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Intangibles: What Put the New in the New Economy?

Leonard Nakamura

Intangibles:
What Put the New
In the New Economy?

he U.S. economy is often called a new
economy. One reason is that newly developed
products are everywhere: Microsoft’s Windows98, Paramount’s movie “Titanic,” Pfizer’s
Viagra, and Gillette’s Mach3 razor blades are
four prominent examples. Developing each product required its corporate sponsor to invest hundreds of millions of dollars. For example, Gillette
invested $700 million to develop the Mach3 razor blade in an effort begun in 1990. Paramount
spent over $200 million to bring director James
Cameron’s vision of “Titanic” to the screen.

*Leonard Nakamura is an economic advisor in the
Research Department of the Philadelphia Fed.

Leonard Nakamura*
These investment expenditures gave rise to
economically valuable, legally recognized intangible assets, including copyrights (“Titanic” and
Windows98) and patents (Viagra and Mach3)
that give the investing firms the exclusive right
for a certain period to sell the newly developed
products. Pfizer sold over $700 million worth of
Viagra in 1998 after its introduction in April;
“Titanic” sold $1 billion in theater tickets before
it entered video sales; and Gillette’s Mach3 razor blade was the top seller in the United States
by the end of 1998, having secured more than 10
percent of the razor blade replacement market in
less than a full year.
Patents and copyrights on new consumer
products are not the only types of intangible as3

BUSINESS REVIEW

JULY/AUGUST 1999

sets. New processes for making existing goods,
such as the process for coating cookie wafers
with chocolate, and new producer goods, like PC
servers and fiber optic telephone cables, can also
be patented or copyrighted or, perhaps, protected
as trade secrets. Other intangible assets are brand
names and trademarks, which can help a firm
certify the quality of an existing product or introduce new products to potential purchasers.
Not only can a reputation for quality persuade
shoppers to try an item for the first time, but a
clever use of advertisements can go a long way
toward targeting precisely those who will gain
the most from the product and thereafter become
loyal, repeat customers.
Yet, because they are not investments in tangible assets, most expenditures on intangible assets are not recognized as investments in either
U.S. companies’ financial accounts or the U.S.
national income and product accounts. This
practice may have been reasonable when investment in such assets was a negligible portion of

our total investment, but that is no longer the
case. In this article, we will look at two key consequences of these accounting conventions.
First, not only are reported corporate profits understated, they’re understated more than they
used to be because corporations are investing
more of their cash flow in intangible assets. As a
result, U.S. price/earnings ratios are overstated.
Second, U.S. national income, saving, and investment are understated because a larger proportion of output is invested in intangibles. As
we shall see, growing investment in intangibles
also helps explain how the measured U.S. personal saving rate can be near zero even as U.S.
wealth has grown considerably. U.S. economic
and financial performance is less puzzling when
we take this intangible investment into account.1
1
In two previous articles in the Business Review, I have
explored the consequences of new products and new
retail practices for the measurement of inflation and
output growth.

TABLE 1

R&D, Tangible Investment, and Advertising
Of Nonfinancial Corporations
(as a proportion of nonfinancial corporate gross domestic product)*
Period

Research and
Development (%)

Fixed Tangible
Investment (%)

R&D and Tangible
Investment (%)

Advertising
Expenditures (%)

1953-59
1960-69
1970-79
1980-89
1990-97

1.3
1.7
1.8
2.3
2.9

12.6
12.7
13.9
14.1
12.6

13.9
14.4
15.7
16.4
15.5

4.2
3.9
3.4
3.9
4.1

Source: Flow of Funds, National Science Foundation, and McCann-Ericson.
*The gross domestic product originated by a firm is its revenues less purchases from other firms. Nonfinancial gross domestic product can be thought of as total nonfinancial domestic corporate revenues after
eliminating double counting due to interfirm transactions. An advantage of using this measure over total
revenues as a basis for comparison is that changes in corporate structure—mergers and spinoffs, for example—can affect the amount of interfirm transactions and thus change the amount of total corporate
revenues even though total final production is unchanged.

FEDERAL RESERVE BANK OF PHILADELPHIA

Intangibles: What Put the New in the New Economy?

Leonard Nakamura

RISING INVESTMENT IN INTANGIBLES...
Research and development (R&D) expenditures to create new products have certainly been
rising. Looking at the long sweep of U.S. data
since 1953, we see that R&D expenditures have
more than doubled as a proportion of nonfinancial corporate gross domestic product (GDP)
(Table 1 and Figure 1). 2 By contrast, we see that
tangible investment in plant and equipment (as
a proportion of nonfinancial corporate GDP)
was no higher in the 1990s than in the 1950s
and 1960s (Table 1 and Figure 2).
During the postwar period, investment spending, including R&D, rose 1.6 percentage points
as a proportion of nonfinancial corporate GDP,

from 13.9 percent in the 1950s to 15.5 percent in
the 1990s. All of this increase was due to R&D
expenditures. Looking at Table 1, we can see that
if we count R&D as investment, the years since

FIGURE 1

FIGURE 2

R&D Investment
As a Share of Nonfinancial
Corporate GDP

Gross Investment
As a Share of Nonfinancial
Corporate GDP

Source: Bureau of Economic Analysis: National
Income Accounts; Federal Reserve System: Flow
of Funds; National Science Foundation; and
author's calculations.

2
The data we are discussing are stated in nominal
terms, rather than being adjusted for inflation (i.e., in
real terms). This distinction is important because prices
of some investment goods—such as computers—have
been declining rapidly, so firms are able to obtain a lot
more computational power for their dollars today than
in the past. On the other hand, these rapid technological
improvements are not, by and large, reflected in the published deflators for R&D expenditures. Indeed, how to
properly deflate R&D expenditures is a substantial, unsolved research question.

BUSINESS REVIEW

the 1970s have been ones of strong investment.
These calculations do not include a number
of expenditures that might also be considered
investments. Advertising and marketing expenditures are often a crucial cost of selling new goods,
and at least some of these expenditures might
well be considered investments.3 U.S. advertising expenditures were high in the 1950s in the
consumer boom after World War II, as households caught up with purchases postponed by
the war. Then, advertising expenditures slipped
through the mid-1970s as the consumer boom
slowed. Since bottoming out at 3.2 percent of
nonfinancial GDP in 1975, these expenditures
have generally been rising along with spending
on R&D (Table 1).
One might further argue that the executive time
spent in support of investment decisions should
be included in investment costs. Certainly, employment in executive occupations has grown
in the past two decades, rising from less than 9
percent of U.S. employment in 1950, 1960, and
1970, to more than 10 percent in 1980 and more
than 14 percent in 1997. (A parallel rise has occurred for manufacturing industries alone.) The
rise in R&D expenditures in the 1980s and 1990s
has been accompanied by increases in advertising expenditure and executive employment,
some part of which was likely a necessary
complement to the rise in R&D.
Creativity costs are generally also not included
in official investment statistics and appear in
the national accounts only as costs of production. For example, the investments made in “Titanic” would not be included in investment ex-

3
New goods, unlike existing goods, are by definition
unfamiliar to consumers. Educating consumers about a
new good’s existence and how to use it raises the value
of the corporation’s product (so it is an investment in a
corporate asset) and raises the benefit received by consumers (so it is a social asset generating consumer surplus). An example is the sales force of a pharmaceutical
company that rapidly disseminates information about a
new drug.

