The Speed Limit

Say it ain't so, Joe," a young
boy is reputed to have implored Shoeless Joe Jackson, the tarnished
star of the infamous Chicago "Black Sox" in 1919. That
same cry went up in February 1997 when the Council of Economic
Advisers, then headed by Joseph Stiglitz, pegged the U.S. economy's
long-term growth rate at only 2.3 percent per annum. "Say
it ain't so, Joe."

Like the young baseball fan, growth optimists from
both the left and the right of the political spectrum do not want
harsh realities intruding upon and ruining their dreams. But Joe
Jackson couldn't say it wasn't so, because it was. And neither
could Joe Stiglitz.

Based on some simple arithmetic that I will display
shortly, mainstream economists are exceptionally united right
now around the proposition that the trend growth rate of real
gross domestic product (GDP) in the United States—the rate at
which the unemployment rate neither rises nor falls—is in the
2 percent to 2.5 percent range. In fact, a central aspect of the
allegedly sharp "controversy" between the Clinton administration
and the Congressional Budget Office (CBO) over the appropriate
"economic assumptions" to use in budget projections
is whether that growth rate is 2.3 percent or 2.1 percent. (The
CBO favors the latter.) That's some controversy.

Nevertheless, a number of leading politicians,
influential business executives, and popular writers refuse to
accept this "pessimistic" conclusion. We could grow
much faster, they insist, if only the government would pursue
more growth-oriented policies. Actually, the argument comes in
two distinct variants, which often get confused but ought to be
kept separate.

One variant makes a cyclical claim:
that overly tight monetary policies are holding back the economy.
According to critics from both the left and the right, a niggardly
Federal Reserve keeps pulling the U.S. economy up short of its
potential by hitting the monetary brakes prematurely, perhaps
because it is seeing inflationary ghosts. The implication is that
there is considerable slack left in the system, so we could grow
much faster for a while by bringing unused resources into

The second variant makes a claim about
long-run growth instead: that trend growth either is or could
be much faster than the conventionally estimated 2 to 2.5 percent.
We could exceed this false "speed limit" forever,
the argument goes, by adopting more capitalist-friendly tax and
regulatory policies. Normally, this critique comes from the right.
In the 1996 presidential campaign, for example, Bob Dole claimed
that his economic plan, which featured a large income tax cut,
would boost trend growth to 3.5 percent per year. His running
mate, Jack Kemp, went even further, asserting that those policies
would double the growth rate. Double? To 5 percent? Now there's
a real Shoeless Joe Jackson fan.

Mainstream economists dismiss both
of these arguments as mostly poppycock. This article explains
why. But let me first state unequivocally that no one wishes more
than I that both arguments were true. I also wish the Dodgers
would return to Brooklyn and that the world were free of want.
Unfortunately, none of these lovely things is in the offing.

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First, the cyclical argument. On this
view, lower interest rates could boost growth for a while without
raising inflation, so the Fed should ease up and give the economy
more running room. Is it true? Let's examine some pertinent facts.

The unemployment rate is by no means
a perfect indicator of aggregate pressure on capacity, but it
is about as good as we have. (Essentially the same story could
be told using the Federal Reserve's capacity utilization index
instead.) It declined from 7.7 percent in June 1992 to 5.8 percent
by September 1994, and then fluctuated within a narrow range between
5.8 percent and 5.4 percent until June 1996, when it dropped another
notch. Unemployment averaged just 5.3 percent between then and
March 1997. The April and May 1997 readings came in below 5 percent,
the lowest levels since 1973.

Let's consider what happened to inflation
during each of those three episodes. From June 1992 through August
1994, the unemployment rate was continuously above 6 percent,
averaging 6.8 percent, and inflation drifted lower. (See "Inflation
and Unemployment Rates Over the Past Decade
".) Then,
from the summer of 1994 to the summer of 1996, unemployment averaged
5.6 percent, and inflation remained remarkably stable. That experience
nominated 5.6 percent as an excellent estimate of the so-called
NAIRU (an awful acronym for the "Non-Accelerating Inflation
Rate of Unemployment"—in plain English, the rate at which
inflation neither rises nor falls).

