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Bank Deposits and
Credit As Sources of
Systemic Risk
R O B E R T A . E I S E N B E I S
The author is senior vice president and director of
research at the Atlanta Fed.

HERE ARE MANY DIFFERENT WAYS TO DEFINE A FINANCIAL CRISIS. INDEED, THE ECONOMICS
AND FINANCE LITERATURE IS FILLED WITH TERMS LIKE PANIC, FINANCIAL CRISIS, RUNS, SYSTEMIC CRISIS, OR CONTAGION.1

THERE

IS IN FACT LITTLE AGREEMENT ON EVEN THE RUDI-

MENTARY DEFINITIONS OF A FINANCIAL CRISIS, THE SEQUENCE OF EVENTS CONSTITUTING A

CRISIS, OR THE CAUSES OF THESE EVENTS.

The professional discussion divides itself into two
broad categories. Macroeconomists typically are concerned with explaining business cycle fluctuations and
determining when a recession will degenerate into a
depression.2 They are equally interested in the financial
system’s role as a propagator of this process because
most depressions have been accompanied by serious
disruptions in the financial system, including banking
failures and panics. Eichengreen and Portes, for example, define a financial crisis as “a disturbance to financial markets, associated typically with falling asset
prices and insolvency among debtors and intermediaries, which ramifies through the financial system, disrupting the market’s capacity to allocate capital within
the economy. . . . Our definition implies a distinction
between generalized financial crisis on the one hand
and bank failures, debt defaults and foreign-exchange
market disturbances on the other” (1991, 10).
Financial economists examine the micro behavior
of market participants to explain disruptions in financial markets (see Diamond and Dybvig 1983; Chari and
Jagannathan 1984). They have tended to focus on banking panics and runs and the reasons depositors withdraw funds rather than on the macro consequences for
employment and output in the real economy per se.
4

While differing in their emphases, the micro and
macro approaches to analyzing financial stability share
several themes. The first focuses on alternative explanations for why a crisis occurs. One prominent thesis
argues that the financial system is inherently unstable
and is therefore vulnerable to random shocks. Shocks
simultaneously cause market participants to lose confidence in the system and exchange their bank deposits
for currency. Others believe that such herd behavior
cannot be explained solely by shocks that, like animal
spirits, randomly induce depositors to run from bank
deposits to currency. They offer more behaviorally oriented explanations and models, the most prevalent
being models based on the existence of information
asymmetries between borrowers and lenders. These
models attempt to show that it is sometimes rational for
depositors to attempt to withdraw their funds in such a
way that it creates a run on the banking system.
Most of the analysis in the random shock and information asymmetries models concentrates on aggregate
behavior, assuming essentially that all market actors—
both depositors and institutions—are identical. It does
not admit differences among depositors and institutions
or even the presence of more than one institution in the
financial system. When the analysis recognizes more

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

realistic features of market and financial structure,
researchers are better able to examine the process by
which a shock or problem in one part of the country or
sector of the economy is transmitted to other sectors or
the system as a whole. These transmission models, representing the second main theme in the literature, have
not been the focus of much empirical work and tend to
be relatively undeveloped.
The third area investigates the causes of financial
crises and their impact on the real economy. For example, do financial crises cause declines in real economic
output, or are they instead manifestations of deeper
problems in the real economy? What are the channels of
transmission? Do deposit runs cause liquidity problems,
which in turn induce contractions in lending, thereby
affecting real output and production? The final area of
analysis examines the role of government policies—
both macro and micro—in generating financial crises
as well as lessening their potential severity.
The remainder of this article explores these issues
in more depth. The discussion gives particular attention
to the possible linkages between deposits and credit
availability as the transmission mechanism for crises
since runs on deposits and payments system disruptions
are believed to be transmitted to the real economy
through a credit channel.

Random Shocks and Inherent
Financial Instability
t the macroeconomic level, models such as those
proposed by Minsky (1982) and Kindleberger
(1978) embody the claim that the banking system
is inherently unstable. Minsky argued that a capitalist
economy, and especially its banking system, is inherently unstable. Furthermore, this instability is endogenous,
originating within the system itself. He defined instability as “a process in which rapid and accelerating
changes in the prices of assets (both financial and capital) take place relative to the prices of current output”
(1982, 13).
Simply stated, Minsky assumed that during relatively stable times firms engage in balanced financing,
by which he meant that cash flows are sufficient to
cover principal and interest payments. However, as the
economy grows and enters the expansion phase of the
business cycle, firms begin to reach for profits, presumably because of management’s preference for short-

term gains. Firms start to leverage up, and banks, in
particular, begin to shorten the maturity structure of
their liabilities relative to their assets. Expanding
returns by funding long-term investments with shortterm borrowing is driven by the desire to take advantage
of an upward-sloping term structure with long-term
interest rates exceeding short-term rates.3 This period
of leveraging, which Minsky labels a period of speculative finance, is still one of relative stability.
Cash flows from investment are still sufficient to
cover principal payments as debts. This speculation
ultimately degenerates into what Minsky calls a period
of Ponzi finance, in
which cash flows cover
neither principal nor
interest payments. Debt
refunding requires new
Do financial crises cause
debt issuance, the proceeds of which are used
declines in real economic
to cover required interoutput, or are they instead
est and principal debt
manifestations of deeper
payments. During this
period, an exogenous
problems in the real
shock will result in a
economy?
collapse of both the
financial system and
the real economy. The
shock, which can come
from many different
sources, serves as the trigger for collapse. Minsky was
silent on the exact mechanisms by which this happens.
Commenting on Kindleberger’s (1978) similar view,
Schwartz observes that “those who regard banks as inherently unstable assume no connection between monetary
policy and the price conditions under which economic
agents make decisions. Proponents of inherent instability see a recurring historical pattern in which many
bankers abandon conservative standards of asset management during business expansions only to be caught
short when booms collapse. For them instability resides
in economic agents. Benevolent government then comes
to the rescue. This is the central thesis offered by Charles
P. Kindleberger in his 1978 book” (1986, 11).
Minsky puts forth certain stylized facts that would
be observed, although they are not the outcome from
any specified model.4 The first is that, during an expansion, credit expands at rates that exceed the growth of

1. For representative examples see Smith (1991), Kaufman (1995), Donaldson (1992), Bartholomew, Moe, and Whalen (1995),
and Eichengreen and Portes (1991). See Benston and Kaufman (1995) for a review of the evidence on fragility.
2. Eichengreen and Portes (1991) require declines in real output for a true financial crisis to occur.
3. Before 1910, however, the most common yield curve in the United States was downward-sloping.
4. It is generally argued that the theory as put forth by Minsky is not a unified theory that yields testable hypotheses. See, for
example, Sinai (1977), Lintner (1977), Mishkin (1991), and Schwartz (1986).

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

income or the capital stock. Second, interest rates and
nominal asset prices must be increasing at a rapid rate.
Third, debt maturities must become shorter, and,
fourth, some exogenous shock must occur to cause a
change in expectations. Finally, governments must fail
to intervene in ways that cushion any asset reevaluations accompanying any changes in expectations.5
Bernanke and James (1991) suggest a different
view of the causal relationship. For them, a precipitating
force that could lead to a financial collapse is a deflation.
Deflation adversely
affects credit quality by
reducing borrower equity cushions. When companies finally default,
Micro random shock
intermediaries become
owners of illiquid, real
models pay no particular
assets. To reliquefy
attention to the source,
their balance sheets,
or nature, of the random
banks are induced to
reduce lending and call
shock that causes
in loans. Those banks
depositors to line up.
that are unable to reliquefy fail, and, by implication, deposits will be
destroyed. In this scenario, credit problems
lead to a reduction in bank deposits, contracting the
money supply.
The chief distinction from the picture Minsky and
Kindleberger paint is that Bernanke and James see
banks as passive bystanders in the process. They are not
required to take on more risk, nor do they have to misprice risk or adjust their balance sheets to take on more
interest rate or maturity risk. The model also suggests
that crises occur only during and after an exogenous
shock has induced a deflation. Bernanke and James are
careful to argue, however, that while deflation is a necessary condition for a crisis to occur, it is not sufficient.
They highlight several aspects of banking structure
that, if present, also help increase the likelihood that
financial institutions would experience a crisis. These
include (a) lack of branch banking, (b) universal banking and the commingling of banking and commerce, and
(c) funding though short-term, foreign deposits. Thus,
banking and financial structure can either mitigate or
accentuate the likelihood that a financial crisis will
result during a deflationary period.
Unlike the macroeconomists’ models discussed,
the random shock models of the financial economists,
most closely associated with Diamond and Dybvig
(1983), look more deeply at the structure of the deposit
contract and the process by which it is redeemed.6
Because deposits are payable upon demand at par, they
offer depositors nearly costless liquidity, provided that
6

not all depositors wish to withdraw their funds at the
same time. With sequential servicing, in which depositors are treated on a first-come, first-served basis, depositors, especially if they are geographically dispersed,
rationally know that not everyone can withdraw simultaneously. If bank loans are inherently not marketable, or
cannot be easily liquefied, then at the first hint of potential trouble, it is rational for depositors to step to the
head of the line rather than incur costs to determine
whether and exactly when deposits will be paid.
These micro random shock models pay no particular attention to the source, or nature, of the random
shock that causes depositors to line up. Depositors just
decide to run, and once they do, all depositors run.
These models also do not consider the credit side of the
balance sheet as a factor in crises, other than the fact
that loans are less liquid than deposits so that banks
cannot pay all claims in currency. Nonetheless, they
make it easy to see that shocks affect depositors’ willingness to hold bank deposits, and, when that willingness is reduced, a contraction in credit follows as loans
must be liquidated to meet the deposit-redemption
demand.
The Diamond and Dybvig model approximates the
situation that prevailed in early U.S. history. Individual
banks issued their own bank notes to the public,
promising to redeem these notes at par for specie.7
Since note issues typically were not backed 100 percent
by specie, periodic liquidity problems arose whenever
noteholders became concerned that a bank might not
be able to honor its redemption commitment and suspend convertibility of deposits into specie. Runs on individual banks and the system sometimes occurred, and
these resulted, albeit infrequently, in cumulative contractions in the money stock.8 Suspension of convertibility of deposits into specie was a common way for
early banks to deal with temporary liquidity problems.
It often resulted, however, in a decline in purchasing
power since the value of deposits declined. By shifting
the cost of nonconvertability at least temporarily to the
creditors (depositors) of the bank, they gave all liability holders an important incentive to worry about bank
solvency.
Diamond and Dybvig (1983) investigate the suspension of convertibility as one equilibrium solution to
the problem of runs, but they do not consider the price
level effects or how the costs of suspension of convertibility are distributed because their model has only a
consumption good and no currency. Another weakness
of their model is that there is only one bank in the system, and hence runs are on the banking system as a
whole and involve flights to the currency rather than
runs on one of many banks in the system.9
For these early banks, avoidance of runs meant
maintaining public confidence. Depositors needed to

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

believe that the institution could convert notes into
specie in sufficient amounts and would not need to suspend convertibility.10 Indeed, the first forms of public
regulation designed to deal with the problems involving
suspension of convertibility imposed reserve requirements specifying permissible ratios of notes to specie.
The regulations sought to assure public confidence by
requiring banks to engage in minimal maturity intermediation, maintain sufficient specie reserves, and have
adequate capital and liquidity.11

Information Asymmetries Models
he micro random shock models have been less
than satisfying, both because they appear generally inconsistent with economic events, as will be
discussed in the next section, and because many economists find it hard to believe that people randomly
decide to run without some just cause rooted in economics. Recent modeling efforts have applied concepts
of information asymmetries to derive conditions that
might make it rational for depositors to engage in runs
on banks. Under the information asymmetries models,
banks are viewed as being “opaque” to depositors and
thus costly for depositors to monitor. With imperfect
and costly information, a type of Akerlof (1979) lemons
model applies in which depositors have a great deal of
difficulty distinguishing between healthy and unhealthy
banks. Any shock or news event that might induce
depositors to reassess their bank’s riskiness (in combination with the sequential servicing constraint) will
cause depositors to assume that all banks are riskier
than previously believed. Under these circumstances, it
is more rational for depositors to withdraw funds than
to seek out and evaluate costly information or risk los-

ing their funds by not withdrawing. In these models, as
in the micro random shock models, the source of the
shock is not specified, in that no particular cause is suggested for a failure. But usually it is hypothesized that
the shock originates in credit markets and in releases of
relevant news about bank asset quality. The model’s
predictions are consistent with the view that shocks are
more likely to result from disturbances in the real sector than from the default of a single borrower.
Macroeconomists have articulated a form of this
same asymmetric information hypothesis in attempting
to counter the inherent instability arguments. As
Schwartz describes it, “a widely held belief in the United
States and the world financial community is that the
default of major debtors—whether companies or municipalities or sovereign countries—could lead to bank failures that would precipitate a financial crisis. . . . A
financial crisis is fuelled by fears that means of payment
will be unobtainable at any price and, in a fractionalreserve banking system, leads to a scramble for highpowered money. It is precipitated by actions of the
public that suddenly squeeze the reserves of the banking
system. In a futile attempt to restore reserves, the banks
may call loans, refuse to roll over existing loans, or resort
to selling assets. . . . The essence of a financial crisis is
that it is short lived, ending with a slackening of the public’s demand for additional currency” (1986, 11).12
Under this scenario, a banking crisis is precipitated
by the failure of a major debtor, which induces a sudden
shift in the public’s demand for currency. In turn, banks
scramble for reserve assets by curtailing lending and
selling assets. By implication the decline in lending and
refusal to roll over existing credits leads to a decline in
economic output. The process becomes systemic in that

5. Minsky argues that the ability to intervene is directly correlated with the size of government; and big government, with its
revenue capacity, has the resources to support, through fiscal and monetary policies, a longer run-up of leverage. Also,
through its lender-of-last-resort capabilities, it can soften the landing during an exogenous shock period by supporting a
gradual rather than precipitous liquidation of assets. It thereby avoids the corresponding collapse of credit, bank failures,
and destruction of the money supply.
6. For other examples of models in this mode see Haubrich and King (1984), Cone (1983), Jacklin (1987), Wallace (1988),
Bhattacharya and Gale (1987), Smith (1991), and Chari (1989).
7. In the Diamond and Dybvig (1983) model there is really no nonbank money in circulation. Individuals deposit a real consumption good in the bank in exchange for a deposit or warehouse receipt. This consumption good is close, but not identical, to specie.
In early U.S. banking, it was not uncommon for notes issued by out-of-area banks to trade at discounts, which reflected
several factors, including transportation and transaction costs, lack of information on the issuing bank, and uncertainties
about the creditworthiness of the issuing bank. This lack of par clearance in no way affected the ability of state bank notes
to function as money.
8. For discussions of the evidence on runs see Kaufman (1988) and Gorton (1987).
9. Because of the way the model is constructed, runs necessarily have an adverse impact on the real economy.
10. For a discussion of these early bank runs see Kaufman (1988) or Bryant (1980).
11. Clearinghouses and other banks in the region often provided temporary credit to institutions experiencing liquidity problems (see Kaufman 1988). Kaufman (1994) notes that bank capital ratios were substantially higher during this period than
they were after deposit insurance was introduced.
12. Although Schwartz articulates this view, she clearly does not believe it is correct or that the policies designed to protect
against the events are appropriate.

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

problems in one or several major creditors raise questions about the quality of bank assets in general and
induce the public to switch to holding currency.
The hypothesis implies a direct linkage between
increased demand for money and the availability of credit—and hence the ability to finance and maintain the
real economy. The information the public perceives is
not assumed to be bank specific; instead, it is the fact
that the information concerns the quality of banking
assets in the aggregate that increases the private sector’s demand for currency relative to deposits. The channel envisioned in this
scenario results in
banks calling in loans
and building up liquidity to meet the public’s
Recent modeling efforts
desire
for currency.
have applied concepts of
Empirically, three
information asymmetries to
elements are necessary
for this view to hold.
derive conditions that
First, there must be a
might make it rational for
credit-related shock that
depositors to engage in
affects the public’s
desire to hold currency
runs on banks.
relative to deposits.
Second, this shock must
induce a liquidation of
deposits for currency by
the public. Third, bank credit must contract.
There are several important differences between
the various random shock models and asymmetric information models. First, Minsky’s random shock model
includes leveraging up of both bank and corporate balance sheets across the board, and, furthermore, it does
not require an inflationary environment. Second, the
collapse that results is not driven by runs forcing institutions to liquefy balance sheets to meet deposit withdrawals. Third, under this type of model financial
institutions accommodate the leveraging up of balance
sheets by underpricing credit risk. They also take on
more interest rate and maturity risk by shortening the
maturity structure of liabilities relative to assets.
Fourth, no interdependence among either borrowers or
lenders is necessary for a collapse to take place. Finally,
the direction of causation, in terms of propagators of
the crisis, appears to run through credit channels by
eroding depository institution real equity values. Only if
institutions fail is the money supply affected.
In the random shock model of Diamond and Dybvig
(1983), the crisis does not result from asset mispricing
or from rational economic behavior but rather from an
exogenous event. Since there is only one bank in the
economy in this model, runs take the form of flights to
currency (or more precisely, the consumption good)
and not to other healthy banks. The panic is due solely
8

to the existence of the sequential servicing requirement
discussed above and the fact that bank assets are not
perfectly liquefiable.
Like the micro random shock models, the asymmetric information models do not rest upon systematic
ex ante asset mispricing or other problems of bank
behavior. Changes in expectations and market assessment of bank asset quality, combined with the opaqueness of bank balance sheets and sequential servicing,
make runs a rational customer response.

Empirical Evidence on Systemic Risk
hen examined carefully, many of these alternative explanations of panics and financial
crises appear to overlap, differing only slightly
in their details. Separating them empirically can therefore be very difficult. Empirical tests of various hypotheses about financial crises and panics have generally
focused on the National Banking Era and the period of
the Great Depression. The reason for studying these
periods is that no broad-based panics have occurred
since (in part because of the existence of federal
deposit insurance and lender-of-last-resort actions followed by the Federal Reserve). In this section, the
empirical evidence is examined to determine which of
the models appear to be more consistent with the data.
The question of whether this empirical work provides useful insights or is relevant today is a legitimate
one, given the changes in financial structure and markets, the rise of technology, the proliferation of information, and the globalization of markets. This issue will
be addressed in the next section.
The Random Shock and Financial Fragility
Hypothesis. Given the lack of precision in specifying
the models, does the evidence suggest that one or more
of the models may be correct? With respect to the macro
models, critics of the Minsky financial fragility hypothesis argue that it does not yield testable hypotheses and
is inconsistent with the data (see Sinai 1977; Lintner
1977; Mishkin 1991; Schwartz 1986). As mentioned previously, for the hypothesis to hold, a sequence of several factors must be present: debt burdens increasing
faster than the growth of income or capital stock, interest rates and nominal asset prices increasing rapidly,
debt maturities at depository institutions becoming
shorter, an exogenous shock occurring to cause a
change in expectations, and, finally, governments failing to intervene in ways that would provide a soft landing to any asset revaluation that must accompany the
change in expectations.
Unfortunately, data do not readily exist for examining a number of the conditions Minsky sets forward. As
an alternative Table 1 lists the periods of economic
recession with information on when panics took place
and, where possible, what possible shocks may have

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

TA B L E 1 P a n i c D a t e s a n d C a u s e s

Panic Date
October 1857

Business Cycle
Peak and Trough
Fall 1853–
July 1857

Percentage
(and Number)
of National
Bank Failures
NA

Prepanic Interest
Rate Movement
Rates fell until the recession
began.

Percent Change
in Currency-toDeposits Ratio
from Previous
Year’s Average
NA

With failure of Ohio Life and Trust, reserves were
pulled from New York City banks. First bank failures occurred in September. Several railroads
went bankrupt in September, and major runs on
New York banks in October culminated in specie
suspensions in mid-October.

14.5

Crisis began when New York Warehouse and
Security Co. failed on September 8. Other failures
and suspensions followed: Kenyon, Cox & Co., Jay
Cooke & Co., and Fisk & Hatch. Panic-selling on
the New York Stock Exchange led to closing of the
market for ten days. The initial failures appeared
related to debt problems and problems with railroad bonds.a

8.8

On May 6 Marine National Bank failed. The Wall
Street brokerage firm Grant and Ward was linked
to a bank that failed on May 8. That failure was
followed by a run on Metropolitan National Bank
and suspension of several other banks. However,
an inflow of foreign capital and the issuance of
clearinghouse notes moderated the panic. It
appeared the clearinghouse notes provided a
signal to the market of bank solvency.

3.0

——

Spread on bonds did not widen
until after the onset of the
recession.

September 1873

October 1873–
March 1879

2.8 (56)

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

Rates rose about 5 percentage
points in August, five months
before the beginning of the
recession.
Spread on bonds did not rise until
the month of the panic and did
not rise prior to that.

June 1884

March 1882–
May 1885

0.9 (19)

No obvious pattern preceded the
panic.
With the exception of a threemonth period, spreads on bonds
declined steadily for two years
prior to the panic.

No panic

March 1887–
April 1888

0.4 (12)

——

Possible Prepanic Exogeneous Shock

(Continued on page 10)
9

TA B L E 1 P a n i c D a t e s a n d C a u s e s (cont.)

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

Panic Date
November 1890

Business Cycle
Peak and Trough
July 1890–
May 1891

Percentage
(and Number)
of National
Bank Failures
0.4 (14)

Prepanic Interest
Rate Movement
Rates did not rise appreciably
until after the recession had
begun.

Percent Change
in Currency-toDeposits Ratio
from Previous
Year’s Average
9.0

New York Stock Exchange prices began falling in
early November. On November 11 Decker, Howell
& Co. failed, involving the Bank of North America.
On November 12 a stock broker failed, and on
November 15 Baring Brothers failed in London.

16.0

On February 26 the Philadelphia & Reading
Railroad went into receivership, and on May 4
National Cordage Co. failed and a stock market
crash followed. New York banks weathered the
situation until banks in the West and South experienced runs and began withdrawing reserves from
New York City banks to meet liquidity needs. In
August there was a general suspension of specie
payments. National banks were reopened after
examination and certification by the Comptroller
of the Currency.

14.3

The period of 1895–96 was a mild, paniclike
period. Although the New York Clearing House
Association made emergency credits available
in the form of loan certificates, none were used.

2.8

——

Spread on bonds was essentially
flat for a year preceding the
panic.
May 1893

January 1893–
June 1894

1.9 (74)

Rates rose beginning in January
1892 approximately 2.5 percentage points in the seven months
preceding the recession.
Spread was essentially flat for
more than one year preceding the
recession.

October 1896

December 1895–
June 1897

1.6 (60)

Rates rose only about 75 basis
points in the three months preceding the peak of the expansion
but rose substantially in the three
months before the panic.

Possible Prepanic Exogeneous Shock

Spread on bonds did not widen
until after the beginning of the
recession and peaked just prior
to the panic.
No panic

June 1899–
December 1900

0.3 (12)

——

No panic

September 1902–
August 1904

0.6 (28)

——

–4.1

——

October 1907

May 1907–
June 1908

0.3 (20)

Rates were flat preceding the
recession and rose only slightly
thereafter.

11.5

Stock market declined in October. During the week
of October 14, five New York members of the New
York Clearing House Association and three outside
banks required assistance. These banks had been
used to finance speculation in copper-mining
stocks. On October 12 Knickerbocker Trust Co.
(third largest in New York City) began to experience clearing problems, and it suspended operations on October 22.

Spread on bonds was essentially
flat prior to the beginning of the
recession.

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

No panic

January 1910–
January 1912

0.1 (10)

——

–2.6

——

August 1914

January 1913–
December 1914

0.4 (28)

——

10.4

This crisis was linked to problems in London and
disruptions to payments on discount bills by foreign (European) borrowers. London stopped discounting foreign bills, and the effect was to
disrupt New York banks, who were in a net debt
position during the summer (as apparently was
usual). New York banks were forced to remit gold,
draining reserves. Both London and New York
Stock Exchanges closed on July 31, and a panic
threatened.

