Full text of Economic Review (Federal Reserve Bank of Cleveland) : 1993 Quarter 4, Vol. 29, No. 4

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Vol. 29, No. 4

ECONOMIC REVIEW
1993 Quarter 4
Required Clearing Balances

2

by E.J. Stevens

The CPI as a Measure
of Inflation

15

by Michael F. Bryan and Stephen G. Cecchetti

The Inaccuracy of Newspaper
Reports of U.S. Foreign
Exchange Intervention
by W illiam P. Osterberg and Rebecca Wetmore Humes




FEDERAL RESERVE BANK
OF CLEVELAND

25

G E E M IC

R E V I E W

1993 Quarter 4
Vol. 29, No. 4

Required Clearing
Balances

2

by E.J. Stevens
More than 20 percent of the funds that banks have on deposit with the
Federal Reserve Banks are required clearing balances, not required re­
serve balances. Since 1981, when they first earned a market return,
clearing balances have become widespread among banks of all sizes.
Here, the author takes a look at the reasons for the popularity of this rela­
tively new phenomenon as well as its impact on the setting and measur­
ing of monetary policy.

The Consumer Price Index
as a Measure of Inflation

15

Economic Review is published
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Coordinating Economist:
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by Michael F. Bryan and Stephen G. Cecchetti
One problem associated with using the Consumer Price Index as a
focal point in monetary policy deliberations is the likelihood that it is a
biased measure of inflation. The authors use a simple statistical frame­
work in this paper to estimate a price index that is immune to some of
these weighting biases. By computing the common inflation element
in a broad cross-section of consumer price changes, they find evi­
dence of a positive weighting bias between 1967 and 1981, and an
insignificant bias in the years since then.

The Inaccuracy
of Newspaper Reports
of U.S. Foreign
Exchange Intervention

25

by W illiam P. Osterberg and Rebecca Wetmore Humes
This paper presents a comparison of official data on U.S. foreign
exchange intervention with newspaper reports. The authors find
that the series are systematically different, which calls into ques­
tion the ability of intervention to signal monetary policy accurately.
Alternatively, this divergence may reflect the fact that not all mar­
ket participants have equally accurate information about exchange
market intervention.




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Jagadeesh Gokhale
Joseph G. Haubrich

Editors: Tess Ferg
Robin Ratliff
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Typography: Liz Hanna

Opinions stated in Economic Re­
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eral Reserve Bank of Cleveland or
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Material may be reprinted pro­
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Please send copies of reprinted
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ISSN 0013-0281

Required Clearing Balances
by E.J. Stevens

E.J. Stevens is an assistant vice
president and economist at the
Federal Reserve Bank of Cleve­
land. The author thanks Cheryl L.
Edwards for helpful comments on
an earlier draft of this article and
Ann Dombrosky for invaluable re­
search assistance.

Introduction
Few people realize that in addition to complying
with a Federal Reserve System regulation for
holding a required reserve balance, many banks
simultaneously meet an additional requirement
to hold a clearing balance in their account at a
Federal Reserve Bank. This clearing balance re­
quirement differs from the familiar reserve re­
quirement in three significant ways. First, a bank’s
agreement to meet the requirement is typically a
business decision, not a legal necessity. Second,
the amount of the requirement is mostly discre­
tionary, not a fixed percentage of the bank’s de­
posit liabilities. And third, the rate of return on a
clearing balance is about equal to the federal
funds rate, not zero, although a bank can use the
earnings only to pay for services it buys from a
Federal Reserve Bank.
About 5,000 banks now maintain required
clearing balances, ranging from small retail de­
positories with a $25,000 minimum requirement
to giant money center banks with clearing bal­
ance requirements of several hundred million
dollars.1 Forty-five percent of all required re­
serve balances and 85 percent of all required

clearing balances are held by banks that use a
http://fraser.stlouisfed.org/
mixed
deposit account at a Federal Reserve
Federal Reserve Bank of
St. Louis

Bank to comply with the combined require­
ments. For each of these institutions, the conse­
quences of modest account deficiencies or
surpluses are reckoned on the basis of re­
quired clearing balance rules. Only if a bank
fails to meet any of its clearing balance require­
ment does it face the familiar “discount rate
plus 2 percent” penalty for a required reserve
deficiency. Likewise, such a bank wastes sur­
plus balances by earning no rate of return only
if its actual balance exceeds its required bal­
ance by more than a preestablished margin.
Almost all analyses of bank reserve manage­
ment behavior focus entirely on reserve require­
ments, ignoring clearing balances because they
are a relatively recent innovation.2 Clearly, how­
ever, an important set of banks now maintains
balances at the Fed following a somewhat differ­
ent set of rules than they would if they held only
required reserve balances. Knowledge of these
rules is of more than accounting interest. For one
thing — contrary to most models of the banking
■

1 For simplicity, I use the term banks to mean all depository institu­

tions.

■

2 A good survey might start with Poole (1968) and include Coats
(1976), Spindt and Tarhan (1978), Friedman and Roberts (1983), Evanoff
(1989), and Feinman (1993).

FIGURE

1

Required Balances at
Federal Reserve Banks
Billions o f dollars

SOURCE: Board o f Governors o f the Federal Reserve System.

system and of monetary policy implementation
— standard indicators of Federal Reserve policy,
including total and excess reserves and the
monetary base, probably contain a growing
(albeit very small) component that effectively
has a positive rate of return.
For another thing, banks seem to be substitut­
ing required clearing balances for required re­
serve balances. In the aggregate, banks now hold
about $33 billion of required balances at the Fed­
eral Reserve, including $27 billion of required re­
serve balances and $6 billion of required clearing
balances. Required reserve balances have de­
clined about $6 billion over the past three years,
while required clearing balances have almost
tripled (see figure l).3 Although banks surely
welcome lower reserve requirement taxes, the
Federal Reserve must deal with the payment sys­
tem risk and monetary policy implementation re­
percussions of a banking system operating on a
smaller cash deposit base. These repercussions
may be muted, however, to the extent that banks
replace required reserve balances with required
clearing balances. The question, then, is why
have required clearing balances grown so rapidly,
and, more particularly, would further cuts in re­
serve requirements be offset by further growth of
required clearing balances?
■

3 The dollar volume of required clearing balances is reported as foot­
note 3 In Factors Affecting Reserve Balances of Depository Institutions and
Condition Statement o f F.R. Banks (Federal Reserve Release H.4.1), and as
part of the larger “service-related balances and adjustments" item in the data
table "Reserve and Depository Institutions and Reserve Bank Credit" (Federal
 Reserve Bulletin, table 1.11). Clearing balance data are also reported in the
pro forma balance sheet for Federal Reserve priced services in the Board of
http://fraser.stlouisfed.org/
Annual Report.
Federal Reserve BankGovernors’
of St. Louis

This article is intended primarily to describe
the little-known rules governing required clear­
ing balances and to introduce some related
issues. The first two sections include back­
ground information about clearing balances
and a look at how a bank might manage a
combined required reserve and required clear­
ing balance. More precise institutional details
are spelled out in the appendix. The third sec­
tion outlines three areas in which issues war­
rant further investigation. One is the way in
which measures of bank reserves and the m on­
etary base have come to include an interestbearing component as a result of required
clearing balances. The next points to ambigu­
ity in explanations of the rapid growth of re­
quired clearing balances. A third sketches
some related central banking concerns about
monetary policy implementation and payment
service delivery.

I. Some Background
The Depository Institutions Deregulation and
Monetary Control Act of 1980 extended coverage
of Federal Reserve System reserve requirements
from member banks to all depository institutions.
At the same time, all depositories gained access
to the Federal Reserve discount window and to
Reserve Bank payment services. Services had to
be priced at levels intended to recover their full
cost of provision, including an allowance for the
interest costs and profit required by competing
private suppliers, such as conespondent banks.

Fair pricing requires a careful cost-accounting
distinction between Federal Reserve non­
priced, central bank activities such as reserve
requirements and the discount window, and its
priced semice activities such as check clearing.
Both activities may lead a bank to maintain a
deposit balance in an account at a Federal Re­
serve Bank.
Banks whose vault cash is not sufficient to
satisfy their reserve requirement can meet the
remainder of the requirement in either of two
ways. They can maintain funds in a deposit ac­
count at a correspondent bank on a pass­
through basis, making it easier for them to use
the services of correspondents without also
having to maintain an account at a Federal Re­
serve Bank to handle their payment needs. Al­
ternatively, banks can maintain the required
funds on deposit at a Federal Reserve Bank.
The Federal Reserve’s priced service activi­
ties are those for which it is not the sole sup­
plier. These include collection of commercial
checks, processing of commercial automated
clearinghouse items, wire transfer of funds and
government securities, safekeeping of definitive
securities, collection of noncash items, and
transportation of cash.4
A bank that uses these priced services needs
an account to which its payments and receipts
can be posted. Three possibilities exist. First, a
bank can contract to have its activity posted to
a correspondent bank’s Fed account. As just
noted, this might be especially appealing to
those institutions already maintaining required
reserve deposits at a correspondent on a pass­
through basis. Second, a bank that maintains a
required reserve deposit at a Federal Reserve
Bank might have its activity posted to that ac­
count. Flistorically, this has been the typical
choice of banks using the Reserve Banks’ pay­
ment services. Third, if required reserve depos­
its are unnecessary or inadequate for transaction
purposes, a bank might maintain additional bal­
ances in its Fed account under the required
clearing balance anangement.’ Since 1981, banks
have been able to pay for priced services with
earnings credits on required clearing balances.

■

4 The Reserve Banks also provide fiscal agent services for the U.S.
Treasury. A bank may use its Fed account to make and receive payments
associated with these services, whose costs are covered by fees paid by
either the banks or the Treasury.

■

5 Federal Reserve Banks have always been able to provide an ac­
count for customers who do not need to keep a required reserve balance
but who wish to make and receive payments there. Flistorically, this nor­
 mal banking practice apparently involved only an incidental aggregate
http://fraser.stlouisfed.org/
amount of overnight balances in clearing accounts.

Federal Reserve Bank of St. Louis

Whatever its choice, a bank will want to en­
sure that unexpected charges to its account do
not result in either penalties for daylight or over­
night overdrafts or reserve deficiencies, and
that unexpected receipts do not lead to “wasted”
excess reserves. Moreover, the Federal Reserve
Bank will need some assurance, as a prudent
banker, that charges to a bank’s account are
made against a sufficient balance. Required
clearing balances address these needs.
The mechanism for maintaining required
clearing balances and receiving earnings credits
was introduced in 1981 and modified in 1982
to include a penalty-free band.6 (See the ap­
pendix for a more detailed description.) This
anangement is comparable to the compensating
balance method that some respondent banks
and commercial firms use to pay for commercial
bank services. A required clearing balance is an
average amount that a bank contracts to hold in a
deposit account during a reserve maintenance
period. This balance is over and above any re­
quired reserve balance it must hold in that period.
A bank’s required reserve balance is determined
by deducting its holdings of vault cash from its
total required reserve, which in turn is a percent­
age of the bank’s deposits specified by regula­
tion. A bank’s required clearing balance is selfdetermined, presumably so that it may avoid
overdrafts and receive earnings credits commen­
surate with its monthly bill from the Federal Re­
serve Bank.
Periodically, a bank’s actual maintained bal­
ance is compared with its required balance.
Each business day, payments flow into and out
of a bank’s Federal Reserve account. For each
institution, the Reserve Bank records end-ofday account balances and then averages these
maintained balances for a reserve maintenance
period of one or two weeks, depending on the
size of the bank. If the bank has no required
clearing balance, its average maintained balance
(after certain “carryover” adjustments discussed
below) should equal or exceed the required re-

■

6 Each of the 12 District Banks provides official circulars and other
marketing materials informing customer banks about the terms on which
priced services are available, including the required clearing balance op­
tion. Operating to some extent as 12 distinct businesses, Banks have fol­
lowed procedures for maintaining clearing balances that have differed
somewhat in detail in the past. The most notable ditference was in allocat­
ing maintained balances between reserve and clearing requirements.
Some Banks allocated balances first to the required and then to clearing
requirements, while others did the reverse. This practice affected the pen­
alty structure on the initial amount of a deficiency, with some Banks as­
sessing required clearing balance penalties and others assessing
required reserve penalties. However, banking consolidation across Fed­
eral Reserve District lines, as well as consolidation of some operations
among the 12 Banks, has led to the uniform current set of procedures de­
scribed here (see Conference of First Vice Presidents [1993]).

