Full text of Economic Review (Federal Reserve Bank of Atlanta) : First Quarter 1998, Volume 83, Number 1

View original document

The full text on this page is automatically extracted from the file linked above and may contain errors and inconsistencies.

Policy Credibility and the
Design of Central Banks
R O B E R T O C H A N G
The author is a research officer in the macropolicy
section of the Atlanta Fed’s research department. He
thanks Jerry Dwyer, Adam Posen, Will Roberds, and
Mary Rosenbaum for useful suggestions.

N RECENT YEARS THE PRACTICE OF CENTRAL BANKING AROUND THE WORLD HAS BEEN PROFOUNDLY
AFFECTED BY TWO TRENDS.

THE

FIRST IS TOWARD GRANTING CENTRAL BANKS GREATER INDEPEN-

DENCE VIS-À-VIS OTHER BRANCHES OF THEIR GOVERNMENTS.

THE

BRITISH

GOVERNMENT’S

MAY 1997

THIS TREND IS CLEARLY EXPRESSED IN

MOVE GRANTING THE

BANK

SET SHORT-TERM INTEREST RATES. IT IS ALSO EVIDENT IN THE CURRENT
SINGLE CURRENCY: THE

AUTHORITY, THE

1992 TREATY

MAASTRICHT

ENGLAND

THE POWER TO

EUROPEAN UNION’S PLAN FOR A

PRESCRIBES THE CREATION OF A MONETARY

EUROPEAN SYSTEM OF CENTRAL BANKS (ESCB), THAT WOULD BE FORMALLY INDEPEN-

DENT OF ANY OTHER

EUROPEAN

COUNTRIES, INCLUDING

GOVERNMENT OR INSTITUTION.1 IN ADDITION, MANY

LATIN AMERICAN

MEXICO, ARGENTINA, CHILE, AND PERU, HAVE ENHANCED THE INDEPENDENCE OF

THEIR CENTRAL BANKS IN THE CONTEXT OF BROAD STRUCTURAL REFORMS.

SOUTH AFRICA’S

POSTAPARTHEID GOVERNMENT ALSO AGREED TO AN INDEPENDENT MONETARY AUTHORITY.2

The second trend influencing the nature of central
banking is for countries to formally state that a central
bank’s sole objective should be to ensure price stability.
New Zealand, for example, in its Reserve Bank Act of
1989, stated that the Bank’s monetary policy should be
“directed to the economic objective of achieving and
maintaining stability in the general level of prices.”3
Likewise, Article 105 of the Maastricht Treaty establishes that “the primary objective of the ESCB shall be to
maintain price stability.” The Bank of Canada and some
other central banks are now bound to follow formal
inflation targets. In many other countries there is considerable debate about whether their monetary policy
should be exclusively geared toward attaining zero
inflation.4

These two trends have an underlying unity: they can
be seen as social responses to a more fundamental problem of central bank credibility called the time inconsistency of monetary policy. To aid in understanding this
connection, this article discusses the nature of the time
inconsistency problem and its economic implications.
The theory of time inconsistency stresses that monetary authorities are often tempted to promise low inflation now and to try to surprise the public with
unexpectedly higher inflation later. However, such
promises will not be believed because economic agents,
understanding the authorities’ incentives, realize that
the promises will not be honored. Instead, economically
plausible outcomes have the property that monetary
authorities are not able to systematically surprise the

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W First Quarter 1998

public. As this discussion will show, this property implies
that the monetary authority cannot profit from reneging
on its announcements. In fact, it can only lose by doing
so: expected and realized inflation will often be higher
than if the monetary authorities had made a binding
promise. This consequence is known as inflation bias.
This article explains how the creation of some
institutions can be interpreted as social responses to
time inconsistency. A society may try to ameliorate
inflation bias by providing appropriate incentives for its
monetary authorities to adhere to promises; institutional arrangements may be designed to reduce the gains to
the authorities from creating unexpected inflation. One
approach is to structure the compensation of central
bankers so as to punish them if inflation is outside some
target range, as in New Zealand. Alternatively, a society
may try to constrain the policy instruments available to
the monetary authorities in order to make engineering
inflation surprises more difficult. A country’s commitment to fix its exchange rate can be understood in this
way. For either approach to work, it is necessary that
the monetary authorities be insulated from the rest of
the government. Hence central bank independence
emerges as a necessary condition for institutional solutions to time inconsistency.
Further theoretical analyses imply that such institutional mechanisms may not be necessary, however. In
particular, because monetary authorities are typically
engaged in a long-term relationship with the public,
they can develop a reputation for honoring commitments. The fear of losing a reputation for future “honesty” is an important incentive that may deter a central
bank from “cheating” today. Recent studies have shown
that this incentive may be powerful enough to make
socially optimal outcomes attainable, even in the
absence of any institutional constraints.
Institutional approaches and reputational concerns are both plausible solutions to the time inconsistency problem, and both have weaknesses according to
existing theory. To aid in understanding their relative
merits, this article discusses related empirical work.
Empirical studies have largely focused on testing the
hypothesis that the central banks that are more independent deliver lower inflation. Evidence favoring that
hypothesis has been analyzed in several studies focusing on developed countries. However, it will be seen that
the relationship between central bank independence
and inflation seems fragile, and it does not hold for less
developed countries.
1.
2.
3.
4.

Although the empirical findings provide little support that central bank independence helps lower inflation,
it is too early to discard existing theory. According to the
theory, central bank independence is only one aspect
of institutional solutions to inflation bias. It cannot by itself eliminate inflation bias, so its emergence will not necessarily yield lower inflation. In addition, reputation-based
approaches imply that inflation bias may be addressed
by noninstitutional means; hence, low inflation need not
require central bank independence. Both arguments imply that there
need not be a negative
relation between central
A trend influencing the
bank independence and
nature of central banking
inflation even if current
theory is valid.
is for countries to formally

An Economic Theory
of Credibility

state that a central bank’s
sole objective should be to
ensure price stability.

lthough the role
of credibility in
monetary policy
has been recognized for
a very long time, modern research on credibility started only in the late 1970s with the publication
of seminal papers by Calvo (1978) and Kydland and
Prescott (1977). These two papers showed that the
then-novel hypothesis of rational expectations had profound implications for the credibility of macroeconomic
policy in general and monetary policy in particular.
Before focusing on these implications, it may be helpful
to illustrate the basic nature of Calvo’s and Kydland and
Prescott’s ideas with a simple example.
The example is about a fictional father, Federico, and
his adolescent son, Pablo, at the start of some week. Pablo
is at that age when he dislikes hard work and loves to be
extravagant. Federico wants to teach Pablo the value of
hard work, of course, and to that end he has convinced
the neighbors to let Pablo mow their lawn for money.
Federico’s problem is that he cannot force Pablo to do the
job. Instead, Pablo must be induced to mow the lawn, and
the way to convince him is to allow him to get a tattoo in
exchange for his effort. Federico would like to prevent
Pablo from being tattooed, although this objective is not
as important to him as inducing Pablo to mow the neighbors’ lawn. Federico would rather have Pablo mow the
neighbors’ lawn and use the corresponding payment to

See specifically Article 107 of the Maastricht Treaty.
See “Role Shifts for Central Bankers,” in the New York Times, November 15, 1994, sec. D.
Section 8, Reserve Bank of New Zealand Act of 1989, quoted in Walsh (1995b).
For debate about U.S. policy, see, for instance, “A Matter of Demeanor,” Wall Street Journal, May 20, 1994, sec. A, and “Time
for an Economic Summit,” Wall Street Journal, September 28, 1994, sec. A.
Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W First Quarter 1998

pay for, say, a good book. The prospect of reading a good
book is not enough to induce Pablo to do the lawn, though.
To make the example interesting, assume that the
neighbors, mindful of Federico’s dilemma, will give the
money to Federico and not Pablo. Finally, let us push the
fictional nature of the example and assume that it is the
only interaction that Federico and Pablo will have.
What is the likely outcome of this father-son example?
Federico cannot convince Pablo to mow the neighbors’
lawn without promising
him a tattoo. It seems
that it should be enough
for Federico to tell Pablo,
“If you mow the neighA society may try to
bors’ lawn, you will be
constrain the policy
allowed to use their payinstruments available
ment for whatever you
want.” If Pablo believes
to the monetary authorthis offer and Federico
ities in order to make
honors his word, then
engineering inflation
Pablo will mow the lawn,
get the money, and run to
surprises more difficult.
the tattoo shop.
However, after Pablo
mows the lawn, it is no
longer in Federico’s interest to allow Pablo to be tattooed. Hence, instead of giving
the lawn-mowing money to Pablo, Federico will go to a
bookstore and buy Pablo a good book. Then he will just tell
Pablo, “Sorry, Son, a tattoo will leave an indelible mark on
your body, and I cannot let you have one. Here is a good
book for your effort.” By breaking his promise in this fashion, Federico would have obtained his most preferred outcome: he will have induced Pablo to mow the neighbors’
lawn and also prevented him from being tattooed.
The paradox is that Federico’s ability to renege on
his promise and surprise Pablo turns out to be counterproductive. If Pablo is intelligent enough to understand
his father’s decisions, he will not believe Federico’s
promise and, consequently, he will not mow the neighbors’ lawn. Federico’s promise is “incredible.”
Importantly, Federico ends up worse off than if he
could bind himself to honor his word. If he could, he
would be able to convince Pablo to mow the lawn.
Although he would have to allow Pablo to get a tattoo in
order to achieve this goal, Federico would avoid his least
preferred outcome.
Simple as it is, the father-son example illustrates the
crucial elements of Calvo’s and Kydland and Prescott’s
analysis of credibility. Often, the interaction between a
policymaker and the public is similar to that of Federico
and Pablo. Like Pablo, the public makes some decisions
whose value depends on subsequent policy actions of the
policymaker. Like Federico, the monetary authority may
have an incentive to announce policy actions in order to
6

affect the public’s decisions and to break its promises
once these decisions are made. If the public understands
the policymaker’s incentives, it will disregard its promises. And this interaction will often result in a bad outcome
for society. This is the essence of what Calvo and Kydland
and Prescott call the time-inconsistency problem.
Although time inconsistency pervades all aspects of
government policy, its application to monetary policy has
attracted the most research. A monetary authority, such
as the Federal Reserve, typically has as a major objective
to deliver low inflation. It may also have other objectives
that can be accomplished by creating surprise inflation,
that is, inflation rates over and above those previously
anticipated by the public. A case in point occurs if one
objective is to fight unemployment, as in the studies by
Kydland and Prescott (1977) and Barro and Gordon
(1983a). These studies assume that firms and workers
write contracts before production and sales take place;
these contracts stipulate a fixed nominal wage at which
workers agree to supply labor at the firms’ demand. Then
the monetary authority has an incentive to create unexpected inflation that would reduce the real value of
wages and induce firms to employ more workers.
If, like Federico, the monetary authority is not
bound by its promises, then it will have a credibility
problem. The monetary authority would like to promise
low inflation but has an ex post incentive to engineer
surprise inflation, using whatever policies it has at its
disposal, and expand employment.
Can the monetary authority succeed? Arguably, the
public is intelligent enough to understand the monetary
authority’s credibility problem. This premise is, in fact,
implied by the more general hypothesis of rational expectations, which was gaining acceptance in macroeconomics when Calvo’s and Kydland and Prescott’s contributions
were published. Rational expectations theory maintains
that individuals use efficiently all available information
when making decisions. Under the plausible assumption
that their information includes knowledge about how
monetary policy is chosen, individuals may not believe a
promise of low inflation by the monetary authority, just as
Pablo discounted Federico’s promise in the father-son
example. Rather, understanding correctly that the monetary authority will attempt to engineer surprise inflation,
individuals will adjust their inflation forecasts upward.
If individuals know that the monetary authority may
try to surprise them, what is the outcome, or equilibrium,
that will be observed? The answer, first advanced by
Barro and Gordon (1983a), is somewhat tricky. The key
observation is that a plausible outcome must have the
property that the monetary authority does not profit, at
the end, from surprising the public. This property must
hold because individuals know that the monetary authority will try to create surprise inflation if it can gain from
doing so. Therefore, in an equilibrium, expected inflation

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W First Quarter 1998

must equal actual inflation, and both have to be such that
there is no incentive for the monetary authority to create
unanticipated inflation.
Since expected and actual inflation must coincide
in equilibrium, the monetary authority cannot succeed
in its effort to expand employment. Given this restriction, it seems plausible that the monetary authority
would choose to keep inflation low. However, time
inconsistency means that expectations of low inflation
provide an incentive for the monetary authority to create unexpected inflation, which would be incompatible
with an equilibrium. Instead, in an equilibrium both
expected and actual inflation must be such that that
incentive is eliminated. Under plausible conditions the
result is inflation that is inefficiently high.5
The result is very bad from a social perspective: not
only is the monetary authority unable to expand employment, but expectations of high inflation end up being
accommodated by monetary policy. In short, monetary
policy suffers from an inflation bias because of the timeinconsistency problem.
Like Federico, the monetary authority would be better off if it could somehow bind itself to honor its promises. If that were possible, then the monetary authority
would achieve a better outcome by promising to deliver
low inflation. Making such a promise would imply giving
up on the employment objective, but it would at least
succeed in keeping inflation low.
The emergence of a time inconsistency problem
when a central bank is concerned with both inflation
and employment has been one focus of the literature,
and because of its importance the rest of the article will
explore this scenario as well. However, the reader should
keep in mind that a monetary authority may have to deal
with time inconsistency and a resulting inflation bias
when it has objectives other than fighting unemployment. For instance, a central bank forced to finance government expenditures through money creation may have
an incentive to promise low inflation to maximize the
demand for money, which forms the base of the inflation
tax, and then to break that promise to increase inflationary revenue. Other examples are not hard to find,
suggesting that time inconsistency may be a pervasive
feature of monetary policy.

Dealing with Inflation Bias:
Delegation and Incentives
t is clear that, in the presence of time inconsistency, a
monetary authority would benefit from tying its hands
behind its back to enhance its credibility. However,
doing so is not so simple. The monetary authority may try

to promise or even enact a rule that it will behave “honestly.” Such announcements would presumably be no
more believable, though, than a promise of low inflation.
What else could be tried? To explore some possibilities, let us return to the father-son example. Obviously,
Federico would not suffer from lack of credibility if he did
not dislike tattoos. Even with the assumption that Federico
hates tattoos, he might obtain desirable results if he were
to give up dealing with Pablo directly and delegate Pablo’s
education to a tutor. In
pursuing this solution,
Federico should be careful that the tutor’s incentives are such that he
Institutional approaches
does not have a credibiliand reputational concerns
ty problem himself. To
are both plausible soluensure the tutor’s credibility, Federico has two
tions to the time inconsisoptions. One is to hire a
tency problem, and both
tutor who likes tattoos,
have weaknesses accordon the premise that such
a tutor would not be
ing to existing theory.
tempted to buy a book
rather than paying Pablo
for mowing the lawn. The
other option is to pay the
tutor only according to whether Pablo mows lawns and not
according to what he does with the money earned.
Analogously, a society may try to deal with the time
inconsistency of monetary policy by delegating the execution of monetary policy to agents with appropriate
incentives. This point was first developed in an important paper by Rogoff (1985). Rogoff studied an idealized
economy in which there were well-defined social preferences on inflation-employment combinations. In such
an economy, a central banker with the same preferences as those of society would suffer from a credibility
problem, as discussed in the previous section. Given
this problem, Rogoff’s key insight was that this society
may not be constrained to choose an individual with the
same preferences as itself to conduct monetary policy.
Instead, it should choose a person whose distaste for
inflation is greater than the social one.
The appointment of a “conservative” central banker
mitigates the inflation bias because the public would
know that such a person would refrain from using unexpected inflation to expand employment. Accordingly, individuals would reduce their inflation forecasts, and they
would turn out to be correct because of the central
banker’s distaste for inflation. The conservative central
banker would not attempt to stimulate employment but

5. One such condition is that the marginal cost of creating inflation increases the level of inflation while the marginal effect
on employment is constant.
Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W First Quarter 1998

would be able to promise and deliver low inflation. Hence
delegating monetary policy to a conservative central
banker would improve matters, just as hiring a tutor who
likes tattoos would help Federico ensure that Pablo will
mow the neighbors’ lawn.
Rogoff’s analysis may explain why central bankers are
often known to be “hawkish” on inflation: according
to Rogoff’s theory, this position would be a social response to the credibility problem in central banking. More
subtly, Rogoff’s prescription requires that central bankers be independent of other branches
of the government. This
A society may try to deal
independence is needed
with the time inconsistency
because the policy choicof monetary policy by
es of a central banker
whose preferences are
delegating the execution
different from those of
of monetary policy to
society must, ex post, be
agents with appropriate
suboptimal from a social perspective. Society
incentives.
therefore would have an
incentive to dismiss the
conservative central
banker when he is about
to implement policy, just like Federico would have an
incentive to fire the tutor after the lawn is mowed and
then buy Pablo a book. This incentive must be held in
check for the conservative central banker to be effective.
Another option discussed for Federico is that,
instead of hiring a tutor who likes tattoos, he may solve
his credibility problem by paying the tutor only according
to the execution of Pablo’s job. Likewise, rather than
choosing a conservative central banker, a society may
deal with a monetary policy credibility problem by appropriately structuring the rewards and compensation of its
central banker, that is, by designing an efficient “contract.” What would such a contract look like? Recall that
the key implication of time inconsistency is that it
induces an inflation bias. Eliminating that bias would
seem to require that the central banker be penalized
when inflation is high and rewarded when inflation is
low. In addition, the contract might stipulate additional
rewards or penalties to the central banker depending on
other variables such as employment growth.
These questions were first investigated in an influential paper by Walsh (1995a). Walsh obtained several interesting results in the context of the monetary policy model
of Barro and Gordon (1983a). He showed that an optimal
contract for a central banker would make his compensation depend only on the realized rate of inflation or, alternatively, on the realized rate of money growth. This finding
is surprising because one could have conjectured, as in the
previous paragraph, that optimal rewards would depend
8

on other variables in addition to inflation or money
growth.6 Also, Walsh showed that the optimal reward
structure may resemble an inflation-targeting rule in that
the central banker would be rewarded according to how
close inflation turned out to be relative to some given values or targets.
Hence Walsh’s theory provides a formal justification
for inflation targeting and for the recent trend toward
assigning central banks the sole objective of maintaining
low inflation. That justification is based on the incentives
that inflation-based compensation schemes would provide to central bankers. This argument contrasts with
others in favor of inflation-based rules for monetary policy, which have emphasized the implications for the distribution of macroeconomic outcomes assuming that the
rules will be followed.7
As with Rogoff’s approach, a necessary condition for
Walsh’s approach is that the central banker must be independent, in the sense that his contract with society must be
respected even if it is beneficial, ex post, to rescind it. In
order to deal with time inconsistency, the central banker’s
contract must induce him not to create unanticipated inflation even if inflationary surprises may be beneficial. If the
central banker’s contract could be repealed at no cost, the
contract would itself become incredible and its effects on
the public’s expectations would disappear.
Summarizing, the inflation bias caused by time inconsistency may be ameliorated if society can change the
incentives of its central banker. This change can be accomplished by choosing a very inflation-averse individual to
head the central bank or by designing his contract to discourage him from creating inflationary surprises. The latter approach may resemble a regime of inflation targeting.
In both cases, central bank independence emerges as a
necessary ingredient to ensure that the change in incentives is effective.
It has been emphasized that incentive-based
approaches are feasible provided that society can affect the
incentives of its central banker. But doing so may not be possible. If, for example, a government can commit to a particular contract with the head of its central bank, why is it
impossible for that government to commit to honor promises of low inflation? The question has no fully satisfactory
answer. In the end, the incentives approach depends crucially on the assumption that a society can make some commitments (such as honoring the contract of its central
banker) and not others. Such an assumption must ultimately be justified on institutional or political grounds, but
on this point theory remains to be developed.8

Dealing with Inflation Bias: Rules
nstead of imposing constraints on incentives, a different approach to solving the credibility problem
imposes external constraints on the instruments that
central bankers can use. The consequences would be