Sprague ([1910] 1968) notes that all the failures were due to criminal mismanagement or to neglect or violation of the National Banking Act and not to questions about bank solvency.

Source: Gorton (1988) and Schwartz (1986), except for Panics of 1857 and 1893 (Mishkin 1991).

existed. Looking first at the timing of the panics relative
to the peaks and troughs of the business cycles shows
that in only one instance was there a panic before the
peak of the business cycle. In most cases, the panic
occurred anywhere from three to six months after the
business cycle had peaked. Such long lags would seem
to be logically inconsistent with Minsky’s view.
Mishkin (1991) devotes considerable attention to
the rate pattern and to risk premiums and their relationship to the onset of panics. In general, the spread
between rates on high- and low-quality bonds rose before
the panic began. However, these spreads generally
widened after the recession started rather than before
as the Minsky hypothesis would require.13
The Asymmetric
Information Hypothesis
versus Micro Random
Shock Models. Gorton
(1988), Mishkin (1991),
Evidence suggests that
and Donaldson (1992)
specifically investigate
recession, and not a
the information asymtriggering bank failure,
metric hypothesis in
is the critical factor in
detail. Examining the
National Banking Era
determining whether a
and the post–Federal
panic will occur.
Reserve Era through
1933, Gorton models
depositor behavior in
terms of the currency/
deposit ratio. He poses
two questions. First, if panics are random events, then is
the model predicting a different currency/deposit ratio
during panic periods than exists in other times? Second,
are panics predictable in terms of movements of perceived risk? From these two questions Gorton suggests
the following testable hypothesis: “Movements in variables predicting deposit riskiness cause panics just as
such movements would be used to price such risk at all
other times. This hypothesis links panics to occurrences
of a threshold value of some variable predicting the riskiness of bank deposits” (1988, 751). Such predictive variables might be extreme seasonal fluctuations, unexpected
failure of a large corporation (usually a financial corporation), or a major recession.
A third question Gorton asks is whether certain
predictors of risk stand out as important predictors of
panics. Finding no evidence that panics are random
events, he concludes that there is strong support for the
asymmetric information hypothesis. Furthermore, panics appear to be predictable ex ante. Evidence also suggests that recession, and not a triggering bank failure, is
the critical factor in determining whether a panic will
occur. Gorton explains: “the recession hypothesis best
explains what prior information is used by agents in
12

forming conditional expectations. Banks hold claims on
firms and when firms begin to fail (a leading indicator
of recession), depositors will reassess the riskiness of
deposits” (1988, 778). In short, causation seems directed from the real sector to the financial sector rather
than vice versa.
Donaldson (1992) extends Gorton’s analysis using
a somewhat different specification of the model and
weekly data between 1867 and 1907 to determine
whether panics are systematic and predictable events.
Unlike Gorton, Donaldson rejects the conclusion that
panics are systematic events and argues that the data
are more consistent with the random shock model than
the asymmetric information model.14 However, for the
panics of 1914 and 1933 (which required expansion of
the money supply during crisis periods), he finds behavioral patterns of earlier panics had been dampened.
Given that the later panics followed the creation of the
Federal Reserve in 1913 and passage of the AldrichVreeland Act of 1912, this finding suggests that government involvement to increase liquidity can truncate
panic situations. He concludes that panics are therefore
special events. But he also finds evidence that panics
are more likely to occur when seasonal and cyclical factors are present.
Mishkin (1991) formulates the asymmetric information hypothesis somewhat differently. He argues that
key variables help to capture differences in depositor
assessment of bank risk. In particular, during periods of
financial distress high-quality firms will be less affected
and lenders will have less uncertainty about the riskiness of such firms than they will have for low-quality
firms. To the extent that these risks are priced, an
important index of asymmetric information uncertainty
should be captured by the spread between the rates on
high- and low-quality bonds, by stock prices (as a measure of net worth and collateral value), and by interest
rates (as a measure of agency costs and adverse selection). His analysis, like that of Gorton (1988), supports
the information asymmetries hypothesis to the extent
that the proxy variables are in fact good proxies. He concludes that most financial crisis periods begin with an
increase in interest rates and a widening of the spread
between high- and low-quality bonds and a decline in
stock prices, rather than with a panic. “Furthermore,”
Mishkin observes, “a financial panic was frequently
immediately preceded by a major failure of a financial
firm, which increased uncertainty in the marketplace”
(1991, 97). He also asserts that the information hypothesis offers a better explanation than the macro theories
of financial fragility for the pattern of rate spreads and
stock market movements both before and after a panic
as well as the panic’s likely occurrence.
Finally, Park (1991) argues that the provision of
bank-specific information overcame the information

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

asymmetries that played a role in runs on banks. In particular, by analyzing the panics of 1873, 1884, 1893,
1907, and 1933 he concludes that clearinghouse and
government intervention were effective devices in settling panics but only when they provided information on
bank-specific solvency.15 In the panic of 1884, a run was
abated following certification of solvency by the
Comptroller of the Currency and by subsequent extensions of clearinghouse certificates to Metropolitan
National Bank, which was the bank suffering the greatest withdrawals.
The panic of 1893 followed a long period of depression during which banks suffered prolonged periods of
withdrawals of gold and uncertainty about U.S. adherence to the gold standard. Gold hoarding culminated in
suspension of convertibility, and repeal of the Sherman
Silver Act was promised by the president. Banks lifted
the suspension of convertibility, and the runs stopped.
Because no systematic attempt was made to release
information on individual banks, public confidence in
all banks remained low until the source of uncertainty—lack of confidence in U.S. maintenance of the gold
standard—was removed. Park (1991) interprets the
Comptroller of the Currency’s certification of individual
bank solvency before their reopening following the
panic of 1893 as the major information factor that
quelled depositor uncertainty.
In the panic of 1907, the problem began with runs
on individual New York banks and trust companies that
had been directly or indirectly associated with a failed
attempt to corner the market in copper stocks. Only intervention by the New York Clearing House Association,
which attested to the solvency of banks experiencing
runs and provided financial assistance, resolved the situation. Again, release of firm-specific information
appeared to have addressed the information asymmetries and helped stabilize the crisis.16 Unlike other cases,
in the panic of 1907 runs did not affect all banks, and,

indeed, some New York Clearing House member banks
experienced reserve inflows (Park 1991).
Transmission Models. Neither the basic random
shock models nor the information asymmetry models
specifically address the issue of which mechanisms
transmit panics or financial crises through the economy. In fact, no models admit more than one institution,
a condition that would be necessary to model customers
simply transferring funds from an unhealthy to a
healthy institution as distinct from retreating to currency.17 The models provide no information on what, if
any, real impacts such funds transfers among banks
have. Nor have the models addressed when depositors
will run on one bank and when they will run on the
entire system.
Researchers have addressed the question of
transmission mechanism more indirectly by attempting
to generalize from the basic models. For example,
Calomiris and Gorton (1991) maintain that it is the
sequential servicing constraint imposed in the Diamond
and Dybvig–type models that can induce banks to run
on other banks. Such runs are especially likely when
banks are geographically dispersed but are permitted to
count interbank deposits as legal reserves, as under the
National Banking system. Two other regulatory constraints—restrictions on branching and on the payment
of interest on interbank deposits—have also been
regarded as important.18
The structure of the National Banking system prior
to creation of the Federal Reserve in 1913 added a further source of instability to the economy. Under that
system, legal reserves for National Banks included not
only cash in vault but also deposits in Reserve City
and Central Reserve City banks. In such a fractionalreserve banking system that has pyramiding of reserves,
a run on an individual bank could more easily have systemic, systemwide effects. Shocks originating in the
countryside, for example, could induce country banks to

13. The exception is the panic of 1873.
14. As a robustness test, he also reruns the analysis using monthly data as Gorton does and gets similar results to those found
by Gorton. He concludes that monthly data are too spaced out to provide a sharp test of the hypothesis.
15. A more complete test of the Gorton-Mishkin-Park hypothesis about information asymmetries would be provided by examining fund flows from individual solvent and insolvent institutions. Relying upon aggregate statistics can be only circumstantial, not conclusive.
16. The Roosevelt administration, following the declaration of the bank holiday on March 6, 1933, employed this same policy.
17. Smith (1991) does provide a model in which banks are permitted to hold funds at a Reserve City bank. Bhattacharya and
Gale (1987) provide a model with geographically dispersed depositors and banks. Again, however, these models only look
at the interdependence among banks through the interbank deposit markets.
18. See also the discussions in Haubrich (1990), Bordo (1986), and Williamson (1989). All emphasize the advantages over U.S.
banks that banks in Canada and other countries that permitted branching had in weathering panics. Calomiris and
Schweikart (1991) have explored in detail for the United States the effects that structure had on failure rates in different
states with different branching statutes. They show that branch banks had both lower failure rates and in general paid
lower premiums on their notes during the crisis of 1857 than banks in other parts of the country.

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

improve their liquidity positions by recalling interbank
deposits from the Reserve City and Central Reserve City
banks. Hence, panics were also endemic to the structure of the system as a whole, and it is clear how a panic
or run in a rural region could blossom into a systemic crisis for healthy banks in Reserve Cities and Central
Reserve Cities. Chari (1989) addressed this issue directly in considering a model of spatially separated banks.
He argued that the most likely source of a shock that
would cause country banks to withdraw reserve funds
was seasonally related, with differences in currency
demands rising significantly during planting
and harvest times.
Inferences about financial
Calomiris
and
Gorton (1991) attemptcrises and systemic risk
ed to determine specifidrawn from study of the
cally whether panics
banking situation during
were transmitted from
rural areas through the
the National Banking Era
National Banking sysand early 1900s are not
tem, as the analysis
particularly meaningful or
suggested, and also
whether the patterns
relevant in today’s economwere more consistent
ic environment.
with the random shock
or information asymmetries models. They
found that three important differences between the
models have empirical implications.
The first concerns the origin of problems. The random shock model suggests that shocks would occur in
rural areas because of seasonal demands for currency.
In contrast, the asymmetric information model implies
that adverse economic news related to asset-quality
problems would precede a panic.
Second, the two theories would seem to predict different patterns of failures during a crisis. The asymmetric information model suggests that banks whose asset
portfolios were closely linked to the specific shock
would be more prone to failure whereas the random
shock model would predict that failures would be experienced in the areas suffering currency withdrawals.
Finally, the models differ in the conditions
required to resolve a crisis. In the random shock model,
the key to resolving a panic is liquefication of assets. In
the asymmetric information model, it is the effectiveness of mechanisms initiated to resolve depositor
uncertainty about bank solvency.
Calomiris and Gorton’s exhaustive investigation of
the sources of panics between 1873 and 1907 led them
to reject the idea that seasonal money-demand shocks
were the cause of banking panics. Rather, their analysis
suggests that panics originated in bad economic news
and bank vulnerability to that news. Moreover, their
14

inspection of failure patterns shows virtually no support
for the random shock model. Finally, they conclude that
in terms of resolving crises, the mere availability of currency, which would provide the ability to liquefy assets,
was not sufficient to stop panics during the periods
studied. Again, this conclusion suggests that the asymmetric information model was more consistent with the
data than was the random shock model.
Smith (1991) provides some specific evidence on
country banks’ behavior vis-à-vis their holdings of cash
reserves as compared with reserves held in the form of
interbank deposits when panics occurred. He provides
analysis of some anecdotal and other evidence, derived
mostly from Sprague ([1910] 1968), about the behavior
of Reserve City banks during the crises of 1873, 1893,
1907, and 1930–33.
Smith describes the situation leading up to the
panic of 1873, indicating that interbank deposits were
concentrated in seven of the New York City banks. These
interbank deposits constituted about 45 percent of the
sources of funds for the New York banks and were the
base upon which their bond holdings and loans were
built. These banks were clearly vulnerable to demands
by country banks for withdrawal of reserves, and funds
were especially tight in the few months before the crisis.
When the key triggering events occurred (see Table 1),
a combination of circumstances made the crisis severe.
In addition to having virtually no excess reserves, several of the banks were in weak financial condition. As subsequent events would prove, several had been the
victims of fraud and defalcations, probably accounting in
part for their financial weakness. Clearly, however, the
institutions’ problems stemmed primarily from reserve
withdrawals and their inability to call in loans in that
economic environment rather than from major credit
problems in the New York Central Reserve City banks.
The Reserve City banks experienced similar problems caused by currency outflows during the panics of
1893 and 1907. Thus, it seems clear that reserve outflows, coupled with the lack of excess currency reserves
at the Central Reserve City banks in New York and
Chicago, forced contractions in loans and finally resulted in the suspension of currency payments. Smith notes
that currency suspension was the prime transmission
mechanism of panics once a triggering mechanism
occurred. He also concludes that the problems during
the 1930–33 period originated in the rural agricultural
areas as well and were intimately intertwined with the
correspondent banking system.
Despite a fairly clear pattern in the transmission
mechanism of panics emanating from large reservedeposit withdrawals (rather than from uncertainties
about credit quality in Reserve City banks, as the
Minsky hypothesis would imply), a number of questions
remain. For example, Tallman (1988) indicates that

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

looking at the data over longer time periods does not
suggest a clear linkage between the incidence of panics
and either increases in currency demand relative to
deposits or contractions in loans. He presents evidence
that loan contractions occurred at several intervals during the period between 1893 and 1907, for example, that
exceeded the declines during periods when panics
occurred. Similarly, during some periods of time
between 1873 and 1930 the number of bank failures far
exceeded those observed during panic periods. Finally,
Tallman provides aggregate data on the growth in loans
relative to high-powered money and on the growth of
manufacturing output between 1873 and 1914. Two
observations are important. First, loans do increase in
the years prior to panic periods, but the panics occur
after loan growth has fallen significantly. Second,
numerous periods during the interval show the same
patterns in loan and output growth and decline but are
not accompanied by a panic. These aggregate data do
not reveal whether there are differences in the loancontraction periods in terms of their concentration in
particular parts of the country during episodes of panic
and nonpanic periods.
Causal Direction. The research evidence seems to
indicate fairly consistently that the dynamics between
financial panics and changes in real economic output
begin in the real sector and move to the financial sector
rather than starting in the financial sector. There are no
examples in U.S. history of the economy operating at
high levels of output when a financial crisis occurred
that resulted in a contraction in the real economy. As
the discussion in the previous sections suggests, however, banks were sometimes under pressure and were
forced to call in loans. It seems reasonable to assume
that once problems in the financial sector become
severe, there could be negative feedback effects to the
real sector.
Indeed, Bernanke (1983) has made precisely this
point. Financial crises can have real effects outside the
normal reserve/loan transmission mechanism because
of the disruptions to the intermediation process. Bank
failures disrupt borrower/lender relationships and
make attaining financing more difficult and costly. But
this observation should not obscure the fact that financial crises are better viewed as creatures of recession
and economic downturns rather than primary causal
agents precipitating the downturns.
The Role of Government. A substantial body of evidence indicates that government actions have played

significant roles in contributing to crises as well as in
mitigating them. For example, Sprague ([1910] 1968)
notes that lack of access to a reliable lender of last
resort to provide short-term liquidity can help escalate
a period of financial tightness into one of crisis.
Friedman and Schwartz (1963) argue that several
Federal Reserve actions during the Great Depression
contributed to both its duration and magnitude. For
instance, they observe that the Federal Reserve’s failure
to liquefy the assets of many small nonmember institutions (the Fed was not obligated to lend to nonmember
banks), together with its insistence that it would lend
only upon sound collateral, added to the number of
bank failures. This policy, in conjunction with the Fed’s
attempt to adhere to the rules of the gold standard, contributed to a 33 percent decline in the money supply
and clearly exacerbated the severity of the recession.
While it has become fashionable to criticize the
Fed for its policy failures during the Great Depression,
it is also the case that government interference affected financial soundness long before the Fed was created.
For example, during the National Banking Era the monetary base was tied, except for a period of suspension, to
gold and silver specie monies through the Treasury.19
When the United States adhered to the gold standard,
fluctuations in the gold supply expanded and contracted the monetary base, directly affecting banks’ lending
behavior. Decisions about how much in the way of
international gold flows would be permitted before conversion could be suspended was a matter of Treasury
and government policy. European central banks, and to
a lesser extent the U.S. Treasury, often intervened to
prevent loss of gold reserves by raising short-term interest rates. Government policies frequently exacerbated
gold flows and, by implication, induced fluctuations in
the monetary base. For example, following passage of
the Sherman Silver Purchase Act in 1890, foreigners’
concern that the United States would remain on the
standard precipitated gold outflows and contributed to
the panic of 1890.20
Tallman and Moen note that each panic after 1897
was preceded by unusual gold flows. They conclude that
political uncertainties concerning the U.S. commitment
to the gold standard were important influences on gold
flows and, hence, the U.S. monetary base. Political conditions outside the United States also affected gold
flows. For example, in 1907 the Bank of England
responded to problems in the London money markets by
raising its discount rate to stem potential speculative

19. Specifically, the monetary base included gold coin, gold certificates backed 100 percent by gold, silver dollars, silver certificates, other small silver coins, U.S. notes and other Treasury fiat, and national bank notes. See Tallman and Moen (1993).
20. Tallman and Moen (1993) indicate that this uncertainty was greatly reduced with the discovery of large gold supplies in
the late 1890s.

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

outflows of gold to the United States. At that time
London was the most important market for discounting
U.S. trade bills. The increase in the discount rate not
only disrupted the flow of gold to the United States but
also discouraged the discounting of trade bills and
caused a liquidity crisis in the United States.
Since the debacle of the Great Depression, U.S.
intervention in markets has often had as its objective
providing liquidity to avoid a crisis. Numerous examples
exist of emergency liquidity having been provided
through the efforts of the Federal Reserve either directly or indirectly, such as during the Penn Central scare,
the Chrysler problem, the collapse of Drexel-Burnham,
and the failure of
Continental Illinois
Bank, to name just a
few. The Federal ReWhile panics do appear to
serve has on occasion
be associated with recesattempted to provide
liquidity not only to
sions and deflationary
cushion problems in
periods, the direction of
interbank markets but
causation seems to run
also to prevent disruptions in other markets.
from the real sector to

the financial sector rather
than the other way around.

Relevance in
Today’s World

t can be argued that
inferences about
financial crises and
systemic risk drawn from study of the banking situation during the National Banking Era and early 1900s are not particularly meaningful or relevant in today’s economic
environment. Pyramiding of legal reserves in private banks is
not a structural feature of the present reserve requirement
regime. Markets are no longer isolated, and informationavailability problems that might have resulted in the past
in information asymmetries have been reduced significantly. Communications technology and new instruments
have increased the liquidity of all banking assets and have
given rise to new markets that make the kinds of liquidity crises that occurred in the National Banking Era
unlikely today. Furthermore, the United States has abandoned the gold standard, and thus the domestic money
supply is not subject to the random fluctuations and
shocks that it was vulnerable to under strict adherence to
the gold standard rules. Deposit rate ceilings of the 1930s
have been phased out, and branching restrictions, which
essentially prevented institutions from achieving geographical diversification, are a thing of the past.
Certainly the focus on protecting the money supply
from sudden shocks is no longer of prime policy concern
for three reasons. First, it seems unlikely that significant runs to currency will occur (see Kaufman 1988).
Deposits still have large advantages over currency for a

variety of purposes, and there are many banks to chose
from. Runs on individual banks would simply transfer
reserves from one institution to another. Second,
Federal Reserve policy is likely to provide emergency
liquidity to prevent such runs from disrupting other
institutions. Finally, while still accounting for the bulk
of payment items, checks and currency are no longer
the dominant forms in terms of dollar volume of transactions in the economy. The concerns and risks have
shifted to other sectors of the payments system that did
not exist during the National Banking Era.
Today, the payments system is larger, has many
more components (both private and public), and is subject to different risks than in the past. The check/
demand deposit system, which accounts for the bulk of
individual payments (except for currency), and the one
that the present regulatory structure was primarily
designed to protect, is small in terms of the dollar volume of payments. The rest are made in the form of computerized transfers of reserve balances on the Federal
Reserve’s Fedwire system and the privately owned
Clearing House Interbank Payments System (CHIPS)
and in the form of automated clearinghouse (ACH)
transactions. Payments on the former two systems
account for about 85 percent of the dollar value of
transactions. Closely related to these systems are the
automated transfers of book-entry Treasury securities,
which also take place on Fedwire and involve substantial volumes of transactions.
Finally, as markets have become increasingly global, timing differences and differences in clearing and
settlement conventions can add temporal and other
dimensions to credit risks not always found in the
domestic markets that characterized earlier times.
Many other significant sources of uncertainty can also
be identified in the clearing and settlement processes
in modern financial markets (see, for example,
Eisenbeis 1997 and McAndrews 1997).
Maintaining the integrity of payment flows is a substantially more complicated and difficult problem today
than protecting the stock of demand deposits for a number of reasons. First, given the large size of transactions
in the system and the size of the system itself, the
resources required to support unwinding even a shortrun problem may be enormous and could exceed the
capacity of private participants to self-insure. Second,
because the transactions are electronic and occur
instantaneously, monitoring them and the net position
of each participant is critical to controlling participants’ credit risk exposure. Third, when the international activities of U.S. banks and the links between the
U.S. domestic payments system and foreign banking
organizations are recognized, it becomes difficult to
conceive of ensuring domestic financial stability without also ensuring international financial stability.

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

Clearly, different types of uncertainties exist with
respect to systemic risk exposures today than existed in
the past. There is also reason to believe that liquidity
problems for borrowers may be significantly different
than they were for borrowers in the 1800s. The growth
of new mortgage lending instruments and, particularly,
the development of home equity lines of credit provide
ways for borrowers instantaneously to liquefy previously illiquid assets during tight times. While this ability to
liquefy assets more easily may enable borrowers to
maintain payments on outstanding debts and lessen the
severity of the credit component of a recession, it also
suggests introduction of a new discontinuity that might
systematically transfer risks to the banking system at a
critical trigger point. If during times of financial distress borrowers draw down lines on home equity and
similar lines of credit and are then forced into default,
the burdens of these defaults will be shifted to the
providers of the home equity lines. Should these losses
be large, capital might be wiped out, with few options
available to lenders to avoid the costs of those defaults.
Examples of similar impacts in commercial and real
estate lending markets occurred when commercial
paper borrowers drew down banks’ back-up commitments during the Penn Central and Real Estate
Investment Trust (REIT) crises.

Summary and Conclusions
his article has investigated the various theories of
financial panics and crises with particular
emphasis on the links between credit and
deposits. The survey suggests that panics are not random events, as some of the theories may suggest, but
neither are they perfectly predictable. Nevertheless, it
does appear that information asymmetries about the
ability to liquefy deposits were a major contributing factor to banking panics in the past. Moreover, while panics do appear to be associated with recessions and
deflationary periods, the direction of causation seems to
run from the real sector to the financial sector rather
than the other way around. It is not that financial crises
cannot exacerbate economic declines; rather, they are
not primary causal agents of recessions.
The analysis also suggests that government policies can affect the likelihood of a financial crisis as well
as play a role in its solution. These considerations are as
relevant today as they have been historically. At the
same time, the article raises a cautionary note that the
dynamics of crises and how they might play out may be
significantly different in the future given recent, rapidly developing changes in the U.S. and world financial
system.

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

REFERENCES
AKERLOF, GEORGE. 1979. “The Market for Lemons: Qualitative
Uncertainty and the Market Mechanism.” Quarterly Journal
of Economics 84:488–500.

DONALDSON, R. GLEN. 1992. “Sources of Panics: Evidence from
Weekly Data.” Journal of Monetary Economics 30
(November): 277–305.

BARTHOLOMEW, PHILIP F., LARRY R. MOE, AND GARY WHALEN. 1995.
“The Definition of Systemic Risk.” Office of the Comptroller
of the Currency. Presented at the seventieth annual Western
Economic Association International Conference, San Diego,
California, July.

EICHENGREEN, BARRY, AND RICHARD PORTES. 1991. “The Anatomy
of Financial Crises.” In Financial Markets and Financial
Crises, edited by R. Glenn Hubbard, 10–58. Chicago:
University of Chicago Press.