5

serve balance (required reserves minus applied
vault cash). If the bank also has a required clear­
ing balance, the average maintained balance, after
carryover, should equal or exceed the total re­
quired balance plus or minus a penalty-free band.7
Maintained balances satisfy the reserve re­
quirement first, and the remainder is used to
satisfy the clearing balance requirement. A
bank is penalized if its balance falls short of the
required amount by more than a penalty-free
band, at the rate of 2 percent on amounts up
to 20 percent of the required clearing balance,
then 4 percent on amounts up to the whole re­
quired clearing balance, and at the discount
rate plus 2 percent on any remaining deficien­
cies in required reserves. The bank receives earn­
ings credits, based on the daily effective federal
funds rate, on balances in excess of its required
reserve up to the amount of its required clearing
balance plus the penalty-free band (adjusted
according to the bank’s marginal reserve ratio;
see appendix).8 Beyond that point, a bank penal­
izes itself for balances in excess of the required
amount plus the penalty-free band, because the
excess funds receive no earnings credits.
The penalty-free band is the greater of 2 per­
cent of a bank’s required clearing balance or
$25,000. Thus, a bank with a minimum required
clearing balance of $25,000 could satisfy the re­
quirement and receive earnings credits on the
amount by which its balance exceeds its required
reserve by anywhere from zero to $50,000, with­
out penalty. A bank with a $200 million required
clearing balance would receive earnings credits
on any balance above its required reserve up to
$204 million, and would satisfy its clearing bal­
ance requirement without penalty when this bal­
ance reached $196 million.
Required clearing balances affect the Fed’s
cost of providing priced services in two largely
offsetting ways. Total cost includes the earn­
ings credits that Reserve Banks grant on clear­
ing balances ($177.8 million in 1992), reduced
by an offset for unused credits. Total cost also
is lowered by an offset for the income that Re­
serve Banks earn on assets financed with re­
quired clearing balances. This offset is imputed
at the coupon-equivalent yield on three-month
Treasury bills ($180.2 million in 1992).9

Frequent stops to fill up take time and may
preclude unforeseen opportunities to buy gas
at a lower price. However, buying gas at a low
price only when the tank is nearly empty risks
running out of gas. So, too, a bank that buys
and sells funds frequently in order to keep its
balance close to the required amount at all
times may waste opportunities to buy or sell at
bargain rates, while buying or selling only
when the funds rate is a bargain raises the risk
of overdrafts and failure to satisfy require­
ments, or of wasted balances.
Banks work toward a target balance over
seven or 14 calendar days (normally, five or 10
banking days), depending on the size of the insti­
tution. Thus, a bank’s cumulative required balance
is seven or 14 times its average required balance.
During the period, the account manager has a
daily opportunity to target the day’s closing bal­
ance to add to the cumulative maintained balance.
The cost of financing an extra dollar of bal­
ances is essentially the rate at which a bank
might borrow or lend in the federal funds mar­
ket. This rate can vary noticeably over the
course of a single banking day, over differing
risk categories of borrower, and over days of a
maintenance period. A bank does better, the
more likely its manager is to “hit” the market
when the rate is attractive, in effect filling up
the fuel tank at places where gas is cheapest.
Clearly, the attractiveness of the rate depends
on the manager’s judgment about how expen­
sive funds are relative to what they might be
over the remainder of the period (and, with
carryover, over the following period).
Ultimately, at the end of a maintenance pe­
riod, the value of an extra dollar of balances is
determined by the structure of penalties and
earnings credits within which the Reserve
Banks administer requirements, including their
permissiveness in waiving penalties. For a
bank operating with only a required reserve bal­
ance, ignoring carryover, a deficiency would be
penalized at a rate 2 percent above the discount
rate, and frequent deficiencies would bring con­
sultations aimed at changing management’s be-

■

7 Hereafter, “required balance" will be used to indicate the sum
of a required reserve balance and a required clearing balance.

II. Managing a
Bank’s Fed Balance
In general, managing a bank’s balance at its Fed­
eral Reserve Bank is rather like managing one’s
 fuel supply on an extended automobile trip.


■

8 Earnings credits are not added to the balance in the account, but
accumulate for use in offsetting charges for priced services (on a first-in,
first-out basis) within 52 weeks.
■ 9 The amounts of these two items for calendar years are reported
as components of “Other income and expenses’’ in the pro forma balance
sheet for Federal Reserve priced services, published in the Board of Gov­
ernors' Annual Report.

6

havior. An excess would be wasted, costing
something to finance but earning no interest.
With this general background, the rationale for
a bank’s decision to hold a required clearing bal­
ance can be investigated in three different time
dimensions — a day, one or two maintenance
periods, and the long run of many maintenance
periods.

A Day
Uncertainty can be a dominant factor in a sin­
gle banking day. For a full-service bank, par­
ticularly a very large one, the level of its final
end-of-day balance results from its last-minute
interbank loan market maneuvering. A bank is
likely to be involved in daily payments and re­
ceipts whose aggregate value is thousands of
times larger than the required reserve balance.
Thus, even slight deviations of payments or re­
ceipts from projected levels might flood or
drain the bank’s Fed account during a day rela­
tive to the typical desired end-of-day balance.
The manager of this account nonetheless must
be able to come close to a targeted daily bal­
ance by arranging overnight borrowing or lend­
ing in the waning hours of the banking day in
amounts that can be far larger than the target
balance itself, and at attractive rates.
The protection that required clearing bal­
ances provide against daylight and overnight
overdrafts has become increasingly important
over the past decade. Reductions in reserve re­
quirements and increased use of vault cash to
satisfy requirements have left banks with
smaller required reserve balances, but with no
necessary change in the volume, time pattern,
or predictability of charges and receipts for
transactions. All else equal, this would be ex­
pected to increase the size and incidence of
overdrafts, both daylight and overnight.
The Federal Reserve Banks have measured
and monitored daylight overdrafts with increas­
ing precision over the last 10 years, with
amounts in excess of a minimum slated to be­
come subject to a fee in April 1994. Overnight
overdrafts already are subject to penalty (the
greater of 2 percentage points above the dis­
count rate or 10 percent). A bank without a re­
quired clearing balance might employ a variety
of strategies to reduce the probability of over­
drafts, including targeting a higher level of noninterest-bearing excess reserves. Contracting to
hold a required clearing balance would accom­
plish the same thing at almost no net cost, as
 long as the bank could use its earnings credits.


A Maintenance
Period
A bank needs a strategy for maintaining a set
of overnight Fed balances whose average will
most profitably satisfy its balance requirements
for the period, taking into account both the
previous period’s reserve surplus or deficiency
and the possibility of carrying a reserve defi­
ciency or surplus into the next period.
No single reserve management strategy ap­
pears to dominate banking practice. Some
banks target the average daily balance neces­
sary to meet the required balance (perhaps in­
cluding a margin of safety), recalculated daily
for the remaining days of the maintenance pe­
riod. Others try to accumulate balances toward
requirements only when the funds rate seems
low relative to the expected rate for the pe­
riod. Still others deliberately keep a lean posi­
tion early in a period, lest a negative surprise
in required reserves or a positive surprise in re­
ceipts provide more excess reserves than they
could work off over the remainder of the pe­
riod without overnight overdrafts. Also, some
banks try to alternate surplus and deficient pe­
riods, while others aim for a stable positive av­
erage balance, using the carryover feature only
to deal with big surprises.
Carryover. Without a required clearing bal­
ance, a large bank’s average balance for a
maintenance period could be above or below
the required level by as much as 8 percent of
its required reserves (not just its required re­
serve balance). Large banks are permitted to
carry over to the next period a surplus or defi­
ciency of up to 4 percent of required reserves,
but they cannot carry any resulting surplus or
deficiency into the following period. Eight per­
cent would result from using the maximum al­
lowable carryover of a surplus/deficiency from
the previous period and carryout of the maxi­
mum deficiency/surplus to the next period.
Adding a required clearing balance widens
the range within which a bank can allow its
maintained balance to fluctuate from one period
to the next while still satisfying requirements.
With the addition of a required clearing bal­
ance, the bank could be above or below the
(higher) required level by as much as 8 per­
cent of required reserves plus 8 percent of the
required clearing balance. This is because the
clearing balance requirement itself provides a
penalty-free band of plus or minus 2 percent
of the required clearing balance, and maximum
allowable carryover is 4 percent of required re­
serves, plus 4 percent of the required clearing

balance, minus the penalty-free band of 2 per­
cent of the required clearing balance.
A smaller bank (required reserves less than
$1.25 million) without a clearing balance require­
ment could be above or below the required level
of balances by as much as $100,000, because
banks may carry over the larger of 4 percent of
required reserves or $50,000. However, adding a
$25,000 minimum clearing balance requirement
would not change the range within which that
same small bank could allow its balance to vary.
Allowable carryover would actually decrease to
$25,000 ($50,000 net of the minimum $25,000
penalty-free band), offset by the ability to utilize
that penalty-free band.

The Long Run
Opting to maintain a required clearing balance
has obvious advantages for a bank. It can earn
a market rate of return on relatively small bal­
ances that might not fetch such an attractive
rate if sold as odd lots. Targeting a larger bal­
ance means, on average, holding a larger bal­
ance, thereby creating a greater buffer against
daylight and overnight overdrafts. Moreover,
the bank gains flexibility in managing its bal­
ance, with the penalty-free band providing a
convenient, costless margin of error around
the targeted balance that would be absent if it
were targeting a zero balance or only a re­
quired reserve balance.
With these benefits in mind, it might seem
surprising that all banks do not obligate them­
selves for as large a clearing balance as their
need for earnings credits would support. Pre­
sumably, this is because a bank’s capital is a
scarce resource, if for no other reason than
that banking regulations specify minimum lev­
els of capital per dollar of total assets. Banks
may restrict the volume of their required clear­
ing balances to the level at which, at the mar­
gin, it is more profitable to allocate scarce
capital coverage to other assets that promise a
better return than the expected spread be­
tween the earnings credit rate on required
clearing balances and their cost of financing.
Adopting a required clearing balance thus
has the following effects on a bank’s manage­
ment of its Fed balance:
• It holds a larger balance, with the addition
likely to be financed at little or no net out-ofpocket cost, but requiring a modest allocation
of capital.
• Its incidence of daylight and overnight
 overdrafts would likely be lower.


• Allowable carryover, whether positive or
negative, may be greater, providing a larger
base either for interperiod rate arbitrage or for
a bigger pool of funds from which to absorb
unforeseen shocks to the closing balance on
the last day, as well as for the period.
• The penalty-free band absorbs small de­
viations of actual from target balances without
either penalty or wasted earnings.

III. Three Issues
Related to Required
Clearing Balances
Measuring Bank
Reserves and the
Monetary Base
Traditional measures of Federal Reserve mone­
tary policy activity, including total and excess re­
serves and the monetary base, are being affected
by the growing influence of required clearing bal­
ances. The required clearing balance facility can
create an interest-bearing component of meas­
ured bank reserves quite distinct from the tradi­
tional non-interest-bearing reserve assets.
The potential influence of clearing balances
can be seen by considering how the reserve
and monetary base aggregates are constructed
from six measured values, each of which is an
average for a two-week reserve maintenance
period. In addition to required clearing bal­
ances, the other five measured values include
1) Fed balances: The aggregation of over­
night balances of all depository institutions.
2) Applied vault cash: The amount of priorperiod vault cash holdings being used to sat­
isfy current-period reserve requirements.
3) Other vault cash: The difference between
banks’ current and applied vault cash.10
4) Currency in M l: The portion of currency
in circulation held by the nonbank public.
5) Required reserves: The total amount of
reserves that banks are required to hold, as speci­
fied in Federal Reserve Regulation D.
Data are derived from banks' reports of depos­
its to the Federal Reserve and are assembled
with and without “adjustments to eliminate the
effects of discontinuities,” or “breaks,” associ­
ated with changes in reserve requirements.
The adjusted series estimates the amount of trans­
action deposit reserve requirements that would
have prevailed in the past, had cunent reserve
requirements been in effect; the unadjusted se-

■

10 This is not the same as surplus vault cash (see Gartinkel and
Thornton [1991]).

F I G U R E

2

Reserve and Clearing Balance
Requirements: The Rules

NOTE: XR = excess reserves; RCB = required clearing balance; RRB = required
reserve balance; AVC = applied vault cash; PFB = penalty-free band; Rf = fed­
eral funds rate; and Rd + 2 = discount rate.
SOURCE: Author.

ries reports the then-current actual requirements.
Required clearing balances are excluded from
all measures of reserves, by definition, and from
the adjusted monetary base, but are included in
the unadjusted monetary base. This treatment is
consistent with the differing purposes of the two
measures of the monetary base.
The adjusted series emphasizes the role of
base money as actual or potential reserve as­
sets. These are the high-powered “tickets” that
banks must hold when issuing reservable de­
posits, with the amount issued per ticket con­
strained by a reserve requirement. The adjusted
monetary base includes the reserve assets held
both by banks (adjusted total reserves plus vault
cash not being used to meet reserve requirements)
and by the nonbank public (cunency in M l). A
historically consistent measure of adjusted total
reserves has been derived by adding the actual
historical quantity of excess reserves to adjusted
required reserves. Similarly, because banks’ bal­
ances held to meet a clearing balance require­
ment cannot be used to satisfy reserve require­
 ments, the adjusted monetary base excludes
http://fraser.stlouisfed.org/
required clearing balances.
Federal Reserve Bank of St. Louis

The unadjusted monetary base emphasizes
the federal government’s role in providing
monetary assets directly to users in the private
sector, rather than distinguishing between the
quantities of private and public issues of
money. The monetary base consists of all feder­
ally issued currency held by banks and the
public (applied vault cash plus other vault
cash plus currency in M l), plus all deposit li­
abilities of Federal Reserve Banks to private
banks (Fed balances, including required
clearing balances). The associated measure of
total reserves adds applied vault cash to Fed
balances and then subtracts required clearing
balances (because they are not reserves). Ex­
cess reserves is the difference between this
measure of total reserves and required reserves.
Measuring total or excess reserves thus in­
volves distributing aggregate account balances
between reserve balances and clearing balances.
The current method does so by measuring re­
serve balances as all cunent balances other than
required clearing balances.11 Any excess of
maintained balances above the required clearing
balance level, even within the penalty-free band
(for example, point A in figure 2), thus augments
aggregate total and excess reserves. Similarly,
any deficiency of maintained balances from the
required clearing balance level, both within and
below the penalty-free band (for example, point
B in figure 2), reduces aggregate total and excess
reserves, even though the bank may have satis­
fied its reserve requirement.
A potential implication of this measurement
convention can be illustrated by imagining an
extreme case. Suppose that a ll banks were to
move simultaneously from the upper to the
lower edge of their respective penalty-free
bands between adjacent maintenance periods.
Within a 2 percent penalty-free band above
and below the current $6 billion of required
clearing balances, actual total and excess re­
serves would vary by about a quarter of a bil­
lion dollars, with banks largely indifferent to
the change. That is, their earnings loss from
holding a lower balance at the Fed would be
approximately equal to their earnings gain from
financing a lower balance. With many banks,
some holding more and some holding less
than their required clearing balances, positive
and negative deviations from required clearing
balances within penalty-free bands would likely

■ 11 Adjusted total reserves equals adjusted required reserves plus
actual excess reserves, which in turn equals applied vault cash plus Fed
balances net of required reserves and required clearing balances. Unad­
justed total reserves equals applied vault cash plus Fed balances net of
required clearing balances.

tend to be offsetting. More generally, however,
the greater the participation in required clearing
balance anangements, the more probable that
modest variations either in the supply of bank
balances at the Fed, in total and excess re­
serves, or in the adjusted monetary base would
be a matter of little moment to banks, since
their net earnings would be unaffected.12
The essential issue here is whether total and
excess reserves, as now measured, match any
useful economic concept. The measures have no
necessary counterpart at the level of an individ­
ual bank managing its reserve position, because
carryover and penalty-free bands are unrecog­
nized. Banks that perpetually maintain cunent
balances in excess of cunent requirements truly
have cunent-period “excess” reserves. Other
banks, however, will be in different stages of us­
ing carryover, either satisfying some of their cur­
rent reserve requirements with surplus balances
from adjacent periods, or using cunent surplus
balances to satisfy some of their reserve require­
ments in adjacent periods.
Carryover itself does not destroy the utility
of the current measures: A positive shock to
the supply of reserves in one period, for exam­
ple, tends to imply a comparable negative
shock to demand for total and excess reserves
in the next period, and the System can rely on
that carryover relationship in managing nextperiod supply. The difficulty comes from the
addition of a penalty-free band, which makes
it impossible to know whether a shock to re­
serve supply will affect next-period demand
through carryover, or simply be accommo­
dated as earning assets this period through the
penalty-free band.

