Full text of Business Review (Federal Reserve Bank of Philadelphia) : March/April 2000

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The Changing Nature of the
Payments System: Should
New Players Mean New Rules?

D

Loretta J. Mester*

uring the past 25 years a multitude of mavens have written the obituary of the paper check,
predicting that by the time the new millennium
arrived everyone would be paying bills electronically. But the demise of the paper check has been
greatly exaggerated—checks are still a very important means of payment in the U.S. Indeed,
according to the Bank for International Settle-

ments, 66 billion checks were written in the U.S.
in 1997.1 Check volume over the preceding five
years had been rising between 2 and 3 percent a
year, albeit the share of transactions made via
check fell slightly.
Similarly, it seems you cannot pick up a newspaper or turn on the TV without hearing that
electronic forms of banking and finance, includ-

*Loretta Mester is a vice president and economist in
the Research Department of the Philadelphia Fed. Loretta
thanks Edward Boehne, president of the Federal Reserve
Bank of Philadelphia, for suggesting the topic of this
article. She also thanks Bob Hunt, Leonard Nakamura,
and Blake Prichard for valuable input.

1
The data reported in this article were those available
as of January 11, 2000. Unlike many government statistics, much of the data on payments is not systematically
collected by government agencies. These data come from
both private-sector sources and government sources, often rely on surveys, and are subject to more error than
other government-collected statistics.

3

BUSINESS REVIEW

ing Internet and PC banking and electronic billpaying, are taking over the financial services industry. But will electronic means of payments
become dominant, and if so, how soon? This
article discusses some of the recent developments
in electronic payments in the U.S. and what the
future may hold.
The payments system refers to the parties that
make or receive payments and the means by
which monetary value is transferred between
these parties. In 1997, the U.S. payments system
generated 650 billion payments worth about $22
trillion among businesses, households, and governments (see BAI/PSI Global, p. 2). In terms of
the number of transactions, the majority (about
590 billion) were from households to businesses;
in terms of dollar volume, the largest amount
($8.2 trillion) was between businesses. A wellfunctioning payments system is crucial to a wellfunctioning economy, and to function well, the
payments system needs to be reliable, accurate,
secure, and efficient.
The most popular forms of retail payments in
the U.S. have been currency, coin, and paper
checks.2 Electronic forms of payments, like those
made via an automated clearing house, ATM, or
credit card, have become more popular and are
an increasingly important part of the retail payments system.3 For example, between 1992 and
1997, the share of the number of consumer payments made in cash at the point-of-sale fell markedly, from 79 percent to 53 percent, and the share
paid by check grew by six percentage points to
about 22 percent; the share made by credit cards
showed the largest increase, growing threefold,
to 19 percent4 (BAI/Global) (Figure 1). Estimates
2
Retail payments refer to payments between an individual and another party.
3

An automated clearing house (ACH) is an electronic
interbank payments system used for small and recurring
payments, such as direct deposit of payrolls or automatic payment of utility, mortgage, or other bills. The
Federal Reserve System runs the largest ACH network;
there are private systems as well.
4

MARCH/APRIL 2000

put cash payments at about 27 percent of the
total dollar value of consumer payments made
at the point-of-sale in 1997, while check payments represented about 40 percent of the dollar
value, and credit cards around 25 percent.5 Most
recently, a number of new electronic forms of
payments and components of the payments system have been added to the mix, for example,
stored-value cards, smart cards, debit cards, electronic check truncation, PC banking, and banking over the Internet.
Traditionally, the payments system in the U.S.
has been built around the banking industry. It is
estimated that the payments business represents
about a third of the banking industry’s revenues,
expense, and profits.6 It makes sense that banks

4

In 1997, payments made at the point-of-sale represented 93 percent of all payments, while bill payments
represented 5 percent and government represented 2 percent of all payments (BAI/PSI Global).
5
Data on the dollar-value shares were not available,
so I roughly estimated these based on the shares of the
number of transactions and data on the average size of
transactions by payments means, given in Table 1. Since
for checks, the average size of transactions at the pointof-sale is likely to be less than the average size given in
Table 1, which covers checks written at both the point-ofsale and also to pay bills, the check payment share at the
point-of-sale is probably less than 40 percent.
6
In a recent speech, Federal Reserve Board Vice Chairman Roger Ferguson put the payments system share of
banking revenues, expenses, and profits at a third (April
4, 1998), and a study by Lawrence J. Radecki of the New
York Fed estimates that payments services represent twofifths of operating revenue of the 25 largest bank holding
companies operating in 1996. Revenue from banks’ payments services includes demand deposit and other transaction account fees, bad check fees, checkbook charges,
certified transaction fees, ATM fees, ACH wire fees, commercial services like lockbox processing and trade finance, processing of electronic benefits transfers, correspondent processing charges, and cash handling services.
A BAI/PSI Global study (pp. 73-75) estimates that
banks obtain about 24 percent of the total revenues generated by the payments business, while technology vendors and other third parties (such as credit card pay-

FEDERAL RESERVE BANK OF PHILADELPHIA

The Changing Nature of the Payments System: Should New Players Mean New Rules?

would be at the center of the payments system,
since they are experts at assessing and handling
risk, an attribute of any means of payment, and
they are experienced at clearing and settling
transactions. But new nonbank players have
entered the payments arena. Electronic technologies enable settlement and clearing to be done
by different entities, which are not necessarily
banks. Currently, the Fed plays an important
role in ensuring safety and soundness, efficiency,
and access to the payments system. Should new
players mean new rules?
INNOVATIONS IN ELECTRONIC
PAYMENTS
Electronic funds transfer is not new. Wholesale banking, involving large-scale payment

Loretta J. Mester

transfers, has been electronic for some time. What
is relatively new is the electronic transfer of payments
in the retail market. There
are two types of developments in today’s retail payments system. Some of the
new means of payments
are really just extensions of
instruments that have been
around for decades. For example, if I buy books over
the Internet using my credit
card, this is a new way to
buy books rather than buying them in person at the
bookstore. However, the
means of payment is only a
little different: sending my
credit card information, encrypted, over the Internet
versus handing my credit card to the sales clerk
in the store. Types of payments that are really
just extensions of existing payment instruments
include debit cards; electronic check presentment
(in which information on the amount of the check
and the account is sent to the paying bank electronically); PC banking; electronic benefits transfer, through which the government will pay welfare benefits; and direct deposit through the
ACH.7 These instruments use current technologies and are tied to bank deposits, so bank regulators are tuned in to these instruments.8

7

Stephen Franco and Timothy Klein provide an informative description of PC banking and other electronic
payments methods.
8

ment processors) each obtain almost 38 percent, and the
Federal Reserve System obtains less than 1 percent of
payments services revenues (from check clearing, check
return fees, Fedwire transfer services, and automated
clearing house services).

Of course, that’s not to say there aren’t issues that
must be dealt with: for example, how to best oversee the
development of third-party systems that intermediate
information between regulated counterparties; how to
prevent abuse and fraud; and how to handle the very
rapid development of technologies.
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BUSINESS REVIEW

MARCH/APRIL 2000

Other types of payment instruments are really new forms of payment. These new forms,
called electronic money or electronic cash, include stored-value cards, smart cards, and electronic purses or software-based money.9 Under
current regulation, these instruments can be offered by both banks and nonbanks. Electronic
money, or e-money, involves using traditional
money to purchase a claim on a merchant or
vendor, then trading this claim for goods and
services with merchants willing to accept the
claim.10 The claims can be stored on cards, called
stored-value cards, using either a magnetic strip,
as on a traditional credit card, or a computer
chip, which turns the stored-value card into a
smart card. Or the claims can be stored on the
customer’s PC, in an electronic purse or wallet,
and used to purchase goods over the Internet or
to pay anyone who has a similar type of account.
E-money was designed for small-value payments.
Often, an electronic money system is a closed
one in which the issuer of the claim is also the
merchant selling the good. For example, many
subways, telephone companies, and universities run closed systems, which are similar to the
traditional bank-based payment system. But
there can also be open systems. Cards in open
systems are usable in more locations and for
more types of goods, and such systems could, in
principle, operate independently of banks and
outside the traditional payments system. So long
as merchants were willing to accept the claims
and then were able to use the claims to purchase
the goods and services they themselves wanted,
the claims need not ever be redeemed for cash.

9

Karsten Schulz provides an informative description
and discussion of electronic money. See also the article
by Felix Stalder and Andrew Clement for an analysis of
the Mondex electronic money system.
10
See the U.S. Treasury, “An Introduction to Electronic Money Issues,” September 1996, for a nice overview of terms and issues.

6

FEDERAL RESERVE BANK OF PHILADELPHIA

The Changing Nature of the Payments System: Should New Players Mean New Rules?

Loretta J. Mester

They would constitute their own payments system, separate from the one that exists today.11
Unfortunately and surprisingly, there is no
one official source for data on U.S. payments
transactions.12 But data from several sources
suggest that the adoption of new forms of payments has been slow to date. Figure 2 and Table
1 present data on consumer payments for 1997
from The Nilson Report (www.nilsonreport.com)
in Oxnard, California, a newsletter covering consumer payment systems worldwide (Issue 680,
November 1998). As shown, although their usage grew between 1990 and 1997, stored-value
cards, debit cards, and preauthorized payments
accounted for only 6 percent of the number of
transactions made by consumers in 1997; in
terms of dollar value, they accounted for less than
5 percent. Cash and checks are still the favored
means of payment, followed by credit cards.13
Of course, even the traditional means of payment are becoming more electronic, although this

11

The Mondex electronic money system allows person-to-person (in addition to person-to-merchant) transfers of electronic money from one smart card to another.
12

I thank Bill Conant of Payment Technologies, Inc.,
Kathy Paese of the Federal Reserve Bank of St. Louis,
and Blake Prichard of the Federal Reserve Bank of Philadelphia for informing me about several data sources.
13
Checks are a relatively important means of payment in the U.S., Canada, the U.K., and France, but they
are much less important in other countries, including
Germany, Switzerland, and Belgium. According to figures from the Bank for International Settlements, checks
represented over 73 percent of the total number and over
10 percent of the value of all cashless transactions (both
retail and wholesale) in the U.S. in 1997. Comparable
figures for Canada are 36 percent and 97 percent; for the
U.K, 31 percent and 4 percent; for France, 42 percent and
4 percent; for Germany, 6 percent and 2 percent; for Switzerland, 1 percent and less than 1 percent; and for Belgium, 8 percent and 3 percent (Bank for International
Settlements, 1998). The 1999 study by the Bank for
International Settlements provides an informative overview and cross-country comparison of various means of
retail payments.