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W First Quarter 1998

trivial if society could force its central bankers always to
honor promises, but research along these lines assumes
that imposing such a stringent constraint is not feasible.
Instead, it is assumed to be feasible to impose other, less
than perfect rules. Then the interesting question is to
investigate the implications of those rules for equilibrium outcomes.
Consider again the father-son problem, assuming
that Federico deals directly with Pablo. It may be impossible for Federico to credibly promise that he will give
Pablo money to pay for a tattoo as his reward for mowing
the neighbors’ lawn. Nevertheless, Federico may instruct
the neighbors to pay Pablo directly; this approach would
prevent Federico from using the money to buy books
instead. This arrangement may be a good idea in spite of,
or precisely because, everyone knows that Pablo will get a
tattoo if he gets the money.
Analogously, a society may be able to restrict the
actions of its monetary authorities so as to alleviate the
inflation bias caused by time inconsistency. The commitment to fixed exchange rates in European countries has
been justified in this fashion (see Giavazzi and Pagano
1988). If a country is committed to a fixed exchange rate,
it becomes difficult for the central bank to engineer inflation surprises, as they are likely to put downward pressure
on the country’s currency. This constraint tends to reduce
the inflation bias since the public understands its consequences for monetary policy.
This kind of reasoning also provides a justification
for simple monetary rules, such as a constant money
growth rule. These procedures are interpreted as constraints on the choices available to central bankers,
designed with the purpose of ameliorating inflation bias
by preventing inflation surprises.
The conclusion is that, provided society can commit
to at least some rules, the imposition of rules may help
deal with credibility. This view may help justify some
rules, such as fixed exchange rates, that would otherwise
be irrelevant or even counterproductive.
As with incentive-based approaches, a key question is
what policy choices can and cannot be ruled out. In justifying a fixed exchange rate regime, the implicit assumption is that the monetary authority can commit to fixing
exchange rates but not to honoring promises of low inflation. Why is there a difference? One answer is that,
because of institutional reasons, some commitments are
harder to break than others. This argument carries some
force for fixed exchange rate regimes, which may require

international agreements that are costly to ignore.
However, even in the case of fixed exchange rates the
argument is grounded on an institutional factor and not
completely satisfying.
An alternative answer holds that society can in fact
commit to rules, but only imperfect ones. This limitation
exists because there is incomplete knowledge about the
nature of shocks that may hit the economy. In this view,
espoused most prominently by Flood and Garber (1989), the
assumption that society
can commit to some rules
but not to honoring its
promises approximates
the fact that no rule can
The monetary authority
be written that takes into
account every possible
may eliminate the inflation
kind of disturbance to the
bias by developing a repueconomy. Is this argutation for honoring its
ment convincing? That
all rules are imperfect
announcements of low
is not controversial. Howinflation.
ever, Flood and Garber’s
interpretation amounts
to assuming that policymakers cannot use standard probability theory to
describe the likelihood of some relevant macroeconomic
shocks. This assumption is problematic, for it makes it
very hard to solve the model in a convincing way. In particular, how are individuals supposed to make investment
and portfolio decisions in such an environment? Flood and
Garber assume that agents’ choices are based on rational
expectations, that is, on full knowledge of the structure of
the economy. But such knowledge must include the probabilities of all the shocks, and therefore its availability is
inconsistent with Flood and Garber’s interpretation of the
limitations of policy rules.
The discussion in this article implies that there is no
satisfactory justification for assuming that a society can
commit to some rules but not to others. Such an assumption makes the theory interesting but may also be its main
weakness.

The Role of Reputation
o far the emphasis has been on institutional responses to the problem of policy credibility. Since
the creation and enforcement of appropriate institutions may be difficult and costly, one should ask whether

6. As Walsh noted, this result depends on the assumption that the central banker cares about not only his compensation but
also social welfare. Also, the result hinges on a particular property of the Barro-Gordon model—that the magnitude of the
inflation bias is not affected by macroeconomic shocks. Whether the result holds under more general assumptions is the subject of current research.
7. For an example of this kind of argument, see Taylor (1993).
8. And, indeed, this point has been identified as a major weakness of the incentives approach (see McCallum 1995).
Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W First Quarter 1998

there are other ways to deal with the credibility problem.
One alternative exists provided that the monetary
authorities and the public interact for sufficiently long
periods. In such cases, the monetary authority may eliminate the inflation bias by developing a reputation for
honoring its announcements of low inflation, as discussed briefly above.
In the father-son example, it is unlikely that Federico
would be left unpunished if he breaks a promise to Pablo.
In real life Federico
and Pablo would have to
face each other for many
years. Federico may
Central bank independence
therefore be deterred
plays a role in dealing with
from reneging on his
time inconsistency but only
promises by the fear that
Pablo will not believe
as a complement to more
subsequent promises.
fundamental arrangements
Somewhat paradoxically,
intended to bind central
Federico’s fear of losing
his reputation vis-à-vis
bankers to honor their
Pablo is in fact useful.
promises.
Federico may be able to
credibly promise Pablo
a tattoo in exchange for
mowing the neighbors’
lawn if Pablo believes that Federico wants strongly enough
to be able to make credible promises in the future.
The same considerations apply to monetary policy. It
is likely that a monetary authority that today makes and
breaks a promise of low inflation will be unable to credibly promise low inflation in the future. This incentive
may be powerful enough to deter the authority from
reneging on its current promise because, as the discussion has shown, the ability of making credible promises is
socially valuable.
These ideas were first discussed in the context of
monetary policy by Barro and Gordon (1983b). They
analyzed a simple version of the monetary model in
Kydland and Prescott (1977), the main difference being
the assumption that the monetary authority and the
public interacted for many periods. One of the outcomes
of that interaction, Barro and Gordon found, was that
the monetary authority acted as if it were able to make
binding promises in every period, provided it were
patient enough.9
In spite of its importance, further study of the role
of reputation was hindered for several years by the technical issues involved in analyzing the long-term relationship between a central bank and the public. The main
problem is that such analysis quickly leads to a problem
of infinite regress. Describing an outcome of a long-term
interaction requires specifying not only what happens if
the central bank breaks a promise of low inflation but
also what happens if it breaks another promise after the
10

first one and then a third promise, and so forth. In fact,
even the very concept of equilibrium, that is, of the plausible outcomes of a model, is not obvious.
Very recently, however, new methods have appeared
that promise a drastic reconsideration of models of
reputation. Chari and Kehoe (1990) and Stokey (1991)
provide a convincing definition of equilibria in macroeconomic models of long-term relationships. In addition,
these two papers present a general method for identifying the complete set of equilibrium outcomes of many
such models. Although that method turns out to be difficult to apply, recent studies by Chang (1998) and Phelan
and Stachetti (1997) have shown how the solution of
such models can be drastically simplified, thus greatly
broadening the scope of the theory of reputation.
Chang and Phelan-Stachetti exploit the fact that,
in some sense, tomorrow will be very similar to today. To
see this concept, recall that an outcome of the longterm relationship between the central bank and the
public involves a description of what will happen if the
central bank breaks a promise today, tomorrow, or the
day after tomorrow, and thus ad infinitum. This kind of
analysis can be exceedingly complex. However, Chang
and Phelan-Stachetti show that an equivalent description can be obtained by focusing on the central bank’s
decision problem today, after any possible history of
(possibly broken) promises, with the understanding
that tomorrow’s problem will be just like today’s (except that the relevant history will be a little different).
This approach effectively reduces the analysis to a twoperiod problem, involving only today and tomorrow, and
hence eliminates the infinite regress problem.
The papers by Chang (1998) and Phelan and
Stachetti (1997) discuss in detail the theoretical advantages of their formulation. Interestingly, they find that in
any equilibrium monetary policy must follow “rules,” even
in the absence of external mechanisms to enforce them.
The intuition is as follows. A crucial part of Chang’s and
Phelan-Stachetti’s method is that, at any point in time,
the whole history of the economy can be summarized by
a small number of “state” variables. An implication is that
any equilibrium has the property that monetary policy
and market outcomes depend only on those variables and
not on calendar time. Since monetary policy is, in any
equilibrium, optimally chosen by the monetary authority,
this reasoning reveals that monetary policy is governed
by a relatively simple relationship between the state variables and policy instruments, that is, by a rule. Although
the nature and properties of the resulting rules remain to
be investigated, this finding is important because it
means that observing that monetary policy follows rules
should be the norm and not the exception.
In addition, Chang’s and Phelan-Stachetti’s studies
imply that models of reputation in monetary policy can
be analyzed by computational methods that many others

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W First Quarter 1998

thought were inapplicable. Chang’s study, in particular,
analyzes the model of Calvo’s (1978) original contribution and shows that reputational considerations may
imply that one of the model’s outcomes is indistinguishable from the best the central bank can do when it
can commit perfectly to its promises. That is, the timeinconsistency problem may not prevent the attainment
of socially optimal outcomes.
While the results just described are suggestive, it is
too early to conclude that the long-term nature of the
interaction between a central bank and the public implies
a solution to the credibility problem. Other, more realistic
models of monetary policy need to be investigated. More
importantly, that the central bank can implement its most
preferred policy is only one of many possible outcomes. In
most models it remains possible that reputational considerations will not be enough to convince the public that a
central bank will, in fact, honor its promises. Consider, for
example, what would happen if the central bank were to
assume that reputation will never matter for the public’s
behavior. In such a case, the central bank might behave
myopically and, in general, try to cheat on the public at all
times. This behavior may in turn validate the public’s
belief that the central bank will not attempt to develop a
“good” reputation. The outcome would be that the role of
reputation would not solve the time-inconsistency problem, even if the central bank and the public face each
other indefinitely.
Since the theory of reputation implies that the central bank interaction with the public may have multiple
outcomes, determining which outcome will occur
becomes a key issue. Unfortunately, existing studies do
not provide a satisfactory answer, and at this point the
presumption that reputational effects eliminate the
inflation bias caused by time inconsistency is based on
optimism rather than theory.

Some Comments on the Empirical Evidence
natural reaction to the theoretical discussion above
is to turn to empirical evidence to check whether
the credibility problem of central banks is, in fact, a
problem. Unfortunately, testing the various theories
described in this article has proved to be very difficult.
One of the sources of difficulty is that it is impossible to measure credibility directly. To see this problem,
consider testing the key proposition that more credible
central banks deliver lower inflation. What dimension
identifies a central bank as “more credible”? In the theoretical discussion, credibility is a central bank’s ability
to make binding promises. How can such ability be
observed, let alone measured, in the real world?

Because of these difficulties, existing empirical studies have by and large focused on testing a different but
related proposition: that more independent central banks
deliver lower inflation. This approach can be seen as an
indirect test of the theory since, as the discussion noted
earlier, central bank independence may emerge as part of
society’s attempt to eliminate the inflation bias caused by
lack of policy credibility. If such an attempt is successful,
one should expect a high degree of central bank independence to be associated
with low inflation.
The change of focus
from central bank credibility to central bank
It is likely that a monetary
independence is useful
authority that today makes
because independence is
typically expressed in
and breaks a promise of
many indicators found in
low inflation will be unable
legal documents and
to credibly promise low
central bank statutes. In
some cases, there is little
inflation in the future.
disagreement on when
such indicators signal
more or less independence; for instance, most
people would agree that
a central bank whose chairman can be fired at the will of
the president of the country is less independent than one
whose chairman cannot be so easily dismissed.
The most comprehensive attempt to quantify central bank independence is given by Cukierman (1992).
He rates the central banks of several countries in different decades according to four measurable dimensions of
central bank independence. The first concerns the procedures governing the appointment, tenure, or dismissal
of central bankers. For example, Cukierman rates a central bank whose head is appointed by the executive
branch of the government as less independent than one
whose chairperson is appointed by the legislature, which
in turn is rated less independent than one whose head is
chosen by the central bank’s board. Likewise, he considers a central bank to be more independent the longer its
chairperson’s statutory tenure is.
The second dimension is related to the formulation
of monetary and fiscal policy. Cukierman gives a high
independence rating to central banks that can decide on
monetary policy without interference from the executive
or legislative branches. In contrast, he gives lower ratings to central banks that must obey their government’s
decisions about the formulation and execution of monetary policy.

9. The monetary authority’s degree of impatience is important in Barro and Gordon’s analysis because the punishment they
considered for a government that reneges on today’s promise is the loss of reputation in the future; this punishment carries
less force if the future is discounted more heavily.
Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W First Quarter 1998

C H A R T 1 Central Bank Independence and Inflation, 1980–89

All countries

Av e r a g e I n f l a t i o n

300

200

100

0
0.1

0.3

0.5

0.7

Independence Index

Alesina-Summers Sample

Av e r a g e I n f l a t i o n

0.1

0.3

0.5

0.7

Independence Index

A third dimension of independence has to do with
the goals that a central bank is instructed to pursue.
Central banks whose sole objective is to ensure low
inflation are given high independence ratings. If the
central bank’s mandate includes other objectives, such
as pursuing full employment, that bank is given a lower
rating. It can be argued that whether price stability is
the central bank’s only objective has little to do with the
usual meaning of independence. Cukierman’s rationale

is that the preeminence of price stability among a central bank’s possible objectives measures society’s willingness to have a conservative central banker.
The fourth and final dimension of independence
lies in the extent to which a central bank is required
to finance government deficits. The easier the terms
are under which a central bank is required by law to
finance government deficits, the lower its independence rating is.

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W First Quarter 1998

Since each available indicator is likely to convey
some information about central bank independence, it is
useful to include all of them in empirical work. Cukierman
(1992) and others do so by constructing indices of central
bank independence. Each index is essentially a weighted
average of many indicators. Since the weights can vary
from study to study, the construction of an independence
index involves some subjectivity. However, the conclusions
obtained in the existing literature do not seem to depend
on the use of a particular index. Those conclusions, therefore, merit attention.
Recent research has underscored the difficulty of
obtaining a tight relationship between measures of central bank independence and inflation, as the top panel of
Chart 1 illustrates. Each point in the chart represents a
country’s central bank independence, measured along
the horizontal axis, against its long-term inflation, measured along the vertical axis. Cukierman’s index is a
proxy for central bank independence, and the annual
percentage change in the consumer price index is used
for long-term inflation; both variables refer to the
1980–89 decade.
A glance at the top panel of Chart 1 suggests the
absence of a systematic link between central bank independence and inflation. This conjecture is confirmed by
formal statistical tests, which reveal that increases in
the Cukierman index are associated with mild increases in inflation, although the association is not significant. Ordinary least squares applied to the data in the
top panel of Chart 1 yields the following estimated
equation: INF = 30.27 + 15.05 CBI, where INF denotes
1980–89 average inflation and CBI denotes Cukierman’s
index for each country. The t-statistic associated with
the CBI coefficient is 0.23, which is quite consistent with
the hypothesis that the CBI coefficient is zero. Since
an increase of Cukierman’s index expresses a higher
degree of central bank independence, the data in the
top panel of Chart 1 suggest that the empirical relationship between independence and inflation is the
opposite of that predicted by the theory of time inconsistency.
The above finding seems to contradict the hypothesis that central bank independence translates into lower
inflation. Belief in that hypothesis has become widespread after the publication of news stories discussing

studies that seem to confirm it.10 The difference
between those studies and the results reported here can
be explained easily. For a small subset of developed
countries, greater central bank independence seems to
be associated with lower inflation, as the theory predicts. To illustrate the point, the bottom panel of Chart 1
plots the same data as in the top panel but for only a subset of developed countries. In fact, the countries included in the bottom panel are the ones studied in an
influential paper by
Alesina and Summers
(1993). For this subset
of countries, the bottom
panel of Chart 1 suggests
At this point the presumpthe existence of a negation that reputational
tive relation between
effects eliminate the inflaCukierman’s index and
inflation, a conjecture
tion bias caused by time
that is confirmed by forinconsistency is based
mal statistical tests. For
on optimism rather than
the sample of the bottom
panel, ordinary least
theory.
squares yields the following equation: INF =
9.79 – 9.11 CBI. The
t-statistic associated
with the CBI coefficient is –2.36, which is inconsistent
with the hypothesis of a zero CBI coefficient at conventional significance levels.11
The conclusion is that greater central bank independence seems to have no beneficial impact on inflation,
except perhaps for a small group of developed countries.
How should these findings be interpreted? A possible
reaction is to keep believing that independence is conducive to lower inflation, blaming shortcomings in empirical procedures for failing to confirm that belief. It has
been argued—for example, by Cukierman (1992)—that
the problem is one of poor measurement. The independence indices used in Chart 1, as well as in most of the literature, capture only the legal aspects of central bank
independence. The real degree of independence may
depend on other, nonlegal variables that are hard to quantify. The solution seems to lie in finding alternative, more
accurate measures of central bank independence;
research on that front is still under way.12

10. Examples are “Role Shifts for Central Bankers,” New York Times, November 15, 1994, sec. D, and “Divorcing Central Banks
and Politics: Independence Helps in Inflation Fight,” New York Times, May 7, 1997, sec. D.
11. This finding need not imply that central bank independence helps lower inflation. An alternative explanation is that countries that have stronger anti-inflationary postures tend to be more conservative with their central bank arrangements. This
“reverse causality” view is proposed by Posen (1995).
12. Cukierman (1992) observes, for instance, that in some countries the average tenure of central bank presidents is much
shorter than the legal tenure period, which is one of the variables summarized in independence indices. Accordingly,
Cukierman argues that central bank independence can be measured more accurately in less developed countries by the
turnover ratio of their central bank heads.
Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W First Quarter 1998

An alternative reaction to the empirical findings
summarized by Chart 1 is that the theory implies that
central bank independence is associated with lower
inflation only under narrow conditions that may not hold
in practice. As was discussed earlier, the inflation bias
problem associated with time inconsistency may be
solved if central bankers develop a good reputation with
the public. If reputation does in fact work, one should
not expect to find any systematic relationship between
central bank independence and inflation, and hence the
empirical facts reported earlier are not a puzzle.
A more pessimistic view is that central bank independence is only a necessary but not a sufficient condition for eliminating the inflation bias caused by time
inconsistency. According to the theory discussed earlier
in this article, central bank independence plays a role
in dealing with time inconsistency but only as a complement to more fundamental arrangements intended
to bind central bankers to honor their promises. It may
be the case that central bank independence emerges for
reasons not related to those institutions, but in and of
itself it does not help solve the time-inconsistency problem and, therefore, does not result in lower inflation.

Conclusion
his article has reviewed the problem of time inconsistency of monetary policy and its possible solutions. The theory of time inconsistency emphasizes
that, if a central bank cannot credibly commit to honor
announcements of low inflation, expected and actual
inflation will be larger than if such a commitment could
be made. In other words, time inconsistency leads to an
inflation bias.
The discussion considers how some currently fashionable institutions such as central bank independence
and price stability rules may emerge as attempts to minimize the inflationary consequences of time inconsistency. But it also argues that there may be no need for such
institutions. The empirical evidence reviewed here did
not provide strong confirmation of the hypothesis that
central bank independence lowers inflation. This empirical failure may reflect that the time inconsistency bias
has been solved by reputational considerations, as suggested by recent theoretical advances. Alternatively, it
may be the case that the degree of central bank independence is determined by reasons other than eliminating inflation bias.

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W First Quarter 1998

REFERENCES
ALESINA, ALBERTO, AND LAWRENCE H. SUMMERS. 1993. “Central
Bank Independence and Macroeconomic Performance.”
Journal of Money, Credit, and Banking 25 (May): 151–62.

MCCALLUM, BENNETT T. 1995. “Two Fallacies Concerning
Central Bank Independence.” American Economic Review
85 (May): 207–11.

BARRO, ROBERT J., AND DAVID B. GORDON. 1983a. “A Positive
Theory of Monetary Policy in a Natural Rate Model.” Journal
of Political Economy 91:589–610.

PHELAN, CHRISTOPHER, AND ENNIO STACHETTI. 1997. “Subgame
Perfect Equilibria in a Ramsey Taxes Model.” Unpublished
manuscript, Northwestern University.

———. 1983b. “Rules, Discretion, and Reputation in a
Model of Monetary Policy.” Journal of Monetary Economics
12:101–21.

POSEN, ADAM. 1995. “Declarations Are Not Enough: Financial
Sector Sources of Central Bank Independence.” In NBER
Macroeconomics Annual 1995, edited by Ben Bernanke and
Julio Rotemberg. Cambridge, Mass.: MIT Press.

