Ben S Bernanke: Productivity
Remarks by Mr Ben S Bernanke, Member of the Board of Governors of the US Federal Reserve
System, at the C Peter McColough Roundtable Series on International Economics, Council on Foreign
Relations, 19 January 2005.
The references for the speech can be found on the Board of Governors of the Federal Reserve System's website.
* * *
Almost certainly, the most important economic development in the United States in the past decade
has been the sustained increase in the rate of growth of labor productivity, or output per hour of work.
From the early 1970s until 1995, productivity growth in the U.S. nonfarm business sector averaged
about 1-1/2 percent per year - a disappointingly low figure relative both to historical U.S. experience
and to the performance of other industrial economies over the same period.1 Between 1995 and 2001,
however, the rate of productivity growth picked up significantly, to about 2-1/2 percent per year - a
figure that contributed to a growing perception that the United States might be entering a new
economic era. Talk of the "new economy" faded with the sharp declines in the stock valuations of
hightech firms at the turn of the millennium; yet, remarkably, productivity growth continued to rise. The
pace of productivity gains averaged better than 4 percent per year since 2001 despite adverse
developments that included the 2001 recession, the September 11 terrorist attacks, corporate
governance scandals, and, most recently, a sharp rise in energy costs.
Why is the rate of productivity growth so important? Economists agree that, in the long run,
productivity growth is the principal source of improvements in living standards. The link between
productivity growth and the standard of living of the average person is somewhat looser in the short-
to-medium run, as factors such as the share of the population that is employed and the division of
income between capital and labor also play a role. Nevertheless, the rate of productivity growth
influences the economy in important ways even in the short run, affecting key variables such as output
growth, employment growth, and the rate of inflation.
In my remarks today, I will discuss the pickup in U.S. productivity growth and its implications for the
economy. I will first review our current understanding of the causes of the recent productivity
resurgence. With that background, I will next consider the near-term prospects for productivity growth.
Finally, I will discuss briefly how the evolving productivity picture affects both the economic outlook
and the appropriate stance of monetary policy. As always, my remarks today do not necessarily reflect
the views of my colleagues at the Federal Reserve.2
The U.S. productivity resurgence and its causes
Why has productivity growth increased? The favored explanation of the rise in productivity growth
since about 1995 has evolved somewhat over time. By 2000 or so, an emerging consensus held that
the pickup in productivity growth was, for the most part, the product of rapid technological progress
and increased investment in new information and communication technologies (ICT) during the 1990s
(Jorgenson and Stiroh, 2000; Oliner and Sichel, 2000). According to this view, rapid developments in
ICT promoted U.S. productivity growth in two ways. First, technological advances allowed the
ICT-producing sectors themselves to exhibit rapid productivity growth. For example, the development
of more reliable semiconductor manufacturing equipment and faster wafer-inspection technologies
increased the rate at which companies such as Intel were able to produce microprocessors. In part as
a reaction to heightened competitive pressures, Intel also shortened its product cycle and increased
the frequency of new chip releases, shifting its product mix toward more-powerful (and, consequently,
higher-value) chips. Both the more-rapid pace of production and the higher average quality of output
raised productivity at Intel and competing firms.
Second, ICT advances also promoted productivity growth outside the ICT-producing sector, as firms in
a wide range of industries expanded their investments in high-tech equipment and software and used
the new technologies to reduce costs and increase quality (McKinsey, 2001). For example, some large
retailers, most notably Walmart, developed ICT-based tools to improve the management of their
supply chains and to increase their responsiveness to changes in the level and mix of customer
demand. Securities brokers and dealers achieved substantial productivity gains by automating their
trading processes and their back-office operations. In the durable goods sector, General Motors and
other automobile producers developed programmable tooling systems to increase the flexibility of their
manufacturing processes - for example, to permit vehicles based on different platforms to be produced
on the same assembly line. One study found that nearly two-thirds of U.S. industries, comprising about
70 percent of total employment, experienced an acceleration of productivity in the latter part of the
1990s. Significantly, the study also found the gains to be the greatest in industries using ICT capital
most intensively (Stiroh, 2002).