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BUSINESS REVIEW

MARCH/APRIL 2000

TABLE 1

Consumer Payments
1990
Method of Payment

1. Cashb
c

Dollar Value
(Billions)

% of Total
Dollar
Value

Number of
% of Total
Transactions Number of
(Billions)
Transactions

$ 579.32

19.5%

33.37

44.7%

$ 1822.05

Average
Size of
Transaction
$

17

$

65

61.3%

27.99

37.5%

3. Official Checksd

$

11.15

0.4%

0.09

0.1%

$ 124

4. Food Stamps

$

14.20

0.5%

0.88

1.2%

$

16

5. Money Orders

$

60.88

2.0%

0.89

1.2%

$

68

6. Traveler’s Checks

$

21.84

0.7%

0.41

0.5%

$

53

7. Credit Cards

$ 430.96

14.5%

10.37

13.9%

$

42

8. Debit Cards

$

11.74

0.4%

0.29

0.4%

$

40

9. Stored-Value Cards

$

0.00

0.0%

0.00

0.0%

$

0

2. Personal Checks

e

10. EBT Cards

$

0.01

0.0%

<0.01

0.0%

$

20

11. Preauthorzied Paymentsf

$

17.98

0.6%

0.29

0.4%

$

62

$

1.98

0.1%

0.02

0.0%

$

99

$ 2972.10

100.0%

74.59

100.0%

$

40

g

12. Remote Payments
a,h

13. Total

a

May not add up to sum of rows because of rounding.
Cash includes cash advances via credit or debit cards and personal checks written for the purpose of obtaining cash.
c
Personal checks include checks written to cover the receipt of goods and services; checks written to prepay or repay
another form of payment (e.g., to purchase money orders or to pay a credit card bill) are excluded from this category to
avoid duplication.
d
Official checks are cashier’s, teller, and certified checks.
e
EBT cards are electronic benefits cards that replace food stamps at participating merchants.
f
Preauthorized payments refer to payments that the consumer preauthorizes to be debited from his/her account and
are handled electronically through an automated clearing house.
b

might not be apparent to the consumer. For example, electronic check presentment (ECP) still
accounts for only a small portion of the checks
cleared annually, about 5 percent, but the volumes have been growing. Check conversion (also
called electronic checking) is also being developed. In this process, the consumer writes a
8

check to pay a merchant, who then uses a reader
to send the information on the check to an automated clearing house that transfers the funds.
The paper check is not routed to the paying bank
or cleared.14 Conversion is currently being used
for less than 1 percent of checks written at the
point-of-sale (which represent less than one-third
FEDERAL RESERVE BANK OF PHILADELPHIA

The Changing Nature of the Payments System: Should New Players Mean New Rules?

Loretta J. Mester

1997
Method of Payment

Dollar Value
(Billions)

1. Cashb

$
c

% of Total
Dollar
Value

Number of
Transactions
(Billions)

% of Total
Number of
Transactions

747.58

17.4%

37.42

40.8%

$ 2246.31

Average
Size of
Transaction
$

20

$

76

52.4%

29.67

32.3%

3. Official Checksd

$

18.85

0.4%

0.12

0.1%

$ 157

4. Food Stamps

$

14.64

0.3%

0.64

0.7%

$

23

5. Money Orders

$

99.01

2.3%

1.11

1.2%

$

89

6. Traveler’s Checks

$

20.20

0.5%

0.34

0.4%

$

59

7. Credit Cards

$

905.85

21.1%

16.51

18.0%

$

55

8. Debit Cards

$

119.14

2.8%

3.39

3.7%

$

35

9. Stored-Value Cards

$

5.91

0.1%

1.38

1.5%

$

4
23

2. Personal Checks

e

10. EBT Cards

$

4.08

0.1%

0.18

0.2%

$

11. Preauthorzied Paymentsf

$

86.55

2.0%

0.83

0.9%

$ 104

12. Remote Paymentsg

$

20.87

0.5%

0.21

0.2%

$

99

$ 4289.00

100.0%

91.80

100.0%

$

47

a,h

13. Total

g

Remote payments refer to payments made using telephone, on-line computer, the Internet, or ATMs.
The share of the dollar value of paper payment instruments, rows 1-6, decreased from 84.5% in 1990 to 75.2% in 1996
to 73.4% in 1997. The share of the value of payments made with cards, rows 7-10, increased from 14.8% in 1990 to 22.5%
in 1996 to 24.1% in 1997. The electronic bill payment share, rows 11 and 12, rose from 0.7% in 1990 to 2.3% in 1996 to 2.5%
in 1997.
h

Source: The Nilson Report (www.nilsonreport.com), a newsletter covering payment systems worldwide, Oxnard, California,
Issue 599, July 1995 and Issue 680, November 1998. Used with permission.

of all checks written). (See the article by Oria
O’Sullivan.)
14

Usually the consumer keeps the voided paper check,
but there is currently some debate about whether the
merchant or consumer should keep it. See the article by
Debra Janseen.

While more and more banks are offering some
form of electronic banking, and more and more
households are beginning to use these electronic
forms, the in-person visit is still the most common means of interacting with one’s bank, according to the 1995 Federal Reserve Survey of
Consumer Finances (SCF). This survey of more
9

BUSINESS REVIEW

MARCH/APRIL 2000

than 4000 households, designed to represent the
99 million households in the U.S., for the first
time in 1995 contained questions on the use of
electronic banking.15 Over 60 percent of households have an ATM card (Table 2), indicating
this form of electronic banking is now mainstream (although only about 25 percent of households that have a financial institution report this
as their main way of doing business with the
15
See the article by Arthur Kennickell, Martha StarrMcCluer, and Annika Sundé for a description of the survey. The paper by Arthur Kennickell and Myron Kwast
also uses the survey data to analyze the use of electronic
banking. The 1995 SCF survey data are available on the
web at www.bog.frb.fed.us/pubs/oss/oss2/95/
scf95home.html.

institution) (Table 3).16 As shown in Table 3, 75
percent of households say the main way they do
business with at least one of their financial institutions is in person. The data also show that
the use of various methods of dealing with one’s
financial institution differs by age, income, and
education. For example, very few households,
16
The survey indicates that over 93 percent of households have a relationship with at least one financial institution. Referring to each financial institution with which
the household does business, the survey asked: “How
do you mainly do business with this institution?” Respondents could list multiple methods, with the main
method listed first. The 25 percent refers to the number
of households that listed ATM first for at least one of
their financial institutions. If we include all the methods
respondents listed, ATM usage rises to 34 percent.

TABLE 2

Percent of U.S. Households That Use Each Instrumenta
ATMb
All Households
By Age:
Under 30 years old
Between 30 and 60 years old
Over 60 years old
By Incomec:
Low income
Moderate income
Middle income
Upper income
By Education
No college degree
College degree

Debit
Card

Direct
Deposit

Automatic
Bill Paying

Smart
Card

Any of
These

61.2%

17.6%

46.8%

21.8%

1.2%

76.5%

71.1%
67.2%
43.1%

24.5%
19.7%
9.6%

31.1%
42.9%
63.2%

17.9%
24.5%
18.2%

1.8%
1.5%
0.3%

75.2%
77.4%
75.2%

36.0%
60.1%
69.4%
76.6%

7.1%
16.0%
20.3%
25.0%

32.7%
43.1%
48.3%
58.3%

9.8%
17.7%
23.4%
32.0%

0.8%
0.6%
1.3%
1.8%

54.5%
77.0%
83.6%
89.1%

52.8%
80.1%

14.3%
25.2%

40.4%
61.0%

18.2%
30.1%

0.8%
2.1%

69.8%
91.5%

a
The percentages reported are based on the population-weighted figures. (For further discussion see the
Survey of Consumer Finances codebook at www.bog.frb.fed.us/pubs/oss/oss2/95/scf95home.html.)
b
The question on ATMs asked whether any member of the household had an ATM card, not whether the
member used it. The other questions asked about usage.
c

See note on Table 3

Source: 1995 Survey of Consumer Finances, Federal Reserve System.
10

update to table

FEDERAL RESERVE BANK OF PHILADELPHIA

The Changing Nature of the Payments System: Should New Players Mean New Rules?

about 1.75 percent, say that the computer is the
main way they deal with their financial institutions.17 But youth, high income, and a college
degree are associated with a higher incidence of
17

If we include households that listed computers as
one of the ways they mainly conduct business with at

Loretta J. Mester

computer banking. In fact, 7 percent of upper
income households where the head of household is less than 30 years old and has a college
least one of their financial institutions (although not necessarily as the main way), this percentage rises but, at
3.75 percent, is still small.

TABLE 3

Percent of U.S. Households With at Least One
Financial Institution Using Each Method
As the Main Way of Conducting Business With at Least One
Of Their Financial Institutionsa
In Person
All Households
By Age:
Under 30 years old
Between 30 and 60 years old
Over 60 years old
By Incomec:
Low income
Moderate income
Middle income
Upper income
By Education
No college degree
College degree

Phone

Computer Electronicb

Mail

ATM

75.1%

52.2%

24.6%

13.3%

1.7%

37.1%

64.6%
75.2%
79.9%

54.9%
57.2%
40.2%

39.2%
27.7%
11.2%

8.5%
14.5%
13.2%

2.9%
2.1%
0.4%

47.7%
41.3%
23.2%

73.7%
76.7%
74.6%
75.5%

28.4%
44.7%
52.4%
69.8%

13.7%
22.8%
27.2%
30.8%

4.8%
9.0%
11.0%
21.5%

0.7%
0.5%
1.9%
2.8%

19.3%
30.4%
40.0%
49.6%

76.9%
71.3%

45.5%
66.0%

19.6%
35.1%

8.9%
22.4%

1.3%
2.6%

29.1%
53.6%

a
Referring to each financial institution with which the household does business, the survey asked: “How do
you mainly do business with this institution?” Respondents could list multiple methods, with the main
method listed first. This table reports on the first method listed for each of the household’s financial institutions. The percentages reported are based on the population-weighted figures. Note, the percentages do not
add up to 100 percent across columns, since households could have more than one financial institution.
b

Electronic refers to ATM, phone, payroll deduction and direct deposit, electronic transfer, or computer.

c
Low income is defined as less than 50 percent of the median household income; moderate income is 50 to
80 percent of the median; middle income is 80 to 120 percent of the median; and upper income is greater than
120 percent of the median. Median income was $32,264 in 1994, the year to which the survey questions refer.
So, low income is less than $16,132; moderate income is $16,132 to $25,811; middle income is $25,811 to
$38,717; and upper income is over $38,717.

Source: 1995 Survey of Consumer Finances, Federal Reserve System.

update to table
11

BUSINESS REVIEW

degree report that the main way they deal with
their financial institution is by computer.18
Certainly, since 1995, when the SCF was conducted and the first Internet banking was offered,
the use of PC banking has increased, but it still
hasn’t taken off. According to the informationmarket research firm Dataquest, at the end of
1998, 7 percent of all households did some banking by PC.19 Dataquest’s March 1999 survey of
16,000 consumers suggests that over 5 percent
of U.S. adults view their account data on line,
3.75 percent transfer funds online, and 2 percent pay bills online (Bank Network News, 1999).
According to a PSI Global survey, small companies’ use of PC banking has risen over the last
few years from about 1 percent in 1996; but still,
in 1999, fewer than 10 percent of the respondents reported using it.20 According to the survey, about 200,000 small businesses currently
bank online.
One development that makes predictions of
double- or even triple-digit growth of PC banking more credible now than at any time in the
past is the growth of the Internet. Internet banking, one form of PC banking, offers customers
24-hour access and the ability to bank from multiple venues, since proprietary software need not
reside on each machine. According to estimates,
30 to 40 percent of all households access the
Internet now, and this number has been growing quickly.21 According to the Graphics, Visualization, and Usability (GVU) Center’s 1998 survey, over 90 percent of the Internet users surveyed are making purchases online and about
18
It’s important to remember that this group makes
up only 1.5 percent of all households.
19

As reported by Bill Orr, 1999a.