CALVO, GUILLERMO A. 1978. “On the Time Consistency of
Optimal Policy in a Monetary Economy.” Econometrica 46
(November): 1411–28.

ROGOFF, KENNETH. 1985. “The Optimal Degree of Commitment
to an Intermediate Monetary Target.” Quarterly Journal of
Economics 100 (November): 1169–89.

CHANG, ROBERTO J. 1998. “Credible Monetary Policy in an
Infinite Horizon Model: Recursive Approaches.” Journal
of Economic Theory, forthcoming.

STOKEY, NANCY. 1991. “Credible Public Policy.” Journal of
Economic Dynamics and Control 15:627–56.

CHARI, V.V., AND PATRICK KEHOE. 1990. “Sustainable Plans.”
Journal of Political Economy 98:783–802.

TAYLOR, JOHN B. 1993. “Discretion versus Policy Rules in
Practice.” Carnegie Rochester Conference Series in Public
Policy 39 (December): 195–214.

CUKIERMAN, ALEX. 1992. Central Bank Strategies, Credibility,
and Independence. Cambridge, Mass.: MIT Press.

WALSH, CARL E. 1995a. “Optimal Contracts for Central
Bankers.” American Economic Review 85 (March): 150–67.

FLOOD, ROBERT P., AND PETER GARBER. 1989. “Monetary Policy
Strategies.” IMF Staff Papers 36:612–32.
GIAVAZZI, FRANCESCO, AND MARCO PAGANO. 1988. “The Advantage
of Tying One’s Hands: EMS Discipline and Central Bank’s
Credibility.” European Economic Review 32 (June):
1055–82.

———. 1995b. “Is New Zealand’s Reserve Act of 1989 an
Optimal Central Bank Contract?” Journal of Money, Credit,
and Banking 27 (November): 1179–91.

KYDLAND, FINN E., AND EDWARD C. PRESCOTT. 1977. “Rules
Rather than Discretion: The Inconsistency of Optimal Plans.”
Journal of Political Economy 85 (June): 473–92.

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W First Quarter 1998

A Dynamic Multivariate
Model for Use in
Formulating Policy
TA O Z H A
The author is an economist in the macropolicy section
of the Atlanta Fed’s research department. He is indebted to Eric Leeper for instrumental suggestions. He is
also grateful to Rob Bliss, Jerry Dwyer, Bob Eisenbeis,
Frank King, Will Roberds, Mary Rosenbaum, Ellis
Tallman, and Dan Waggoner, whose detailed comments have significantly improved the article’s argument and exposition. Bryan Acree and Jeff Johnson
provided able research assistance.

O
“BELIEVES

MARCH 25, 1997,

THE

FEDERAL OPEN MARKET COMMITTEE (FOMC)

SHORT-TERM INTEREST RATE TARGET—THE FEDERAL FUNDS RATE—BY

THE WALL STREET JOURNAL

CALLED THE MOVE

STRIKE AGAINST INFLATION”

RAISED ITS KEY

BASIS POINTS.

CHAIRMAN ALAN GREENSPAN’S “PREEMPTIVE

(WESSEL 1997). ACCORDING

GREENSPAN,

THE

FOMC

IT IS CRUCIAL TO KEEP INFLATION CONTAINED IN THE NEAR TERM AND ULTIMATELY TO MOVE

TOWARD PRICE STABILITY”

(1997A, 1). THE FOMC DESCRIBED THIS INCREASE “AS A PRUDENT STEP THAT

AFFORDS GREATER ASSURANCE OF PROLONGING THE CURRENT ECONOMIC EXPANSION BY SUSTAINING THE
EXISTING LOW INFLATION ENVIRONMENT THROUGH THE REST OF THIS YEAR AND NEXT”

The notion of “preemptive strike” or “prudent step”
connotes the most important part of policy making: the
process of looking forward. Because the Federal
Reserve’s monetary policy has effects on the overall
economy only through long and variable delays, policymakers must look forward to forecast, to the best of
their abilities, how today’s policy actions will affect
economic conditions such as inflation in the future.
This process of anticipating the future is indispensable
in formulating sound monetary policy (see, for example, Cecchetti 1995, King 1997, and Blinder 1997).
16

(WESSEL 1997).

The Humprey-Hawkins Act has set out multiple
objectives for the Federal Reserve, including balanced
growth and stable prices (Board of Governors 1994). A
policy action by the Fed consists of using any one of various instruments, such as the federal funds rate and different measures of money, to pursue its multiple
objectives. However, to provide clearer analysis this article characterizes monetary policy actions more narrowly
as changes in the federal funds rate and the discussion
concentrates on only one of the Federal Reserve’s objectives—keeping inflation, as measured by the consumer

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W First Quarter 1998

price index (CPI), low and stable. In such a framework,
one aspect of effectively advising policymakers is to provide a forecast of how inflation outlook changes if the
Federal Reserve adopts different paths of the federal
funds rate over the next two or three years. By consulting
a menu of such projected outcomes, called policy projections, policymakers can decide which particular policy
actions are most likely to keep inflation around the level
commensurate with their objective.
Policy projections are essential in helping policymakers decide on policy actions. Unfortunately, obtaining an accurate estimation of such projections is a
daunting task. Because the projections are based on various forecasts under different scenarios—here, alternative federal funds rate paths—the first and critical step
is to develop good forecasting models (Sims 1980). It is
therefore the purpose of this article to present a forecasting model that seems to overcome conceptual and
empirical difficulties encountered in other models and
promises to provide policymakers with a more useful tool
for anticipating effects of policy.
The model, one of a class of models called dynamic
multivariate models, introduces new techniques that offer
two distinctive advantages. One is the ability to forecast
the values of key macroeconomic variables such as inflation and output beyond a period over which these values
are known, on the assumption that the trends followed
within the period continue beyond it. These extrapolated
forecasts are known in technical jargon as out-of-sample
forecasts. The model’s other advantage is its explicit structure that allows empirically coherent ways to assess the
uncertainty of forecasts through error bands. These error
bands are constructed so that there is a two-thirds probability that actual outcome is contained within the band.
The article first discusses dynamic multivariate
modeling in general and reviews other approaches to
forecasting. The discussion then turns to the model
itself. After describing the specifics of the model, the
article presents the model’s point forecasts through the
1980s and 1990s. These forecasts represent the scenarios most likely to develop. Finally, the article shows how
to use probability distributions to gauge forecast errors.

Dynamic Multivariate Modeling
he term dynamic means that economic variables
influence one another through variable lags over
time. For example, today’s change in the federal
funds rate will have consequences on the path of inflation
in a year or two. The term multivariate implies that a set
of multiple variables are examined together, not sepa-

rately, in one framework. By dynamic multivariate models this article means a class of models that are designed
to capture, in a single framework, joint movements and
dynamic patterns in an array of multiple key macroeconomic variables over a particular period of time.
(Technical details are discussed in Box 1 in relation to the
specific model presented here.)
Other Approaches. Before explaining the key aspects
of dynamic multivariate modeling, it is perhaps useful to
review briefly two other
approaches to forecasting and policy analysis.
One approach is to use
rules of thumb. Rules of
The dynamic multivariate
thumb are often used in
model presented in this
actual policy discusarticle provides a useful
sions because they may
be based on theoretical
tool for gauging future
work and thus can prouncertainty and an empirivide compelling stories
cally consistent way to
to policymakers. Unfortunately, they are generupdate forecasts.
ally insufficient for
characterizing the actual economy, and therefore forecasts derived
from these rules are likely to be quantitatively unreliable.
For example, one rule of thumb often referred to in the
popular press is the Phillips curve relationship, which implies that whenever the unemployment rate is low (high),
inflation will soon rise (fall).1 Chart 1 displays annual inflation and the annual unemployment rate from 1960 to 1996.
As the chart shows, there were times when inflation and
unemployment tended to move in the same direction, not
in opposite directions. For instance, from the early to
mid-1970s, rising unemployment was coupled with rising
inflation; from 1982 to 1986 both inflation and the unemployment rate fell. During other times inflation and unemployment moved in quite different fashions. Consider
1992–96, for example. During this period, the unemployment rate fell steadily but inflation stayed almost flat. If
one used the negative relationship between inflation and
unemployment in the 1987–91 period to predict inflation,
the result would be to overpredict inflation for 1992–96.2
Another example of rules of thumb is the bivariate
relationship between inflation and the growth rate of
money. A number of economists (for example, Friedman
1992) have argued that the M2 growth rate in particular
appears to have a stable relationship to inflation. Chart 2
displays time-series patterns of inflation and the M2

1. A.W. Phillips first noted such a relationship in 1958. His original study examined a temporary trade-off between changes in
nominal wages and the unemployment rate in the United Kingdom over a period from 1861 to 1957.
2. The literature presents several versions of the bivariate relationship between unemployment and inflation. For critical discussions consult, for example, Chang (1997), Espinosa and Russell (1997), and Staiger, Stock, and Watson (1997).
Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W First Quarter 1998

B O X

Details of the Model
his box, heavily drawn from Sims and Zha (1998),
describes the important features of the model that is
used to produce the results presented in Charts 6–10. The
dynamic multivariate model takes the following simultaneous equations form:

y(t) A( L) = ε(t), t = 1,..., T ,

(1)

where A(L) is an m × m matrix polynomial of parameters
in lag operator L, y(t) is a 1 × m vector of observations of
m variables at time t, and ε(t) is a 1 × m vector of independently, identically distributed (i.i.d.) structural shocks
so that
Eε(t) = 0, Eε(t)′ ε(t) =

(2)

m× m

Note that T is the sample size. To estimate system (1),
the likelihood function is multiplied by a probability density function. This probability density, formally a Bayesian
prior distribution, aims at eliminating the undesirable
problems associated with the estimation. These problems
are discussed in detail below.
The number of parameters in A(L) grows with the
square of the number of variables in system (1). Given the
short period of macroeconomic data after World War II, traditional, ordinary least squares (OLS) estimation of a large
model (for example, the eighteen-variable model studied by
Leeper, Sims, and Zha 1996) becomes imprecise because of
relatively low degrees of freedom and a large number of parameters. Thus, models used in macroeconomics are often of
small size (say, six variables). For small models like the sixvariable model presented in this article, error bands on the
OLS estimates of parameters are usually tight, and thus
quantitative analysis from these models can be informative.
Nonetheless, when a model is used for out-of-sample forecasting, one can no longer take comfort in “good” in-sample
properties of the OLS estimates. Three major problems prevent reasonable out-of-sample forecasting, especially over
long horizons (such as two or three years out).
The first problem is a familiar one: overfitting. Because
of a large number of parameters, the model tends to fit the

sample unrealistically well but fails badly for out-of-sample
forecasting.1 To see how unbelievable the overfitting problem could become, Chart A displays actual values and insample (not out-of-sample) forecasts of the stock of M1
from January 1960 to March 1996. These in-sample forecasts, drawn directly from Sims and Zha (1998), are made as
of 1959:12 from the estimated model (using the data from
1959:7 to 1996:3) without any prior distribution (that is,
with OLS estimates). As shown in Chart A, one could, in
1959, predict with almost perfect precision the level of M1
stock in 1996—an incredible outcome.
Another aspect of overfitting, which has not been
addressed in the textbooks, is an unreasonable extraction of
business cycles into deterministic components (see Sims
and Zha 1998 for technical details). This undesirable feature
may have contributed to findings about substantial differences in OLS estimates across different subsamples. It may
distort long-run relationships among variables in the model
as well. To deal with these overfitting problems, the model
used here, following Sims and Zha (1998), uses priors that
favor unit roots and cointegration.2 At the same time, the
model avoids imposing exact, but likely spurious, unit roots
and cointegrated relationships with a probability of one.
The third problem relates to low degrees of freedom in
most macroeconomic models. Typically, OLS estimates tend
to produce large coefficients on distant lags and erratic
sampling errors. One of the prior distributions used in the
model here is to downweight the influence of distant lags or
the unreasonable degree of explosiveness. This prior distribution is essential for ensuring reasonable small-sample
properties of the model, especially when degrees of freedom are relatively low.
The prior distributions used here do not intend to
encompass all briefs that are likely to improve out-of-sample forecasts. Rather, they reflect some widely held briefs
that are likely to be uncontroversial. In this sense, the
prior distributions are of a reference nature, and such an
approach closely follows the likelihood principle.

1. Dynamic multivariate models are not the only types that produce overfitting. This problem is common across many empirical
models (see Diebold 1998b).
2. From a different perspective, Christofferson and Diebold (1997) discuss why cointegrated relationships are important for shortterm forecasts.
18

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W First Quarter 1998

B O X

( C O N T I N U E D )

CHART A

Actual and Forecast M1 Monthly Series
(1960:1–1996:3)

Billions of Dollars

1200

Actual

800

In-Sample

400

0
1960

1980

1970

1990

Source: Sims and Zha 1996.

growth rate from 1960 to 1996. The M2 growth rate
reached a peak three times—in 1972, 1976, and 1983. But
the path of inflation after each peak was quite different.
Clearly, past M2 growth rates predict future inflation
through variable lags, and there are no regular patterns.
Another approach to forecasting is to link forecasts
of macroeconomic variables to a large array of other
variables through econometric techniques. This approach usually involves many strong assumptions or
judgmental adjustments. Large-scale structural econometric models are examples of this approach. The goal
of these models is to not only provide forecasts of key
macroeconomic variables but also examine in detail
many different sectors of the economy (Diebold 1998a).
Because of their detailed, intricate nature, however,
these models are often difficult to produce and evaluate
independently. Furthermore, strong assumptions contained in these kinds of models, such as the Phillips
curve relationship, may be at odds with the data.
Judgmental adjustments consequently play roles in the
model’s outcomes from period to period. Such periodical
adjustments make it difficult to gauge the quality of the
model itself.
Distinctive Aspects of Dynamic Multivariate
Modeling. Dynamic multivariate modeling offers a different approach. It is not designed to study every detail of
the economy. Rather, it is designed to capture only essen-

tial elements so that the model can be readily understood
and reproduced. It is closely connected to modern economic theory and usually involves only six to eight variables.3 After the model—the array of variables, the lag
length, and other assumptions—is set up, forecasts from
the model will not be altered from period to period on the
basis of judgments or assumptions outside the model
itself. Thus, the model can be evaluated objectively.
At the same time, dynamic multivariate modeling
has complex structures in the sense that it allows both
contemporaneous and dynamic interactions among the
macroeconomic variables. In relation to rules of thumb,
dynamic multivariate models capture the relationships
implied by these rules if such relationships exist in the
data. In contrast to large-scale models, dynamic multivariate modeling avoids imposing strong assumptions that
may be at odds with the data. Consequently, both the
Federal Reserve’s complex behavior and the public’s
expectations about future policy actions are implicitly
embedded in dynamic multivariate models.
More important, dynamic multivariate modeling provides empirically coherent ways to assess the uncertainty
about forecasts (Sims and Zha 1998). All forecasts have
errors. The errors usually come from two sources—
uncertainty about model parameters and uncertainty
emanating from exogenous shocks (that is, those that
cannot be predicted by the model). Dynamic multivariate

3. See, for example, Diebold (1998a) and Sims and Zha (1996) for detailed discussions.
Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W First Quarter 1998

C H A R T 1 Annual Inflation and Unemployment Rates, 1960–96

14
Inflation

10
Percent

Unemployment

1970

1960

1980

1990

Source: See Box 2.

C H A R T 2 Annual Inflation and M2 Growth Rates, 1960–96

Percent

6
Inflation

1960

1970

1980

1990

Source: See Box 2.

modeling lays out a probabilistic structure that takes both
types of uncertainties into account explicitly. When probability distributions or error bands are attached to point
forecasts, policymakers will be well informed of the likelihood of future inflation.

The Model

T
20

he dynamic multivariate model used in this article
employs monthly data with the six key macroeconomic variables often used in the literature: the

federal funds rate, the stock of M2, the consumer price
index, real (inflation-adjusted) gross domestic product,
the unemployment rate, and an index of commodity
prices (see Box 2 for a precise description of the data
set). The data begin at 1959:1 and end at the time when
the forecast is made. The model allows these variables to
interact with one another both simultaneously and
through lags.4 The lag length is thirteen months, meaning
that variables in the past thirteen months are allowed to
affect those in the current month.

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W First Quarter 1998

B O X

Data Description
The model uses monthly data from 1959:1 to 1997:9 for six
macroeconomic variables:
CPI. Consumer price index for urban consumers (CPI-U),
seasonally adjusted. Source: Bureau of Economic Analysis,
the Department of Commerce (BEA).
Commodity Prices. International Monetary Fund’s index
of world commodity prices. Source: International Financial
Statistics.

GDP. Real GDP, seasonally adjusted, billions of chain 1992
dollars. Monthly real GDP is interpolated using the procedure described in Leeper, Sims, and Zha (1996). Source:
BEA.
M2. M2 money stock, seasonally adjusted, billions of dollars. Source: Bureau of Labor Statistics (BLS).
Unemployment. Civilian unemployment rate (ages sixteen
and over), seasonally adjusted. Source: BLS.

Federal Funds Rate. Effective rate, monthly average.
Source: Board of Governors of the Federal Reserve System.

Because the model does not allow for judgmental
adjustments periodically, it aims at strong performance of
out-of-sample forecasting by the model itself (see Box 1
for details). When decision making is guided by forecasts
extrapolated from the model, actual data for the future
period are of course not available to policymakers.
Therefore, out-of-sample forecasts, with probability distributions or error bands attached, can be invaluable.
The error bands of forecasts give policymakers an indication of the range of the future data. Before the discussion turns to greater detail about the use of probability
distributions of forecasts, the next three sections discuss
out-of-sample point forecasts produced from the specific dynamic multivariate model presented here.

Out-of-Sample Point Forecasts
he 1980s. In the late 1970s inflation was accelerating to rates unprecedented in the period since
1960. Then in the 1980s inflation slowed down
more quickly than the public thought possible. Thus,
1980s inflation is difficult to forecast. Chart 3 displays
the model’s forecasts of annual inflation through the
1980s. In each panel of Chart 3, the thick line represents
actual outcomes of inflation, the thin line represents the
model’s forecasts for the next two years, and the dots are
the Blue Chip forecasts for the next two years.5 Note that
the Blue Chip forecasts at the beginnings of 1980, 1981,
1982, and 1983 are not displayed here because the new
methodology introduced to compute the CPI has significantly changed figures for actual inflation before 1984.

New definitions or revisions of the data always affect the
accuracy of evaluating the forecasts that were made
using old data at the time. Inflation figures after 1983,
however, have not been altered much by subsequent
data revisions. In Panel E, for instance, the Blue Chip
forecasts were made at the beginning of 1984. To be comparable, the model’s forecasts are also made at the
beginning of 1984. In addition, Panel E displays the actual data in the two years (1982 and 1983) prior to the
forecast year. Similarly, in all other panels, the forecasts
for the next two years are displayed along with the actual data in the two years prior to the forecast year. For
example, in Panel F, inflation forecasts in 1985 and 1986
(the thin line and dots) are made at the beginning of
1985 along with actual inflation in 1983 and 1984.
As Chart 3 shows, without periodic judgmental
adjustments the dynamic multivariate model here produces quite reasonable results that are as least as accurate as the Blue Chip forecasts. In particular, the model
forecasts the slowdown of inflation in the 1980s fairly
well. Because the model is dynamic, it adjusts its forecasts accordingly by systematically incorporating the
most recent data. For example, at the beginning of 1981
the model tends to predict that the trend of inflation will
be higher than that of actual outcome (Panel B); by the
time 1981 is over, the model is able to predict the downturn of future inflation (Panel C).
How do the new data in 1981 help ameliorate the
forecasting performance? Remember that the model is
not only dynamic but also multivariate. The new data

4. The mathematical structure is similar to Sims and Zha (1998). See Box 1 for details.
5. Blue Chip Forecasts is a monthly publication based on a survey of a number of forecasters from different industries. The
Blue Chip forecasts displayed in this article are the consensus forecasts.
Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W First Quarter 1998

C H A R T 3 Point Forecasts of Annual Inflation Rate, 1980s

A
15

1978

1979

1980

1981

1979

1980

1981

1982

1983

1981

1982

1983

1984

1985

1983

1984

Percent

1986

1987

1988

1989

1990

1984

1985

1986

1987

1985

1986

I
15

1986

1987

1988

1989

Actual Inflation
Model's Inflation Forecast
Blue Chip Forecast

Source: See Box 2; Blue Chip Forecasts.

