Cool.

After you are done investing in internet social networking websites, I have some investment opportunities for you in a few record labels,

Guaranteed to make money. Record labels! How can you go wrong?

Also, I can get you stocks in furniture.com for dirt cheap.

The Boom and Bust in Information Technology Investment*
Mark Doms
Senior Economist
Federal Reserve Bank of San Francisco
The growth rate of business investment in information technology boomed in the 1990s and 2000 before plunging in 2001.
This boom and bust raises some natural questions: what were the reasons for the accentuated swings in growth rates, and,
more importantly, what do those reasons portend for the future of IT investment? Much of the increase in IT investment in
the late 1990s appears to be attributable to falling prices of IT goods, which in turn is largely attributable to technological
change. However, IT investment was much higher in 1999 and 2000 than a model would predict. Another reason for the high
growth rates in IT investment was that expectations were too high, especially in two sectors of the economy, telecommunications
services and the dot-com sector. Looking ahead, technological change in the IT area will likely continue to move
quickly, in large part because large amounts of research and development are being devoted to finding further technological
breakthroughs.
Figure 1
Annual Percent Change in IT Investment
-20
-10
0
10
20
30
40
91 92 93 94 95 96 97 98 99 00 01 02 03
Nominal IT investment
Real IT investment
Percent
Source: Bureau of Economic Analysis. Percent changes based on year-end
values.
1. Introduction
The last recession may well be remembered as a high-tech
recession. The growth rate of investment by businesses in
computers, communications equipment, and software (referred
to as IT investment in this paper) boomed in the
1990s and 2000 before plunging in 2001. As shown in
Figure 1, growth in real IT investment was especially
strong between 1995 and 2000, averaging 24 percent per
year and adding an annual average of over 3/4 percentage
point to GDP growth (not shown).1 However, in 2001, IT
investment contracted sharply, with real IT investment
falling nearly 11 percent and nominal investment plunging
almost 17 percent.2 In 2002, with a recovery in IT investment
late in the year, real and nominal IT investment were
up modestly. IT investment picked up further in 2003, with
real investment posting a respectable 21 percent increase.3
The boom and bust in IT investment raises some natural
questions: what were the reasons for the accentuated
*I thank Fred Furlong and Anita Todd for their comments. I also thank
Ashley Maurier for technical assistance and Ana Aizcorbe, Charles
Gilbert, and Michael Kiley for data.
1. All percent changes are reported on an end-of-year basis unless otherwise
noted.
2. When it comes to IT investment, the distinction between nominal and
real investment can be quite important; for a discussion of the relationship
between nominal and real investment and prices, see Box 1.
3. For a fuller and very readable discussion of the importance of IT to
the economy, see Department of Commerce (2003).
20 FRBSF Economic Review 2004
expectations on the returns to IT investment, or changes in
the service lives of IT goods, or some other factors?
To get at the answers to these questions, I present results
from a model of IT investment to identify those portions of
investment that are “explained” by economic fundamentals
and those portions that are “unexplained.” I then discuss
and examine the reasons for the explained and unexplained
portions. In a nutshell, the model suggests that most, but
not all, of the very high rate of IT investment growth from
1994 through 1999 can be explained. The driving force behind
the high rates predicted by the model is the cost of IT
goods; these costs fall much more quickly than costs for
other investment goods, hence the demand for IT goods
rises. However, the gap between actual and predicted IT investment
(the unexplained portion) grows in 1999 and
2000. Additionally, IT investment falls more quickly than
the model predicts in 2001 and stays below the model’s
predictions for 2002 and into 2003 (that is, the unexplained
portion turns negative and remains negative).
In trying to understand what can “explain” the unexplained
portions, one hypothesis that I examine is that
overly exuberant expectations about IT investment led
businesses to overinvest in IT systematically. At first
glance, the sharp contraction in IT investment following
several years of exceptionally high growth lends credence
to this hypothesis. However, the exceptional productivity
performance in the economy that coincided with the boom
in IT investment throws this hypothesis into doubt. With
that said, there were indeed pockets in the economy that, ex
post, overinvested in IT; two such pockets were the
telecommunications services and dot-com sectors. Capital
spending by telecom service providers, which are large
consumers of IT products, surged in 2000 and subsequently
fell sharply in 2001 and 2002. In fact, estimates
show that the large swing in nominal IT investment between
2000 and 2001 was greatly exacerbated by the telecom
service industry, and that the telecom service industry
placed a significant drag on nominal IT investment in
2002. Data for the dot-com industry are harder to come by.
However, by several measures, it appears that the rise and
fall of the dot-com industry plays a nontrivial role in understanding
the “unexplained” portion of IT investment.