BENSTON, GEORGE J., AND GEORGE G. KAUFMAN. 1995. “Is the
Banking and Payments System Fragile?” Journal of
Financial Services Research 9 (December): 209–40.
BERNANKE, BEN S. 1983. “Non-Monetary Effects of the
Financial Crisis in the Propagation of the Great Depression.”
American Economic Review 73 (June): 14–31.
BERNANKE, BEN, AND HAROLD JAMES. 1991. “The Gold Standard,
Deflation, and Financial Crisis in the Great Depression: An
International Comparison.” In Financial Markets and
Financial Crises, edited by R. Glenn Hubbard, 33–68.
Chicago: University of Chicago Press.

EISENBEIS, ROBERT A. 1997. “International Settlements: A New
Source of Systemic Risk?” Federal Reserve Bank of Atlanta
Economic Review 82 (Second Quarter): 44–50.
FRIEDMAN, MILTON, AND ANNA J. SCHWARTZ. 1963. A Monetary
History of the United States, 1867–1960. Princeton, N.J.:
Princeton University Press.
GORTON, GARY. 1987. “Banking Panics and Business Cycles:
Data Sources, Data Construction, and Further Results.” The
Wharton School, University of Pennsylvania. Photocopy.
———. 1988. “Banking Panics and Business Cycles.” Oxford
Economic Papers 40:751–81.

BHATTACHARYA, SUDIPTO, AND DOUGLAS GALE. 1987. “Preference
Shocks, Liquidity, and Central Bank Policy.” In New
Approaches to Monetary Economics, edited by William
Barnett and Kenneth Singleton, 69–88. New York: Cambridge
University Press.

HAUBRICH, JOSEPH. 1990. “Non-Monetary Effects of Financial
Crises: Lessons from the Great Depression in Canada.”
Journal of Monetary Economics 25 (March): 223–52.

BORDO, MICHAEL. 1986. “Financial Crises, Banking Crises,
Stock Market Crashes, and the Money Supply: Some
International Evidence.” In Financial Crises and the World
Banking System, edited by Forest Capie and Geoffrey E.
Wood, 190–248. London: Macmillan.

JACKLIN, CHARLES. 1987. “Demand Deposits, Trading
Restrictions, and Risk Sharing.” In Contractual
Arrangements for Intertemporal Trade, edited by Edward D.
Prescott and Neil Wallace, 26–47. Minneapolis: University of
Minnesota Press.

BRYANT, JOHN. 1980. “A Model of Reserves, Bank Runs, and
Deposit Insurance.” Journal of Banking and Finance
4:335–44.

KAUFMAN, GEORGE G. 1988. “Bank Runs: Causes, Benefits, and
Costs.” Cato Journal 7 (Winter): 559–87.

CALOMIRIS, CHARLES W., AND GARY GORTON. 1991. “The Origins of
Banking Panics: Models, Facts, and Bank Regulation.” In
Financial Markets and Financial Crises, edited by R. Glenn
Hubbard, 109–73. Chicago: University of Chicago Press.

HAUBRICH, JOSEPH, AND ROBERT KING. 1984. “Banking and
Insurance.” NBER Research Working Paper No. 1312.

———. 1994. “Bank Contagion: A Review of the Theory and
Evidence.” Journal of Financial Services Research 8:123–50.
———. 1995. “Comment on Systemic Risk.” In Research in
Financial Services, vol. 7, edited by George G. Kaufman.
Greenwich, Conn.: JAI Press.

CALOMIRIS, CHARLES W., AND LARRY SCHWEIKART. 1991. “The
Panic of 1857: Origins, Transmission, and Containment.”
Journal of Economic History 51:807–34.

KINDLEBERGER, CHARLES P. 1978. Manias, Panics, and Crashes.
New York: Basic Books.

CHARI, V.V. 1989. “Banking without Deposit Insurance or
Bank Panics: Lessons from a Model of the U.S. National
Banking System.” Federal Reserve Bank of Minneapolis
Quarterly Review 13 (Summer): 3–19.

LINTNER, JOHN. 1977. “Discussion.” In Financial Crises:
Institutions and Markets in a Fragile Environment, edited
by Edward I. Altman and Arnold W. Sametz, 204–207. New
York: John Wiley and Sons.

CHARI, V.V., AND RAVI JAGANNATHAN. 1984. “Banking Panics,
Information, and Rational Expectations Equilibrium.”
Northwestern University. Photocopy.

MCANDREWS, JAMES J. 1997. “Banking and Payment System
Stability in an Electronic Money World.” Federal Reserve
Bank of Philadelphia Working Paper No. 97-9.

CONE, KENNETH. 1983. “Regulation of Depository Institutions.”
Ph.D. diss., Stanford University.

MINSKY, HYMAN P. 1982. “The Financial-Instability Hypothesis:
Capitalist Processes and the Behavior of the Economy.” In
Financial Crises: Theory, History, and Policy, edited by
Charles P. Kindleberger and Jean-Pierre Laffargue, 13–38.
Cambridge: Cambridge University Press.

DIAMOND, DOUGLAS, AND PHILIP DYBVIG. 1983. “Bank Runs,
Liquidity, and Deposit Insurance.” Journal of Political
Economy 91 (June): 401–19.

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

MISHKIN, FREDERIC S. 1991. “Asymmetric Information and
Financial Crises: A Historical Perspective.” In Financial
Markets and Financial Crises, edited by R. Glenn Hubbard,
69–108. Chicago: University of Chicago Press.

SPRAGUE, O.M.W. [1910] 1968. History of Crises under the
National Banking System. National Monetary Commission.
Reprint. New York: Augustus M. Kelley.

PARK, SANGKYN. 1991. “Bank Failure Contagion in Historical
Perspective.” Journal of Monetary Economics 28 (October):
271–86.
SCHWARTZ, ANNA. 1986. “Real and Pseudo Financial Crises.” In
Financial Crises and the World Banking System, edited by
Forest Capie and Geoffrey E. Wood, 11–31. London:
Macmillan.
SINAI, ALLEN. 1977. “Discussion.” In Financial Crises:
Institutions and Markets in a Fragile Environment, edited
by Edward I. Altman and Arnold W. Sametz, 187–203. New
York: John Wiley and Sons.
SMITH, BRUCE D. 1991. “Bank Panics, Suspensions, and
Geography: Some Notes on the ‘Contagion of Fear’ in
Banking.” Economic Inquiry 29 (April): 230–48.

TALLMAN, ELLIS W. 1988. “Some Unanswered Questions about
Bank Panics.” Federal Reserve Bank of Atlanta Economic
Review 73 (November/December): 2–21.
TALLMAN, ELLIS W., AND JON MOEN. 1993. “Liquidity Shocks and
Financial Crises during the National Banking Era.” Federal
Reserve Bank of Atlanta Working Paper 93-10, August.
WALLACE, NEIL. 1988. “Another Attempt to Explain an Illiquid
Banking System: The Diamond and Dybvig Model with
Sequential Service Taken Seriously.” Federal Reserve Bank
of Minneapolis Quarterly Review 12 (Fall): 3–16.
WILLIAMSON, STEVEN. 1989. “Bank Failures, Financial
Restrictions, and Aggregate Fluctuations: Canada and the
United States, 1870–1913.” Federal Reserve Bank of
Minneapolis Quarterly Review 13 (Summer): 20–40.

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

Decision Time
for European
Monetary Union
J O S E P H A . W H I T T J R .
The author is an economist in the macropolicy section
of the Atlanta Fed’s research department. He thanks
Peter Abken, Roberto Chang, and Mary Rosenbaum
for helpful comments and Mike Chriszt and Jeff
Johnson for research assistance.

RAVELERS IN THE

UNITED STATES TAKE FOR GRANTED THEIR ABILITY TO USE THE SAME DOL-

LAR BILLS TO PAY FOR MEALS, TAXIS, AND OTHER GOODS AND SERVICES THROUGHOUT THE
NATION WHETHER THEY ARE IN

HOWEVER,

EUROPE

NEW YORK, LOS ANGELES,

THE SITUATION IS QUITE DIFFERENT.

OR ANYPLACE IN BETWEEN.

EVEN

FAIRLY SHORT TRIPS

OFTEN INVOLVE TRAVELING THROUGH MORE THAN ONE COUNTRY, AND, EACH TIME A BORDER IS CROSSED,
TRAVELERS MUST USE COMPLETELY DIFFERENT CURRENCY AND COINS.

This situation may change dramatically in the next
few years. If the plans of European governments for economic and monetary union (EMU) are realized, within
five years a new common currency called the euro will
replace the money currently in use in at least a few
western European countries. A traveler going to Paris,
Amsterdam, Berlin, and Rome might be able to use
euros in all four places.
Even earlier, starting in 1999, a new European
Central Bank is slated to take control of monetary
policy in the initial member countries. At that time,
exchange rates between the initial members will be
fixed permanently. Eventually, in two or three decades,
the euro may be in use throughout most of western and
central Europe, from Ireland to Greece and from
Portugal to Finland.
The choice of initial members in the monetary
union is scheduled to be made early in 1998, but as of
this writing major hurdles remain that could delay or
possibly kill the whole plan. The biggest stumbling
20

block involves budget deficits. To be eligible to join the
proposed monetary union, countries are supposed to
have budget deficits of no more than 3 percent of gross
domestic product (GDP) in 1997, but it now appears
likely that many prospective members, including the
largest, Germany, will violate that limit.
This article examines the economic and political
factors that will determine whether monetary union
proceeds on schedule and, if so, which countries will be
initial members. The first section provides background
and lays out the current official timetable for monetary
union. The second section reviews the convergence criteria to be used in determining which countries are
ready to join, with special emphasis on the fiscal or budget deficit criterion that is proving to be the biggest
problem.
Because so many countries are in danger of failing
to satisfy all the convergence criteria, the third section
describes several quite different scenarios that even at
this late date are still under consideration, especially in

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

unofficial forums. The final decision on EMU will be
made through political bargaining among the leaders of
the prospective member countries. The next section
outlines the results of economic models of such a bargaining process.
The prospect of monetary union is already affecting
financial markets. The final part of the discussion
shows how financial market data can be used to try to
infer the market’s assessment of the likelihood that certain countries will enter monetary union. Such estimates are no doubt imprecise, but as of early 1997 the
pattern of market interest rates appeared to embody a
substantial likelihood that a widespread monetary
union will begin operation in the next few years.

Current Timetable for Monetary Union
t the beginning of 1999, Europe is scheduled to
begin a major experiment in monetary arrangements. The Maastricht Treaty, which was signed
by the members of the European Union (EU) in 1991,
provides for economic and monetary union and creation
of a European central bank by the end of this decade.1
In many respects this undertaking is highly unusual; we
are accustomed to thinking of each nation as having its
own government, its own money, and its own central
bank, which is either directly or indirectly a part of the
government. The Maastricht framework would create
both a new money that would be legal tender in all participating countries and a central bank that would not
be an agency of any one government.
The Maastricht Treaty specified that monetary
union between those countries that were ready would
begin on January 1, 1999.2 On that date the new
European Central Bank would begin carrying out monetary policy in the uniting countries, and exchange
rates between their individual currencies would be
fixed permanently.
The countries that joined the monetary union initially would continue to use their national currencies
for a time, but their bilateral exchange rates would be
fixed irrevocably and their monetary policy would be set
by the new European Central Bank, which is modeled
on the German Bundesbank and is supposed to carry
out monetary policy with the aim of ensuring price stability. By January 2002, notes and coins denominated in
the new monetary unit, the euro, would be put into circulation, and after a short time the old national currencies and coins would be withdrawn from circulation. At

that point, the euro would be the single currency in circulation throughout the monetary union.
The Maastricht Treaty was not approved merely to
make life easier for travelers. To some extent monetary
union was just one part of a more general move toward
closer economic integration of the EU that also included
the Single European Act or Europe 1992, which called
for the elimination of many regulatory barriers to the
free flow of goods, capital, and workers within the EU.
European leaders hoped that greater economic integration would help rejuvenate their economies, many of
which were plagued by high unemployment. Moreover, a
larger, more integrated Europe would, it was hoped,
benefit from economies
of scale and be able to
compete more effectively against economic
Many preparatory steps
rivals such as the United
States and Japan.
have been taken, but a
The decision to disnumber of key decisions,
mantle restrictions on
notably about which councapital flows gave particular impetus to montries will be part of the
etary union because
union at its beginning, still
free movement of capiremain to be made.
tal is incompatible with
fixed (or managed)
exchange rate systems
such as the European Monetary System
(EMS) and national autonomy in the formation and
implementation of monetary policy (see PadoaSchioppa 1994). When the proposals that became the
Maastricht Treaty were under discussion in the late
1980s and early 1990s, the exchange rates of many of the
European countries were already linked in the EMS.
Fluctuations of each member’s exchange rate relative to
other members were limited to ranges defined by fairly
narrow target bands. If one country—for example,
Belgium—tried to exercise national autonomy in its
monetary policy by lowering its interest rates significantly below those of other members, capital outflows
could become so large that they would push Belgium’s
exchange rates to, if not beyond, the limits of the target
bands. Free movement of capital would make the
exchange rate target bands even harder to maintain. To
proponents of monetary union (for example, Sutherland
1997), Europe would need to move ahead to monetary

1.When the Maastricht Treaty was signed, the EU had twelve members: Belgium, Denmark, France, Germany, Greece, Ireland,
Italy, Luxembourg, the Netherlands, Portugal, Spain, and the United Kingdom. Austria, Finland, and Sweden were added in
1995. For reviews of the literature on European monetary union, see Bean (1992), Kenen (1992), and Eichengreen (1993).
2.The treaty envisioned an earlier start-up date for monetary union, at the beginning of 1997, but only if a majority of members were ready in time. If a majority were not ready in time for that earlier date (as actually occurred), then the treaty specifies the currently planned start-up date at the beginning of 1999, with no requirement that a majority be ready.
Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

union, or the attempt to create a single European market (including free movement of capital) would fail.
Another reason for monetary union would be the
resulting reduction in transactions costs on intraEuropean trade. Travelers would no longer have to
exchange one money for another each time they crossed
a national border. Over time, all the workers, computers, and other equipment currently used simply to convert one European money into another could be
redeployed. The European Commission (1990) has estimated the gain from lower transactions costs to be modest, 0.3 to 0.4 percent of GDP every year, with the largest
proportional gains going to countries with relatively
unsophisticated and inefficient financial sectors.
Political considerations also played an important
role. Countries such as France may have regarded monetary union as a way of gaining greater influence over
their own monetary policy, as compared with the existing EMS, which is often interpreted as being dominated
by Germany.3 For its part, Germany may have supported
monetary union in exchange for benefits on other
issues, notably the acquiescence of its European neighbors in its rapid unification with the former East
Germany (see Garrett 1994 and Woolley 1994).

While political considerations in some countries
may have favored monetary union, critics such as
Feldstein (1992) and Dornbusch (1996) argue that,
from an economic perspective, monetary union would
be a mistake for Europe. In their view, a country hit by
a decline in worldwide demand for its output has two
main ways of adjusting. One involves reducing relative
prices and wages in the country affected. However,
given the rigidities in European labor markets, a reduction in wages relative to those in other countries might
occur only after a long and painful period of recession.
The other way involves offsetting changes in economic
policy, such as a loosening of monetary policy or a
depreciation of the exchange rate that would reduce
the need for nominal wage reductions. As far as individual countries are concerned, monetary union would
eliminate the possibility of changing monetary policy or
the exchange rate, forcing adjustment back primarily
onto the labor market. From this perspective, the economic recoveries that occurred in Italy and Britain after
those two countries allowed their currencies to depreciate in 1992 illustrate the advantages of retaining
separate currencies and autonomy in economic policymaking.

T A B L E 1 Maastricht Convergence Criteria, 1996

Country
Criteria

Annual
Inflation Rate
(Percent)

Long-Term
Interest Rate
(Yield)

Government
Budget Deficita

Government
Debta

3.0

60.0

2.6

8.9

Austria

4.3

71.7

1.7

6.5

Belgium

3.3

130.6

1.6

6.7

Denmark

1.4

70.2

2.2

7.4

Finland

3.3

61.3

0.9

7.4

France

4.0

56.4

2.1

6.6

Germany

4.0

60.8

1.3

6.3

Greece

7.9

110.6

8.4

15.1

Ireland

1.6

74.7

2.1

7.5

Italy

6.6

123.4

4.7

10.3

+0.9

7.8

1.3

7.0

The Netherlands

2.6

78.7

1.2

6.3

Portugal

4.0

71.1

3.0

9.4

Luxembourg

Spain

4.4

67.8

3.8

9.5

Sweden

3.9

78.1

1.6

8.5

United Kingdom

4.6

56.3

3.0

8.0

a
As a percentage of GDP
Source: European Commission (1997)

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

Other economists counter that the absence of monetary union can itself be a source of problems. Buiter
(1996) argues that if exchange rates are flexible, financial shocks will move them and result in temporary
changes in international relative prices and wages that
are not required by the underlying real fundamentals
and that have negative effects on economic performance. In a similar vein, Obstfeld (1996) argues that as
long as a discretionary devaluation is possible, a country has more than one economic equilibrium, some of
which are worse for the country than a permanently
fixed exchange rate. He suggests that Italy was in such
a “bad equilibrium” prior to its devaluation in 1992, with
unemployment and real interest rates both at suboptimally high levels.
Regardless of their motivations, European policymakers no doubt were hoping for a smooth transition to
monetary union. The policymakers who signed the
Maastricht Treaty in December 1991 probably believed
that with minor exceptions, EMS exchange rates would
be kept within the existing target bands until monetary
union was achieved; in effect, monetary union would
simply shrink the width of the bands down to zero.
However, those expectations of exchange market tranquility were dashed just a few months after the signing.
The British pound and Italian lira came under
enormous pressure as investors bet that those two governments would not maintain their exchange rates in
the face of domestic economic weakness. In September
1992 both currencies dropped out of the EMS and soon
fell well below their previous values. The following year
further speculative pressures on other currencies led to
a substantial widening of most of the EMS exchange
rate bands from plus or minus 21⁄4 percent to plus or
minus 15 percent. At that point, prospects for achieving
monetary union on the Maastricht schedule looked dim.
However, since the crisis of 1993, exchange markets within Europe have been generally stable. In the
case of members of the EMS the 15 percent bands allow
for fairly large exchange rate movements, but most of
the time central banks have succeeded in keeping actual exchange rates within much narrower boundaries.
For example, throughout 1996 the French franc was
kept within or very close to the narrow pre-1993 target
band, even though officially the wide bands were in
effect. As of this writing, with the exchange markets
fairly tranquil and political leaders in key countries,
notably France and Germany, still publicly committed,
the odds on monetary union starting up in 1999 have

improved considerably from what they were during the
crisis year of 1993. Nevertheless, major issues remain
unresolved.
One of the major unresolved issues is the question
of which countries will be part of the initial monetary
union. The current plan is for the political leaders of the
fifteen countries in the European Union to meet early in
1998 in order to make this decision. At that time, each
country’s economic data for 1997 should be available
and could be compared with the convergence criteria in
the treaty that provide guidelines for assessing a country’s readiness for monetary union.

The Convergence Criteria
hen the treaty was signed, economic conditions in the various EU members differed substantially. The treaty specified that to be
considered ready for monetary union a country’s inflation rate and long-term interest rates should first converge to values similar to those of other prospective
members. The treaty also set targets for fiscal policy and
exchange rate behavior for each prospective member.
The specific convergence criteria are as follows:
inflation in each prospective member is supposed to be
no more than 11⁄2 percent above the average of the inflation rates in the three countries with lowest inflation
rates; long-term interest rates are to be no more than 2
percent above the average interest rate in those countries; the exchange rate is supposed to have been kept
within the target bands of the European Monetary
System with no devaluations for at least two years prior
to joining monetary union; and, importantly for the current debate, there are two requirements regarding fiscal
policy. One fiscal criterion is that the budget deficit in a
prospective member should be at most 3 percent of
GDP; the other is that the outstanding amount of government debt should be no more than 60 percent of a
year’s GDP.
Table 1 shows each country’s performance in 1996
relative to the criteria for inflation, long-term interest
rates, fiscal deficit, and level of government debt.4 A
majority of the members of the EU satisfied the inflation and interest rate criteria, but nearly all were in violation of at least one of the two fiscal criteria.
The economic rationale for the fiscal criteria is
that such limits are needed to ensure the support and
commitment of all monetary union members to the goal
of low inflation enshrined in the treaty. Historically, governments have sometimes used inflation as a way of

3.For evidence on whether Germany dominates the EMS, see von Hagen and Fratianni (1990) and Herz and Roger (1992).
4.The exchange rate criterion is not shown because it does not have a numerical value. As discussed earlier, the exchange rate
criterion requires that during the two years prior to a country’s entry into monetary union, its exchange rate be kept within the target bands of the EMS, with no devaluations.

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

raising revenue to maintain spending on politically popular programs. Once monetary union is achieved, inflation could not be confined to one member but would
necessarily involve the entire membership. A single
member wishing to pursue an inflationary policy might
exert pressure on the European Central Bank to raise
inflation throughout the union. Alternatively, if a member government with large debts had financial difficulty, the European Central Bank might feel obliged to bail
it out to avoid a financial crisis, at the cost of compromising its low-inflation goal.
The fiscal criteria
were intended to
ensure that only govCritics argue that, from
ernments with sound
finances would be able
an economic perspective,
to enter the union.
monetary union would be
Moreover, to guard
a mistake for Europe. . . .
against future problems
the members of the EU
It would eliminate the poshave agreed to set limsibility of changing moneits on deficits even
tary policy or the exchange
after monetary union
is achieved. According
rate, forcing adjustment
to the Stability Pact
back onto the labor market.
approved by European
finance ministers in
December 1996, members of the monetary union will be fined if they consistently violate the 3 percent limit on budget deficits (J.P.
Morgan and Company 1996b).5
The economic rationale for the fiscal criteria has
been questioned by many observers (see Bean 1992 and
Kenen 1992). One issue is whether the specific numbers
in the treaty are optimal. Buiter, Corsetti, and Roubini
(1993) and Eichengreen (1994) argue that the numerical limits of 3 percent for deficits and 60 percent for
debt are arbitrary and give little indication of whether a
country is suitable for monetary union. According to
Bean (1992), the only historical justification for these
limits is that they happen to be close to the average that
prevailed at the time the treaty was signed.
Masson (1996) argues that efforts to meet the
deficit criterion have diverted attention from other
important fiscal problems. He points out that since 1992
governments have often used the Maastricht criterion
as justification for imposing tax increases. However,
considering the sluggish growth and high unemployment that have prevailed in many European countries,
he suggests that reductions in high tax burdens and cutbacks in social transfers—for example, generous early
retirement benefits and high unemployment benefits
that discourage job seeking—would seem preferable
methods of reducing budget deficits because they would
encourage an expansion of economic activity and, by so
24

doing, raise the tax base. In many European countries,
high taxes are needed to finance government spending
of 50 percent or more of national output. Moreover, like
the United States, many European countries will face
major fiscal pressures soon after the turn of the century as demographic factors cause soaring increases in
the cost of retirement programs.6
More generally, it is debatable whether restrictions
on fiscal policy are needed for a successful monetary
union. Eichengreen and von Hagen (1995, 1996) note
that many existing monetary unions, including the
union of Belgium and Luxembourg, impose no debt or
deficit limits on the members. In the United States,
there is no nationwide agreement that limits the budget
deficits of individual states. Some states do have limits
on deficit spending, but these were adopted on a stateby-state basis and were not motivated by the desire to
make monetary union viable.
Eichengreen and von Hagen study various monetary unions around the world, including the United
States, Canada, and Australia. They argue that restrictions on borrowing by subunits of a monetary union are
most common when those subunits have little control
over their own sources of revenue: for example, in some
countries almost all revenue is raised by the central
government, with part being passed on to subunits to
finance their activities. When the sub-units control
their own sources of revenue, restrictions on borrowing
are often not imposed.
In the European context, the national governments
will be subunits after monetary union is achieved.
Currently and for the foreseeable future, the national
governments are financed predominantly with their
own sources of revenue: very little spending is or would
be financed by central EU institutions based in
Brussels. Eichengreen and von Hagen conclude that the
EU would therefore not need fiscal limits on the national governments in order to have monetary union.
Buiter (1996) also downplays the need for fiscal
restrictions on members of the monetary union. In his
view, a default or rescheduling by one member country—for example, Italy—would not necessarily be a
problem for the EU as a whole. Its costs should properly fall on either the owners of the debt, Italian taxpayers, or those who benefit from Italy’s public spending.
The European Central Bank would become involved if a
financial or banking crisis ensued, but in his view the
way to avoid such a snowballing crisis would be to use
bank supervision and regulation to set upper limits on
the exposure of financial institutions to risks of default
by European governments. Of course, such limits on
exposure might require significant portfolio shifts
because relative to their capital many banking systems
currently have large exposures to their home-country
governments.