1985

1984

1983

1982

1981

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W First Quarter 1998

1987

1988

include prices as well as the model’s other macroeconomic variables, such as output, the interest rate, and
the unemployment rate. The model systematically
explores the dynamic relationships among these other
variables and the CPI, complex though they might be. It
is therefore unsurprising that inflation forecasting can be
further improved by the model’s ability to capture multivariate relationships in new data.
The 1990s. 1990 was a turning point for inflation.
Since then, inflation has declined steadily, from 5.4 percent in 1990 to 2.9 percent in 1996. Such a favorable environment has, to a large extent, surprised the public and
professional forecasters as well. Indeed, many forecasting firms have overpredicted inflation for this period. The
1990s is thus considered another very difficult inflation
period to forecast. Nonetheless, the model’s forecasts for
this period, as shown in Chart 4, look reasonable in capturing the steadily declining pattern of inflation.
From Chart 4 one can see that since 1991, Blue Chip
forecasts have been consistently higher than actual outcomes. The overprediction of inflation in the 1990s is
consistent with simple rules of thumb such as the
Phillips curve trade-off, given the declining unemployment rate after 1992. In contrast, the model’s dynamic
forecasts are more optimistic about the downward trend
in inflation and closer to actual outcomes.
Regime Shifts. There is a common view that monetary policy follows simple rules and that these rules
change from time to time in an exogenous fashion. For
example, the 1979–82 period is often regarded as one in
which the policy “rule” was completely changed because
the Federal Reserve adopted new operating procedures
to target nonborrowed reserves rather than the federal
funds rate. After 1982 the Federal Reserve returned to
targeting the federal funds rate. By this argument, the
period after 1982 has been under a different regime than
the 1979–82 period, and some empirical modelers use a
sample period that begins only after 1982 as if the data
before 1983 were irrelevant.
To examine this idea, the model here is reestimated
using the data starting in 1983. Chart 5 reports inflation
forecasts out of sample (indicated by the dots). Evidently,
throwing away the data before 1983 does not improve outof-sample forecasting in general and worsens it considerably in some cases (Panels D, E, and F).6 One
interpretation of these findings is that the Federal
Reserve’s behavior is complicated and cannot be characterized by discontinuous or abrupt changes in simple
rules. Even among economists there is no agreement on

whether the Federal Reserve’s behavior during the
1979–82 period was actually different (Cook 1989). For
example, Goodfriend (1993, 4) argues that “it is more
accurate to refer to the period from October 1979 to
October 1982 as one of aggressive federal funds rate targeting than one of nonborrowed reserve targeting.” From a
forecasting point of view, Charts 3 and 4 show that including data in this period helps forecast inflation in the 1980s
and 1990s; Chart 5 suggests that in dismissing
the data simply by a priori reasoning valuable
All models at best only
information may be lost.
approximate the actual
In a nutshell, the
economy. No model can
dynamic multivariate
model that generates
forecast economic condiresults in Charts 3–5
tions with perfect accuraaims at accounting for
cy. Thus, policymakers
both short-run dynamics
and long-run relationmust use point forecasts
ships among the six key
cautiously and carefully.
macroeconomic variables. Such a modeling
strategy may explain the
model’s reasonable performance in forecasting inflation. Model-based forecasts
provide benchmarks by which policymakers can decide on
the best policy action given all current information.
Furthermore, explicit modeling makes it easy to document the model’s forecasting performance (as in Charts
3–5) and to continue improving the model or replace it by
a better model when available.

The Distributions of Forecasts
ll models at best only approximate the actual economy. No model can forecast economic conditions
with perfect accuracy. Thus, policymakers must
use point forecasts cautiously and carefully. When a
model is used to advise policymakers, it is desirable that
an explicit measure of uncertainty about the model’s forecasts be provided. One effective way to measure uncertainty is to provide probability distributions of particular
forecasts. With such a distribution, one is able to construct an error band on the forecast or to infer how likely
the forecast is to be above or below a certain number.
Error bands provide a sense of the uncertainty of economic conditions in the future and where the distribution
of, say, inflation lies. Producing realistic error bands on
forecasts has been a difficult technical problem. In a

6. Technically, these two sets of forecasts may not be statistically different when error bands are considered. Small samples
such as the data after 1982 tend to give unreliable results due to erratic sampling errors, as found in, say, Cecchetti (1995).
The fact that the model with only the post-1982 data delivers reasonable results may be due to recent developments in
Bayesian methods that deal with problems associated with low degrees of freedom (see Sims and Zha 1998 and also Box 1).
This feature is still largely unexplored and deserves further research.
Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W First Quarter 1998

C H A R T 4 Point Forecasts of Annual Inflation Rate, 1990s

A
6

1988

1989

1990

1991

1989

1990

Percent

2
1990

1991

1992

1993

1991

1992

2
1992

1993

1994

1995

1996

1992

C
6

1991

1994

1995

1993

1994

Actual Inflation
Model's Inflation Forecast
Blue Chip Forecast

Source: See Box 2; Blue Chip Forecasts.

recent paper Sims and Zha (1998) provide ways to compute probability distributions of forecasts from dynamic
multivariate models (see also Box 1).
Given probability distributions of forecasts, error
bands can be constructed for any desired probability. The
purpose of constructing such a band is to demarcate reasonably high and low probability regions usable for policy
deliberations. The error bands used in this article are
constructed so that there is a two-thirds probability that
the realized value is contained within the band. With this
demarcation, events outside the band are given low probability and thus should be given less weight in decision
making. One should bear in mind that low probability
events do occur at times but less frequently.
As an example, Chart 6 presents the same forecasts
as in Panel B of Chart 3 but with error bands attached.
Whereas actual inflation for 1981 falls within the error
band, actual 1982 inflation lies outside the error band.
The error band at the two-year forecast horizon (that is,
1982) suggests that it is unlikely that 1982 inflation
would return to the 1980 level, which indeed did not
occur. At the same time, the model gives low probability
to values far below 7.9 percent (the lower bound of the
24

1982 error band). But actual inflation in 1982 did occur
at the level of 6.2 percent.
Most of the time, however, actual outcomes of inflation fall within error bands. This evidence is clear from
Charts 3 and 4, in which point forecasts are often close to
actual values of inflation. In addition to assessing quantitatively the uncertainty of forecasts, error bands provide ways of evaluating forecasts from other sources.7 To
show an example, Chart 7 displays the model’s forecasts
for the real GDP growth rate in 1995 and 1996 with error
bands and Blue Chip predictions.8 Actual GDP growth is
inside the error bands, but the Blue Chip 1995 forecast of
GDP growth at about 3.2 percent is far outside the error
band. The model suggests that such a high growth rate is
unlikely for 1995.
Although the error bands considered here are sufficient for most purposes, it is sometimes useful to know the
entire distribution or likelihood that a particular forecast
is going to be realized. Charts 8 and 9 provide two examples. Corresponding to Chart 6, Chart 8 presents the distribution of the inflation forecast for 1982. The two dashed
vertical lines mark the band that contains two-thirds probability, and the solid vertical line marks the actual out-

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W First Quarter 1998

C H A R T 5 Point Forecasts of Annual Inflation Rate, 1990s (Using post-1982 data)

A
6

1988

1989

1990

1991

1989

1990

Percent

2
1990

1991

1992

1993

1991

1992

2
1992

1993

1994

1995

1996

E
6

1992

1991

1994

1995

1993

1994

Actual Inflation
Model's Inflation Forecast
Forecast Using Only Post-1982 Data

Source: See Box 2.

come of inflation in 1982. The dispersed distribution in
Chart 8 reflects a great uncertainty about inflation shortly
after the high volatility of inflation during the late 1970s
and early 1980s. Note that although actual inflation is outside the band, it is close to the lower bound of the band
(that is, far away from the tail of the distribution).
Chart 9, corresponding to Chart 7, displays the distribution of the forecast of the real GDP growth rate in
1995. Again, the two dashed vertical lines mark the twothirds probability band, the solid vertical line at 2 marks
actual output growth in 1995, and the outer vertical line
indicates the Blue Chip forecast. As can be seen in Chart
9, the Blue Chip forecast is near the tail of the distribution, implying that by the model’s criterion such a forecast is very unlikely to be realized.

The discussion so far has been concerned exclusively with probability distributions or error bands around
individual forecasts. While this focus is sufficient and
effective for most policy analyses, it is important to bear
in mind that individual forecasts are not independent of
one another. Indeed, because of the multivariate nature of
the model, forecasts of a set of variables of interest have a
joint distribution. Such a distribution can be used to construct an error region that describes how likely forecasts
of, say, both high output growth and low inflation are.
Chart 10, for example, displays the error region that contains both real GDP growth and inflation for 1998 with a
two-thirds probability.9 The square represents the model’s
point forecast. The scattered circles are forecasts of real
GDP growth and inflation for 1998 from fifty-five different

7. These sources can be various commercial firms, particular economic theories, institutional knowledge, or even ad hoc views.
8. All forecasts are made at the beginning of 1995. Although this article concentrates on inflation for simplicity of the analysis,
forecasts of other macroeconomic variables such as output and unemployment are equally important for monetary policy.
In particular, a number of economists believe that there is a short-term trade-off between inflation and output, especially
when unexpected large shocks hit the economy (King 1997).
9. Similar to error bands of individual forecasts, error regions of joint forecasts can be constructed for any desired probability. Again, the discussion here focuses on two-thirds probability.
Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W First Quarter 1998

C H A R T 6 Inflation Forecasts with Error Bands for 1981 and 1982

Percent

Point forecasts

Upper & lower bounds
of error bands

Actual inflation

1979

1981

1980

1982

C H A R T 7 Real GDP Forecasts with Error Bands for 1995 and 1996

Percent

Blue Chip Forecast

Actual GDP
Growth Rate

Upper & lower bounds
of error bands

Point forecasts

1993

1994

firms, published by the Wall Street Journal on January 2,
1998. Because these forecasts were submitted by
December 18, 1997, the model’s 1998 forecasts and error
region in Chart 10 were made as of December 1997 to be
as compatible with the Wall Street Journal forecasts as
possible.10 According to the error region, the model gives
as much probability to the scenario of high GDP growth
(3.5–5.5 percent) and low inflation (around 2 percent) as
to that of medium GDP growth (2–3.5 percent) and low
inflation (around 2 percent). But the model gives low
probability to the scenario of low GDP growth (under 2
26

1995

1996

percent). The Wall Street Journal forecasts are unequally dispersed. At least one-fifth of the firms produced forecasts outside the model’s error region. None of the firms
produced forecasts that fall within the top half of the
error region implied by the model.

Conclusion
he real world of monetary policy is complex.
Because of long and variable lags in the effects of
policy actions, the Federal Reserve faces a difficult task in trying to achieve its multiple objectives. The

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W First Quarter 1998

C H A R T 8 Distribution of Inflation Rate Forecast for 1982

Probability Density

0.18

0.14

Actual outcome
Lower & upper bounds
of error bands

0.10

0.06

0.02
0
–1

Inflation Rate (percent)

CHART 9

Forecast Distribution of GDP Growth Rate for 1995

Probability Density

0.7

Lower & upper bounds
of error bands

0.5

Actual outcome

0.3
Blue Chip forecast

0.1

0
–2

–1

GDP Growth Rate (percent)

foregoing discussion concentrates on only one of these
objectives—to keep the path of inflation low and stable.
Given this objective, policy projections under different
paths of a policy instrument (for example, the federal
funds rate) are an integrated part of forward-looking
policy formation. And reliable forecasts of the path of
inflation are the first step in this process (Bernanke and
Mishkin 1997).

The dynamic multivariate model discussed here is
transparent enough to be reproduced and improved. At
the same time, it is sufficiently complex to capture
dynamic interplay between policymakers and the private
sector. Consequently, it shows reasonable performance in
forecasting as compared with other forecasts. More
important, this approach provides empirically coherent
ways to assess the uncertainty inherent in forecasts. Error

10. The forecasts displayed in Chart 10 are the 1998 averages of published figures in the Wall Street Journal.
Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W First Quarter 1998

Real GDP Growth (percent)

C H A R T 1 0 Error Region for Forecasts of Real GDP Growth and Inflation Rates for 1998

Inflation Rate (percent)
Forecasts (averages of published figures)
Model's Point Forecast

Source: Wall Street Journal, January 2, 1998.

bands or distributions of forecasts are essential for gauging this uncertainty in at least two aspects. First, they
offer an assessment of how likely or realistic other forecasts are. Second, error bands inform policymakers of the
uncertainty they face, reminding them of the “need to be
flexible in revising forecasts and the policy stance in
response to new information contradicting their previous
predictions” (Kohn 1995, 233).
As Chairman Greenspan has observed, “Operating on
uncertain forecasts, of course, is not unusual. . . . [I]n

conducting monetary policy the Federal Reserve needs
constantly to look down the road to gauge the future risks
to the economy and act accordingly” (1997b, 17). The
dynamic multivariate model presented in this article provides a useful tool for gauging future uncertainty and an
empirically consistent way to update forecasts. It is hoped
that future research will apply such a model to tasks of
policy projections.

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W First Quarter 1998

REFERENCES
BERNANKE, BEN S., AND FREDERIC S. MISHKIN. 1997. “Inflation
Targeting: A New Framework for Monetary Policy?” Journal
of Economic Perspectives 11 (Spring): 97–116.

GOODFRIEND, MARVIN. 1993. “Interest Rate Policy and the
Inflation Scare Problem: 1979–1992.” Federal Reserve Bank
of Richmond Economic Quarterly 79 (Winter): 1–24.

BLINDER, ALAN S. 1997. “What Central Bankers Could Learn
from Academics—and Vice Versa.” Journal of Economic
Perspectives 11 (Spring): 3–19.

GREENSPAN, ALAN. 1997a. Statement before the Senate
Committee on Banking, Housing, and Urban Affairs.
February 26.

BOARD OF GOVERNORS OF THE FEDERAL RESERVE SYSTEM. 1994.
The Federal Reserve System: Purposes and Functions.
Washington, D.C.

———. 1997b. Statement before the House Subcommittee on
Domestic and International Monetary Policy, Committe on
Banking and Financial Services. July 22.

CECCHETTI, STEPHEN G. 1995. “Inflation Indicators and
Inflation Policy.” NBER Macro Annual 1995,189–219.

KING, MERVYN. 1997. “The Inflation Target Five Years On.”
Bank of England Quarterly Bulletin (November): 434–42.

CHANG, ROBERTO. 1997. “Is Low Unemployment Inflationary?”
Federal Reserve Bank of Atlanta Economic Review 82
(First Quarter): 4–13.

KOHN, DONALD L. 1995. “Comment on ‘Inflation Indicators and
Inflation Policy’ by Cecchetti.” NBER Macro Annual 1995,
227–35.

CHRISTOFFERSON, PETER F., AND FRANCIS X. DIEBOLD. 1997.
“Cointegration and Long-Horizon Forecasting.” Journal of
Business and Economic Statistics, forthcoming.

LEEPER, ERIC M., CHRISTOPHER A. SIMS, AND TAO ZHA. 1996.
“What Does Monetary Policy Do?” Brookings Papers on
Economic Activity 2:1–63.

COOK, TIMOTHY. 1989. “Determinants of the Federal Funds
Rate: 1979–1982.” Federal Reserve Bank of Richmond
Economic Review 75 (January/February): 3–19.

SIMS, CHRISTOPHER A. 1980. “Macroeconomics and Reality.”
Econometrica 48 (January): 1–48.

DIEBOLD, FRANCIS X. 1998a. “The Past, Present, and Future
of Macroeconomic Forecasting.” Journal of Economic
Perspectives, forthcoming.
———. 1998b. Elements of Forecasting. Cincinnati, Ohio:
South-Western College Publishing.
ESPINOSA, MARCO A., AND STEVEN RUSSELL. 1997. “History and
Theory of the NAIRU: A Critical Review.” Federal Reserve
Bank of Atlanta Economic Review 82 (Second Quarter):
4–25.
FRIEDMAN, MILTON. 1992. Money Mischief: Episodes in
Monetary History. New York: Harcourt Brace Jovanovich.

SIMS, CHRISTOPHER A., AND TAO ZHA. 1996. “Does Monetary
Policy Generate Recessions?” Yale University and Federal
Reserve Bank of Atlanta, manuscript.
———. 1998. “Bayesian Methods for Dynamic Multivariate
Models.” International Economic Review, forthcoming.
STAIGER, DOUGLAS, JAMES STOCK, AND MARK WATSON. 1997. “The
NAIRU, Unemployment, and Monetary Policy.” Journal of
Economic Perspectives 11 (Winter): 33–50.
WESSEL, DAVID. 1997. “Fed Lifts Key Short-Term Interest
Rate Amid Speculation More Rises Are Likely.” Wall Street
Journal, March 26.

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W First Quarter 1998

The Rise of Risk
Management
J . D AV I D C U M M I N S ,
R I C H A R D D . P H I L L I P S , A N D
S T E P H E N D . S M I T H
Cummins is the Harry J. Loman Professor of Insurance
and Risk Management at the Wharton School, University of Pennsylvania, and a senior fellow at the Wharton
Financial Institutions Center. Phillips is an assistant
professor at Georgia State University. Smith holds the
H. Talmage Dobbs Jr. Chair of Finance, Georgia State
University, and is a visiting scholar at the Atlanta Fed.
The authors thank Robert Bliss, Gerald Dwyer, Saikat
Nandi, and Mary Rosenbaum for helpful comments.

ISK MANAGEMENT CAN BE ROUGHLY DEFINED AS ANY SET OF ACTIONS TAKEN BY INDIVIDUALS OR CORPORATIONS IN AN EFFORT TO ALTER THE RISK ARISING FROM THEIR PRIMARY
LINE(S) OF BUSINESS.

VIEWED

FROM THIS PERSPECTIVE, RISK MANAGEMENT IS NOTHING

NEW, DESPITE THE INCREASED ATTENTION GIVEN TO THE SUBJECT BY ACADEMICS AND MAN-

AGERS AS FINANCIAL DERIVATIVE MARKETS HAVE EVOLVED OVER THE PAST DECADE OR TWO.

For well over one hundred years farmers, for example, have engaged in risk management as they attempted
to hedge their risks against price fluctuations in commodity markets. Their preferred risk-management strategy has
been to sell some or all of their anticipated crop, before
harvest time, to another party on what is called futures
markets. This strategy guarantees the farmer a known
price for his crop, regardless of what the commodity’s actual price turns out to be when the harvest comes in. Risk
management along these lines makes sense for farmers for
at least two reasons. First, agricultural prices are volatile.
Moreover, many of these family farmers are not diversified
and, in addition, must borrow in order to finance their
crops. Therefore, setting the sale price now shifts their risk
of price fluctuations to other participants in the futures
market better able or willing to bear this volatility.
Contrast the above story with that of a large corporation, owned by a large number of shareholders, facing
similar commodity price risk. For concreteness, consider

a firm primarily engaged in the extraction and sale of
copper. Given that copper prices are relatively volatile,
the first rationale for risk management might seem similar to the farmer’s. However, unlike in the farmer’s circumstance, this firm is owned by a large number of
shareholders, who can, if they so wish, greatly reduce or
eliminate the risk that copper prices will be low simply by
holding a diversified portfolio that includes only a small
fraction of assets invested in the copper extraction corporation. More generally, if investors can freely trade
securities in many firms, they can choose their exposure
to volatility in copper prices. Indeed, in two studies
Modigliani and Miller (1958; Miller and Modigliani 1961)
showed that, in a world with no transactions costs or
taxes and with equal information, managers could not
benefit their shareholders by altering the risk profile of
the firm’s cash flows. Essentially, in this situation shareholders can already do whatever they choose at no costs;
actions by managers are redundant.

