FEDERAL RESERVE BANK OF NEW YORK

IN ECONOMICS AND FINANCE

Equipment Expenditures since 1995:

The Boom and the Bust

Jonathan McCarthy

Business investment in equipment surged in the 1990s, then fell back sharply after mid-2000. 

A popular explanation of these trends holds that the soaring stock market and declining 

computer prices of the last decade encouraged excess investment, setting the stage for the

retrenchment that followed. Yet an analysis of the factors underlying investment suggests that

capital spending patterns in the late 1990s would have been quite similar had stock values 

and equipment prices remained near their recent historical averages.

One pillar of the late 1990s expansion was the strength

of business investment in equipment and software. This

category of expenditures captures firms’ purchases 

of computers and other high-tech equipment as well

as purchases of more traditional forms of machinery

such as industrial and construction equipment, aircraft,

and trucks. Although business investment spending

accounts for less than 10 percent of U.S. GDP—a far

smaller share than that claimed by consumer spending—the rapid growth of these expenditures provided

an unusually strong stimulus to GDP growth in the second half of the last decade. Indeed, capital spending is

widely regarded as a key contributor to the productivity

gains that enabled the economy to grow strongly with

little inflation during this period.1

Now, with the slowdown in the economy, expenditures

on equipment and software have fallen dramatically.

Predictably perhaps, this reversal has given rise to the

view that businesses, responding to a strong stock market

and rapidly declining prices in many high-tech capital

goods, overinvested in these goods in the 1990s.

Proponents of this view suggest that the resulting glut of

high-tech products has prompted firms to cut back

sharply on investment—a move that, over time, could lead

to significantly lower output and productivity growth.

In this edition of Current Issues, we investigate the

recent behavior of equipment expenditures with an eye

toward evaluating this view of investment trends. We

begin by tracking the growth of the components of

equipment spending to determine whether high-tech

expenditures have in fact dominated the investment

boom and bust. Our analysis suggests that while the

capital spending surge of the late 1990s was concentrated in the high-tech sector, the decline in equipment

expenditures since mid-2000 has been broad based,

affecting investment in transportation equipment and

other conventional machinery as well as purchases of

computers and software.

In the remainder of the article, we develop an empirical forecasting model to explain the changes in business

investment behavior over 1995-2001. The model results

suggest that the standard economic determinants of

investment can account for most of the boom in the late

1990s but not the steep drop-off in 2000-01. We then use

our model to test the notion that a robust stock market and

declining equipment prices led businesses to overinvest

during the last decade. Significantly, we find that investment would probably have been strong in the late 1990s

even if stock values and relative equipment prices had

followed paths near their recent historical averages.

October 2001 Volume 7 Number 9
Although we do uncover evidence that the stock market

decline has contributed to the investment bust, its effect

appears modest relative to the severity of the slowdown.

Equipment and Software Expenditures since 1995

Real expenditures on equipment and software boomed

during the late 1990s, growing more than 12 percent

annually between 1995 and the second quarter of 2000

(Table 1, column 1). As one might expect, the boom was

greatest for high-tech expenditures: information equipment increased at an annual rate of more than 20 percent during this period, and computers rose at a 45 percent rate. Spending on other components of equipment

also rose markedly, but at single-digit rates.

Since the second quarter of 2000, however, equipment

and software expenditures have declined precipitously

(Table 1, column 2). As recent press reports suggest,

much of the drop has been in high-tech equipment.

After many years of very high growth, real computer

and software expenditures have barely risen in the past

year. Meanwhile, spending for information equipment

excluding computers and software has fallen more than

10 percent, principally because of weakness in telecommunications equipment.

Significantly, however, more traditional forms of

equipment have also shown sizable declines in their

rates of growth. Although the slowdown in high-tech

expenditures has captured most of the press attention,

the retrenchment in spending has in fact been widespread. In particular, expenditures for transportation

equipment have declined almost 13 percent, and spending on “other equipment”—a category that includes furniture and fixtures as well as machinery for agriculture,

construction, mining, and the service industry—has

fallen more than 4 percent.

Paralleling the growth and subsequent cutback in

equipment expenditures has been a strong shift in

equipment expenditures’ contribution to GDP growth.

Although these expenditures make up less than 10 percent of GDP, they accounted for almost 1.1 percentage

points of the growth in GDP from the first quarter of

1995 through the second quarter of 2000 (Table 2, column 1). Given that GDP growth during this period averaged a little under 4 percent, equipment expenditures’

growth contribution far exceeded their share of GDP.