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

Regardless of its economic desirability, the deficit
criterion has taken on political importance, especially
because of German leaders’ insistence that only governments satisfying it be allowed into the monetary
union. Germany’s highest court has ruled that the fiscal criteria are an integral part of the treaty: if they are
violated, Germany may be required to renounce monetary union (Gros 1995, 4). Given Germany’s economic
and political importance in Europe, its withdrawal of
support would probably spell the end of monetary
union.
The actual language of the treaty is not in fact so
rigid. It indicates that political leaders can exercise
some judgment rather than having to apply the convergence criteria mechanistically to determine a country’s
readiness. In particular, the treaty states that a deficit
above 3 percent of GDP should not be considered excessive if the deficit “has declined substantially and continuously and reached a level that comes close” to the
limit or if the deficit “is only exceptional and temporary”
(European Commission 1997, 17).
With so many prospective members in violation of
at least some of the convergence criteria, and little
chance that major progress can be made toward meeting them in the few months remaining before decisions
about initial membership are scheduled to be made, the
shape of the initial union remains an open question.

The Initial Union: Maxi-, Mini-, or Delayed?
he combination of doubts about whether all or
even most EU members would actually satisfy all
the convergence criteria and the insistence of
some countries (notably Germany) that the criteria be
strictly enforced has generated continuing debate over
what will actually transpire when the treaty’s deadline
for beginning the monetary union is reached. There are
three main possibilities: a maxi-union, a mini-union, or
delay.
Maxi-union. A maxi-union would be a broad monetary union that would cover most of the EU, including at
least three of the four largest members, namely,
Germany, France, Italy, and Britain. This alternative
would generate the greatest benefits in terms of

reduced transactions costs, but the diversity of its membership might produce severe internal strains as different countries push for different monetary policy
choices. For example, according to Shilling (1997), 90
percent of mortgages in Britain have adjustable interest
rates compared with only 30 percent in Germany. As a
result, changes in interest rates have much stronger
direct effects on homeowners in Britain than in
Germany, effects that could at times result in divergent
views about monetary policy in the two countries.
As far as entry is concerned, the biggest question
marks are whether Italy and Britain will join. Italy very
much wants to join the monetary union, in part as a
matter of national pride.7 Along with France and
Germany, Italy was one of the founding members of the
European Community in the 1950s, and it opposes the
idea of being left behind by the others.8 Unfortunately
for its chances, Italy has for several years been in violation of the convergence criteria (European Commission
1997). Perhaps the biggest hurdle is its fiscal problem:
its budget deficit has exceeded the 3 percent limit for
some years, and its stock of debt has exceeded 120 percent of GDP, double the convergence criterion of 60 percent.
In recent years Italy has managed to reduce its
inflation rate and long-term interest rates enough to
more nearly satisfy those two criteria than in the past,
and it has also cut its budget deficit substantially.
Moreover, it reentered the EMS in late 1996, albeit with
new target bands that implied a substantial devaluation
(more than 30 percent) from the rate prevailing just
before its departure in 1992. If Italy can keep its
exchange rate within the new target bands until late
1998, it will come into compliance with the exchange
rate criterion just prior to the scheduled start of monetary union. Nevertheless, only loose interpretations of
the convergence criteria will make it likely that Italy
can qualify for monetary union in 1999, given its fiscal
problems.
Britain is in a relatively good position as far as the
convergence criteria, but it has a traditional diffidence
about tying itself to its continental neighbors as shown,
for example, by its decision not to join the Common

5.The fines may range from 0.2 to 0.5 percent of a country’s GDP and are imposed by vote of the political leaders on the
European Council, the highest decision-making body of the EU. No fine is to be imposed if the deficit occurs during a severe
recession or because of “exceptional circumstances.”
6.The Organisation for Economic Cooperation and Development (OECD) (1995) shows that of the G-7 countries (the United
States, Germany, France, Italy, the United Kingdom, Japan, and Canada), all except the United Kingdom will face major
budgetary pressures from the interaction of demographics and retirement programs after the turn of the century.
7.See the Financial Times, October 11, 1995, and July 21, 1997.
8.For example, when the German finance minister stated that Italy would not be one of the initial members of monetary union,
his remarks created a furor in Italy. The Italian prime minister responded by insisting that his country was committed to
being an initial member and also suggested that the entire project be delayed rather than go forward without Italy. See the
Financial Times, September 23 and 25, 1995.

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

Market when it was founded in the 1950s.9 In addition,
Britain is particularly cautious about pegging its
exchange rate because, rightly or wrongly, several periods of recession or sluggishness in Britain during this
century have been blamed on pegging the pound at an
overvalued rate.10
The Labour government that took power in May
1997 seems inclined to take a wait-and-see attitude,
with the intention of joining monetary union only after
it has proven to be a success. However, it is possible that
Britain might decide to go ahead if nearly all the other
members, including Italy, decide to start together in
1999.11
Mini-union. The second possibility is a mini-union
that would leave out much of the EU. Most discussion of
this option has focused on a possible union involving
Germany, France, the Benelux countries, and perhaps
one or two other small countries like Ireland or Austria.
These countries have been in compliance with several
of the convergence criteria for the past several years
and are likely to continue in compliance in 1997
(European Commission 1997). Moreover, exchange
rates within this smaller group have been kept within
fairly narrow bands for the past several years.
Nevertheless, even the mini-union faces obstacles.
One problem is that several of these countries are in
violation of at least one of the convergence criteria, usually in the fiscal area. In particular, for some time
Belgium has had outstanding debt of more than 120 percent of GDP. Moreover, budget deficits in Germany and
France were above the convergence limit of 3 percent of
GDP in 1995 and 1996, partly because sluggish growth
has boosted spending on such items as unemployment
benefits while cutting into tax receipts (European
Commission 1997).
Delayed. The problems with the maxi- and miniunion options have led to speculation about a third
option: delay. Perhaps the start of monetary union could
be put off for two or three years in the hope that by that
time Germany and France (and perhaps Italy) would be
in compliance with the deficit criterion. This option
would, however, cause acute political embarrassment
for the leaders of France and Germany, who have been
instrumental in pushing monetary union forward.
Another risk is that during the interim other obstacles
could arise that would indefinitely delay monetary
union. The main risk, though, is the possibility that the
new deadline might not be credible to market participants, resulting in financial market turmoil.

The Bargaining Process
ow will the bargaining process turn out?
Economic models of strategic behavior, in which
the offers made by bargainers are influenced by
their expectations about the future behavior of others,

H
26

offer some insights. Chang (1995) develops a model in
which two countries may benefit from monetary union
but each wants to maximize its share of those benefits.
In some cases the two countries will reach an immediate agreement and unify their currencies, but in other
cases agreement will be delayed by a number of periods
of bargaining. Moreover, private market expectations
affect the length of delay. Alesina and Grilli (1993)
examine whether a mini-union is a good first step
toward complete monetary union. They consider the
case in which a few countries in the EU proceed with
monetary union and then, by majority vote, decide
whether to allow additional countries to join. Because a
maxi-union is politically feasible in their model, in the
sense that every country is better off with a maxi-union
than with no union, one might logically expect a miniunion to be a stepping stone to full union. Alesina and
Grilli show, however, that a mini-union may in fact prevent complete monetary union because it may be in the
interests of the initial members to veto the others. This
analysis provides a rationale for Italy’s reluctance to be
left behind at the beginning of monetary union.
Other scenarios are possible. The Maastricht treaty
specifies that the decision to admit an individual country into monetary union will not be made by a simple
majority vote but by the vote of a “qualified majority.”12
Under this procedure, less than half the fifteen members of the EU could block a country’s admission. De
Grauwe (1996b) argues that if the most commonly discussed version of a mini-union is proposed (consisting
of Germany, France, the Netherlands, Belgium, and
Luxembourg, plus possibly Austria or Ireland), such a
proposal will be blocked by negative votes from some of
those left out. For example, the group of the four southern European members (Italy, Spain, Portugal, and
Greece) have enough votes to block the mini-union. De
Grauwe concludes that the only politically viable choices will be maxi-union or postponement.
Countries such as Germany might find maxi-union
more palatable if a suggestion by De Grauwe (1995) and
Gros (1995) were adopted. They propose that, rather
than putting so much emphasis on whether a country
meets the convergence criteria prior to the start of
monetary union, as in the current transition process,
the treaty be changed to take away a country’s vote on
the European Central Bank’s governing board after the
start of monetary union whenever that member violates
the deficit limit. Under this approach, countries with
large fiscal deficits could join and remain members of
the union but would be unable to vote to bail themselves out of fiscal difficulty through higher inflation.
J.P. Morgan (1996a) suggests another possibility. A
mini-union could start in 1999, with disappointed
would-be members such as Italy or Spain assuaged by a
conditional commitment that they would be allowed to

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

C H A R T 1 Eurocurrency Interest Rates (Italy minus Germany, Weekly Average)

Spread (percent)

0
1990

1991

1992

1993

enter a year or two later, as long as they made further
progress toward meeting the convergence criteria.
Because the members of the EU are constantly
negotiating over a wide range of issues, there are many
such options that countries strongly favoring an initial
mini- or maxi-union can use to try to win over their
opponents. Accordingly, as long as political leaders in
the two largest countries in the EU, Germany and
France, are committed to going ahead, the prospects for
at least a mini-union beginning in 1999 seem favorable.

Market-Based Probabilities of Monetary Union
he prospect of monetary union has implications
for the patterns of interest rates in Europe that
can be used to make rough estimates of whether
market participants expect monetary union to go forward. In the past, interest rates often differed considerably, even for the same borrower, depending on the
denomination of the debt’s currency. For example,
Chart 1 shows that over the last several years shortterm interest rates denominated in Italian lire have
usually been at least 200 basis points above those

1994

1995

1996

1997

denominated in deutsche marks, thereby compensating
for expected depreciation of the Italian currency.
Once exchange rates are fixed permanently at the
start of monetary union, currency of denomination
should no longer affect interest rates in the member
currencies because (for example) Italian lire and
German deutsche marks would both be convertible into
the new euros at a fixed and unchanging rate: expected
depreciation of the lira vis-à-vis the deutsche mark
would become zero. Long-term interest rate contracts
that are written before monetary union but apply to
periods after it should reflect this lack of future depreciation.
A special version of a concept called covered interest parity can be used to estimate the probability that
market participants attach to monetary union going
ahead on schedule. Intuitively, covered interest parity
states that as investors seek the highest returns on their
liquid assets in different countries, foreign returns that
are hedged or “covered” against future changes in
exchange rates will be equal to the returns on similar
domestic assets.

9.For instance, see Dornbusch (1996), Sutherland (1997), and the Economist (September 21, 1996).
10.One such episode occurred in the 1920s when Britain returned the pound to its pre–World War I value in terms of gold and
the dollar (see Ingram 1983, 140–56). Another occurred in the mid-1960s, culminating in the devaluation of the pound in
late 1967 (see Cohen 1969, 143–49).
11. See Sutherland (1997). One factor in Britain’s decision is the concern of some economists and financial executives that
London’s role as a financial center would suffer if monetary union, especially a maxi-union, occurs and Britain stays outside. Their influence on the new government may be sufficient to overcome the doubters. See “Growing Fears in Britain of
Single-Currency Isolation,” New York Times, August 22, 1996, D2.
12.Qualified majority voting is a special system of weighted voting used by the EU. Under this procedure, large countries such
as Germany and France have more weight than small ones such as Ireland and Finland. To be approved by a qualified
majority, a proposal must win roughly 70 percent of the weighted votes.

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

More technically, covered interest parity states
that in the absence of capital controls, the difference
between the spot exchange rate (the rate on conversions of money from one currency to another that settle
immediately) and the forward exchange rate (the rate
on conversions of money that are agreed upon today but
do not settle until some time in the future) is just
enough to offset cross-country differences in interest
rates, thereby making investors indifferent between
investing at home and abroad. Covered interest parity,
discussed in more depth in many international economics textbooks, can be represented as follows:

Rt*,T − Rt,T =

Ft,T − St
,
St

(1)

where Rt,T is the interest rate in the home country at
time t on securities (for example, Treasury bills or certificates of deposit) that mature at time T (for example,
three months in the future); Rt,T* is the interest rate in
the foreign country on similar securities with the same
maturity date; St is the spot exchange rate at date t,
measured in foreign currency per unit of domestic
money; Ft,T is the forward exchange rate, measured in
foreign currency per unit of domestic money, that is
agreed upon on date t but does not settle until the forward contract matures on date T (which coincides with
the term of the interest rates Rt,T and Rt,T* ).
Equation (1) is the most common form of covered
interest parity; if it holds, and various researchers such
as Frenkel and Levich (1975) and Taylor (1987) have
found that it holds quite well when capital controls are
not in force, an investor gets the same rate of return on
a foreign security that is covered for exchange rate risk
as on a domestic security.

Covered interest parity should also hold in terms of
forward interest rates. A forward interest rate is an
interest rate that pertains to a time period that begins
not today but sometime in the future. For instance, suppose some investors have bonds that mature five years
in the future, and they wish to lock in a return on those
funds for three additional years. Some banks are willing
to agree today to accept the investors’ deposit of the
bond proceeds five years from now and to pay them
interest at a rate agreed today for the following three
years. The interest rate on such a contract would be a
forward interest rate with settlement five years in the
future and a maturity of three years.
Suppose such investors were considering two
options: investing at the forward deutsche mark interest rate or investing at the forward Italian lira interest
rate. If deutsche marks are the home currency for these
investors, at the maturity date of the forward interest
1
contract they would receive (1 + RDt,t1,T)T–t deutsche
marks for each mark they deposited, where RDt,t1,T is the
annualized forward interest rate on deutsche marks
today (at time t) for settlement at time t1 with maturity
date T; hence the funds would actually be on deposit for
(T – t1) years.
Alternatively, if the investors made a covered
investment in Italian lire, they would convert each
deutsche mark to Ft,t1 lire at time t1 (where Ft,t1 is the forward exchange rate in lire per mark prevailing today [at
time t] for settlement at time t1). They would then
invest the proceeds until time T, receiving at the end the
1
amount (Ft,t1) 3 (1 + RLt,t1,T)T–t in lire; RLt,t1,T is the
annualized forward interest rate on lire today (at time t)
for settlement at time t1 with maturity date T. Finally, to
be fully covered against exchange rate risk, the investors

C H A R T 2 Forward Interest Rates (Italy minus Germany, Weekly Average)
10

Spread (percent)

8
6
4
2
0
–2
–4
–6
–8
1990

1991

1992

1993

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

1994

1995

1996

1997

would have to make a contract today to convert their
final proceeds in lire back into deutsche marks: each lira
would yield (1/Ft,T) deutsche marks.
For investors to be indifferent between the two
investment alternatives, the ultimate return on them
should be equal, or

(1 + RDt, t1, T )T− t =
1

Ft, t1
Ft, T

(1 + RLt, t1, T)T − t ,
1

(2)

where the term on the right-hand side is the covered
return (in deutsche marks) from investing at the
Italian forward interest rate. Equation (2) is another
version of covered interest parity, expressed in terms of
forward interest rates.
De Grauwe (1996a) observes that if market participants were convinced that permanent monetary union
involving Italy and Germany would occur on schedule
and that the times t1 and T were both after the scheduled beginning of monetary union, then the forward
exchange rates Ft,t1 and Ft,T should be identical to one
another. This equality would hold even if the postunion
conversion ratio between lire and deutsche marks, St1,
was uncertain as of time t. In this case, equation (2)
indicates that the forward interest rates RDt,t1,T and
RLt,t1,T would be equalized as well, even if they were
observed at time t well before monetary union.
As an example, Chart 2 shows the difference
between lira and deutsche mark forward interest rates
from 1990 through January 28, 1997. These are five-year
forward interest rates on five-year interbank loans.13
The horizontal axis gives the date of observation, t in
terms of the notation in equation (2), where settlement
date t1 is five years after t and maturity date T is five
years after t1.
The earliest observations were made well before
the Maastricht Treaty was signed, at a time when expectations of monetary union were presumably low.
Moreover, for the early observations, most of the fiveyear periods covered by the contracts (the period
between the settlement date t1 and the maturity T) fell
before the scheduled 1999 start date for monetary
union. For example, the points on the chart for January
1991 represent contracts made in January 1991 with
settlement dates in January 1996 and maturity dates in
January 2001, implying that roughly three-fifths of the
period covered by these particular contracts fell before
1999. The treaty was signed in late 1991, and as time
passed the fraction of the period covered by these contracts that fell after the scheduled beginning of monetary union gradually rose, making expectations about
monetary union more and more important in their deter-

mination. After January 1, 1994, the entire period covered by these contracts fell after the scheduled beginning of monetary union.
During the first few months shown in Chart 2 Italy’s
five-year forward interest rate spread showed tremendous volatility, perhaps in part because capital controls
were still in effect, though slated for removal. By the
second half of 1990 volatility lessened, and the spread
usually ranged between 300 and 500 basis points. Over
the next few years the forward spread tended to rise and
fall along with the short-term interest rate spread
shown in Chart 1, but in the second half of 1996 the forward spread fell well below the short-term spread. In
January 1997 the forward spread averaged only 87 basis
points, even though the short-term spread for the next
three months was still high, 411 basis points. The drop
in the forward spread so far below the short-term spread
is consistent with a market expectation that in the
future Italian interest rates will be much closer to
German ones than they are today.
A rough estimate of the probability of EMU can be
derived from the forward interest rate spreads, as
described by De Grauwe (1996a). Suppose the forward
interest rate spread observed before the beginning of
monetary union is a weighted average of the spreads
that would prevail in two alternative scenarios—namely, that monetary union occurs on schedule or it is
delayed indefinitely—with the weights being the market’s assessment of the probability of each. That is,

sto = pt × stu + (1 − pt ) stN ,

(3)

where sto is the forward interest rate spread versus the
deutsche mark observed at time t (prior to monetary
union), pt is the market’s assessment at time t of the
probability that monetary union will proceed on schedule, stu is the spread that would be expected to prevail if
monetary union proceeds, and stN is the spread that
would be expected to prevail if monetary union does not
proceed.
As discussed earlier, if the forward interest rates
pertain entirely to the period after monetary union is
scheduled to begin, they should be equalized, implying
that stu would be zero. In this case, equation (3) simplifies to the following expression for the probability of
monetary union pt:

pt = 1 − ( sto / stN ).

(4)

As noted earlier, data on sto are available. The problem is
estimating stN, the forward interest rate spread that

13.Market quotations on forward interest rates in various European currencies were provided by J.P. Morgan and Company.

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

C H A R T 3 Probability of Entering EMU
France

Percentage

100
80
60
40
20
0
1994

1995

1996

1997

1996

1997

1996

1997

1996

1997

1996

1997

Britain

Percentage

100
80
60
40
20
0
1994

1995

Belgium

Percentage

100
80
60
40
20
0
1994

1995

Italy

Percentage

100
80
60
40
20
0
1994

1995

Spain

Percentage

100
80
60
40
20
0
1994

1995

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

would be expected to prevail if monetary union does not
proceed. De Grauwe suggests using the average spreads
on five-year forward interest rates that were observed
during 1990, a year before the Maastricht Treaty was
signed and a time when monetary union seemed a remote
possibility. However, charts of the data on spreads show
great volatility for Italy (see Chart 2) and Spain in early
1990, including some sizable negative values (meaning
that Italian and Spanish five-year forward interest rates
fell substantially below German ones).
The position taken here, however, is that these
negative values reflect market imperfections or capital
controls and do not represent the market’s true expectation about future interest rates. Indeed, Italy did not
abolish its remaining restrictions on capital flows until
May 14, 1990 (Ungerer and others 1990).
Accordingly, instead of using all of 1990 to estimate
stN, this study uses the average spread during the second
half of that year. The resulting estimates of pt for France,
Britain, Belgium, Italy, and Spain are shown in Chart 3.
The charts start in January 1994, when the five-year forward interest rates used in the calculations began to
apply solely to the period after the scheduled commencement of monetary union in January 1999. The probabilities pt calculated using equation (4) were converted to
percentages by multiplying by 100. A value of zero corresponds to zero probability that the country will be part of
monetary union, while a value of 100 corresponds to virtual certainty that the country will participate.14
The results for France indicate that the markets
have usually regarded that country as being almost certain to participate in monetary union. The results for
Britain are surprising: since 1994 market estimates of
the probability of British participation have usually been
well above 50 percent and in January 1997 some 80 percent. Considering the political opposition that exists in
Britain, these probabilities seem high. De Grauwe
(1996a, 11–12) obtains similar results but argues that
1990 was a poor benchmark year for such calculations in
the British case because in October of that year the
pound entered the EMS after months of market turbulence. Moreover, many observers claimed at the time

that the pound had entered the EMS at an overvalued
exchange rate and that sooner or later a devaluation was
certain. The forward interest rate spread for pound sterling that prevailed during 1990 may therefore not be an
accurate proxy for the market’s estimate of the spread
that would prevail if Britain stayed out of monetary
union. Another explanation of the surprising British
results is given in the caveat below.
Belgium, Italy, and Spain all show notable increases in the last year or so of the period. De Grauwe
(1996a), whose data sample ended in March 1996,
reported that as of the end of his sample Belgium’s probability of joining was about 60 percent while that of Italy
and Spain was much less, perhaps 20 or 30 percent.
Using the slightly different proxy for s tN (only the last
half of 1990) and extending the sample through January
1997, the charts in this article show end-of-sample probabilities of about 100 percent for Belgium, 90 percent
for Spain, and more than 80 percent for Italy. Strictly
speaking, these are probabilities that the country in
question will be in monetary union five years after the
date of the observation. Accordingly, the observations
from January 1997 indicate a high likelihood that these
three countries will enter monetary union either at the
scheduled beginning in January 1999 and certainly no
later than January 2002.
Using a somewhat different approach, J.P. Morgan
(1997) has also estimated market expectations of EMU
that are quite high for most of these countries. This
approach uses non-European financial data to estimate
the forward interest rate spread for potential EMU members that would prevail if there were zero probability of
the country joining.15 The company’s results indicate
that market perceptions of the likelihood of a maxiunion increased noticeably in the second half of 1996,
probably because of progress toward the Stability Pact at
two political summits during the period. As of early
February 1997, which was approximately the end of the
data sample used in Chart 3, the Morgan approach yielded the following probabilities of joining EMU: 100 percent for France and Belgium, 85 percent for Spain, 66
percent for Italy, and 40 percent for Britain.16 These

14.In some time periods, the estimated probability obtained from equation (4) is either negative or above 100 percent. Negative
values can occur if the observed spread sto is larger than the average spread that prevailed in the second half of 1990, when
monetary union was presumably considered a remote possibility. Values above 100 percent can occur if the observed spread
sto is negative, meaning that the country’s forward interest rate is actually lower than Germany’s. Because probability is
normally defined only in the range between zero and 100 percent, the chart was drawn showing such observations as falling
at either 100 or zero.
15.For example, J.P. Morgan regressed French franc forward interest rate spreads vis-à-vis Germany onto financial variables
not directly affected by EMU, such as the U.S. three-month rate, the Japanese three-month rate, and the difference between
ten- and two-year interest rates in the United States. The regression was estimated using data from the late 1980s and early
1990s, a period when expectations of monetary union should have been very low. The estimated coefficients were then
applied to recent data on U.S. and Japanese rates in order to generate a proxy for the current value of stN.
16.These probabilities were reported in the Financial Times, March 4, 1997. In later weeks the probabilities for Spain, Italy, and
Britain dipped somewhat.
Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

estimated probabilities are lower than those shown at
the end of Chart 3 but are still quite substantial. If
either set of estimates is correct, market participants
have concluded that a mini-union, at least, seems virtually certain in the next few years and a maxi-union
including the two largest countries in Southern Europe
is quite likely.
The similarity of the probabilities obtained by different methods is comforting, but an important caveat
is in order. All these estimates depend critically on the
accuracy of the measure of the unobservable spread
that would prevail if monetary union did not occur. If
the proxy is not correct, the estimated probability
derived using it will of course be inaccurate as well.
Consider the case of Britain. In the chart, as noted earlier, the spread that actually prevailed between fiveyear forward rates on sterling and deutsche marks
during the second half of 1990 was used as a proxy—321
basis points. By January 1997 that spread had shrunk to
only 57 basis points, implying, using equation (4),
approximately an 80 percent probability that Britain
would join monetary union by 2002. However, the
shrinkage in the spread has another possible interpretation: perhaps Britain’s commitment to continuing low
inflation became substantially more credible during the
years between 1990 and 1997. In that case, one would
expect a reduction in the spread vis-à-vis deutsche
marks even if the market really was not expecting
Britain to participate in monetary union.
While the caveat suggests that all these probability
estimates should be treated with caution, the view here
is that it does not vitiate the entire exercise. Perhaps
the most interesting results are those for Italy and

Spain. Though still not in compliance with the convergence criteria, these two countries have made important progress in reducing their budget deficits during
the past few years. Italy has cut its deficit from 9.6 percent of GDP in 1993 to 6.6 percent in 1996, and Spain
has cut its from 6.8 to 4.4 percent over the same period
(European Commission 1997, 12). The governments of
both countries have consistently supported their membership in the proposed monetary union. According to
the results shown here, market participants think they
have a substantial likelihood of joining the union.