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W First Quarter 1998

Although the Modigliani and Miller studies considered the option of changing the firm’s risk profile only
through the use of debt financing (1958) or the distribution (or lack thereof) of dividends (Miller and Modigliani
1961) and not through the use of financial derivative
securities, the powerful intuition here is the same as that
outlined earlier. If managers of the firm wished to
increase their use of debt financing (say, because they
thought it was cheaper than equity), investors could
undo this transaction by, for example, taking equal positions in the firm’s debt and equity. This move would leave
investors facing the same risk from the firm’s operations
as they had before the increase in debt financing.
Given the above discussion, one is tempted to ask,
Why are managers doing for shareholders what shareholders apparently can do for themselves? In other
words, why do managers of corporations find it worthwhile to engage in risk-management activities, and why
has interest in this topic mushroomed over the past
decade or two?
This article is intended to provide a review of the
rationales concerning when firms should engage in risk
management. The first section lays the groundwork for
that discussion by defining more precisely what risk
management is in terms of the alternative instruments
available to managers. The second section provides a
discussion of the reasons firms might have for managing
risk, while the third section summarizes the empirical
evidence concerning the actual economic factors associated with using one such set of instruments, namely,
derivative securities. Since derivatives exist solely for
purposes of managing risk, studies of this type are relatively “clean” tests of the various rationales put forth for
why corporations manage risk.

What Constitutes Risk-Management Activities?
he term risk management, at its most general
level, simply denotes a situation in which an individual or firm makes decisions to alter the
risk/return profile of future cash flows. The terminology
typically used is that if managers are attempting to
reduce risk through their actions, they are said to be
hedging; if managers are trying to increase the firm’s risk
exposure because they believe that such a strategy will
yield abnormal profits, they are said to be speculating.
To put the decision about engaging in risk management in some perspective, this section of the article outlines the types of activities most commonly thought of as
risk management. For concreteness, again consider the

problem faced by the firm engaged in copper extraction.
Because commodities markets are competitive in the
sense that one firm’s activities will typically have a very
small impact on market prices, the underlying risk—copper price fluctuations—facing this firm can be generally
seen as given.
How might the firm alter this risk?1 One approach
would involve diversifying its product line. That is, management could divert some of the firm’s resources to the
extraction of some other commodity—silver, perhaps—
and to the extent that copper and silver prices do not move
in perfect unison, doing so would lower the firm’s net risk.
Secondly, the firm could try to manage its expenditures so that they would tend to increase when revenues
are high and fall when copper prices (and sales dollars)
are abnormally low. For example, the firm could shift
extraction methods away from those relying heavily on
capital assets (with their fixed costs) to those methods
depending more on labor or other inputs that would be
viewed as variable costs. Under this scenario, when copper prices increase the firm can hire more workers and
when prices fall unusually low they can lay off some of
the workforce. In this situation, fluctuations in
investors’ net income are less than if the firm uses a
more automated technology, which requires payments
on the machines whether copper prices turn out to be
high or low. Thus, changes in operating leverage could
be viewed as a form of risk management.
A third possibility would be for the firm to reduce its
leverage—its percentage of financial capital raised
through the sale of debt securities. In this case, fluctuations on the firm’s return on invested capital result in
smaller fluctuations in the return-to-equity capital. In
short, the firm’s choice of debt versus equity financing can
be viewed as a form of risk management.
Another way that management can alter the distribution of cash flows involves the use of derivative securities, so named because their price depends on the
price of some underlying instrument (such as stocks or
interest rates). While modern derivatives contracts can
be, in many ways, exceedingly complex, almost all these
types of instruments essentially consist of some combination of options and forward contracts. Moreover, the
claims are linked, in the sense that one can, for example, replicate the cash flows from a forward contract by
simultaneously buying certain options and selling others.2 Options are contracts that, for an up-front fee, give
the purchaser the opportunity, over some period of
time, to buy or sell something (for example, a share of

1. The examples discussed here focus on reducing risk. Of course, if managers wanted to increase the risk faced by a firm’s
shareholders, they could reverse these actions.
2. Cox and Rubinstein provide an excellent discussion of options and a detailed analysis of how the prices of these securities
are determined as a function of the prices of underlying securities. They also provide a concise treatment of the cash flow
replication idea discussed in the text (1985, 59–60).
Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W First Quarter 1998

B O X

If Derivatives Are Used to Hedge Risk, Why Do
Some Firms Lose So Much Money?
s there a significant downside to the use of derivatives in
risk management? A casual glance at press reports over
the past few years seems to indicate that derivatives are
excessively risky and, in fact, dangerous to the financial
health of corporations and other derivatives traders. Among
the most widely publicized derivatives debacles are the losses of Proctor and Gamble ($137 million) and Gibson
Greetings ($20 million) as a result of transactions in interest
rate swaps.1 Orange County, California, and the Orange
County Investment Pool (OCIP) declared bankruptcy in
1994 following a $1.7 billion drop in the market value of the
pool due to transactions in leveraged intermediate-term
fixed-income securities. And perhaps the most spectacular
example is the 1995 collapse of Barings Bank, a highly
respected British merchant bank, due to losses of $1.3 billion
on options and futures transactions in the Japanese stock
and bond markets. Barings financed the U.S. Louisiana
Purchase from France in the early nineteenth century and
was banker to the royal family. The collapse of such a historically significant financial institution was all the more surprising given that it reported record profits for 1994.
These examples reveal the truism that derivatives, like
other risky securities, can expose traders to the risk of substantial losses. However, the proper conclusion to be drawn
from these cases is not that derivatives should be avoided
but rather that participants should have the expertise and
oversight systems that would be common for other investment and trading activities. In each of the cases cited above,
the losses can be traced to inappropriate behavior on the
part of one or more parties involved in the derivatives transactions. Some authors (see, for example, Smith 1997) argue
that, at least in the case of Proctor and Gamble, lack of
expertise by managers in assessing market risk seems to
have played a role. However, both Proctor and Gamble and
Gibson Greetings collected substantial damages from the
counterparty in their interest rate swap contracts (Bankers
Trust Company). The Securities and Exchange Commission

(SEC) concluded that Bankers Trust had defrauded Gibson
Greetings, and the Proctor and Gamble case was settled out
of court. The SEC later cited Gibson Greetings for failing to
disclose properly its derivatives-related profits and losses.
The company was also sanctioned for having inadequate
internal controls to ensure that its derivatives transactions
were accounted for in accordance with generally accepted
accounting principles. In the case of Orange County, the
investment manager for the investment pool entered into
inappropriate speculative transactions.2 And, in the Barings
Bank case, inadequate supervision and controls allowed a
rogue trader to run up millions of dollars in losses while concealing his positions from superiors.
The message from recent derivatives debacles thus
seems clear: derivatives positions need to be carefully
designed and managed and controls should be in place to
ensure that positions taken are fully understood by and consistent with the objectives of the organization. The need for
expert management and control is the source of most of the
fixed costs of entering derivatives markets, discussed in the
text. That is, organizations planning to enter derivatives
markets must put in place a team of investment managers
who can structure an effective derivatives program, and
monitoring and control systems must be created that prevent fraud and mismanagement. Of course, the same cautionary message applies to other activities undertaken by
firms that involve substantial sums, such as investments in
new projects, capital structure decisions, and mergers and
acquisitions. In this regard, derivatives are not really different from other transactions conducted by firms. They are
simply newer, and therefore many firms have acquired less
experience in their management or have failed to implement appropriate accounting and control systems. The message from the derivatives debacles is that firms should
acquire the appropriate human expertise in the areas of
both trading and control before entering the market.

1. For more on the Proctor and Gamble and Gibson Greeting cases see Smith (1997) and Overdahl and Schachter (1995), respectively.
2. There is also evidence that mismanagement after the decline in the market value of OCIP exacerbated Orange County’s losses.
Miller and Ross (1997) suggest that OCIP was neither insolvent nor illiquid in December 1994. They argue that OCIP should not
have been liquidated and that the suspect financial instruments should have been held to maturity. This strategy would have
enabled the county to avoid some of its losses and realize substantial net cash inflows during 1995.
32

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W First Quarter 1998

stock), with the sale price fixed today. A forward contract is an agreement between two parties to engage in
a trade at some point in the future, with the terms of
trade (for example, the sale price) set today.3
Although derivatives problems have made the news
in recent times (see Box 1), they are no more or less
risk-management tools than the other available alternatives discussed above. Indeed, Peterson and Thiagarajan
(1997), among others, have argued that one cannot
meaningfully assess whether one firm is more or less
engaged in risk management without knowledge of all
important operating, financial, and accounting decisions. They find evidence in their case studies to suggest
that some managers use accounting practices that tend
to smooth earnings, along with decisions concerning
operating and financial leverage, as substitutes for trading in derivative securities.

Recent Advances in the
Theory of Risk Management
he puzzle the introduction outlined involves the
question of why managers of widely held corporations, acting in the interest of their stockholders,
should manage risk that their shareholders could presumably manage themselves. Given the nature of this
statement, the answer must, roughly speaking, lie in
one of two areas: either there are some risks that shareholders cannot manage for themselves as inexpensively
or managers are acting in their own interests, rather
than those of the stockholders of the firm. There are
proponents for each of these points of view, as discussed
below.
Managerial Motives for Risk Management.
Managers themselves may engage in risk-management
activities because they have disproportionately large
investments (their skills or human capital) in the firm
they manage and, unlike shareholders, cannot easily
diversify this personal risk. Being averse to risk, they are
concerned about negative shocks to profits, particularly
those that might bring the firm to the brink of bankruptcy. Bankruptcy or, more generally, times of financial distress are often associated with the replacement of
current management. Thus, these undiversified managers are in much the same position as the farmers discussed in the introduction, and they might well be willing
to engage in risk-management practices that will generate positive cash flows should the firm fall on bad times,
at the cost of reducing cash flows in the good times.

Consider again the firm primarily engaged in the
extraction of copper. According to traditional finance
theory (for example, Sharpe 1964), shareholders care
only about the systematic risk of their holdings, that is,
only that risk that cannot be eliminated by having small
investments in many different types of firms. Given that
hedging copper prices may be costly in terms of lower average future income (after
all, insurance is not typically free), stockholders
would not be inclined to
While modern derivatives
support actions by mancontracts can be, in many
agement that reduce
ways, exceedingly complex,
risk that is viewed as
diversifiable; namely,
almost all these types of
they would not share
instruments essentially
management’s consterconsist of some combinanation about the financial difficulties or even
tion of options and forward
the failure of one particcontracts.
ular corporation. Smith
and Stulz (1985) provide
formal discussions of
this issue. It is also intuitively clear why the manager would favor such activities—job protection. To the extent that managers have
an excess investment in human capital in the firm and
it is costly to transfer these skills should they need to
seek other work, they have an economic incentive to
have the firm continue as a going concern.
Shareholders may tolerate such potentially valuereducing activities if their managers are viewed as having
other unique value-enhancing skills, bankruptcy is not
costless, managers demand higher compensation in
return for the risk they face, or confronting management
is costly in terms of time and effort. Individual shareholders with, by design, relatively small stakes involved in a
given firm may simply attempt to “free ride” and hope that
some other group of stockholders will take up the cause
of replacing management. But, of course, the other shareholders may be thinking the same thing, and often no
action is taken.4
Rationales for Risk Management that Enhances
Value. Numerous reasons have been put forth to argue
that it really may be in shareholders’ interests for certain types of enterprises to manage risk. The following
is an incomplete sampling of the specific rationales, but
the two general points are that there may be some risks

3. In some cases the terms of trade allow one or another of the parties some latitude concerning, for example, what exactly will
be exchanged.
4. Of course, if things get bad enough in terms of too many value-reducing activities, outsiders with large amounts of capital
may try to take over the firm, for example, by offering to buy up the shares of the firm’s stockholders. Grossman and Hart
(1981) note that there is a free rider problem here as well (“I will not sell my shares now. Rather, I will hold my shares until
the new management improves firm performance and then sell at a profit.”).
Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W First Quarter 1998

that are not tradable and that there exist situations in
which there are informational differences among owners and managers. The existence of nontradable risk
limits the degree of homemade diversification that
shareholders can achieve; managing these risks is not
something the shareholders can do for themselves.
Informational differences can result in undervaluation
of some firms, which is clearly not in the interests of the
corporation’s shareholders.
What are some of the noninformational frictions
that might lead to a demand for risk management?
First, whatever the underlying, value-related motive for
risk management, the existence of fixed costs associated with using derivative instruments may make it more
likely that only larger firms, with the resources to pay
these large up-front costs, will manage risk through
derivatives trading.5 Second, if bankruptcy or financial
distress imposes costs on the firm, shareholders may be
willing to hedge profits in an effort to forgo these costs
(see for example, Smith and Stulz 1985). These costs
include both the direct legal and regulatory costs of
bankruptcy as well as the indirect costs resulting from
deteriorating relationships with key employees, suppliers, or customers. The indirect costs can have an
adverse impact on the firm’s cash flows even in the
event bankruptcy is not the ultimate outcome. This
dynamic suggests that firms with more fixed obligations—for example, debt obligations—will be willing to
hedge more, other things held constant (see Brennan
and Schwartz 1988).
It is also the case that many tax write-offs, such as
depreciation, are not independently tradable, although
they may be carried forward. However, given the time
value of money, it may make sense for the firm to hedge
against situations (for example, extremely low copper
prices) in which it cannot exploit its tax deductions
because income is low or negative.6 Furthermore, the
very fact that, other things held constant, corporate
taxes are increasing at a nondecreasing rate in beforetax corporate profits provides another potential motivation for hedging. Smith and Stulz (1985) show that the
firm can minimize its expected tax bill by keeping the
volatility of income low (staying in the middle of the tax
schedule). For example, given today’s corporate tax
code (and ignoring the alternative minimum tax), a
firm with a fifty-fifty chance of having taxable income of
$70,000 or $0 will have an expected tax bill of $6,250
while one with a sure taxable income of $35,000 will pay
a tax of $5,250, an expected tax savings of $1,000.7 While
this factor might appear to be unimportant for most corporations (the marginal tax rate flattens out at taxable
income of around $18,000,000), Graham and Smith
(1996) provide evidence that, because of factors such
as tax-loss carry provisions, tax effects may be more pronounced than would appear at first glance, especially
34

for firms whose before-tax incomes tend to fluctuate
between large positive and negative values.
In both of the above cases, shareholders might rationally support managers in their attempt to moderate
income fluctuations by using risk-management tools, such
as locking in at least some component of future income by
being short forwards or futures contracts in copper or
reducing fixed costs so that there is less fluctuation in
pretax income. Using the same reasoning as above, firms
that finance themselves with generally illiquid, if not outright nontradable, debt securities (for example, privately
placed bonds) or hold particularly illiquid assets (such as
collateralized mortgage obligations with unconventional
repayment schedules) might find hedging their fluctuations in income or value worthwhile.
One might be tempted to ask why, if a firm is fundamentally sound but in temporary distress, managers do not
simply keep these assets and liabilities on the books and
raise additional outside funds. Froot, Scharfstein, and
Stein (1993) argue that in a world of differential information between managers and potential outside investors,
firms may encounter situations in which funds are needed but outside capital either is not available or is too
costly. In such a case, managers may increase the current
value of their firms by entering into contracts (the example they use is forward contracts) that generate positive
payoffs when the firms’ cash flows from operations turn
out to be low.
The essence of the argument by Froot, Scharfstein,
and Stein and others is that if there is asymmetric information between those who manage the firm and outside
investors, better-than-average firms will have to sell
securities to outsiders at a discount (less than the fullinformation value of the claims on the firm). By engaging in risk-management activities, these firms can avoid
having to go to capital markets to acquire funds during
a period of temporarily poor performance. This follows
from the fact that their risk-management contracts are
designed to pay off when the firm is otherwise doing
poorly.8 Notice, however, that if the firm keeps relatively large cash balances, there is less need to worry about
times when the company is “short cash,” and one would
therefore expect larger levels of liquidity to be associated with less risk-management activity.

What Kinds of Firms Manage Risk
and Why Do They Do It?
s mentioned earlier, managers can manage risk
using a wide variety of tools. However, unlike
some traditional methods, like changing operating or financial leverage, derivative securities exist only
for purposes of risk management. Tests with these data
therefore provide somewhat “cleaner” results concerning why firms may choose to engage in risk management.9 It is also the case that the volume of activity in

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W First Quarter 1998

derivatives contracts has grown dramatically over the
past two decades. Box 2 provides some details on the
overall growth of derivatives transactions and some summary data concerning what firms are actually engaging
in these transactions. With these points in mind, this
section first provides a review of results from some
recent empirical studies that test the primary theoretical hypotheses relating to why firms actually do (or do
not) use derivative securities for risk management.
Why Firms Manage Risk. A major study investigating the question of motive is by Tufano (1996), who
looks at managerial compensation schemes and hedge
ratios in the gold mining industry in an attempt to contrast managerial motives with those associated with
value-maximizing theories of risk management. Hedge
ratios are usually defined as the percentage of expected
future production that the firm has effectively sold
short through risk-management activities: in this case
the firm is using derivative securities like short futures
positions (that is, agreeing to sell gold forward with the
price fixed today) or the purchase of put options (purchasing the right to sell gold in the future at a price
fixed today) on gold.
Tufano argues that risk-averse managers whose compensation comes in large part through acquiring shares in
the firm will want to hedge their risk. As discussed at
length earlier, such a policy would not necessarily benefit
diversified shareholders, so, to the extent that there are
costs associated with hedging, the manager is better off
and the shareholders worse (or at least no better) off than
if the firm abstained from risk management altogether. He
contrasts these managers with those who earn a relatively
large portion of their compensation through the granting

of stock options (call option contracts on the stock of the
firm). In this situation managers can walk away from the
options should the firm do poorly, but if the firm does well
their positions will provide high payoffs. In a “heads
I win, tails you lose” environment like this, even riskaverse managers would be more willing to tolerate gold
price, and therefore earnings, fluctuations. Thus,
they would find it less
advantageous to hedge.
Tufano finds supThe evidence from studies
port for this hypothesis
in the data. In particular,
investigating the decision
his evidence suggests
by financial companies to
that managers with high
use derivatives as a way
option holdings manage
risk less than those with
to avoid financial distress
high stock holdings. Such
costs is mixed.
results are consistent
with the managerial riskaversion hypothesis of
risk management.10 Tufano claims to find almost
no evidence in favor of the various rationales that would
make risk management a value-maximizing decision and
thus in the interests of shareholders. He does find, however,
that firms with large cash balances tend to manage risk less.
This finding is consistent with the hypothesis that firms
with less risk of having to seek outside financing, other
things being the same, will hedge less.11
Contrary to Tufano’s results, some authors have
provided evidence that they believe is consistent with
value-maximization theories of risk management. The

5. However, there is an offsetting notion that suggests that larger firms have more built-in diversification (more independent
product lines) and therefore should have less need for the services provided by risk management. This hypothesis would be
the alternative associated with the fixed-cost idea discussed in the text.
6. MacMinn (1987) provides a rigorous analysis of this issue.
7. These calculations follow from the fact that the first $50,000 in taxable income is taxed at the rate of 15 percent, while the
income between $50,000 and $70,000 is taxed at a rate of 25 percent.
8. Froot, Scharfstein, and Stein argue that another condition needed for this type of hedging to be valuable is that the firm’s
production function display decreasing returns to scale—that is, the firm’s output is increasing in its inputs but at a
decreasing rate. Alternative assumptions can substitute for this condition. For example, any type of asset that is indivisible
(for example, it is difficult to sell one office in an office building), when combined with the scenario of asymmetric information, will do the job in the sense that a firm might rationally want to hedge against the possibility that they might end
up having to sell all this valuable asset at an unfavorable price when they only need a small amount of cash to pay creditors or invest in some new growth opportunity.
9. However, even these are not perfectly unambiguous tests since it is difficult to control for all of the other risk-altering strategies undertaken by the managers of these firms.
10. As a substitute for these actions, managers could hedge their risk on their own personal accounts. However, effectively hedging the risk of adverse movements in the stock of the firm may require, for example, managers to short sell the stock of the
firm for which they work. This, or economically similar actions such as buying puts on the firm’s stock, may be contractually prohibited or, at a minimum, send a bad signal to outside shareholders. Therefore, managers may choose to avoid hedging on personal accounts. Moreover, even if trading in, say, gold futures may not be prohibited, it is still the case that
transacting at the firm level spreads the transactions costs across all shareholders.
11. Mian (1996), using a larger set of industrial firms, finds a similar negative relationship between the level of liquid balances
and the degree of risk-management activities on the part of corporations.
Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W First Quarter 1998

