Full text of Economic Review (Federal Reserve Bank of Cleveland) : Fall 1984

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

Economic
Review
Federal Reserve Bank
of Cleveland
Fall 1984




R isk in Large-Dollar
Transfer Systems .................................... 2

Settlement risk is the risk that a bank will
be unable to repay other banks for daylight
credit, meaning the net amount (payments
minus receipts) owed for a day’s transactions
on a payment system. Payments volumes have
been growing rapidly on Fedwire and even
more rapidly on privately operated systems.
This growth highlights the need for man­
agement of settlement risk exposure. One
vital ingredient of settlement risk manage­
ment is the ability to control daylight credit
extended or used by a bank across the various
payment systems. Equally vital is the need
for banks and their customers to recognize
who is at risk in making and receiving largedollar payments.
Sources of Change in Rates of
Return on Capital: 1952-82 .............

17

This article reconsiders the problem of a de­
clining rate of return on capital. The rate of
return for noncorporate businesses and
corporations fell after 1965. A model designed
to examine sources of the decline indicates
that the major forces at work were inflation­
ary distortions in the relative price of capital
and falling capital productivity. Other con­
tributors were a one-time-only price-cost dis­
tortion in the late 1960s and periodic cyclical
weakness. None of these effects, perhaps ex­
cepting falling capital productivity, can be
considered a permanent or long-term erosion
in the profitability of capital.
Economic Review

is published quarterly by the
Research Department of the Federal Reserve Bank
of Cleveland, P.O. Box 6387, Cleveland, OH 44101.
Telephone: 216/579-2000.
Editor: Pat Wren. Assistant editor: Meredith Holmes.
Design: Jamie Feldman. Typesetting: Lucy Balazek.

Economic Review

Opinions stated in
are those of
the authors and not necessarily those of the Fed­
eral Reserve Bank of Cleveland or of the Board of
Governors of the Federal Reserve System.
Material may be reprinted provided that the source
is credited. Please send copies of reprinted materi­
als to the editor.
ISSN 0013-0281

A n assistant vice
president with the
Federal Reserve
Bank of Cleveland,
the author is re­
sponsible for Fed­
eral Open Market
Committee briefings
and other monetary
policy advice. The
author has benefited
from the comments
of Donald Hester,
Ernest Patrikis,
David Humphrey,
James Hoehn,
Roger Hinderlitcr,
Kim Kowalewski,
John Carlson, and
Mark Sniderman.

Risk in Large-Dollar
Transfer Systems
by E.J. Stevens

Risk in large-dollar transfer systems was an
unfamiliar topic until quite recently. Even
today, people who are not banking profession­
als probably have little notion of what these
systems are, what risks they involve, and why
those risks should be investigated.
In a nutshell, large-dollar transfer sys­
tems in the United States are telecommuni­
cations networks (currently including Fed wire,
CHIPS, CashWire, and CHESS) almost entirely
dedicated to same-day handling of multimil­
lion dollar payments among banks (see box 1).
These payments may be for a bank itself, as
it buys and sells money, or for the accounts of
the bank’s customers, especially financial
institutions, active in world money and capi­
tal markets, and nonfinancial corporations.
The risk being discussed is settlement risk:
that, at the end of a day, a participating bank
will not be able to pay the net amount (pay­
ments minus receipts) it owes to the other
banks on one of the systems for that day’s
transactions. How to deal with this risk may
be viewed differently by banks, their custom­
ers, and the Federal Reserve System. NevBox 1

Large-Dollar Transfer Systems

CashWire is operated by the Payment and Administra­
tive Communication Corporation owned by a consortium
of 180 U.S. banks. Service is currently provided to 17 of
these banks, which send approximately 350 payments
daily with an average value of about $700,000.
CHESS, or Clearing House Electronic Settlement Sys­
tem, is operated by the Chicago Clearing House Associa­
tion with service available to members, who must be in
the 7th Federal Reserve District. Service is currently pro­
vided to six banks, which send approximately 450 mes­
sages daily with an average value of about $1.0 million.
CHIPS, or Clearing House Interbank Payments System,
is operated by the New York (City) Clearing House Asso­
ciation with service available to its members. Service is
currently provided to over 120 institutions, which send
approximately 75,000 payments daily with an average
value of about $3.0 million.
Fedwire is operated by the 12 Federal Reserve Banks and
their branches with service available to any depository
institution with an account relationship with a Reserve
Bank. Service is currently provided to over 7,000 insti­
tutions, which send approximately 150,000 payments
daily with an average value of about $2.4 million.

2

Federal Reserve Bank of Cleveland




1. For example,
see “Risks in Elec­
tronic Payments
Systems, ’’ Report
of the Risk Task
Force, Association
of Reserve City Bank­
ers, October 1983.
. See Board of Gov­
ernors of the Fed­
eral Reserve System,
“Proposals to Re­
duce Risk on LargeDollar Transfer
Systems,” Docket
No. R-0515.