Another hypothesis for why the model of investment
would have underpredicted then overpredicted IT investment
is that service lives of IT equipment were shortened
in the late 1990s (boosting investment) and subsequently
lengthened in this decade (damping investment). One reason
why service lives were shortened in the late 1990s was
because concerns surrounding the effects of the century
date change (known as Y2K) forced firms to replace some
of their IT capital earlier than they had expected. However,
based on survey data, I find that the Y2K problem played a
minor role, at best, in the swings in IT investment. A second
reason for shortened service lives is that advances in
personal computer (PC) software increased the obsolescence
of PCs; thus, many firms upgraded their PC stock in
the late 1990s, earlier than they had anticipated. So far this
decade, so the story goes, the rate of obsolescence has apparently
been reduced, lengthening the service lives of PCs
and damping IT investment. Quantifying this story is extremely
difficult, but there is much circumstantial evidence
suggesting that this may indeed have happened.
The stories just discussed help explain why IT investment
was so high in 1999 and 2000 and why it fell so
quickly in 2001. However, the most salient feature of the
model of IT investment is just how much growth in IT investment
it predicted. The growth in predicted IT investment
stems largely from the fall in prices of IT goods,
which results largely from technological progress. I find
that prices for several IT goods fell very quickly during the
late 1990s, and that these drops in prices appear to coincide
with an acceleration in technological progress. Prices in the
late 1990s probably fell even faster than the official data indicate,
especially for communications gear and software.
There is also some evidence that technological progress
eased up some at the beginning of this decade but continues
to gain at a rapid pace. Looking forward, it appears that
the pace of technological change for IT products should
continue for a while, reflecting the large amounts that companies
are spending on R&D and the expectations about
what products can be developed.
Large differences in the growth rates for nominal investment
and real investment can arise because the prices for
high tech goods fall much more quickly than overall
prices. As an example, say that nominal investment in (that
is, actual dollars spent on) computers falls 10 percent in a
year. However, as has been well documented and extensively
studied, the prices of computers tend to fall sharply,
averaging over 20 percent per year. In our example, suppose
that prices fall 20 percent. Then, although nominal investment
falls 10 percent, real investment grows by 12.5
percent.1 Therefore, there can sometimes be confusion
over what constitutes a rebound in investment.
1. The real growth rate in percent between two time periods (t
and t + 1) is 100 × [(Nt+1/Pt+1)/(Nt/Pt ) − 1] , where N
denotes nominal investment and P is the price index.
Box 1
The Relationship between Prices and
Nominal and Real Investment
Doms / The Boom and Bust in Information Technology Investment 21
In this paper, Section 2 presents the stylized facts about
investment in IT goods. Section 3 discusses a model of IT
investment, highlighting those factors that are important
behind investment and a rough framework to think about
IT investment. To address some possible reasons for the errors
in the investment model, I present a discussion of the
role of overly optimistic expectations in Section 4 and the
role of shortened IT service lives in Section 5. To explain
one of the more important determinants of IT investment, I
describe what has happened to prices and technological
change for computers, communications equipment, and
software in Section 6. Section 7 concludes with some information
about what may be in store for technological
change in the IT field.
2. Basic Facts of the Boom and Bust
Investment in IT has become an increasingly important
component of the economy and played a disproportionately
large role in the past economic downturn. In 1990,
nominal investment in IT goods totaled just $131.5 billion,
a bit less than one-third of private nonresidential equipment
and software (E&S) investment. By 2000, IT investment
had surged to $401.6 billion, close to a 44 percent
share of E&S spending. Nominal IT investment still accounted
for close to 43 percent of E&S investment in 2003,
two years after the IT bubble burst.
These IT investments contributed significantly to GDP
growth during the late 1990s and contributed greatly to the
swings in GDP growth during the past economic downturn.
For instance, IT investment contributed about 3/4 percentage
point to real GDP growth in 1998, 1999, and again
in 2000. However, in 2001, the drop in IT investment subtracted
0.4 percentage point from GDP growth. After having
a minor effect in 2002, IT investment once again
provided a substantive boost to GDP in 2003 by contributing
0.7 percentage point to growth.