Information equipment provided the largest boost to

growth: its contribution was about 3⁄4 percentage point

(almost a one-fifth share), even though its share of

nominal GDP is only about 41⁄4 percent.

Since the middle of 2000, however, the contribution of

equipment expenditures to GDP growth has turned negative (Table 2, column 2). Indeed, equipment investment

accounts for more than one-half of the slowdown of GDP

growth during this period (Table 2, column 3). Although

computer and software expenditures continued to grow,

information equipment contributed about 0.8 percentage

point to the slowdown. Nevertheless, the more traditional, low-tech sectors account for almost as much of

the slowdown as the high-tech sectors. For example,

transportation equipment has contributed slightly more

to the slowdown than has information equipment exclusive of computers and software.

Clearly, equipment and software expenditures have

played a greater role in the economic expansion and

slowdown of recent years than their share of GDP

would seem to justify. For this reason, an examination

of the factors underlying the behavior of equipment

FRBNY 2

CURRENT ISSUES IN ECONOMICS AND FINANCE

Table 1

The Investment Boom and Decline

Annualized Growth Rate of Expenditures, in Percentage Points

1995:Q1 - 2000:Q3 - 

Category 2000:Q2 2001:Q2 Change

Total equipment and software 12.37 -4.00 -16.37

Information equipment 20.32 -2.08 -22.39

Computers 45.11 1.69 -43.43

Software 17.30 3.76 -13.54

Other information equipment 10.33 -10.67 -21.00

Industrial equipment 4.76 1.43 -3.32

Transportation equipment 8.06 -12.80 -20.86

Other equipment 6.59 -4.23 -10.81

Memo:

GDP growth

(annualized percentage rate) 3.94 1.32 -2.62

Source: U.S. Department of Commerce, Bureau of Economic Analysis.

Note: Expenditures are measured in 1996 chain-weighted dollars.

Table 2

Equipment Expenditures’ Contribution to GDP Growth

Average Annual Contribution, in Percentage Points

Share of

Nominal

1995:Q1- 2000:Q3- GDP

Category 2000:Q2 2001:Q2 Change (Percent)

Total equipment and software 1.07 -0.38 -1.44 9.04

Information equipment 0.74 -0.08 -0.82 4.23

Computers 0.35 0.04 -0.32 0.88

Software 0.23 0.07 -0.16 1.84

Other information equipment 0.16 -0.18 -0.34 1.50

Industrial equipment 0.08 0.03 -0.05 1.65

Transportation equipment 0.15 -0.26 -0.41 1.73

Other equipment 0.10 -0.07 -0.16 1.45

Memo:

GDP growth

(annualized percentage rate) 3.94 1.32 -2.62

Source: U.S. Department of Commerce, Bureau of Economic Analysis.

Note: The figures in the right-hand column (“Share of Nominal GDP”) are as of

second-quarter 2001.
expenditures is likely to shed significant light on recent

economic fluctuations. In the next section, we consider

some of these factors in detail.

What Drives Investment?

Standard economic theories and intuition point to three

factors as determinants of business investment. One

factor is GDP growth, whose role is straightforward.

When GDP growth accelerates, firms desire to increase

their capital stock to meet heightened demand, and

investment consequently increases.2 By this logic, the

1990s investment boom stems partly from the strong

economic growth of the period.

A second factor likely to drive investment is the rental

cost of capital—that is, the cost of purchasing and holding investment goods.3 Rental costs will reflect not only

depreciation and interest rates but also changes in the

price of capital goods relative to other goods (relative

price). When capital goods become less costly, firms will

desire to hold more capital and thus will increase investment. In particular, holding all else constant, a decline 

in the relative price of investment goods should boost

investment.

Of course, relative prices of investment goods did

decrease during the 1990s, largely because of the drop in

computer prices (Chart 1). Although the trend toward

lower equipment prices has been evident since the early

1960s, relative prices fell particularly sharply during the

investment boom of the late 1990s. The timing of this

steep decline appears to support the view that relative

prices figured importantly in the investment boom.

However, this story has a potential complication. If a

price decline today leads firms to expect even greater

price decreases in the future, then firms may delay current purchases of capital goods in order to take advantage of lower prices in the future. Essentially, the

prospective price declines imply that buying and holding investment goods is costly, even though the current

purchase price has declined. Such reasoning would

prompt firms to reduce investment—a possibility that

makes the effect of declining prices on investment more

ambiguous than it initially appears.4

A third factor thought to influence investment is the

market value of firms relative to their underlying capital assets (a factor typically designated by economists

as q).5 When the stock market values firms and their

future prospects highly, investments in physical assets

such as capital goods are more profitable for firms than

financial investments such as stock repurchases, mergers, and corporate takeovers. Consequently, holding all

else constant, higher equity values should lead to

greater investment in equipment and software. This

relationship implies that the strong stock market during

the 1990s may have helped spur the investment boom in

the second half of the decade.