Conclusion
ore than five years ago the members of the EU
decided to form a monetary union by the end of
the decade. Many preparatory steps have been
taken, but a number of key decisions, notably about
which countries will be part of the union at its beginning, still remain to be made. These choices cannot be
put off much longer.
There is little chance that most of the countries
will comply with a strict reading of the convergence criteria for membership, but evidence from the financial
markets suggests that by early 1997 market participants
were leaning toward the belief that the political impetus in favor of a broad union might prevail in the end,
resulting in a monetary union that would encompass a
substantial portion of western Europe. The recent election in France has injected new uncertainty into the
process, though, and final decisions about monetary
union may remain up in the air until the last possible
moment.

REFERENCES
ALESINA, ALBERTO, AND VITTORIO GRILLI. 1993. “On the
Feasibility of a One- or Multi-Speed European Monetary
Union.” National Bureau of Economic Research Working
Paper No. 4350, April.

DE GRAUWE, PAUL. 1995. “The Economics of Convergence
towards Monetary Union in Europe.” Centre for Economic
Policy Research Discussion Paper No. 1213, July.

BEAN, CHARLES. 1992. “Economic and Monetary Union in
Europe.” Journal of Economic Perspectives 6 (Fall): 31–52.

———. 1996a. “Forward Interest Rates as Predictors of
EMU.” Centre for Economic Policy Research Discussion
Paper No. 1395, May.

BUITER, WILLEM H. 1996. “The Economic Case for Monetary
Union in the European Union.” Cambridge University.
Photocopy, November.

———. 1996b. “The Prospects of a Mini Currency Union in
1999.” Centre for Economic Policy Research Discussion
Paper No. 1458, September.

BUITER, WILLEM, GIANCARLO CORSETTI, AND NOURIEL ROUBINI.
1993. “Excessive Deficits: Sense and Nonsense in the Treaty
of Maastricht.” Economic Policy 16 (April): 58–100.

DORNBUSCH, RUDIGER. 1996. “Euro Fantasies.” Foreign Affairs
75 (September/October): 110–24.

CHANG, ROBERTO. 1995. “Bargaining a Monetary Union.”
Journal of Economic Theory 66:89–112.
COHEN, B.J. 1969. Balance of Payments Policy. Baltimore:
Penguin Books.

EICHENGREEN, BARRY. 1993. “European Monetary Unification.”
Journal of Economic Literature 31 (September): 1321–57.
———. 1994. “Fiscal Policy and EMU.” In The Political
Economy of European Monetary Unification, edited by
Barry Eichengreen and Jeffry Frieden, 167–90. Boulder,
Colo.: Westview Press.

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

EICHENGREEN, BARRY, AND JÜRGEN VON HAGEN. 1995. “Fiscal
Policy and Monetary Union: Federalism, Fiscal Restrictions,
and the No-Bailout Rule.” Centre for Economic Policy
Research Discussion Paper No. 1247, September .

KENEN, PETER B. 1992. EMU after Maastricht. Washington:
Group of Thirty.
MASSON, PAUL. 1996. “Fiscal Dimensions of EMU.” Economic
Journal 106 (July): 997–1004.

———. 1996. “Federalism, Fiscal Restraints, and European
Monetary Union.” American Economic Review Papers and
Proceedings 86 (May): 134–38.
EUROPEAN COMMISSION. 1990. “One Market, One Money: An
Evaluation of the Potential Benefits and Costs of Forming an
Economic and Monetary Union.” European Economy 44.
———. 1997. “Report on Convergence in the European
Union in 1996.” European Economy (January, Supplement
A, no. 1): 1–31.
FELDSTEIN, MARTIN. 1992. “The Case against EMU.” Economist,
June 13, 23–26.
FRENKEL, JACOB A., AND RICHARD M. LEVICH. 1975. “Covered
Interest Arbitrage: Unexploited Profits?” Journal of Political
Economy 83 (April): 325–38.
GARRETT, GEOFFREY. 1994. “The Politics of Maastricht.” In The
Political Economy of European Monetary Unification, edited by Barry Eichengreen and Jeffry Frieden, 47–65. Boulder,
Colo.: Westview Press.
GROS, DANIEL. 1995. “Towards a Credible Excessive Deficits
Procedure.” Centre for European Policy Studies Working
Document No. 95, July.

ORGANISATION FOR ECONOMIC COOPERATION AND DEVELOPMENT.
1995. “Effects of Ageing Populations on Government
Budgets.” OECD Economic Outlook 57 (June): 33–42.
PADOA-SCHIOPPA, TOMMASO. 1994. “The EMS Is Not Enough:
The Need for Monetary Union.” In The Road to Monetary
Union in Europe, edited by Tommaso Padoa-Schioppa,
117–34. Oxford: Clarendon Press.
SHILLING, A. GARY. 1997. “Good Luck, Tony.” Forbes 159,
February 24, 184.
SUTHERLAND, PETER. 1997. “The Case for EMU.” Foreign Affairs
76 (January/February): 9–14.
TAYLOR, MARK P. 1987. “Covered Interest Parity: A HighFrequency, High-Quality Data Study.” Economica 54
(November): 429–38.
UNGERER, HORST, JOUKO HAUVONEN, AUGUSTO LOPEZ-CLAROS, AND
THOMAS MAYER. 1990. “The European Monetary System:
Developments and Perspectives.” International Monetary
Fund Occasional Paper No. 73, November.

HERZ, BERNHARD, AND WERNER ROGER. 1992. “The EMS Is a
Greater Deutschemark Area.” European Economic Review
36:1413–25.

VON HAGEN, JÜRGEN, AND MICHELE FRATIANNI. 1990. “German
Dominance in the EMS: Evidence from Interest Rates.”
Journal of International Money and Finance 9 (1990):
358–75.

INGRAM, JAMES C. 1983. International Economics. New York:
John Wiley and Sons.
J.P. MORGAN AND COMPANY. 1996a. “EMU: Impact on Financial
Markets.” European Fixed Income Research, August.
———. 1996b. “FX Markets and Europe’s Stability Pact.”
Foreign Exchange Research, December.

OBSTFELD, MAURICE. 1996. “Destabilizing Effects of ExchangeRate Escape Clauses.” University of California at Berkeley,
Center for International and Development Economics
Research Working Paper No. C96-075, December.

WOOLLEY, JOHN T. 1994. “Linking Political and Monetary
Union: The Maastricht Agenda and German Domestic
Politics.” In The Political Economy of European Monetary
Unification, edited by Barry Eichengreen and Jeffry Frieden,
67–86. Boulder, Colo.: Westview Press.

———. 1997. “EMU Calculator Handbook.” Global Foreign
Exchange Research, January.

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

The Role of Currency
Derivatives in Internationally
Diversified Portfolios
P E T E R A . A B K E N A N D
M I L I N D M . S H R I K H A N D E
Abken is a senior economist in the financial section of
the Atlanta Fed’s research department. Shrikhande is
an assistant professor of finance at the Georgia Institute
of Technology and a visiting scholar in the financial
section of the Atlanta Fed’s research department. The
authors thank Rob Bliss, Jerry Dwyer, Larry Wall, and
Tao Zha for helpful comments and Elizabeth Bram of
Salomon Brothers for providing bond return data.

HE POWER OF DIVERSIFICATION IN REDUCING RISK IS WIDELY UNDERSTOOD AND PRACTICED
BY INVESTORS. IN RECENT YEARS INVESTORS HAVE BEEN TURNING TO FOREIGN MARKETS TO
OBTAIN EVEN GREATER SCOPE FOR DIVERSIFICATION THAN IS POSSIBLE IN A DOMESTIC MARKET.

WITH

THE INTERNATIONALIZATION OF SECURITY PORTFOLIOS, HOWEVER, ALSO COMES

AN ADDITIONAL RISK—FOREIGN EXCHANGE RISK.1

FOREIGN

EXCHANGE RATE FLUCTUATIONS INDUCE

CHANGES IN PORTFOLIO RETURNS BECAUSE UNCERTAIN FUTURE EXCHANGE RATES TRANSLATE RETURNS ON
FOREIGN-CURRENCY-DENOMINATED INVESTMENTS INTO DOLLAR RETURNS.2

DIVERSIFICATION

OF PORTFO-

LIO HOLDINGS ACROSS SEVERAL COUNTRIES CAN HELP MITIGATE FOREIGN EXCHANGE RISK.

DERIVATIVE

SECURITIES ARE INSTRUMENTS THAT ALTER THE CASH FLOWS OF A PORTFOLIO.

THE

USE OF CURRENCY

DERIVATIVES CAN FURTHER REDUCE RISK IN INTERNATIONALLY DIVERSIFIED PORTFOLIOS.

This article investigates the impact of currency
hedging on internationally diversified stock and bond
portfolios. It explains how currency hedging works and
shows how hedging affects actual historical portfolio
returns. The focus of the analysis is on index portfolios
of stocks and bonds from markets in seven industrialized countries. Portfolio diversification eliminates the
influence of what is called idiosyncratic risk—the
unpredictable losses specific to individual security
returns—from a securities portfolio. Domestic diversifi34

cation, however, leaves exposure to “systematic” risk,
the unpredictable losses that affect all domestic securities.3 Because domestic systematic risks are likely to
differ from country to country, international diversification can further reduce the volatility of portfolio returns
by mitigating country-specific risk.
Several studies have suggested that hedging
against foreign exchange risk has little effect on expected return, or may even enhance it, while reducing the
variability of portfolio returns (Perold and Schulman

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

1988; Thomas 1988, 1989; Eun and Resnick 1988, 1994;
Kaplanis and Schaefer 1991; Eaker and Grant 1991;
Glen and Jorion 1993; Levich and Thomas 1993).4 The
advantage of hedging has even been described as a “free
lunch” (Perold and Schulman 1988) because currency
hedging appears to deliver benefits at no cost.
This article reexamines the data for international
equity and bond returns and foreign exchange rates for
sample periods running from 1980 to 1996 for equities
and from 1986 to 1996 for bonds. Most of the previous
studies include sample periods that were dominated by
the dollar’s appreciation against most major currencies
during the first half of the 1980s. After the Plaza Accord
of 1985, the dollar began a long depreciation that lasted
until the mid-1990s.5 This more recent period is also
characterized by a different structure of security return
and foreign exchange volatilities and correlations. This
change had a significant impact on the apparent performance of hedging. These relationships and their effects
are explained in the following sections.
The results in this article are derived from an
analysis of “efficient” portfolios, securities portfolios that
offer the greatest feasible return for a given level of risk.
The apparent risk-reducing benefits of currency hedging
of equity portfolios in the early 1980s are not confirmed
for the 1986–96 period overall or for subperiods. In contrast, foreign long-term bond portfolios consistently
exhibited dramatically lower variability of hedged
returns compared with the variability of unhedged
returns, a finding that agrees with results from the earlier studies of currency hedging based on earlier sample
periods. However, even for bond portfolios, the case for
currency hedging is not decisive because, historically,
the lower variability of hedged return is associated with
lower returns. The decision to hedge depends on the
investor’s preference for risk and return.

Diversification
odern portfolio theory dates back to the work of
Markowitz (1952). Markowitz started with the
assumption that a portfolio’s riskiness may be
measured by the variance of its returns. He showed that
an investment in a portfolio of securities offers investors
risk and return combinations that are not possible from
individual securities. In most cases, diversification
allows an investor to obtain higher expected return for
the same risk or lower risk for the same expected return
relative to the return available from a single security.
Markowitz’s insight is easily seen by considering
the formulas for the mean and variance of return from
a two-asset portfolio:

rp = w1r1 + w2r2
sp2 = w12 s21 + w22 s22 + 2w12 w22 rs1s2,

(1)

where ri is the security return on security 1 or 2 or the
portfolio p, s 2i is the variance of the corresponding
return, w1 and w2 are portfolio weights, and r is the correlation coefficient between the individual security
returns. Because the portfolio weights are assumed to
sum to one, the portfolio mean return is a weighted average of the returns on the two assets. However, because of
the covariance term for s p2 in equation (1), a portfolio
containing both securities will usually have a lower standard deviation (square root of the variance) than simply
a weighted sum of their individual standard deviations.6
An efficient portfolio has the greatest feasible
return for a given standard deviation of return. The
later empirical section focuses principally on determining the proportions of international stock or bond portfolios that generate the efficient “frontier,” which is a
graph of efficient portfolios’ standard deviations against
their returns. A particular investor’s taste for risk and

1. Stock prices themselves may reflect the foreign exchange exposures of firms with multinational operations. However, firms
can reduce this risk using derivatives or other risk-management techniques. See Chow, Lee, and Solt (1997).
2. A security’s return is the rate of price appreciation, including associated cash flows such as dividend or interest payments.
3. The measure of risk used in this article is the standard deviation of a security’s excess return, that is, its return in excess of
the risk-free rate of interest. Because the portfolios used are market-value weighted index portfolios of stocks or bonds, the variability of excess return is assumed to reflect predominately systematic risk.
4. This article focuses on “buy and hold” strategies, constructed purely as hedges, which are described in a later section. A number of studies on foreign exchange markets claim that foreign exchange movements contain a predictable component. For
example, Glen and Jorion (1993) and Levich and Thomas (1993) show that by taking positions in foreign exchange derivatives based on forecasts of exchange rate movements, it is possible to earn “excess returns.” The key unresolved issue regarding these returns is whether they represent compensation for risk exposure. Exploiting apparent foreign exchange market
inefficiencies may offer the potential to enhance expected return without increasing risk.
5. In September 1985 the finance ministers and central bank governors of the so-called Group of Six industrial countries (the
United States, France, Germany, the United Kingdom, Japan, and Canada) met at the Plaza Hotel in New York City and
reached what was later referred to as the Plaza Accord or Agreement. They announced that it would be desirable for most
major currencies to appreciate vis-à-vis the U.S. dollar and pledged to intervene in exchange markets to accomplish this objective. The dollar had already started to fall during the spring and summer of 1985.
6. For perfectly correlated returns (p = 1), the standard deviation of portfolio returns is exactly equal to the weighted sum of
the standard deviations of the individual returns.
Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

return would guide the selection of an optimal portfolio
along the efficient frontier.
International Diversification. The principles of
diversification apply regardless of the kind of assets or
currencies of their denomination. What is different
about investing abroad is the assumption of foreign
exchange risk that comes with owning foreign securities. The impact of exchange rate movements on
unhedged dollar returns can be understood by considering the return in terms of two sources of risk, volatility of the foreign security returns and volatility of the
foreign exchange rate. Movements in both are largely
unpredictable, and they
are generally correlated with one another.
A security’s rate of
Foreign exchange rate
return, measured from
fluctuations induce changes
period t – 1 to t, is
defined as the rate of
in portfolio returns because
price appreciation plus
uncertain future exchange
associated cash flows
rates translate returns
such as dividend or
interest payments. The
on foreign-currencyreturn based on prices
denominated investments
denominated in foreign
into dollar returns.
or “local” currency is
referred to as the local
return. 7 The rate of
change of the exchange
rate, st / s t–1 – 1, is denoted by et, where positive values
signify an appreciation of the foreign currency.
The rate of return at time t in dollars on an
unhedged foreign investment is rt = (1 + rlt)(1 + et) – 1
= rlt + et + rltet.8 The dollar return rt depends on the
local security return rlt and the rate of change of
exchange rate et. The dollar return can be approximated by rt ' rlt + et because the cross-product term rltet is
generally small. For example, if the foreign equity index
over a three-month period depreciated by 3 percentage
points and paid dividends at the rate of 1 percent of the
index level, the local return would be –2 percentage
points. If during the same period, the exchange rate
appreciated by 4 percentage points, the total dollar
rate of return would be approximately 2 percentage
points.
For a portfolio involving securities denominated in
several currencies, the diversification effects can be
described by giving a weight wi to each portfolio, where
the subscript i indexes the portfolios available. The
weights for N index portfolios sum to unity. Based on the
approximation rt ' rlt + et for the unhedged dollar return
of an individual securities portfolio, Eun and Resnick
(1988) derive an approximation for variance of the
return on an unhedged multicountry securities portfolio
that takes the following form analogous to equation (1):
36

σ u ≈ ∑ i =1 ∑ j =1 wi wj ρijσ iσ j
N

(2)

144
42444
3
security return covariances

wwρ σ σ
∑
∑42
144
444
3
N

i =1

j =1

foreign exchange rate covariances

σ ,
∑ ∑ w w ρ σ3
14442444

i =1

j =1

l ,e

local return–foreign exchange rate covariances

where the first term represents weighted covariances of
the security returns on the N index portfolios making up
the overall portfolio (with superscript l for local
return), the second is for the covariances of the corresponding exchange rates (with superscript e for
exchange rate), and the third term is for the crosscovariances between exchange rates and security
returns, such as the mark exchange rate with the
Japanese equity portfolio return.
Chart 1 illustrates the benefits of international
diversification using as an example data from 1980 to
1985, a period that will be discussed in detail below. The
average annual return and standard deviation of a U.S.
stock portfolio is represented by the dot. The efficient
frontier generated by combining the U.S. portfolio with
stock portfolios from Germany, the United Kingdom,
Japan, France, Canada, and Switzerland lies above the
U.S. portfolio.9 For the same standard deviation of
return, the internationally diversified portfolio offers a
higher return. The minimum standard deviation efficient portfolio has a return that is 1 percentage point
higher than the standard deviation of the U.S. portfolio
and a standard deviation of return that is 2 percentage
points lower than the U.S. portfolio’s. In short, investors
who evaluate portfolios based on their expected mean
returns and standard deviations would choose a portfolio along the efficient frontier.

Currency Derivatives and Hedging
hile the choice of securities and their degree of
diversification fundamentally affects the riskreturn profile of a portfolio, further tailoring of
a portfolio’s risk-return characteristics can be achieved
through the use of derivative securities. Derivatives are
instruments that change the cash flows of a portfolio.
This transformation of cash flows alters fluctuations in
the market value of a portfolio. Hedging is a transformation of cash flows or market value that the investor
regards as reducing the risk of a position.
All hedging of securities portfolios considered in
this article is implemented using foreign exchange forward contracts. A foreign exchange forward contract is
an agreement between two parties to buy (or sell) foreign currency at a future date at an exchange rate
determined at the time of the transaction. (In contrast,

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

CHART 1
Example of an Efficient Frontier for
International Equity Portfolios, 1980–85
Unhedged Portfolios

Return

16
U.S. Portfolio

14
13

Standard Deviation

a spot contract specifies an immediate exchange of currency at the prevailing exchange rate.) Although other
kinds of derivatives can serve the same purpose as forwards, forwards are a simple, cost-effective way to alter
the variability of securities portfolio returns.10 Box 1
discusses the costs associated with hedging using forward contracts. Foreign exchange forward contracts are
sold by major commercial banks and typically have
fixed, short-term maturities of one, six, and nine
months. As with many other kinds of derivatives, forward contracts do not involve a net investment upon
initiation of a position.
Foreign Exchange Forward Contracts. The following example gives a straightforward hedging application, in which all risk is eliminated, and at the same
time demonstrates an important arbitrage condition
that determines the relationship between forward and
spot foreign exchange rates on the one hand and domestic and foreign short-term interest rates on the other.

This relationship is useful for understanding the portfolio hedging results.
The arbitrage condition known as covered interest
parity is given by the following equation:
f/s = (1 + rUS)/(1 + rDM),
where f and s are forward and spot rates, respectively,
expressed in units of dollars per mark, and rUS and rDM
are short-term rates of interest in the United States and
Germany, respectively (DM for deutsche mark). The
meaning of arbitrage condition is clarified as the example is developed.
Suppose an investor borrows one dollar and thereby obligates himself to repay 1 + rUS dollars upon maturity of the loan or bond in one month. By converting this
borrowing into deutsche marks at the spot exchange
rate s, the investor receives 1/s DM per dollar. The
investor then buys a one-month German Treasury bill

7. The return on a U.S. domestic securities portfolio is also a local return.
8. This discrete-time formulation is given in Eun and Resnick (1988). Eun and Resnick assume that the investor sells the
expected foreign currency proceeds from a foreign investment forward, whereas the examples in the text assume for simplicity that the current value of that investment is sold forward.
9. The efficient frontier is computed by solving the following problem. Suppose there are n securities. Let x be an n 3 1 vector
of portfolio weights, m be an n 3 1 vector of mean security returns, and S be an n 3 n covariance matrix of security returns.
The efficient portfolio for a target return of µ is determined by finding optimal portfolio weights x* that minimize the varix ′ ∑ x , subject to x ′µ = µ and x ′1 = 1 , where 1 is an n 3 1 vector of ones. An additionance of the portfolio’s returns: min
x
al constraint is imposed in this study that requires the portfolios’ weights to be nonnegative, that is, the asset portfolios are
not permitted to be sold short. Without the nonnegativity constraint, the optimization typically results in improbable or
infeasible positions in securities (or portfolios), in particular huge short positions that even most institutional investors cannot assume (Glen and Jorion 1993). The optimal portfolio variance is then given by x * ′ ∑ x *. The efficient frontier is generated by varying the target return µ and solving for the corresponding portfolio variances.
10. One alternative to standard forwards is “quanto” forwards and options. See Rubinstein (1991) and Reiner (1992). With such
instruments, the user avoids the quantity risk of forward contract hedges. A less exotic alternative is currency futures contracts traded on futures exchanges.