Table 1 presents a fuller description of what happened to
IT investment in the late 1990s and so far this decade. The
table summarizes the changes in nominal investment,
prices, and real investment for three IT categories: software,
computers, and communications equipment. The
table also presents statistics on nonresidential investment
outside of IT (non-IT). There are several stories to take
away from the table. The most striking is that nominal and
real investment grew very sharply during the late 1990s
and into 2000 for all IT categories. Between 1995 and
2000, growth in IT investment in real terms averaged
nearly 24 percent per year, five times greater than investment
in other types of equipment. In nominal terms,
Table 1
Changes in Nominal Investment, Real Investment, and Prices for IT
Average annual percent change Percent change from preceding year
____________________________________ __________________________________________________
1990–1995 1995–2000 2000–2003 1999 2000 2001 2002 2003
Nominal investment
IT 10.0 14.2 –1.2 15.3 16.0 –16.6 0.2 15.5
Software 9.5 18.5 0.8 24.1 12.2 –9.6 2.5 10.6
Computers 13.5 7.1 1.4 6.6 9.2 –23.4 8.4 25.4
Communications equipment 7.2 15.5 –6.4 11.0 28.6 –21.1 –9.8 15.2
Non-IT 6.8 4.9 –1.4 3.6 0.2 –7.8 0.3 3.6
Prices
IT –6.2 –7.8 –4.8 –5.7 –2.4 –6.6 –3.9 –4.0
Software –2.7 –0.5 –0.9 2.3 3.5 –0.4 –0.7 –1.7
Computers –14.8 –21.0 –14.3 –18.3 –11.1 –20.6 –11.8 –10.1
Communications equipment –1.4 –3.4 –2.7 –4.7 –3.2 –3.9 –2.4 –1.8
Non-IT 1.9 0.4 1.3 –0.1 0.5 0.6 0.6 2.8
Real Investment
IT 17.2 23.8 3.9 22.3 18.9 –10.7 4.3 20.3
Software 12.6 19.1 1.8 21.3 8.4 –9.3 3.2 12.6
Computers 33.2 35.6 18.3 30.5 22.9 –3.5 22.9 39.6
Communications equipment 8.7 19.6 –3.8 16.6 32.9 –17.9 –7.6 17.4
Non-IT 4.8 4.4 –2.7 3.7 –0.3 –8.3 –0.3 0.8
Source: Bureau of Economic Analysis. All figures computed using year-end values.
22 FRBSF Economic Review 2004
growth in IT investment in the late 1990s was nearly three
times as great as in other equipment.
The gaps between the growth rates in real and nominal
IT investment reflect the estimated changes in prices for IT
equipment and software based on price deflators compiled
by the Bureau of Labor Statistics (BLS) and the Bureau of
Economic Analysis (BEA). These agencies face a difficult
task in deriving accurate price indexes for IT products because
IT products are constantly changing. There has been
much research into measuring prices for computers (the
component of IT that shows the fastest price declines), but
much less progress has been made in measuring qualityadjusted
prices for software and communications equipment.
As I discuss in Section 6, it is very likely that prices
for these two components actually fell much faster than the
official data indicate, implying that the growth in real investment
was even higher than reported in the table.
Another notable feature in Table 1 is the sharp reversal
of fortune that befell IT investment and other investment to
a lesser extent in 2001. To paraphrase, the higher the rise,
the harder the fall. Nominal IT investment dropped almost
17 percent in 2001, a whopping 33 percentage point reversal,
reflecting declines in all three IT categories, but especially
for computers and communications equipment. Real
investment in IT declined 10.7 percent in 2001, representing
an equally stunning swing in growth rates. The slide in
IT investment began to reverse slowly in 2002 and had recovered
substantially by the end of 2003.
Although business demand for IT goods declined sharply
during the recession, the declines should not be overstated
since the level of investment remained high. For instance,
nominal investment in 2002 was at the same level as it was
in 1999, and real investment was 30 percent higher, indicating
that businesses continued to add to their stock of IT
hardware and software, at least in real terms.
3. A Model of IT Investment
The data in the previous section show IT investment went
through a period of phenomenal growth followed by a
sudden contraction. This brings to mind the question,
how much of this pattern was based on economic fundamentals
and how much was based on other factors?
Another way to pose the question is to ask, how much of
the boom and bust in IT investment can be “explained” by
traditional models of IT investment and how much is “unexplained”?
One model of IT investment, as described in Kiley
(2001), is part of the larger macroeconomic model,
known as FRB/US, that is maintained at the Board of
Governors of the Federal Reserve System. At its heart,
the FRB/US model asks what profit-maximizing amount
of IT capital firms in the U.S. economy should have, what
it refers to as the “optimal” IT capital stock. The optimal
IT capital stock for the economy depends on a number of
factors, including a concept referred to as the “user cost
of capital.” The user cost of capital is akin to the wage
rate for labor in that it attempts to capture how much it
costs a firm to use a piece of capital over a period of time,
just as the wage rate attempts to capture how much a firm
has to pay for a worker. Box 2 provides more details.
Although the exact construction of the user cost of capital
can be a little convoluted, it stands to reason that if, for instance,
the user cost of IT declines, then firms would buy
more IT and substitute away from other factors of production,
such as labor or other types of capital.
Figure 2 shows indexes of the user cost for IT goods
and for other investment goods since 1990.4 The user cost
of IT goods has fallen over time, averaging about 6 percent
per year in the early 1990s and over 7 percent in the
late 1990s. In contrast, the user cost of non-IT goods increased
an average of little more than 1 percent per year
from 1990 to 2003. Over the 1990s, the primary factor
driving down the user cost of IT was the decline in the
price of IT capital goods, at least as measured by the BLS
and BEA. The decline in the prices for IT goods was stunning,
and, like other normal goods, these falling prices
pushed up the quantity of IT capital demanded by busi-
The user cost of capital is made up of two types of costs.