Although theory and intuition alike suggest that

rental costs and stock values are key determinants of

investment, empirical studies have generally failed to

bear out the importance of these factors. Studies relating investment to rental costs have shown only a modest

effect from this variable, although some recent research

suggests that relative prices—one component of rental

costs—may have a larger impact.6 Similarly, estimates

of q models typically do not find a strong effect on

investment from this variable, probably in part because

of problems constructing empirical counterparts to the

unobserved theoretical q variable.7

Modeling Investment Growth: 1995-2001

To assess the influence of the factors outlined in the

preceding section—GDP growth, rental costs, and

equity values—on investment in 1995-2001, we incorporate all three in an empirical forecasting model more

inclusive than the models typically used to analyze

investment. Comparing the forecasts produced by this

model with actual investment growth rates over the

period reveals the extent to which these standard economic variables can explain the recent changes in

investment growth.

In addition to the features just cited, our model

assumes that previous investment behavior will affect

current behavior. To account for such effects, we

include “lagged”—or past—values of investment growth

as explanatory variables.8 The model also allows for cash

flow effects on investment, a factor considered important by many analysts.9 Finally, the model assumes that

3

-35

-30

-25

-20

-15

-10

-5

0

5

1980 82 84 86 88 90 92 94 96 98 00

Chart 1

Relative Price of Equipment and Software

Total equipment and software

Computers and 

peripherals

Information

equipment

Source: U.S. Department of Commerce, Bureau of Economic Analysis.

Note: The prices of investment goods are measured relative to the deflator

for GDP of the nonfarm business sector.

Year-over-year percentage change
investment adjusts so that the capital stock slowly

approaches its desired level.10

We use the model to produce a series of one-stepahead forecasts of the investment growth rate from the

first quarter of 1995 through the second quarter of

2001. For each quarter, we estimate the model using

data from 1960 through the end of the previous quarter

(that is, the quarter immediately preceding the one that

is the subject of our forecast). We then use the estimated

model to generate the forecast of investment growth.

For example, to predict investment growth in the first

quarter of 1995, we estimate the model over a period

beginning in 1960 and extending through the fourth

quarter of 1994, then use the estimated model to arrive

at the forecast.11 By repeating this procedure for each

subsequent quarter, we can project the course of investment growth from 1995 to 2001.

Comparing the forecasts with actual investment

growth rates during the 1995-2001 period, we find that

the model tracks investment growth fairly well through

the end of 2000 (Chart 2). This result suggests that standard economic variables can, in fact, explain the strong

investment growth during the mid-to-late 1990s. The

model is also fairly successful in identifying the middle

of 2000 as the period when equipment expenditures

began to slow down.

What the model fails to do, however, is to capture the

depth of the decline in investment spending and, in particular, the sharp drop in the first two quarters of 2001.

Clearly, the historical relationship between investment

and its economic determinants cannot account for the

sustained decline since mid-2000. By including GDP

growth and stock values as explanatory variables, the

model allows the recent general economic slowdown

and the stock market tumble to influence investment.

But despite the inclusion of these factors, the model

predicts a slowdown much more moderate than the one

that actually occurred.

Seeking an explanation for this puzzle, many

observers have suggested that the seeds of the investment decline were planted in earlier years. One popular

hypothesis along these lines is that the stock market

boom and the rapid fall in equipment prices encouraged

“too much” investment in the 1990s, paving the way for

a sharp pullback in equipment expenditures when the

expected strong demand did not materialize. In the next

section, we examine this hypothesis in more detail.

The Role of the Stock Market and Relative Prices

To determine whether the behavior of stock prices and

equipment relative prices in the 1990s prompted the

steep decline in investment, we can compare the model

projection from the previous section with two counterfactual projections based on the same model. The first

counterfactual assumes that equity values increase at 

a constant rate equal to their 1980-94 average. In this

scenario, there is no stock market boom and bust and

the equity value at the end of first-quarter 2001 is about

13 percent below the actual value. The second counterfactual assumes that the relative price of equipment 

and software decreases at a constant rate equal to its

1980-94 average. In this scenario, there is no period of

especially rapid price decline.12

Comparing the stock market counterfactual projection with the base projection from the previous section,

we see little difference until 2001 (Chart 3). The consistency of the two projections over the second half of the

1990s suggests that, given the behavior of the other

variables in the model, equipment investment probably

would have grown at double-digit rates during this

period even if equity values increased at a rate near

their historical average. Therefore, the stock market

boom by itself is unlikely to have planted the seeds of a

sharp retrenchment in capital spending by encouraging

overinvestment in the 1990s.