2

3. Automated Fedwire payments, for
example, involve
a fee of 55C to each
of the sending and
receiving banks.
The banks them­
selves would have
to charge substan­
tially more than this
to cover the 55C fee
plus inhouse costs.
Non-pecuniary
costs may loom just
as large. Specifically,
it is sometimes ar­
gued that small-value
wire transfers are
more likely to go
astray. A bank that
fails to receive a
transfer, standing
to gain only the over­
night return on the
value of the payment,
has little incentive
to initiate a search
fora m issing$ 1,000
payment; other par­
ties to the transaction
may be relied on to
do the job. The incen­
tive is a thousand­
fold greater on a
million-dollar trans­
fer, which is there­
fore likely, if lost, to
be sought assiduously
until found.

3

ertheless, there is a common concern that the
risk be recognized and methods of risk man­
agement be understood.1To that end, the Board
of Governors of the Federal Reserve System
has formally asked for industry comment on
a number of proposed methods of risk man­
agement and control.2
The purpose of this article is to examine the
concept of settlement risk (section II). This
requires, in addition, a background description
of the institutional basis for making largedollar payments in the United States (section I)
and an explanation of why concern about set­
tlement risk has only recently come to the
fore (section III).

I. Large-Dollar Payments
and Settlement
Payment Systems
The nature of large-dollar transfer systems
in the United States is best understood by con­
trasting them with small-dollar systems on
the one hand and, on the other, with nonpay­
ment message systems. Small-dollar transfer
systems—cash, checks, automated clearing­
houses (e.g., for direct deposit of Social Secu­
rity or salary payments)—are familiar to most
people. Whereas an average cash transaction
is for considerably less than $100, and even the
average check (including business checks)
is for less than $1,000, the average wire trans­
fer (the generic name for payments made on
large-dollar systems) is in the million-dollar
range. This is not to imply that wire transfers
are somehow restricted to such large sums:
small payments can be made as readily as
large. However, routine wire transfer of small
payments is usually un-economic because the
value of gaining interest for a day or so by
completing a same-day payment is not worth
the additional cost of a wire transfer.3
Wire transfers typically are completed on
a telecommunications system, although tele­

Economic Review • Fall 1984




phone and other devices can be employed.
Fledgling debit card and home banking sys­
tems exist, some automated clearinghouse
transactions are now made on a computer-tocomputer basis, and electronic check collec­
tion is contemplated. Nonetheless, small pay­
ments typically are not completed on tele­
communications systems.
Large-dollar transfer systems should also
be contrasted to inter-bank message systems
that, standing alone, do not necessarily effect
payments. SWIFT and Bankwire II, for exam­
ple, are technologically sophisticated tele­
communications systems; however, they are
only capable of conveying messages. Those
messages may be—frequently are—instruc­
tions authorizing a bank to remove funds from
the account of one depositor and place them
in the account of another. When both deposi­
tors maintain accounts at the bank receiving
the message, only follow-up internal book­
keeping is required to complete the process.
However, if the account to which the payment
is directed is at any other bank, then no pay­
ment has been made until a follow-up inter­
bank payment has been initiated via one of
the large-dollar transfer systems. In this sense
SWIFT and Bankwire II, despite restricted
access, standardized formats, and a sophisti­
cated telecommunications vehicle for trans­
mission, are closer to telex, telephone, and
mail service than to large- or small-dollar
transfer systems. What distinguishes largedollar transfer systems from these message
systems is the ability of one participant to
transfer cash in the form of immediately
available bank balances to any other partici­
pant by a single message. In the jargon of
payments, these large-dollar transfer systems
make payments because they include settle­
ment—the irrevocable transfer of ownership
of bank balances from one participant to
another. This transfer is analogous to pay­
ment in cash in the form of legal tender cur­
rency and is brought about by the transfer of
deposit balances at Federal Reserve Banks
from the account of the paying bank to that
of the receiving bank.

Settlement Risk
The risk that is the major concern in largedollar transfer systems is settlement risk,
reflecting the possibility that the recipient’s
bank will not be paid by the payor’s bank.
This risk should be distinguished from the
more familiar risks confronted in ordinary
payments, including the simple risk of non­
payment of a debt and the risk of being paid
with a bad check (see box 2). Settlement
risk is the risk that a bank, despite a paying
customer’s adequate balance or credit line,
will be unable to cover payments it has initi­
ated on various payment systems during the
banking day.
Box 2

Three K inds of R isk

A and B are banks.
A' and B' are customers of those banks.
1. Nonpayment A'owes money, but may fail to do any­
thing about it. B' is exposed to a credit risk: A' may be
a deadbeat.
2. Bad Check: A' pays B' by check, but has insufficient
funds in his account with A to cover the check. A'gives
the check to B\ who deposits it in B. B sends the check
to A for payment, receiving provisional credit in B’s ac­
count at the Federal Reserve Bank, where A's account
is provisionally debited. A then finds A'has insufficient
funds and returns the check to B via the Federal Reserve,
which reverses the previous entries.
3. Settlement Risk: Upon instruction from A\ A wires
funds to B for credit to B'. At the end of the day, A has
insufficient funds to pay B the amount it owes for this
(and other) payments, even after subtracting other
payments made by B to A.