The first is the cost of the acquisition of the capital good,
and this equals the prevailing interest rate, i , multiplied by
the purchase price of the capital good, pt .
The second type of cost is what happens to the value of
the capital good over the period it is used. This type of cost
includes the change in prices, π , and depreciation, δ .
Depreciation is the idea that the value of the good declines
over time simply because it ages. The change in prices, π ,
enters into the user cost because the worth of a good depends
on the market for that good. Say, for example, a
company buys a computer for $1,000. If computer prices
fall 20 percent in the next year, that computer will have lost
$200 in value because of price changes alone.
Putting all of these components together (excluding the
effects of taxes for simplicity), the user cost of capital can
be written as
(1) UCt = pt (it + δ − πt ) .
Box 2
The User Cost of Capital
4. The user costs shown here do not make any adjustments for taxes.
Doms / The Boom and Bust in Information Technology Investment 23
nesses. In fact, the declining user cost for IT is the primary
driver of the strong IT investment during the 1990s,
according to FRB/US.
Using the user cost of capital, FRB/US estimates how
much IT investment would be necessary to reach the optimal
capital stock. This is referred to as the “target level”
of investment. Figure 3 shows actual real IT investment
and the target level of real investment predicted by
FRB/US since 1994.5,6 The figure shows that the target
level of investment and actual investment track each other
fairly well from 1994 to 1998, though FRB/US tends to
systematically underestimate IT investment a bit. For instance,
over the 1994 to 1998 period, the average target
IT investment growth is 24.4 percent per year, compared
to 25.2 percent for actual IT investment. The underestimation
of the model is about $26 billion (in 1996 dollars)
as of 1998. That is, IT investment was about 6 percent
greater in 1998 than would be expected based on the
model.
The model does not do quite as well predicting the
rapid growth of IT investment in 1999 nor the slump during
the recession and the degree of rebound. For instance,
the model predicted that real investment would increase
14.7 percent in 1999, when in fact it increased 20.5 percent.
Also, in 2001, the model predicted a 7.9 percent increase,
but investment actually fell 7.8 percent.7 In 2002,
actual investment remained below predicted investment.
In the first half of 2003, some shortfall in actual investment
still was evident, but it was quite small.
The results in Figure 3 appear to take a good deal of the
mystery out of the boom in IT investment by businesses.
A concern is that the results in Figure 3 are based on an
estimated model. However, the results of the model
should not be taken as truth for several reasons. For example,
the outputs of the model are only as good as the
inputs, and, as I discuss later in this paper, it is extremely
difficult to measure the components of IT properly.
Additionally, there are the problems associated with any
estimated model, such as parameters that may vary over
5. The FRB/US estimates are based on data from before the benchmark
revision in December 2003. It is too early to tell if the new data will produce
a better or worse fit. However, the percentage decrease in real IT
investment in 2001 before the benchmark revision was 7.2 percent, and
after the benchmark revision the drop was 2.7 percent.
6. Figure 3 is drawn with a logarithmic vertical scale instead of a traditional
linear vertical scale. A straight line on a graph with a logarithmic
vertical scale indicates that a series is changing at a constant rate. In contrast,
when graphed with a traditional linear vertical scale, that same series
that increases at a positive constant rate would become steeper over
time. The distinction between linear and logarithmic scales can be especially
important for a variety of series in the IT industry that are characterized
by high growth rates, such as Moore’s law, the speed of
microprocessors, the prices of IT goods, and so on.
7. These gaps are large relative to how FRB/US performs for other
types of equipment investment.
Figure 2
Indexes of User Costs for IT and Other Equipment
(1990:Q1=1)
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1990 1992 1994 1996 1998 2000 2002
IT
Other equipment
Source: Federal Reserve Board of Governors.
1994 1995 1996 1997 1998 1999 2000 2001 2002 2003
150
200
300
400
500
600
656500
600
500
400
300
200
150
1994 1995 1996 1997 1998 1999 2000 2001 2002 2003
Actual real
IT investment
Target real
IT investment
Source: Federal Reserve Board of Governors.
$ billions
(log-scale)
Figure 3
Actual and Target Real IT Investment
(1996 $ Billions)
24 FRBSF Economic Review 2004
time or missing factors in the equations. Therefore, it is
still interesting to ask whether there is any other evidence
of overinvestment in IT during the 1990s.
