimes called the New Economic Paradigm, may be summarized as the view that globalization and information technology have led to a surge in the productivity of U.S. workers. This, in turn, has produced a sharp increase in the rate of growth that the U.S. economy can achieve without running up against capacity limits. "Forget 2% real growth," urges Shepard. "We're talking 3%, or even 4%." This increase in the potential growth rate, in turn, is supposed to explain why the United States has managed to drive unemployment to a 25-year low without inflation.

The conventional view that the economy has a "speed limit" of around 2-percent to 2.5-percent growth does not come out of thin air. It is based on the real-life observation that when the output of the U.S. economy--as measured by real gross domestic product--is growing rapidly, the unemployment rate falls; when the output is growing slowly or is shrinking, the unemployment rate rises. Over the last 20 years, the break point--the growth rate at which unemployment neither rises nor falls--has been between 2 percent and 2.5 percent. And this break point does not seem to have changed much in recent years: Since mid-1994, GDP has grown at about a 2.7-percent annual rate, while unemployment has fallen at a steady rate, implying that the no-change-in-unemployment growth rate is closer to 2 percent than to 3 percent. (Click to see a chart that illustrates the break point.)

So what? Don't we want unemployment to fall? Yes, of course, but the unemployment rate can fall only so far. Obviously it can't go below zero; and in reality, the limits to growth are reached long before the economy gets to that point. Both logic and history tell us that when workers are very scarce and jobs very abundant, employers will start bidding against each other to attract workers, wages will begin rising rapidly, and real growth will give way to inflation. That means that while the economy can grow faster than 2-point-whatever percent for a while if it starts from a high rate of unemployment (like the 7.5-percent unemployment rate that prevailed in late 1992), in the long run, that growth rate cannot remain higher than the rate that keeps unemployment constant. And that is where the infamous "speed limit" comes from.

Behind that speed limit, in turn, lies another bit of arithmetic: The rate of growth of output, by definition, is the sum of the rate of growth of employment (which is limited by the size of the potential labor force) and that of productivity, a k a output per worker.

A ha! say the New Economy advocates--that's exactly our point. Productivity growth has accelerated, which means that the old speed limit has been repealed. It's true, they concede, that official productivity statistics do not show any dramatic acceleration--in fact, measured productivity growth in the '90s has been about 1 percent per year, an unimpressive performance similar to that of the two previous decades. (It has gone up more than 2 percent in the last year, but this is probably just a statistical blip.) But they insist that the official statistics miss the reality, understating true productivity growth because, as Shepard insists, "we don't know how to measure output in a high-tech service economy."

He's probably right about that. What he may not realize is that we really didn't know how to measure output in a medium-tech industrial economy, either. How could productivity indexes--which basically measure the ability of workers to produce a given set of goods--properly take account of such revolutionary innovations as automobiles, antibiotics, air conditioning, and long-playing records? Just about every economic historian who has looked at the issue believes that standard measures of productivity have consistently understated the true improvement in living standards for at least the past 140 years. It's anybody's guess whether unmeasured productivity growth in the last few years is greater or less than in the past. (My personal guess is that the hidden improvements are less important than they were in the 1950s and 1960s: For example, direct-dial long-distance calling and television made more real difference to our lives than the Internet and DVD.)