Sources of Growth
in Required Clearing
Balances
Managing a bank’s required reserve balance at
successively lower levels of reserve require­
ments has been likened to landing an airplane
on a shrinking aircraft carrier. As the target bal­
ance gets closer to zero, there is less room for
error. Averaging within a maintenance period
provides less opportunity to absorb surprises,
as does the possibility of carrying forward ex­
cesses and deficiencies. Overall, the banking

■

12 Paying interest on total or excess reserves would not preclude
effective monetary policy. See Dotsey’s (1991) investigation of monetary
policy operating procedures in New Zealand, where there are no reserve
 requirements and where banks settle using a below-market interest-bearing
http://fraser.stlouisfed.org/
asset whose supply is controlled by the central bank.

Federal Reserve Bank of St. Louis

system becomes less effective in smoothing
interest rates.13
With these impediments in mind, the rapid
growth of required clearing balances in recent
years might be linked to the cuts in reserve re­
quirements of December 1990 and April 1992.14
Banks increased their required clearing bal­
ances by more than a third in the month follow­
ing the December 1990 cut and doubled their
requirements within a year (see figure 1). How­
ever, it would not be easy to distinguish the im­
pact of lower reserve requirements from that of
either rising bills for priced services or declining
interest rates.
The utility of earnings credits lies in paying
bills for priced services, so the size of these
bills places an upper limit on the volume of
clearing balances that banks could find useful.
In the aggregate, the percentage of total sales
of priced services paid with earnings credits,
while growing, was still less than 20 percent
in 1992. There is some indication that banks,
including some with the largest required clear­
ing balances, do tend to adjust their require­
ments in concert with the magnitude of their
bills. What would be difficult to discover, how­
ever, is the extent to which annual growth of
billings has “caused” the growth of required
clearing balances. More important for the fu­
ture would be to determine what portion of
the remaining 80 percent of the priced services
revenue billed to banks would be capitalized
as additional required clearing balances if re­
serve requirements were cut further.1'’
Many banks could be expected to adjust
balances to keep pace with bills because their
required clearing balances are likely to be fi­
nanced at a slightly positive rate spread, mak­
ing priced services cheaper when paid from
earnings credits. Earnings credits are calculated
on the basis of the daily effective federal funds
rate, which is the quantity-weighted average
rate paid by all borrowers of unsecured over­
night balances each day. Large banks operat­
ing actively in the interbank funds markets

■

13 Feinman (1993) provides an excellent analysis of these relation­

ships.

■

14 The 1990 action reduced the 3 percent reserve requirement
against nontransaction deposits to zero, lowering required reserves by an
estimated $13.7 billion. The 1992 action reduced from 12 percent to 10
percent the highest marginal reserve requirement on net transaction de­
posits, cutting required reserves by an estimated $8.9 billion.

■

15 Hilton, Cohen, and Koonmen (1993) have Investigated this
question, as well as a variety of techniques that might expand the use of
required clearing balances.

thus might expect to acquire marginal financ­
ing at rates averaging less than the effective
rate, because foreign buyers and some others
typically pay risk premiums that large domestic
banks, for example, do not pay. This would in­
sert a profit wedge between the effective rate
used in calculating earnings credits and the
cost of financing required clearing balances.
With this in mind, some of the past growth in
required clearing balances probably reflects
the increase in total sales of priced services
and the attraction of paying with earnings cred­
its. In fact, if this relationship were one for
one, about 14 percent of the growth of re­
quired clearing balances since 1990 might re­
flect growth of total sales of priced services.
Putting aside billing magnitudes, the level of
the federal funds rate can also exert an inde­
pendent, powerful influence on the size of a
required clearing balance needed to produce a
dollar’s worth of earnings credits. For example,
to hold earnings credits constant at their 1990
value, the substantially lower federal funds rate
would have called for a 61 percent increase in
required clearing balances by 1992.
Even if, for purposes of argument, demand
for required clearing balances had been direct­
ly proportional to billings and inversely propor­
tional to the level of the federal funds rate, banks
added about $1 billion more to their holdings of
required clearing balances after 1990 than the hy­
pothetical amounts these two forces would have
produced. This suggests that banks have been
induced to replace required reserve balances
with required clearing balances. The relative in­
fluences of the three forces are not clear, how­
ever, because their movements have been conelated. Clarifying their relative importance will be
crucial in dealing with some of the policy issues
with which required clearing balances may be­
come associated.

Monetary Policy
Issues
Reserve requirements are a tax whose cost has
become a serious issue in the United States in
recent decades, as the competitive niche of tra­
ditional banking has faded in financial markets.
Lower requirements can increase Federal Re­
serve payment system risk exposures through
daylight and overnight overdrafts, can contrib­
ute to volatile overnight interest rates that could
hamper monetary policy implementation, and
can degrade the value of central bank payment
 services (Stevens [1989, 1991b, 19931). Further


cuts in reserve requirements might bring signifi­
cant institutional changes in banking and pay­
ment arrangements, with increased privatization
of payment services to avoid daylight over­
drafts, or with new Federal Reserve arrange­
ments to ensure that deposit balances at the
Fed remain an effective vehicle for monetary
policy implementation (Meulendyke, ed. [1993],
Stevens [1991a, 1992]).
Additional cuts in required reserves could re­
duce the System’s effectiveness in interperiod
smoothing of short-term interest rates. Reserve
carryover plays a role in this smoothing proc­
ess, allowing the banking system to absorb un­
intended variations in the System’s supply of
balances. The penalty-free band can serve the
same purpose, but has different implications
for policy implementation. Banks tend to “make
u p ” reserve deficiencies and surpluses in the
next period, providing the System with a vital
clue to interperiod variations in demand for the
balances it supplies.16 This is lacking in the op­
eration of the penalty-free band. Thus, the Sys­
tem could face multiperiod runs of demand for
balances below or above a required level.
An additional policy implementation prob­
lem may arise from the earnings credit feature of
required clearing balances. Restrictive policies
will carry within themselves the seeds of their
own disorganization. That is, as the federal funds
rate rises, the quantity of clearing balances
needed to pay for a given quantity of Reserve
Bank priced services will decline, increasing the
possibility of the interest-rate variability associ­
ated with low balances. A high interest-rate pol­
icy might also discourage use of some Federal
Reserve payment services, by reducing the nomi­
nal quantity of Fed balances available for imme­
diate transfer within overdraft limits.
Relying on required clearing balances as the
vehicle for implementing monetary policy thus
raises a more general question. Is a bank’s re­
quired clearing balance a by-product of its
choice of the Fed as the best among alternative
suppliers of services, or is the choice of the Fed’s
priced services a by-product of the bank’s need
for a larger balance? In either case, the Monetary
Control Act’s neat distinction between central
bank activities and priced service activities is not
as clear-cut as it once appeared.

■ 16 Feinman (1993) finds that for a sample of large banks from
1987 to 1991, excess reserves and carry in had opposite signs about 90
percent of the time.

KB
IV. Conclusion
The emergence of required clearing balances is
changing the institutional setting in which indi­
vidual banks manage their Fed balances. Banks
are able to hold balances substantially larger
than dictated by reserve requirements, provid­
ing greater flexibility in avoiding overdrafts
and meeting reserve requirements— and at
minimal cost.
Familiar aggregate data series are being af­
fected by bank holdings of required clearing
balances. In effect, a definable, probably small,
but as yet unmeasured portion of the total and
excess reserves of the banking system is now
earning assets, rather than being held as noninterest-bearing vault cash or reserve deposits.
More important, marginal variations in banks'
Fed balances increasingly take place within the
earnings and cost structure of required clearing
balances, not required reserve balances.
Growth of required clearing balances relative
to required reserve balances raises questions
that need further investigation. Can required
clearing balances be expected to replace re­
quired reserve balances if reserve requirements
are cut further? How would monetary policy
implementation be influenced when a change
in the money market stance of policy affects
not only the marginal cost but also the mar­
ginal revenue of many banks’ Fed balances?
To what extent does the demand for clearing
balances reflect a desire to pay bills with earn­
ings credits, and to what extent does it reflect
a demand for larger balances? If demand is
mainly for convenient bill paying, could Fed­
eral Reserve priced services generate a pool of
balances large enough to maintain a smoothly
operating money market when interest rates
are high? O n the other hand, if demand is
mainly for a level of balances high enough to
accommodate transaction needs, could banks
use all of the Federal Reserve priced services
their balances could buy when interest rates
are high?
Congress created the Federal Reserve Sys­
tem as a single response to the joint desire for
a more uniform national payment system and
for a regulator of the nation’s money supply.
The mandate of the Monetary Control Act of
1980 was that these two functions should exist
independently, in the sense that the Federal
Reserve Banks could no longer provide free
payment services to offset banks’ costs of main­
taining required reserves. Subsequent cuts in re­
serve requirements have allowed the banking
 system to reduce its holdings of non-interest

bearing required reserve balances at the Federal
Reserve Banks to historically low levels relative
to bank deposits and the monetary base. All
else equal, continuing along this trend would
require some combination of changes in mone­
tary policy implementation and in the payment
system to accommodate the absence of cash in­
ventories in the banking system. Alternatively,
required clearing balances could provide a new
basis for banks to hold deposits at the Federal
Reserve Banks, but whether this is feasible re­
mains to be demonstrated.

Appendix
Required Balances:
The Rules17
Current reserve and clearing balance require­
ments include two types of rules: those for
computing and maintaining required balances
and those for calculating earnings credits and
penalties.
Many banks are “unbound”— that is, either
they have a zero reserve requirement or they
meet the requirement entirely with vault cash.
These banks nonetheless may maintain a re­
quired clearing balance. Other banks are
“bound” by a positive reserve requirement that
exceeds their vault cash. They must maintain a
required reserve balance, but do not hold a re­
quired clearing balance. A large number of
banks, however, are both bound to hold a re­
quired reserve balance and elect (or have been
asked) to hold a required clearing balance.
The rules laid out here, and summarized in
figure 2, are for a bank that must meet a com­
bined reserve and clearing balance, maintained
on the biweekly basis that is typical of a rela­
tively large institution. The other two cases
may be derived by dropping all references to a
required reserve balance or to a required clear­
ing balance, as the case may be. Note that in
maintaining a balance, a bank that holds only
a required clearing balance cannot use the car­
ryover feature, and a bank that holds only a re­
quired reserve balance cannot use the
penalty-free-band feature.

■

17 From Standard Operating Procedure 10.0, Conference of First
Vice Presidents (1993). See also Board of Governors of the Federal Re­
serve System, Monetary Policy and Reserve Requirements Handbook,
Washington, D.C.: Federal Regulatory Service.

Computing and
Maintaining a
Required Balance
A bank’s required balance, RB, is not a unique
dollar amount, but a range around the com­
bined required balance.
RB = (RRB + RCB) ± PFB.
The combined required balance includes a
required reserve balance, RRB, that is the
bank’s total reserve requirement, RR, net of its
applied vault cash, A VC.
RRB = RR —A VC.
The total reserve requirement is computed
by applying appropriate marginal reserve re­
quirement ratios to the amount of a bank’s
transaction deposit liabilities in each of three
“tranches.” In 1993, requirements are zero on
the first $3-8 million of deposits, 3 percent on
additional deposits up to $46.8 million, and 10
percent on deposits in excess of $46.8 million.
Requirements typical of large banks are
computed on the basis of daily average transac­
tion deposit liabilities outstanding during suc­
cessive two-week reserve computation periods
ending every other Monday. Applied vault
cash is the bank’s daily average holdings dur­
ing the 14-day period that ends three days be­
fore the beginning of the maintenance period.
The required clearing balance, RCB, is nor­
mally a dollar amount agreed to by the bank
and its Federal Reserve Bank, with a $25,000
minimum. As stated by the Federal Reserve
Bank of Cleveland (1992),
The prescribed level of an institution’s clearing bal­
ance will be determined in consultation with the in­
stitution on the basis of the deposit size of the
institution, the volume and type of services that are
or will be used, and the need to avoid account
overdrafts.... This Bank may make adjustments in
the prescribed level of an institution’s clearing bal­
ance from time to time as may be appropriate.
Such adjustments will normally be made no more
than once a month and will be effective on the first
Thursday of the month that coincides with the first
day of a maintenance period.

The penalty-free band, PFB, for required clear­
ing balances establishes a range of balances that
will satisfy the combined required balance, be­
cause actual holdings are allocated first toward
 the required reserve balance, with the remainder


allocated toward the required clearing balance.
The band is 2 percent of the required clearing
balance, or $25,000 if the required clearing bal­
ance is less than $1.25 million.
A bank’s maintained balance, MB, is the av­
erage daily closing balance in its Fed account,
averaged over a two-week maintenance period
(for a typical large bank) that begins on a
Thursday and ends on a Wednesday, two days
after the end of the required reserve computa­
tion period.
Carryover provisions allow a bank to carry
forward to the next maintenance period an ex­
cess or deficiency in its maintained balance to
the extent that it is offset by a deficiency or ex­
cess in the next period. The amount of carry­
over can be no more than (0.04 [RR + RCB] PFB) and cannot be carried forward more than
one period. Note that the limit on eligible carry­
over is based on a bank’s reserve requirement,
RR, not on its reserve balance requirement.