JULY/AUGUST 1999

penditures in the national accounts.
Software purchases are generally not considered investments either.4 Moreover, much of the
work done on a computer has an investment element. For example, a substantial part of the work
of architects, engineers, artists, photographers,
and scientists is now written onto computer
disks (including hard drives and removable
media), where it can be more easily saved and
used in future projects.
These examples suggest that rising R&D expenditures are but one piece of a larger acceleration of intangible investment since the mid1970s, much of which has not been viewed as
investment in our corporate or national accounts.
...LEADS TO RISING STOCK MARKET
VALUE OF FIRMS
One surprising aspect of the U.S. economy
has been the rapid growth in the value of corporations’ stock market equity. The Dow Jones Industrial Average of share prices rose from 933 in
1981 to 9300 in early 1999. This tenfold increase
contrasts with the performance of nonfinancial
corporations’ after-tax reported profits, which
went up fivefold, and with the growth of nonfinancial GDP, which went up less than 2.5 times.5
The swift rise in share prices has led to a rise in
the ratio of stock prices to current after-tax profits (called the price/earnings ratio) to a level
which, while not unprecedented, has been rare
(Table 2 and Figure 3). This turn of events has
worried many observers and has raised the possibility that stockholders have become excessively optimistic about the value of U.S. corporations.

4
The Bureau of Economic Analysis has announced
that for the national income and product accounts, it is
likely to reclassify software purchases as investment.
5
The growth of the market value of nonfinancial corporate equity, the S&P 500, and the Dow Jones Industrials has been approximately equal over this period.

FEDERAL RESERVE BANK OF PHILADELPHIA

Intangibles: What Put the New in the New Economy?

Leonard Nakamura

TABLE 2

FIGURE 3

Profits and Stock Market
Value of Nonfinancial
Corporations

Price-to-Earnings Ratio,
Based on Book After-Tax
Earnings of Nonfinancial
Corporations

(as a proportion of nonfinancial corporate
gross domestic product)
Period

1.
After-Tax
Book
Profits
(%)

2.
Stock
Market
Value
(%)

PriceEarnings
Ratio= (2)/(1)

1953-59
1960-69
1970-79
1980-89
1990-97

8.8
8.3
7.7
5.2
6.3

110
145
92
75
127

12.56
17.48
11.90
14.55
20.21

Source: Bureau of Economic Analysis and Flow of
Funds. Book profits are after-tax nonfinancial corporate profits. Stock market value is market value
of nonfinancial corporate equity.

Other things equal, the price/earnings ratio
should be high when the expected growth rate
of profits (and thus of earnings per share) is high
relative to the rate of return that stockholders
require on the shares they own. That can happen when profits are temporarily low and expected to bounce back, as was the case during
the 1990-91 recession. It can also happen when
profits are high, as during the second half of the
1990s, if they are expected to grow rapidly in the
future.
But over the long run, profits have tended to
grow at the same rate as the economy as a whole.
Is there any rational reason to believe that profits should grow strongly in the future and thereby
justify the high valuations placed on shares? In
fact, there is. As we shall show, rising investment in intangible assets reduces measured current profits and raises expected future profits.
Thus, rising new product development can help

Source: Bureau of Economic Analysis: National
Income Accounts; Federal Reserve System: Flow
of Funds; National Science Foundation; and
author's calculations.

explain the high price/earnings ratio. To see
how investment in intangibles affects reported
price/earnings ratios, we first need to think
about how we measure profits.
Financial Accounting. The accurate measurement of profit is fundamental to financial accounting. Profit tells us two things: how much
revenues exceeded costs (a measure of the economic value of current operations of the firm)
and how much the assets of the corporation have
increased (before any cash distributions to shareholders). Formally, accountants define profit as
7

BUSINESS REVIEW

“the excess of revenues over all expenses.” Expenses are “the costs of goods, services, and facilities used in the production of current revenue” (Estes, 1981). To the extent that a firm
buys things that are not used up in production,
those additional costs are investments, not expenses, and are capitalized, that is, considered
assets. A capital asset gives rise to an expense
only to the extent that the capital asset’s value
falls while in use, a process called depreciation
or capital consumption. The intertwining of the
measurement of corporate earnings and corporate assets depends on how we define investment and assets. To understand how our definitions of investment affect our measures of profit,
we need to follow the details of corporate profit
accounting.
The World According to GAAP. In the United
States, corporate books are kept by certified public accountants who apply a set of rules called
generally accepted accounting principles
(GAAP). According to GAAP, “All R&D costs
covered by GAAP are expensed when incurred,”
that is, R&D costs are treated as part of the current expenses of the firm, and this treatment reduces reported profit.6 (See the Appendix, Are
All R&D Projects Lemons?) The only part of R&D
costs not expensed is purchases of durable, tangible assets “that have alternative future uses”
beyond the project at hand.7 The rationale for
this treatment of R&D is, in part, that firms might
be tempted to artificially manipulate profits if
R&D were capitalized. For example, by pretend-

JULY/AUGUST 1999

ing that some ordinary expenses of the business
were R&D, the firm might disguise a loss. Another part of the rationale is that R&D expenditures are more speculative than investments in
fixed assets (fixed assets may have alternative
uses and thus could be sold to others, but the
product under R&D may not pan out and therefore have no alternative use).
Notice that expensing R&D, by lowering profits, reduces corporate taxes and thus encourages
R&D spending. But there are alternative ways to
subsidize R&D if that is what we wish to do.
Indeed, the federal government already provides
additional subsidies to R&D through the research and experimentation tax credit.
Over the years, studies have relatively consistently shown that a firm’s R&D expenditures
raise the stock market valuation of that firm by
at least an equal amount.8 This finding suggests
that the book value of assets would be a better
guide to the true value of a corporation if R&D
expenditures were capitalized, that is, treated
as long-term investments and depreciated over
time.9
Indeed, in some industries creativity expenditures are treated just this way. For example, in
the film industry, the expenses of making a movie
are capitalized, then depreciated over the commercial life of the property.10 So the investing
groups that produced “Titanic” had to forecast
the revenues expected from movie theaters, payper-view broadcasts, cable TV rights, and video

See, for example, the article by Bronwyn Hall.

See Jan R. Williams, chapter 41, p. 41-04. This treatment was formalized in 1974. Before that, most companies followed “the conservative procedure of expensing
such costs as incurred, rather than capitalizing any part
of them,” Johnson and Gentry, p. 443.
7
That is, a computer purchased for an R&D project
can be capitalized to the extent that after its current use,
it will retain value because it can be used in future
projects. But durable lab equipment whose only use is
the project at hand should be expensed.

Although ideas need not deteriorate over time, they
do tend to lose their economic value. In particular, patents and copyrights give their owners monopoly rights
over the assets for a limited time (20 years in the case of
patents).
10

Note that even though these creativity expenses are
treated as investments and capitalized under GAAP,
they are not treated as investments in the national accounts, as discussed earlier.
FEDERAL RESERVE BANK OF PHILADELPHIA

Intangibles: What Put the New in the New Economy?

Leonard Nakamura

sales and depreciate the expenses of making the
movie over the period in which these revenues
were expected to be earned. If investments as
risky as films can be capitalized and depreciated, there seems little reason to believe that an
acceptable estimate cannot be made for R&D
expenditures.
Fortunately, under GAAP, accountants are
required to record R&D expenditures separately
so that shareholders and others can be aware of
them. Thus, we have data to empirically estimate what corporate profits would be if R&D
expenditures were treated the same way as tangible investment expenditures.
Can expensing R&D, rather than capitalizing and depreciating it, make an important difference in how we assess the profitability of U.S.
firms over the past half century? Consider Table
3. The first column represents after-tax profits of
corporations as they are normally reported, socalled book profits, from Table 2. These “book
profits” show that profitability as a proportion

of corporate product has generally declined.
True, earnings in the 1990s are higher than the
low earnings of the 1980s, but both are well below earnings in the three other postwar decades.
And the price/earnings ratio based on book profits averages 20.21 from 1990 to 1997 compared
with only 17.48 in the 1960s.
However, book profits are somewhat deceptive. Economic profits are a better measure (Table
3). For one thing, economic profits correct for the
fact that during the 1970s, corporate earnings
were bloated by inventory “profits” that corporations earned because inventories they were
holding rose in price along with everything
else.11 Furthermore, economic profits also adjust
depreciation rates to reflect more accurately the

11
This adjustment, called the inventory valuation adjustment, removes the part of inventory profit due strictly
to inflation and also adopts a uniform convention for the
valuation of inventories.