20

Reported in Future Banker, May 1999, p. 34. PSI
Global surveyed 900 financial decision-makers designed
to represent about 2.2 million small businesses overall,
including so-called small office and home office businesses. The survey had a margin of error of plus or
minus two percentage points.
12

MARCH/APRIL 2000

60 percent are also paying for the items over the
Internet most or all of the time. This indicates
that these buyers have some confidence in the
security of the Net for financial transactions.22
As people have gained confidence, more
banks have begun to offer Internet banking web
sites through which their customers can perform
transactions. One motivation is profit: data from
Fleet Boston Corp suggest that while its average
web-only customer generates less revenue than
its average customer who uses both the web and
branches, the web-only customer is half as costly
to service and, therefore, is a more profitable customer (Kutler, 1999b). Interesting findings by
Lorin Hitt and Frances Frei, based on case studies and customer data from four institutions,
suggest that users of PC banking tend to be more
profitable customers for the bank, but this is due
more to characteristics that existed before they
started using PC banking rather than the fee
structure, cost savings, or possible cross-selling
opportunities that PC banking affords the institution. In other words, users of PC banking tend
to be high-profit customers regardless of which
method of banking they choose.
A study by staff at the Office of the Comptroller of the Currency (Egland, Furst, Nolle, and
Robertson, December 1998) estimates that the
number of commercial-bank web sites through
which a customer can move or access funds more
than tripled in 1998; the number continued to
grow in 1999.23 According to the Wall Street Journal (May 10, 1999), Bank One announced it was
not planning any more major acquisitions but

21

As reported in Orr (1999a), Dataquest estimates
that 37 percent of households access the Internet. The
brokerage firm Piper Jaffray (in Franco and Klein) puts
the number at about 32 percent in 1998, rising to about
41 percent in 1999.
22

The GVU Center is located at Georgia Tech University. The 10th survey was conducted between October
and December 1998. There were 645 respondents to
questions about making purchases on the Internet.
FEDERAL RESERVE BANK OF PHILADELPHIA

The Changing Nature of the Payments System: Should New Players Mean New Rules?

now planned to concentrate on expanding via
the Internet. In June, it established the web bank
WingspanBank.com, an institution separate from
Bank One. In August, Citibank unveiled its web
bank and brokerage firm, Citi f/i.24 And, of
course, several banks have only a web presence
and no physical brick-and-mortar presence at
all, for example, NetB@nk.25
Consumers can pay bills electronically even
if they don’t have a PC. The SCF indicates that
in 1995, about 22 percent of households used
automatic bill-paying services, whereby the customer preauthorizes a debit from his or her account for regularly scheduled payments, such
as utility bills and mortgage payments; the transactions are cleared through an automated clearing house facility (Table 2). According to The
Nilson Report data (shown in Table 1), in 1997
these payments represented only 2 percent of
the dollar value of consumer payments, and
when payments authorized by telephone or over
the Internet are included, this percentage rises
only to 2.5 percent (up from 0.7 percent in 1990
and 2.3 percent in 1996). A recent survey of 2800
households by PSI Global found that 63 percent
of respondents felt sending payments through
23
While the number of such sites continued to grow in
1999, as of July 31, 1999, still less than 7 percent of
banks and thrifts offered transactional web sites (personal correspondence from the OCC).
24

The entry of these very large banks into the Internet
arena has caused North Fork Bancorp, New York, with
$11 billion in assets, to scale back its plans for a separate
Internet bank (see Senior).
25
A special problem that web banks have to solve is
how to deliver cash to their customers and how to accept
deposits. Some are allowing customers to access ATMs
without cost. Direct deposit can be used to make some
deposits, but in other cases, deposits have to be mailed
to the bank. So much for the electronic age! (See the
article by Rick Brooks for further discussion of the pros
and cons.) Bank of Montreal, with $144 billion in assets,
punted: it ended its web-only bank, mbanx, in August
1999, and gave mbanx customers access to physical
branches (see Power, 1999).

Loretta J. Mester

the mail was more secure and reliable than sending them electronically; 74 percent felt paper
checks offered more privacy; and 72 percent felt
that paper checks were more convenient (Souccar,
1999b).
Smart cards are another relatively new electronic payments instrument—at least in the
U.S.—and they have been slow to develop here.
As shown in Table 2, only 1.2 percent of households report using a smart card, that is, a card
including a computer chip on which financial
information, including value, may be stored.
(Again, the percentages using these cards are
higher for the younger, richer, and more educated.) This is consistent with reports that trials
of smart cards in various places in the U.S., including New York’s Upper West Side in 1997
and 1998, have not been very successful, as users have not found the cards more convenient
than cash or credit cards. A trial of a new smartcard technology in Canada by Bank of Montreal
and the Toronto Dominion Bank in 1997 also
saw extremely low usage of the card.26
About 85 percent of smart cards are deployed
in Europe, while only 1 percent have been issued in North America. According to data cited
in the American Banker, the U.S. was expected to
have 50 million smart cards in 1999, while Europe had 1 billion.27 Analysts project faster
growth in the U.S. over the next three years, but
even this would leave U.S. usage at just 10 percent of the total. One reason for the fast adoption abroad and the slow adoption in the U.S. is
that in the 1970s, when the first patents for smart
26
Christopher Plouffe, Mark Vandenbosch, and John
Hulland researched this trial and found that consumer
and merchant participants viewed the smart-card system as an additional way for the bank to charge fees,
rather than as a benefit to themselves; they were concerned about security of personal information; and they
found the processing time at the point-of-sale too slow.
27
Jeffrey Kutler (1999a) reported on a presentation by
MasterCard Vice President Michael Tempora, who cited
projections from the research firm Datamonitor.

13

BUSINESS REVIEW

cards were obtained, telephone lines were relatively scarce and expensive in Europe, which
meant that credit card authorizations were expensive in Europe and off-line transactions via
a smart card were advantageous. In the U.S., on
the other hand, the credit card took off, since it
was relatively cheaper than the smart card. Visa
and MasterCard are reported to be trying to expand usage of smart cards in the U.S. and
Canada. Visa is running a 450-card trial with
the federal government’s General Services Administration, with the smart cards issued by
Citibank. (See the article by Miriam Souccar,
1999a.) Hibernia National Bank is planning a
smart card trial in the first quarter of 2000; the
cards will be issued to its PC banking customers
so that they can access their accounts remotely
from various locations (Souccar, 1999c). Mondex
Canada Association ran a trial in Guelph with
some success and plans a further trial in
Sherbrooke, near Quebec. (See the paper by
Joanne DeLaurentiis.)
As with smart cards, electronic money systems in which customers have an electronic
purse or wallet on their PCs have been slow to
catch on. A three-year U.S. trial of eCash,
DigiCash’s electronic money that uses the
Internet, ended abruptly in September 1998;
DigiCash announced it was filing for Chapter
11 bankruptcy protection in November 1998
(Schulz). First Virtual Holdings has also left the
e-money business. (See the Tim Clark reference.)
Perhaps one reason demand for this type of emoney has been low is that as better security
software has been developed, people have become more comfortable using their credit cards
to pay for purchases over the Internet. And credit
cards are more convenient, since consumers
aren’t tied to particular computers that hold their
electronic purses to make purchases.
SLOW ADOPTION AT FIRST
MAKES ECONOMIC SENSE
Given all the publicity new payment instruments have received, it might seem surprising
14

MARCH/APRIL 2000

that the traditional methods are still the most
popular. Computer technologies mean that the
cost of processing an additional transaction using one of the new instruments is less than the
marginal operating cost of a transaction using
one of the older instruments. For example, according to a study by Booz, Allen & Hamilton, a
typical transaction over the Internet costs about
one cent, compared to 27 cents at an ATM, and
$1.07 at a teller window (Orr, 1999b). According
to an Ernst and Young study (as cited in Franco
and Klein), the average cost to the bank of handling a transaction via the Internet is about 26
cents versus 53 cents at an ATM, and 84 cents
using a telephone call center; an ACH deposit is
estimated to cost about 8 cents (Furst, Lang, and
Nolle, September 1998). Hence, electronic forms
of payment are potentially much more efficient
than paper-based and other traditional methods of payment.
But this does not mean the older instruments
will be quickly replaced. One reason is that the
new instruments require large expenditures for
computer systems and other fixed costs upfront,
before they can offer low additional costs per
customer served. The fixed costs mean that the
average cost of the new instrument can exceed
the average cost of an older instrument for some
time to come. Indeed, the 623 respondents in a
1998 survey by the Treasury Management Association (a professional association of treasury
and financial management executives in industry, government, and universities) cited the cost
of the technology and the need to integrate it
with existing financial systems as important
barriers to their organizations’ making more use
of electronic payments. These barriers were cited
even more often by those firms that, at the time of
the survey, could not initiate payments electronically. (See the study by Aaron Phillips.)
Network effects are also at work. Consumers’
acceptance of a new payment instrument depends on how many merchants accept it, and
merchants’ acceptance depends on the expectation of sufficient customer demand as well as
FEDERAL RESERVE BANK OF PHILADELPHIA

The Changing Nature of the Payments System: Should New Players Mean New Rules?

the decisions of competing merchants about
whether to adopt the new means of payment.28
And widespread adoption by consumers and
merchants depends on their confidence in the
medium’s safety and soundness.
How fast a payments instrument is adopted
also depends on how the risk, costs, and benefits of the new instrument are distributed
among participants. For example, David Barstow points out that the greater cost efficiency of
the government’s shift to electronic provision of
welfare payments and food stamps (electronic
benefits transfer) has yet to benefit the recipients
of such relief in New York.29 This certainly affects how recipients feel about using the new
electronic system compared to the old paperbased system, although they do not have a choice.
But other consumers do have a choice in their
payments method. The traditional payments instruments—cash and checks—are convenient
and work quite well from a consumer’s viewpoint.30
Until very recently, consumers have not explicitly paid for the costs of using checks (for
example, many accounts offered free check-writing privileges), and they receive the float—the
use of the money between the time the check is
written and the time the person’s account is ac28

In a 1999 study, Gautam Gowrisankaran and Joanna
Stavins present empirical evidence that network externalities exist in ACH processing. See also the article by
James McAndrews (1997).
29
In their study, Jeanne Hogarth and Kevin O’Donnell
examine the ways in which lower income households use
banking services and the implications of the government’s
move to electronic payment of welfare and benefits.

Loretta J. Mester

tually debited.31 Paying banks also benefit from
float. Consumers implicitly paid for check services by receiving lower rates on deposits or paying higher rates on loans, but the costs were not
apparent. This situation is changing as consumers are paying more explicit fees for banking services. It is still an unanswered question whether
the discrepancy between what a payor pays to
use a particular instrument (the private cost) and
the total production and processing costs of the
instrument (the social cost) can explain the continued dominance of paper checks.32
An alternative explanation is that users don’t
necessarily view checks and preauthorized bill
payments cleared through an automated clearing house as close substitutes. Checks give users more control over when to initiate a payment;
preauthorized payments are automatically debited or credited to a consumer’s account. Businesses can easily attach remittance information
to a check; for an ACH transaction they need
special software that allows financial electronic
data interchange (Wells).33 There are fixed costs
31

Of course, float can also hurt customers when they
are on the receiving end of a payment.
32
Studies include those by David Humphrey and Allen
Berger; Kirsten Wells; Joanna Stavins; and Jeffrey Lacker.
Using 1987 data, Humphrey and Berger found that the
private cost of a check was less than the social cost of an
ACH payment because of float. This difference encouraged the payor to choose to pay by check even though
the social cost of the check was greater than the social
cost of an ACH payment, making the check a less efficient means of payment. But using 1993 data, Wells
found that both the social cost and the private cost to the
payor of making an ACH payment were less than that of
writing a paper check. Based on these estimates, the
domination of checks remains a mystery.

30

According to the BAI/PSI Global study, approximately 40 percent ($45 million) of total revenue from the
payments business is generated from paper checks. This
revenue comprises bank fees associated with checking
account transactions and services, vendor revenues from
check processing systems and equipment sales, thirdparty service revenues, and bill-payment postage. Banks
get nearly half of this (about $21 billion).

33
According to the Treasury Management
Association’s survey, while over two-thirds of the 623
respondents had the ability to make or receive electronic
payments, fewer than 60 percent of these had the ability
to transmit or receive remittance information with the
payment (so-called electronic bill presentment and payment services).