Undoubtedly, the ICT revolution and the productivity resurgence in the United States after 1995 were
closely connected, but several puzzles have arisen that challenge the view that ICT investment leads
mechanically to higher productivity. First, the United States was not the only country to see a rapid
expansion in ICT investment, as other industrial countries also invested heavily in these technologies
in the 1980s and 1990s. Yet, with a few exceptions, productivity growth in other advanced countries
has not increased recently to the extent seen in the United States. The comparison with the member
states of the European Union is particularly interesting. Throughout most of the post-World War II
period, labor productivity growth in Europe exceeded that in the United States, reflecting, first, rapid
gains during the postwar reconstruction and then a gradual convergence of European technology and
business practices to American standards. By one estimate, on average, European productivity
increased from 44 percent of the U.S. level in 1950 to 94 percent in 1995 (Gordon, 2004). However,
since about 1995, productivity growth in Europe has slowed, in contrast to the U.S. experience, and
productivity levels in the United States and Europe have begun to diverge.3
Researchers have made the important point that U.S.-European differences in productivity growth do
not appear to have been particularly large in the ICT-producing sectors, where U.S. strengths in the
development of information technologies have been offset by European leadership in communications.
Rather, the U.S. advantage has been most evident in the ICT-using sectors, which have performed
better in the United States than elsewhere. What accounts for the apparent U.S. advantage in
applying ICT to a wide range of industries?
One popular hypothesis, put forth by Alan Greenspan (2000) and Martin Feldstein (2001), holds that
European economies have been less successful in applying new technologies because of a relatively
heavy regulatory burden that inhibits flexibility. For example, taking full advantage of new information
and communication technologies may require extensive reorganization of work practices and the
reallocation of workers among firms and industries. Regulations that raise the cost of hiring and firing
workers and reduce employers' ability to change work assignments, as exist in a number of European
countries, may make such changes difficult to achieve. Likewise, the presence of government-owned
firms with a degree of monopoly power, together with restrictions on the entry of new firms, may
diminish competitive pressures that often foster innovation and greater efficiency (Nicoletti and
Scarpetta, 2003). Recent empirical research has generally found that economies with highly regulated
labor and product markets are indeed less able to make productive use of new technologies (Gust and
Marquez, 2004). Industry-specific regulations may also be an important barrier to productivity
improvement; for example, some writers have argued that restrictions on land use and on shopping
hours in Europe have impeded the development of "big box" retail outlets, denying European firms the
economies of scale that have been important for productivity growth in the U.S. retail sector (Gordon,
2004).
Differences in regulatory burden do not appear to be a complete explanation of comparative
productivity performance, however. For example, the United Kingdom, whose approach to the
regulation of labor and product markets is closer to that of the United States than to that of continental
Europe, has not done noticeably better in the productivity arena than other advanced European
countries (Basu, Fernald, Oulton, and Srinivasan, 2003). A shortage of workers with appropriate skills
may be part of the problem in the United Kingdom, as average educational attainment in that country
is lower than in many other industrial countries. Skill shortages may have also been a factor in
continental Europe, possibly because high youth unemployment has reduced opportunities for workers
to acquire new skills on the job. Other suggested explanations for the relatively better productivity
performance of the United States in recent years include the depth and flexibility of U.S. capital
markets, its relatively open immigration policies (at least before 9/11), and the role of U.S. research
universities in fostering innovation. Further study of the productivity differentials among the United
States, Europe, and other regions clearly is warranted.
A second puzzle that challenges the conclusion that advances in ICT are the primary source of recent
productivity gains is the observation that, over the past twenty years or so, increases in ICT
investment have not been followed reliably and in short order by increases in productivity growth.
Instead, the lag between investments in new technologies and their putative productivity benefits
appears to be long and variable. For example, ICT investment in the United States began in earnest in
the 1980s, but productivity did not begin to accelerate until the mid-1990s. Indeed, an oft-quoted quip
by economist Robert Solow held that, as of the late 1980s, "computers are everywhere except in the
productivity statistics."4 Likewise, although ICT investment declined sharply after the meltdown in tech
stocks in 2000, productivity growth has continued to rise in recent years, as I have already noted.
Perhaps the link between investment in high-tech capital and improving productivity is not so tight as
we thought.