Another more indirect way to examine the IT investment
trend is to assume that firms are making the correct
decisions in terms of how much they are investing in IT,
and then examine what has happened to productivity. The
logic behind this approach is that, if there were a great
deal of overinvestment in IT—that is, if a lot of IT goods
were purchased that ended up not being very useful—
then productivity would not be as high as expected. This
is not a conclusive test, as there are many factors that affect
productivity, but, as discussed in Box 3, it appears to
be increasingly difficult to tell a story that there was too
much investment in IT given what has happened to productivity
growth and given the multitude of stories that
cite the importance of IT. With that said, however, there
were several sectors that obviously overspent on IT (and
on other equipment, for that matter), and they are described
in the next section.
4. Ebullience
Perhaps the story that is first and foremost in many people’s
minds to explain the excessive IT investment in
1999 and 2000 is that expectations about the rate of return
on IT investment were too high. In the late 1990s, the dotcom
industry was growing and there was a sense that the
way business was conducted around the world was
changing, creating a “new economy.” Businesses believed
that they had to invest heavily in IT if they wanted to be
part of this new economy. Using the language from the
model section, businesses thought that there was an outward
shift on the returns to IT investment, increasing the
desired capital stock and, therefore, increasing investment
in IT goods. In 2000 and 2001, expectations began
to sour (lowering the expected rate of return on IT goods)
and the reverse happened: firms cut investment in IT
goods.
Although this story has a tremendous amount of intuitive
appeal, the question is, to what extent did changes in
Labor productivity grew at an average rate of 1.4 percent between
1973 and 1995. Since 1995 through the end of 2003,
labor productivity growth perked up to 3.1 percent, with especially
strong gains of over 4 percent since the end of 2000.
Why did productivity growth pick up in the late 1990s and
so far this decade? To answer that question, many studies have
decomposed labor productivity growth into several sources.1
These sources include improvements in the quality of labor,
increases in the amount of capital, and improved efficiencies
in producing with a given amount of capital and labor. This
last form of productivity improvement is often called total
factor productivity, or TFP. Although different studies use different
decompositions, most come to the conclusion that a
good deal of the pickup in labor productivity growth comes
from a pickup in TFP.2
If firms made many unwise capital investments, including
IT investments, all else equal, then TFP would be adversely
affected. Yet, TFP has gone up during and after the strong
surge in IT spending. Now, there are many reasons why TFP
may have gone up, and TFP is something that is not well understood
(in fact, TFP is sometimes referred to as a measure
of our ignorance). However, the collected stories about the
improving productivity performance of the U.S. economy resonate
an IT theme, either directly or indirectly. For instance,
Jorgenson, Ho, and Stiroh (2002) find that industries that
were intense users of IT accounted for a disproportionate
share of productivity growth. Similar results are produced independently
by the Department of Commerce (2003). For instance,
the finance and retail industries posted above average
gains in productivity growth and they are also sectors that are
also relatively IT-intensive.
Digging beneath the surface a bit, the McKinsey Global
Institute has come out with several studies (McKinsey 2001,
2002) that examine productivity growth and ask, sometimes
specifically, what role IT played. A theme of the McKinsey
studies is that IT was one reason, but not the only reason, for
the surge in productivity growth. Other reasons McKinsey
cites include increases in competition (in the case of the
development of microprocessors) and changes in the regulatory
environment (in the case of cellular phones). Another
theme in the McKinsey studies is that investment in IT does
not in itself yield marked productivity improvements.
Instead, organizations must make complementary changes in
the way they do business to reap the full rewards that IT
potentially offers. In a related vein, Basu, et al. (2003) argue
that IT is a general purpose technology, that is, a technology
that is widely used in a number of different applications. As
such, it takes time for firms and industries to learn how to use
IT, so the improvements we are seeing more recently in TFP
are the fruits of investments made several years ago.
1. Several of the more commonly cited studies include Oliner and
Sichel (2002), Gordon (2003), Jorgenson, Ho, and Stiroh (2002), and
the Council of Economic Advisors (2003).
2. It should be noted that most of the pickup in TFP is outside of the
IT-producing industries.
Box 3
The Relationship between Productivity Growth and IT Investment
Doms / The Boom and Bust in Information Technology Investment 25
expectations affect the swing in IT goods? It is dangerous
to point to examples and then make generalizations, because
regardless of the type of investment good we could
examine—computers, airplanes, aluminum smelters—
one can always find examples of investments that turned
out not to be wise. The more appropriate question to ask
is, what happened on average or, if there were particular
pockets of excessive enthusiasm, how large were those
pockets and what effects could they have had on the aggregate
figures for IT investment? What follows, then, is
a closer examination of two industries that epitomized
overinvestment in IT.