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

B O X

The Costs of Hedging
he benefits of hedging could potentially be offset by its
costs. There are the costs of dealing with a financial
intermediary, which provides access to hedging instruments such as forward contracts. These costs depend on
the particular instruments. Forward contracts involve
commission costs, and transactions at prices or rates
reflecting the payment of a bid-ask spread, and possibly the
opportunity costs of posting collateral against future losses on the forward position.1 Perold and Schulman (1988)
observe that hedging costs are the least significant of the
costs associated with international investment. They estimate that rolling over six-month forwards would incur
costs reflecting the bid-ask spread and transaction costs of
only 0.12 percent per year of the amount invested (Perold
and Schulman 1988, 48).
A potential cost of the hedge is the forward premium
or discount. As discussed in the text, short forward positions are closed out upon maturity of a contract and rolled
into new contracts. The new contracts fix the current forward rate for the hedge. If the foreign currency being sold
forward is at a discount (because the foreign interest rate
exceeds the home country rate), the investor is effectively
paying to hedge and the expected return of the investment
is reduced by the interest rate differential. The opposite is
true of short hedging when the currency is at a forward
premium; that is, the interest rate differential can increase
the hedged portfolio return.2 The impact on hedged portfolio returns of the cost of carry can be sizable, as will be
seen in the next section.
Another potential cost is a risk premium implicit in
the forward rate. In contrast with the forward discount,
this cost is not directly observable. For example, if the forward exchange rate is a downward biased estimate of the

future mark spot rate and an investor wishes to sell marks
forward for dollars, the average outcome of entering into
such contracts is that fewer dollars per mark would be
received through the forward contract than through spot
exchanges at the time the forward matures.3 The forward
would still give a certain rate of conversion in contrast
with the random rate of a future spot transaction, but on
average an investor would be paying an implicit premium
for a predetermined rate of exchange.
Theoretical modeling of the risk premium in forward
and futures markets as well as empirical tests of those
models have been long-standing research topics (see
Hodrick 1987 for a survey of the early literature and Dumas
1996 for more recent studies). Empirically useful characterizations of the risk premium still elude researchers.
Most studies find that forwards and futures do not give
unbiased estimates of subsequent spot rates; however,
linking the estimated bias with variables that measure risk
based on theoretical considerations has largely been
unsuccessful. The bias fluctuates through time. The literature is substantially in agreement that over long holding
periods, typically a few years, the bias and presumably the
risk premium are close to zero. This observation is the crux
of the argument that currency hedging is a free lunch:
hedging delivers a substantial reduction in risk, in the
form of a large reduction in the standard deviation of
returns, while not entailing the implicit payment of a risk
premium. Standard tests for risk premiums applied to the
sample used in this article confirm that the average risk
premium for each of the six major currencies considered
was not statistically significantly different from zero
(results available from the authors).

1. Options have similar costs of transacting as well as the payment of the option premium since, unlike forwards, long option positions
are net investments.
2. The costs accruing from rolling over hedges can cause serious problems for the hedger if not handled with care. A roll-over hedging
strategy used by Metallgesellschaft precipitated a liquidity crisis and eventual bankruptcy of this huge German oil refining and distribution firm. See Culp and Miller (1995).
3. The risk premium could also be collected rather than paid by the forward contract holder. It is not necessarily a cost of using
forwards.

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

paying interest of rDM. Such an investment would offer a
guaranteed nominal payoff of (1 + rDM)/s DM upon
maturity. However, this sum would then have to be translated back into dollars at an unknown future dollarmark exchange rate. The investment would be risky in
dollar terms as a result of exchange rate fluctuations.
That risk could be eliminated at the outset by a sale of
marks for dollars using a forward contract, which specifies a rate of future conversion. The exchange risk is
irrelevant with the forward contract because the mark
payoff of the investment is translated into dollars at the
known forward rate, giving f 3 (1 + rDM)/s dollars
toward paying back 1 + rUS dollars of the borrowing.
Borrowing at home in dollars and lending abroad in
marks must result in equal dollar outcomes on both
sides of the transaction; otherwise, investors would
seek to exploit or arbitrage the discrepancy because the
strategy involves no risk.11 If the dollar receipt of lending exceeds the dollar outlay of borrowing, the foregoing
strategy would be undertaken. If the dollar receipt of
lending falls short of the dollar outlay of borrowing, the
strategy would be reversed, with marks being borrowed
and converted into dollar investments. The consequence of this arbitrage pressure is that the following
equation must hold: 1 + rUS = f 3 (1 + rDM)/s or f/s =
(1 + rUS)/(1 + rDM). The forward exchange rate is determined by the spot exchange rate and the domestic and
foreign short-term interest rates for investments with
the same maturity as the forward contract.
Another way to view this example is from a financial intermediary’s perspective, typically a bank that
offers forward contracts to its customers. For example,
a bank could enter into a forward contract with a customer who wants to buy marks and sell dollars at the
forward rate. The bank could hedge its resulting exposure by borrowing dollars and lending marks to lock in
a payment of 1 + rUS dollars and a receipt of f(1 + rDM)/s
dollars. In other words, by covered interest parity, no
matter what happens to the exchange rate, the bank is
guaranteed a later receipt of f(1 + rDM)/s dollars upon
expiration of the forward contract and a payment of 1 +
rUS dollars. If the mark depreciates against the dollar,
the bank gains on its short forward position in marks
vis-à-vis its customer but offsets the gain upon translating the mark lending back into dollars. If the mark
appreciates, the bank loses on its forward position but
recoups the loss by gains on its lending. The bank’s

obligation to its customer would be fully covered by
these hedging transactions.
Portfolio Hedging. In contrast with the covered
interest parity example, the investments now under
consideration will have maturities or holding periods
that are longer than the instruments used to hedge
them. For practical reasons, such as reducing the costs
of hedging, hedges are adjusted only periodically; consequently, they will be imperfect, leaving an unhedged
exposure.
As applied in this article, hedging will involve
matching a currency hedge with a portfolio in such a way
that the full foreign currency exposure of the initial
value of the investment
position is covered. This
type of hedging is someBecause domestic systemtimes called unitary
hedging, which has
atic risks are likely to
proved to be effective
differ from country to
compared with more
country, international
sophisticated meth12
ods. A hedged long
diversification can further
position in foreign secureduce the volatility of
rities involves selling
portfolio returns by mitithe current foreign currency value of the
gating country-specific
investment forward for
risk.
dollars. The investor is
said to have a short
position in the forward
contract—that is, he is obligated to sell foreign currency at the forward rate upon maturity of the contract. As
a forward contract matures and is settled with the contract’s counterparty, another forward contract is sold to
maintain the hedge for the next, say, three-month period on a continuing underlying foreign asset exposure.
This process is called rolling the hedge.
The results of single-period hedging can be described using the following notation. The rate of gain (or
loss) on the forward contract is fpt–1 – et, where fpt–1 is
the forward premium, defined as ft–1/st–1 – 1 (which
by covered interest parity is the difference between the
domestic and foreign short-term bond yields of the same
maturity as the forward). Being short the forward contract implies that a gain accrues to the forward position
if the future spot exchange rate at the time the forward
matures is below the forward rate. Equivalently, the

11. For simplicity, this example neglects transaction costs and differences in borrowing and lending rates in a given currency.
12. More sophisticated methods that use information derived from joint comovements among forward contract returns and
security returns (such as using Japanese yen forwards to hedge mark portfolio exposures) have not yielded better results
than the simple full hedging prescription. See Adler and Simon (1986), Eun and Resnick (1988), Kaplanis and Schaefer
(1991), and Glen and Jorion (1993); see Anderson and Danthine (1981) and Duffie (1989) for general discussions of hedging predetermined portfolio positions.

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

forward position shows a gain if the forward premium
exceeds the rate of change in the exchange rate (fpt–1 >
et). Note that the forward premium can be negative,
which is called a forward discount (a foreign short-term
interest rate greater than the domestic). A gain (loss)
on the forward position would help to offset a loss
(gain) on the unhedged position in the event the foreign exchange rate depreciates (appreciates).
The strategy of short hedging the foreign exposure
of the initial investment does not perfectly hedge the
foreign securities position because the investment
result is unhedged. It turns out that the imperfect
hedge is not of great consequence, as demonstrated in
the empirical discussion, because the magnitude of the
hedging error is small. The initial value of the investment is sold forward for gross return of 1 + fpt–1 at time
t, and the investment result is converted at the prevailing spot exchange rate, giving a gross dollar return of
rlt(1 + et). As noted above, the cross product term rltet,
which is the hedging error, is small and is ignored in the
discussion to follow.
The net dollar return on the hedged portfolio can
be interpreted in two equivalent ways: either as the sum
of the gross return on the hedged initial foreign investment and the unhedged investment return minus one,
(1 + fpt–1) + rlt(1 + et) – 1 ' rlt + fpt–1, or as the sum of
the gross return on the unhedged foreign investment
and the return to a short forward position minus one, (1
+ rlt)(1 + et) + (fpt–1 – et) – 1 ' rlt + fpt–1.13 The hedged
dollar return is thus approximated by the local return
plus the forward premium. Based on unitary hedges of
exposures to each country’s index portfolio, the variance of the hedged diversified portfolio dollar return is

σ h ≈ ∑ i =1 ∑ j =1 wi wj ρi jσ iσ j
N

(3)

144
42444
3
local return covariances

∑
∑ wwρ σ σ
144424443
N

i =1

j =1

forward premium covariances

+ 2∑ i=1 ∑ j =1 wi wj ρilj, fpσ ilσ jfp ,
144424443
N

security return–forward premium covariances

where the forward premium standard deviations (with
superscript fp for forward premium) and correlation
coefficients replace those of the foreign exchange rates
that appear in equation (2).
The key argument for currency hedging is that the
variance reduction by diversifying internationally that
may be realized through the first term in equation (2)
for local returns may be offset by the contributions of
the second two terms for the exchange rate interactions. Foreign exchange rates tend to be more highly
correlated than international equity or bond returns.14
40

In contrast, the forward premium has a much lower
standard deviation and a lower correlation with local
returns than the spot exchange rate. Both of these characteristics may improve the risk-return trade-off for
internationally diversified portfolios.

Analysis of Unhedged and Hedged
Internationally Diversified Portfolios
his section evaluates the impact of currency hedging on diversified portfolios of bonds and diversified portfolios of stocks. After a brief overview of
the data used to construct internationally diversified
portfolios, the effects of currency hedging are assessed
by analyzing efficient frontiers for hedged diversified
portfolios and unhedged diversified portfolios.
Data. Equity and government bond investments in
seven countries are considered: Germany, the United
Kingdom, Japan, France, Canada, Switzerland, and the
United States. Portfolio performance is examined at
quarterly intervals, based on portfolio values, spot
exchange rates, and three-month forward rates as of the
last day of the quarter. The full period runs from first
quarter (Q1) 1980 to Q4 1996. The first subperiod, Q1
1980 to Q4 1985, was selected to match or substantially
overlap the sample periods in Thomas (1988, 1989),
Perold and Schulman (1988), Kaplanis and Schaefer
(1991), and Glen and Jorion (1993).
The equity returns under consideration are computed from stock indexes compiled by Morgan Stanley
Capital International (MSCI) and include the reinvestment of dividends paid during the holding period. The
indexes for each country represent portfolios of all listed firms, included in industry proportions that reflect
industry composition in the local market. The stocks in
the index are weighted by the market capitalization of
the included firms, which themselves are drawn from a
representative sample of large, medium, and small capitalization firms (MSCI 1995).
The government bond index is the government
bond subsector of the Salomon Brothers World Bond
Index, which is a value-weighted index of bonds with at
least one year to maturity. The bond portfolio data cover
Q1 1986 to Q4 1996. Coupon payments are reinvested.
Three-month forward and spot exchange rates are from
Data Resources, Inc.
Stock and bond returns are expressed as excess
returns by subtracting the three-month Treasury bill yield
from U.S. dollar returns and by deducting a foreign country’s three-month risk-free yield from its security
returns.15 This adjustment improves the comparability of
returns that are computed for multiyear periods and has
little effect on the measured standard deviation of return.
Equities. Charts 2–5 display the efficient frontiers
for internationally diversified equity portfolios for various subperiods. The top panel in each chart shows two

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

frontiers, one for the unhedged efficient portfolios and
the other for the hedged. The unhedged portfolio frontier is derived from the unhedged dollar excess returns
during a given period and the hedged portfolio frontier
from the hedged dollar excess returns. (All rates shown
in the charts and tables are in percent on an annual
basis.16) Optimal weights were computed to combine
these individual country index portfolios.
The left-hand starting point of a frontier represents
the minimum standard deviation portfolio’s excess
return and standard deviation. The curve moves to the
northeast as higher excess return necessitates the addition of greater risk, as approximated by the standard
deviation of excess return. The range of excess return
and standard deviation of a given frontier reflects all
possible efficient outcomes that could be derived from
the seven individual country index portfolios that
entered the portfolio optimization.17 The dot in this
graph is the excess return and standard deviation of the
U.S. index portfolio.
The optimal portfolio weights appear in the second
and third panels of the chart. The second panel gives
the weights for the unhedged efficient portfolios, and
the third gives them for the hedged efficient portfolios.
The country weights are vertical slices of this area plot,
which shows how the weights vary continuously from
the minimum standard deviation portfolio on the
extreme left-hand side to the maximum standard deviation portfolio on the extreme right-hand side.
Chart 2 dramatically illustrates what drove currency hedging advocates’ enthusiasm. The hedged portfolio
efficient frontier is mostly to the northwest of the
unhedged portfolio’s. (This unhedged portfolio efficient
frontier, computed using returns rather than excess
returns, appeared as Chart 1.) Hedging delivers much
higher excess return at substantially lower risk. Note
that simply holding the U.S. index was an inefficient
choice compared with either type of diversified portfolio. The hedged efficient portfolio frontier does not

include the U.S. portfolio. Not surprisingly, the optimization for the portfolio weights mainly selected the
high excess return markets of Japan, the United
Kingdom, and Germany. The optimization constrained
the weights on these portfolios to be nonnegative (that
is, selling an index portfolio short was not permitted).
However, no constraint was placed on the share of a particular country’s index in the portfolio. In practice, it
may not be cost-effective to attempt to take large securities positions in countries with relatively low capitalization equity markets.
(Such purchases could
raise the cost of shares
The impact of exchange
if an institutional portfolio manager attemptrate movements on
ed to acquire a large
unhedged dollar returns
position.)
can be understood by
Table 1 shows the
results by country and
considering the return in
subperiod. Panel A of
terms of two sources of
Table 1 for unhedged
risk, volatility of both forstock index portfolios
during 1980–85 indieign security returns and
cates that the standard
the foreign exchange rate.
deviations of the quarterly non-U.S. portfolio
unhedged dollar excess
returns are all substantially greater than that of the U.S.
portfolio. The reason for the volatility of the dollar
excess returns is apparent from the rows giving the standard deviations of the foreign exchange returns and the
correlation coefficients of the local excess return with
the rate of change in the foreign exchange rate. Given
the way the variables are measured in this article, the
standard deviation of the local excess return is identical
to the standard deviation of the hedged dollar excess
return.18 The correlation coefficients are between 0.3
and 0.6. The relatively high foreign exchange rate variances and positive local excess return–foreign exchange

13. This second interpretation can also be viewed in terms of an unhedged investment position and a position in domestic and
foreign bonds that substitutes for the forward contract. Namely, a short forward position is synthesized by being short foreign bonds (borrowing) and being long domestic bonds (lending), resulting in predetermined payment of foreign currency and receipt of domestic currency. Specifically, from the earlier discussion of covered interest parity, the dollar receipt
from lending would be 1 + rUS and the mark payment would be (1 + rDM)/s.
14. During the 1986–96 period, the average correlation coefficient between two countries, excluding Canada, is about 0.6 for
equity or bond returns on index portfolios, whereas the average correlation is 0.8 for foreign exchange returns. The average
foreign exchange correlation drops to 0.5 when Canada is included.
15. The foreign three-month risk-free rate is estimated by the negative of the difference between the forward premium and the
three-month Treasury bill yield.
16. All rates are reported as annualized quarterly logarithmic differences of the variables. Means are annualized and converted to percentages by multiplying by 400; standard deviations by 200 (==43100)
17. The optimization algorithm frequently failed to converge for efficient portfolios that approached the extremes of maximum
excess return and maximum standard deviation. These portfolios typically consist of a single index, as seen in the panels
for the optimal portfolio weights.
18. The identity occurs when the forward premium is assumed to equal the U.S.–foreign interest rate differential.

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

CHART 2
International Equity Portfolios, 1980–85
Efficient Frontiers
16

Excess Return

14
12
U.S.

Hedged

Unhedged

10
8
6
4
7

13
15
17
Standard Deviation

Optimal Por tfolio Weights, No Currency Hedging
1.0
U.S.

We i g h t

0.8

0.6

0.4

France
Japan

0.2
U.K.
Germany
0
14.4

15.0

18.0

21.5

Standard Deviation

Optimal Por tfolio Weights, Currency Hedging
1.0
France
0.8

We i g h t

Japan
0.6

0.4
U.K.
0.2
Germany
0
9.1

9.6

12.2

Standard Deviation

Note: Standard deviations on portfolio weight charts are not measured in equal intervals.

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

15.2

CHART 3
International Equity Portfolios, 1986–96
Efficient Frontiers
10
Unhedged

Excess Return

9
8
7
U.S.
6
Hedged
5
4
3
2
12.5

13.5

14.5

15.5

16.5

17.5

Standard Deviation

Optimal Por tfolio Weights, No Currency Hedging
1.0

U.S.
0.8

We i g h t

France
0.6

Switzerland
0.4

Canada

U.K.

Japan
0.2

Germany
0
12.7

12.8

13.4

17.2

Standard Deviation

Optimal Por tfolio Weights, Currency Hedging
1.0

0.8

We i g h t

U.S.
0.6

0.4

Canada
0.2
Japan

Germany

0
12.8

13.0

13.6

14.4

Standard Deviation

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

CHART 4
International Equity Portfolios, 1986–90
Efficient Frontiers
12
Unhedged

Excess Return

10
8
6
4
2
U.S.

Hedged

0
–2
–4
–6
16

24
Standard Deviation

Optimal Por tfolio Weights, No Currency Hedging
1.0

Switzerland

France

0.8

We i g h t

Canada
0.6

Japan
0.4

U.K.
0.2

Germany
0
16.9

17.5

19.5

23.7

Standard Deviation

Optimal Por tfolio Weights, Currency Hedging
1.0

0.8

We i g h t

U.S.
0.6

0.4
Japan

Canada
0.2
Germany
0
16.5

17.5

19.2

Standard Deviation

Note: Standard deviations on portfolio weight charts are not measured in equal intervals.

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

30.6

CHART 5
International Equity Portfolios, 1991–96
Efficient Frontiers
15
14
Excess Return

Unhedged
13
12
11
10
Hedged

U.S.
9
8
7
6
5.5

6.5

7.5

8.5

9.5

10.5

11.5

12.5

Standard Deviation

Optimal Por tfolio Weights, No Currency Hedging
1.0

0.8

We i g h t

U.S.
0.6

Canada
0.4

Switzerland

Japan
0.2

Germany
0
5.9

6.0

7.0

11.0

Standard Deviation

Optimal Por tfolio Weights, Currency Hedging
1.0

0.8

We i g h t

U.S.
0.6

Canada
0.4

Switzerland

Japan
0.2

Germany
0
6.5

6.7

7.6

12.5

Standard Deviation

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

TA B L E 1 S t o c k I n d e x P o r t f o l i o s

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

Panel A: 1980–85
Germany

U.K.

Japan

France

Canada

Switzerland

U.S.

Unhedged Stock Index Portfolio Dollar Excess Returns
Mean excess return
Standard deviation

7.30

4.46

9.95

–0.59

–3.46

3.90

5.42

23.55

20.26

22.12

29.13

24.83

25.06

15.14

—

Hedged Stock Index Portfolio Dollar Excess Returns
Mean excess return

15.82

11.54

10.69

5.18

–1.28

12.30

Standard deviation

15.74

12.85

13.86

21.20

22.20

16.02

—

Percent change in standard deviation of hedged
returns to standard deviation of unhedged returns

–33.2

–36.6

–37.4

–27.2

–10.6

–36.1

—

Perfect Foresight Hedge Dollar Excess Returns
Mean excess return

15.65

11.51

10.19

4.54

–1.73

11.75

—

Standard deviation

15.39

13.11

14.16

22.08

22.29

15.59

—

Forward Premium
Mean

4.56

0.06

4.59

–3.36

–0.59

6.54

—

Standard deviation

1.04

1.42

1.62

2.59

0.71

1.33

—

–0.28

–0.12

–0.15

0.12

–0.30

—

Correlation between local excess return
and forward premium

Foreign Exchange Returns
Mean return

–3.96

–7.02

3.85

–9.12

–2.78

–1.86

—

Standard deviation

13.14

12.14

13.18

13.61

4.42

13.68

—

0.30

0.24

0.26

0.34

0.55

0.37

—

Correlation between local excess return
and foreign exchange return

TA B L E 1 S t o c k I n d e x P o r t f o l i o s (cont.)
Panel B: 1986–96
Germany

U.K.

Japan

France

Canada

Switzerland

U.S.

Unhedged Stock Index Portfolio Dollar Excess Returns
Mean excess return
Standard deviation

4.21

9.29

3.67

8.64

3.33

8.19

7.96

19.34

18.00

28.35

20.70

14.68

16.32

14.41

Hedged Stock Index Portfolio Dollar Excess Returns
Mean excess return
Standard deviation
Percent change in standard deviation of hedged
returns to standard deviation of unhedged returns

0.04

4.49

0.77

2.85

1.17

5.22

—

22.66

17.97

25.70

22.23

13.06

20.99

—

17.2

–0.1

–9.3

7.4

–11.0

28.6

—

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

Perfect Foresight Hedge Dollar Excess Returns
Mean excess return
Standard deviation

1.30

4.92

0.81

3.58

0.96

6.90

—

21.38

17.19

25.17

21.41

12.81

20.01

—

Forward Premium
Mean

0.04

–3.26

2.07

–2.35

–1.98

0.95

—

Standard deviation

1.58

1.08

1.10

1.43

0.74

1.45

—

Correlation between local excess return
and forward premium

0.03

0.00

0.13

0.00

0.33

0.00

—

0.18

3.93

—

Foreign Exchange Returns
Mean return

4.21

1.54

4.97

3.45

Standard deviation

12.83

11.92

13.19

11.82

4.26

14.43

—

Correlation between local excess return
and foreign exchange return

–0.52

–0.33

–0.05

–0.38

0.29

–0.64

—

(Continued on page 48)

TA B L E 1 S t o c k I n d e x P o r t f o l i o s (cont.)

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

Panel C: 1986–90
Germany

U.K.

Japan

France

Canada

Switzerland

U.S.

Unhedged Stock Index Portfolio Dollar Excess Returns
Mean excess return
Standard deviation

2.67

10.86

11.37

11.34

2.22

1.26

3.96

25.75

22.54

35.57

27.83

18.40

20.45

19.70

—

Hedged Stock Index Portfolio Dollar Excess Returns
Mean excess return

–4.90

1.23

6.17

1.80

–3.90

–5.77

Standard deviation

29.88

23.83

31.95

30.04

16.55

27.05

—

16.0

5.8

–10.2

7.9

–10.0

32.2

—

Percent change in standard deviation of hedged
returns to standard deviation of unhedged returns

Perfect Foresight Hedge Dollar Excess Returns
Mean excess return

–3.46

1.70

5.64

2.46

–4.26

–3.72

—

Standard deviation

27.90

22.21

30.68

28.46

16.09

24.89

—

Forward Premium
Mean

2.24

–3.85

2.55

–1.60

–2.40

2.52

—

Standard deviation

0.72

0.85

0.73

0.92

0.65

0.96

—

Correlation between local excess return
and forward premium

0.14

–0.03

0.12

–0.06

0.32

0.27

—

Foreign Exchange Returns
9.81

5.77

7.75

7.93

3.72

9.55

—

Standard deviation

Mean return

11.82

11.79

14.33

10.71

3.66

13.43

—

Correlation between local excess return
and foreign exchange return

–0.52

–0.37

0.04

–0.39

0.48

–0.67

—

TA B L E 1 S t o c k I n d e x P o r t f o l i o s (cont.)
Panel D: 1991–96
Germany

U.K.

Japan

France

Canada

Switzerland

U.S.

