Full text of Economic Commentary (Federal Reserve Bank of Cleveland) : Why the Optimism?, April 1, 2002

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April 1, 2002

Federal Reserve Bank of Cleveland

Why The Optimism?
by John B. Carlson

ising productivity allows an economy to grow faster than its labor force
and thereby increases living standards. A
lot hinges on productivity’s future trend
growth rate. Small changes in assumptions about productivity growth, for
example, have huge implications for
budget forecasts and for the actuarial
soundness of Social Security.
Despite a stagnant economy, U.S. workers produced 2 percent more for every
hour they worked in 2001 than they had
in 2000—equal to the average annual
productivity increase over the past business cycle, but above the rate registered
from 1973 to 1990 (see figure 1). Recent
research suggests that productivity can
grow even faster over the years ahead,
with some economists projecting a range
as high as 3 percent. (See Jorgenson, Ho,
and Stiroh 2001 and Oliner and Sichel
2002 in the recommended readings).
Just four years ago, such projections
would not have been taken seriously.
The 1997 Economic Report of the
President, for instance, projected a meager 1.2 percent annual productivity gain
over a horizon of seven years. Given an
additional assumption that hours worked
would grow 1.1 percent, the economy
was projected to grow at an average
annual rate of 2.3 percent. The 2001
Economic Report of the President now
assumes an average productivity
increase of 2.1 percent a year over the
next 10 years, allowing 3.2 percent output growth over the same period. Is the
new-found optimism justifiable?
This Economic Commentary examines
the prospects for continued strong productivity growth. First, we examine evidence that recent productivity gains are
more resilient than first thought. We
then identify and discuss the primary
ISSN 0428-1276

engine for the recent productivity surge.
We also assess the basis for believing
that this engine of growth has many
miles left on it.

■

It’s for Real

As measured productivity accelerated in
the late 1990s, many economists questioned the sustainability of higher productivity growth. Some argued, for
example, that the increase was largely
related to the business cycle and hence a
transitory phenomenon. They noted that
productivity typically declines around
business cycle peaks. These skeptics,
who believed that the expansion was
running on borrowed time, reasoned that
productivity would eventually revert to
a lower trend.
Data available since the recent business
cycle peak, however, provide some
important evidence on this issue. Figure 2
illustrates that productivity often falls in
periods surrounding business cycle peaks.
Even when productivity has not declined,
its growth slows substantially relative to
the average rate over the previous business cycle. The 2001 peak, however, was
different. Although productivity growth
slowed from its recent trend, it was substantially stronger than it had been around
the peaks of previous expansions. The
1.4 percent productivity increase around
the 2001 peak is even more impressive
because it provides convincing evidence
that the acceleration in productivity is
more enduring than skeptics believed.
(For an alternative analysis documenting
the strength of productivity growth, see
Bauer, Jensen, and Schweitzer 2001).
This new evidence is somewhat limited,
however. Though it sheds light on the
recent productivity trend, it tells us little
about what to expect in the future.

In spite of the recent recession, hopes
for the New Economy have been little
daunted. Surprisingly robust productivity growth during the recent
downturn provides compelling new
evidence that something truly fundamental is going on. This Commentary
argues that advances in information
technology, and their diffusion
through the economy, are justifiable
reasons for our optimism. Higher
productivity growth is not an
ephemeral phenomenon but one likely
to persist for some time into the future,
perhaps even accelerating further.

What basis is there for extrapolating
higher productivity growth out over a
longer-term horizon? What are the fundamentals behind this growth? Are they
likely to persist? To answer these questions, we need to explore some factors
that account for the recent productivity
surge.