B O X

The Growth of Derivatives
he worldwide derivatives market has grown dramatically in the last decade to become a significant component of the world’s financial markets. A 1996 survey,
conducted by twenty-six central banks, estimated the
worldwide volume of derivative contracts, measured as the
total notional value of derivative contracts outstanding,1 to
be approximately $55.7 trillion as of the end of March 1995
(Bank for International Settlements 1995). The market
value of the potential cash flows from these contracts was
estimated to be approximately $2.2 trillion.
To get a better idea of how fast the market for derivatives has grown over the last decade, consider the chart,
which displays the total worldwide notional value of all privately negotiated interest rate swap, interest rate option
(including caps, floors, collars, and swaptions), and currency swap contracts outstanding over the period from
1987 to 1996. Based on the data in the chart, the average
yearly growth rate of the notional value of these contracts
is more than 40 percent annually. Likewise, in the United

States, the growth rate of derivative transactions by banks,
insurers, and securities firms also has been impressive.
Although not quite as high as the worldwide rate, the average annual growth rate of the notional value of derivative
contracts outstanding over the 1990–95 period for the fifteen largest over-the-counter derivatives dealers in the
United States was 27 percent, as reported by the U.S.
General Accounting Office (1997).
One of the reasons for such impressive growth rates in
the volume of derivative transactions has been the everincreasing demand for financial risk-management products
by corporations. Although corporations from most industries report only very sketchy details of their risk-management strategies, there is a growing consensus that more and
more firms are managing their exposure to various financial
risks using derivative contracts. The top panel in the table
reports the percentage of nonfinancial firms using derivatives contracts according to several recent empirical studies. For example, Dolde (1993) reports that 85 percent of

TA B L E A

Users of Derivative Instruments

Author/Study
Nonfinancials
1992 Mian
1992 Dolde Survey
1994 Wharton/Chase Survey
1995 Wharton/Chase Survey
Banks
Sinkey and Carter

Insurance Companies
Cummins, Phillips, and Smith

Firms Included/Surveyed

Percentage of
Firms Reporting
Derivatives Use

All nonfinancial firms with data on both LEXIS/NEXIS
and Compustat. Number of firms: 3,022
Survey of Fortune 500 companies
Number of respondents: 244
Survey of 2,000 nonfinancials not including Fortune 500
companies. Number of respondents: 530
Survey of 2,500 nonfinancials including Fortune 500
companies. Number of respondents: 350
All U.S. commercial banks, 1991
Number of banks: 11,308
U.S. commercial banks with assets > $1 Billion, 1991
Number of banks: 353
All U.S life/health insurance companies, 1994
Number of life/health insurers: 1,202
All U.S life/health insurance companies with assets >
$1 Billion, 1994. Number of life/health insurers: 193
All U.S property/casualty insurance companies, 1994
Number of property/casualty insurers: 1,664
All U.S property/casualty insurance companies with assets >
$1 Billion, 1994. Number of property/casualty insurers: 112

25.5
85.0
35.0
41.0

5.4
75.9

9.8
42.0
6.7
30.4

Sources: Bodnar, Hayt, and Marston (1996); Cummins, Phillips, and Smith (1997a); Dolde (1993); Mian (1996); and Sinkey and
Carter (1994).

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W First Quarter 1998

B O X

( C O N T I N U E D )

CHART A

Total Notional Value of Interest Rate Options, Interest Rate Swaps,
and Currency Swaps Outstanding, 1987–96

N o t i o n a l Va l u e ( $ B i l l i o n )

30000

20000

Interest Rate Options
Interest Rate Swaps
Currency Swaps

10000

1987

1990

1993

1996

Source: International Swaps and Derivatives Association, Inc.

the Fortune 500 companies responding to his survey use
derivatives to manage their risk exposure.
There are a number of rationales for the increased
demand for financial derivatives at the corporate level.
First, it could be argued that it is less costly to write these
contracts than it is to change the firm’s operating or financial leverage. If this argument is true, the same features
would make these instruments useful for managers who
are prepared to take on additional risk with the hope of
generating additional profits. For example, an insurance
company may try to achieve a higher yield on its asset portfolio by investing in long-term, low-grade bonds. By purchasing such a security the insurer has an exposure to both
movements in interest rates and movements in the credit
quality of the borrowers. This net exposure can, however,

be altered by purchasing interest rate derivatives, leaving
the insurer with credit risk but not interest rate risk.
A second rationale for increased volume could involve
the seminal work of Black, Scholes, and Merton on the
pricing of options. These studies were published in the
early seventies, about the same time that exchange-traded
options were introduced in Chicago. Prior to this work,
there did not exist a rigorous understanding of how to
accurately price or use derivative securities. When combined with the fact that volatility in asset and commodity
prices increased dramatically in the 1970s, ’80s, and ’90s
(when compared with the earlier postwar years), one has
all the ingredients needed to make these the popular
financial instruments that they are today.

1. The notional value of a derivative contract is analogous to the par, or face, value of an underlying contract as it is used to calculate the cash flows that change hands. It is not, however, necessarily the amount that is exchanged.
Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W First Quarter 1998

results of various studies investigating the primary
value-maximization rationales are presented below.
Mitigation of Financial Distress Costs. Numerous
authors have investigated whether firms more likely to
incur financial distress costs engage in risk management in
an effort to reduce the probability of incurring these costs.
The evidence is not persuasive for nonfinancial companies.
An early study by Wall and Pringle (1989) reports that firms
with lower credit ratings
are more likely than
higher-rated firms to
use derivative contracts
Among the explanations
known as swaps.
that have been advanced to
Other authors have
justify risk management as
considered the more
general question of
a value-maximizing decision
whether the firm’s capiis the need to mitigate the
tal structure is related
costs of financial distress,
to the likelihood that
the firm will engage in
minimize taxes, and avoid
risk management via
costly external finance.
derivatives contracting.
For example, neither
Mian (1996) nor Nance,
Smith, and Smithson
(1993) report any evidence to suggest that derivatives
trading is related to the capital structure of the firm. A
more recent study by Geczy, Minton, and Schrand (1997)
investigates the relationship between the capital structure
of the firm and the decision to manage foreign currency
exposures using derivatives. This study differs from its predecessors as the authors recognize the simultaneous
nature by which managers make capital structure and
risk-management decisions for their firms. Even after
incorporating the joint decision-making process of managers in their estimation procedure, the authors conclude
that there does not appear to be a relationship between
the decision to use derivatives and capital structure
choice.
One exception to these studies of nonfinancial firms
is Dolde (1996). He finds that after controlling for the
firm’s underlying exposure to various financial risks, there
is a significant complementary relationship between risk
management and the leverage of the firm. That is, highly
leveraged firms are more likely to use derivatives to avoid
the expected costs of financial distress.
The evidence from studies investigating the decision
by financial companies to use derivatives as a way to avoid
financial distress costs is mixed. Sinkey and Carter
(1994) provide only weak evidence suggesting that the
capital structure and risk-management decisions of U.S.
commercial banks are related. Likewise, Gunther and
Siems (1995) report no significant relationship between
the decision to use derivatives and the capital structure of
the firm. In addition, focusing on only those banks that
38

are active in derivatives markets, Gunther and Siems note
that banks reporting a higher volume of derivatives activity also have higher capital ratios. This result is in fact
inconsistent with the financial distress hypothesis, at
least as it is usually defined in the literature. Cummins,
Phillips, and Smith (1997b) find a similar result regarding
the volume of derivatives activities for U.S. life/health
insurers although they also report a significant and negative relationship between the capitalization level of both
life/health and property/casualty insurers and the decision
to use derivative securities, consistent with the financial
distress hypothesis.
Use of Risk Management to Lower Expected Tax
Burdens. Evidence on using risk management via derivatives contracting as a way to lower the firm’s expected tax
burdens is more convincing. Nance, Smith, and Smithson
(1993) conducted one of the earliest empirical studies
investigating whether taxes were a significant determinant of a firm’s decision to transact in derivative markets.
From their sample of nonfinancial companies, they
conclude that firms with higher investment tax credits
are more likely to engage in derivative transactions.
Cummins, Phillips, and Smith (1997b) also find evidence
consistent with the tax hypothesis. For the life insurance
industry, they report a significant and positive relationship between the decision to participate in derivative
markets and proxies for insurers having tax-loss carry forwards. They also find a positive relationship between
derivatives usage and proxies for having net income in the
progressive region of the tax schedule. Finally, a paper by
Graham and Smith (1996) develops a simulation model to
empirically determine the convexity of the tax schedule
faced by a large sample of COMPUSTAT firms. They conclude that approximately 50 percent of the firms in their
sample face convex tax schedules and therefore have an
incentive to reduce the volatility of their income stream.
They use the estimated simulation model and report that,
for the subsample of companies that they estimate are
facing convex tax functions, a 5 percent reduction in the
volatility of the firm’s taxable income stream leads to a 4.8
percent reduction in their expected tax liability.
Avoiding Costly External Financing. A number of
authors have found strong evidence documenting that
firms use derivatives to reduce the variability of their
income stream and thus help ensure that adequate
internal funds are available to take advantage of attractive projects. Gay and Nam (1997), for example, investigate nonfinancial companies’ use of derivatives and
provide test results consistent with the hypothesis that
firms with both low levels of liquidity and high growth
opportunities, as measured by the ratio of the market
value to the replacement value of the firm, tend to
hedge more. This finding is consistent with managers’
trying to mitigate the need to seek costly external funds
or lose their opportunity to invest in valuable projects.12

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W First Quarter 1998

Other authors have found similar results. Studies of
nonfinancial firms by Geczy, Minton, and Schrand
(1997) and Nance, Smith, and Smithson (1993) both
found that companies with less liquidity or companies
that use less preferred stock, as opposed to using
straight debt, are more likely to use derivatives to avoid
circumstances under which a shock to the internal capital resources of the firm might force the company to
forgo profitable projects.
A recent study by Ahmed, Beatty, and Takeda
(1997) investigating 152 U.S. commercial banks also
finds support for the costly external finance hypothesis.
The authors report that banks with less liquidity are
more likely to use derivatives to manage their exposure
to various price risks. Finally, Cummins, Phillips, and
Smith (1997a, 1997b) report that insurers with large
proportions of their assets invested in illiquid markets,
such as real estate for the property/casualty insurers or
privately placed bond and collaterialized mortgage
obligations for life insurers, are more likely to hedge the
volatility of their income using derivatives.

Conclusion
his article has provided a review of the rationales
that are often put forth concerning why corporations might engage in the practice of actively
managing their exposure to a wide variety of risks—socalled risk-management practices. One school of
thought is that managers attempt to reduce the volatility of cash flows because managers are personally
averse to risk and their compensation is often tied to
the firm’s performance. Others have argued that managers attempt to overtly alter the risk profiles of their
firms in an effort to increase the value of the firm’s
shares. However, basic finance theory says that, absent

frictions in capital markets, shareholders can manage
their own risk exposure. Thus, the value-maximization
rationale for the use of derivatives requires some specific notion of important market imperfections because
the use of insurance of this type is typically not free.
Among the explanations that have been advanced to
justify risk management as a value-maximizing decision
is the need to mitigate the costs of financial distress,
minimize taxes, and avoid costly external finance.
The discussion of the empirical literature on risk
management focuses on one particular set of tools,
namely, derivative securities. These contracts exist only
for purposes of risk management and, as such, provide
a natural set of data from which to glean managers’
motives for changing the distribution of future cash
flows. Tufano (1996) has provided some evidence from
the gold mining industry that is consistent with the idea
that managers use derivatives to reduce the volatility of
their own income stream. Thus there is some evidence
consistent with the managerial demand for risk management. On the other side of this question, the empirical evidence on the relationship between derivatives
transactions and firm value has so far been mixed.
However, there is a growing body of literature that suggests that at least a portion of total derivatives contracting is related to activities known to increase firms’
value—for example, avoiding costly external finance
and lowering expected tax bills. Further research on
this question is important because it gets to the heart of
whether or not derivatives in particular, and risk-management techniques in general, are being used to
enhance value in underlying securities markets or to
provide benefits to parties other than the shareholders
of the firm.

12. The market-to-replacement value (or Tobin’s Q) is a measure of growth opportunities used by a number of researchers. The
logic is that if investors are willing to pay more than what it would cost to start the firm over, then they must believe that
the firm’s future prospects are valuable in an economic sense.
Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W First Quarter 1998

REFERENCES
AHMED, ANWER S., ANNE BEATTY, AND CAROLYN TAKEDA. 1997.
“Evidence on Interest Rate Risk Management and Derivatives
Usage by Commercial Banks.” University of Rochester
Working Paper, July.
BANK FOR INTERNATIONAL SETTLEMENTS. 1995. Central Bank
Survey of Derivatives Market Activity. Basel.
BODNAR, G.M., G.S. HAYT, AND R.C. MARSTON. 1996. “1995
Wharton Survey of Derivative Usage by U.S. Non-Financial
Firms.” Financial Management 25:113–33.
BRENNAN, MICHAEL, AND EDWARDO SCHWARTZ. 1988. “The Case
for Convertibles.” Journal of Applied Corporate Finance
1:55–64.
COX, JOHN, AND MARK RUBINSTEIN. 1985. Options Markets.
Englewood Cliffs, N.J.: Prentice Hall.
CUMMINS, J. DAVID, RICHARD D. PHILLIPS, AND STEPHEN D. SMITH.
1997a. “Corporate Hedging in the Insurance Industry: The
Use of Financial Derivatives by U.S. Insurers.” North
American Actuarial Journal 1:13–49.
———. 1997b. “Derivatives and Corporate Risk Management:
Participation and Volume Decisions in the Insurance Industry.”
Paper presented at the 1997 conference of the International
Association of Financial Engineers, Boston, September 22–24,
1997.
DOLDE, WALTER. 1993. “The Trajectory of Corporate Financial
Risk Management.” Journal of Applied Corporate Finance
6:33–41.
———. 1996. “Hedging, Leverage, and Primitive Risk.”
Journal of Financial Engineering 4:187–216.
FROOT, KENNETH A., DAVID S. SCHARFSTEIN, AND JEREMY C. STEIN.
1993. “Risk Management: Coordinating Invest-ment and
Financing Policies.” Journal of Finance 68:1629–58.
GAY, GERALD D., AND JOUAHN NAM. 1997. “The Under-investment
Problem and Derivatives Usage by Corpora-tions.” Paper presented at the 1997 conference of the International Association of Financial Engineers, Boston, September 22–24, 1997.
GECZY, CHRISTOPHER, BERNADETTE A. MINTON, AND CATHERINE
SCHRAND. 1997. “Why Firms Use Currency Derivatives.”
Journal of Finance 52:1323–54.
GRAHAM, JOHN R., AND CLIFFORD W. SMITH. 1996. “Tax Incentives
to Hedge.” University of Rochester Working Paper, September.
GROSSMAN, SANFORD J., AND OLIVER D. HART. 1981. “The
Allocational Role of Takeover Bids in Situations of
Asymmetric Information.” Journal of Finance 36:253–70.
GUNTHER, JEFFERY W., AND THOMAS F. SIEMS. 1995. “The
Likelihood and Extent of Bank Participation in Derivative
Activities.” Federal Reserve Bank of Dallas Working Paper,
May.

MACMINN, RICHARD D. 1987. “Forward Markets, Stock Markets,
and the Theory of the Firm.” Journal of Finance 42:1167–85.
MIAN, SHEHZAD L. 1996. “Evidence on Corporate Hedging
Policy.” Journal of Financial and Quantitative Analysis
31:419–39.
MILLER, MERTON H., AND FRANCO MODIGLIANI. 1961. “Dividend
Policy, Growth, and the Valuation of Shares.” Journal of
Business 34:411–33.
MILLER, MERTON H., AND DAVID J. ROSS. 1997. “The Orange
County Bankruptcy and Its Aftermath: Some New Evidence.”
Journal of Derivatives 4:51–60.
MODIGLIANI, FRANCO, AND MERTON H. MILLER. 1958. “The Cost of
Capital, Corporation Finance, and the Theory of Investment.”
American Economic Review 48:261–97.
NANCE, DEANA R., CLIFFORD W. SMITH JR., AND CHARLES W.
SMITHSON. 1993. “On the Determinants of Corporate Hedging.”
Journal of Finance 68:267–84.
OVERDAHL, JAMES, AND BARRY SCHACHTER. 1995. “Derivatives
Regulation and Financial Management: Lessons from Gibson
Greetings.” Financial Management 24:68–78.
PETERSON, MITCHELL A., AND S. RAMU THIAGARAJAN. 1997. “Risk
Measurement and Hedging.” Northwestern University, J.L.
Kellogg Graduate School of Management,Working Paper.
SHARPE, WILLIAM. 1964. “Capital Asset Prices: A Theory of
Market Equilibrium under Conditions of Risk.” Journal of
Finance 19:425–42.
SINKEY, JOSEPH F., AND DAVID CARTER. 1994. “The Determinants
of Hedging and Derivatives Activities by U.S. Commercial
Banks.” University of Georgia Working Paper presented at
the American Finance Association Annual Meeting,
Washington, D.C., January 6, 1995.
SMITH, CLIFFORD W., JR., AND RENE M. STULZ. 1985. “The
Determinants of Firms’ Hedging Policies.” Journal of
Financial and Quantitative Analysis 20:391–405.
SMITH, DONALD J. 1997. “Aggressive Corporate Finance:
A Close Look at the Proctor & Gamble/Bankers Trust
Leveraged Swap.” Journal of Derivatives 4:67–79.
TUFANO, PETER. 1996. “Who Manages Risk? An Empirical
Examination of Risk Management Practices in the Gold
Mining Industry.” Journal of Finance 51:1097–137.
U.S. GENERAL ACCOUNTING OFFICE. 1997. “Financial Derivatives:
Actions Taken Since May 1994.” Washington, D.C.
WALL, LARRY D., AND JOHN PRINGLE. 1989. “Alternative
Explanations of Interest Rate Swaps: An Empirical Analysis.”
Financial Management 18:119–49.

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W First Quarter 1998

The Impact of Fraud
on New Methods of
Retail Payment
W I L L I A M R O B E R D S
The author is a research officer in the macropolicy
section of the Atlanta Fed’s research department.
N MARKET ECONOMIES, PAYMENTS SYSTEMS PROVIDE CERTAINTY OF VALUATION IN EXCHANGE.

PEOPLE

SELLING GOODS OR SERVICES EXPECT MONEY IN RETURN, WHERE MONEY MEANS EITHER

CURRENCY OR A FINANCIAL CLAIM THAT IS WORTH A FIXED AMOUNT OF CURRENCY.

TO PROVIDE THIS

CERTAINTY, A SUCCESSFUL PAYMENTS MEDIUM HAS TO OVERCOME VARIOUS RISKS THAT ARE A NAT-

URAL PART OF THE PAYMENTS PROCESS.

An important risk associated with payments systems
is the risk of fraud. Fraud can occur because purchases
of goods typically involve at least three parties. The first
party, a buyer (sometimes referred to as a consumer),
wants to purchase some good or service from the second
party, a seller (or merchant). In modern economies, such
purchases are rarely accomplished by barter, or direct
trade of goods between buyers and sellers. Instead, the
buyer offers to transfer to the seller a claim on a third
party, an issuer.
Such transactions are preferable to barter because
it is easier for sellers to value such claims than to value
goods offered in barter. If, however, the issuer cannot be
physically present to verify the claim when it is transferred from buyer to seller, then there is always some
chance that the buyer may offer a fraudulent claim.1
Payments fraud takes on many forms, but most
cases of fraud consist of one of two types of misrepresentation. The first is an offer to exchange a claim where
none exists. For example, a buyer may write a check on
insufficient funds. The second type of misrepresentation
occurs when a buyer offers to transfer a claim that rightfully belongs to someone else. Examples of this type of
fraud include check forgery or use of a stolen credit card.
42

As these examples indicate, traditional payments
media such as currency, checks, and credit cards are not
exempt from the risk of fraud. Currency fraud (counterfeiting), check fraud, and credit card fraud are serious
problems, costing the U.S. economy billions of dollars
each year. But with each of these payments methods, the
problem of fraud has been kept at a manageable level so
that their overall integrity has been maintained.
This article explores the potential impact of fraud
on new forms of retail payment such as electronic cash
and stored-value cards. These new payments media
can increase economic efficiency by incorporating
advances in computer technology into payments systems. Payments systems based on these new media
communicate much of the same information as traditional payments systems but at a potentially lower cost.
Electronic payments systems have this advantage
because it is cheaper to move electrons than it is to
move paper. This natural advantage of electronic systems can be a disadvantage, however, when it comes
to the risk of fraud. Since computer data are readily
stored, copied, and manipulated, complex security procedures are needed to guarantee the integrity of electronic payments data.