15

BUSINESS REVIEW

involved and also a network externality—each
individual business takes into account only its
private benefit of joining an ACH network, but
the social benefits grow as more and more businesses join. So the market could be
underproviding electronic payments relative to
checks.
In any case, consumers and businesses have
been slow to adopt many of the new forms of
electronic payment, like smart cards, stored-value
cards, and electronic purses. Furthermore, these
methods have been designed for making mainly
small-value payments and are not likely to represent large dollar values of liabilities even if or
when fully adopted. For the time being, new
forms of electronic payment do not seem to be a
threat to the safety and soundness of the existing payments system.34 But they still deserve
monitoring. For example, they may expose individuals and institutions using them to substantial liability through fraud. (See What Are the
Risks?, page 25)
REGULATING NONBANK PROVIDERS
OF NEW FORMS OF PAYMENTS
The Federal Reserve works to ensure the integrity of the nation’s payments system. By and
large this is accomplished by prudential oversight of banks and by requirements imposed on
clearing arrangements that wish to use the Federal Reserve’s net settlement services. Nonbank

34

Moreover, at least in the near term, the new forms of
payment aren’t likely to have a large effect on the conduct of monetary policy. If use of these payment methods were to take off, the measured velocity of money
could be affected, but measures of money have become
less important in the conduct of monetary policy. The
Fed would adjust, as it has adjusted to previous financial innovations. New forms of payment could eventually reduce the demand for cash. This would reduce the
government’s income from seignorage, but the reduction
is likely to be inconsequential. Nevertheless, the monetary policy implications of electronic money are worth
contemplating. See Alan S. Blinder’s testimony for a
review of the issues from the Fed’s perspective.
16

MARCH/APRIL 2000

participation in the payments system is not new
(consider Western Union moneygrams and
American Express traveler’s checks). But to date,
nonbank participants represent only a small part
of the payments system. Given that the new instruments, like smart cards and other forms of
electronic money, are not expected to involve large
sums or represent a large part of total U.S. payments in the near future, permitting nonbanks
to compete in this market is unlikely to threaten
the dominant position of banks in the payments
arena in the near term.
Nonbanks are subject to some regulation.
Laws in 44 states regulate nonbanks that issue
physical stores of value, for example, traveler’s
checks or money orders. Some require 100 percent reserves, minimum capital levels, licensing,
bonding, and periodic examinations and audits.
The laws might also cover, or be amended to
cover, issuers of electronic money. In addition,
the Federal Reserve has some authority to regulate new forms of electronic payments used by
consumers under Regulation E. This regulation
implements the Electronic Funds Transfer Act
and includes provisions to protect consumers
when they use electronic payments. Nonbank
issuers of smart cards and other forms of electronic money fall under the regulatory purview
of the Federal Reserve with respect to this consumer protection regulation. Other relevant
forms of regulatory authority over electronic
forms of payment are laws that relate to reserve
requirements, deposit insurance, privacy, consumer protection, access, and antitrust.35

35

Under current U.S. law, stored-value cards, smart
cards, and e-wallets are being viewed as liabilities but
not deposits, thus allowing nonbanks to issue these instruments. Whether they will continue to be viewed this
way as they develop and, therefore, whether nonbanks
will continue to be able to offer them is unclear. Also, if
a depository institution issues stored-value cards, it’s
possible the balances on those cards would be treated as
deposits in the future. (Currently, the Fed does not consider these balances to be deposits if the card does not
FEDERAL RESERVE BANK OF PHILADELPHIA

The Changing Nature of the Payments System: Should New Players Mean New Rules?

Nonbank competitors are not automatically
covered by the federal regulatory system for ensuring the safety and soundness of the payments
system. Hence, it is still an open question as to
whether the Federal Reserve or any other regulator enjoys adequate authority to protect the
payments system in a world where nonbanks
play a much larger role in retail clearing arrangements. Although new payments methods
haven’t taken off yet, the adoption rate of new
forms of payment, as with many new technologies, is likely to be slow at first and then accelerate. Regulators like the Fed need to continue to
track these new forms of payment even if none
seems dominant today.
In terms of how to treat these new types of
payment instruments, at least three regulatory
approaches are possible, each with pros and
cons. One approach would be to allow all types
of firms to issue new forms of payment instruments. Such laissez-faire would encourage innovation and allow the market to develop, but
the failure of an issuer might lead to a loss of
confidence in electronic systems from which it
might be difficult to recover. Another approach
would be to allow only banks to issue new payment instruments like smart cards.36 The bank

access a deposit account.) In other words, there is the
possibility of disparate treatment between bank and nonbank issuers. This is not unprecedented: traveler’s checks
issued by banks are subject to reserve requirements and
are covered by deposit insurance, but those issued by
nonbanks are not. (Note, however, that many states
require nonbank issuers to hold ample reserves against
the instruments they issue.) In another case, as cited in a
study by the Congressional Budget Office, the FDIC issued an unpublished advisory opinion (Oct. 20, 1995)
that granted passthrough deposit insurance to the customers of an institution that issues electronic scrip. This
opinion was based, in part, on the grounds that the issuer of the electronic scrip holds the funds as an agent
for the owners of the funds. The marketing literature for
DigiCash’s system of online scrip, on the other hand,
stated that it was equivalent to cash rather than a deposit.

Loretta J. Mester

regulatory system already in place could then
be used by regulators to oversee electronic-payment instruments. But this might limit competition and stifle innovation. A third approach
would be to allow a variety of different kinds of
firms to issue electronic money but only with
prior regulatory approval. Regulators could then
impose a greater regulatory burden on issuers
and systems that pose greater risk to the payments system as a whole. Disclosure requirements and perhaps restrictions on the portfolios
of electronic-money issuers (similar in spirit, for
example, to those on money market mutual
funds) could be part of this “light-handed” regulatory approach.
Which regulatory regime is best depends on
the tradeoff between having a very secure but
perhaps less efficient payments system today
versus allowing for innovation to enhance the
efficiency and security of tomorrow’s payments
system. While heavy regulation might mean a
more secure system today (although this is debatable), it would likely stifle any innovation
undertaken by private-sector participants in the
payments system. This could mean a less secure and less efficient system in the future. But
some type of regulatory oversight is desirable.
The success of a new form of payment depends
on its being adopted by large numbers of consumers and merchants, and this adoption depends on consumers and merchants having confidence in the safety and effectiveness of the system. Light-handed regulation can foster their
confidence. Even nonbank issuers might find
some regulation useful, since the failure of a large
nonbank provider because of inadequate oversight could set back the ultimate adoption of the

36

The European Central Bank recommends that all
issuers of electronic money be subject to prudential supervision, that multi-use smart cards be treated as deposits, and that these cards and other forms of electronic
money be issued only by credit institutions (see European Central Bank, August 1998).
17

BUSINESS REVIEW

new payment instruments—users of new payment instruments have long memories. The PCbanking systems in the 1980s were so slow that
consumers were turned off, and it was very difficult to get them to try PC banking again once the
technology improved.37
Another benefit of the light-handed approach
is that it recognizes that we still don’t know
which new payment instruments and which
technologies will turn out to be the best. Lighthanded regulation offers a better chance for various technologies and different forms of instruments to compete until the best types win out.
Since it is unclear which instruments will survive the market test, it makes sense to avoid setting up a regulatory scheme based on how the
system looks today, since it could look quite different in the future. In a speech, Vice Chairman
Ferguson discussed the benefits of a lighthanded approach (see Ferguson, 1998).
THE FEDERAL RESERVE
AS A SERVICE PROVIDER
The Fed needs to ensure a well-functioning
wholesale (that is, large dollar, interbank) payments system to support economic growth. To
this end, it provides the Fedwire funds transfer
system to ensure final settlement of interbank
payments, and it offers net settlement services
for payments cleared outside the Fed. But the
Federal Reserve is also directly involved in providing retail payments services, in particular,
check and ACH services. Together, the Federal
Reserve Banks are the largest ACH operator and
process about three-fourths of interbank ACH
transactions, including all ACH transactions
initiated by the federal government. (The main
private-sector ACH operators are the New York
Clearing House [now called Electronic Payments
Network], Visa, and the American Clearing

37
See Frances Frei and Ravi Kalakota for an interesting discussion of the history of PC banking and current
developments.

18

MARCH/APRIL 2000

House.) The Federal Reserve also clears about
one-third of interbank checks collected in the U.S.
Federal Reserve Board Vice Chairman
Ferguson has pointed out that the rationale for
the Fed’s involvement in the check business
stems from the early 1900s when checks were
used to make interbank wholesale transfers.
Today, the Fed’s involvement in retail payments
is aimed at facilitating competition, guaranteeing universal access to the payments system, and
exerting some influence on developments in retail payments (Ferguson, 1998). For example,
the Fed is the “provider of last resort.” That is, it
provides payments services such as check clearing in any area underserved by the commercial
sector. As such, the Fed can influence the market by promoting efficiency and ensuring access.
In 1997, the Fed undertook a study to determine whether it should remain a provider of retail payment services and to see what role it
should play, given the electronic developments
taking place. Senior Federal Reserve officials,
the so-called Rivlin Committee, held meetings
with various participants in the retail payments
system, both users and providers of these services, and issued a final report in January 1998
(“The Federal Reserve in the Payments Mechanism”).
The study found that most participants want
the Fed to continue to provide check and ACH
services. Many participants questioned whether
private-sector suppliers would meet the needs
of all depository institutions, especially small
ones in remote areas. Thus, one of the study’s
major conclusions was that the Fed “should remain a provider of both check collection and
ACH services with the explicit goal of enhancing the efficiency, effectiveness, and convenience
of both systems, while ensuring access for all
depository institutions.”
Another of the study’s major conclusions was
that the Fed should play a more active role, working closely with providers and users of the payments system, to help new, more efficient payment instruments evolve. The Fed would enFEDERAL RESERVE BANK OF PHILADELPHIA

The Changing Nature of the Payments System: Should New Players Mean New Rules?

courage participants to communicate with one
another. It would also encourage changing regulations and laws to allow the emerging payment
instruments to evolve, rather than promote any
particular payment method.38
For example, the Fed could play a role in helping to clarify some legal issues regarding electronic forms of payment, which would help facilitate their adoption. It is still not clear when
these payment instruments are considered deposits, and what the potential liabilities, rights,
and responsibilities of issuers, merchants, and
consumers are. For example, under the Uniform
Commercial Code, a set of laws that govern commercial and financial activities, presentment of
checks for payment by the electronic transmission of information is allowed, but paying banks
still have the legal right to insist on paper presentment (U.S. General Accounting Office, p. 4).
Also, some states still require banks to offer canceled checks to their customers. According to
the GAO’s reading of a 1997 Boston Fed survey,
41 states plus the District of Columbia had at
least one law or regulation that required individuals or organizations to retain their canceled
checks for various purposes, including documentation for state and local governments.39
These types of laws hinder the adoption of electronic check presentment. Legal ambiguities
surround other new payment instruments as
well.40 For example, if an issuer were to become

38

The results of the Treasury Management
Association’s survey suggest that government can play
an important role in fostering the move to electronic payments: federal mandates, followed by state mandates,
were the dominant factors cited by the 544 respondents
with electronic payment capability in their decision to
originally adopt it.
39

My canceled check, with the city’s account information stamped on the back, saved the day when I had to
prove I’d paid a city tax.
40

Two bills introduced in the House during the last
Congress attempted to clarify some of the legal issues