TABLE 3

Profits and Stock Market Value
Of Nonfinancial Corporations
(as a proportion of nonfinancial corporate gross domestic product)
Profits

Price-Earnings Ratios

Period

1.
After-Tax
Book
Profits
(%)

2.
After-Tax
Economic
Profitsa
(%)

3.
R&D
Adjusted
Economic
Profitsb
(%)

4.
Stock
Market
Value
(%)

5.
After-Tax
Book
Profits
(4)/(1)

6.
After-Tax
Economic
Profits
(4)/(2)

7.
R&D
Adjusted
Economic
Profits
(4)/(3)

1960-69
1970-79
1980-89
1990-97

8.3
7.7
5.2
6.3

9.3
6.1
6.2
7.6

9.9
6.8
7.1
8.6

145
92
75
127

17.48
11.90
14.55
20.21

15.67
14.98
12.19
16.62

14.70
13.55
10.53
14.84

After-tax nonfinancial corporate profits with inventory valuation and capital consumption adjustments.
After-tax nonfinancial corporate profits with inventory valuation and capital consumption adjustments
were further adjusted as R&D expenditures were capitalized and depreciated as described in the text.
b

BUSINESS REVIEW

economic lives of corporate tangible assets.12
Even economic profits, however, treat R&D as
an expense rather than as an investment.
How different would profit measures be for
nonfinancial corporations if we included R&D
expenditures as investments and capitalized
and depreciated them? Suppose we use a relatively conservative depreciation period of six
years, a figure suggested by the work of Dennis
Chambers, Ross Jennings, and Robert Thompson. The third column in Table 3 shows what
happens when we capitalize and gradually depreciate R&D expenditures, rather than expensing them.
R&D-adjusted profits are higher than economic profits. On average during the 1990s,
R&D-adjusted profits have been 13 percent
higher than economic profits and nearly 37 percent higher than book profits. More important,
the amount by which R&D-adjusted profits exceed economic profits has been growing. The
gap has nearly doubled from the 1960s to the
1990s, rising from 0.6 percent of corporate product to 1 percent. Hence, as we see in the seventh
column of Table 3, the adjusted price-earnings
ratios of the two periods are roughly equal—
about 14.8.
Although other factors are undoubtedly important in explaining stock prices and earnings,
treating R&D in a way that parallels treatment
of tangible investment expenditures takes an
important step toward improving our understanding of current stock market equity values
(Figure 4). The low stock market valuations of
the 1970s and the relatively high valuations of
the 1960s and 1990s are easier to understand.13

JULY/AUGUST 1999

And R&D is just one example of investment in
intangible assets. Adjustments to account for
other intangibles would have similar effects.
NATIONAL INCOME ACCOUNTING
AND INTANGIBLES: RISING WEALTH,
FALLING SAVING
The difference in accounting treatment of tangible and intangible assets affects the U.S. national income and product accounts as well as
corporate financial statements. By not counting
spending on R&D and other intangible assets
as investment, our national accounts understate
not only investment but also national income
and national saving.
Our national income accounts need not use
the same investment definitions as do financial
accountants; indeed, it is economic profits and
FIGURE 4

Price-to-Earnings Ratios of
Nonfinancial Corporations

12
This adjustment, called the capital consumption
adjustment because capital consumption is a synonym
for depreciation, is necessary because depreciation charges
allowed by tax law often do not match true depreciation.
13

Still, the 1980s appear somewhat out of line, since
stock market valuation in general was very low then.
10

Source: Federal Reserve Board: Flow of Funds;
and author's calculations.

FEDERAL RESERVE BANK OF PHILADELPHIA

Intangibles: What Put the New in the New Economy?

not book profits that fit into our measures of national income. Nevertheless, the national income
accounts do not treat spending on intangible
assets as investment. Why?
Two Types of Wealth: Intangible and Tangible. Peter Hill, of the Organization for Economic Cooperation and Development and one
of the chief modern architects of national accounting systems, has traced the exclusion of
intangible assets back to the distinction between
goods and services. He argues persuasively that
as far back as Adam Smith, goods were material
and could be stored while services were immaterial and transitory. This transitory nature meant
services could not be counted as assets, but goods
could. Logically, then, things counted as investment must be tangible. The role of immaterial
assets, such as patents or the goodwill of brand
names, was easily downplayed or ignored, given
this basic dichotomy. Irving Fisher, the Yale Economics professor who invented the chainweighted index now used to construct quantity
and price indexes in the U.S. national income
accounts, began his 1911 classic, The Purchasing
Power of Money, by defining economics as “the
science of wealth” and wealth as “material objects owned by human beings.” This definition—
that only what is material, and therefore tangible, can constitute wealth—underlies the national income accounting conventions we use to
determine asset value, profit, saving, and investment. But as we have seen, tangible assets—
equipment, structures, and land—are not the
only assets of lasting economic value. Indeed,
investment in intangible assets represents a growing proportion of our economy.14
More investment and higher profits mean
more output and saving, too. Gross domestic

Leonard Nakamura

product (our primary measure of U.S. production of goods and services) is constructed by summing estimates of the following: production of
goods and services used by consumers and by
governments, production of goods and services
sold to foreigners, investment goods used by
businesses, and construction of housing and
other buildings. As we have seen, treating spending on intangible assets the same way we treat
spending on tangible assets would raise measured business investment. Thus, similar treatment would also raise measured output of goods
and services. Making the adjustment for R&D
investment alone would raise measured U.S.
gross domestic product in the 1990s roughly 1.5
percent.15
Treating investment in R&D in the same manner that we treat investment in tangible assets
would raise reported national saving, too. National saving is the sum of saving done by households, governments, and businesses. Business
saving is defined as retained earnings plus depreciation and amortization allowances. (Thus,
business saving is that part of firms’ total revenue not paid out to employees, suppliers, creditors, owners, or governments.) Treating investment in R&D the same way we treat investment
in tangible assets would not only show that profits—and thus retained earnings—were higher
than reported in the 1990s, but it would also
make depreciation allowances larger. These two
adjustments would raise reported business saving enough to raise reported gross national saving in the 1990s from 15.9 percent to 17.1 percent of GDP.16

15
Between 1990 and 1997, R&D spending by corporations averaged $104 billion per year and GDP averaged $6.81 trillion per year.

The Bureau of Economic Analysis has recently published a statistical accounting of R&D investment and
assets (a “satellite” account) but has neither incorporated these data into its regular accounts nor kept the
data up to date (see the article by Carol Carson, Bruce
Grimm, and Carol Moylan).

16
Between 1990 to 1997, gross national saving averaged $1.08 trillion per year before adjustment for R&D,
but it averaged $1.18 trillion per year adjusted for R&D.
GDP after adjustment for R&D averaged $6.91 trillion
per year.