4.1. Dot-com Overinvestment
There were expectations that new firms that relied heavily
on the Internet, and firms that provided services to
other businesses that relied heavily on the Internet,
would be wildly profitable, a claim that only a few firms
would be able to make several years later. Ebay is one
such dot-com company that has survived, while
Pets.com and Furniture.com are examples of dot-com
companies that failed. Unfortunately, there are no accurate
statistics on the dot-com industry, especially when it
comes to IT capital spending. However, there are several
ways to obtain some back-of-the-envelope calculations
to see how potentially important these companies may
have been to the swings in IT investment. One method is
to examine patterns of venture capital (VC) spending and
another is to examine employment in industries that have
properties similar to dot-coms. Both methods come to a
similar conclusion: the dot-com bubble and its bursting
could have accounted for a small portion of the excessive
run-up in IT investment and a somewhat larger portion of
the decline.
The first method of measuring the potential magnitude
of dot-coms on the investment swings is to examine
VC spending. According to the MoneyTree survey,8 VC
spending (excluding health care and biotechnology)
surged in 2000 to nearly $98 billion, a staggering increase
from nearly $18 billion just two years earlier. The question
is, how much of this money was spent on IT?
According to data from Informationweek,9 companies
tend to spend very little of their revenue on IT. For instance,
even telecom firms (which are IT-intensive) are
estimated to spend only about 4 percent of their revenue
on IT, and about one-third of that spending is on salaries.
If we assume that companies that received VC funding
spent 5 percent of their funding on IT equipment and software
(about double the rate of telecom companies), then
VC spending accounted for $2.4 billion of the $53.8 billion
increase (4.5 percent) in IT spending between 1999
and 2000. However, between 2000 and 2002, the drop in
VC spending would have accounted for a $4.1 billion
drop in IT spending, about 7.5 percent of the $55 billion
decline.
Another approach to looking at the effect dot-coms had
on IT investment is to examine employment in industries
that are dot-com-like. Four industries that likely encompassed
many of the dot-coms are wholesale electronic
markets and agents and brokers; electronic shopping and
mail-order services; Internet service providers and web
search portals; and data processing, hosting, and related
services. Between 1995 and the end of 2000, employment
in these industries accounted for 2.3 percent of all net
nonfarm jobs created in the U.S. (365,000 compared to
16.1 million created elsewhere in the nonfarm sector). In
terms of the downturn though, these industries accounted
for about 5 percent of the decline in total nonfarm employment.
In terms of the role that these industries played in the
swings of IT investment, we need to make an assumption
about how IT-intensive they are relative to the rest of the
economy. For example, let’s suppose these industries invest
three times more in IT per employee than other industries
do.10 Under this assumption, these industries
would have accounted for about 6.5 percent of the increase
in IT spending from 1995 to 2000 and 13.1 percent
of the drop from 2000 to 2002.
4.2. Telecommunications Service Industry
Overinvestment
More than any other sector, the telecom service industry
was the poster child of overinvestment. Spurred on by
the Telecommunications Act of 1996 and ebullient
expectations for future demand, the telecom service sector
went on a capital expenditure binge. As shown in
Figure 4, capital investment by publicly traded telecom
service companies rose sharply in the late 1990s, starting
at $47 billion in 1995 and peaking at $121 billion in
2000. Since then, however, the telecom service industry
landscape is littered with the wrecks of overly optimistic
expectations, as witnessed by the bankruptcies by
WorldCom, Global Crossing, and numerous smaller
8. The MoneyTree Survey is a collaboration among Pricewaterhouse-
Coopers, Thomson Venture Economics, and the National Venture
Capital Association.
9. See www.Informationweek.com.
10. Based on the 1998 Annual Capital Expenditure Survey (ACES),
this assumption would make dot-coms about two times more ITintensive
than the financial services industries.
26 FRBSF Economic Review 2004
firms. By 2002, investment had fallen by over half to $49
billion.11,12 These large swings in investment by this single
industry likely helps explain a portion of the swing in
IT investment, since telecom service providers are big
spenders on IT equipment.
Working on the assumption that capital spending by telecom
service providers fell by 20 percent in 2001 and using
information from the U.S. Census Bureau’s 1998 Annual
Capital Expenditures Survey and the BEA’s 1997 Capital
Flows Table, Figure 5 shows the changes in estimated annual
IT spending by telecom and nontelecom firms.13 In
2000, telecom companies went on a spending binge, accounting
for a majority of the increase in IT investment in
the country. Almost as pronounced as the 2000 increase is
the 2001 decrease. I estimate that IT spending by telecom
companies dropped by $22 billion, more than two-thirds of
the total decrease in IT spending. In 2002, I estimate that a
further drop in telecom spending accounted for nearly all of
the decline in total IT spending.14 The Appendix provides a
more detailed look at the causes of the boom and bust in
capital investment by the telecom service industry.
13. According to the 1998 ACES, the communications industry spent
72 percent of its capital expenditures on information processing equipment.
Additionally, the 1997 Capital Flows Table suggests that, of capital
equipment spending by communications firms, 62 percent is doled
out on communications equipment, 9 percent on computers, and 12 percent
on software.