Loretta J. Mester

bankrupt or insolvent, what would be the status
of the claim represented by a balance on a smart
card?41
The Fed could also help facilitate standardsetting in the electronic payments industry.
Having a set of standards that all current and
potential providers follow will solve a problem
of coordination and, thus, encourage faster adoption. One reason the Internet has been so successful and has developed so quickly is that it is
based on a common standard that is widely available. Standards also help a payment method
achieve a volume sufficiently large to attain the
benefits of network effects. The value of a new
payment instrument depends on how many others adopt it. If compatibility standards can be
agreed on, there’s greater potential that more
consumers and merchants will use the instrument, making it more attractive, and leading to
even wider adoption. There is a risk, however,
that the wrong set of standards will be adopted,
which could retard developments. Hence, analysis should be done before a particular set of standards is settled upon.
The Fed has been modestly proactive in setting standards in areas where it is a direct provider. For example, the Fed has implemented an
enhanced net settlement service, set new risk
management guidelines, promoted electronic
check imaging and presentment, and undertaken

about the use of electronic signatures, one component of
making electronic payments. HR 1714, the Electronic
Signatures in Global and National Commerce Act, sought
to extend U.S.-style electronic signature policy overseas
and to recognize electronic signatures as legally valid,
even though they aren’t in the traditional written form.
This bill narrowly failed in the House on November 1,
1999. HR 1685, the Internet Growth and Development
Act of 1999, proposed recognizing electronic signatures
in interstate and foreign commerce.
41

With credit cards, if the issuing bank fails, the credit
card association guarantees payment to merchants with
outstanding transactions and then has a creditor’s claim
on the failed bank.
19

BUSINESS REVIEW

an electronic checks initiative. Since the Fed does
not have any more relevant expertise than others in the area of new types of electronic payment instruments, the Fed may not want to set
standards for technology in this area. It may,
however, want to be involved in setting guidelines pertaining to security and risk management
with these new instruments.
The Fed’s study also recommended that the
Fed work with other participants in the retail
payments system to assess the potential use of
the Fed’s electronic payments infrastructure for
clearing or settling new forms of electronic retail
payments to help spur their growth. The report,
however, did not recommend that the Fed become a direct provider of new electronic payment instruments. As Governor Ferguson has
stated, a rationale for the Fed’s being a provider
of these new payment instruments would be the
existence of some type of market failure, which
would mean that the private sector was unable
or unwilling to provide these services. There is
insufficient evidence that this is true today. Further, it is not clear which payment instruments
will ultimately be best—the market will have to
decide. Thus, rather than provide these payment instruments directly, the Fed intends to
work toward creating an environment that fosters the development of more efficient electronic
payment instruments in the private sector.
This decision is not without consequences. It
means that over time, if new electronic forms of
payment become dominant, the Fed will no
longer be a major provider of payment services.
So it will lose one of the mechanisms through
which it can influence the safety and efficiency

20

MARCH/APRIL 2000

of the payments system. For example, currently,
the Fed is the dominant provider of ACH and
net settlement services, and it sets conditions that
must be met by all participants. These conditions help ensure safety and soundness of the
system. If the Fed loses market share, its conditions for participation become less relevant. It is
still an open question about how important the
loss of this mechanism for influencing the market is. The Fed would still retain the authority to
oversee and regulate, as necessary, the payments
system.
CONCLUSION
Electronic instruments for making payments
are developing, some more quickly than others,
and nonbanks are beginning to become payment
providers. Does this necessarily mean that the
rules must change? No. The Fed will continue
to monitor developments in the payments system to help ensure its safety and soundness. The
Fed has some authority to regulate certain aspects of electronic payments. Moreover, the Fed
will remain a provider of its traditional services
of ACH and check clearing. At this point, the
Fed is not planning to become a provider of ecash or other new electronic payment instruments, but it will work to foster an environment
to encourage a move toward more efficient electronic payment instruments. This might include
helping the private sector develop standards to
facilitate coordination among providers and
users of the payments system and helping to
clarify some of the legal issues surrounding new
means of payment.

FEDERAL RESERVE BANK OF PHILADELPHIA

The Changing Nature of the Payments System: Should New Players Mean New Rules?

Loretta J. Mester

REFERENCES
BAI/PSI Global. Profiting from Change in the U.S. Payments System. Chicago: Bank Administration
Institute, 1998.
Bank for International Settlements (BIS). “Statistics on Payment Systems in the Group of Ten Countries,” December 1998, www.bis.org/publ/index.htm (Committee on Payment and Settlement
Systems).
Bank for International Settlements (BIS). “Retail Payments in Selected Countries: A Comparative
Study,” September 1999, www.bis.org/publ/index.htm (Committee on Payment and Settlement
Systems).
Barstow, David. “A.T.M. Cards Fail to Live Up to Promises,” New York Times, August 16, 1999.
Blinder, Alan S. “Statement before the Subcommittee on Domestic and International Monetary Policy
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Electronic Payment Technologies,” October 1995.
Brooks, Rick. “Bank One’s Strategy as Competition Grows: New, Online Institution,” Wall Street
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Bruce, R. Christian. “Electronic Commerce Consumers Want Repudiation Power in Electronic Commerce, Expert Says,” BNA Banking Daily, June 9, 1999.
Cahill, Joseph B. “Acquisitive Bank One Turns Its Back on Takeovers, Pins Hopes on Internet,” Wall
Street Journal, May 10, 1999.
Clark, Tim. “DigiCash Files Chapter 11,” CNET News.com, November 4, 1998.
Congressional Budget Office (CBO). “Emerging Electronic Methods for Making Retail Payments,”
June 1996.
DeLaurentiis, Joanne. “A Mondex Case Study: Results from the Guelph, Canada Implementation,”
Payment Systems Worldwide, Spring 1999, pp. 11-14.
Egland, Kori L., Karen Furst, Daniel E. Nolle, and Douglas Robertson. “Banking Over the Internet,”
Office of the Comptroller of the Currency, Quarterly Journal 17 (December 1998), pp. 25-30.
European Central Bank. “Report on Electronic Money,” April 1998, www.ecb.int/pub/pdf/emoney.pdf.
“The Federal Reserve in the Payments Mechanism,” Committee on the Federal Reserve in the Payments Mechanism, Federal Reserve System, January 1998 (the Rivlin Committee Report),
www.bog.frb.fed.us/boarddocs/press/General/1998/19980105/19980105.pdf.
Ferguson, Jr., Roger W. “The Federal Reserve’s Role in the Payments System and Its Effect on Competition,” Remarks before the Bankers Roundtable, Phoenix, Arizona (April 4, 1998),
www.bog.frb.fed.us/boarddocs/speeches/1998/19980404.htm.

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MARCH/APRIL 2000

REFERENCES (continued)
Franco, Stephen C., and Timothy M. Klein. “1999 Online Banking Report: The Fog Is Lifting,” Piper
Jaffray Equity Research, February 1999, www.ecinvestor.com/archive/onlinebanking0299.pdf.
Frei, Frances, and Ravi Kalakota, “Frontiers of Online Financial Services,” in M. J. Cronin, ed., Banking
and Finance on the Internet. New York: Van Nostrand Reinhold Press, 1997.
Furst, Karen, William W. Lang, and Daniel E. Nolle. “Technological Innovation in Banking and Payments: Industry Trends and Implications for Banks,” Office of the Comptroller of the Currency,
Quarterly Journal 17 (September 1998), pp. 23-31.
Gowrisankaran, Gautam, and Joanna Stavins. “Are There Network Externalities in Electronic Payments?” Federal Reserve Bank of Boston, manuscript presented at the Federal Reserve Bank of
Chicago Conference on Bank Structure and Competition (May 1999).
Graphics, Visualization, and Usability Center (GVU). “Results of GVU’s Tenth World Wide Web User
Survey,” Georgia Tech University, May 14, 1999, www.gvu.gatech.edu/user_surveys/ survey1998-10/tenthreport.html.
Hitt, Lorin M., and Frances X. Frei. “Do Better Customers Utilize Electronic Distribution Channels?
The Case of PC Banking,” Working Paper 99-21, Wharton Financial Institutions Center (April
1999).
Hogarth, Jeanne M., and Kevin H. O’Donnell. “Banking Relationships of Lower-Income Families and
the Governmental Trend Toward Electronic Payment,” Federal Reserve Bulletin 85 (July 1999), pp.
459-73.
Humphrey, David B., and Allen N. Berger. “Market Failure and Resource Use: Economic Incentives to
Use Different Payment Instruments,” in D.B. Humphrey, ed., Efficiency, Risk and the Role of the
Federal Reserve: Proceeding of a Symposium on the U.S. Payment System Sponsored by the Federal Reserve
Bank of Richmond. Boston: Clair Academic Publishers, 1990, pp. 87-92.
Janseen, Debra. “Comment: Electronic-Checking Question—Who Gets the Voided Check?” American
Banker, September 24, 1999.
Kennickell, Arthur B., and Myron L. Kwast. “Who Uses Electronic Banking? Results from the 1995
Survey of Consumer Finance,” Finance and Economics Discussion Series Paper 1997-35, Board of
Governors of the Federal Reserve System (July 1997).
Kennickell, Arthur B., Martha Starr-McCluer, and Annika E. Sundé. “Family Finances in the U.S.:
Recent Evidence from the Survey of Consumer Finances,” Federal Reserve Bulletin 83 (January
1997), pp. 1-24.
Kimelman, John. “Oh, What a Tangled Web: Cyberfraud Sullies Internet, Real Banks Strive for OnLine Credibility,” American Banker, July 1, 1999.

22

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The Changing Nature of the Payments System: Should New Players Mean New Rules?

Loretta J. Mester

REFERENCES (continued)
Kutler, Jeffrey. “Reporter’s Notebook: Smart Cards Put on Hot Seat at Conference,” American Banker,
May 21, 1999a.
Kutler, Jeffrey. “Two Senior Execs Call Web Most Profitable Channel,” American Banker, October 6,
1999b.
Lacker, Jeffrey M. “The Check Float Puzzle,” Federal Reserve Bank of Richmond Economic Quarterly
83(3) (Summer 1997), pp. 1-25.
McAndrews, James J. “Network Issues and Payment Systems,” Federal Reserve Bank of Philadelphia
Business Review (November/December 1997), pp. 15-25.
McAndrews, James J. “E-Money and Payment System Risk,” Contemporary Economic Policy 17 (July
1999), pp. 348-357.
The Nilson Report (www.nilsonreport.com). Issue 599 (July 1995) and Issue 680 (November 1998).
Orr, Bill. “At Last Internet Banking Takes Off,” ABA Banking Journal (July 1999a), p. 36.
Orr, Bill. “E-banks or E-branches? Both Are in Play as Early Adopters Make Them Work,” ABA
Banking Journal (July 1999b), pp. 32-34.
O’Sullivan, Oria. “When a Check Is Not a Check,” USBanker (July 1999), pp. 43-47.
Phillips, Aaron L. “Migration of Corporate Payments from Check to Electronic Format: A Report on
the Current Status of Payments,” Financial Management 27 (Winter 1998), pp. 92-105.
Plouffe, Christopher R., Mark Vandenbosch, and John Hulland. “The Ongoing Failure of Smart Cards
in North America: A Case Study,” Future Banker (August 1999), p. 42.
Power, Carol. “Web Bank Pioneer May Lead Way—Back to Branches,” American Banker, November
17, 1999.
Radecki, Lawrence J. “Banks’ Payments-Driven Revenues,” Economic Policy Review 5 (July 1999),
pp. 53-70.
Roberds, William. “The Impact of Fraud on New Methods of Retail Payment,” Federal Reserve Bank
of Atlanta Economic Review (First Quarter 1998), pp. 42-52.
Schulz, Karsten. “The Future of Digital Cash,” Banking Policy Report, 18 (August 1999), pp. 8-13.
Senior, Adriana. “Branding, Money Concerns Halt a Web-Only Plan,” American Banker, October 27,
1999.