BUSINESS REVIEW

JULY/AUGUST 1999

These numbers probably understate the importance of investment in intangible assets because they account only for R&D and not other
intangible investments. Nonetheless, they make
clear that standard measures of investment, output, income, and saving are systematically understated. That understatement has become bigger as intangible investment has become more
important.
Though our official statistics rarely treat
spending on R&D and other intangible assets
as investment, the stock market recognizes that
such investments usually generate future profits. That is why investment in R&D generally

makes stock prices rise. The resulting capital
gains are taxed when realized but are not
counted in personal income. That fact helps explain why our official measure of personal saving—saving out of after-tax income—fell nearly
to zero in 1998. (See If the Personal Saving Rate Is
So Low, Why Are We Becoming Wealthier?)
CONCLUSION: A NEW PARADIGM?
This article has explored how investment,
profit, and saving are understated in our corporate and national accounts, particularly since
the mid-1970s, because of our accounting treatment of intangible assets.17 In fact, the U.S.

If the Personal Saving Rate Is So Low,
Why Are We Becoming Wealthier?
We have seen that firms that invest in R&D and other intangible assets generally see the price of
their shares rise as a result. Those capital gains are taxed when they are realized, but they are not
counted as income in our national accounts. The seemingly paradoxical result is that rapid growth of
spending on R&D and other intangible assets can make stockholders’ wealth grow rapidly and at the
same time make their personal saving rate appear to decline. Indeed, this phenomenon helps to
account for the reported decline in the U.S. personal saving rate in the 1990s.
Personal saving is measured as after-tax personal income (also called disposable income) less
personal outlays. In our national accounts, capital gains are not included in personal income.a But
taxes on realized capital gains are part of the taxes subtracted from personal income to get after-tax
income. Thus, our definition of personal saving does not count capital gains as income, but does
subtract capital gains taxes from income, artificially lowering measured disposable income and personal saving. Consumers have spent an essentially constant fraction of their pre-tax income since
1994. But after-tax income has fallen relative to pre-tax income in part because of unusually high
capital gains taxes. So the difference between disposable income and outlays—personal saving—has
fallen steadily.
According to the Congressional Budget Office, capital gains realizations likely increased about $230
billion between 1994 and 1997, and capital gains taxes rose by about $40 billion over that same period.
This surge in capital gains taxes helps to explain how, in the wake of the extraordinary rise in the U.S.
stock market in the 1990s, rising taxes have helped erase the budget deficit and turn it into a surplus.b
a
There is a good reason for this, in that capital gains are large and volatile; in most years the change in the
market value of stocks is substantially larger than the change in all other personal income. So if we included
capital gains in personal income, variations in personal income would mainly represent the change in the value
of stocks.
b

Another important contributor to the surplus has been rising Social Security payments.

FEDERAL RESERVE BANK OF PHILADELPHIA

Intangibles: What Put the New in the New Economy?

economy is in better condition than statistics
suggest. Rising investment in intangible assets
helps explain the rising value of U.S. equities.
That explanation, in turn, suggests that continued strong economic growth and strong profit
growth in the future are not so implausible. The
economic growth that ensues from rapid development of new products has largely been hidden from economists because our accounting
framework does not reveal this linkage clearly.
However, there can be no guarantee that investment in intangibles will grow as it has in the
past two decades. The growth of intangible investment depends on the continuing belief that
new products are waiting to be discovered, invented, and created, and the accompanying be-

17
Additional discussion of how mismeasurement of
inflation has contributed to the underestimation of output since the mid-1970s can be found in my 1997 Business Review article.

Leonard Nakamura

lief that such products will prove to be profitable. If the expected rate of return to intangible
investment were to decline, such investment
would slow.
R&D creates risks as well as opportunities.
The popularity of new products can cause old
product lines to be abandoned and existing businesses to become outmoded. Economist Joseph
Schumpeter referred to this process as “creative
destruction.” In an ideal world, creativity would
run ahead of destruction, keeping workers employed and consumption rising at a steady pace.
In the real world, the disruptive forces sometimes
gain the upper hand, and we encounter widespread unemployment, declines in asset values,
and slowdowns in investment in intangibles.
In either case, in good times or in bad, we
need to recognize the increasing importance of
intangible investment for our economy. Otherwise, statistical conventions can cause us to misread the fundamental forces propelling economic
activity.

BUSINESS REVIEW

JULY/AUGUST 1999

Appendix
Are All R&D Projects Lemons?
Accountants use balance sheets and income statements to illustrate the interrelationship of income,
expenses, profits, and assets. Balance sheets present the assets of the firm, such as cash and inventory,
and its liabilities, or debts. The excess of assets over the firm’s debts is called the book value of equity.
(This equity is listed as a liability, since it is “owed” to the owners of the business, so total liabilities,
including equity, are equal to total assets.) Income statements present the income and expense flows
that determine whether a profit has been made. The difference between book value of equity at the start
of an accounting period and at the end of the period equals the profit shown on the income statement
for that period.
Take as an example my son, Moses, setting up a lemonade stand. He starts with $5 on hand; at this
point his “firm” has a book value of equity of $5 (Balance Sheet 1a). Assume, for the sake of simplicity,
that the only cost of production for the lemonade stand is lemons.* Lemons cost 25 cents each, so the
$5 is used to purchase 20 lemons, which are in turn used to produce lemonade, which is then sold for $10.
Revenues were $10 and expenses were $5, so profit was $5 (Income Statement 1). This $5 profit is
reflected in the asset balance sheet, because Moses now has $10 cash-in-hand to prove that his firm’s net
worth has gone up $5 (Balance Sheet 1b).
Balance Sheet 1a
(beginning of day)

Income Statement 1

Assets:
cash

Liabilities:
Book value of equity:

Revenues:
lemonade
Expenses:
lemons
Profit:

Balance Sheet 1b
(end of day)
$10

Assets:
cash

$10

$ 5
$ 5

Liabilities:
Book value of equity:

$10

Lemons as Tangible Assets. Now suppose that Moses had started with $10 on hand (Balance Sheet
2a). This purchases 40 lemons, 20 of them used to make $10 worth of lemonade, and 20 stored for the
next day’s business. Again there is a $5 profit, for although $10 was spent on lemons, only $5 worth was
used to produce current revenue (Income Statement 2). Twenty lemons went into inventory, the technical term for goods owned by the firm that are available for future use or sale. So the lemonade firm is
now worth $15, consisting of $10 cash and $5 in lemon inventory (Balance Sheet 2b).

Balance Sheet 2a
(beginning of day)

Income Statement 2

Assets:
cash

$10

Liabilities:
Book value of equity:

$10

Revenues:
lemonade
Expenses:
lemons used
Profit:

Balance Sheet 2b
(end of day)

$10
$ 5
$ 5

Assets:
cash
$10
lemon inventory
$ 5
Liabilities:
Book value of equity: $ 15

FEDERAL RESERVE BANK OF PHILADELPHIA

Intangibles: What Put the New in the New Economy?