14. The decompositions presented in Figure 5 are based on several assumptions,
so they should not be taken literally. Nonetheless, the results
that telecom service firms would have accounted for a disproportionate
share in the 2000/2001 swing in IT investment is robust to a wide range
of alternative assumptions.
11. The data for publicly traded companies are very close to the figures
reported in ACES for communications service firms. For instance, government
data show that telecom companies ramped up capital spending
by 206 percent between 1994 and 2000, slightly above the 189 percent
increase for the publicly traded companies. U.S. Census Bureau data are
usually about 90 percent of the publicly traded company data, again
likely reflecting that some firms in our sample do make capital investments
outside of the U.S. The one anomaly between the two series occurs
in 2001, the last year government data are available, when the
government data show only a 7 percent drop in capital spending,
whereas publicly traded companies register a 25 percent drop. Given
what happened in the industry, the numerous reports of companies
slashing capital spending, various financial indicators of the industry,
what happened to revenues of companies that make communications
gear, and the number of bankruptcies, the true drop in investment spending
could be much larger than the figures reported by the Census
Bureau.
12. Based on results from the first half of 2003, it is likely that capital
spending for these companies increased in 2003 to over $55 billion.
Figure 4
Capital Spending by Publicly Traded
Telecommunications Service Providers
Figure 5
Changes in Estimated Nominal IT Spending
by Telecom and Nontelecom Companies ($ Billions)
0
20
40
60
80
100
120
140
91 92 93 94 95 96 97 98 99 00 01 02
$ billions
Source: Compustat and author’s calculations.
-40
-30
-20
-10
0
10
20
30
40
50
60
1996 1997 1998 1999 2000 2001 2002
Nontelecom
Telecom
$ billions
Note: All figures are year-over-year changes
Source: Author’s calculations based on data from Compustat, the Annual
Capital Expenditures Survey (multiple years), and the 1997 Capital Flows
Tables (from BEA).
Doms / The Boom and Bust in Information Technology Investment 27
5. Changes in IT Service Lives
Most investment models assume depreciation is constant
over time, that is, that capital goods are discarded according
to a fixed schedule. These assumptions about fixed retirement
schedules are made because there is a lack of
information otherwise.15 For IT goods, there were three
events in the 1990s and 2000 that would have caused firms
to shorten the service lives of their IT goods unexpectedly
and then boost their IT investment. The first was the famous
Y2K problem, which implied that some software and hardware
would not function or would function improperly after
December 31, 1999. As a result, firms had to replace some
hardware and software sooner than they had expected.
Second, unexpectedly large advances in software requirements
during the second half of the 1990s induced firms to
upgrade their computer hardware more quickly. Finally, a
more nuanced argument has been put forth by Whelan
(2000) that says that service lives are shortened when prices
fall rapidly; during the late 1990s, computer prices fell extremely
rapidly and arguably more rapidly than firms expected.
16 The three stories have a certain amount of
credibility. What is unfortunate, though, is that it is difficult
to quantify the importance of the two latter stories.
5.1. Preparations for Y2K
According to the Department of Commerce (1999), it is estimated
that about $100 billion was spent on “fixing” the
Y2K problem from 1995–2001.17 Money was spent on fixing
and testing software, replacing embedded chips that had
the Y2K problem hard-wired, and replacing computers and
software earlier than they would have been otherwise.
Based on data in the Department of Commerce report, it is
unlikely that fixing the Y2K problem had an appreciable effect
on the time series pattern of aggregate IT spending.18
For instance, in 1998, the year in which Y2K-related
expenditures peaked, these expenses accounted for only an
estimated $4.8 billion in software (compared to a total $140
billion that private businesses spent on software in that year)
and $3.2 billion in hardware (compared to a total $165 billion
that private businesses spent on IT hardware).19
5.2. Changes in PC Hardware Requirements
Perhaps more important in understanding the swings in IT
investment than Y2K are the more general relationships between
hardware and software, especially for PCs. During
the 1990s, sales of PCs outstripped sales of midrange and
mainframe computers, and PCs became a more important
component of the IT capital stock. Also during this decade,
there were tremendous changes in the technology of PCs
and in their software. Windows-based operating systems
and software became the norm, as did the ability to browse
the Internet. In the face of these software changes, the replacement
cycle of PCs may have changed. Some research
suggests that the mean service life of personal computers
shortened during the late 1990s (McKinsey 2001), which
provided a boost to investment. During the more recent
downturn, there were claims that the average service lives
of PCs were lengthened, damping investment. However,
just how long PCs (or other IT goods for that matter) are
used before they are retired is not known; in most
investment models and in calculations that estimate the
contribution of IT capital to productivity growth, the
replacement cycle is considered to be constant.20
The story is that during the late 1990s there was a surge
in the hardware requirements needed for running various
software programs. Since the recommended configurations
for many computer operating systems are very similar to
the recommended configuration for the latest version of
Microsoft Office, I use that software package’s configurations
to measure changes in business requirements for
computing. The increases for minimum required hardware
during the mid- to late 1990s are stark: between 1994 and
2000, RAM requirements increased at a 67 percent annual
rate (from 2 megabytes to 64 megabytes), while hard disk
requirement increased at a 90 percent annual rate (from 8
megabytes to 650 megabytes). Therefore, firms may have
replaced their PCs more frequently during the late 1990s
and less since then.