Unhedged Stock Index Portfolio Dollar Excess Returns
Mean excess return

5.50

7.98

–2.75

6.40

4.26

13.97

11.30

Standard deviation

12.28

13.60

20.83

12.59

11.09

11.53

7.81

5.40

14.38

—

Hedged Stock Index Portfolio Dollar Excess Returns
Mean excess return
Standard deviation
Percent change in standard deviation of hedged
returns to standard deviation of unhedged returns

4.16

7.20

–3.73

3.72

14.59

11.42

19.50

13.34

9.08

13.08

—

18.8

–16.0

–6.4

5.9

–18.1

13.5

—

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

Perfect Foresight Hedge Dollar Excess Returns
Mean excess return
Standard deviation

5.27

7.61

–3.22

4.51

5.31

15.75

—

14.25

11.86

19.93

13.68

9.06

13.85

—

Forward Premium
–1.79

–2.77

1.68

–2.97

–1.64

–0.35

—

Standard deviation

Mean

1.52

1.20

1.32

1.71

0.78

1.48

—

Correlation between local excess return
and forward premium

0.17

–0.01

0.14

0.07

0.32

0.07

—

Foreign Exchange Returns
Mean return

–0.45

–1.98

2.66

–0.29

–2.78

–0.76

—

Standard deviation

13.42

11.99

12.35

12.59

4.23

15.09

—

Correlation between local excess return
and foreign exchange return

–0.60

–0.29

–0.22

–0.50

0.34

–0.68

—

rate change covariances contribute to the relatively high
standard deviations of many of the unhedged efficient
portfolios in Chart 2.19 Nevertheless, the effects of international diversification still result in some efficient
unhedged portfolios having lower standard deviations
than that of the U.S. domestic portfolio.
During the 1980–85 period, the average across all
countries for the standard deviation of hedged dollar
excess returns was 30.2 percent smaller than the average standard deviation of unhedged dollar excess
returns. The hedged dollar excess return standard deviations for Japan and the United Kingdom are lower than
the U.S. standard deviation, and none of the remaining
standard deviations is
as large as the corresponding unhedged
dollar excess return
The strategy of short hedgvalues. This finding is
consistent with those
ing the foreign exposure of
reported in Thomas
the initial investment does
(1988), Perold and
not perfectly hedge the
Schulman (1988), and
Kaplanis and Schaefer
foreign securities position
(1991), including data
because the investment
that extended back to
result is unhedged.
1978. Based on this
substantial variance
reduction, Perold and
Schulman offered this
advice: “Our prescription does not say the prescient investor should not
selectively lift a hedge, just that hedging should be the
policy, and lifting the hedge an active investment decision” (1988, 45).
The effectiveness of currency hedging using forwards is apparent from the results under the heading
Perfect Foresight Hedge Dollar Excess Returns. These
measures of the mean excess return and standard deviation reflect a currency hedge that was scaled to match
the ex post quarterly security return. That is, rather
than matching the hedge to the initial beginning-ofquarter portfolio value, the hedge was constructed to
match the end-of-quarter portfolio value. In this way,
the perfect foresight hedge covers the investment
return, which is not known with certainty in practice. In
this panel as well as in the others to follow, the unitary
hedge results are close to those of the perfect foresight
hedge, especially relative to the results derived from
unhedged positions.
Another point to notice is that, from equation (3),
the hedged portfolio standard deviation depends on the
variance of the forward premium as well as on the
covariance of the forward premium with the local
excess return. The forward premium standard deviations are an order of magnitude smaller than the foreign
50

exchange return standard deviations. The correlation
coefficients for the forward premium with the local
excess return are negative, a fact that also contributes
to reducing the hedged portfolio variance. In Chart 2,
most hedged efficient portfolios have a lower standard
deviation than the minimum standard deviation
unhedged portfolio.
The mean annual rates of dollar excess return for
the unhedged country portfolios are determined
approximately by the sum of the average local return for
the period and average rate of foreign exchange appreciation less the risk-free rate of interest. The dollar’s
appreciation depressed unhedged relative to hedged
dollar excess returns. As discussed above, the hedged
dollar return is approximately the local return plus the
forward premium, implying, by covered interest parity,
that the hedged dollar excess return is approximately
the local excess return—for example, rl + (rUS – rDM) –
rUS = rl – rDM. All mean unhedged dollar excess returns
are less than the corresponding mean hedged dollar
excess returns. (The same is true of Japan, whose currency appreciated against the dollar during this period,
because the Japanese risk-free rate was much less than
the U.S. risk-free rate.)
Chart 3 for 1986 to 1996 presents an entirely different picture of the currency hedging argument. The
unhedged efficient frontier dominates the hedged frontier. The case for currency hedging of internationally
diversified equity portfolios has not held up because of
the instability of the covariance structure, that is, the
variability through time of standard deviations and correlation coefficients of excess returns. Most striking in
Panel B of Table 1 is the standard deviations of hedged
dollar excess returns across countries. Only Canada
has a lower standard deviation of excess return compared with the United States, and consequently the
hedged portfolio frontier was generated mainly by positions in the Canadian and U.S. portfolios. (In the
1980–85 subperiod, only two countries, France and
Canada, have substantially higher volatility than the
United States.) At the same time, the United States has
the highest mean hedged dollar excess return during
1986–96, making it the endpoint of the hedged portfolio frontier.
Another related point to note in Panel B for the
1986–96 subperiod is that the correlation coefficients
of the unhedged dollar excess returns and foreign
exchange returns show a reversal of signs for all coefficients except Canada’s compared with the corresponding values in Panel A for 1980–85. The negative
correlation and relative increase in foreign market
volatility translate into unhedged dollar excess return
standard deviations and hedged dollar excess return
standard deviations that are much closer in size relative
to the values in Panel A. The combined effects of the

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

apparent changes in the covariance structure between
these two periods account for the reversed positions of
the unhedged and hedged efficient portfolio frontiers in
Charts 2 and 3.
During the 1986–96 subperiod, foreign currencies
generally appreciated against the dollar. Unhedged foreign portfolio investments did well ex post because
investment proceeds converted into more and more dollars over time. By limiting the dollar excess return to
the local excess return, hedging stripped out the positive foreign exchange return while largely exposing the
investor to higher local excess return volatility.
Charts 4 and 5 display the subperiod efficient frontiers for 1986–90 and 1991–96, respectively.
Qualitatively, the results are similar for the combined
period. The same is true of efficient portfolios for either
1986–96 or 1986–90 that exclude the quarter containing
the 1987 crash (these graphs are not reported). The
large portfolio weight on Canada, with its –3.9 percent
hedged dollar excess return, pushes the minimum variance hedged portfolio’s standard deviation close to –4
percent in Chart 4 for 1986–90. (Of course, if a negative
excess return were expected by investors ex ante, no
one would hold the portfolio.)
Corresponding to Charts 4 and 5, Panels C and D,
respectively, of Table 1 split the 1986–96 period into
subperiods as a check on the stability of the portfolio
excess returns, standard deviations, and correlations.
The 1986–90 subperiod includes the crash of 1987,
which was a global phenomenon. The greatest negative
equity returns occur in each country in the fourth quarter of 1987. As documented in Panel C, the United
States actually had the second least volatile equity
market during this subperiod. This subperiod was also
the time of the most rapid depreciation of the dollar
against the currencies of the six countries, as shown in
Panel C.
In Panel D for 1991–96, equity market volatility
subsided but foreign exchange market volatility
increased compared with the earlier subperiod. The
United States had the least volatile equity market. The
correlation of local excess returns and foreign exchange
returns is generally negative across these subperiods.
Although there is some variation in the correlation coefficients in these subperiods, the correlation structure is
distinctly different from what it was during the 1980–85
period with the exception of Canada, which has a relatively large positive correlation in each period.
Bonds. The bond portfolio results differ markedly
from the equity portfolio results. Although the Salomon
Brothers bond indexes are only available as of 1985, the
results here are consistent with those from other stud-

ies that relied on different indexes from earlier periods.
The full period ran from 1986 to 1996 to match the same
period used for equities.
The standard deviations of the hedged dollar
excess returns in Panel A of Table 2 for the 1986–96
period are much smaller than those for the equity
index dollar excess returns, whether hedged or
unhedged, or those for foreign exchange returns. The
correlation coefficients for foreign exchange returns
and local excess returns are positive for five of six
countries and all except Japan’s are small in magnitude. A comparison of the hedged dollar excess returns
with the perfect foresight hedge dollar excess returns
reveals that quarterly
hedging closely matches the perfect foresight
case, especially for the
standard deviation of
Putting the practice of curexcess return.
rency hedging on a firmer
The standard deviations of unhedged dolfoundation requires better
lar excess returns are
models and techniques for
always substantially
predicting the correlation
larger than those for
hedged dollar excess
structure.
returns. Exposure to
foreign exchange rate
fluctuations contributes disproportionately
to the risk of holding
foreign bonds. The average reduction across countries
in the standard deviation of hedged dollar excess
returns relative to the unhedged excess returns standard deviation is 55.6 percent. This decline is about the
same as or somewhat greater than the magnitudes for
similar measures reported in Perold and Schulman
(1988), Thomas (1989), and Kaplanis and Schaefer
(1991) for the years from 1975 to 1988 or subperiods
within that span of years. Panels B and C show that the
lower variability of hedged excess returns also occurs
for the 1986–90 and 1991–96 subperiods.
The efficient bond frontiers generated by the
excess returns for hedged and unhedged bond positions are shown in Charts 6–8. The full-period results
appear in Chart 6. The hedged portfolio frontier lies to
the southwest of the unhedged portfolio frontier and
intersects the unhedged portfolio frontier just above
the point for the U.S. bond portfolio, which is the minimum variance portfolio for the unhedged portfolio
frontier. Unitary hedging of foreign exchange exposures has a pronounced impact on the standard deviation of dollar excess return. The configuration of these

19. The contribution of these elements of the unhedged efficient portfolio variance is apparent from equation (2).

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

TA B L E 2 B o n d I n d e x P o r t f o l i o s

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

Panel A: 1986–96
Germany

U.K.

Japan

France

Canada

Switzerland

U.S.

Unhedged Bond Index Portfolio Dollar Excess Returns
Mean excess return
Standard deviation

5.78

6.46

5.95

7.85

4.92

3.65

2.78

13.38

15.16

16.27

12.31

8.35

14.57

5.34

Hedged Bond Index Portfolio Dollar Excess Returns
Mean excess return

1.61

1.66

3.05

2.05

2.76

0.68

—

Standard deviation

3.72

7.84

5.97

5.37

6.46

4.27

—

–72.2

–48.3

–63.3

–56.4

–22.6

–70.7

—

Percent change in standard deviation of hedged
returns to standard deviation of unhedged returns

Perfect Foresight Hedge Dollar Excess Returns
Mean excess return

1.51

1.37

2.73

1.96

2.63

0.69

—

Standard deviation

3.69

7.70

5.78

5.25

6.46

4.33

—

2.07

–2.35

–1.98

0.95

—

Forward Premium
Mean

0.04

–3.26

Standard deviation

1.58

1.08

1.10

1.43

0.74

1.45

—

Correlation between local excess return
and forward premium

0.01

–0.03

–0.08

–0.10

0.09

0.02

—

0.18

3.93

—

Foreign Exchange Returns
Mean return
Standard deviation
Correlation between local excess return
and foreign exchange return

4.21

1.54

4.97

3.45

12.83

11.92

13.19

11.82

4.26

14.43

—

0.02

0.14

0.29

–0.12

0.17

–0.14

—

TA B L E 2 B o n d I n d e x P o r t f o l i o s (cont.)
Panel B: 1986–90
Germany

U.K.

Japan

France

Canada

Switzerland

U.S.

Unhedged Bond Index Portfolio Dollar Excess Returns
Mean excess return
Standard deviation

7.24

8.48

5.23

10.09

5.86

4.92

2.03

13.70

17.76

19.19

13.01

8.19

15.03

5.72

Hedged Bond Index Portfolio Dollar Excess Returns
Mean excess return

–0.33

–1.15

0.03

0.56

–0.26

–2.11

—

Standard deviation

3.79

9.11

7.29

6.20

6.47

3.57

—

–72.3

–48.7

–62.0

–52.4

–20.9

–76.2

—

Percent change in standard deviation of hedged
returns to standard deviation of unhedged returns
Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

Perfect Foresight Hedge Dollar Excess Returns
Mean excess return

–0.58

–1.85

–0.55

0.24

–0.46

–2.32

—

Standard deviation

3.69

8.75

7.02

5.91

6.40

3.49

—

Forward Premium
Mean

2.24

–3.85

2.55

–1.60

–2.40

2.52

—

Standard deviation

0.72

0.85

0.73

0.92

0.65

0.96

—

Correlation between local excess return
and forward premium

0.33

–0.03

–0.16

–0.34

0.04

0.33

—

3.72

9.55

—

Foreign Exchange Returns
Mean return
Standard deviation
Correlation between local excess return
and foreign exchange return

9.81

5.77

7.75

7.93

11.82

11.79

14.33

10.71

3.66

13.43

—

0.33

0.40

0.48

0.06

0.26

—

(Continued on page 54)

TA B L E 2 B o n d I n d e x P o r t f o l i o s (cont.)

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

Panel C: 1991–96
Germany

U.K.

Japan

France

Canada

Switzerland

U.S.

Unhedged Bond Index Portfolio Dollar Excess Returns
Mean excess return
Standard deviation

4.56

4.77

6.55

5.98

4.14

2.59

3.40

13.37

12.94

13.80

11.90

8.65

14.48

5.11

Hedged Bond Index Portfolio Dollar Excess Returns
Mean excess return

3.22

3.99

5.57

3.30

5.28

3.00

—

Standard deviation

3.53

6.58

4.37

4.61

6.32

4.52

—

–73.6

–49.1

–68.3

–61.3

–27.0

–68.8

—

Percent change in standard deviation of hedged
returns to standard deviation of unhedged returns

Perfect Foresight Hedge Dollar Excess Returns
Mean excess return

3.24

4.05

5.46

3.40

5.21

3.19

—

Standard deviation

3.53

6.59

4.19

4.63

6.35

4.62

—

1.68

–2.97

–1.64

–0.35

—

Forward Premium
Mean

–1.79

–2.77

Standard deviation

1.52

1.20

1.32

1.71

0.78

1.48

—

Correlation between local excess return
and forward premium

0.19

–0.11

0.06

0.07

0.03

0.15

—

–2.78

–0.76

—

Foreign Exchange Returns
Mean return

–0.45

–1.98

2.66

–0.29

Standard deviation

13.42

11.99

12.35

12.59

4.23

15.09

—

Correlation between local excess return
and foreign exchange return

–0.13

–0.07

0.07

–0.26

0.30

–0.30

—

CHART 6
International Bond Portfolios, 1986–96
Efficient Frontiers
8

Excess Return

7
6
Unhedged
5
4
3
2
Hedged

U.S.

1
0
3

7
9
Standard Deviation

Optimal Por tfolio Weights, No Currency Hedging
1.0

We i g h t

0.8

0.6

U.S.

France

Canada

0.4

0.2

0
5.3

6.1

8.1

12.1

Standard Deviation

Optimal Por tfolio Weights, Currency Hedging
1.0

0.8

U.S.
Switzerland

France

We i g h t

0.6

0.4
Japan

Germany
0.2

0
3.7

3.8

4.5

5.5

Standard Deviation

Note: Standard deviations on portfolio weight charts are not measured in equal intervals.

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

CHART 7
International Bond Portfolios, 1986–90
Efficient Frontiers
10
Hedged

U.S.

Unhedged

Excess Return

8
6
4
2
0
–2
3

Standard Deviation

Optimal Por tfolio Weights, No Currency Hedging
1.0
U.S.

We i g h t

0.8

0.6
Canada
0.4
Switzerland
0.2
France
0
5.7

6.2

8.5

12.7

Standard Deviation

Optimal Por tfolio Weights, Currency Hedging
1.0
U.S.
0.8

We i g h t

Switzerland
0.6
France
0.4
Germany
0.2

0
3.5

4.6

3.7
Standard Deviation

Note: Standard deviations on portfolio weight charts are not measured in equal intervals.

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

5.6

CHART 8
International Bond Portfolios, 1991–96
Efficient Frontiers

Excess Return

6
Unhedged

Hedged

U.S.
4

3
2

Standard Deviation

Optimal Por tfolio Weights, No Currency Hedging
1.0

0.8

We i g h t

U.S.

Canada

France

0.6

0.4

Japan
0.2

0
5.1

6.1

13.0

8.0
Standard Deviation

Optimal Por tfolio Weights, Currency Hedging
1.0

U.S.

Switzerland

Canada

We i g h t

0.8

0.6

0.4
Japan

Germany
0.2

0
3.4

3.5

3.9

4.4

Standard Deviation

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

frontiers implies that the decision to hedge depends
on an investor’s preference for risk and return; high
returns are attainable only through unhedged positions and conversely low-risk returns only through
hedged positions.
The comparatively more volatile 1986–90 subperiod predominates in the full sample as the efficient frontiers and the optimal weights that compose them are
similar. As is evident from Chart 7 and Table 2, Panel B,
Switzerland’s heavy weight in the minimum variance
hedged portfolio is mainly responsible for the negative
excess return. In contrast, for the 1991–96 period in
Chart 8, the hedged efficient frontier dominates the
unhedged, except for the high levels of excess return
above about 5.6 percent. In all three cases, the U.S.
bond portfolio is, or is very nearly, the minimum variance unhedged efficient portfolio, which reflects the
high volatility of unhedged foreign bond portfolios.20

Conclusion
his analysis of efficient portfolios of stocks and
bonds only partially confirms the claims of the
proponents of currency hedging. Simple unitary
hedging consistently yields a low standard deviation of
excess return on efficient, internationally diversified
bond portfolios. This finding agrees with those of other
studies of internationally diversified bond portfolios.
Whether this result is optimal depends on investor preferences. For hedged and unhedged portfolios from 1986

to 1996, the efficient frontiers corresponding to hedged
and unhedged positions partition the excess return and
standard deviation outcomes, with low excess return,
low standard deviation results for hedged portfolios and
high excess return, high standard deviation results for
unhedged portfolios.
Internationally diversified equity portfolios do not
show the same gains or consistency of results. The risk
reduction achieved through currency hedging found in
several earlier studies is confirmed for the 1980–85
subperiod. The efficient frontier for hedged portfolios
lies far to the northwest of the frontier for unhedged
portfolios. However, this hedged portfolio performance
is reversed in the 1986–96 period. Another way to state
this finding is that the covariance structure of international equity excess returns was unstable—it was subject to a large shift that drastically altered hedging
outcomes.
Earlier articles on currency hedging, and especially the unitary hedging prescription, were predicated on
an implied confidence in the stability of the covariance
structure of security and foreign exchange returns.
Putting the practice of currency hedging on a firmer
foundation requires better models and techniques for
predicting the correlation structure (see especially
King, Sentana, and Wadhwani 1994 and Solnik,
Boucrelle, and Le Fur 1996). Developing these tools is
clearly a challenge that calls for continuing research.

20. The low standard deviations of hedged efficient bond portfolios relative to the standard deviation of the U.S. bond portfolio
was confirmed by an alternative procedure. As discussed in note 9, the optimal portfolio weights and the efficient frontier
itself depend on the ex post security return. Instead of computing weights by optimization, weights were randomly drawn
from a uniform distribution and their sum normalized to one. Hedged diversified portfolios were then formed using these
weights. Of 10,000 such randomly weighted hedged portfolios, fewer than 2 percent had standard deviation greater than
that of the U.S. portfolio in the 1986–96 period. A similar procedure confirmed the results for stock portfolios shown in Charts
2 and 3. Fewer than 1 percent of randomly weighted hedged stock portfolios had standard deviation greater than that of the
U.S. portfolio in 1980–85. In contrast, more than 99 percent of randomly weighted hedged stock portfolios in 1986–96 had
standard deviation greater than the U.S. portfolio’s. The remaining fraction had large weights on the U.S. and Canadian
stock portfolios and very small weights on the other countries’ portfolios, consistent with the third panel of Chart 3.

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

REFERENCES
ADLER, MICHAEL, AND DAVID SIMON. 1986. “Exchange Risk
Surprises in International Portfolios.” Journal of Portfolio
Management 12 (Winter): 44–53.

KAPLANIS, EVI, AND STEPHEN M. SCHAEFER. 1991. “Exchange Risk
and International Diversification in Bond and Equity
Portfolios.” Journal of Economics and Business 43:287–308.

ANDERSON, RONALD, AND J.P. DANTHINE. 1981. Journal of
Political Economy 89 (December): 1182–96.

KING, MERVYN, ENRIQUE SENTANA, AND SUSHIL WADHWANI. 1994.
“Volatility and Links between National Stock Markets.”
Econometrica 62 (July): 901–33.

CHOW, EDWARD H., WAYNE Y. LEE, AND MICHAEL E. SOLT. 1997.
“The Exchange-Rate Risk Exposure of Asset Returns.”
Journal of Business 70:105–23.

LEVICH, RICHARD M., AND LEE R. THOMAS III. 1993. “Internationally Diversified Bond Portfolios: The Merits of Active
Currency Management.” NBER Working Paper No. 4340,
April.

CULP, CHRISTOPHER L., AND MERTON H. MILLER. 1995. “Metallgesellschaft and the Economics of Synthetic Storage.”
Journal of Applied Corporate Finance 7 (Winter): 62-76.

MARKOWITZ, HARRY. 1952. “Portfolio Selection.” Journal of
Finance 7 (March): 77–91.

DUFFIE, DARRELL. 1989. Future Markets. Englewood Cliffs,
N.J.: Prentice Hall.
DUMAS, BERNARD. 1996. “Partial Equilibrium versus General
Equilibrium Models of the International Capital Market.” In
The Handbook of International Macroeconomics, edited by
Frederick Van der Ploeg. Cambridge, Mass.: Blackwell.
EAKER, MARK R., AND DWIGHT M. GRANT. 1991. “Currency Risk
Management in International Fixed-Income Portfolios.”
Journal of Fixed Income (December): 31-37.
EUN, CHEOL S., AND BRUCE G. RESNICK. 1988. “Exchange Rate
Uncertainty, Forward Contracts, and International Portfolio
Selection.” Journal of Finance 43 (March): 197–215.
———. 1994. “International Diversification of Investment
Portfolios: U.S. and Japanese Perspectives.” Management
Science 40 (January): 140–61.
GLEN, JACK, AND PHILIPPE JORION. 1993. “Currency Hedging
for International Portfolios.” Journal of Finance 48
(December): 1865–86.
HODRICK, ROBERT J. 1987. The Empirical Evidence on the
Efficiency of Forward and Futures Foreign Exchange
Markets. Chur, Switz.: Harwood Academic Publishers.

MORGAN STANLEY CAPITAL INTERNATIONAL. 1995. Index Data
Dictionary. New York: DRI/McGraw-Hill.
PEROLD, ANDRÉ F., AND EVAN C. SCHULMAN. 1988. “The Free
Lunch in Currency Hedging: Implications for Investment
Policy and Performance Standards.” Financial Analysts
Journal (May/June): 45–50.
REINER, ERIC. 1992. “Quanto Mechanics.” Risk 5 (March):
59–62.
RUBINSTEIN, MARK. 1991. “Two into One.” Risk 49 (May): 49.
SOLNIK, BRUNO, CYRIL BOUCRELLE, AND YANN LE FUR. 1996.
“International Market Correlation and Volatility.” Financial
Analysts Journal 52 (September/October): 17–34.
THOMAS, LEE R. 1988. “Technical Notes: Currency Risks in
International Equity Portfolios.” Financial Analysts Journal
(March/April): 68–71.
———. 1989. “The Performance of Currency-Hedged
Foreign Bonds.” Financial Analysts Journal (May/June):
25–31.

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

Common Trends and
Cycles and the Structure
of Florida’s Economy
E D G A R PA R K E R
The author is an analyst in the regional section of the
Atlanta Fed’s research department. He thanks David
Avery, Zsolt Becsi, Tom Cunningham, Robert Eisenbeis,
Frank King, Whitney Mancuso, William Roberds, Gus
Uceda, and Tao Zha for helpful conversations and
comments on earlier drafts.

LORIDA, LIKE THE REST OF THE NATION, HAS UNDERGONE MANY ECONOMIC CHANGES IN THE
LAST QUARTER-CENTURY.

SOME

OBVIOUS EXAMPLES OF THIS ONGOING EVOLUTION ARE THE

DECLINE OF THE MANUFACTURING BASE AND THE GROWTH OF INTERNATIONAL TRADE. IN THE
CASE OF

FLORIDA SPECIFICALLY, THE GROWTH OF THE IMPORTANCE OF TOURISM HAS ALSO FIG-

URED SIGNIFICANTLY. IN ADDITION TO CHANGES AT THE STATE LEVEL, FLORIDA’S CITIES HAVE BECOME LESS
SIMILAR OVER TIME.