Inflation and Unemployent Rates Over the Past Decade

Graph--inflation and unemployment rates
Source: Bureau of Labor Statistics

Since inflation fell when unemployment
averaged 6.8 percent and stabilized when unemployment averaged
5.6 percent, it stands to reason that unemployment much below
5.6 percent should make inflation rise. The last time we
experienced unemployment that low for a protracted period of time
was 1988 to 1990. The unemployment
rate first dipped below 6 percent in the fall of 1987, fell all
the way to 5 percent by March 1989, and did not climb back to
6 percent again until November 1990. During that period, core
inflation increased from about 4 percent to about 5.5 percent.
Thus the theory seemed to work pretty well.

Very recent experience has, however,
been somewhat more favorable than history would suggest—as it
has been remarked by many. Specifically, inflation appears to
have inched downward even as unemployment fell below
5.4 percent. But this period is less than a year long—far too
short to draw any conclusions, given the sluggish response of
inflation to tight markets. For example, a standard rule of thumb
suggests that if the NAIRU is 5.6 percent, one year of 5.2 percent
unemployment should boost the inflation rate by 0.2 percent. Such
a minuscule rise in inflation is simply too small to pick up in
the data. And furthermore, improvements in the Consumer Price
Index (CPI) have reduced measured inflation at precisely the same
time. To be sure, recent experience does offer some hope that
the NAIRU might be below 5.5 percent. But to conclude so at this
point would be premature.

Finally, let us ask what the miserly
Fed was doing while all this was going on. During the roughly
two-year period of 5.6 percent unemployment—a number that most
observers in 1994 thought to be below the NAIRU—the Fed first
raised its overnight interest rate by 1.25 percentage points (in
November 1994 and February 1995) to slow the economy, and then
lowered it by 0.75 percentage points (in July 1995, December 1995,
and January 1996) to give the economy a little boost. Thereafter,
until March 1997, it sat on its hands while the unemployment rate
not only remained low but actually drifted down. That does not
sound like Scrooge-like behavior to me. Rather, the Fed was cautiously
(and perhaps accidentally) probing how low the NAIRU might be.

Was the Fed really holding growth below
its potential? Remember, trend growth is defined as the rate that
is just enough to absorb the normal year-to-year increase in the
labor force, leaving the unemployment rate neither rising nor
falling. Let's look at the numbers. From the third quarter of
1994 through the first quarter of 1997, the annual growth rate
of real GDP averaged 2.6 percent. During those two and a half
years, the unemployment rate dropped by about 0.7 percent—which
means that 2.6 percent growth is somewhat above trend.

To claim that we could have grown much
faster without higher inflation is to claim that unemployment
could have fallen much more than it did without rising inflation.
Again, let's look at the numbers. Had growth averaged 3.5 percent
instead of 2.6 percent, the unemployment rate would now be below
4 percent—a rate last seen during the Vietnam War inflation. No
serious student of the U.S. labor market believes we have this
much unutilized labor. Indeed, anecdotal evidence from around
the country supports the conventional view that labor markets
are now very tight.

In sum, it is highly unlikely that
our economy has much running room before it reaches its normal,
full-employment capacity. In fact, it is more likely that we have
already passed this benchmark. Do economists know that with 100
percent certainty? Certainly not; this is not physics. But, if
you are planning to bet against it, insist on long odds.


Now let's turn to the bigger issue:
estimates of the economy's long-run growth trend. To begin with
a "top-down" estimate, recall that unemployment fell
while GDP growth averaged 2.6 percent. That means that the trend
must be below 2.6 percent per annum. How much below? The simplest
way to estimate the trend is to calculate real GDP growth between
any two years with equal unemployment rates. (Quarters will also
do, but using years rather than quarters helps smooth over blips
in the data.) The most recent such example is the period from
1990 to 1995. Over that five-year period, real growth averaged
1.9 percent per annum.

A "bottom-up" calculation
yields a similar estimate. The laws of arithmetic dictate that
you get the trend growth rate of output by adding up the growth
rates of labor input and labor's productivity—that is, output
per hour of work. Conventional estimates place each number around
1.1 percent per annum. So the estimated growth trend is 2.2 percent,
give or take a tenth or two.