In attempting to explain the relatively loose temporal link between ICT investment and productivity
growth, economists have emphasized that much more than the purchase of new high-tech equipment
is needed to achieve significant gains in productivity. First, managers must have a carefully
thought-out plan for using new technologies before they acquire them. Case studies of individual
industries show that, in some cases, the planning for technological modernization has not always been
adequate, with the result that some purchases of high-tech equipment and software have not added
much to productivity or profits. The idea that managers can buy the hardware first and then decide
what to do with it - sometimes heard as an explanation for the apparently delayed effects of
ICT investments made during the late-nineties boom - does not square with the case-study evidence.
Effective planning alone does not guarantee that ICT investments will be beneficial, however. Some
observers have characterized the new information and communications technologies as
generalpurpose technologies
(GPTs), which means that - like earlier GPTs such as electrification and the
internal combustion engine - they have the potential to revolutionize production and consumption
processes in a wide variety of contexts (Bresnahan and Trajtenberg, 1995). To make effective use of a
GPT within a specific firm or industry, however, managers must supplement their purchases of new
equipment with investments in research and development, worker training, and organizational
redesign - all examples of what economists call intangible capital. For example, to realize the benefits
of its ICT investments, Walmart had to reorganize work assignments, retrain workers, develop new
relationships with suppliers, and modify its management systems. Although investments in intangible
capital are (for the most part) not counted as capital investment in the national income and product
accounts, they appear to be quantitatively important.5 One recent study estimated that, by the late
1990s, investments in intangible capital by U.S. businesses were as large as investment in traditional,
tangible capital (Corrado, Hulten, and Sichel, 2004).
Recognizing the importance of intangible capital has several interesting implications. First, because
investment in intangible capital is typically treated as a current expense rather than as an investment,
aggregate saving and investment may be significantly understated in the U.S. official statistics.
Second, firms' need to invest in intangible capital - and thus to divert resources from the production of
market goods or services - helps to explain why measured output and productivity may decline initially
when firms introduce new technologies. Finally, the importance of intangible investment explains to
some degree why the lags between ICT investment and the resulting productivity gains can be long
and variable. Because investments in high-tech capital typically require complementary investments in
intangible capital for productivity gains to be realized, the benefits of high-tech investment may
become visible only after a period of time.
Medium-term prospects for productivity growth
Historical analysis of the sources of the productivity acceleration is challenging, but not nearly so
challenging as trying to predict how productivity will evolve over the next few years. However, because
the rate of productivity growth is a primary determinant of economic performance, policymakers have
few options other than to try to forecast future productivity gains. What can be said about the
mediumterm prospects for productivity growth?
The task of trying to predict the medium-term behavior of productivity is complicated by the fact that
productivity growth tends to vary with the business cycle. According to one popular hypothesis, this
tendency reflects cyclical variations in the intensity with which labor is utilized.6 Because adjusting the
size of a company's labor force may involve significant fixed costs (including training costs as well as
costs of hiring and firing), employers are generally reluctant to add or subtract workers at the first sign
of a change in the demand for their products. Thus, in the earliest stages of a contraction, for example,
employers may choose not to dismiss workers but instead to use them less intensively or assign them
tasks that do not involve current production, such as maintenance or training. Measured productivity
growth consequently declines when the economy enters a recession. Similarly, during the early stages
of an economic recovery, employers may hesitate to add new workers and instead may ask existing
employees to work harder, at least until the expansion seems better established. Output per hour of
work thus tends to rise faster than its secular (long-run) rate early in the recovery. Finally, as the
expansion matures and hiring picks up, productivity growth tends to slow again as the level of
employee effort returns to normal and as the need to devote firm resources to hiring and training new
workers detracts from current production. At present, three years from the official end of the 2001
recession, the U.S. economy has likely entered this latter stage, as productivity growth appears to be
falling from its recent high levels to a rate that is likely below its longer-term trend.
Cyclical factors tend to unwind, however; and so, looking ahead a couple of quarters, say, to the
second half of 2005, we can reasonably assume that productivity growth will approach its secular
trend. What is that trend? Using various econometric methods, together with a liberal dose of
judgment, several leading economists have recently offered estimates for secular productivity growth
of about 2-1/2 percent per year, close to the rate of productivity growth achieved during 1995-2001
(Baily, 2003; Gordon, 2003; Jorgenson, Ho, and Stiroh, 2004). If these estimates turn out to be correct
- and they are certainly subject to a great deal of uncertainty, as I will discuss - then the increase in
productivity growth of the mid-1990s may come to be seen as having initiated a new era for the
U.S. economy.