Leonard Nakamura

When a firm invests in tangible assets—in this case 20 lemons—there is no deduction from profit until
the assets either are used in production or begin to depreciate or spoil. If assets depreciate, a portion of
the initial expense is deducted. The principle is that the facilities used to produce current revenue are a
cost only to the extent that their value has declined during use. For example, if four of Moses’ lemons
spoil, his $5 inventory will decline in value to $4. In this case, the firm’s accounts would show spoilage of
$1, profits of $4, and a lemonade firm worth $14 (Income Statement 3 and Balance Sheets 3a and 3b).
Balance Sheet 3a
(beginning of day)

Income Statement 3

Assets:
cash

$10

Liabilities:
Book value of equity:

$10

Revenues:
lemonade
Expenses:
lemons used
lemon spoilage
Profit:

Balance Sheet 3b
(end of day)
$10
$ 5
$ 1
$ 4

Assets:
cash
$10
lemon inventory
$ 4
Liabilities:
Book value of equity: $14

Are All R&D Projects Really Lemons? So far, we have said nothing about intangible investment.
Again, let’s suppose Moses starts with $10 cash-in hand (Balance Sheet 4a), but let’s suppose he is also a
designer, who spends $5 developing a lemonade-pitcher design and sells $10 worth of lemonade using $5
worth of lemons. According to standard accounting principles, his firm’s total revenue is $10, and the
cost of the R&D to design the lemonade pitcher is expensed, that is, counted as a cost of current operations, not as an investment. In other words, the investment in the design of the lemonade pitcher is
treated as an additional cost of making the lemonade. The day’s profits are zero (Income Statement 4).
The accounting value of the lemonade firm is $10, the proceeds from the sale of lemonade (Balance Sheet
4b). Until Moses sells the lemonade-pitcher design, the design’s accounting value is zero. If Moses can
later sell the lemonade-pitcher design for $10, the firm will recognize a capital gain of $10 and an extraordinary profit of $10. The profit, in accounting terms, will appear out of nowhere. Put another way,
accounting procedures treat all R&D efforts as if they are destined to be failures— they produce zero
assets until proven otherwise.

Balance Sheet 4a
(beginning of day)

Income Statement 4

Assets:
cash

$10

Liabilities:
Book value of equity:

$10

Revenues:
lemonade
Expenses:
lemons used
design costs
Profit:

Balance Sheet 4b
(end of day)
$10
$ 5
$ 5
$ 0

Assets:
cash

$10

Liabilities:
Book value of equity:

$10

*Thus to avoid cluttering up the analysis, we assume that the sugar, water, cups, and labor normally used in
selling lemonade are not necessary in this case or, perhaps more realistically, are supplied free by Moses’ dad.

BUSINESS REVIEW

JULY/AUGUST 1999

REFERENCES
Carson, Carol S., Bruce T. Grimm, and Carol E. Moylan. “A Satellite Account for Research and Development,” Survey of Current Business 74 November 1994, pp. 37-71.
Chambers, Dennis, Ross Jennings, and Robert B. Thompson. “Evidence on the Usefulness of Capitalizing and Amortizing Research and Development Costs,” mimeo, University of Texas, January
1998.
U.S. Congressional Budget Office, The Economic and Budget Outlook, Fiscal Years 2000-2009. Washington, D.C.: U.S. Government Printing Office, Washington D.C., January 1999, pp. 48-50.
Estes, Ralph. Dictionary of Accounting. MIT (Cambridge, MA), 1981, pp. 81 & 105.
Fisher, Irving. The Purchasing Power of Money, 2nd Edition. New York: Macmillan, 1920, p. 1.
Hall, Bronwyn. “The Stock Market Value of R&D Investment During the 1980’s,” American Economic
Review 83, May 1993, pp. 259-64.
Hill, Peter. “Tangibles, Intangibles, and Services: A New Taxonomy for the Classification of Output,”
paper presented at CSLS Conference on Service Sector Productivity and the Productivity Paradox,
April 11-12, 1997, Ottawa, Canada.
Johnson, Glenn L. and James A. Gentry Jr. Finney and Miller’s Principles of Accounting, Intermediate.
Englewood Cliffs, NJ: Prentice-Hall, Inc., 1974.
Nakamura, Leonard. “Measuring Inflation in a High-Tech Age,” Federal Reserve of Philadelphia
Business Review, November/December 1995.
Nakamura, Leonard. “Is the U.S. Economy Really Growing Too Slowly? Maybe We’re Measuring
Growth Wrong,” Federal Reserve of Philadelphia Business Review, March/April 1997.
Nakamura, Leonard. “The Retail Revolution and Food-Price Measurement,” Federal Reserve of
Philadelphia Business Review, May/June 1998.
Williams, Jan R. 1999 Miller GAAP Guide. New York: Harcourt Brace, 1998.

FEDERAL RESERVE BANK OF PHILADELPHIA

Intangibles: What Put the New in the New Economy?

Leonard Nakamura

Do States Respond Differently
To Changes in Monetary Policy?
Gerald A. Carlino and Robert H. DeFina

n earlier research we found that monetary
policy affects real income quite differently in each
of the eight major U.S. regions as defined by the
Bureau of Economic Analysis (BEA).1 In this article, we extend our analysis of the effects of

*Jerry Carlino is an economic advisor in the Research
Department of the Philadelphia Fed and an adjunct professor in the Real Estate Department of the University of
Pennsylvania’s Wharton School. Bob DeFina is the John
A. Murphy Professor in the College of Commerce and
Finance, Villanova University, Villanova, Pennsylvania.
1

See the 1996 article by Gerald A. Carlino and Robert
DeFina.

monetary policy to the state level. Extending the
evidence to the state level is important for two
reasons. First, states within a region may have
quite varied responses to monetary policy actions: responses different from one another and
from the region’s overall response. For example,
we found that five of the seven states in the Plains
region show an effect below the regional average, and two states, Missouri and Minnesota,
show an above-average impact. Missouri and
Minnesota account for more than one-half of the
personal income in the Plains region.
Second, a state-level study provides 48 individual responses to monetary policy actions, not
just the eight responses in our regional study.2
17

BUSINESS REVIEW

The states, therefore, provide a richer testing
ground for determining the sources of the differential responses. Our analysis indicates that
state economies with a large proportion of the
interest-sensitive industries—construction and
durable goods manufacturing—are more responsive to changes in monetary policy than the
more industrially diverse states. Our earlier
study showed the same is true for regional economies as well. While our earlier analysis indicated that a region’s concentration of small firms
possibly has an effect on a region’s response to
changes in policy, no such association was evident for states. Finally, as in our regional study,
a greater concentration of small banks is found
to decrease a state’s sensitivity to monetary
policy shocks, contrary to predictions of some
economists.
WHAT IS THE EVIDENCE?
Individual States’ Responses. We used a statistical technique known as vector
autoregression (VAR) to estimate the effects of
changes in monetary policy on real personal income growth at the state level.3 The variables in
our model included real personal income
growth for the state under consideration as well
as real personal income growth in each of the
eight major regions defined by the BEA.4 Includ-

Since Alaska and Hawaii do not share common borders with any other state, we limited our study to the 48
contiguous states.
3

See Gerald Carlino and Robert DeFina (1999). A
VAR is a widely used modeling technique for gathering
evidence on business-cycle dynamics. VARs typically rely
on a small number of variables expressed as past values
of the dependent variable and past values of the other
variables in the model. See Theodore Crone’s article for a
discussion of VARs as applied to regional analysis.
4

More precisely, we included the seven regions not
containing the state under study, plus the personal income from the region containing the state less that state’s
income.
18

JULY/AUGUST 1999

ing income growth in the regions permits feedback effects. The model also included the change
in the relative price of energy to account for the
effects of oil-price shocks, the change in core CPI
to capture underlying trends in the aggregate
price level, the change in the index of leading
indicators as a parsimonious way to summarize a variety of macroeconomic variables, and
the change in the federal funds rate as a measure of changes in monetary policy.5 The study
employed quarterly data for the period 1958-92.
A typical way to summarize the impact of
monetary policy on personal income growth is
to show how the level of real personal income in
a state changes over time because of monetary
policy surprises, or shocks. Such shocks are
measured by unanticipated changes in the federal funds rate. For example, in the fall of 1994,
Fed actions raised the federal funds rate 0.75
percentage point. Shortly before, forecasters had
been publicly predicting an increase of 0.25 percentage point. Thus, the additional 0.50 percentage point represented a policy shock.6 The im-