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MARCH/APRIL 2000

REFERENCES (continued)
Souccar, Miriam Kreinin. “Visa, MasterCard Step Up Push for Smart Cards,” American Banker, May 17,
1999a.
Souccar, Miriam Kreinin. “Survey: People Favor Paper for Paying Off Their Plastic,” American Banker,
July 13, 1999b.
Souccar, Miriam Kreinin. “Smart Cards: Hibernia Plans Customer Card Trial in 1Q,” American Banker,
October 20, 1999c.
Stalder, Felix, and Andrew Clement. “Exploring Policy Issues of Electronic Cash: The Mondex Case,”
Information Policy Research Program, Faculty of Information Studies, University of Toronto,
Working Paper 8 (July 1998), www.fis.utoronto.ca/research/iprp/dipcii/workpap8.htm.
Stavins, Joanna. “A Comparison of Social Costs and Benefits of Paper Check Presentment and ECP
with Truncation,” Federal Reserve Bank of Boston New England Economic Review (July/August
1997), pp. 27-44.
Sweeney, Paul. “Cyber-Crime’s Looming Threat,” Banking Strategies (July/August 1999), pp. 54-59.
U. S. General Accounting Office. “Experience with Electronic Check Presentment,” GAO/GGD-98-145
(July 1998).
U.S. Treasury. “An Introduction to Electronic Money Issues,” September 1996.
Wells, Kirstin E. “Are Checks Overused?” Federal Reserve Bank of Minnesota Quarterly Review 20(4)
(Fall 1996), pp. 2-12.

24

FEDERAL RESERVE BANK OF PHILADELPHIA

The Changing Nature of the Payments System: Should New Players Mean New Rules?

Loretta J. Mester

What Are the Risks?
New forms of retail payments, like traditional payment methods, involve some risks. Fraud and
counterfeiting are probably the most significant risks in using the new instruments, at least in the short
run.a Even though each transaction in the wholesale market is much larger, it is easier to make the
wholesale payments system secure than it is the electronic retail system, because the wholesale
market involves a relatively small number of participants. The electronic security of the Internet, of
internal or closed payment networks, and of new instruments is difficult to ensure, and breaches
have occurred. Kimelman, in the American Banker, reports on a “bank” that took in $6 million from
customers over the Internet in 1997 and 1998, with the intent to defraud. Off-line transactions, like
those initiated by smart cards, are more difficult to monitor for fraud than on-line transactions. There
is a risk the card can be counterfeited and the value erroneously transferred or replicated. Ensuring
security of credit card information over the Internet is complex, since packets of information can pass
through many different computers, each one accessible to a large number of people, before reaching
its final destination. Also, a dishonest bill-paying outfit can abscond with customers’ money.
Concerns about fraud can slow the adoption of electronic payment methods. Regulators and
bank officials interviewed by the GAO indicated that one thing that might deter banks from moving
to electronic check presentment (ECP) was their feeling that ECP had higher potential for fraud
because in their view it was more difficult to detect forged signatures than with paper checks (U.S.
General Accounting Office).b
Some estimates show a higher incidence of fraud for credit cards, an electronic means of payment,
than for checks. According to William Roberds, while annual losses due to credit card fraud are small
compared with losses due to check fraud, as a percent of the dollar value of transactions, credit card
losses are higher than check losses.c He estimates that in 1995, the incidence of loss on credit cards
was about 10 to 20 basis points; the loss on checks was less than 2 basis points. To date, the losses from
breaches of organizations’ computer systems for the purpose of committing financial fraud have not
been very large. Sweeney reports that in a 1999 Computer Securities Institute survey of 521 organizations, including corporations, financial institutions, universities, and government agencies, 27 respondents reported break-ins into their computer systems for the purposes of executing financial
fraud, which resulted in $39.7 million in losses. However, there are concerns that the proliferation of
computers and electronic payment instruments will make financial fraud much more common.
Methods are being developed to try to contain fraud. Digital signatures or public-key technology
can allow users to know whether they have gotten to a financial institution’s true web site. Digital

a
See the article by William Roberds for a thorough analysis of potential fraud in the use of new retail
payment instruments. See also the article by James McAndrews (1999), which discusses e-money and risks
to the payments system.
b
But some argue that because of the speed that electronic check and bill presentment brings to the check
collection process, it may enhance security by reducing float and, therefore, the uncertainty about receiving a
payment (see Sweeney).
c
Roberds reports estimates of gross fraud losses in the U.S. on credit cards of $2-3 billion in 1993 and $1.3
billion in 1995. Estimates of gross fraud losses on checks range as high as $10 billion (with banks’ share of
these losses amounting to $615 million in 1995, according to a survey by the Federal Reserve). Gross losses
do not include any recoveries made of lost funds.

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MARCH/APRIL 2000

What Are the Risks? (continued)
encryption is built into smart cards and software-based money. Encryption provides a higher level of
security than magnetic strips on credit cards. But because it is very cheap to duplicate cards, any
security breach could result in large losses to an institution. Limits on the amount of value that can be
put on a card or on the size of a transaction could help limit this risk. Security methods involving
biometrics are also being developed, for example, smart cards with built-in fingerprint scanners (see
Bruce) or iris scanners. However, existing biometrics can be unreliable: some rely on hand geometry,
but according to Jim Wayman, director of the U.S. National Biometric Center, about six out of 1000
people have the same hand characteristics. Also, as he demonstrated at a conference, the best available systems were unable to recognize that two sets of fingerprints were from the same person: the
prints were taken just six weeks apart but under different conditions (Bruce).
A second risk involves potential for criminal activity (which is closely related to fraud). While not a
new risk, the new modes of payment make it more likely that criminal organizations will be able to
evade regulations aimed at curtailing their payment transactions. For example, a smart card is easier
to conceal than a large volume of currency.
Liquidity, market, and settlement risk are additional risks. In a world of large international capital
flows, the possibility of a problem spreading from one country’s payment system to another and then
another, until payment systems worldwide are affected, creates a potential for crisis in electronic
payment networks, particularly for large-value clearing arrangements. Systemic risk arising from
clearing retail payments is relatively small. In general, systemic risk is greatest when the value of
settlements represents a significant share of participating institutions’ capital or when the gross value
of transactions is much larger than the net amounts to be settled. Most clearing arrangements for
retail payments do not involve settlement values that are a significant share of an institution’s capital.
There is some room for caution, however, because most small-value clearing arrangements have less
sophisticated risk controls than do the large-value clearing arrangements.
Operational risk also needs to be considered. At least initially, problems with errors, reliability, and
compatibility of systems should be expected. But if the problems are large enough, they could deter
adoption of new and better technologies. The initial tries at PC banking left a bad taste in consumers’
mouths. Also, electronic bill-payment services currently have a higher error rate and are more costly
to the recipients of the payments than traditional check payments, partly because of the difficulties of
sending remittance information along with the payment (Franco and Klein, p. 16). Technologies are
being developed to help solve this problem.

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From Cycles to Shocks: Progress in Business-Cycle Theory

Satyajit Chatterjee

From Cycles to Shocks: Progress in
Business-Cycle Theory
Satyajit Chatterjee*

E

arly analysts of business cycles believed that
each cyclical phase of the economy carries within
it the seed that generates the next cyclical phase.
A boom generates the next recession; that recession generates the next boom; and the economy
is caught forever in a self-sustaining cycle. In
contrast, modern theories of business cycles attribute cyclical fluctuations to the cumulative
effects of shocks and disturbances that continually buffet the economy. In other words, without
shocks there are no cycles.

*Satyajit Chatterjee is an economic advisor in the Research Department of the Philadelphia Fed.

The evolution of thought about business
cycles from an emphasis on self-sustaining behavior toward one in which random shocks take
center stage is a significant development in macroeconomics, and it is an especially important
one for policymaking institutions like the Federal Reserve. The view that cycles are self-sustaining implies that a market economy cannot
deliver stable economic performance on a sustained basis. Generally speaking, this view
points to aggressive countercyclical policies or
institutional reform as the appropriate response
to cyclical fluctuations.
In contrast, the view that shocks are the ultimate sources of business cycles does not point
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to a particular policy stance. Whether a
countercyclical policy should be pursued depends on the nature of the shocks. If shocks can
be eliminated, macroeconomic policy should
endeavor to do so because a more stable economic environment is preferable to a less stable
one. But if shocks cannot be eliminated, it may
be in the long-run interests of society to adapt to
the shocks. To the extent that countercyclical
policies interfere with the necessary adaptations,
they may do more harm than good.1
Not surprisingly, the shift of professional
opinion toward the shock-based view of business cycles has been accompanied by increasing debate about the sources of cyclical volatility. Few macroeconomists doubt that random
shocks underlie business cycles, but they have
been unable to agree on which random shocks,
historically, have been the main causes of cyclical volatility.
To a person not versed in business-cycle
theory (including economists who are not macroeconomists), this situation must seem somewhat
paradoxical: How can macroeconomists be certain that shocks cause cycles, yet not agree on
which shocks are responsible for cyclical volatility? Moreover, if a person is told that despite this
ignorance, macroeconomists have made great
strides in understanding business cycles, his or
her perplexity can only increase. How can there
be any understanding of business cycles (let
alone an improvement in it!) if economists don’t
know the causes of cyclical volatility?
This article will answer these questions by
sketching the historical evolution of the shockbased theory of business cycles. The answer to
the first question delineates the key discoveries
that led macroeconomists away from the self1

For instance, a boom in residential construction could
reflect speculative excess or changing demographics. An
increase in the interest rate can eliminate speculation,
but it cannot change demographics. Thus, policy action
is desirable in the former case but probably not in the
latter.
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MARCH/APRIL 2000

sustaining view of business cycles and toward
the shock-based view. The impetus for the shockbased view of business cycles came in the 1920s
when mathematicians made a major breakthrough in the statistical description of cyclical
phenomena. They established that many kinds
of irregular cyclical phenomena (in fields as diverse as economics, geology, and physics) are
best explained by random shocks.
This discovery set economists on the search
for a shock-based theory of business cycles. Initially, economists thought that observable random events, such as an unexpected increase in
government spending or a financial panic, would
turn out to be the shocks causing business cycles.
And to some extent they are. But they are not the
major source of cyclical volatility. The major
source appears to be shocks that manifest themselves as deviations of macroeconomic variables
from their model-predicted values. Such shocks
cannot easily be connected to observable realworld events. The unobservable nature of these
shocks is the fundamental reason macroeconomists disagree about the ultimate causes of cyclical fluctuations. Yet, most macroeconomists
agree that some set of unspecified shocks must
be ultimately responsible for business cycles.
Although macroeconomists lack firm knowledge about the ultimate sources of cyclical volatility, they do understand how these shocks, once
they occur, contribute to business cycles. Thus,
the answer to the second question is that advances in business-cycle theory have provided
a better understanding of how industrial economies respond to random shocks. One outcome
of these developments is a new appreciation of
the role that erratic changes in business-sector
productivity play in cyclical fluctuations. According to the real business cycle, or RBC, theory
(arguably one of the most successful shockbased business-cycle theories to date), random
variation in business-sector productivity is the
key proximate cause of post-WWII U.S. business
cycles.
Let’s now examine the historical process by
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From Cycles to Shocks: Progress in Business-Cycle Theory

which business-cycle theorists have come to this
conclusion.
THE STATISTICAL THEORY
OF RANDOM WAVES
The fact that random disturbances may underlie business cycles was clearly demonstrated
by the Russian statistician and economist Eugen
Slutzky. In an article published in Russian in
1927 (and reprinted in English in
1937), Slutzky described in compelling
detail how chance events could generate cyclical movements in economic
data.2
Slutzky began with a series of many
random numbers, each an integer between 0 and 9. If such numbers are
plotted on a graph, they produce a line
that moves up and down without displaying any particular pattern (Figure
1). This simply reflects the fact that the
numbers, being drawn at random,
don’t bear any relationship to each
other. Next, Slutzky constructed a new
series by adding the random numbers
10 at a time in the following way. The
first number in the new series was the
sum of the first 10 random numbers;
the second number in the new series
was the sum of the second through
the 11th random number, and so on.
Thus, each member of the new series
was a 10-item sum of random numbers. In the new series, the difference
in value between adjacent members
could be at most nine, but the difference between widely separated mem-

Satyajit Chatterjee

bers could be much larger.
Slutzky recognized that this combination of
facts—adjacent members of the series are likely
to be similar in value, and widely separated
members are unlikely to be similar in value—
implies wavelike, or cyclical, movement. Indeed,
when plotted as a graph, the 10-item moving
sums of the random numbers shown in Figure 1
display an unmistakable wavelike pattern (Fig-

2
Priority of discovery is attributed to the
British statistician G. Udny Yule, who made
this point in the early 1920s. However,
Slutzky went much further than Yule in showing how random shocks could lead to apparently cyclical movements in economic (and
other) data.