Of course, as the saying goes, past returns are not a guarantee of future results; not all the evidence
supports the emerging consensus that secular productivity growth will remain at its current elevated
level. For example, although spending on high-tech equipment and software has recovered smartly
from its recent lows, growth in ICT spending still remains well below rates seen before the 2001
recession. Some industry participants have suggested that less-rapid growth in ICT spending reflects
the absence of major new business applications for ICT - "killer apps," as they are called - and that
ICT investment for the foreseeable future will largely reflect replacement demands. Researchers have
also found some evidence that the technological frontier may not have advanced as quickly recently
as it did in earlier years; as one indicator, the price of computing power has recently declined more
slowly than it did in the 1980s and 1990s.
These caveats notwithstanding, I think the productivity optimists have a good case. Computing power
may not be falling in price quite so rapidly now as in the late 1990s, but a dollar nevertheless buys a
great deal more computational capacity today than it did even five years ago. And if rapidly improving
information and communication technologies are truly general-purpose technologies, history suggests
that they will continue to stimulate new ways of producing and of organizing production (DeLong,
2002). In particular, the enormous expansion in available computing power has already contributed to
advances in other emerging fields, such as biotechnology.
Moreover, even if the technological frontier advances more slowly during the next few years, further
diffusion of the existing technologies and applications can continue to raise aggregate productivity.
The available evidence suggests that this diffusion process is not complete. For example, a survey
conducted in 2003 by the Institute of Supply Management and Forrester Research found that most
managers consider their company to be at a relatively early stage in exploiting the potential gains from
using the Internet for their purchasing activities. In a more formal analysis, Jason Cummins and
Giovanni Violante constructed a measure of the "technological gap" in U.S. industry, defined as the
difference in efficiency between state-of-the-art capital equipment and the actual mix of equipment
held by firms (Cummins and Violante, 2002). As of 2000, the last year included in their study, the
authors found this gap to be 40 percent and rising, suggesting that substantial opportunities remain for
increasing productivity. This gap is unlikely to have declined much since 2000, for even if the rate of
technological progress has slowed, so has the pace of ICT investment.
I draw two conclusions: first, on the whole, the relatively optimistic estimates of secular productivity
growth espoused by leading scholars in the field do not seem unreasonable, so that, for the longer
term, continued growth in productivity in the range of, say, 2 percent to 2-1/2 percent per year
probably represents a good baseline assumption. Second, qualifying the first conclusion, the range of
uncertainty in forecasts of productivity growth is inevitably quite wide. For example, a 2004 study by
three leading scholars produced an estimate of trend productivity growth of 2.6 percent, but with a
range of plausible outcomes between 1.4 percent and 3.2 percent (Jorgenson, Ho, and Stiroh, 2004).
This qualification naturally leads us to ask: Suppose that, over the next year, the incoming evidence
suggests that the trend rate of productivity growth is either substantially higher or substantially lower
than we currently expect. How would that development affect the economy and monetary policy? In
the final portion of my remarks, I will address this important question.
Implications for the economy and monetary policy
For concreteness, suppose that the pace of productivity gains in the latter part of 2005 and in 2006
proves disappointing, sufficiently so to suggest that current estimates of the sustainable rate of
productivity growth may be overoptimistic. Let us first consider what this information would likely imply
for the medium-term economic forecast. To anticipate the conclusion, we will see that the strength of
the response of aggregate demand to productivity developments is the key determinant of their overall
impact.7
In the first instance, incoming evidence of a secular slowdown in productivity would likely result in
slower growth in consumption spending, capital investment, and aggregate output relative to what
would have been otherwise expected. Consumption growth would weaken as downwardly revised
profit expectations limit stock market gains, thereby reducing household wealth, and as
moreforesighted consumers perceive that smaller productivity gains portend lower real wage growth. Lower
expected rates of productivity growth should also tend to moderate growth in business investment by
reducing the prospective return to capital. As consumption and investment spending make up more
than four-fifths of aggregate output, slower productivity growth would perforce reduce output growth as
well.