■

A Key Fundamental

Basic economic principles tell us that
labor productivity—the ratio of output to
an hour worked—can increase for several fundamental reasons. Clearly, productivity is enhanced when firms invest
in more efficient equipment and structures. In some cases machines may substitute directly for a worker, while in
other cases a new machine may help
workers produce more. Productivity is
also enhanced by more efficient ways of
organizing production and by increased
labor quality. Recent productivity gains
have been driven largely, but not exclusively, by new and more efficient equipment, especially in the information

technology (IT) sector. More importantly, the nature of these drivers suggests they will lead to comparable, if not
even greater gains, in the future.
In 1965 Gordon Moore—the cofounder
of Intel Corporation—observed that the
number of transistors on a silicon chip
had doubled every 18 months and was
likely to continue to do so. This seemingly specialized engineering prediction
turned out to be not only incredibly
accurate and durable, but also profound
in its economic importance. For the
number of transistors on a chip roughly
translates into computing power, and
increasing computing power is the rare
sort of technological advance that has
spillover effects that generate other
innovations.
It is doubtful that in 1965 many people
could appreciate the significance of that
important observation—now known as
Moore’s Law. Few people had any tangible connection to the advances in computing power. Personal computers had
not been invented. The early gains from
electronic computing power were
embodied in large, expensive “mainframe” computers and applied to very
specialized applications done largely at
universities and large corporations, in
the defense industry, and at the Census
Bureau.
The advent of the personal computer
changed things dramatically, illustrating
concretely how computing power could
be applied to a wide variety of purposes,
and thus highlighting the economic
salience of Moore’s Law. Those of us
who made the transition from electric
typewriters to early PCs and then to
their modern counterparts gained a clear
insight into the efficiencies of increased
computing power. Does anyone remember the slide rule—a necessary device
for engineering students as late as the
early 1970s? The development of the
Internet provides yet another worldtransforming gain from IT.
The economic importance of IT, while
now tangible to us all, has only recently
become obvious in the economy as a
whole. In 1987 Nobel Prize winning
economist Robert Solow observed, “You
can see the computer age everywhere
but in the productivity statistics.” Even
in the early 1990s there was no statistical
evidence that productivity had accelerated in the aggregate economy. In the

late 1990s we saw why this was so—the
IT sector was not yet big enough to matter. By the second half of the decade,
however, this would change. The IT sector expanded throughout the economy,
and productivity accelerated sharply.
Oliner and Sichel (2000) estimate that
during the period 1974 to 1990, the IT
capital sector accounted for only 3.3 percent of the income earned in the economy
but still contributed 0.5 percentage points
to economic growth. In the late 1990s,
they estimate that the IT sector expanded
to 6.3 percent of income earned and but
contributed 1.1 percentage points to
economic growth. It is important to note
that as IT’s share of income increased
91 percent, its contribution to growth
increased 124 percent. This extraproportional effect occurred because productivity gains in the IT sector were so much
higher than in the rest of the economy.
Thus, as the IT share grew, overall productivity accelerated.

■

Can Productivity Continue
to Accelerate?

Productivity could accelerate further if
Moore’s Law continues to hold and
advances in computing power continue
to diffuse throughout the economy. The
prospects for Moore’s Law seem very
promising. At a recent conference of
chipmakers, Intel’s current CEO Craig
Barrett predicted that it would hold for
another 15 years. Is this credible? The
37-year track record seems to dictate that
the burden of proof be on the doubter.
Moreover, computing power actually
accelerated in the late 1990s as Intel
sped up its product cycle—introducing
new chip designs every two years instead
of every three.
But Moore’s Law doesn’t have to hold
for productivity to accelerate. Even if the
pace of computing power growth slows,
average productivity can grow faster if
IT’s share of the economy grows sufficiently fast. Of course, just having more
computing power available doesn’t mean
that it will be effectively and usefully
employed. There must be some reason to
believe that households and businesses
will adopt the new technology and
thereby embed the productivity gains
in the economy as a whole.
Delong and Summers (2002) offer one
reason that IT’s share of the economy will
likely grow. They note that IT goods are
what economists call “luxury” goods. As