Earnings Credits,
Penalties, and
Wasted Balances
Earnings credits provide a return on required
clearing balances that can be used only to pay
for Federal Reserve Bank priced payment serv­
ices.18 Required reserve and surplus balances
earn nothing. The return is based on the average
federal funds rate during the maintenance period
in which the required clearing balance was held.
The funds rate is applied on an annualized basis
to the actual average daily clearing balance (with­
in the upper limit of the penalty-free band), ad­
justed by the bank’s marginal reserve requirement
ratio. A bank subject to the 10 percent marginal
reserve requirement will earn the funds rate on
its entire allowable clearing balance, a bank
subject to a 3 percent marginal requirement
will earn the funds rate on only 93 percent of
that balance, and a bank subject to a zero mar­
ginal reserve requirement will earn the funds
rate on only 90 percent of the balance.
The marginal reserve requirement adjustment
incorporates two factors that allow Federal Re­
serve Banks and correspondent banks to pro­
vide similar services to customer banks on the
“level playing field” envisioned in the Mone-

■

18 More specifically, earnings credits
be used to pay pen­
alties for clearing balance deficiencies or to cover charges related to non­
priced service functions of the Federal Reserve Banks, such as penalties
for deficient required reserve balances, Interest on discount window
loans, and cost recoveries for providing accounting information services.

tary Control Act. To illustrate, first suppose that
correspondent banks have a 10 percent mar­
ginal reserve ratio and that the incidence of
the cost of a correspondent’s reserve require­
ment is on its respondent customer banks.
This suggests that the Reserve Banks might
give earnings credits on only 90 percent of a
required clearing balance to avoid placing
themselves at an advantage relative to corre­
spondent banks in providing priced services.
Second, recognize that a bank paying for
correspondent bank services with earnings
credits on balances held with the correspon­
dent is able to deduct the amount of those bal­
ances from its own deposit liabilities subject to
reserve requirements. (Deducting amounts “due
from other banks” avoids double-reserving of
interbank deposits.) If the same bank were to
buy services of equal value from a Federal Re­
serve Bank and pay for them with earnings
credits on a required clearing balance, it would
lose the deduction. This is irrelevant for a bank
with a zero marginal reserve requirement, but
not for those reserving 3 percent or 10 percent
at the margin. Therefore, the Fed should give
earnings credits on 93 percent or 100 percent
of required clearing balances, depending on
the customer’s marginal reserve ratio, to avoid
placing itself at a disadvantage relative to corre­
spondents in providing priced services.
Penalties are imposed on a bank whose
maintained balance is deficient, to the extent
that the deficiency is not offset by carryover
from the previous period or to the next period.
Maintained balances are allocated first toward
the required reserve balance, with the remain­
der allocated toward the required clearing bal­
ance. A bank pays a penalty at an annual rate
that rises with the size of the deficiency: no
penalty on the first 2 percent (or $25,000) of
the required clearing balance (the penalty-free
band), 2 percent of the next 18 percent of the
required clearing balance (or of the next 20
percent minus $25,000), and 4 percent of the
remainder of the required clearing balance.
Deficiencies that extend into the required re­
serve balance are penalized at a rate 2 percent­
age points above the discount rate.
Balances can be said to be wasted to the ex­
tent that they exceed the required range and
are not carried forward to the next period. Such
balances do not contribute to satisfying a re­
serve or clearing balance requirement and do
not receive earnings credits.




References
Coats, Warren L., Jr. “What Do Reserve Carry­
overs Mean for Bank Management and for
Free Reserves?” Jo u rn a l o f B ank Research,
Summer 1976, pp. 123-27.
Conference of First Vice Presidents. Subcommit­
tee on Accounting Systems, Budgets, and Ex­
penditures, Standard Operating Procedure
10.0. Washington, D.C.: Board of Governors
of the Federal Reserve System, 1993Dotsey, Michael. “Monetary Policy and Operat­
ing Procedures in New Zealand,” Federal Re­
serve Bank of Richmond, Economic Review,
vol. 77, no. 5 (September/October 1991),
pp. 13-19.
Evanoff, Douglas D. “Reserve Account Manage­
ment Behavior: Impact of the Reserve Ac­
counting Scheme and Carry Forward
Provision,” Federal Reserve Bank of Chi­
cago, Working Paper No. 89-12, June 1989.
Federal Reserve Bank of Cleveland. “Mainte­
nance of Reserve and Clearing Accounts,”
Operating Letter No. 4, August 27, 1992.
Feinman, Joshua. “Bank Reserve Management,
Overnight Overdraft Penalties, and Carryover:
Theory and Evidence,” Board of Governors
of the Federal Reserve System, unpublished
manuscript, June 1993Friedman, Richard M., and William W. Roberts.
“The Carry-Forward Provision and Manage­
ment of Bank Reserves "Jo u rn a l o f Finance,
vol. 38, no. 3 (June 1983), pp. 845-55.
Garfmkel, Michelle R., and Daniel L. Thornton.
“Alternative Measures of the Monetary Base:
What Are the Differences and Are They Im­
portant?” Federal Reserve Bank of St. Louis,
Review, vol. 73, no. 6 (November/December
1991), pp. 19-35.
Hilton, Spence, Ari Cohen, and Ellen Koonmen.
“Expanding Clearing Balances,” in Ann-Marie
Meulendyke, ed., Reduced Reserve Require­
ments: Alternativesfo r the Conduct o f Mone­
tary Policy an d Reserve Management. New
York: Federal Reserve Bank of New York,
April 1993, pp. 109-35.

Poole, William. “Commercial Bank Reserve Man­
agement in a Stochastic Model: Implications
for Monetary Policy,” Journal o f Finance, vol.
27 (December 1968), pp. 769-91Spindt, Paul, and VefaTarhan. “The Liquidity
Structure Adjustment Decision of Large
Money Center Banks,” Board of Governors
of the Federal Reserve System, Special Stud­
ies Paper No. 121, October 24, 1978.
Stevens, E. J. “Removing the Hazard of Fedwire
Daylight Overdrafts,” Federal Reserve Bank
of Cleveland, Economic Review, vol. 25, no.
2 (1989 Quarter 2), pp. 2-10.
___________ . “Federal Funds Rate Volatility,”
Federal Reserve Bank of Cleveland, Eco­
nom ic Commentary, August 15, 1991a.
___________ . “Is There Any Rationale for Re­
serve Requirements?” Federal Reserve Bank
of Cleveland, Economic Review, vol. 27, no.
3 (1991b Quarter 3), pp. 2-17.
___________ . “Comparing Central Banks’ Rulebooks,” Federal Reserve Bank of Cleveland,
Economic Review, vol. 28, no. 3 (1992 Quar­
ter 3), pp. 2-15.
___________ . “Price Isn’t Everything,” Federal
Reserve Bank of Cleveland, Economic Com­
mentary, April 1, 1993-




I B

The Consumer Price Index
as a Measure of Inflation
by Michael F. Bryan and Stephen G. Cecchetti

Introduction
As the economy approaches the Federal Reserve’s
stated objective of price stability, it has become
necessary to examine carefully the price indices
on which policy is based. The most popularly
used aggregate price statistic in the United States
is the Consumer Price Index (CPI). This fact alone
probably accounts for the prominence it has
achieved as a measure of inflation and as a focal
point in the Federal Reserve’s inflation fight. As
an expenditure-weighted index of cost-of-living
changes, though, the CPI was never intended
to be used as an indicator of inflation.
Broadly speaking, there are two problems as­
sociated with using the CPI to measure inflation.
The first concerns the transitory noise created by
nonmonetary events, such as sector-specific
shocks and sampling enors. The second involves
a potential bias in the index that results both from
the expenditure-based weighting scheme the CPI
employs (weighting bias) and from persistent er­
rors in measuring certain prices (measurement
bias). In an earlier paper, Bryan and Cecchetti
(1993), we study the first of these issues.1 Here,
we examine the second.
The existence of bias, or deviations between

http://fraser.stlouisfed.org/
the trend in the price indices and inflation, im­
Federal Reserve Bank of St. Louis

Michael f. Bryan is an economist at
the Federal Reserve Bank of Cleve­
land, and Stephen G. Cecchetti is a
professor of economics at The
Ohio State University and a re­
search associate at the National
Bureau of Economic Research.
The authors wish to thank Mark
Watson for helpful discussions
and for providing his software.
This paper benefited from the sug­
gestions of Martin Feldsteln,
Dennis Fixler, Spencer Krane,
Pok-sang Lam, Nelson Mark,
Angelo Melino, Alan Viard, and
Mark Wynne. In addition, the
authors thank Edward Bryden,
Christopher Pike, and Matthew
Mercurio for research assistance.

plies that any fixed-weight price index will be
an imperfect long-run target for a policy aimed at
aggregate price stability. The magnitude of the
bias in the CPI is an empirical matter. Previous
researchers have addressed the issue of bias in
price statistics by performing calculations based
on highly disaggregated information.2 This ap­
proach provides at best only a broad approxima­
tion. Moreover, the bias in price statistics
depends on the severity and origin of supply
shocks, on changes in technology and tastes,
and on other time-varying phenomena, so the
time-invariant estimates derived from these saidies are of only limited value to policymakers.
Our strategy is different. Using a simple sta­
tistical framework, we compute a price index
that is immune to the weighting bias inherent

■

1 That paper shows how the use of limited-influence estimators,
such as the median of the cross-sectional distribution of individual con­
sumer goods prices, removes transitory elements that create difficulties
with interpreting month-to-month movements in the aggregate CPI. We
find that the median CPI performs well as a high-frequency measure of
the persistent component of inflation.
■

2 See Wynne and Sigalla (1993) for a thorough review of the literature.

in the CPI as a measure of inflation. The recent
work of Stock and Watson (1991) provides a
method for combining information in many
time series to generate an index of coincident
economic conditions. This paper attempts to do
for prices what Stock and Watson have done
for output. We use a dynamic factor model
analogous to theirs to compute the common
inflation element in a broad cross-section of
consumer price changes.
Unlike expenditure or output-weighted price
indices, the dynamic factor index is an unbiased
estimate of the component common to each of
the individual price changes in the crosssection of data we examine. By comparing the
trend in the dynamic factor index with the trend
in the CPI, we are able to gauge the extent of
the weighting bias in the CPI as a measure of
inflation. Our results suggest that over the 25year period from 1967 to 1992, the weighting
bias in the CPI averaged roughly 0.6 percent­
age point per year. But, since we can construct
a time series for the dynamic factor index, we
are able to estimate the bias over two economi­
cally distinct periods. We find that there was a
large positive weighting bias during the 15 years
beginning in 1967, but that the weighting bias
has been insignificant since 1981.'
The following section discusses the sources
of bias in fixed-weight price indices. We con­
tinue with a brief description of the dynamic
factor model employed to construct an unbiased
measure of consumer price inflation together
with its standard error, and then present a sum­
mary of our results.

I. Bias and
Expenditure-Weighted
Price Indices
In order to understand the bias in fixed-weight
price indices as measures of inflation, we be­
gin by defining measured inflation, n t , as a
constant expenditure-weighted index of price
changes from period t-1 to t, or

(1 )

nt =Y.wpPr

mon inflation component and an idiosyncratic
relative price movement, represented as
(2)

where mt is inflation and xjt is a relative, or
real, price disturbance.
Substituting equation (2) into (1), and not­
ing that
= 1, we can write measured infla­
tion as
(3)

which states that the growth rate of a standard
fixed-weight price statistic sums inflation and a
weighted average of relative price disturbances.
For purposes of policy formulation, we need
to obtain a measure of the common element
mt or, alternatively, a measure of n t constructed
so that the expectation of the sum on the right
side of equation (3) is zero.4
Unfortunately, the expectation of Kt does not
equal mt\E( ¿JVp xjt) * 0. There are two rea­
sons for this “bias.” First, the individual prices
may, on average, be measured inconectly. We
broadly refer to this as a “measurement bias.” In
addition, actual expenditure shares, wjt , and xj{
are conelated, producing a “weighting bias.” In
either case, the expectation of the observed xJt’s
will be nonzero. Our approach is designed to
minimize enors caused by weighting bias. And
although the dynamic factor approach we have
chosen will have little directly to say about meas­
urement biases— inasmuch as they are unrelated
to the choice of weighting schemes employed—
we can make inferences about certain types of
these biases by examining subsets of the data.

■

3 Strictly speaking, the weights used by the Bureau of Labor Statistics
(BLS) in the construction of the CPI vary slightly with relative price changes
from year to year. This Is necessary in order to hold constant the Implicit real
quantity of any item used in the calculation of the index. This fixed-weight
price index also differs slightly from the CPI because we are summing the
weighted logs of the individual prices rather than the weighted levels.
■




n t = mt + ^ w Joxj t ,
j

j
where wJO is a set of base-period expenditure
weights and pjt is the percentage change in the
price of good j from period t-1 to t? The ex­
penditure weights are defined to sum to one.
The next step is to note that changes in the
individual goods prices, the pJt’s, share a com­

pj{ = mt + xjt,

4 If the xjt's are mean zero and the weights are constant, then

E (n { )= mr However, realizations of n , are unlikely to equal m t , and
we can also think of nt as a noisy measure of inflation. There are several
reasons why realizations of £

wj0 xjt will not equal zero period by pe­

riod. First, there is simple sampling error in the Individual price data. But
in its absence,
wj0 xjt may not equal zero period by period because of
the way the economy adjusts to real shocks. In our earlier paper, we use a
simple model derived from Ball and Mankiw (1992) to describe how
supply shocks may cause price indices such as n t in equation (1) to con­
tain transitory movements away from mt .