What about inflation? In principle, the medium-term effect of slowing productivity growth on inflation is
ambiguous. As a number of analysts have noted, under the reasonable assumption that nominal
wages adjust slowly, slower productivity growth results in a more rapid rise in unit labor costs (the
nominal-wage cost of producing a unit of output).8 All else equal, a more rapid increase in unit labor
costs will tend to increase inflation as well. However, the effect of higher unit labor costs may be offset
if the decline in consumption and investment spending induced by the productivity slowdown is
particularly sharp. Indeed, a large deceleration in spending could conceivably cause inflation to slow
following a productivity slowdown, as firms' markups contract more than unit labor costs rise.
The effect of a productivity slowdown on employment growth is likewise ambiguous in the medium
term. Slower output growth depresses employment growth as firms face weaker demand, but slower
productivity growth implies that firms need more workers to produce a given level of output. As in the
case of inflation, the strength of the spending response is crucial. The more sharply spending and
output decline following a productivity slowdown, the more adverse the effects on employment will be.
Both the late 1990s and the more recent period illustrate the central role of the spending response in
determining the macroeconomic effects of a change in productivity growth, although (as I have
discussed today) in both of these episodes the productivity surprise was to the upside rather than the
downside. The rise in productivity growth after 1995 was accompanied by surges in both consumption
and investment spending, supported by a booming stock market. Employment rose and
unemployment fell, as the strength of aggregate demand induced employers to hire, the increases in
productivity notwithstanding. Inflation remained fairly stable during this period, as upward pressures
from increased aggregate demand were balanced by downward pressures on unit labor costs (for any
given level of wages) and by the increase in aggregate supply created by higher productivity.
In contrast to the experience of the late 1990s, during the early part of the new millennium the
response of spending to rising productivity growth was comparatively weak. Investment spending was
particularly slow to respond to the further increase in productivity growth, for reasons that are still
debated. Possible explanations for the weak investment response include an unusually high degree of
corporate caution, cost-cutting pressures, and the after-effects of the corporate governance scandals
of 2002. An explanation suggested by my discussion today is that, for most of this period, companies
were enjoying the fruits - in terms of higher productivity - of earlier investments in both tangible and
intangible capital. The extra productive capacity created by those investments, together with a
recovery whose durability in the early stages was not assured, may have implied little need for further
investment, at least until relatively recently. Whatever the cause, the weaker response of spending in
the more-recent period, coupled with impressive gains in productivity, helped to generate both a
pattern of slow job growth (the "jobless recovery") and the worrisome decline in inflation in 2003.
What are the implications of these observations for current monetary policy? Certainly, monetary
policy makers should pay close attention to developments on the productivity front, as the effects of
changing productivity trends permeate the economy. However, as we have seen, the appropriate
policy response to any perceived change in the trend rate of productivity growth will depend to a
significant degree on the response of private-sector spending. For example, if productivity growth
appears poised to decelerate, but (for whatever reason) aggregate private spending does not slow
materially in response, then inflation risks would rise, but employment would not be adversely affected.
The appropriate response in this case would be a tightening of monetary policy (or a more rapid
removal of accommodation). On the other hand, if slower productivity growth were accompanied by a
sufficiently large slowdown in aggregate demand and economic activity, then easier monetary policy
(or a slower removal of policy accommodation) might be called for.
My best guess - and it is only a guess - is that future responses of consumption and investment
spending to changes in the pace of productivity growth are likely to be less powerful than those of the
late 1990s, if for no other reason than that we may have learned to be more careful in our
enthusiasms. If so, then the principal effect of an unexpected slowdown in productivity growth during
the next few years would likely be higher inflation, with the short-term impact on the growth of output
and employment likely to be relatively minor. In this scenario, the appropriate monetary policy
response would be toward less accommodation. By similar reasoning, if productivity growth were to
accelerate in the next few years, then easing inflation pressures and slowing employment growth
would likely allow for less-restrictive policies. As I have emphasized, however, these conclusions
depend on other developments in the economy, most importantly on how strongly aggregate spending
responds to any perceived change in secular productivity growth.
Of course, it should go without saying that the world is more complicated than theoretical arguments
suggest. Notably, imperfect data and the difficulties of distinguishing permanent from temporary
changes will make changes in secular productivity growth exceptionally difficult to identify in real time,
both for the private sector and for the Federal Reserve. The need to discern the underlying economic
forces and to react appropriately in an environment of incomplete information makes monetary policy
an exceptionally challenging endeavor.