The core CPI is the CPI minus food and energy. The
change in core CPI and the change in the index of leading
indicators are two variables that did not appear in the
list of variables for our earlier regional study.
6
An important part of our study requires the separation of changes in the funds rate that are predictable
responses to important indicators of the economy’s health
from changes in the funds rate that cannot be systematically predicted (policy shocks). The model includes an
equation that predicts changes in the federal funds rate
on the basis of a year’s worth of past data for each of the
variables in the model (including change in core CPI and
the change in the index of leading indicators). Unexpected changes in the federal funds rate are measured by
taking the difference between the actual and predicted
change. Unexpected changes in the federal funds rate are
used to measure monetary policy shocks in the policy
simulations that follow. The analysis assumes that unexpected changes in the federal funds rate arise only
from policy shocks. Some economists believe that only
unanticipated changes in monetary policy affect real eco-

FEDERAL RESERVE BANK OF PHILADELPHIA

Intangibles:
What Put
the NewtoinChanges
the New
Do
States Respond
Differently
in Economy?
Monetary Policy?

pact of this unanticipated change in monetary
policy is measured by the gap between the
model’s estimate of what real personal income
in a state would have been without the monetary policy action and what it turned out to be
with it.7
We found that an unexpected one-percentagepoint increase in the federal funds rate generally reduces real income growth temporarily and,
thus, leaves the level of real personal income
below what it otherwise would have been.8 The
model treats tightening and easing of the fed
funds rate symmetrically, so that an unexpected
cut in the funds rate temporarily raises real personal income growth relative to what it otherwise would have been.
The greatest response to an unanticipated
change in monetary policy is not immediate. In
fact, real income at the state level is essentially
unchanged for two quarters after an unanticipated one-percentage-point increase in the federal funds rate, but then real income declines
substantially in most states. The maximum gap
between actual personal income and what it
would be without the change in monetary policy
occurs, on average, about eight to 10 quarters
following the policy shock. This general profile

Nakamura
Gerald A. Carlino andLeonard
Robert H.
DeFina

is similar to the estimated impact of monetary
policy changes on the U.S. economy as reported
in other studies.9 If we look at real personal
income’s response to an unexpected increase of
one percentage point in the federal funds rate,
income in the nation falls 1.16 percent (compared
with what it would have been) eight quarters
after the increase (Figure).
9
See, for example, the 1996 study by Eric Leeper,
Christopher Sims, and Tao Zha.

FIGURE

Response of Real Personal
Income to an Unexpected
One-Percentage-Point
Increase in the
Fed Funds Rate
National Average

nomic variables. See Shaghil Ahmed’s article for a fuller
discussion of the distinction between unanticipated and
anticipated changes in monetary policy and their effects
on real activity.
7
The gap in each period is called the cumulative impulse response.
8

The question of how monetary policy affects real
personal income in the long run remains open. We did
not conduct formal statistical tests on the significance of
the long-run response and so cannot shed light on the
issue. While the graph presented in the text suggests a
sustained impact, the effects of policy shocks over long
horizons are estimated with less statistical precision than
those estimated over short horizons. Since the estimates
become less precise, statements about policy’s long-term
impact become more tenuous.

Graph shows the percent difference in real personal
income from what it would have been without the
unanticipated increase in the fed funds rate.
19

BUSINESS REVIEW

JULY/AUGUST 1999

While the vast majority of state responses follow the general pattern demonstrated by the national average, not all states respond by the same
magnitude (see map).10 Michigan has the largest response: real income fell 2.7 percent eight
quarters after a one-percentage-point increase
in the federal funds rate. Seven states (Arizona,
Georgia, Indiana, Michigan, New Hampshire,
Oregon, and Tennessee) respond at least 38 percent again as much as the national average.11

Possible explanations for this high response include the fact that four of these states (Indiana,
Michigan, New Hampshire, and Oregon) have
a relatively high concentration of durable goods
manufacturing, an interest-sensitive industry.
One state (Arizona) has a much higher than average concentration of construction, another interest-sensitive industry. While Georgia and
Tennessee do not have an especially high concentration of interest-sensitive industries, they

10
The cumulative impulse response functions for individual states are shown in our 1999 article on the
Internet at www.phil.frb.org/econ/wps/1997/wp9712.pdf.

11
The average state response was 1.16 percent with a
standard deviation of 0.4684. The seven most responsive states are at least one standard deviation above the
average state response.

Response of Personal Income to a One-Percentage-Point
Increase in the Fed Funds Rate*

0 to -0.7%
-0.7% to -1.6%
-1.6% and below
National average = -1.16
*Eight-quarter cumulative impulse response of personal income

FEDERAL RESERVE BANK OF PHILADELPHIA

Intangibles:
What Put
the NewtoinChanges
the New
Do
States Respond
Differently
in Economy?
Monetary Policy?

may have large markets for their products in the
states that are highly responsive to monetary
policy shocks; if so, Georgia and Tennessee
would tend to be more sensitive to monetary
policy actions than their own industrial structures would indicate.12
Seven states (Colorado, Louisiana, Oklahoma, New York, North Dakota, Texas, and
Wyoming) are the least sensitive to monetary
policy shocks, responding no more than 60 percent as much as the national average.13 Interestingly, the total output of four of these states (Louisiana, Oklahoma, Texas, and Wyoming) includes
a high concentration in the extractive industries
(drilling and mining). Although these states are
found to be the four least sensitive to monetary
policy actions, they are buffeted by other types
of shocks, particularly shocks to the price of energy. For example, a one-percentage-point decrease in the growth rate of the relative price of
energy leaves real personal income in the four
states between 1.6 percent (Oklahoma) to 3.2
percent (Wyoming) lower than otherwise after
two years. (Personal income fell 1.9 percent in
Texas and 2.8 percent in Louisiana in response
to this energy price shock.)
By contrast, New Jersey, an energy-consuming state, experiences a rise in personal income
of about 2 percent two years after a one-percentage-point decrease in the growth rate of the relative price of energy. We also found that Colorado, New York, and North Dakota tend to be
less responsive to monetary policy shocks than
the national average. One reason is that production in these states involves relatively small

12
Since we used broad regional aggregates to capture
these spillovers in our model, we are unable to shed any
light on the extent to which trade among individual states
influences their responsiveness to monetary policy actions.
13
States were placed in this grouping if their policy
response was at least one standard deviation below that
of the average state.

Nakamura
Gerald A. Carlino andLeonard
Robert H.
DeFina

shares of interest-sensitive industries.
Responses of States Within a Region. By using a weighted average of the responses of states
within a region, we can form an average response for each of the eight major regions (Table
of Regional Summaries). The absolute value of
these responses ranges from 0.52 in the Southwest to 1.72 in the Great Lakes; in terms of absolute value the national average is 1.16.14
Comparisons of states’ responses to monetary
policy actions reveal that an individual state’s
response is often quite different from the average response of its region and from the response
of the other states in that region. For example,
14

Real personal income growth in the Rocky Mountain region also has a relatively small response to monetary policy shocks. Thus, our findings match up well
relative to those reported in our earlier article, which
found the largest response to monetary policy actions in
the Great Lakes region and the least response in the Southwest and Rocky Mountain regions.

Table of
Regional Summaries
Region

Average
Response*

New England
Mideast
Great Lakes
Plains
Southeast
Southwest
Rocky Mountain
Far West

-1.26
-0.91
-1.72
-1.14
-1.23
-0.52
-0.80
-1.16

All Regions

-1.16

*Eight-quarter cumulative impulse response of real
personal income. The regional responses are computed as weighted averages of the individual state
responses; the weights reflect each state’s share of
its region’s personal income.