Where could such a calculation go wrong?
There cannot be much dispute about the trend growth rate of the
labor force, which is known within a small margin of error. Notice,
by the way, that the labor force expanded about 1.7 percent annually
in the 1980s and 2.7 percent in the 1970s—which is one reason
why we can no longer grow as fast as we did then. (The huge expansion
of female labor force participation, for example, cannot be repeated.)

So the argument between a 2.2 percent
growth trend and a 3.5 percent growth trend cannot be about labor
force. It must be about productivity growth. And so it is. The
evidence for the mainstream view is neatly summarized in "The
Slowdown in Productivity Growth
" (below), which is adapted
from the 1997 Economic Report of the President. It shows
that output per hour in the U.S business sector grew much more
slowly after 1973 than before—just 1.1 percent per annum for 23
years. A prudent forecaster would extrapolate that behavior, not
presume that a sharp upsurge in productivity growth is imminent.

The Slowdown in Productivity Growth

Output per hour of work in the U.S. business sector.
Graph--slowdown in productivity growth
Source: U.S. Department of Labor

Here the growth optimists rise to object.
"Wait a minute," they say. "With all the evident
technological miracles in computers and telecommunications, and
with all the industrial restructuring, how can you expect us to
believe that productivity growth in the U.S. is just 1.1 percent
per annum? The measurements must be wrong." I'd like to answer
this objection at two levels, for in one sense I agree and in
another sense I disagree.

The disagreement is more important.
Suppose our trend productivity growth rate—under current official
measurements—was really much higher than 1.1 percent. For concreteness,
let's use the Dole-Kemp estimate of 2.4 percent. In that case,
GDP growth of 1.9 percent per year from 1990 to 1995 should have
been accomplished with decreasing use of labor input because
output per hour grew faster than output. In fact, payroll employment
expanded by almost eight million jobs. That's quite an error!
Another way to make the same point is this: If actual growth over
these five years really fell short of trend growth by 1.6 percent
per year (1.9 percent instead of 3.5 percent), the unemployment
rate should have risen by about 4 percentage points over this
period. In fact, it was unchanged.

But there is a sense in which the growth
optimists may be right: The official data may badly underestimate
productivity growth. Government statistics want us to believe
that what economists call total factor productivity—the increment
to output you get from skills, technology, and managerial efficiency,
without the need to apply any additional inputs—has not grown
at all since about 1977. That is simply not believable.

Readers of The American Prospect
will be aware of the recent debate over the so-called bias
in the Consumer Price Index. Arguments that the CPI overstates
inflation are compelling, although the magnitude of the bias
is hotly disputed. Fewer people seem to have noticed, however,
that any upward bias in measuring inflation implies a corresponding
downward bias in measuring real growth. And since labor
input is measured fairly precisely, the entire measurement error
shows up in productivity. For example, if inflation is overestimated
by 1 percent per year, then real growth may actually be a full
percentage point higher than recorded in the official statistics—say,
3 percent instead of 2 percent.

In this case, however, the growth optimists
who rail at the Fed for restraining the economy are still wrong.
Critics are confused on two points.

First, errors in measuring productivity
affect data on actual and potential GDP equally.
So they carry no implication that the economy has more spare capacity
than we think. It is not that we should be growing faster than
we are; it is that we are in fact growing faster than the data

Second, those who argue that the U.S.
economy has experienced a recent upsurge in productivity growth
must explain why the measurement error has grown much worse in
the last year or two, for the official data show no such upsurge.
No one has yet offered such an explanation.


The evidence I have just presented
is not secret; it is available to anyone who looks. Why, then,
do intelligent people ranging from Bob Dole and Jack Kemp on the
right through Jerry Jasinowski in the center to Lester Thurow
and Felix Rohatyn on the left argue otherwise? I have been able
to think of six reasons. Three of them are measurement issues.

First, as just noted, the likely overestimation
of inflation means that real growth has probably been underestimated.
We may well have been growing at 3 percent during the 1990s.