5.3. Faster Falling Prices, Faster Replacement
The other story of how service lives may vary over time is
provided by Whelan (2000) who suggests that the faster the
15. Just how little is known about service lives is discussed in Doms,
et al. (2003).
16. Another form of increased depreciation that may have been important
during the 1990s was the depreciation of midrange and mainframe
computers induced by the widening acceptance of the personal computer.
17. The Department of Commerce analysis uses estimates from the
Federal Reserve and from IDC.
18. According to IDC, about 16.5 percent of these Y2K expenditures
were on software and 10.9 percent were on hardware.
19. Another way the Y2K problem may have affected IT investment is
that investment in the latter part of 1999 could have been postponed
until 2000, until after the effects of Y2K were established. The magnitude
of this swing is hard to quantify and is not likely to be large.
20. In calculating depreciation rates for capital stocks, there are several
components, including the loss of value as a good ages and when a good
is retired. For computers, it is the latter that is the most important, as
shown by Doms et al. (2003).
28 FRBSF Economic Review 2004
pace of price declines, the faster machines will be replaced.
As I noted in Section 2, computer prices fell exceptionally
quickly in the late 1990s. The thinking behind Whelan’s research
is that firms incur expenses in maintaining computers,
an idea that has a lot of appeal based on estimates of
support costs relative to the cost of computer hardware.
Facing these costs, when new computer prices drop significantly,
firms will be more inclined to buy a newer machine
rather than incur the costs of maintaining an older one. The
Whelan story reinforces the story that service lives may
have decreased in the late 1990s (when computer prices
fell the quickest) but have since increased.21
6. Technological Change and Prices
One of the driving factors in IT investment has been the
rapid drop in the user cost of capital for IT goods, which is
driven mainly by the drops in prices for IT goods. Going
one step further, the drops in prices for IT are largely
driven by technological change, as discussed in Box 4.
Given the importance of prices and technological change,
this section goes into more detail about what happened to
prices and technology for the three components of IT
investment.
In particular, one reason for going through this exercise
is to try to understand better why prices for IT goods fell
very quickly in the late 1990s, more quickly than they had
earlier in the 1990s.22 Did these rapid price declines in the
late 1990s coincide with an increased pace of technological
change, or did prices appear to fall for other reasons?
Also, what has happened to the pace of technological
change since then? The answer to the first question appears
to be that the pace of technological change did pick
up in the late 1990s, at least for certain types of IT products,
helping to propel prices downward very quickly.
The answer to the second question is less clear. Official
prices for IT goods show some deceleration, and there
are some areas where technological change may have
slowed. However, the deceleration in IT prices is somewhat
puzzling given that demand slowed (which usually
puts downward pressure on prices) and prices for several
types of semiconductors (important components of IT
goods) continued to fall very quickly.
6.1. Computers
Given the importance of the prices of IT goods in understanding
investment, it is not surprising that there has
been some effort exerted in measuring prices for IT
goods, much of it devoted to measuring prices for computers.
According to the BEA, prices for computers and
peripheral equipment fell at unusually high rates in the
late 1990s, dropping an average of 21.0 percent per year
Although measuring the changes in the technology of goods
(such as chip speed and horsepower) is interesting in its own
right, perhaps a more important question to ask is, how much
is our welfare improved by those technological changes? For
instance, if Intel comes out with a new microprocessor that is
twice as fast as the previous generation, or if General Motors
comes out with a car that has twice the horsepower of last
year’s model, does that mean that we are twice as well-off?
Probably not, especially if the faster computers and faster cars
are more expensive than the older models.
One way to measure how much our society values technological
change is by examining prices. Price indexes are supposed
to answer the question of how much money we need
today to be as well-off as we were, say, last year. For the economy
as a whole, prices tend to increase, so we tend to need
more money today than we did last year to maintain a given
level of satisfaction. In contrast, prices for high-tech goods
tend to fall, implying that not as much money is needed today
to spend on IT goods to get the same level of performance that
we got last year. In practice though, official price indexes for
many high-tech goods likely understate price declines, that is,
they understate how much better-off we are because of new
and better products.
There are many other factors beyond technological change
that affect prices as well, especially in the short-run, such as
changes in profit margins, costs