It should be clear at this point that the bias
in a price statistic as a measure of inflation,
which is a statistical concept, is distinct from
the bias as a measure of the cost of living, al­
though the two may share similar origins, as
we explain shortly. In a strict sense, the choice
of the term “bias” may be somewhat unfortu­
nate here, as it does not reflect an error in the
calculation of the CPI per se, but rather an er­
ror caused by applying the CPI to a problem it
was never intended to address. Bias in the CPI
as a measure of inflation is simply the devia­
tion in the trend of n t from mt , whereas bias
in the CPI as a measure of the cost o f living is
defined as the deviation in the CPI trend from
a constant utility price index.
Consider the case of substitution bias, in
which the price of a single good rises. Label
this as good k, so that xkt > 0. In the absence
of monetary accommodation, the household
budget constraint requires the sum of the rela­
tive price disturbances weighted by actual ex­
penditure shares to be zero, or

where (3 measures the covariation of actual
expenditure weights and relative price distur­
bances. Substituting equation (5) into (4) yields

(6)

I> y 0 ^ i+ X P / * / i = °
j

j

or

(6')

2 > y o Xj X = “ X M v i j

j

This is the weighting bias — only if
= 0 will
the sum of the base-period weights and the
relative price disturbances be zero. Otherwise,
a weighting bias will arise that has the oppo­
site sign of the covariation of the expenditure
weights and the relative price disturbance.
Nevertheless, there exists a set of weights, wjt,
such that
(7)

E ( ^ w jt xjt) = 0.
j

(4)

5 > A

= °-

j

For each relative price increase xkt, the relative
price of the remaining goods must fall propor­
tionately such that wktxkt + ^ wjtxjt = 0. Yet,
j*k
consumer theory implies that expenditure shares
will change depending on the price elasticity of
demand for the product: Goods having an elastic­
ity greater than one will experience declines in
their relative expenditure, and vice versa. The
implication here is that if an actual expenditure
weight tends to fall for a product whose relative
price rises, it reduces the exactly offsetting relative
price influence of the remaining set of commodi­
ties when applied to their original expenditure
weights and creates a positive bias in the infla­
tion statistic: wkoxkt +
Xjt > 0 .
j* k
Substitution bias is simply a specific form of a
general weighting bias. To see this more clearly,
consider a simple two-period example. We can
represent actual expenditure weights in period 1
as a function of the base period weight and the
relative price disturbance in period 1,
(5)

wjX = wjQ + pyxyl ,




The Wjt ’s can be thought of as the inflation
weights — those that yield a price index with­
out a weighting bias.

II. Origins of Bias
in the CPI
In general, we think of all of the biases in the CPI
as a measure of inflation as arising from some
combination of weighting and measurement
bias. As we have already described, weighting
bias is the consequence of covariation between
relative price changes and a set of properly con­
structed weights. The classic example of such a
weighting bias is substitution bias, where the py’s
are negative and the weighting bias is positive.
Studies of the size of the commodity substi­
tution bias conducted in recent years have con­
cluded that the amount of substitution bias in
the CPI is relatively small. For example, Manser
and McDonald (1988) estimate that the com­
modity substitution bias averaged between 0.14
and 0.22 percentage point per year over the
period 1959 to 1985. This is largely a confirma­
tion of Braithwait’s (1980) earlier estimate of
0.1 percentage point per year over the 1958 to
1973 period. Moreover, Manser and McDonald
find the level of the bias to be one-third greater
for the high-inflation period (1972 to 1985)
than for the more moderate inflation period of
1959 to 1972.

It is entirely conceivable that there are cases
in which the correlation between expenditure
weights and measured relative price changes is
positive, imparting a downward weighting bias
in fixed-weight inflation measures. One such
case would be a demand-induced relative price
increase resulting from a change in tastes,
where the relative price of a commodity rises
because the relative expenditure on it has risen.
Consider also the case in which new goods
are introduced. The market basket purchased by
households will expand to include items not given
any weight in the cunent index or, alternatively,
actual expenditure weights on the included goods
will fall. As a consequence, price changes for the
goods included in the price index are given too
much weight relative to a conectly measured
price index. If the relative price change for the
new good is negative, the new good produces a
positive bias in the price index that is analogous
to substitution bias. But it is possible to imagine
a case in which the relative price change of the
new good is positive, resulting in a negative bias
in the price statistic. This would hold true if new
goods cause a substitution away from, as well as
a decrease in the relative price of, the goods in­
cluded in the index.
Similarly, changes in relative product quality
produce a weighting bias by introducing a cor­
relation between actual expenditure weights
and relative prices. Quality changes imply that
the same effective quantity is available for a
generally lower price and, depending on the
elasticity of demand for the product, the share
of expenditure on such a good could either
rise or fall as its effective price drops.5
In many instances, weighting bias is not the
sole source of the error from using the CPI as
a measure of inflation. A number of potential
biases arise when the prices of individual com­
modities are mismeasured. To see how this af­
fects the indices we are studying, consider the
case in which measured price changes have
three components: the common element, mt,
the correctly measured relative price change,
xJt, and a common, nonzero measurement
error, et . We can write this as
■

5 As an empirical matter, measuring new goods bias is much more
difficult than measuring commodity substitution bias, since new goods
prices are unobservable prior to their introduction. As noted in Diewert
(1987), Hicks (1940) suggests that the price of the new good prior to its in­
troduction should be the shadow price at which demand is equal to zero.
While this is an excellent theoretical criterion, implementation is simply not
possible. As a result, little work has been done on estimating the importance
of new goods bias. There are, however, several rough estimates of the size of
this problem. Diewert (1987) suggests that the bias caused by new goods
could be as high as 0.5 to 1.0 percentage point annually, while Lebow,
 Roberts, and Stockton (1992) gauge the amount as no more than 0.5 per­
http://fraser.stlouisfed.org/
centage point per year.

Federal Reserve Bank of St. Louis

(8)

pjt = mt + xjt + et.

It is readily apparent that the measured price
index will be
(9)

n = m t + et + ^ w j0 xjr
j

That is, measurement enor will be embedded in
the inflation statistic independent of the weight­
ing scheme. New goods (and other excluded
goods more generally) introduce the potential for
measurement bias to the extent that the set of
prices is no longer complete. Moreover, insofar
as average quality changes are reflected in the
price data, they also create a measurement bias
by producing a common trend in the price data
that is unrelated to inflation.6
So-called “outlet substitution bias,” arising from
the tendency of consumers to escape some part
of price increases by shifting purchases toward
lower-priced (discount) stores, is another recently
identified source of measurement bias. We can
think of this bias as some combination of newgoods bias and quality bias, as the goods sold by
the discount retailers might be considered sepa­
rate commodities from those sold by full-service,
higher-priced stores.7

■

6 The quality adjustment problem has been the subject of the bulk
of academic work on price measurement bias. Beginning with Griliches’
(1961) study of automobile prices, this literature has concentrated on esti­
mating the quality bias in the prices of specific durable goods, presum­
ably because the quality of durable goods Is more easily quantifiable and
data are usually readily available. Estimates of quality bias in the aggre­
gate price index are then extrapolated from the measurements derived for
specific commodity groups. For example, Gordon (1992) estimates that
quality changes account for slightly more than 1.5 percentage points of
the average rise in the prices of consumer durable goods over the 1947
to 1983 period. By applying this estimate to goods that they presuppose
to be subject to quality improvements, Lebow, Roberts, and Stockton
(1992) estimate aggregate quality bias in the CPI to be 0.3 percentage
point annually.
■

7 The recent growth in the discount retail business has led econo­
mists to increase their concern over outlet substitution bias. When con­
sumers substitute between retail outlets on the basis of price, and this
shift in the buying pattern is not captured in the point-of-purchase survey
conducted by the BLS, the CPI overstates inflation. While the Labor De­
partment adjusts its sample over time, no more than 20 percent of the
change in outlet patterns is incorporated into a particular year’s survey.
Consequently, this measurement problem can affect the aggregate
price statistic for a period of several years. A recent study by Reinsdorf
(1993) examines the effect of outlet substitution during the 1980s on
food and fuel commodities. Assuming that none of the price differences
among outlets reflect quality differentials, he concludes that outlet bias
accounts for between 0.25 and 2.0 percentage points annually for food,
and between 0.25 and 1.0 percentage point annually for energy.

III. A Dynamic
Factor Index
Approach
Our objective is to compute a reduced-bias esti­
mate of inflation from consumer price data. Re­
call from equation (3) that we can write a fixed
expenditure-weight price index as the sum of
common inflation, rht, and a term representing
the weighted sum of relative price changes,
^ w J0xJt. This makes clear that the measure­
ment of inflation requires a set of weights that
allow us to construct an estimate of the com­
m on element in all price changes. Price indices
such as the CPI, the Producer Price Index (PPI),
or the implicit price deflator for personal con­
sumption expenditures (PCE) share a common
core, but as a result of their weighting method­
ologies, each has a unique weighting bias as a
measure of inflation.
As an alternative to the expenditure weighting
schemes generally used, we propose weighting
commodity prices based on the strength of the
inflation signal, mt, relative to the noise, xJt, in
each time series. To do this, we assume that the
log of each individual product price is the sum of
two components: a nonstationary, common core,
and a nonstationary, idiosyncratic component
measuring movements in relative prices. Taking
first differences, the model can be written as

Maximum likelihood estimation of mt is ac­
complished by applying a Kalman filter to a
set of either aggregate or individual price data.
The result
is AanA estimate
of both the 1parameter
A
A
vector, a = {'P jB .r}, where T is the diagonal
covariance matrix of r\and the common factor,
mt . We can write mt as a weighted sum of cur­
rent and past individual pJt’s. Expressly,

(13)

which is an unbiased estimate of mt . Put slightly
differently, the dynamic factor index is an esti­
mate of the common trend in the individual inflar
\
tion series such that E
Wj(L) xjt = 0 .

I

v J
Our main interest is in measuring the average
weighting bias in the CPI over various sample pe­
riods. This is the difference between the average
inflation in the CPI and the average mt, which
we label rht . We would also like to construct an
estimate of the standard enor of this bias.
Rewriting (13) in matrix form, we have
(14)

(11)

y (Z )m ,= 5 + ^f,

(12)

Q(L)xt = P + ri,,

where p t and xt are vectors;
and 0 are, respectively, a vector and matrix of lag polyno­
mials with stationary roots; i, and r\are i.i.d.
random variables; and P and 8 are vector and
scalar constants.8 We identify mt by assuming
that relative price disturbances are unconelated
with common inflation at all leads and lags. This
is what is meant by a common component. If
mt were conelated with any of the x ’s, then
they would contain a part of the common core.
In addition, it is necessary to restrict the (3’s to
sum to zero. For computational convenience, we
further assume that 0(Z) is a diagonal matrix of
lag polynomials, that T), is serially unconelated,
and that the covariance matrix of r\t is diagonal.9


http://fraser.stlouisfed.org/ 8 See Stock and Watson (1991 ) for details.
Federal Reserve Bank of St. Louis

mt = W ( L ) p t .

It follows that
(1 5 )

(10) p t= m t + x t ,

mt = ^ W j ( L ) pJt,

m

= \ r ( l) p /;,

A

where |i/; is the vector of estimated means of in­
flation in the individual component price series
and 11/(1) is a function of the elements of a .10
It is useful to rewrite the CPI in a way analo­
gous to (15). From equation (1), we have
^6)

n=

which is the estimate of average inflation in the
CPI constructed as a constant weighted log-linear
index. An estimate of the bias follows as
(17)

BUts=K- rh = W0ÿip - W(l)\ip
= [W0 - W ( l ) ] Î p .

The construction of standard error estimates
is slightly more complicated, but still straightfor­
ward. To do this, we require an estimate of all

■

9 Throughout, we assume that both mt and the x jf 'scan be

modeled as AR(2)’s.

■

10 The notation H/(1) represents the evaluation of the lag polyno­
mials at L = 1, and so is the sum of the polynomial coefficients.

F I G U R E

1

Comparison of the CPI,
PCE Deflator, and DF2

SOURCES: U.S. Department o f Labor, Bureau o f Labor Statistics; U.S. Depart­
ment o f Commerce, Bureau o f Economic Analysis; and authors’ calculation«

TABLE

1

Comparisons of the CPI and the
CPI/PCE Dynamic Factor Index
(annualized percent changes)

of the parameters used to calculate m and n. This
includes the estimated covariance matrix of a as
well as an estimate of the covariance matrix of
the vector of estimated means
The first of
these is a by-product of the maximum likelihood
estimation of a , while the second can be con­
structed from the raw inflation data.
Calculation of the covariance matrix of |x is
complicated by the fact that the p f s have sub­
stantial serial conelation. In fact, the model (10)(12) implies that when 'F(Z) and the 0 (Z)’s are
all second-order polynomials, the individual infla­
tion series will follow an ARMA(4,2).n This
leads us to use the Newey and West (1987) heteroskedasticity and autoconelation consistent co­
variance estimator, with 24 lags.
We can now construct an estimate of the co­
variance matrix of the entire parameter vector
y = {a , jiip} , called jr. Assuming that a and |i^
are independent, then X is block diagonal. Be­
cause m and n are both functions of y, we
can construct standard errors by computing the
vector of first partial derivatives of each with re­
spect to y. The variance estimates follow by
pre- and post-multiplying X by this vector of
derivatives.
A
It is worth noting that the uncertainty in Bias
comes from variation in W {\), which is a func­
tion of a , and variation in
. But the uncer­
tainty in the mean vector creates variation in the
estimation of mean CPI inflation as well, and so
the variance in the estimated bias is likely to be
lower than the variance in either m or 71.12

Feb. 1967Dec. 1981

Jan. 1982Dec. 1992

Full
Sample

CPI all items

7.05
(0.94)

3.75
(0.33)

5.65
(0.71)

IV. The Results

PCE deflator

6.36
(0.71)

4.05
(0.26)

5.38
(0.53)

DF2

6.65
(0.81)

3.75
(0.33)

5.48
(0.59)

Weighting bias

0.39
(0.23)

0.00
(0.00)

0.17
(0.15)

We constructed two alternative dynamic factor
indices of inflation based on consumer price
data from 1967 to 1992. The first, labeled DF2,
is the common element derived from the CPI
and the PCE deflator, two aggregate consumer

NOTE: Numbers in parentheses are standard errors. The covariance matrix
of the means o f the two components was com puted using a Newey and
West (1987) robust covariance estimator with 24 lags. Subperiod calculations
were made independently from the full sample. All values are the average an­
nual difference in the natural log of the index.
SOURCE: Authors.