BUSINESS REVIEW

we found that real personal income in the Far
West region fell 1.16 percentage points following a one-percentage-point increase in the fed
funds rate, matching the average national response. However, two of the four states that make
up the Far West region (Oregon and Nevada) are
considerably more responsive to monetary policy
shocks.
Being part of a region that has a low response
to monetary policy actions is no guarantee that
each state in the region will respond similarly.
Arizona responds more than half again as much
as the U.S. average, despite being part of the least
responsive Southwest region. In general, there
is much less variation in regional responses to
monetary policy shocks than in state responses.15
WHAT CAUSES THE DIFFERENTIAL
STATE RESPONSES TO MONETARY
POLICY ACTIONS?
In our regional study, we showed that a
region’s response to monetary policy is related
to its mix of interest-sensitive industries and
possibly to its mix of large and small firms. Because small businesses typically have banks as
their sole sources of credit they might be considered more sensitive to Fed policy. Our regional
study found only slight evidence that economic
activity in regions that have high concentrations
of small firms was more sensitive to changes in
Fed policy. Similarly, some researchers believe
that the effects of monetary policy would be
greater in regions with a large share of small
banks. But our regional study found that the mix
of small and large banks has the opposite effect.
In another recent study, we looked at how important these factors are in accounting for the
different state responses to monetary policy
shocks (Appendix).16 The individual state re15
The standard deviation of the regional responses is
0.3574; state responses show a considerably larger standard deviation of 0.4684.
16

See Gerald A. Carlino and Robert DeFina (1998b).

JULY/AUGUST 1999

sponses (the estimated values of the cumulative
responses shown on the map) were systematically related to variables capturing two of these
three factors.
The interest sensitivity of a state’s industries
is likely to rise with the percent of a state’s total
gross state product accounted for by construction or durable goods manufacturing. Studies
have shown that consumer spending on housing and manufactured goods, especially durable
goods, tends to be interest sensitive. Spending
on services, in contrast, tends to vary little with
interest rates.17 Our analysis indicates that state
economies with a large proportion of construction or manufacturing of durable goods are more
responsive to changes in monetary policy than
the more industrially diverse states.
On the other hand, the analysis found that
states with relatively large shares of output accounted for by the extractive industries and by
the finance, insurance, and real estate industries
are less sensitive to changes in monetary policy
than the more industrially diverse states. This
finding suggests that differences in interest-rate
sensitivities across industries are one reason for
different state responses.18 Differences in the mix
of interest-sensitive industries may explain why
the states that make up the Third Federal Reserve District (Pennsylvania, New Jersey, and
Delaware) respond somewhat more to monetary
policy shocks than other states in the Mideast
region. (See Monetary Policy and the Third District
States.)
17

See Paul Bennett’s article for a survey of relevant
studies.
18
The finding of high interest-rate sensitivity for states
that depend heavily on durable goods manufacturing is
consistent with our findings for regions. However, unlike
the state-level findings, our regional results did not offer
significant evidence that regions that depend on the construction industry have greater responsiveness to monetary policy initiatives. The state-level findings are likely
to be more reliable, since they are based on a much larger
sample.

FEDERAL RESERVE BANK OF PHILADELPHIA

Intangibles:
What Put
the NewtoinChanges
the NewinEconomy?
Do States Respond
Differently
Monetary Policy?

Gerald A. Carlino andLeonard
Robert Nakamura
H. DeFina

Monetary Policy and the Third District States
The responses of the states of the Third Federal Reserve District to monetary policy shocks are
similar to one another and to the national average response.a The states of the Third District have a
somewhat stronger response, however, than the other two states in the Mideast region—Maryland
and New York. This stronger response can be attributed, at least in part, to differences in the mix of
interest-sensitive industries. For example, New York has a much higher concentration of finance,
insurance, and real estate industries (24.3 percent) compared with the average state (14.9 percent),
which tends to reduce New York’s responsiveness (see the Table). Also limiting New York’s responsiveness is its relatively low fraction of construction and durable goods manufacturing.

Share of Total Output Attributable
To Selected Interest-Sensitive Industriesb
State

Delaware
Maryland
New Jersey
New York
Pennsylvania
U.S. Average

Construction

Durable
Goods

5.0
5.9
4.4
3.4
4.5
4.7

9.8
7.1
9.6
9.4
14.8
11.5

Finance,
Policy
Insurance,
Responsec
and Real Estate
19.8
18.1
18.4
24.3
15.6
14.9

-1.00
-0.92
-1.06
-0.72
-1.14
-1.16

While Maryland has a somewhat higher share of interest-sensitive construction, Maryland’s responsiveness tends to be limited by its relatively low share of interest-sensitive durable goods manufacturing and its relatively high concentration of income from the finance, insurance, and real estate
sector. By contrast, Pennsylvania has a relatively high share of durable goods manufacturing and
only a slightly above-average share of income from the finance, insurance, and real estate sector.
Thus, among the states of the Mideast region, Pennsylvania tends to be the most responsive to
monetary policy actions.
Because the policy responses (impulse responses) were estimated over a long period, the industry
mix variables given in the table are averaged over 1977-90. However, states have experienced changes
in their mix of industries over time, so that long-run averages may not be representative of a state’s
current industrial structure. Therefore, we also looked at the 1996 share of each state’s personal
income accounted for by the industries given in the table and found that conclusions based on 1996
shares are consistent with those based on shares averaged over the period 1977-90.
a

The Third District covers the eastern two-thirds of Pennsylvania, southern New Jersey, and Delaware.

Shares are averaged over the period 1977-90.

c
Eight-quarter cumulative impulse response in real personal income that results from an unanticipated
one-percentage-point increase in the federal funds rate.

BUSINESS REVIEW

JULY/AUGUST 1999

At the state level we find no evidence that
states containing a larger concentration of small
firms tend to be more responsive to monetary
policy shifts than states containing small concentrations of small firms.19 In addition, we
found that a region becomes less sensitive to an
increase in the federal funds rate as the percentage of small banks in that region increases. This
result is inconsistent with the view espoused by
Anil Kashyap and Jeremy Stein that small banks
do not have as many alternative sources of funds
and are therefore affected more by changes in
monetary policy.20 One possibility for the inconsistency is that a bank’s asset size may be a poor
indicator of its ability to adjust its balance sheet
to monetary policy actions. In a study at the
Federal Reserve Bank of Boston, Joe Peek and

According to one theory, Fed actions affect economic
activity by altering banks’ ability to provide loans. Large
firms usually have greater access to alternative, nonbank
sources of funds, such as issuing corporate stocks and
bonds or commercial paper. We found no evidence, however, that activity in states that have high concentrations
of small firms was especially sensitive to changes in Fed
policy.
20
This contrary effect was also found in our regional
study.

Eric Rosengren suggested that bank capital is a
better indicator—better capitalized banks have
more and cheaper alternative sources of funds
available. Using data for New England banks
during the late 1980s and early 1990s, the authors found that the number of loans made by
banks that were under regulatory pressure to
raise their capital levels did not increase in response to a lower federal funds rate.
CONCLUSION
Does monetary policy have differential effects
across states? The answer clearly is yes. Comparisons of states’ responses to monetary policy
actions reveal that an individual state’s response
is often quite different from the average response
of its region and from the response of the other
states in that region.
We provided some reasons for the differential
policy response across states. The size of a state’s
response to a monetary policy shock is positively
related to its share of construction and durable
goods manufacturing and negatively related to
its share of extractive industries and the finance,
insurance, and real estate industries. A state’s
concentration of small firms has no significant
effect on the size of the state’s policy response.
Finally, a greater concentration of small banks
decreases a state’s sensitivity to monetary policy
shocks, contrary to the predictions of Kashyap
and Stein.