households become wealthier, they allocate an increasing share of their expenditures on such items. HDTVs, broadband
Internet connections, and other such
items will increasingly be added to the
shopping lists of American households,
especially if prices continue to fall.
Falling prices allow greater penetration
into smaller budgets. As IT’s share of
spending increases, income grows faster,
which in turn causes IT’s share to
increase further—a virtuous cycle.
There are other reasons to expect the
new technology to be drawn further into
the economy. First, IT is what is known
as a general-purpose technology—
meaning that efficiencies gained are not
solely embodied in the production of IT
equipment but are more generally transmitted throughout other sectors of the
economy such as automotive, housing,
retail, and so on. Today with PCs, engineers and architects conduct “what if”
experiments with computer-assisteddesign programs that make them much
more productive. Researchers in pharmaceutics use similar computer-assisted
experiments to generate new drugs at a
faster pace. Retailers have exploited new
IT technologies to organize their distribution systems more efficiently. The
result has been that firms that have
moved quickly to exploit the new technologies have increased market share,
inducing an acceleration in productivity
of the retail sector.
One interesting approach to assessing
the degree to which firms will invest in
new technology is developed by Cummins and Violante (2002). They assess
the potential returns that firms stand to
gain from investing in new technology.
Their approach calculates a “technology
gap”—a measure of how much more
productive new machines are compared
to the average machine currently
employed. They show that firms are
spurred on to invest more rapidly when
the technology gap widens. By their
estimates, the gap has increased substantially over the past decade. In 1975,
for example, they estimate that the average technology in use was 15 percent
less productive than the best practices
available at the time. By 2000, however,
the gap widened to 40 percent, despite
the huge increase in investment during
the 1990s.
This analysis bodes well over the near
term. One of the hallmarks of the New

FIGURE 1 PRODUCTIVITY GROWTH

FIGURE 2 PRODUCTIVITY GROWTH AROUND
BUSINESS CYCLE PEAKS
Annualized percent change
3.5

Percent change, (year-over-year)
6

3.0

Average over cycle

2.5

Average near peak a

4
2.0
3

1.5

1.0

0.5
0

0
1990:IIIQ–2001:IVQ,
average = 2.0%

–1

–0.5
–1.0

–2

–1.5

1973:IVQ–1990:IIIQ, average = 1.3%

–2.0

–3
12/73

12/77

12/81

12/85

12/89

12/93

SOURCE: U.S. Department of Labor, Bureau of Labor Statistics.

Economy is that firms are limited in
their ability to make price increases
stick. Firms can maintain or increase
their market shares only by becoming
more productive and inducing customers with lower prices. Competitive
pressures thus give firms strong incentives to invest in more efficient technologies, which, in the case of IT, are
becoming less costly. In many cases, it
will not be a matter of choice but one
of survival.

■

Some Concluding Thoughts

When Gordon Moore first observed the
pace at which computer chips were
shrinking, few if any could appreciate
its profound economic significance. It
wasn’t obvious in the productivity statistics even as recently as five years ago.
Today, computers are everywhere, even
in the productivity numbers. Now we
can say with some confidence that the
recent IT revolution has been an important component driving the acceleration
in productivity. We can even say that
higher productivity growth is not an
ephemeral phenomenon but one likely
to persist for some time into the future,
perhaps even accelerating further.

12/97

12/01

1960:IIQ

1969:IVQ

1980:IQ

1981:IIIQ

1990:IIIQ

2001:IQ

a. Annualized percent change from two quarters before a business cycle peak to two
quarters after it.
SOURCE: U.S. Department of Labor, Bureau of Labor Statistics.

We would be remiss in not offering a
caveat. Although the basis of the surge
in productivity is now better understood
and documented, we cannot know what
surprises the future might bring. With
so much at stake, it is human nature to
want to believe that the best outcome
will occur. Oliner and Sichel (2002)
remind us, however, that current estimates of the productivity trend might
best be thought of as structured guesses.
Even with that in mind, we have good
reasons be optimistic.

■

1973:IVQ

Full text of Economic Commentary (Federal Reserve Bank of Cleveland) : Why the Optimism?, April 1, 2002

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