■

11 It is simple to show that the model implies that, ignoring con­
stants, each individual inflation series can be written as 0¡(L) 4* (L) pjt
= 0y(/.)£f+¥ (L) r\
]t, which is a restricted ARMA (4,2).

■

12 As implied by the discussion at the end of the previous section,
the block diagonality of the covariance matrix allows us to measure the
relative contribution of variation in the model parameters, the elements of
â , and the mean vector, j i to the estimated variance of the bias. In virtu­
ally all of the cases we examine, the uncertainty from estimation of the
means accounts for more than 95 percent of the uncertainty in Bias.

F I G U R E

2

12-Month Growth Rates of the
CPI, DF2, and DF36

SOURCES: U.S. Department o f Labor, Bureau o f Labor Statistics; U.S. Depart­
ment o f Commerce, Bureau o f Economic Analysis; and authors’ calculations.

Comparisons of the CPI and the
36-Component Dynamic Factor Index
(annualized percent changes)
Feb.1967Dec. 1981

Jan. 1982Dec. 1992

Full
Sample

CPIa

6.93
(0.85)

4.04
(0.26)

5.71
(0.63)

DF36

6.05
(0.68)

4.11
(0.25)

5.11
(0.52)

Weighting bias

0.88
(0.26)

-0.07
(0.13)

0.60
(0.17)

a. The CPI used here was constructed as the weighted sum o f the difference
o f the natural logs o f the individual components (1985 weights).
NOTE: Numbers in parentheses are standard errors. The covariance matrix
o f the means o f the 36 components was com puted using a Newey and West
(1987) robust covariance estimator with 24 lags. Subperiod calculations were
made independently from the full sample. All values are the average annual
difference in the natural log o f the index.
SOURCE: Authors.




price statistics that are constructed from essen­
tially the same price data, but that employ dif­
ferent weighting schemes (figure 1). Over the
full sample, this dynamic factor index averaged
5.48 percent per year with a standard error of
0.59 percentage point. This yields a weighting
bias over the period of 0.17 percentage point
with a standard error of 0.15 percentage point
(table 1). Subperiod estimates, which are com­
puted separately using data for only the sub­
samples, reveal more bias in the 1967 to 1981
interval, about 0.4 percentage point annually.
Over the latter period, there appears to have
been no bias in the CPI.
The aggregate CPI and the PCE deflator
may not provide a rich enough set of price
data to measure the common element accu­
rately. As an alternative, we calculated the dy­
namic factor index from disaggregated price
data for 36 components of the CPI (DF36),
spanning the complete set of the consumer
market basket over the same January 1967 to
December 1992 period.13 The 12-month
growth rates of the CPI, DF2, and DF36 are re­
produced in figure 2.
The average rate of increase of this more com­
prehensive dynamic factor index over the sample
period is 5.11 percent, compared with 5.71 per­
cent for the CPI, implying an average annual bias
in the CPI of 0.60 percentage point over the 1967
to 1992 period with a standard enor of 0.17 per­
centage point (table 2). Using 36 rather than two
indices increases the estimated weighting bias
with virtually no change in precision. But again,
we find substantial differences in the magnitude
of the CPI weighting bias between the two sub­
periods. Between 1967 and 1981, we estimate the
weighting bias at 0.88 percentage point annually
(with a standard enor of 0.26). But since 1981,
we fix the bias in the CPI to be nearly zero (-0.07
percentage point with a standard enor of 0.13
percentage point).
The dynamic factor indices have limitations,
of course. First, the degree of disaggregation
and the extent of the sample covered by the
price data used are incomplete. More generally,
our calculations do not account for the poten­
tially important measurement biases that arise
when goods are systematically excluded or
when there is a common measurement error,
such as unmeasured aggregate quality changes.
While we cannot address such measurement
biases directly, we can gauge their severity by

■ 13 A catalog of the 36 components can be found in Bryan and
Cecchetti (1993).

Comparisons of the Dynamic Factor
Indices of Goods and Services Prices
(annualized percent changes)
Feb. 1967Dec. 1981

Jan. 1982Dec. 1992

Full
Sample

CPIa

6.93
(0.85)

4.04
(0.26)

5.71
(0.63)

DF36

6.05
(0.68)

4.11
(0.25)

5.11
(0.52)

DFGOODS

5.43
(0.69)

3.55
(0.30)

4.47
(0.54)

DFSERVICES

7.06
(0.70)

4.90
(0.27)

(0.53)

6.02

Estimated Bias
CPI-DF36

0.88
(0.26)

CPI-DFGOODS

1.50
(0.30)

-0.07
(0.13)

0.60
(0.17)

0.49
(0.15)

1.23
(0.20)

a. The CPI used here was constructed as the weighted sum o f the difference
o f the natural logs o f the individual components (1985 weights).
NOTE: Numbers in parentheses are standard errors. The covariance matrix of
the means o f the 36 components was com puted using a Newey and West
(1987) robust covariance estimator w ith 24 lags. Subperiod calculations were
m ade independently from the full sample. All values are the average annual
difference in the natural log o f the index.
SOURCE: Authors.

comparing dynamic factor indices computed
from commodity subsets of the data.14
In our statistical model, equations (10) to (12),
relative price changes are taken to be stationary.
With the additional assumption that relative price
changes are zero on average (that is, that the P’s
in equation [12] are all zero), we can estimate the
common factor from any subset of the data.
Some economists have suggested that the most
serious problem may be in measuring service
output. This means that services prices are un­
reliable, and we use that insight to examine
the size of this potential measurement bias.15

14 Measurement bias might manifest itself as low-frequency com­
ponents in the X jt ’s of certain series. The implication is that the single­
factor model we employ may not be sufficiently general to capture the
time-series behavior of some prices. If this were a serious problem, then
we should find that some of the roots of the estimated AR(2) coefficients
in 0 (L) imply nearly nonstationary behavior. Our estimates suggest that
this may be a problem for medical commodities, motor fuel, and transpor­
tation services, but is unlikely to affect the commodities generally thought
to suffer from significant measurement difficulties.

To test the hypothesis that there is a systematic
bias in the measurement of services prices, and
to evaluate the recommendation that these prices
be excluded from the calculation of inflation, we
have split the CPI into goods and services compo­
nents and have computed a dynamic factor in­
dex for each. The results are reported in table 3.
Assuming that the difference between infla­
tion in goods prices and inflation in services
prices is entirely a result of measurement bias in
the latter category, we can gauge the weighting
bias in the CPI from the difference between the
dynamic factor index estimated using goods only
(DFGOODS) and the aggregate CPI. Again,
while we note rather substantial differences be­
tween the two prior to 1982, for the recent pe­
riod, we estimate the weighting bias in the CPI at
less than 0.5 percentage point per year.
These results also allow us to estimate the
size of the measurement bias in services prices di­
rectly by comparing the dynamic factor indices
for goods only (DFGOODS) and services only
(DFSERVICES). Curiously, the deviation between
the dynamic factor indices calculated from the
component data, while relatively large for the
1967 to 1981 period (1.63 percentage points an­
nually), is slightly smaller in the post-1981 period
(1.35 percentage points annually). While there
appears to have been a systematic bias in serv­
ices prices before 1982, which may be attribut­
able to their mismeasurement, that difference
was reduced after 1981.16

V. Conclusion
Gauging the accuracy of price indices, which
has a long tradition in economics, has taken
on new enthusiasm in the recent era of rela­
tively moderate inflation. At issue is whether a
goal of zero inflation literally means zero or
whether, because of various biases in the calcu­
lation of inflation, some low but nonzero rate
of measured inflation is sufficient.
We have computed dynamic factor indices
of consumer prices, which are constructed by
essentially weighting commodities on the strength

■


http://fraser.stlouisfed.org/
■ 15 A recent example is in Poole (1992).
Federal Reserve Bank of St. Louis

■ 16 In the early 1980s, the methodology used to construct the shel­
ter component of the CPI, which accounts for roughly half of all services
in the index, was changed from a relatively volatile purchase-price basis
to a rental equivalence basis. To account for this change, we reconstruct­
ed the shelter component to conform to a rental equivalence basis for the
entire sample. This change, not surprisingly, had little impact on the dy­
namic factor index calculations. Nevertheless, the results reported here
are on the adjusted basis.

of a common inflation signal, in an attempt to
assess a potentially important source of bias in
the CPI as a measure of inflation— weighting
bias. Our estimate of weighting bias in the CPI
is roughly 0.6 percent annually in the 1967 to
1992 period, but the size of that bias varies sub­
stantially within subperiods. In fact, on the ba­
sis of the estimates provided here, we conclude
that since 1981, weighting bias in the CPI as a
measure of inflation has been negligible.
If there is measurement bias common to the
consumer prices in our data set, such as may
occur from the systematic mismeasurement of
quality changes, it would still be embedded in
the estimates presented here. We found signifi­
cant differences between the dynamic factor es­
timates derived from all items and the dynamic
factor indices derived from goods prices only.
In this paper, we have considered only the
case of consumer prices, given their impor­
tance in the monetary policy setting and also
allowing for comparisons with other studies of
bias. Conceivably, a measurement bias com­
mon to all consumer prices caused by, say, a
reallocation of the economy’s resources be­
tween investment and consumption goods
may be embedded in the dynamic factor indi­
ces presented here.17 This could presumably be
conected by allowing the dynamic factor index
to include a broader range of prices, particularly
asset prices. An area of future research, then,
would involve the integration of investment
goods into these dynamic factor calculations.

References
Alchian, Armen A., and Benjamin Klein. “O n a
Correct Measure of Inflation,” Jo u rn a l o f
Money, Credit, a n d Banking, vol. 5, no. 1
(February 1973), pp. 173-91.
Ball, Laurence M., and N. Gregory Mankiw.
“Relative Price Changes as Aggregate Sup­
ply Shocks,” National Bureau of Economic
Research Working Paper No. 4168, Septem­
ber 1992.
Braithwait, Steven D. “The Substitution Bias of
the Laspeyres Price Index: An Analysis Us­
ing Estimated Cost-of-Living Indexes,”
Am erican Economic Review, vol. 70, no. 1
(March 1980), pp. 64-77.
Bryan, Michael F., and Stephen G. Cecchetti.
“Measuring Core Inflation,” National Bureau
of Economic Research Working Paper No.
4303, March 1993.
Diewert, W.E. “Index Numbers,” in John Eatwell, Murray Milgate, and Peter Newman,
eds., The New Palgrave D ictionary o f Eco­
nomics. London: Macmillan Press, 1987, pp.
767-80.
Gordon, Robert J. “Measuring the Aggregate
Price Level: Implications for Economic Per­
formance and Policy,” National Bureau of
Economic Research Working Paper No.
3969, January 1992.
Griliches, Zvi. “Hedonic Price Indexes for Auto­
mobiles: An Econometric Analysis of Quality
Change,” in Price Statistics o f the Federal Gov­
ernment. New York: National Bureau of Eco­
nomic Research, 1961, pp. 173-96.
Hicks, John R. “The Valuation of Social Income,”
Economica, vol. 7 (1940), pp. 105-24.
Lebow, David E., John M. Roberts, and David J.
Stockton. “Economic Performance under
Price Stability,” Board of Governors of the
Federal Reserve System, Working Paper No.
125, April 1992.

■

17

The potential for a systematic measurement bias, caused by the

exclusion of investment goods in the CPI, has been suggested by Alchian
http://fraser.stlouisfed.org/
and Klein (1973).
Federal Reserve Bank of St. Louis

Manser, Marilyn E., and Richard J. McDonald.
“An Analysis of Substitution Bias in Measur­
ing Inflation, 1959-1985,” Econometrica,
vol. 56, no. 4 (July 1988), pp. 909-30.

Newey, Whitney K., and Kenneth D. West. “A
Simple, Positive Semi-Definite, Heteroskedasticity and Autocorrelation Consistent Co­
variance Matrix,” Econometrica, vol. 55, no.
3 (May 1987), pp. 703-08.
Poole, William. “Where Do We Stand in the Battle
against Inflation?” Report to the Shadow Open
Market Committee, March 8-9, 1992.
Reinsdorf, Marshall. "The Effect of Outlet Price
Differentials on the U.S. Consumer Price In­
dex,” in Murray F. Foss, Marilyn E. Manser,
and Allan H. Young, eds., Price Measure­
ments a n d Their Uses. Chicago: University of
Chicago Press for the National Bureau of
Economic Research, 1993, pp. 227-54.
Stock, James H., and Mark W. Watson. “A Prob­
ability Model of the Coincident Economic
Indicators,” in Kajal Lahiri and Geoffrey H.
Moore, eds., Leading Economic Indicators:
New Approaches a n d Forecasting Records.
Cambridge: Cambridge University Press,
1991, pp. 63-89.
Wynne, Mark A., and Fiona Sigalla. “A Survey of
Measurement Biases in Price Indexes,” Fed­
eral Reserve Bank of Dallas, Research Paper
No. 9340, October 1993-




The Inaccuracy of Newspaper
Reports of U.S. Foreign
Exchange Intervention
by William P. Osterberg and
Rebecca Wetmore Humes

Introduction
Central bank intervention in foreign exchange
markets most recently came into prominence dur­
ing the period of exchange-rate volatility in the
autumn of 1992. Speculators doubted that Euro­
pean central banks would be able to defend the
exchange rates agreed upon as part of the Euro­
pean Rate Mechanism. After massive intervention,
central banks eventually capitulated, and several
key exchange rates were allowed to fall radically
against the German mark (DM). While this se­
quence of events would seem to have cast con­
siderable doubt on the usefulness of sterilized
intervention, disagreement continues both within
policy circles and among researchers as to
whether sterilized central bank intervention is a
useful tool for exchange-rate management.1
Until recently, studies of intervention have
been hampered by a lack of official data, as
direct measures of central bank intervention
■

1 Researchers would point out that this most recent period was not
a good test of intervention's efficacy because exchange-rate management
was not the sole objective of the central banks. In addition, some of the
intervention may not have been sterilized, making it difficult to isolate its
impact. “Sterilization” occurs when the effect of intervention on the money
supply is offset by open market operations. Nonsterilized intervention is
http://fraser.stlouisfed.org/
thus, in some sense, equivalent to monetary policy.