Second, the government altered its
measurement system at the start of 1996, adopting what the green-eyeshade
crowd calls "chain-weighted" GDP. Through the end of
1995, the government calculated real GDP by valuing all goods
and services at 1987 prices—which vastly overpriced computers,
for example. Chain-weighted GDP uses more recent market prices,
thereby putting less weight on computers. That naturally produces
slower measured growth even with no change in the real
economy. The new measurement system probably reduced the 1996
growth rate by about three-quarters of a percentage point.

Third, our antiquated statistical system
lavishes far too much attention on the manufacturing sector—which
accounts for only about 20 percent of GDP. Productivity performance
in manufacturing has indeed been excellent in recent years. No
argument there. The problems reside in the other 80 percent of
the economy, which is where most of us work.

Fourth, biases in reporting lead to
what I call "the tyranny of the selective anecdote."
The business press—like businesses themselves—tends to trumpet
success stories and bury failures. When leaders of particular
successful companies tell me that they have achieved dramatic
productivity gains, I believe them. But the U.S. economy is not
BusinessWeek cover stories writ large. Some companies downsize
and fail. Some companies automate with catastrophic results. That's
why we need economy-wide data.

Fifth, people tend to forget about
the reallocation of labor that accompanies downsizing. When some
large corporation restructures to produce the same output with
far less labor, its productivity rises dramatically. But the displaced
workers then must seek jobs elsewhere. If they find employment
in firms with much lower value-added per worker, then economy-wide
productivity may not rise much despite the vaunted productivity

Finally, I come to what may be the
biggest puzzle of them all—and perhaps the biggest reason for
the "Say it ain't so, Joe" attitude: advances in computers,
and in information technology (IT) more generally. As Robert Solow
has put it, "The computer is everywhere except in the productivity
statistics." Why not?

The pace of technological advance in
electronics has indeed been mind-boggling. Businesses now communicate
with lightning speed. Some serve their customers via automated
devices rather than human beings—ATMs, voice mail, and sales over
the Internet are common examples. Computerization has also revolutionized
some factory floors and the inventory management practices of
many companies. And so on. All this is beyond dispute.

But is this new computerized world
a vastly more productive world—in the narrow sense of producing
more GDP per hour of labor? The official statistics say no. In
fact, the timing of the productivity slowdown shown in "The
Slowdown in Productivity Growth
" corresponds roughly
to the invention of the personal computer. Furthermore, when you
examine the industry-by-industry data, some of the worst productivity
performances have been turned in where you might expect innovations
in IT to have paid the richest dividends. What's going on here?

No one knows for sure, but my tentative
answer is: Don't be taken in by the hyper-hype. Sure, I now can
surf the Net, send and receive e-mail in seconds, and have more
computing power on my desk than ever before. But has any of this
made me produce more GDP per hour of work? Don't forget that rapid
turnover of hardware and software keeps us perpetually in the
learning mode, that people spend countless hours mindlessly exploring
the Internet and playing amusing computer games, and that most
of us suffer more from information overload than from information
shortage. Perhaps most important, the human brain has not advanced
apace with the microprocessor.

A productivity miracle based on the
computer may be just around the corner. Perhaps. But, if so, it
is around the next corner, not the last one.


One final thought. This article is
intended as a reality check, not as a counsel of despair. Our
economy's long-run growth trend, be it 2.1 percent, 2.3 percent,
or 2.5 percent per year, is not a constant of nature. Growth can
be enhanced by intelligent economic policies and damaged by foolish

For example, the principal rationale
for reducing the government budget deficit is not to pay homage
to our Puritan ancestors, but to spur capital formation and thus
accelerate economic growth. Similarly, I have long urged greater
investments in education and training as a pro-growth policy.
And the basic case for government-supported research and development
is that R&D is the mainspring of total factor productivity
growth. Even well-designed tax, regulatory, and trade policies
can make modest and transitory contributions to growth.

Many such policies are well worth doing. An artfully
chosen combination might conceivably add one-quarter or even one-half
of a percentage point to the growth rate for a time, which would
certainly be a notable achievement. But with economic growth,
as with all things, you should be wary of fast-talking purveyors
of miracle cures. Nothing—I repeat, nothing—that economists know
about growth gives us a recipe for adding a percentage point or
more to the nation's growth rate on a sustained basis. Much as we might wish otherwise, it just ain't so.

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