Nevertheless, the fact that the counterfactual projection is noticeably above the base projection in 2001 

suggests that the stock market decline over the past year

has exacerbated the investment slowdown. Specifically,

it appears that equipment expenditure growth would

have been about 4 percentage points higher had stock

values not dropped sharply. Still, the effect of the stock

market decline on investment appears rather modest

when we recall that equipment expenditure growth has

fallen more than 16 percentage points from its average

over the 1995-2000 period.

4 FRBNY

CURRENT ISSUES IN ECONOMICS AND FINANCE

Percent

-20

-10

0

10

20

30

1995 96 97 98 99 00 01

Chart 2

Equipment and Software Expenditure Growth: 

Actual Growth versus Forecast Model Projection

Annualized Growth Rate

Model projection

Actual

Sources: U.S. Department of Commerce, Bureau of Economic Analysis; 

author’s calculations.
When we shift our attention to the relative price

counterfactual projection, we find a greater degree of

disparity with the base projection, indicating that equipment relative prices historically have had a larger effect

on investment than equity values (Chart 3). Throughout

the late 1990s, the counterfactual projection of equipment expenditure growth is noticeably below the base

projection. The implication is that expenditure growth

probably would have been somewhat lower in this

period if the rapid drop in equipment relative prices had

not buoyed up investment. Nevertheless, under the

counterfactual scenario, equipment investment would

still have grown at double-digit rates. Thus, it is doubtful that the sharp decline in relative prices by itself

encouraged excess investment.

The large gap between the projections for 2001 merits some comment. The base projection is about 5 percentage points higher than the counterfactual projection, suggesting that the recent resumption of large

price decreases would ordinarily have mitigated the

slowdown in investment. Since actual investment

plunged sharply during the year, we can infer that the

recent decline in equipment relative prices most likely

stems from weak demand, not from the technology

improvements that drove price declines in the 1990s.

Overall, these counterfactual exercises indicate that,

given the behavior of the other variables in the model,

equipment investment in the 1990s probably would

have been strong even if equity values and equipment

relative prices had followed paths closer to their historical averages. Moreover, it appears that although the

recent stock market tumble has contributed to the

investment slowdown, its effect on capital spending is

small compared with the depth of the investment

decline. Thus, an analysis based on historical relationships provides little evidence that rising equity values

and falling equipment relative prices precipitated the

investment boom and bust.

Conclusion

This study makes two important points about the recent

behavior of business investment expenditures. First,

although the capital spending boom of the late 1990s was

concentrated in the high-tech information sector, the 

capital spending slowdown of 2000-2001 has been broad

based. Therefore, analyses that focus on the difficulties

of the high-tech sector provide too narrow a picture of

the slowdown. Second, even though many commentators

assign the stock market and equipment relative prices a

pivotal role in the sharp rise and fall of investment, capital spending patterns probably would have been roughly

similar to those observed if stock values and equipment

relative prices had moved in line with their recent 

historical averages.

While our findings allay concerns about overinvestment in the 1990s, they raise a new question: If stock

values and capital goods prices did not drive the decline

in equipment expenditures, what did? Within the forecasting model used in this article, the variable most

responsible for the decline would appear to be slower

output growth. To be sure, the reasoning behind this

answer is somewhat circular—output growth, after all,

has slipped in part because investment has slowed

down—but it is consistent with the assessments of the

economy that were current in 1999 and the first half of

2000. During this period, firms (along with many analysts) believed that the economic boom would continue

and, as a consequence, they made capital expenditures

based on this expectation. Then, as the economy began

to slow in the second half of 2000, firms reevaluated

their assumptions and abruptly revised down capital

spending plans.

But while slower GDP growth may have figured in

the investment decline, the plunge in capital spending is

well beyond the predictions of most economic models,

including the one used in this study. Since the standard

economic variables cannot explain the magnitude of the

slowdown, one recourse would be to appeal to “animal

spirits.” Anecdotal evidence suggests that firm-manager

psychology may very well have contributed to the

investment slowdown: news reports have described how

the fear of a future slump in demand led some managers

to reduce capital expenditures, even before concrete

evidence of a slowdown had emerged.13

5 FRBNY

Percent

0

2

4

6

8

10

12

14

16

18

1995 96 97 98 99 00 01

Chart 3

Effect of Equity Values and Relative Prices on Equipment 

and Software Expenditure Growth

Annualized Growth Rate

Base projection

Source: Author’s calculations.