Federal Reserve Bank of St. Louis

William P. Osterberg is an econo­
mist and Rebecca Wetmore Humes
is an economic analyst at the Fed­
eral Reserve Bank of Cleveland.
The authors thank Owen Humpage
and Mark Sniderman for helpful
comments.

have usually not been made available to the
public. Now, however, the Board of Governors
of the Federal Reserve System provides a time
series of U.S. dollar intervention vis-à-vis the
DM and the Japanese yen from 1985 to 1992.
One consequence of the former lack of imme­
diately available and accurate intervention in­
formation has been the use of daily newspaper
reports as proxies for actual intervention mag­
nitudes in related studies.
The possibility that intervention is not re­
ported accurately may have important implica­
tions for understanding the signaling mechanism
of intervention. For example, such inaccuracy
may call into question the ability of intervention
to signal future monetary policy with precision.
In addition, it may reflect differences in the infor­
mation available to foreign exchange traders, sug­
gesting that some traders may be able to profit
from inside information.
In this paper, we begin with a discussion of
issues regarding information about intervention.
We then describe the data on actual intervention
and newspaper reports. In the third section, we
outline the procedure that we use to test for sys­
tematic differences between reported and actual in­
tervention series. In the final section, we briefly
discuss the implications of our results.

I. Information about
Intervention:
Reported versus
Actual Data
There is by now a substantial literature de­
voted to understanding the impact of central
bank intervention on foreign exchange mar­
kets. Recent useful summaries of this literature
have been provided by Dominguez and
Frankel (1993), Edison (1993), Humpage
(1991), and Obstfeld (1990).2
While most recent studies, such as Baillie and
Humpage (1992), Baillie and Osterberg (1993),
and Hung (1992), use official daily intervention
data, others, such as Klein and Rosengren (1991)
and Kaminsky and Lewis (1993), use daily news­
paper reports of intervention.3 If the focus of a
given study is on the signaling role of interven­
tion. then it makes sense to utilize newspaper re­
ports that reflect the information available to the
average trader.
One concern is that the choice of interven­
tion data, reported or actual, may influence re­
searchers’ conclusions about the efficacy of
intervention. However, we would like to raise
two other possible concerns, namely, that if
there is a systematic difference between actual
and reported intervention, 1) the signals as rep­
resented by the newspaper reports may be mis­
leading, and 2) some market participants may
have more accurate information about interven­
tion than do others. That the latter is possible
can be seen simply by considering the mecha­
nisms of intervention. U.S. intervention counter­
parties are either brokers or commercial banks.
If brokers are utilized, they will not reveal that
the transaction is official intervention. If com­
mercial banks are utilized, the wire services
should accurately reveal that the Federal Re­
serve has entered the market.4 In either case,
the only market participants with definitive
knowledge are the counterparties chosen by
the Federal Reserve Bank of New York.
If we are willing to assume that the newspaper
reports indicate what is known about interven­
tion by the uninformed trader, then a systematic
difference between actual and reported interven­
tion implies a systematic difference in knowledge
among market participants. However, it is not
clear how much time passes before all market
participants learn of the intervention, or even if
they ever obtain accurate information short of
the official release one year later by U.S. authori­
ties. In addition, it is unclear if the newspaper re­
ports are written during the course of the day
 and are thus affected by changing and uncertain


views about intervention activity, or whether
they represent a presumably more accurate,
end-of-day assessment.
We know of only three previous comparisons
of actual and reported U.S. intervention data.
Klein (1993) uses multinomial logit analysis to
calculate the probability that intervention is re­
ported, conditional on the size of the interven­
tion. He estimates that, without conditioning on
size, the probability that actual intervention is
reported is 72 percent, and the probability that
reported intervention actually occurred is 88
percent. He also shows that newspaper reports
are more likely if the intervention is relatively
large. Dominguez (1992) examines the impacts
of reported and “secret” intervention on the
volatility of the DM/U.S. dollar exchange rate.
She assumes that actual intervention not re­
ported in the newspapers is “secret.” No signifi­
cant difference is seen between the impacts of
the two categories of intervention on volatility.
Dominguez and Frankel (1993) tabulate actual
and reported interventions by the United States
and Germany from November 1982 through
October 1989. The accuracy of newspaper re­
ports varied across different time periods. For
example, while all 22 U.S. interventions in the
period September through November 1985
were reported, only 73 percent of interven­
tions from March 1989 through October 1989
appeared in the print media.5
We make two contributions to the literature
on central bank intervention. First, we construct
a comprehensive data set from newspaper re­
ports of central bank intervention for the period
January 2, 1985 to October 11, 1991. This data set
improves on those constructed by other research­
ers by quantifying qualitative reports (such as
“small” intervention) rather than disregarding
them. Second, we test for the existence of sys­
tematic components in the differences between

■

2 A consensus of the literature is that if sterilized intervention mat­
ters at all, it does so because it signals a change in information about
monetary policy.

■

3 Still others have 1) constructed monthly numbers intended to
capture the shift in international portfolios due to intervention (for exam­
ple, Ghosh [1992]), 2) attempted to define intervention in terms of the
monetary authorities’ balance sheets (see Danker et al. [1987]), or 3)
used measures of central banks’ foreign reserves (for example, Glick and
Hutchison [1992] and Watanabe [1992]).

■

4 However, the market sometimes seems to make guesses that con­
fuse intervention operations with correspondent transactions.

■

5 Dominguez (1992) and Dominguez and Frankel (1993) utilize re­
ports of intervention from The London Financial Times, The New York
Times, and The Wall Street Journal. Klein (1993) uses the first two sources.

27

actual and reported intervention, calculating
these differences using either dummy variables
or numerical magnitudes. We also either in­
clude “rumors” in the reported series or dis­
card them. With few exceptions, we find that
there are systematic components; that is, the
differences are serially conelated.

II. Data
Actual
The Board of Governors of the Federal Reserve
System provided us with time series of U.S. net
daily dollar transactions from January 1985 to Oc­
tober 1991. All data are in dollars, representing
the actual net dollar purchases (sales) rather than
dollar equivalents that have been translated into
dollars via application of the exchange rate.6
These data are now publicly available, with a
one-year lag, from the Board of Governors. We
report the results of our analyses with three
categories of intervention: U.S. intervention visà-vis unspecified cunencies carried out in
terms of U.S. dollars, U.S. intervention vis-a-vis
the DM, and U.S. intervention vis-a-vis the yen.
Using these data, we created dummy vari­
ables, each of which equals +1 for positive net
dollar purchases, -1 for negative net dollar pur­
chases (positive sales), and 0 if the country did
not intervene (its net dollar transaction was 0).

Newspaper Reports
After having searched The Wall StreetJournal,
The Neu> York Times, and The Financial Times,
we ultimately decided to record the daily press
reports of intervention from the foreign exchange
column of The Wall StreetJournal.7 We recorded
all mentions of intervention that were indicated
as pertaining to the previous day or previous
business day. Thus, if there was first mention of
intervention a week after its occunence, we do
not record it, on the presumption that it would
not have been known by the market at the time.
As in the case with the actual data, for each
category of intervention, a buy/sell variable
was created to indicate whether a country was
a net buyer or seller of dollars. It equals +1 if
the country bought dollars, -1 if it sold dollars,
and 0 if it did not intervene. To correspond to
the way in which the actual intervention data
were constructed, we documented U.S. interven­
tion in the DM/dollar and yen/dollar markets. A
buy/sell variable was constructed for each mar­


ket, indicating whether the United States bought
(+1) or sold (-1) dollars. Thus, reported U.S. in­
tervention in each of these two markets is re­
corded in two places. For example, if the United
States was reported to be buying yen, we would
record this under the United States selling dol­
lars vis-a-vis the yen, and also in the (overall)
U.S. selling category described previously (and
denoted as U.S. vs. $U.S. in the tables). For all
groups, we recorded the size of the interven­
tion if given. This includes qualitative terms
such as small, moderate, and large, as well as
dollar magnitudes when given.
After all data were recorded, we calculated
the minimum, median, and maximum of the re­
ported dollar magnitudes for each U.S. inter­
vention variable when such magnitudes were
reported in the newspaper. We substituted for
qualitative terms. For terms indicating “small,”
“light,” or “token,” we used the minimum for
the particular category of intervention. For
“modest” or “moderate,” we substituted the me­
dian. For “large” or “heavy,” we substituted the
maximum. If no indication of size was given,
we used the median. For example, if the
United States was reported to be intervening
heavily against the yen, we would substitute
the maximum of all numeric reports of the
United States buying or selling dollars against
the yen. We then created a net transaction vari­
able for each category by multiplying the
buy/sell dummy variable by that amount. This
variable is comparable to the actual net inter­
vention variable. The minimums, maximums,
and medians for all of the reported intervention
variables are provided in table 1.
We also recorded specific mention of rumors.8
For a given country A, two types of rumors are
recorded: 1) whether country A intervened on its
own behalf, and 2) whether country A inter­
vened on behalf of country B (or whether coun­
try B intervened on behalf of country A). In the
white noise tests that we describe below, we
either disregard the rumors (treat them as being
nonreports) or count them (treat them the same
as other reports). The details of our treatment of
rumors and “on behalf o f” transactions are de­
scribed in the appendix.

■

6 Such a procedure would embed simultaneity into any sub­
sequent analysis of the relation between intervention and exchange rates.

■

7 This source is the most consistent of the three. While the use of
only one source may seem to make our series less comprehensive than it
would otherwise be, the amount of information that we obtain from this
news report is greater. In addition, we avoid having to determine how to
code reports when disparities arise among different sources.

■ 8 Thus, an erroneous report is not the same as an erroneous rumor.

y
T A B L E

1

III. White
Noise Tests

M in im u m , M e d ia n , and M a xim u m
for the S ize of Reported Intervention
(m illio ns of U .S . dollars)
Minimum

U.S. vs. $U.S.
U.S. vs. DM
U.S. vs. Yen

Median

Maximum

35.00

150.00

600.00

60.00

1 1 8 .3 3
1 4 3 .7 5

250.00

50.00

200.00

SOURCE: Authors’ calculations based on newspaper reports from January 2,
1985 to December 31, 1991.

B 0 X

1

Calculations of the W hite
N oise Te st Statistics

The two test statistics utilized in this article are those calcu­
lated by the SAS/ETS routine SPECTRA. They are the Kappa
(K ) statistic suggested by Fisher (1929) and the KolmogorovSmirnov (K-S) statistics suggested by Bartlett (1966). Fuller
(1976) presents their formulas as follows:

k= 1
K - S = maximum absolute difference of Ck , the cumulative
distribution function of a uniform random variable, where
m
k
C*= [ X
j= 1

X 4<<V'
./= 1

In(L) is the largest periodogram of a sample of m periodogram
ordinates with two degrees of freedom. Here, co indicates fre­
quency, with m - ( n —l)/2 and n being the number of
observations.
In both K and K -S, the periodogram is being used to
search for periodicities of unspecified form.3 Fuller (1976), p.
282, states that “for many nonnormal processes we may treat
the periodogram ordinates as multiples of chi-squared random
variables.” He further discusses how this assumption helps to
motivate the formulas given above. However, as we note in the
text, the peculiar nature of the data here requires us to qualify
our application of these test statistics to our data and to con­
sider alternate sample periods and alternate calculations of the
series. Fuller (1976), p. 284, gives the distribution of K, and
Bimbaum (1952) gives the distribution of K - S.
a. The concept of a periodogram is detailed in Fuller (1976), p. 275.