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W First Quarter 1998

Will the risk of fraud hinder the development of the
new payments media? This article investigates this issue
by first considering which features of payments media
are conducive to fraud. The discussion then turns to
which of these features are also part of traditional payments systems. Finally, the article considers some new
payments media, how certain features of these media
differ from more traditional forms of payments, and
whether these features are likely to detract from the
acceptance of the new media in the marketplace.

The Optimal Incidence of Fraud
ny discussion of payments fraud should begin
from the basic economic principle of balancing
costs and benefits. That is, the benefits of measures designed to reduce fraud should exceed the costs
of such measures.
It is technologically possible to virtually eliminate
fraud in electronic payments, as has been demonstrated
by the experience of large-value, or wholesale, funds
transfer systems. Such systems, which are used by
banks and securities markets participants, are practically devoid of fraud. However, large-value systems typically make use of elaborate and costly security
measures (for example, using dedicated telephone lines
for all transactions) that would be excessively costly,
time-consuming, or otherwise inappropriate for retail
payments systems.
Thus, the key question for retail payments systems
is not whether fraud will occur but instead how much
fraud can be tolerated if the payments system is to
remain effective. While this amount will most certainly
be positive, both economic intuition and practical experience suggest that the optimal amount of fraud is relatively small. Intuitively, fraud is particularly injurious to
the provision of payments services because it detracts
from the essential quality of the service that is being
provided, which is certainty of valuation in exchange.
This intuition is backed by the experience with traditional payments media, for which fraud rates are far
from negligible but, nonetheless, relatively low.

Incentives for Fraud
he problem of fraud is common to all payments systems and dates back to ancient times. Nonetheless,
there are some types of transactions and some features of payments systems that are more likely than others to create incentives for fraud. Some of the key factors
influencing the risk of fraud are the following.

Face Value of the Claim. For fraud to be profitable, the reward from committing fraud has to be large
enough to offset the threat of punishments imposed by
the legal system. There is little incentive to create
fraudulent small-denomination claims such as coins. On
the other hand, transactions of sufficiently large value
are more likely to inspire the use of costly security measures, as noted above.
Verifiability. If the existence and ownership of a claim
can be instantly verified, say, through an on-line verification system, this ability
obviously reduces the
risk of fraud. Effective
verification systems are
costly to set up and operPayments systems based
ate, however.
on these new media
Anonymity of the
communicate much
Transaction. If a buyer
and seller do not have
of the same information
an ongoing business
as traditional payments
relationship, the incensystems but at a potentive for fraud increases.
The incentive for fraud
tially lower cost.
is also enhanced if the
ownership of the claim
offered in payment cannot be traced.
Point-of-Sale Transactions. If the seller can withhold delivery of the good until the claim can be verified,
then the incentive for fraud is reduced. If the good is
exchanged at the point of sale, there is always some chance
that the claim presented by the buyer is fraudulent.
Allocation of Losses. Perhaps the most critical
factor contributing to the incidence of fraud is the allocation of losses.
Suppose that a fraudulent transaction has occurred.
Who should bear the costs of the fraud? Note that to the
extent that prices must be raised in order to cover losses
from fraud, all market participants may end up bearing
some of the cost. However, having different rules concerning the allocation of loss from a particular incident
of fraud changes the distribution of losses among individual buyers, sellers, and issuers and hence affects the
incentives to commit fraud.
One possibility is that these costs are borne directly
by an individual buyer. This arrangement gives maximum
reassurance to the seller and to the issuer. In some cases,
however, the buyer and the legitimate owner of the transferred claim may be two different people. For example, in

1. A second possibility is that the seller could offer worthless merchandise, which is a potentially serious problem with some
forms of electronic commerce. Yet another possibility is that issuers could issue claims on worthless assets. New forms of
financial intermediation are not immune to this type of risk, as evidenced by the recent collapse of the European Union
Bank, an “Internet bank” based in Antigua (see Rohter 1997). Nonetheless, this article will focus on the first risk as the most
likely to affect acceptance of new payments media.
Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W First Quarter 1998

the case of a check forgery, the forger does not have ownership of the claim (deposit) apparently represented by
the forged check. And in point-of-sale transactions, the
buyer may be long gone by the time that a fraud is discovered. For these reasons it can be problematic to
assign the costs of fraud to buyers.
A second possibility is for the seller to bear the
costs of fraud. This arrangement protects the interests
of the buyer and the issuer, but it is unlikely to be popular with sellers.
The third possibility is that the issuer of the claim
bears the costs. This is clearly the most convenient
arrangement for the buyer and seller, but it is also the
most likely to promote fraud. Since the issuer is not present at the transaction, the legitimacy of a claim on the
issuer can never be verified with absolute certainty.
In spite of this disadvantage, there are many circumstances in which it makes sense for the issuer to
bear the risk associated with fraud. If the wealth of the
issuer is large, compared with that of the buyer (say, a
typical consumer) and the seller (say, a small business), then the issuer may be the party most prepared
to face such risks. A large issuer may also be able to
lessen exposure to fraud risk by diversifying this risk
over many transactions.
The above discussion suggests that the problem of
fraud will be greatest in cases involving large informational asymmetries between buyer and seller. Fraud is
more likely to occur when transactions involve large
amounts, when verification is costly, in anonymous
transactions, and in point-of-sale transactions. Fraud
will also be more likely in transactions in which at least
some of the costs of fraud can be shifted to the third
party, the issuer of the claim used for purchase.

Fraud and Traditional Payments Systems
urrency. The simplest traditional payments system is currency. In modern-day currency transactions, the role of issuer is played by a central bank
or sovereign government.2 The claim in this case is a
fixed-denomination note or coin that is considered a liability of the issuer. Payment is effected by physical transfer of the note or coin. Among traditional payments
systems, currency is unique in that a payment in currency does not need to be cleared and settled through the
banking system in order to constitute a valid payment.
Another distinguishing feature of currency is that it can
circulate indefinitely before it is returned to its issuer.
Fraud can occur in currency transactions if the
currency is counterfeit or stolen. The fact that currency
is a convenient, widely accepted, and anonymous medium for point-of-sale transactions in turn creates incentives for counterfeiting and theft.
Several factors serve to limit the risk from counterfeiting currency, however, at least within the United

States. The first is vigorous law enforcement; according
to the U.S. General Accounting Office (GAO) (1996), the
majority of counterfeit currency is seized before it can
be distributed. The second factor is that since all detected counterfeit currency is subject to seizure by law
enforcement authorities, a significant portion of the
costs of counterfeit fraud is borne by buyers and sellers.
The third factor is that currency is not widely used within the United States for transactions with a high dollar
value because other, more suitable payments systems
are widely available. Anyone attempting to pass a large
amount of counterfeit currency would be forced to use it
in a large number of small-value transactions.
The problem of theft also tends to be self-limiting.
Since currency is anonymous, a buyer holding a large
amount of cash is liable for its theft or loss. Consequently,
most people do not hold large amounts of currency.
Statistics on the incidence of counterfeiting are
difficult to obtain since counterfeit currency can circulate for some time without being detected. Available
statistics suggest that counterfeiting is not an economically significant problem in the United States. In 1994
the total amount of counterfeit currency detected by
law enforcement was less than one-tenth of 1 percent of
currency outstanding, most of which never reached circulation (GAO 1996, 11).
Checks. Payment by check is by far the most prevalent system for noncurrency retail payments in the United
States. In a check transaction, a buyer instructs a bank or
similar financial institution to transfer the buyer’s deposit
claim on a bank. The buyer does so by transferring an
order to pay, or check, to the seller. The seller or seller’s
bank then presents the check to the buyer’s bank for payment.3 In such a transaction, the bank plays the role of
issuer, although the check is considered a liability of the
buyer and not of the bank on which it is drawn.4
Checks are a natural target for fraud as they can be
written for large amounts, are relatively easy to alter or
forge, and can be difficult or costly to verify at the point
of sale. Check fraud has recently become a more serious
problem because of several factors. The first is the
widespread availability of computer technology, which
has made it easier to counterfeit checks (see, for example, Hansell 1994 or Nielsen 1994). The second factor
has been the funds availability schedules required by
the Expedited Funds Availability Act of 1987 (see Board
of Governors 1996b). The act requires that banks make
check funds available according to certain, preset
schedules. Consequently, banks must sometimes make
funds available before they can ascertain whether a
deposited check is fraudulent.
Despite these problems, there are certain factors
that have served to limit the incidence of check fraud.
The first and most important is the allocation of losses.
While the law governing the allocation of losses from

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W First Quarter 1998

check fraud is complex, the end result is that the liability for fraud often resides with the seller and not the
bank on which the check is drawn.5 For example, a merchant who accepts a check in a point-of-sale transaction
bears the loss if the check is returned for insufficient
funds.6 Likewise, if a check is stolen, a buyer can stop
payment on the check, again leading to potential losses
for the seller. As a result of this loss allocation, there is
widespread recognition of the potential for fraud in
check transactions and sellers are reluctant to accept
checks in situations that are conducive to fraud, such as
anonymous, point-of-sale transactions.
A second factor limiting the incidence of check
fraud has been the increased use of techniques such as
positive pay. Under a positive pay arrangement, a buyer
(typically a corporation) sends a list of issued checks to
the buyer’s bank. Only checks on the list are automatically paid by the bank. Any check not on the list requires
explicit approval by the buyer before it can be paid.
Positive pay has been an effective weapon against losses
resulting from check counterfeiting, forgery, and embezzlement, among others. A third factor has been the
Federal Reserve’s requirement for “large-dollar return
notifications.” That is, banks must provide prompt
notice of nonpayment on checks for $2,500 or more.
Prompt notice of nonpayment reduces the likelihood
that banks will provide provisional credit for fraudulent
checks before the fraud can be discovered.
As is the case with currency, available statistics suggest that check fraud is not a large enough problem to
significantly detract from the use of checks as a payments medium. Estimates of the total cost of check fraud
in the United States range as high as $10 billion annually (Hansell 1994). An extensive 1995 survey by the
Federal Reserve found that banks’ share of these losses
amounted to $615 million in 1995.7 While these figures
show that check fraud is a serious problem, these numbers are small compared with the total volume of check
payments in the United States, which was roughly $73.5
trillion for 1995 (Bank for International Settlements
1996b). The overall rate of check fraud loss is less than 2
basis points, or two-hundredths of 1 percent.8
Credit Cards. Credit cards are widely used in retail
payment situations, especially when informational asymmetries make payment by check impractical. In a credit
card transaction, the buyer pays for a purchase by draw-

ing on a line of credit from the credit card issuer. The
issuer pays the seller for the purchase, and the balance
on the credit card is then paid down by the buyer. Since
the claim presented in payment is considered a liability
of the credit card issuer, this type of transaction transfers much of the risk of insufficient funds in the original
transaction from the seller to the credit card issuer.
In cases of credit card theft or similar types of fraud,
cardholders’ liability is restricted by the Truth in Lending Act of 1968 and
corresponding Federal
Reserve Regulation Z.
Generally a cardholder’s
The key question for retail
liability is limited to $50
as long as the cardholder
payments systems is not
reports a lost or stolen
whether fraud will occur
card, and in practice the
but instead how much
liability is often less than
this maximum. The
fraud can be tolerated if
remaining liability is
the payments system is
shared between the sellto remain effective.
er, or merchant, and the
credit-card issuer. While
the rules governing the
apportionment of this
liability vary, the GAO
(1997, 114) reports that, on average, the vast majority (70
percent) of the liability is borne by the credit card issuers.
To limit incentives for fraud, the issuer’s liability is contingent on the merchant taking certain steps intended to
curtail fraud (for example, validating a credit card transaction through an on-line verification system).
The incidence of fraud in credit card purchases is
quite small in absolute terms but is relatively high as
compared with checks. While precise figures are unavailable for the credit card industry as a whole, one estimate
put total (gross) fraud losses at $2 billion to $3 billion in
1993 (Pearsall 1994), and another placed this figure at
$1.3 billion for 1995 (Fryer 1996). Given aggregate credit card use of $879 billion for 1995, the estimates imply a
fraud rate of between 10 and 20 basis points (0.1 to 0.2
percent). In the case of bank cards (MasterCard and
Visa), a study by the American Bankers Association
(1996) estimated total gross fraud loss for 1995 at $790
million versus purchases of $451 billion, implying a loss
rate of 18 basis points (0.18 percent).

2. Historically such notes were also issued by commercial banks. These notes are discussed on page 48.
3. For an introduction to details of check clearing and settlement, see GAO (1997).
4. Exceptions are traveler’s checks, cashier’s checks, and certified checks.
5. Generally the loss allocation is determined by Articles 3 and 4 of the Uniform Commercial Code.
6. Of course, in such cases the merchant is entitled to try to recover the amount of the check through legal action.
7. See Board of Governors (1996b, 5). A smaller survey by the American Bankers Association (1994) put this number at $815
million for 1993. Both numbers represent “gross losses,” that is, they do not incorporate any recoveries of lost funds.
8. This is an average rate for all checks, many of which are at low risk for fraud. The risk of fraud is substantially higher for
certain types of checks.
Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W First Quarter 1998

Note that the relatively high rate of fraud on credit cards does not reflect any inherent shortcoming of
credit cards as a payments medium. Rather, the fraud
rate on credit cards reflects the fact that credit cards
tend to be used in situations where incentives for fraud
are greater, particularly in point-of-sale transactions.
The acceptance of credit cards in such situations,
together with the fact that the card issuers bear the
majority of costs associated with fraud, help make credit cards a secure and convenient payments medium
from the standpoint of marketplace participants.
To limit the potential for fraud, credit card issuers
have invested heavily in on-line verification technology
and other technologies to detect fraudulent use (see
Fryer 1996 or Rutledge 1996). While this technology has
been effective, it is also costly: Caskey and Sellon
(1994) report that credit cards are the most expensive
medium for retail transactions.9
Debit Cards. Conceptually, a debit card transaction
closely resembles a check transaction. In a debit card
transaction, a buyer transfers deposit claims from the
buyer’s bank account to that of the seller, just as in a
check transaction. As with checks, this transfer is done as
a debit transaction, in which funds are “pulled” by the seller (via the card network) from a buyer’s bank account.
However, there are several key differences between
a debit card transaction and a check transaction. The
most important is that in contrast to most check transactions, the transaction itself is subject to an electronic verification process, which varies according to the
type of card.10 This verification process lessens the
credit risk associated with the transaction. A second
key difference is that a debit transaction is cleared and
settled electronically through the card issuer’s network
rather than through a traditional paper-based checkclearing process. That is, in contrast to checks, the
clearing and settlement of transactions does not have to
wait for physical delivery or presentment of checks but
can begin more or less immediately.
Debit card transactions also differ from credit card
transactions in that the amount of a purchase is automatically debited from the buyer’s bank account within
a few days of the time of purchase. By contrast, credit
card holders have to either pay for purchases after a
grace period or pay interest on the unpaid balance.
In cases of debit card fraud, cardholders’ liability is
limited by the Electronic Funds Transfer Act of 1978
and the corresponding Federal Reserve Regulation E.
Losses are capped at $50 if loss or theft of a debit card
is reported within two days and at $500 if the loss is
reported within sixty days. Recently the two main debit
card issuers, MasterCard and Visa, have announced
policies that place more stringent limits on cardholders’
liability (see Fickenscher 1997 and Keenan 1997).
Under these new policies, cardholders’ liability is gen46

erally limited to $50. Available estimates suggest that
the overall rate of fraud for debit card purchases is
quite low, comparable to that for credit card purchases
(Lunt 1996 and Keenan 1997).

Why Things Might Be Different with
New Payment Technologies
ecently a number of new retail payment technologies have become available (some of which are
still undergoing trial). Among the most widely discussed technologies are stored-value cards and a group of
technologies that fall under the term on-line payments.11
A stored-value card is a payment card similar in
appearance to a credit or debit card. To use a storedvalue card, a buyer must first purchase a card from an
issuer. The issuer then stores the value of this purchase
on the card itself, in the form of data contained on a
magnetic stripe or an electronic chip. A buyer can then
purchase goods by presenting the card to a seller, who
electronically transfers the value on the card to the seller’s card or account. The value on the card must eventually be redeemed by the issuer.
On-line payments technology includes a number of
important payments media, including on-line banking, online credit card payments, and electronic cash. On-line
banking allows consumers direct computer access to
banking services, either through “closed” networks such as
traditional Automated Teller Machine networks or, more
recently, through “open” networks such as the Internet.
Using on-line banking, a buyer can initiate payment in
much the same way as by writing a check. Clearing and
settlement of on-line payment instructions often takes
place via the automated clearinghouse system (the electronic interbank payments system for small-value transactions). In on-line credit card payments, a buyer initiates a
credit card transaction by sending the buyer’s credit card
information to a seller over a computer network (almost
always the Internet). Finally, payments can be made over
the Internet by transfer of electronic cash, a difficult-tocounterfeit series of electronic messages that represent a
financial claim on its issuer.12
In many ways, these new forms of payment closely
resemble traditional forms. For example, stored-value
cards have many features in common with travelers’
checks, and credit card payments over the Internet are
obviously not so different from credit card payments
made at the point of sale or over the telephone. There
are some features of the new payments media, however,
that are not incorporated into traditional modes of payment. Some of these may affect the incidence of fraud
and are discussed below.
One noteworthy feature of many of the new payments media (on-line credit card payments, some forms
of on-line banking, and electronic cash) is that they allow
for payments over the Internet, which is an open system

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W First Quarter 1998

of computer networks with few restrictions to access.13
The key advantage of the Internet over closed systems is
that it allows buyers and sellers low-cost access to a
greater range of transactions. While its open architecture
makes the Internet an appealing vehicle for electronic
commerce, this same openness offers opportunities for
counterfeiting and fraud. The fact that a buyer or seller
is on the Internet proves nothing in and of itself; additional verification of the transaction is required. For
example, buyers making credit card purchases over the
Internet need to convey enough information to show that
credit cards offered in payment are not counterfeit or
stolen. At the same time, sellers need to demonstrate
that they are selling a legitimate product and not just collecting credit card numbers for fraudulent use. And both
buyers and sellers need to safeguard against surreptitious monitoring of transactions by third parties. The
need to verify on-line transactions has led to the development of technologies such as the Secure Electronic
Transactions (SET) protocol (see, for example, Bloom
1997 or “Survey of Electronic Commerce” 1997). These
technologies are designed to allow buyers and sellers to
identify one another over the Internet and also to prevent
unwanted eavesdropping on private transactions.
A similar difficulty exists with stored-value cards.
These cards are designed to be used for small-dollarvalue transactions, particularly transactions in which
traditional methods of verification are too costly or otherwise impractical. Instead, verification is provided by
data contained on the card itself (perhaps in combination with on-line information). In this sense, stored-value
payments systems may be seen as an electronic analog of
currency, where validity of the payments medium is provided by visual inspection. As is the case with currency,
this feature of stored-value cards increases the incentives for counterfeiting and fraud. Stored-value systems
rely on electronic encryption technologies to protect
against counterfeiting and other fraudulent use.14
Incentives for fraud are magnified in the case of those
stored-value cards that allow for “peer-to-peer” transactions, that is, transactions among cardholders who do not

have access to on-line verification or clearing technologies. In this type of system, value can be successively transferred from one stored-value card to another without
outside verification. This feature can increase the time
interval between counterfeiting or possible fraudulent use
of the card and the subsequent detection of fraud when
the stored value is ultimately presented for redemption.
The issue of who bears the responsibility for fraud is
unresolved for many of the new payments media. For many
of these media, however,
there are strong justifications for the issuer
bearing the responsibiliThe general feeling
ty for losses due to
expressed by policymakers
fraud. The presence of
“network effects” in payis that the long-run benements technologies
fits to the development of
means that new forms of
new payments technologies
payment are unlikely to
be issued by a single
will outweigh any shortfinancial institution but
term difficulties associated
instead by consortiums
with their introduction.
of financial institutions,
data processing firms,
and so on, operating
under a single “brand
name.”15 A network effect occurs when the entrance of one
participant into a payments network increases the benefits or lowers the costs of participating in the network for
all other network members. For example, if only one merchant in a small town accepts a particular brand of storedvalue card, then consumers might not find it advantageous
to use this card, making it difficult for the card issuer to
recover costs. If, on the other hand, all the merchants in
the same town were to accept this card, then consumers
would be more likely to use the card regularly, which
would in turn increase its profitability. Since the usefulness and profitability of a branded payments network
depends heavily on its widespread acceptance, “branded”
networks have a natural incentive to absorb the risk associated with fraud losses.