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BUSINESS REVIEW

ure 2). While widely separated members of the
series may be quite different in value, such as
members A and B, the movement from A to B
must be gradual because adjacent members of
the series cannot be too different from each other.
To persuade his readers that random numbers
may underlie business-cycle movements,
Slutzky compared a segment of his 10-item moving-sum series to an index of English business
cycles. As we can see in Figure 3, the similarity
is indeed remarkable!
Following Slutzky’s pioneering work, mathematicians further developed the statistical
theory of random waves. This development revealed that Slutzky’s random-number-based
explanation of irregular cyclical patterns was,
in fact, the most compelling explanation of such
patterns. This discovery persuaded businesscycle theorists to seek an explanation of business cycles in the cumulative effects of various
random shocks hitting the economic system.

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MARCH/APRIL 2000

THE GENESIS OF SHOCK-BASED
BUSINESS-CYCLE THEORY
Although Slutzky showed that moving sums
of random numbers could display businesscycle-like patterns, he didn’t provide any economic theory as to why macroeconomic variables
might behave like moving sums of random numbers. However, he did point to examples of mechanical systems, such as a pendulum, whose
motion under the influence of random shocks
was, mathematically, a moving (weighted) sum
of random numbers.
Imagine tapping with a hammer a pendulum
whose motion is hampered by friction. If the hammer strokes vary randomly in strength, they’ll
cause the pendulum to swing about in an irregular way. A time-plot of the displacement of
the pendulum from its (vertical) resting position
(with displacement to the right measured as positive numbers and to the left as negative numbers) will show an irregular wavy line. The key

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From Cycles to Shocks: Progress in Business-Cycle Theory

point is that mathematically (and experimentally!), the displacement of the pendulum at any
given point in time is a weighted moving sum of
random numbers, the random numbers being
the strength of each hammer stroke up to that
point in time.
In an article published in 1933, the Norwegian economist and Nobel laureate Ragnar Frisch
described a simple macroeconomic model in
which the evolution of output, investment, and
consumer spending resembled the motion of a
swinging pendulum. Frisch’s model implied
that if some transient random event raised output above the economy’s normal level, all macroeconomic variables (output, investment, and
consumer spending) returned to normal in a cyclical fashion. In other words, the initial periods
of above-normal economic activity (analogous
to displacements of the pendulum to the right)
were followed by periods of below-normal economic activity (analogous to displacements to
the left). These swings in economic activity
gradually diminished in strength and eventually died.
Frisch didn’t work out the behavior of his
model economy for a sequence of random shocks,
but the analogy to the swinging pendulum suggested that the resulting behavior would resemble that of business cycles. In any event, by
adopting the swinging pendulum as an analogy for the evolution of a capitalistic economy,
Frisch took a step back from the prevailing view
that business cycles were self-sustaining. Recall
that without the hammer strokes, the force of friction brings the pendulum eventually to rest. And
so it is, claimed Frisch, with an economic system: without shocks, there are no cycles.
Still, by basing his economic model of business cycles on an analogy to a swinging pendulum, Frisch gave inherently cyclical behavior (i.e.,
pendulum-like movements) a prominent place
in business-cycle theory. However, the influence
of the pendulum in business-cycle theory received a severe setback when Irma and Frank
Adelman published an article in 1959 showing

Satyajit Chatterjee

that shocks, rather than pendulum-like movements, lie at the center of cyclical volatility.
THE DEMISE OF THE PENDULUM
AND THE RISE OF SHOCKS
By the mid-1950s, advances in econometrics
(the use of statistical methods to determine quantitative economic relationships from economic
data) had progressed to the point where equations describing various sectors of the economy
could be inferred from economic data. The KleinGoldberger model of the U.S. economy was one
such model.3 It contained 25 equations describing the evolution of 25 macroeconomic variables
for the U.S. economy and was much more detailed than the simple economic model used by
Frisch.
The question that the Adelmans asked was
whether the Klein-Goldberger model could generate business cycles. First, they simulated the
model on a computer to see if it displayed inherently cyclical behavior. They found that the model
did not display appreciable pendulum-like movements. If some small to moderate transient shock
temporarily raised economic activity, most economic variables simply returned to normal without experiencing any periods of below-normal
activity.4
Next, the Adelmans turned to assessing the
role of shocks in cyclical fluctuations. The first
type of shock they considered was one affecting
observable causal factors. In the KleinGoldberger model, the list of observable causal
factors included changes in short-term and long-

3

The model was developed by Lawrence Klein and
Arthur Goldberger, two well-respected econometricians
(Klein received the Nobel Prize in economics in 1980).
The model is described in their book published in 1955.
4
In their simulations of the Klein-Goldberger model,
the Adelmans did find pendulum-like behavior for very
large shocks to the economic system. But these shocks
were much larger than those actually observed for the
U.S. economy.

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BUSINESS REVIEW

term interest rates, an index of hours worked by
those employed, government employee compensation and government expenditures, agricultural exports and agricultural subsidies, and
population and labor-force variables. The
Adelmans noted that these causal factors didn’t
evolve steadily but tended to jump around their
respective trend paths “more or less erratically.”
The Adelmans treated these erratic movements
in causal factors as random shocks and simulated the Klein-Goldberger model to see how
macroeconomic variables behaved in response
to such shocks. They found that these shocks
didn’t “produce the sort of cyclical behavior observed in the actual economy.” Thus, shocks to
observable causal factors did not seem to be responsible for business cycles, either.
The Adelmans then turned to a second type
of random shock: the random discrepancies between the predictions of the Klein-Goldberger
model and the actual values of macroeconomic
variables. These discrepancies arise for several
reasons, the most important being that any macroeconomic model is likely to omit some relevant
factors. For instance, the Klein-Goldberger equation for predicting consumer spending takes into
account only the influence of income; the stock
of liquid assets (cash as well as checking and
savings accounts) held by people; population;
and consumer spending from the previous year.
It ignores any effects resulting from, say, shifts
in the distribution of personal income. If a shift
in the distribution of personal income is an important factor in some year, that shift will contribute to the discrepancy between the predictions of the model and the actual value of consumer spending for that year. Macroeconomists
refer to such deviations of model-predicted values from actual values as residuals.
When the Adelmans treated the residuals of
the Klein-Goldberger model as random shocks,
they found that the behavior of macroeconomic
variables in the Klein-Goldberger model closely
resembled actual U.S. business cycles. In other
words, they found that residuals were the prime
6

MARCH/APRIL 2000

source of cyclical volatility!
These results were counter to prevailing views
about the role of shocks in cyclical volatility.
Recall that Frisch and his contemporaries believed that business cycles resulted from observable shocks impinging on an economy prone to
pendulum-like movements. But the Adelmans
found that business cycles resulted from unexplained shocks (i.e., residuals) impinging on an
economy that displayed no strong tendency toward pendulum-like movement.
Why does the Klein-Goldberger model generate business cycles even without any strong tendency to pendulum-like movement? The answer
lies in the fact that in the Klein-Goldberger model,
values of macroeconomic variables are determined, in part, by moving sums of random numbers. For instance, the Klein-Goldberger equation for consumer spending holds that the level
of consumer spending during the previous year
has a positive influence on consumer spending
in the current year. Thus, if some shock raised
consumer spending in the past year, that same
shock will raise consumer spending during the
current year as well, although not by as much.
By the same logic, a shock that raised consumer
spending two years ago will also have raised
consumer spending during the past year (again,
not by as much) and, therefore, will raise it during the current year as well. In other words, since
consumer spending in any year is affected by
consumer spending in the previous year, consumer spending in any year is determined, in
part, by a weighted sum of random shocks affecting consumer spending in all previous years.
Now recall Slutzky’s demonstration that a
quantity that’s a moving sum of random numbers will display wavelike movement. Thus, in
the presence of random shocks, the link between
consumer spending in consecutive years becomes a source of wavelike movements in consumer expenditures.
Most modern macroeconomic models incorporate links between consecutive values of macroeconomic variables. These links imply that
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From Cycles to Shocks: Progress in Business-Cycle Theory

values of macroeconomic variables are determined, in part, by moving sums of random numbers, and those random numbers are past unexplained shocks to macroeconomic variables, i.e.,
past residuals.5 Thus, while it’s true that macroeconomists don’t know which factors cause business cycles, they do understand how the changes
brought about by those factors combine to generate cyclical fluctuations.6
Nevertheless, the fact that residuals cause
business cycles is unsettling for business-cycle
theory. Macroeconomists would prefer to explain business cycles in terms of observable
shocks or, failing that, to develop theories that
make minimal use of residuals.
THE POWER OF RESIDUALS
Since the 1960s, the evolution of businesscycle thought has been linked to theoretical developments in economics in general. In particular, advances in dynamic economic theory provided new and powerful tools for tackling problems in business-cycle research. Initially, these
new ideas held out hope of reducing the importance of omitted factors in business-cycle models and correspondingly raising that of included
factors. Consequently, professional attention

5

In principle, random shocks to observable causal
factors can also be a source of wavelike movements.
However, the shocks to observed causal factors are too
small to generate realistic business-cycle fluctuations in
the Klein-Goldberger model.

Satyajit Chatterjee

turned to re-assessing the role of factors included
in business-cycle models. A great deal of energy
was spent in assessing the role of monetary
shocks. As it turned out, this assessment failed
to produce a compelling case for monetary
shocks as an important factor in postwar U.S.
business cycles. It also failed to produce compelling evidence in favor of other easily identifiable shocks.7 Since the early 1980s, interest has
again shifted to consideration of the role of residuals in cyclical fluctuations. Armed with the
new advances in dynamic economic theory, Finn
Kydland in collaboration with Edward Prescott
developed a residual-driven business-cycle
model called the real business cycle (RBC)
model.8
Recall that a residual is the deviation of a
macroeconomic variable from its model-predicted value. In RBC theory, the residual that
generates business cycles is the quarterly deviation of labor productivity from its model-predicted value. The model of labor productivity
used in RBC theory was developed by growth
theorists in the 1940s and 1950s. This model
holds that average labor productivity (output per
worker) is positively related to the amount of
capital per worker in the economy. The difference between growth in actual labor productivity and its model-predicted value is called the
Solow residual, in honor of Nobel laureate Robert Solow, who developed this idea. A positive
Solow residual, i.e., growth in labor productivity in excess of what can be explained by growth
in capital per worker, indicates an improvement

6

For evidence on the importance of residuals for cyclical volatility in modern macroeconomic models, see John
Cochrane’s article. Can the omitted factors be discovered by relating residuals to observable historical events?
Perhaps, but scholars are not sanguine about the prospects. To quote the eminent economic historian Peter
Temin: “If the goal is to find events that can be represented by the residuals, it may be possible to find events
to explain one set of residuals as easily as another. But
the variety of models extant today makes that kind of
exercise unrealistic as a way to identify causes of multiple cycles.”