Appendix
The absolute value of the estimated state cumulative responses shown in Table A (and summarized
in the map) are used as dependent variables in a cross-state regression equation to explain the
differential state responses to monetary policy shocks. An eight-quarter horizon was chosen for the
cumulative response because this is generally when Fed policy has its maximum cumulative impact.
The independent variables in the model are designed to account for the three reasons given to explain
why state responses to monetary policy innovations differ. The shares of a state’s gross state product
(GSP) accounted for by each of eight major industry groupings are included to capture the effect of
monetary policy as a result of the policy’s effect on interest rates. The percent of a state’s firms
(establishments) that are small, defined as the percent of a state’s firms with fewer than 250 employees, is included to capture the possible effects of firm size. Two alternative variables are used to
capture the effects of bank size—the percent of a state’s total loans made by the state’s banks at or

FEDERAL RESERVE BANK OF PHILADELPHIA

Intangibles:
What Put
the NewtoinChanges
the New
Do
States Respond
Differently
in Economy?
Monetary Policy?

Nakamura
Gerald A. Carlino andLeonard
Robert H.
DeFina

Appendix (continued)
TABLE A

Eight-Quarter Cumulative Responses to a One-Percentage-Point Fed Funds Rate Increase
(response in percentage points; weight is the state’s share of regional personal income.)
New England
Connecticut
Massachusetts
Maine
New Hampshire
Rhode Island
Vermont

Response
1.2678
1.0712
1.5099
1.9264
1.4391
1.4246

Weight
0.29
0.47
0.07
0.07
0.07
0.03

Mideast
Delaware
Maryland
New Jersey
New York
Pennsylvania

Response
1.0018
0.9174
1.0607
0.7176
1.1379

Weight
0.01
0.10
0.20
0.44
0.25

Great Lakes
Illinois
Indiana
Michigan
Ohio
Wisconsin

Response
1.2351
1.8345
2.6634
1.5378
1.4604

Weight
0.30
0.12
0.22
0.25
0.11

Plains
Iowa
Kansas
Minnesota
Missouri
Nebraska
North Dakota
South Dakota

Response
0.8278
0.9653
1.1982
1.5282
0.8216
0.7427
0.8695

Weight
0.16
0.14
0.25
0.29
0.09
0.03
0.04

Southeast
Response
Alabama
1.3261
Arkansas
1.3443
Florida
1.154
Georgia
1.6084
Kentucky
1.1599
Louisiana
0.4935
Mississippi
1.3004
North Carolina 1.3404
South Carolina 1.2816
Tennessee
1.5632
Virginia
1.022
West Virginia
1.3803

Weight
0.07
0.04
0.22
0.11
0.06
0.07
0.04
0.11
0.05
0.08
0.12
0.03

Southwest
Arizona
New Mexico
Oklahoma
Texas

Response
1.8006
0.8182
-0.0741
0.361

Weight
0.13
0.05
0.13
0.69

Rocky Mountain Response
Colorado
0.7134
Idaho
0.9573
Montana
0.8469
Utah
1.1396
Wyoming
0.1109

Weight
0.50
0.13
0.11
0.19
0.07

Far West
California
Oregon
Washington
Nevada

Weight
0.79
0.07
0.12
0.03

Response
1.1305
1.7168
0.9757
1.4356

below the 90th percentile in assets nationally, and the percent of a state’s total loans made by the state’s
banks at or below the 90th percentile in assets nationally and not part of a bank holding company.
Because the estimated long-run responses represent average behavior during the sample period,
averaging the data for the explanatory variables is appropriate. Averaging also minimizes the chance
that the results depend on the data for a particular year and helps control for business-cycle dynamics.
(Data availability limited averaging to the period from the mid-1970s to the early 1990s.)
Two versions of the model are presented in Table B, depending on which of the alternative smallbank variables is used. In model 1, the all-small-banks variable is included, whereas model 2 uses only
small banks that are not members of a bank holding company. The results for models 1 and 2 pre-

BUSINESS REVIEW

sented in Table B explain between 61 to 62 percent of the
cross-state variation in cumulative responses. The percent of
a state’s GSP accounted for by
the manufacture of durable
goods and by construction is
positively and significantly related to the size of a state’s longrun response to Fed policy
shocks; the percent of a state’s
GSP accounted for by its extractive industries and by the finance, insurance, and real estate industries is negatively and
significantly related to its longrun response to Fed policy.
These results appear quite reasonable and do not depend on
the choice of the loan variable.
The importance of the shares
of durable goods manufacturing and construction can be interpreted as evidence that
monetary policy affects total
output because higher interest
rates are likely to have profound effects on people’s ability to buy houses and other big
ticket items, such as autos.
We find no evidence that
cross-state variation in the mix
of small versus large firms matters. States containing large
concentrations of small firms
tend to be no more responsive
to monetary policy shifts than
states containing small concentrations of small firms. In contrast, we find some evidence
that a state becomes more sensitive to a monetary policy
shock as the percentage of
small banks in the state goes
down. The estimated coefficients on the small-bank variables are negative in both models 1 and 2 and negative and significant in model 2.

JULY/AUGUST 1999

TABLE B

Explaining Cross-State Variation
in Policy Responsesa
Variableb

Model 1

Model 2

Intercept

0.2179
(1.5218)

0.3194
(1.4867)

% Agriculture

-0.5071
(1.4005)

-0.3359
(1.3818)

% Mining

-3.4785
(1.7354)**

-3.2890
(1.7157)*

% Construction

20.9681
(8.2570)**

19.5034
(8.1240)**

% Durables Mfg.

5.5628
(1.4791)***

5.5225
(1.4374)***

% Nondurable Mfg.

-0.1964
(1.5781)

-0.0639
(1.5585)

% Transportation

3.4391
(4.4016)

3.3139
(4.2550)

% Wholesale Trade

-0.6849
(4.9399)

-0.3864
(4.8691)

% Retail Trade

-3.0018
(7.6550)

-1.6932
(7.5837)

% FIRE

-5.0091
(2.7362)*

-5.2696
(2.7047)*

% Small Firm

0.0064
(0.0109)

0.0047
(0.0107)

% Small Bank Loans
(all banks)

-0.0044
(0.0031)

% Small Bank Loans
(no holding co.)
Adjusted R2

-0.0076
(0.0042)*
0.6070

0.6191

a
The dependent variable is the absolute value of the estimated state cumulative responses shown in the table. Standard errors in parentheses. *, **, and *** indicate that a null
hypothesis of zero is rejected at the 10%, 5%, and 1% levels,
respectively.
b

Variables are averaged over 1977-90.

FEDERAL RESERVE BANK OF PHILADELPHIA

Intangibles:
What Put
the NewtoinChanges
the New
Do
States Respond
Differently
in Economy?
Monetary Policy?

Nakamura
Gerald A. Carlino andLeonard
Robert H.
DeFina

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Crone, Theodore M. “A Slow Recovery in the Third District: Evidence From New Time-Series Models,” Federal Reserve Bank of Philadelphia Business Review (July/August 1992).
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Peek, Joe, and Eric Rosengren. “Is Bank Lending Important for the Transmission of Monetary Policy?
An Overview,” Federal Reserve Bank of Boston New England Economic Review (November/December 1995).

Full text of Business Review (Federal Reserve Bank of Philadelphia) : July/August 1999

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