9. Fraud represents a significant, though relatively minor, component of this cost differential. A more significant component
is the cost of delinquencies (failure to pay accounts due). Delinquencies in 1995 amounted to 3.55 percent of outstanding
credit card balances, according to the American Bankers Association (1996).
10. Debit cards may be either “on-line” or “off-line.” With on-line cards, a transaction is verified by comparing the purchase
amount against a buyer’s bank balance. With off-line cards, the transaction is verified by comparing the buyer’s total purchases over a certain period against a preset limit.
11. These technologies are extensively discussed in Congressional Budget Office (1996), U.S. Department of the Treasury (1996),
and GAO (1997).
12. Electronic cash is also known as e-cash, digital cash, electronic scrip, and electronic coins.
13. See McAndrews (1997a) for an introduction to the Internet and its potential uses in electronic commerce.
14. Encryption refers to the use of mathematical algorithms to convert data into a coded form. See Bank for International
Settlements (1996a) on the use of encryption in payments systems.
15. A detailed discussion of this scenario is laid out in McAndrews (1997b). More generally, see Weinberg (1997) on network
effects in payments systems.
Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W First Quarter 1998

Counteracting this incentive are potential difficulties
resulting from anonymity of some of the new payments
media, particularly for some stored-value cards. For example, if a stored-value card is issued anonymously there is no
way to identify the rightful owner of the card. It would thus
be difficult if not impossible for the issuer of the card to
stop payment on a lost or stolen card, given the current
design of stored-value systems.16 In such situations, users
of stored value cards would have an incentive to handle
these cards with the same care as if they were currency.

What Could Go Wrong?
recent episode in Japan provides some sobering
lessons concerning the potential for fraud over
new payments systems (see Glain and Shirouzu
1996 and Pollack 1996). This case concerns a stored-value
card designed by Sumitomo Corporation and Mitsubishi
Corporation, with the cooperation of Nippon Telephone
and Telegraph as well as various government agencies.
The cards were intended for use with pachinko, a type of
pinball game. One purpose of the cards was to limit criminal activities often associated with the pachinko parlors,
such as gambling, tax evasion, and money laundering.
The value on the cards was held in the form of data
stored on magnetic strips.17 Criminal organizations were
able to defeat the encryption by cloning, that is, by
transferring the data stored on existing cards to used
cards. The cloned stored-value cards were then taken to
pachinko parlors and redeemed for cash. Since the
stored-value issuers had no way to distinguish fraudulent transactions from legitimate transactions, they
were forced to absorb the resulting losses. Published
reports estimate the losses from this episode were at
least $600 million.
The pachinko fraud is instructive in that it illustrates the power of incentives. Although the pachinko
stored-value cards were heavily encrypted, various features of their design created strong incentives for fraud.
Apart from the obvious defect of being too easy to copy,
the cards were almost perfectly anonymous, were
designed for point-of-sale transactions, and were available in large denominations (of about $50 and $100).
Pollack (1996) reports that reductions in fraud were
achieved only after the card issuers both improved the
cards’ encryption technology and reduced the incentives
for fraud by eliminating large-denomination cards and
cracking down on pachinko parlor operators who had
apparently tolerated extensive use of cloned cards.18

Historical Lessons
arious analyses of new payments media (particularly stored-value cards and electronic cash) have
invoked comparisons of the new media with the
banknotes that circulated during the U.S. Free Banking
Era (1837–65).19 During this period, banks issued claims

V
48

in the form of bearer notes, which circulated much as
government-issued currency does today. Banknotes usually traded at par value locally but were often traded at
a discount in transactions that occurred at any distance
from the issuing bank.20 A major cause for this discounting was the fraud risk associated with counterfeit and
altered notes.21 Given that certain of the new electronic
payments media share a number of features with privately issued banknotes, would we expect a similar pattern of discounting to arise? The most likely answer to
this question is no, for at least two reasons.
First, Free Banking Era banknotes were particularly
attractive targets for fraud. Often the notes were available only in large denominations ($5 and up, the equivalent of roughly $80 today), they were widely used for
anonymous, point-of-sale transactions, and nonlocal
notes could only be verified at considerable cost and after
a lengthy delay.22 This unfortunate combination of features is not shared by any of the new payments media.
Second, Gorton (1996) shows that despite the
prevalence of fraud, the most serious risk to holders of
Free Banking Era banknotes, and hence the greatest
source of discounting, was not fraud risk but credit risk
associated with the issuer. In this case, credit risk refers
to the risk that a note would not be honored at full value
because of either the insolvency or illiquidity of the issuing institution. During the Free Banking Era, banknotes’
credit risk was exacerbated by a combination of poor
communications and restrictive banking laws. These
laws effectively prohibited banks from branching beyond
their home state or local area, thereby making it difficult
for banks to build effective coalitions in order to guarantee the value of their notes. In New England, where
banks were able to form such a regional coalition, discounting of notes on banks within the coalition was practically nonexistent.23 The experience of the New England
banks suggests that if the credit risk associated with a
payments instrument can be held in check, then fraud
risk is unlikely to lead to discounting of that instrument.
As discussed above, the “network” economics of the
new payments media are likely to limit credit risk associated with new forms of payment. Holders of stored-value
cards, for example, would prefer to use stored-value
cards that are readily acceptable in as many places as
possible. Providers of stored-value cards and similar payments systems therefore have incentives to form broad
coalitions with a widely recognizable brand name. The
members of such coalitions have strong incentives to
monitor each others’ credit risk in order to maintain
credibility of the brand.
Credit risk could also be eliminated by Federal
Deposit Insurance Corporation (FDIC) insurance of a
payment instrument. As of this writing, however, it
appears that FDIC insurance will not be provided for most
types of stored-value cards. The FDIC has also requested

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W First Quarter 1998

comment on the eligibility of certain other forms of electronic payment for deposit insurance; see FDIC (1996).
The Free Banking Era experience suggests that a
necessary downside of containing credit risk may be
increased fraud risk, however. According to Gorton
(1996, 370) the banknotes of established, creditworthy
banks were the most likely targets of counterfeiters.
Notes of less creditworthy banks were more likely to be
discounted and less likely to circulate, and hence they
were not worth the trouble.

Public Policy Concerns
n important challenge for policy in the area of new
payments technologies has been to promote
increases in efficiency associated with technological improvements while safeguarding consumers from
undue risks. To date, public policy toward new forms of
retail payment has been largely hands-off. The general
feeling expressed by policymakers is that the long-run
benefits to the development of new payments technologies will outweigh any short-term difficulties associated
with their introduction. The view has also been expressed
that premature regulation of new payments media may
hinder the development of potentially more efficient payments systems.24
In the case of stored-value cards, the Federal Reserve
has attempted to avoid excessive regulatory burdens on
new payments technology by proposing that Regulation E
not apply to certain types of stored-value cards (see Board
of Governors 1996a, 1997a). Currently, Regulation E
requires that consumers be provided written records for
electronic funds transfers and limits consumer liability to
$50 (see discussion above) when they use an “access
device” to withdraw or transfer funds from a “consumer
asset account.” While withdrawals from such an account in
order to load the stored-value card would be covered by
Regulation E, the proposed regulations would not be

extended fully to all transactions between buyers and sellers involving stored-value cards. For example, the Federal
Reserve proposal would exempt from these provisions all
cards containing $100 or less, as well as all cards that are
off-line and do not track individual transactions.
Another important
public policy issue in this
area has to do with potenPayments systems that
tial trade-offs between
security and privacy. As
make use of extensive
discussed above, one of
consumer-identifying inforthe factors affecting the
mation can lessen the incirisk of payment is the
anonymity of the transacdence of fraud . . . but the
tion. If a seller has access
value of such information
to enough information
in reducing fraud must be
about a potential buyer
(for example, the buyer’s
balanced against the value
current bank balance),
of privacy.
then the risk of fraud can
be minimized. On the
other hand, a seller’s need
for information about the creditworthiness of potential customers can conflict with the customers’ need for privacy.
This conflict of interest has become more acute in
recent years. Improvements in computing and communications technology have enabled the construction of
extensive computer databases of information on consumers.25 Widespread use of electronic payments media
could result in the creation of even more extensive databases, providing detailed information on the purchasing
habits of users of new payments media. While there
would be many legitimate uses of such information,
including abatement of fraud risk, its use could also
result in some loss of privacy.
In some cases, identifying information on consumers has served to enable, rather than to deter, fraud.

16. See Task Force on Stored-Value Cards (1997, 715–20) or Board of Governors (1997a, 52) for a discussion of these issues.
17. Stored-value cards that make use of data stored on magnetic strips are generally viewed as less secure than cards on which
the data is stored on an electronic chip.
18. While it was difficult to detect individual fraudulent cards during this episode, the widespread use of such cards was public knowledge. According to Pollack (1996), the scale of the fraud became evident when long lines of people would form outside of certain pachinko parlors, hours before the parlors were open for business.
19. See, for example, Greenspan (1996), Dwyer (1996), Rolnick, Smith, and Weber (1997), McAndrews (1997b), or Schreft
(1997).
20. Merchants used publications known as “banknote reporters” to keep track of the notes’ current market value.
21. See, for example, Dillistin (1949) or Gorton (1996) on the prevalence of note fraud during the Free Banking Era.
22. At the time, restriction of note issue to large denominations was thought necessary to lessen the incidence of note fraud; see
White (1995) for a discussion. The reasoning was that holders of small notes would lack sufficient incentive to check on
their authenticity. Another motive for restricting issue of small-denomination notes was the fear that their issue would lead
to inflation and ultimately to erosion of the gold standard; see Timberlake (1978, chap. 9). See Sargent and Wallace (1982)
for a modern interpretation of this view.
23. The regional coalition of New England banks was known as the Suffolk System. See, for example, Calomiris and Kahn
(1996) or Rolnick, Smith, and Weber (1997) on the operation of the Suffolk System.
24. See, for example, Blinder (1995), Kelley (1996), Greenspan (1996), and Kamihachi (1997).
25. See Board of Governors (1997b) or Bernstein (1997) for examples of commercially available data on consumers.
Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W First Quarter 1998

In these “identity theft” cases, criminals have been able
to use stolen information on a consumer to successfully
impersonate the consumer in credit card transactions,
loan applications, and the like.26
Both the need for privacy and the need to protect
consumers from fraud resulting from identity theft can
complicate the cost-benefit trade-off associated with
fraud risk. Payments systems that make use of extensive consumer-identifying information can lessen the
incidence of fraud, benefiting society. But the value of
such information in reducing fraud must be balanced
against the value of privacy, and recent cases of identity theft illustrate that such information may not always
be used in a socially benevolent fashion.

Conclusion
n important function of any payments medium is
to provide certainty of valuation in market
exchanges. One of the risks that must be overcome
by payments systems is the risk of fraud. Traditional payments media such as currency, checks, and credit cards
have effectively contained fraud risk to a level of 20 basis
points (0.2 percent) or less. To be successful in the marketplace, newer forms of payment will need to hold fraud
risk to similarly low levels.
Incentives for fraud increase when transactions are
made in large amounts, when transactions are made anony-

mously or at the point of sale, when claims cannot be effectively verified at the point of sale, and when issuers of payment claims bear the costs of fraudulent transactions.
While these features may be desirable in some situations in
that they allow for a greater range of transactions, they can
also encourage fraud. The recent Japanese experience
with stored-value cards illustrates that vigilance will be
necessary in such cases.
Some of the new payments media have been compared with the banknotes used during the U.S. Free
Banking Era. The banknotes were subject to substantial
fraud risk and were widely discounted. It is unlikely
that similar discounting will apply to new payment
instruments, however. Modern communications technology and changes in the organization of the banking
and payments industries should largely remove incentives for discounting.
Successful payments systems will also have to confront various trade-offs while addressing the problems
posed by fraud. These trade-offs include the need to balance the costs of fraud abatement measures with their
benefits, the need to balance security of payments systems with consumers’ desire for privacy, and the need to
encourage development of new, more efficient payments systems while ensuring equitable treatment of
participants in these systems.

26. One such identity theft is recounted by Vickers (1996).
50

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W First Quarter 1998

REFERENCES
GLAIN, STEVE, AND NORIHIKO SHIROUZU. 1996. “How Japan’s
Attempt to Slow Nuclear Work in North Korea Failed.”
Wall Street Journal, July 24, sec. A.

AMERICAN BANKERS ASSOCIATION. 1994. 1994 ABA Check Fraud
Survey. Washington, D.C.
———. 1996. 1996 Bank Card Industry Survey Report.
Washington, D.C.

GORTON, GARY. 1996. “Reputation Formation in Early Bank
Note Markets.” Journal of Political Economy 104 (April):
346–97.

BANK FOR INTERNATIONAL SETTLEMENTS. 1996a. Security of
Electronic Money. Basel.
———. 1996b. Statistics on Payments Systems in the Group
of Ten Countries. Basel.
BERNSTEIN, NINA. 1997. “Online, High-Tech Sleuths Find
Private Facts.” New York Times, September 15, sec. A.

HANSELL, SAUL. 1994. “New Breed of Check Forgers Exploits
Desktop Publishing.” New York Times, August 15, sec. A.

BLINDER, ALAN S. 1995. Statement before the Subcommittee
on Domestic and International Monetary Policy, U.S. House
Committee on Banking and Financial Services, October 11.
BLOOM, JENNIFER KINGSON. 1997. “Visa and MasterCard Publish
SET Protocol for Internet.” American Banker, June 5.
BOARD OF GOVERNORS OF THE FEDERAL RESERVE SYSTEM. 1996a.
“Electronic Funds Transfers.” Federal Register 61 (May 2):
19696–705.

KAMIHACHI, JAMES. 1997. “Supervisory Issues in Electronic
Money.” Remarks at the American Banker Conference
on Future Money, June 11. Available on the Internet at
http://www.occ.treas.gov/emoney/kami6-11.htm.
KEENAN, CHARLES. 1997. “Visa One-Ups Rival on Consumer
Card Liability.” American Banker, August 14.
KELLEY, EDWARD W., JR. 1996. Remarks at the CyberPayments
’96 Conference, Dallas, Texas, June 18.

———. 1996b. Report to Congress on Funds Availability
Schedules and Check Fraud at Depository Institutions.
Washington, D.C.

LUNT, PENNY. 1996. “Is It First and Goal for Debit Cards?”
ABA Banking Journal 88 (September): 44.
MCANDREWS, JAMES J. 1997a. “Making Payments on the
Internet.” Federal Reserve Bank of Philadelphia Business
Review (January/February): 3–14.

———. 1997a. Report to Congress on the Application of
the Electronic Fund Transfer Act to Electronic Stored-Value
Products. Washington, D.C.

———. 1997b. “Banking and Payments System Stability
in an Electronic Money World.” Federal Reserve Bank of
Philadelphia Working Paper 97-9.

———. 1997b. Report to Congress Concerning the
Availability of Consumer Identifying Information and
Financial Fraud. Washington, D.C.

NIELSEN, DAVID. 1994. “Check Fraud Rose 136 Percent Over
Two Years, ABA Finds.” American Banker, December 1.

CALOMIRIS, CHARLES W., AND CHARLES M. KAHN. 1996. “The
Efficiency of Self-Regulated Payments Systems: Learning
from the Suffolk System.” Journal of Money, Credit, and
Banking 28 (November): 766–97.

PEARSALL, SUSAN. 1994. “Combating Credit Card Fraud.”
New York Times, December 18, sec. CN.

CASKEY, JOHN P., AND GORDON H. SELLON JR. 1994. “Is the Debit
Card Revolution Finally Here?” Federal Reserve Bank of
Kansas City Economic Review 79 (Fourth Quarter): 79–95.

POLLACK, ANDREW. 1996. “Counterfeiters of a New Stripe Give
Japan One More Worry.” New York Times, June 20, sec. D.
ROHTER, LARRY. 1997. “New Bank Fraud Wrinkle in Antigua:
Russians on the Internet.” New York Times, August 20, sec. A.

CONGRESSIONAL BUDGET OFFICE. 1996. Emerging Electronic
Methods for Making Retail Payments. Washington, D.C.

ROLNICK, ARTHUR J., BRUCE SMITH, AND WARREN E. WEBER. 1997.
“Lessons from a Laissez-Faire Payments System: The Suffolk
Banking System (1825–1858).” Federal Reserve Bank of
Minneapolis Working Paper 584, September.

DILLISTIN, WILLIAM H. 1949. Banknote Reporters and
Counterfeit Detectors, 1826–1866. New York: American
Numismatic Society.
DWYER, GERALD P., JR. 1996. “Wildcat Banking, Banking
Panics, and Free Banking in the United States.” Federal
Reserve Bank of Atlanta Economic Review 81 (December):
1–20.

RUTLEDGE, GARY. 1996. “Taming the Fraud Monster.” Credit
World (September/October): 10.
SARGENT, THOMAS J., AND NEIL WALLACE. 1982. “The Real-Bills
Doctrine versus the Quantity Theory: A Reconsideration.”
Journal of Political Economy 90 (December): 1212–36.

FEDERAL DEPOSIT INSURANCE CORPORATION. 1996. “Stored-Value
Cards and Other Electronic Payments Systems.” Federal
Register 61 (August 2): 40494–97.
FICKENSCHER, LISA. 1997. “MasterCard to Cap Consumer Debit
Card Liability.” American Banker, July 31.
FRYER, BRONWYN. 1996. “Visa Cracks Down on Fraud.”
Information Week, August 26.

GREENSPAN, ALAN. 1996. Remarks at the U.S. Treasury
Conference on Electronic Money and Banking: The Role
of Government, Washington, D.C., September 19.

SCHREFT, STACEY. 1997. “Looking Forward: The Role for
Government in Regulating Electronic Cash.” Federal Reserve
Bank of Kansas City Economic Review 82 (Fourth Quarter):
59–84.
“SURVEY OF ELECTRONIC COMMERCE.” 1997. Economist, May 10.

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W First Quarter 1998

TASK FORCE ON STORED-VALUE CARDS. 1997. “A Commercial
Lawyer’s Take on the Electronic Purse: An Analysis of
Commercial Law Issues Associated with Stored-Value Cards
and Electronic Money.” Business Lawyer 52 (February):
653–727.
TIMBERLAKE, RICHARD H. 1978. The Origins of Central Banking
in the United States. Cambridge, Mass.: Harvard University
Press.
U.S. DEPARTMENT OF THE TREASURY. 1996. “An Introduction to
Electronic Money Issues.” Paper prepared for the Treasury
Department conference “Toward Electronic Money and
Banking: The Role of the Government,” Washington, D.C.,
September 19–20.

———. 1997. Payments, Clearance, and Settlement: A
Guide to the Systems, Risk, and Issues. Washington, D.C.
VICKERS, MARCIA. 1996. “Stop Thief! And Give Me Back
My Name.” New York Times, January 28, sec. C.
WEINBERG, JOHN A. 1997. “The Organization of Private
Payment Networks.” Federal Reserve Bank of Richmond
Economic Quarterly 83 (Spring): 25–43.
WHITE, EUGENE N. 1995. “Free Banking, Denominational
Restrictions, and Liability Insurance.” In Money and
Banking: the American Experience, 99–118. Fairfax,
Va.: George Mason University Press.

U.S. GENERAL ACCOUNTING OFFICE. 1996. Counterfeit U.S.
Currency Abroad: Issues and U.S. Deterrence Efforts.
Washington, D.C.

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W First Quarter 1998

Full text of Economic Review (Federal Reserve Bank of Atlanta) : First Quarter 1998, Volume 83, Number 1

FRASER