7

Pre-WWII fluctuations are another matter. In that
case, monetary shocks may well have been the decisive
factor.
8

Prescott’s 1986 article contains an influential statement of the RBC model. The antecedents of this article
appeared in an earlier 1982 publication by Finn Kydland
and Edward Prescott. Two other authors, John Long
and Charles Plosser, published a closely related article in
1983; they coined the term real business cycles.
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BUSINESS REVIEW

in the economy’s technological capability
(brought on by new inventions). In the theory of
economic growth, positive Solow residuals are
seen as a major cause of economic growth; in
RBC theory, fluctuations in the Solow residual
are seen as a major cause of business cycles.9
Two properties of the Solow residual make it
possible to base a business-cycle theory on it.
First, when the Solow residual rises above its
trend path, indicating better-than-average
growth in the economy’s technological capability, firms are motivated to invest in new plant
and equipment at a faster-than-average rate. To
meet the increased demand for investment goods,
businesses hire more than the average number
of workers. Above-average employment growth
leads, in turn, to faster-than-average growth in
consumer spending. Thus, a rise in the Solow
residual above its trend path makes investment,
employment, and consumer spending rise above
their respective trend paths as well. This comovement of key macroeconomic variables is a
central feature of business cycles.
Second, as was the case with consumer spending in the Klein-Goldberger model, there is a
strong link between the value of the Solow residual in consecutive years. Therefore, the value
of the residual in any given year is determined,
in part, by a weighted sum of random shocks
affecting the residual in past years. Thus, the
observed movements of the Solow residual
around its trend path resemble Slutzky’s moving sums of random numbers. Since RBC theory
predicts that macroeconomic variables will take
on values that are almost proportional to the
Solow residual, all macroeconomic variables in
the RBC model behave like moving sums of random numbers as well. Thus, RBC theory can also
explain the observed wavelike movement of
macroeconomic variables.

9

For a detailed description of the RBC model and
some of its implications, see my 1995 and 1999 articles.
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MARCH/APRIL 2000

RBC theory has had considerable success in
explaining cyclical fluctuations. As shown in
Charles Plosser’s 1989 article, values predicted
by RBC theory (given the observed movements
in the Solow residual) are close to the actual values of key macroeconomic variables during the
post-WWII period. For instance, as predicted by
the theory, a decline in consumer expenditures,
hours worked, investment, and output accompanied the decline in the Solow residual in 1970.
More recently, the faster-than-average growth of
the U.S. economy since 1995 has accompanied a
faster-than-average growth in the Solow residual. Between 1995 and 1997 (the last year for
which the residual can be calculated), the growth
in the Solow residual exceeded its average
growth rate since 1959 by more than 15 percent.
Still, a natural question to ask about the RBC
model is whether it offers a more satisfactory
explanation of business cycles than the one offered by the Adelmans using the KleinGoldberger model. After all, given that both explanations are residual-based, are there any reasons to prefer one to the other?
Quantitatively, the RBC model explains cyclical fluctuations at least as well as the KleinGoldberger model, as Robert King and Charles
Plosser demonstrated in a 1994 article. However,
many macroeconomists prefer the RBC explanation for two reasons. First, RBC theory relies
on only one residual to generate business cycles
whereas the Adelmans relied on a consumer
spending residual, an investment residual, and
other assorted residuals. Second, the RBC model
is based on straightforward economic ideas
whereas the theory underlying the KleinGoldberger model is much more complex and
subtle.
WHITHER BUSINESS-CYCLE THEORY?
The pioneers of RBC theory have steadfastly
maintained that fluctuations in the Solow residual result from technological and institutional changes. Generally speaking, businesscycle theorists don’t view their job as explaining
FEDERAL RESERVE BANK OF PHILADELPHIA

From Cycles to Shocks: Progress in Business-Cycle Theory

changes in technology or institutions. So, if the
omitted factors that cause fluctuations in the
Solow residual are truly technological or institutional in nature, then in one important sense,
RBC theory is complete. The phenomenon left
unexplained, namely, fluctuations in the Solow
residual, falls outside the scope of business-cycle
theory and therefore doesn’t need to be explained
by it. The intellectual journey begun in 1927 on
the pages of an obscure Russian journal has
come to an end!
But has it really? Economists, after all, are a
curious lot. Confronted with a residual that can
explain business cycles, they will want to dig
deeper into its ultimate causes. One reason researchers are motivated to dig deeper is that some
aspects of the Solow residual seem inconsistent
with the assertion that only technological or institutional changes cause the residual to fluctuate. For instance, during recessions, the residual
usually declines. The strict RBC interpretation
would hold that some factor caused a decline in
the productive potential of the economy and led
to the recession. In some cases such an interpretation seems plausible (as it does for the decline
in the Solow residual during the energy crisis in
1974). However, in other cases (for instance, in
1970) the reason for the decline is not clear. Most
macroeconomists find declines in the Solow residual during recessions puzzling, although
many now believe the declines are real and not
simply the consequence of measurement error.
The future development of shock-based theories of business cycles is almost certainly going
to be influenced, in part, by attempts to resolve
such puzzles. Indeed, both critics and proponents of RBC theory have focused increasingly
on the reasons why the Solow residual fluctuates.
For instance, critics of RBC theory have proposed models in which the Solow residual moves
in response to cyclical fluctuations caused by
unexplained shifts in investment or consumer
spending. In these models, a higher rate of production enables businesses to produce at a lower

Satyajit Chatterjee

unit cost, which implies that the Solow residual
rises during booms and falls during recessions.
These induced changes in the Solow residual
magnify the effects of the initial change in investment or consumer spending and may lead
to excessive cyclical volatility.10
On the other hand, proponents of RBC theory
point to evidence from U.S. manufacturing plants
that seems to indicate that technological change
is an important determinant of fluctuations in
the Solow residual. If new plants adopt technological improvements, RBC theory predicts that
such improvements will induce old and obsolete plants to cease production. As the new technology comes into use, both the Solow residual
and national output will rise. U.S. data show
that, as theory predicts, plant closings precede
increases in the Solow residual. Then, as the
Solow residual rises, new plants open and national output increases.11
As research on RBC theory progresses, we may
expect it to shed light on the questions that vex
policymakers. Is there a policy trade-off between
the rate of economic growth and its cyclical volatility? How can policy contribute to reducing
cyclical volatility? What role do existing
countercyclical policies play in promoting economic growth and reducing cyclical volatility?
It is to the credit of shock-based business-cycle
theories, and to the RBC theory in particular, that
progress on these traditional policy concerns can
now be made by learning about the factors that
underlie fluctuations in the Solow residual.
SUMMARY
Early analysts of business cycles believed that
cyclical fluctuations are self-sustaining. But in

10

See, for instance, the article by Marianne Baxter and
Robert King and the article by Roger Farmer and JangTing Guo.
11

This theory is described in Jeffrey Campbell’s ar-

ticle.
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BUSINESS REVIEW

MARCH/APRIL 2000

the 1920s, statisticians and economists realized
that business cycles could result from purely
random causes. This discovery moved economists away from the self-sustaining view of business cycles and toward a shock-based view. The
first shock-based business-cycle model gave
prominence to both random shocks and inherently cyclical behavior as sources of business
cycles. But later research demonstrated that
shocks were the major source of cyclical fluctuations.
However, these shocks turned out to be peculiar in nature in that they couldn’t easily be connected to observable real-world events. They
appeared, instead, as deviations of macroeconomic variables from their model-predicted values (i.e., residuals). Then, in the early 1980s, a
group of economists greatly refined shock-based
(more precisely, residual-based) business-cycle
theories by linking cyclical fluctuations to deviations in labor productivity, the so-called Solow
residual. Using the advances made in dynamic
economic theory in the 1960s and 1970s, these

economists demonstrated that fluctuations in the
Solow residual were powerful enough to generate fluctuations in output that closely resembled
post-WWII U.S. business cycles. This remarkable
demonstration strengthened the links between
business-cycle theory and simple microeconomic
principles and reduced the number of residuals
from several to just one. For both reasons, RBC
theory represents a significant improvement over
first-generation shock-based theories.
Nevertheless, RBC theory doesn’t settle the
issue of the ultimate sources of cyclical volatility
because the random shocks in the RBC model
result from variations in unspecified factors that
cause erratic movements in business-sector productivity. However, by focusing attention on the
role of the Solow residual in cyclical fluctuations,
RBC theory has laid a foundation for better understanding the causes of such fluctuations. As
business-cycle researchers look for reasons why
the Solow residual fluctuates, they may gain
knowledge that will help policymakers fashion
better macroeconomic policies.

REFERENCES
Adelman, Irma, and Frank Adelman. “The Dynamic Properties of the Klein-Goldberger Model,”
Econometrica, 4 (1959), pp. 596-625.
Baxter, Marianne, and Robert G. King. “Productive Externalities and Business Cycles,” Discussion Paper 53, Institute of Empirical Macroeconomics, Federal Reserve Bank of Minneapolis, 1991.
Campbell, Jeffrey R. “Entry, Exit, Embodied Technology, and Business Cycles,” Review of
Economic Dynamics, 1 (1998), pp. 371-408.
Chatterjee, Satyajit. “Productivity Growth and the American Business Cycle,” Business Review, Federal Reserve Bank of Philadelphia, September/October 1995.

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From Cycles to Shocks: Progress in Business-Cycle Theory

Satyajit Chatterjee

REFERENCES (continued)
Chatterjee, Satyajit. “Real Business Cycles: A Legacy of Countercyclical Policies?” Business
Review, Federal Reserve Bank of Philadelphia, January/February 1999.
Cochrane, John. “Shocks,” Carnegie-Rochester Conference Series on Public Policy, 41 (1994), pp.
295-364.
Farmer, Roger E.A., and Jang-Ting Guo. “Real Business Cycles and the Animal Spirits Hypothesis,” Journal of Economic Theory, 63 (1994), pp. 42-72.
Frisch, Ragnar. “Propagation Problems and Impulse Problems in Dynamic
Economics,”Economic Essays in Honor of Gustav Cassel. London: George Allen & Unwin,
1933.
King, Robert G., and Charles I. Plosser. “Real Business Cycles and the Test of the Adelmans,”
Journal of Monetary Economics, 33 (1994), pp. 405-38.
Klein, Lawrence J., and Arthur S. Goldberger. An Econometric Model of the United States, 19291952. Amsterdam: 1955.
Kydland, Finn, and Edward C. Prescott. “Time-to-Build and Aggregate Fluctuations,”
Econometrica, 50 (1982), pp. 1345-70.
Long, John, and Charles I. Plosser. “Real Business Cycles,” Journal of Political Economy, 91
(1983), pp. 1345-70.
Plosser, Charles I. “Understanding Real Business Cycles,” Journal of Economic Perspectives, 3
(1989), pp. 51-77.
Prescott, Edward C. “Theory Ahead of Business Cycle Measurement,” Federal Reserve Bank
of Minneapolis Quarterly Review 10 (1986), pp. 9-21.
Slutzky, Eugen. “The Summation of Random Causes as the Source of Cyclic Processes,”
Econometrica, 5 (1937), pp.19-60.
Solow, Robert M. “Technical Change and Aggregate Production Function,” Review of Economics and Statistics, 39 (1957), pp. 312-20.
Temin, Peter. “The Causes of American Business Cycles: An Essay in Economic Historiography,” in Jeffrey Fuhrer and Scott Schuh, eds., Beyond Shocks: What Causes Business Cycles?
Federal Reserve Bank of Boston, 1998.

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