AS MIGHT BE EXPECTED, THESE GRADUAL ECONOMIC CHANGES COULD AT SOME POINT

CAUSE THE STATE’S METRO ECONOMIES TO INTERACT IN NEW WAYS.

FOR EXAMPLE, LABOR MARKETS THAT

MAY HAVE BEEN VERY SIMILAR IN STRUCTURE AND BEHAVIOR IN ONE PERIOD MAY HAVE BECOME MORE HETEROGENEOUS IN A LATER PERIOD.

Such changes in the structure of a regional economy have implications for economic forecasters, policymakers, businesses, and the general public. The
ultimate effects of economic shocks on a region depend
on the ways different parts of that region are linked to
each other and to external areas, as well as the region’s
relative degree of homogeneity. A particular economic
policy or shock may have a completely different effect
on a highly homogeneous region than it would on a more
heterogenous one.
This article uses multiple cointegration and common cycles analysis to study the evolution of the relationships among some major Florida cities’ labor
60

markets. (See the glossary on page 66 for short discussions of the technical terms.) Cointegration analysis is
used to examine the degree and type of long-run relationships that exist in these labor markets. This analysis
is extended with the introduction of the common cycle
methodology (of Vahid and Engle 1993) to illustrate the
short-run dynamics of the labor markets studied.

Cointegration
ointegration analysis deals with long-run equilibrium relationships among economic variables.
When a group of variables move together in a
common way over time they may be cointegrated––that

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

is, influenced by a common (random) trend. This
comovement can be caused by economic links that tie
the variables together in a long-term bond. Economic
theory is used to suggest variables to test for cointegration. Examples may include strongly linked variables
such as consumption and income or the levels of total
payroll employment among metropolitan statistical
areas in a homogeneous, well-integrated state economy.
Once economic theory suggests a list of variables that
may be cointegrated, statistical tests such as the EngleGranger (1987) test and the Johansen (1995) test can
be used to determine formally if a group of variables is
cointegrated. This article suggests that the labor markets within six Florida metropolitan statistical areas
(MSAs) may share a cointegrating relationship.
Cointegration analysis can also reveal the response
of particular labor markets to shocks in other labor
markets. For example, changes in labor demand and
supply in one MSA can be transmitted to another. Such
information, by helping determine which MSAs are
more independent of one another (weakly exogenous)
and which react strongly to disturbances in surrounding
markets (endogenous), can be valuable for clarifying
how the effects of state level policy changes as well as
economic shocks are transmitted among individual
MSAs.
The Florida MSAs studied are the six largest: Fort
Lauderdale, Jacksonville, Miami, Orlando, Tampa, and
West Palm Beach. The study of their labor markets
began with collecting the seasonally adjusted monthly
levels of total nonagricultural payroll employment from
January 1970 to June 1996. The data were tested over
the entire time period for a cointegrating (or long-run
equilibrium) relationship among the MSAs. The hypothesis of a cointegrating relationship over this time period
is not rejected.
Even when they are governed by the same basic
factors, however, economic relationships change over
time. For this reason, the stability of the relationships
over the entire sample period was examined using a
rolling regression. The results are presented in the first
panel of Chart 1. The number 1 on the vertical axis represents the 5 percent level of significance. At points
above this line the hypothesis that the equilibrium relationship of the entire time period studied is the same as
the subperiods (or the cointegrating vectors of the full
sample are the same as those of the subsample) is
rejected.
The first panel of Chart 1 shows that the full sample can be divided into three subperiods. The first, 1970
to 1980:06, is a period of rejection of the hypothesis that
the full-sample cointegrating vectors are those of the
subsample. Next appears a subsample that suggests
increasing acceptance of the stability of the coefficients
of the cointegrating vectors over the period from

1980:07 to 1987:12. Finally, there is a period of high
acceptance of the null hypothesis, from 1988:1 to
1996:06. The stability tests suggest that the relationships among the labor markets of the MSAs change over
time.
Next, tests are applied to these subperiods. First,
the sample of the period from 1970:01 to 1980:06 is studied to determine which MSAs are included in the longrun equilibrium and which are weakly exogenous. Then
an observation is dropped and the cointegrating relationship is examined again. This process was continued
for a three-year period.
It was found that a stable period in the cointegrating relationships
Florida’s cities have
from 1970:01 to 1978:08
become less similar
(with all cities includover time. As might be
ed in the cointegrating
relationship test and
expected, these gradual
with Miami, Tampa,
economic changes could
and West Palm Beach
at some point cause the
found to be weakly
exogenous) was interstate’s metro economies
rupted by a period of
to interact in new ways.
transition beginning
around 1978:09.
The data show that
the point of division
indicated by the stability test is a time period of relatively dramatic change that begins one to two years
before the actual dividing date of 1980:06. An appropriate end date to use in sampling the first period should
therefore be shortly before this transition period.
August 1978 was chosen because it is the month just
before changes in weak exogeneity among the MSAs
occur. The same rolling regression technique used in
the original sample was used to test this subperiod. The
second panel of Chart 1 shows that the hypothesis that
the cointegrating relationship for the period from
January 1970 to August 1978 is the same over subperiods of this sample is accepted over most of the time
period. The results of tests of long-run exclusion and
weak exogeneity for this subperiod are shown in Table 1;
all MSAs are included in the long-run equilibrium relation, as the hypothesis of exclusion is rejected. The
table also shows that Miami, Tampa, and West Palm
Beach are weakly exogenous.
Next, moving past the unstable 1980:06–1987:12
transition period indicated in the first panel of Chart 1,
the months spanning the last time period are examined.
As indicated in the chart, this is the region of high acceptance of the original cointegrating relationship. The
dividing date appears to be early 1988, and thus the sample period is from January 1988 to June 1996. As before,
tests of the robustness of the cointegrating relationships

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

CHART 1
Tests of the Long-Run Relationships
Among Labor Markets in Six Florida MSAsa
January 1970–June 1996

Significance Level

1973b

1978

1983

1988

1993

January 1970–August 1978

Significance Level

Jan-73

Sep-74

May-76

Jan-78

January 1988–June 1996

Significance Level

Jan-91c

Sep-92

May-94

Jan-96

Note: On the y axis, “1” indicates a 5 percent significance level. Data are seasonally adjusted (by the Federal Reserve Bank
of Atlanta) monthly levels of total nonagricultural payroll employment.
a
b
c

Miami, Orlando, West Palm Beach, Fort Lauderdale, Tampa, and Jacksonville
First observation is the result of the initial sample period, January 1970–January 1973.
First observation is the result of the initial sample period, January 1988–January 1991.

Source: Bureau of Labor Statistics
62

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

TA B L E 1
Chi-Squar e Tests, Labor Market Data for Six Florida MSAs,
January 1970–August 1978

Critical Value

Miami

Orlando

West
Palm Beach

Fort
Lauderdale

Tampa

Jacksonville

12.21

19.53

20.95

9.30

1.48

8.09

Long-Run Exclusion
5.99

9.16

14.39

17.74
Weak Exogeneity

5.99

0.70

17.54

1.32

TA B L E 2
Chi-Squar e Test, Labor Market Data for Six Florida MSAs,
January 1988–June 1996

Critical Value

Miami

Orlando

West
Palm Beach

Fort
Lauderdale

Tampa

Jacksonville

10.45

22.78

14.10

Long-Run Exclusion
9.49

8.48

8.59

17.72

are performed by sampling around the transition point.
The results of this period are much less robust than in
the first era, perhaps because of increased linkages of all
Florida MSAs to regions outside the state and less homogeneity (more specialization) among the MSAs. Miami is
always excluded from the cointegrating relationship.
Orlando is excluded in most of the time periods around
the transition. These findings support the thesis that
Florida’s economy has become less integrated, apparently beginning around 1988.
There is strong evidence that Miami and Orlando
are excluded from the long-run equilibrium relationship, as shown in Table 2. There is also strong evidence
that these two MSAs and Fort Lauderdale are weakly
exogenous. This condition indicates that these three
MSAs not only do not move with the others over the
1988:01–1996:06 period but they are also insulated from
short-run shocks in the rest of the state. Just as before,
the stability of the cointegrating relationship is tested
over this period using the rolling regression and chisquare tests. The third panel of Chart 1 shows that the
observed long-run relationship is stable over most of the
last sample period.
The above analysis suggests that for some reason
the relationship between the MSAs changed over the

sample period. Initially the levels of total payroll
employment in the cities grew together in a cointegrated relationship. The nature of this relationship then
changed, and the MSAs became less bound by the longrun equilibrium relationship. What could have caused
this apparent change in behavior?
The concepts of temporary cointegration and sudden change as introduced by Siklos and Granger (1996)
and Krugman (1991, 26), respectively, may help shed
light on the observed relationships. Siklos and Granger
use the concept of temporary cointegration to describe
data for which the underlying series need not be cointegrated at all times. The relationship shown over one time
span may be different from that of another period. This
change in the long-run equilibrium relationship might
be expected if there are changes in the makeup of particular MSAs over time, leading to possible differences in
the demand for and supply of labor in each MSA.
The concept of sudden change offers another possible explanation for why the relationships between the
MSAs became less cointegrated. Krugman (1991, 26)
describes sudden change as the result of a gradual and
unnoticed change in the underlying conditions that
leads to an explosive apparent change. A likely explanation is that the gradual transitions of Florida MSAs,

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

Miami and Orlando in particular, as they became
increasingly linked to economic regions outside Florida
and internally more heterogeneous, fragmented the
state’s economic integration. The growth of tourism in
Orlando and foreign trade in Miami have driven the significant changes in these labor markets.
In testing for the gradual changes in the MSAs that
may have created the new relationships, location quotients are useful. Location quotients indicate the relative concentration of a particular industry in a region.
In this study location quotients are constructed using
total payroll earnings. They are computed by dividing
the percentage of total payroll earnings generated by a
particular industry in an MSA by the percentage of the
industry’s total payroll earnings at the state level. A
location quotient equal to 1 indicates that total payroll
earnings in this industry are as concentrated in the
studied MSA as they are in the state as a whole. If
greater than 1 the location quotient shows greater concentration in the MSA than at the state level, and if less
than 1, less relative concentration. The location quotients are consistent with the hypothesis that increased
specialization in tourism in Orlando and trade in Miami
have led to the breakup of the cointegrating relationship that held the MSAs together. The location quotients identify some gradual changes in the underlying
economic structure that may have resulted in sudden
change. Growth in import and export activity through
the port of Miami are taken to reflect growth in international trade links. For the Orlando area (Orange
County) the hotel and service sector is a proxy for
tourism-related activities.

The water transportation location quotient for the
Miami area (Dade County) from 1969 to 1994 depicted
in Chart 2, shows the rise from an above-average concentration of water transportation in 1969 to the
extremely high level of about three times that of the
state at the end of the period. The increasing concentration of water transportation in Miami’s economy
clearly shows Miami’s emerging trade links with the rest
of the world gradually growing and helping pull Miami
out of its cointegrating relationship with the rest of the
state. Miami is now the seventh-busiest container port
in the United States as well as the number-one cruise
port in the world.
The location quotients of Orlando’s service sector,
measured by sector payroll earnings, tell a similar story
about tourism-related growth in that area in Chart 3. In
1969 Orlando was similar to the state in concentration of
its service sector. This situation changes over the sample
period as this concentration gradually grows to nearly
twice the level in the state. Nationally, Orlando is second
only to Las Vegas when ranked by the relative percentage of service-sector employment in its economy.
Location quotients of hotel total payroll earnings
were calculated to further examine the emergence of
tourism-related activities in the Orlando area. Although
these data are incomplete (the data for hotel payroll
earnings exist only from 1985 to 1987 and 1993 to 1994),
in Chart 4 it can be seen that the Orlando area already
had a high concentration of hotel payroll earnings in
1985 relative to the rest of the state. This concentration
continued to grow to more than five times the state’s
level by 1994. It seems reasonable to assume that the

CHART 2
Dade County Water Transpor tation Location Quotient, 1969–94
3.5

Location Quotient

3.0

2.5

2.0

1.5

1.0
1970

1975

1980

1985

Source: Bureau of Economic Analysis, provided by Regional Financial Associates
64

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

1990

concentration of hotel earnings in Orlando was much
lower in 1970.
These dramatic rises in service and hotel-related
total payroll earnings indicate the growing importance
of tourism in the Orlando area, linking its economy to
areas outside of Florida as well as differentiating it from
the rest of the state. This emerging link helped remove
Orlando from the cointegrating relationship of the early
time period.

The changing level of stability in cointegrating
relationships reveals periods of economic structural
change in the labor forces of the Florida MSAs studied.
What began as a high degree of cointegration began to
lessen by the last period as Orlando and Miami became
excluded. As Siklos and Granger state, “It seems realistic to assume that some series are cointegrated only
during some periods and not at others. The reason is
that events or important changes in some of the

CHART 3
Orange County Service-Sector Location Quotient, 1969–94

Location Quotient

2.2

1.8

1.4

1.0
1970

1975

1980

1985

1990

CHART 4
Orange County Hotel Payroll Earnings Location Quotient, 1985–94

Location Quotient

0
1985

1986

1987

1993

1994

Note: Data are unavailable for 1988–92.
Source for Charts 3 and 4: Bureau of Economic Analysis, provided by Regional Financial Associates

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

Glossary
Cointegration between economic variables may exist if
these variables tend to move together in a common way
over time. Economic theory may suggest which variables to
test for cointegration––for example, strongly linked variables such as consumption and income or the levels of
total payroll employment among MSAs in a homogenous,
well-integrated state economy.
Common cycles refers to the short-run dynamics of the
time series. In this article the decomposition of the levels
of total nonagricultural payroll employment reveals the
effects of short-run shocks to the group of MSAs.
Common trends refers to the long-run behavior of the levels of total nonagricultural employment in the MSAs. This
long-run behavior is revealed by the Vahid-Engle decomposition, which removes the short-run effects of shocks and
leaves the long-run trends associated with the time series.

concentrated in the MSA as in the state as a whole. The
relative concentration of the industry in the MSA is greater
than that of the state if the location quotient is greater
than 1 and the reverse if less than 1.
Rolling regressions, in this article, make use of a statistical test (chi-square) to determine whether the cointegrating relationship of the full sample is the same as that of
subsamples of the full time period. Starting with a subsample that begins at the start of the original sample, the
Chisquare test is performed over and over again adding
one more month of data after each test until all the data
are included and tested.
Sudden change is introduced by Krugman as the result of
“a gradual change in the underlying (economic) conditions (that) can at times lead to explosive . . . change”
(1991, 26).

Endogenous metropolitan statistical areas, in the context of this article, are the cities whose labor markets are
dependent on and react to demand and supply shocks from
other metropolitan areas.

Temporary cointegration is described by Siklos and
Granger (1996) as a change in the long-run relationships
between variables that could lead to the underlying series
not being cointegrated at all times.

Location quotients are used to determine the relative concentration of a particular industry in a region. If the location quotient is equal to 1 then the particular industry is as

Weakly exogenous metropolitan statistical areas transmit internal supply and demand shocks to other less independent metropolitan areas.

institutional features of an economy can interrupt an
underlying equilibrium-type relationship possibly for an
extended period of time” (1996, 8). Examining cointegrating relationships over different periods of time
helps illuminate the evolution of those relationships.

short-run behavior of an economic series. If one can
demonstrate that a specific set of mathematical conditions is met, then it is possible to decompose data series
such as employment in Florida MSAs into their trend
(long-run) and cyclical (short-run) components.
As the appendix shows, the prerequisites of the
Vahid-Engle decomposition are met in data for the
Florida MSAs, so the series can be decomposed into
their long-term and short-term components. Chart 5
depicts the actual series and estimated employment
trends (which incorporate other macroeconomic effects
and are therefore not straight lines) for the six MSAs
from 1970 to 1996. In Chart 6 the cyclical components of
the trends are plotted by themselves. These lines correspond to the distance between the actual series and the
estimated trend in Chart 5.
These charts show that for each MSA there are several periods when the actual series is either above or
below the estimated trend. These deviations from the

Common Cycles
he remaining discussion explores the short-run
dynamics of the Florida MSAs’ labor markets.
This analysis will reveal some of the similarities
and differences in the reactions of the MSAs to shortrun economic shocks. The short-run behavior of the
MSAs can be strikingly different. One MSA may be able
to expand employment above its long-run trend while
another may be left below its long-run trend.
The concepts of common trends and common
cycles, as introduced in Vahid and Engle (1993), extend
the previous cointegration analysis. Their technique
can in some cases be used to separate the long- and

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

CHART 5
Actual Series and Estimated Tr ends of Total Nonagricultural
Payroll Employment for Six Florida MSAs, 1970–96

Employment (thousands)

Miami

Fort Lauderdale
640

960
900

560
840
Series

480

780

Series
720

400

660

320

Trend

600
240

540
480

160
1970

1975

1980

1985

1990

1995

1970

1975

Employment (thousands)

1985

1990

1995

Jacksonville

Orlando

700

450

500

350

Trend
Trend

Series

Series
250

300

150

100
1970

1975

1980

1985

1990

1995

1970

1975

We s t P a l m B e a c h
Employment (thousands)

1980

1985

1990

1995

Tampa
1100

400

Series

900

300
Trend

700
Trend

200

500

100

300
1970

1975

1980

1985

1990

1995

1970

1975

1980

1985

1990

1995

Source: Series from the Bureau of Labor Statistics

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

CHART 6
Estimated Cycles of Total Nonagricultural
Payroll Employment for Six Florida MSAs, 1970–96

Employment (thousands)

Miami

Fort Lauderdale

20
8
0
0
–20

–8

–40

1970

1975

1980

1985

1990

1995

1970

1975

1985

1990

1995

1990

1995

1990

1995

Jacksonville

Orlando
Employment (thousands)

1980

0
0
–20
–10
–40
–20
–60
1970

1975

1980

1985

1990

1995

1970

1975

Employment (thousands)

We s t P a l m B e a c h

1985

Tampa
20

10
10

0
0

–10

1970

1980

1975

1980

1985

1990

1995

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

1970

1975

1980

1985

long-term trend are generated by short-run economic
shocks to the growth of total payroll employment.
Positive shocks such as a temporary increase in demand
for a locally produced product (for example, a defense
contract for a local firm) would lead local businesses
temporarily to hire more workers than they otherwise
would have. While they were employing more workers,
the charts of the actual series and trend would show the
actual number of employees exceeding the long-term
trend. On the cyclical graphs this gap would correspond
to an upswing above the horizontal axis. Shocks in one
area may also spill over into others through demand for
or supply of labor. Further, two or more areas may be
subject to the same outside shocks or to shocks propagating across areas.
Comparing cycles shown by this series of charts
reveals both common and differential effects of shortterm shocks on the MSA’s employment. For example,
Miami’s and Orlando’s deviations from their long-run
trends appear in the Charts 5 and 6. Over the sample
period the short-run behavior of these two MSAs is very
different. In fact, they appear to be on opposite paths,
with Miami hitting the height of its cycle in 1980 at a
time when Orlando is near its lowest point.
Looking at all of the MSAs, it can be seen that during most of the expansion of the 1980s, Miami, Fort
Lauderdale, Tampa, and West Palm Beach are all above
their long-run trend. However, Jacksonville’s level of
total payroll employment, similar to Orlando’s, is below
its trend. Viewing Miami and Orlando as the driving
forces behind Florida’s economy could help explain the
apparent division of the state into a countercyclical
northern half and a procyclical southern one in terms of
total payroll employment during this time period.
Further examination of Chart 6 reveals that the
MSAs can be grouped into three pairs of similar dynam-

ics—Miami and Fort Lauderdale, Orlando and
Jacksonville, and West Palm Beach and Tampa. Miami
and Fort Lauderdale are the first to rise above their
long-run trends in the 1980s’ expansion. They are followed by West Palm Beach and Tampa. Orlando and
Jacksonville remained below their long-run trend during most of this period. It is interesting to note that West
Palm Beach, although geographically closer to Miami,
displays short-run dynamics more similar to Tampa’s in
terms of the timing of its cyclical upswing.

Conclusion
ointegration techniques developed by Johansen
(1995) and the common trends and common
cycles analysis developed by Vahid and Engle
(1993) have aided in studying the long- and short-run
interrelationships in the behavior of total payroll
employment in six Florida MSAs over the past quartercentury. The analysis showed that these MSAs have
shared a long-run comovement in their labor markets.
However, there are indications that these relationships
have changed as the economic structures of the MSAs
have evolved. Further, the cyclical dynamics displayed
by these cities suggest that the labor markets of the
northern half of the state behave differently from those
in the southern half in response to short-run economic
shocks.
This analysis helps underline the growing diversity
of influences on the growth trends of Florida MSAs. It
also suggests that these MSAs react differently to shortrun shocks. Both of these dynamics are important in
gauging the differing effects of policy or economic
shocks on the state in parts and as a whole.

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

A P P E N D I X

Decomposing the Series into
Trend and Cyclical Components
Given r cointegrating vectors defined as the n ´ r
matrix [a] and s cofeature vectors defined as the n ´ s
matrix [b], stack the vectors in one matrix A:

the condition of the Vahid-Engle decomposition that the
sum of the two groups of vectors add up to the number of
variables in the system.

éb ù
A = ê ú.
ëa û
Calculate A-inverse = [a- b-]. Partition A-inverse into the
s ´ n matrix [b-] and r ´ n matrix [a-]. This calculation
allows the decomposition into permanent (P) and cyclical
(C) components such that Y(t) = P + C. It follows, then,
that P = b-b Y(t) eliminates the cycles and leaves the
trend or permanent component; C = a-a Y(t) eliminates
the trend and leaves the cyclical or temporary component.
Using the maximum eigenvalue test results presented in Table A, it was found that the time series has four
cointegrating vectors. Next, to find the number of cofeature vectors, a test of canonical correlations between the
series and certain other variables as explained in Vahid
and Engle (1993) was used. This test (see Table B) shows
that Florida’s MSAs share two cofeature vectors, satisfying

Table A
Test of the Number of Cointegrating Vectors
Test Statistic
Critical Value

Test Statistic

50.30

24.63

31.77

20.90

27.45

17.15

15.65

13.39

6.79

10.60

0.13

2.71

The test of the null hypothesis that the number of
the cointegrating vectors is equal to r results in four
cointegrating vectors.

Table B
Test of the Number of Cofeature Vectors
Row

Appox F

Numerator DF

Denominator DF

Pr > F

2.7092

168

1644.062

0.0001

1.9561

135

1381.116

0.0001

1.7113

104

1113.348

0.0001

1.4652

840.884

0.0080

1.2902

564

0.0968

1.0946

283

0.3502

The F-test of the null hypothesis that the canonical correlations in the current row and all that follow are zero results
in two cofeature vectors. The number of cofeature vectors is equal to the statistically zero canonical correlations
(see Vahid and Engle 1993 for detailed explanations). The sum of the number of cointegrating vectors and cofeature
vectors equals the number of variables in the system, and the Vahid-Engle decomposition can be used.

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

REFERENCES
ENGLE, ROBERT F., AND CLIVE W.J. GRANGER. 1987.
“Co-integration and Error Correction: Representation,
Estimation, and Testing.” Econometrica 55:251–76.

SIKLOS, PIERRE L., AND CLIVE W.J. GRANGER. 1996. “Temporary
Cointegration with an Application Interest Rate Parity.”
University of California at San Diego, Discussion Paper 96-11.

JOHANSEN, SOREN. 1995. Likelihood-Based Inference in
Cointegrated Vector Autoregressive Models. Oxford: Oxford
University Press.

VAHID, FARSHID, AND ROBERT F. ENGLE. 1993. “Common Trends
and Common Cycles.” Journal of Applied Econometrics
8:341–60.

KRUGMAN, PAUL. 1991. Geography and Trade. Cambridge,
Mass.: MIT Press.

Federal Reserve Bank of Atlanta E C O N O M I C R E V I E W Third Quarter 1997

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