The white noise tests focus on the U.S. inter­
vention categories. For each reported intervention
variable, we vary the series along two dimen­
sions: First, we either count all rumors (about
whether there was intervention or rumored “on
behalf o f” intervention) or discount all rumors.9
Second, we use either numerical values or dum­
my variables. The use of dummy variables may
help to ameliorate some problems discussed
below regarding the appropriate use of our statis­
tical technique.
Although we could see if errors in reports
of intervention were of economic significance
by comparing the impacts of actual and re­
ported intervention on exchange rates, that pro­
cedure would require us to specify a model of
the interaction between intervention and ex­
change rates. Given the multiplicity of frame­
works used to study intervention, we elected
to utilize a technique that is not model-specific:
testing for whether the differences between re­
ported and actual intervention are white noise.
A time series is white noise if it has a mean
value equal to zero and if observations are seri­
ally uncorrelated.
The two statistics we report below are those
of the Kolmogorov-Smirnov and Kappa tests,
provided by the SAS/ETS (1990) version 6 rou­
tine SPECTRA. A detailed discussion of these
tests is found in Fuller (1976), pp. 282-85. The
exact calculations are described in box 1. In
our application of the tests, a finding that a se­
ries is not white noise implies that the series
contains serial correlation rather than that it
lacks a nonzero average.10 However, there are
some limitations as to how one can interpret
these test results.
First, the interpretation of the enor equaling
zero is ambiguous because it does so whenever
1) there was no intervention and no intervention
was reported, and 2) there was intervention that
was reported accurately. That this ambiguity is
not a desirable characteristic of our procedure
can be seen by comparing three scenarios. In one

■

9 As an example, consider a report that “the Federal Reserve pur­
chased 100 million yen, rumored to be on behalf of the Bank of Japan."
In a series that counts rumors, this would be entered as a purchase of yen
(sale of dollars) by the Japanese, while in the “no rumors'' series, it
would count as a U.S. purchase of yen.
■

10 Utilizing the ADJMEAN option in the SPECTRA routine sets the
average of the series to equal zero.

29

TABLE

2 A

Descriptive Statistics for Actual,
Reported, and Rumored Intervention:
Full Sample Period
N u m b e r of
Occurrences

Average
Size

Total

Buying

Selling

Buying

Selling

294
203
185

98
61
66

196
142
119

160.34
111.83
134.73

177.74
141.21
124.25

184
38
37

52
6
12

132
32
25

148.08
140.28
131.25

148.56
108.64
137.25

38
4
3

16

22
3
2

142.81
118.33
143.75

140.68
98.89
143.75

Actual intervention

U.S. vs. $U.S.
U.S. vs. DM
U.S. vs. Yen
Reported intervention

U.S. vs. $U.S.
U.S. vs. DM
U.S. vs. Yen
R u m o r e d intervention

U.S. vs. $U.S.
U.S. vs. DM
U.S. vs. Yen
Errors in Reported
Intervention

Total

1
1

Actual but Reported but
Not Reported Not Actual

Reported intervention

U.S. vs. $U.S.
U.S. vs. DM
U.S. vs. Yen

160
171
158

135
168
153

25
3
5

R u m o r e d intervention

U.S. vs. $U.S.
U.S. vs. DM
U.S. vs. Yen

24
4
2

Categories of intervention:
U.S. vs. $U.S.: U.S. intervention vis-à-vis unspecified currencies, carried out
in terms o f U.S. dollars.
U.S. vs. DM: U.S. purchases or sales o f DM in terms o f U.S. dollars.
U.S. vs. Yen: U.S. purchases or sales of yen in terms of U.S. dollars.
NOTE: “Buying” and “Selling” columns are in terms o f purchases and sales
of millions o f U.S. dollars.
SOURCE: Authors’ calculations.

case, imagine a typical day in the midst of a
long period in which there was no interven­
tion and no reason to expect intervention. In
the second case, imagine that the newspapers cor­
rectly report the cessation of intervention at the
end of a period of turbulent markets and frequent
intervention. In the third case, assume that a non­
zero amount of intervention is conectly reported.
In all three cases, the error is zero, although differ­
ent information is provided in each case.11
We hope to ameliorate the impact of this
factor on our result by varying the data in two




ways. First, we split the sample in half to con­
trol in part for changes in the frequency and
patterns of intervention. Second, we calculate the
enors using both dummy variables and numeric
variables. Using dummy variables will reduce the
number of enors if the newspapers seldom cor­
rectly report the amount of intervention.
Another limitation to our procedure is that
our data may violate the maintained hypothesis
that they are generated by a continuous random
variable. Intervention either takes the value of
zero (the vast majority of days) or jumps to a
number of the magnitude of 100 (100 million
U.S. dollars). Here again, we hope that by using
dummy variables, which exhibit smaller jumps,
we reduce the impact of such discontinuities.

IV. Intervention
Data and Errors
Tables 2A-2C describe the actual intervention
data, the reports of intervention, and rumored
interventions.12 The first line, “U.S. vs. $U.S.,” de­
notes U.S. purchases or sales of unspecified cur­
rencies. This includes the number of days that
the United States intervened in all cunencies, in­
cluding the DM and yen, as indicated on the
next two lines.13 We use this measure in our as­
sessment of the overall accuracy of reports about
U.S. intervention, since newspaper reports often
do not specify the foreign cunency in which the
United States is intervening.14
In table 2A, we see that there were 294 actual
U.S. interventions for the full sample period, 184
reports of intervention, and 38 rumors of inter­
vention. Thus, at most, 76 percent of interven­
tions were mentioned in the newspaper ([184 +
38] 7294 = 0.76). At the bottom of the table, we

■

11 This problem would be ameliorated if we were able to model
the joint process governing the intervention/exchange-rate interaction.
This process presumably will yield an expected intervention variable and
in turn will specify the significance of errors in reported intervention on
the exchange rate.

■

12 We compiled many more categories of reports than are ana­
lyzed in the tables. Our comparisons were restricted to those series for
which we had actual intervention data.
■ 13 Note that the United States sometimes intervened with more
than one currency within one day.
■

14 The official data are In dollars, so in our comparison of re­
ported and actual intervention, we have restricted ourselves to reports of
dollar intervention. Fortunately, when reports specify amounts, they indi­
cate the dollar magnitudes, eliminating the need to convert via applica­
tion of the exchange rate.

TABLE

2 B

Descriptive Statistics for Actual,
Reported, and Rumored Intervention:
January 2 , 1985-May 20,1988
N u m b e r of
Occurrences

Average
Size

Total

Buying

Selling

Buying

Selling

100
60
78

61
33
53

39
27
25

176.68
116.83
130.60

119.99
115.41
62.53

55
4
8

33
2
8

22
2
0

153.18
118.33
132.03

138.18
109.17
0

20
2
0

12
0
0

8
2
0

140.42
0
0

124.38
89.17
0

Actual intervention

U.S. vs. $U.S.
U.S. vs. DM
U.S. vs. Yen
Reported intervention

U.S. vs. $U.S.
U.S. vs. DM
U.S. vs. Yen
R u m o r e d intervention

U.S. vs. $U.S.
U.S. vs. DM
U.S. vs. Yen
Errors in Reported
Intervention

Total

Reported intervention

U.S. vs. $U.S.
U.S. vs. DM
U.S. vs. Yen

65
56
72

Actual but Reported but
Not Reported Not Actual

55
56
71

10
0
1

R u m o r e d intervention

U.S. vs. $U.S.
U.S. vs. DM
U.S. vs Yen

13
2
0

Tables 2B and 2C present similar information
for the two sample halves.15 Almost twice as
much actual intervention in the U.S. vs. $U.S.
category occurred in the second half of the
sample as in the first. In the U.S. vs. DM cate­
gory, intervention was much heavier in the sec-,
ond half of the sample, as the United States
shifted to buying DM (selling dollars). Reports
of intervention appear to capture these pat­
terns. However, in the U.S. vs. DM and U.S. vs.
yen categories, occurrences of reports fall far
short of the number of actual interventions.
This finding stands in sharp contrast to the find­
ings in the previous paragraph regarding the
U.S. vs. $U.S. category.
Table 3 presents the results of the white noise
tests, separated by whether the reported series
omits or includes rumors and by whether we use
numeric or dummy variables.16 All of the white
noise tests were performed on both the full sam­
ple and on each half of the sample. Splitting the
sample is an attempt to see if the results are sen­
sitive to choosing sample periods that vary re­
garding either the intensity of intervention or its
pattern. In this case, intervention activity was
heavier during the second subsample.
Generally, with both tests, the full sample and
split samples reject the hypothesis that the time
series of enors are white noise. Thus, there are
systematic components to the differences be­
tween actual and reported intervention. For dum­
my variables, we reject the hypothesis of white
noise in all cases.

Categories of intervention:
U.S. vs. $U.S.: U.S. intervention vis-à-vis unspecified currencies, carried out
in terms o f U.S. dollars.
U.S. vs. DM: U.S. purchases or sales o f DM in terms o f U.S. dollars.
U.S. vs. Yen: U.S. purchases or sales o f yen in terms o f U.S. dollars.
NOTE: “Buying” and “Selling” columns are in terms o f purchases and sales
o f millions o f U.S. dollars.
SOURCE: Authors’ calculations.

report errors, either from comparing actual and
reported or from comparing actual and ru­
mored intervention. O n the one hand, there
were 135 days on which intervention occuned
but was not reported, implying that it was re­
ported only 54 percent of the time. On the
other hand, only 25 of the 184 reports were er­
roneous (86 percent accuracy). In the case of
rumors, however, most were in enor: For 24
of 38 rumors, there was no actual intervention.




V. Summary
Newspaper reports of central bank intervention
are often used as if they are interchangeable with
actual intervention data. Except in rare cases, ac­
tual data have become available only recently for
the United States, with a one-year lag. Here we
describe detailed time series culled from The Wall
StreetJournal and compare them to actual inter­
vention data. We quantify qualitative reports of
intervention for all of the series. To the best of

■

15 We have also compiled analogous tables for the subperiods
January 2—December 31,1985; January 1,1986—February 20,1987;
February 21,1987—February 19,1990; and February 20,1990—October
11,1991. These tables are available from the authors and facilitate com­
parison with previous research on the effectiveness of intervention over
various subsamples.
■

16 Rumored intervention includes rumors about both “own" and
“on behalf of” intervention.

31

TABLE

2 C

Descriptive Statistics for Actual,
Reported, and Rumored Intervention:
May 23,1988—October 11,1991
N u m b e r of
Occurrences

Average
Size

Total

Buying

Selling Buying

194
143
107

37
28
13

157
115
94

133-41
105.93
151.54

192.09
147.27
140.66

129
34
29

19
4
4

110
30
25

139.21
151.25
129.69

150.64
108.61
137.25

18
2
3

4
1
1

14
1
2

150.00
118.33
143.75

150.00
118.33
143.75

Selling

Actual intervention

U.S. vs. $U.S.
U.S. vs. DM
U.S. vs. Yen
Reported intervention

U.S. vs. $U.S.
U.S. vs. DM
U.S. vs. Yen
R u m o r e d intervention

U.S. vs. $U.S.
U.S. vs. DM
U.S. vs. Yen
Errors in Reported
Intervention

Total

Actual but Reported but
Not Reported Not Actual

Reported intervention

U.S. vs. $U.S.
U.S. vs. DM
U.S. vs. Yen

95
115
86

80
112
82

15
3
4

R u m o r e d intervention

U.S. vs. $U.S.
U.S. vs. DM
U.S. vs. Yen

11
2
2

Categories of intervention:
U.S. vs. $U.S.: U.S. intervention vis-à-vis unspecified currencies, carried out
in terms o f U.S. dollars.
U.S. vs. DM: U.S. purchases or sales of DM in terms o f U.S. dollars.
U.S. vs. Yen: U.S. purchases or sales o f yen in terms of U.S. dollars.
NOTE: “Buying” and “Selling” columns are in terms o f purchases and sales
of millions of U.S. dollars.
SOURCE: Authors’ calculations.




our knowledge, this is the first such treatment
of qualitative reports.
Whether we examine numeric values or dum­
my variables, count or discount rumors, or split
the sample, we find that there usually are system­
atic components in the differences between the
actual and reported intervention series. While the
economic significance of any such differences is
unclear, we believe that these findings may have
important implications for understanding the sig­
naling mechanism of intervention. If the newspa­
per reports reflect the markets’ final assessment
of intervention activity, then reporting enors im­
ply that the market (with the exception of the
intervention counterparties) is misinformed and
that intervention is unlikely to signal monetary
policy accurately.

32

T A B L E

3

White Noise Tests for Errors
in Reported Intervention
First Half:
January 2, 1985M a y 20, 1988

Full Sample
Variable

Second Half:
M a y 23, 1988October 11, 1991

K

K-S

N

K

K-S

N

K

K-S

N

35.3842a
39.7927a

0.26563
0.4l42a

884
884

10.2977b
20.31093

0.19363
0.36733

442
442

27.51593
30.16263

0.29163
0.43673

442
442

33.68173
43.4345a

0.25883
0.4l20a

884
884

8.6115
20.20563

0.18343
0.36773

442
442

27.25513
32.7564a

0.28973
0.43193

442
442

55.60833
58.98623

0.3180a
0.3472a

884
884

22.20643
39.45403

0.27903
0.38143

442
442

35.7343a
27.4339a

0.33403
0.30693

442
442

53.28133
62.6117a

0.3035a
0.34793

884
884

20.7967s
39.14643

0.25503
0.38663

442
442

34.99083
32.41263

0.32753
0.30133

442
442

N o R umors

U.S. vs. DM
U.S. vs. Yen
With Rumors

U.S. vs. DM
U.S. vs. Yen
D u m m y Variables
N o Rumors

U.S. vs. DM
U.S. vs. Yen
With Rumors

U.S. vs. DM
U.S. vs. Yen
Categories of intervention:

U.S. vs. DM: U.S. purchases or sales o f DM in terms o f U.S. dollars.
U.S. vs. Yen: U.S. purchases or sales o f yen in terms o f U.S. dollars.
NOTE: N = num ber of observations. For K and K-S, see box 1.

a. Significant at the 5 percent level.
b. Significant at the 10 percent level.
SOURCE: Authors’ calculations.

Appendix
Treatment of
Rumors and
“On Behalf of”
Intervention
We created two sets of variables from the re­
ported intervention data: The first treats all ru­
mors as true, and the second treats all rumors
as false. The first step in the creation of both
data sets was the formulation of the net dollar
transaction variables for each category of inter­
vention. For the U.S. intervention categories,
this variable is equal to the amount variable,
which is always non-negative, multiplied by
the buy/sell dummy variable.
To compare reported and actual interven­
tion data, we must transfer intervention that
was reported as being on behalf of another
country to that particular country. For exam­
ple, if the United States actually purchased yen




on behalf of Japan, the data that we receive
from the Federal Reserve’s Board of Governors
will attribute such intervention to Japan rather
than to the United States. To accomplish this
adjustment, we created two variables for each
country, FORI and FOR2. FORI equals 1 if the
country intervened on behalf of another coun­
try. FOR2 equals the number of countries re­
ported to be intervening on its behalf.
There is also is a third dummy variable,
FORRUMOR, which equals 1 if intervention by
the country was rumored to be on behalf of an­
other country. To create the data set in which
all rumors are considered true (false), we trans­
ferred (did not transfer) all of the intervention
that was rumored to be on behalf of another
country. Additional details regarding these pro­
cedures are available from the authors.

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Economic Review

H

1992 Quarter 4

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October 15, 1992

T h e Importance of Structure
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Federal Credit and Insurance
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H o m e Mortgage Lending by the
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