Projection assuming 

constant relative 

price decline a

Projection assuming

constant equity growthb

a Relative price decline equal to 1980-94 average decline.

Equity growth rate equal to 1980-94 average growth rate. b
CURRENT ISSUES IN ECONOMICS AND FINANCE

In the end, such explanations are not very satisfying

(nor are they testable), and instead point out how limited

our knowledge of investment really is. A fuller understanding of the forces underlying investment growth will

require more research, particularly in two areas. First,

because high-tech equipment now accounts for such a

large share of business capital expenditures, studies of

the interactions between technological advancement,

productivity, and investment are in order. Second, a

close examination of how the shift to fast-depreciating

capital goods such as computers and telecommunications equipment has affected investment behavior is

likely to prove fruitful. Such studies, carefully conducted, should improve our future predictions about the

growth of capital spending.

Notes

1. Federal Reserve Chairman Alan Greenspan (2001) summarized

this point of view in a recent speech: “The synergies of key technologies markedly elevated prospective rates of return on high-tech

investments, led to a surge in business capital spending, and significantly increased the underlying growth rate of productivity.”

2. This is the intuition behind the accelerator model of investment

(Clark 1917).

3. Both GDP growth and the rental cost of capital are important

components of the neoclassical investment model (Jorgenson 1963),

versions of which underlie the investment equations in many largescale macroeconometric models.

4. Resolving this issue would require modeling investment in general equilibrium, a task that is beyond the scope of this article.

5. The intuition for the q theory of investment comes from Keynes

(1936); Tobin (1969) began the formalization of the theory.

6. See Tevlin and Whelan (2000).

7. For more about the empirical evidence concerning this variable,

see Chirinko (1993).

8. The estimates of the model indicate, however, that these effects

are relatively small.

9. Several empirical studies (for example, Gilchrist and

Himmelberg [1995]) have shown that cash flow affects investment,

though standard economic theories would suggest otherwise.

10. This desired level is determined using a theoretical (neoclassical) benchmark.

11. Estimates of the model for selected periods are available from

the author. All coefficients have the expected signs and are statistically significant at the 10 percent level when the model is estimated

over the period from 1960 to second-quarter 2001.

12. Because the forecast model is a reduced-form partial equilibrium model, these exercises do not account for possible changes in

expectations and feedback effects under the counterfactual path.

Since our intent is to illustrate the historical relationship between

these variables and investment, such effects can be ignored.

13. For example, see Uchitelle (2001).

References

Chirinko, Robert S. 1993. “Business Fixed Investment Spending: A

Critical Survey of Modeling Strategies, Empirical Results, and

Policy Implications.” Journal of Economic Literature 31, no. 4:

1875-911.

Clark, John Maurice. 1917. “Business Acceleration and the Law of

Demand: A Technical Factor in Economic Cycles.” Journal of

Political Economy 25, no. 3: 217-35.

Gilchrist, Simon, and Charles P. Himmelberg. 1995. “Evidence on

the Role of Cash Flow for Investment.” Journal of Monetary

Economics 36, no. 3: 541-72.

Greenspan, Alan. 2001. “Economic Developments.” Remarks

before the Economic Club of New York, New York, May 24.

Available at <http://www.federalreserve.gov/boarddocs/speeches/

2001/200105242/default.htm>.

Jorgenson, Dale W. 1963. “Capital Theory and Investment

Behavior.” American Economic Review 53, no. 2: 247-59.

Keynes, John Maynard. 1936. The General Theory of Employment,

Interest, and Money. New York: Harcourt Brace.

Tevlin, Stacey, and Karl Whelan. 2000. “Explaining the Investment

Boom of the 1990s.” Board of Governors of the Federal Reserve

System Finance and Economics Discussion Paper no. 2000-11.

Tobin, James. 1969. “A General Equilibrium Approach to Monetary

Theory.” Journal of Money, Credit, and Banking 1, no. 1: 15-29.

Uchitelle, Louis. 2001. “Wary Spending by Companies Cools

Economy.” New York Times, May 14, p. A1.

The views expressed in this article are those of the author and do not necessarily reflect the position of the

Federal Reserve Bank of New York or the Federal Reserve System.

About the Author

Jonathan McCarthy is an economist in the Business Conditions Function of the Research and Market

Analysis Group.

Current Issues in Economics and Finance is published by the Research and Market Analysis Group of the Federal

Reserve Bank of New York. Dorothy Meadow Sobol is the editor.