Federal Reserve Bank of Cleveland



The circumstances under which this might
happen are extreme. Inability of a bank to
settle would be the symptom not just of a
bank failure but of an unexpected bank fail­
ure. Indeed, it might be argued that, at least
for very large banks, such an event could
not happen. After all, in the event of trouble,
wouldn’t the supervisory authorities be sum­
moned immediately to arrange a last-resort
loan from its Reserve Bank? In this way, every
other participant in a large-dollar transfer
system would be paid; no settlement failure
would occur. This argument ignores two vital
matters. First, as explained in the next para­
graph, settlement risk would not disappear;
it would simply be transformed into credit risk
of the Federal Reserve or other creditors of
the troubled institution. Second, as explained
in section II, the supervisory authorities and
the Federal Reserve might be well-advised
to adopt a “hands-off” policy in the case of
an incipient and isolated settlement failure,
allowing other participants in a network
to absorb the losses occasioned by settlement
failure. Settlement risk is, therefore, the risk
that no other bank, supervisory authority,
or government lender of last resort will lend
enough to a bank to cover its debit position
vis-a-vis another institution before the end
of the day.
Exposure to settlement risk may be borne by
the recipient of a payment or by his bank,
depending on which payment system is util­
ized. Settlement risk for Fedwire payments is
borne by the Reserve Banks, which stand as
the bankers (B in box 2) for the depository
institutions receiving payments (B' in box 2).
Notification of a payment sent by a Reserve
Bank to a recipient bank is an irrevocable
notice that immediately available funds have
been credited to its account. If the Reserve
Bank discovers at the end of the day that the
paying bank has insufficient funds to cover
its Fedwire payments, the Reserve Bank can­

4. These matters are
spelled out in the
Federal Reserve’s
Regulation / Sec­
tion 210.36, Final
Payment and Use
of Funds: (a) Final
Payment. A transfer
item is finally paid
when the transfer­
ee’s Reserve Bank
sends the transfer
item or sends or tele­
phones the advice of
credit for the item
to the transferee,
whichever occurs
first, (b) Right to Use
Funds. Credit given
by a Reserve Bank
for a transfer of
funds becomes avail­
able for use when
the transfer item is
finally paid, subject
to the Reserve Bank s
right to apply the
transferred funds to
an obligation owed
to it by the trans­
feree. See “Regula­
tion J: Collection of
Checks and Other
Items and Wire
Tra nsfers of Fu nds,
Federal Reserve
Regulatory Service,

vol. Ill, section 210,
as amended, effec­
tive April 2, 1984,
p. 7-043.

not recover the funds from the recipients.4
The location of settlement risk exposure in
CHIPS is different from Fedwire. This largedollar system is not a bank, but a clearing­
house with net settlement. Participating
banks receive notices of payment during the
day from each of the other banks and send
notices of payments to the other banks. The
clearinghouse records all of these payments,
but no transfer of assets between partici­
pants takes place. At day’s end, each bank
then is in a net debit or credit position with
respect to each other bank, reflecting the net
balance of payments to, relative to payments
from, each of those other banks. Of course,
the sum of all these bilateral net debit and
credit positions is always zero because what
each bank owes is what each other bank is
owed. This accounting identity makes clear
why settlement of the day’s payments can be
such a simple matter. Each bank in net debit
position with respect to the aggregate of all
other participants might pay what it owes into
a pool from which each bank in net credit
position could be paid. In this way 120 partic­
ipants would be able to settle 7,140 bilateral
positions [(120 X 119) -r- 2] with a total of only
120 payments, some into and some out of the
clearinghouse settlement account (see box 3).
The facts of CHIPS settlement are both
more and less simple than these few sen­
tences suggest. CHIPS participants include
both settling and non-settling banks. Non­
settling banks both send and receive pay­
ments in their own names. However, at the
end of the day, they pay or receive the net
balance due from or to them through one of
the settling banks rather than directly with
the settlement account at the Federal Reserve
Bank of New York. A settling bank agrees to
receive the net credits or pay the net debits
attributable both to its own activity as well as
to that of each of its non-settling respondents.
Settlement then proceeds in several steps at
the end of the day. First, net positions are

Economic Review • Fall 1984



reported so that each participant has an oppor­
tunity to verify all of its bilateral net debit
and credit positions and its aggregate net debit
or credit (“net net”) position. Then, settling
banks must indicate their readiness to settle,
before which they have had an opportunity
to confirm that their non-settling respondent
participants in debit positions either have
a sufficient balance with the settling bank, or
are able to borrow a sufficient amount from
the settling bank, to cover the debit. When all
settling banks have signaled their readiness
to settle, those in debit positions send the
amounts they owe from their Federal Reserve
Bank deposit accounts via Fedwire to the
CHIPS settlement account at the Federal Re­
serve Bank of New York. When all payments
are received, the balance in the settlement
account is dispersed via Fedwire to the Fed­
eral Reserve Bank deposit accounts of the
settling banks in credit positions.
Settlement risk in CHIPS, then, refers to
the possibility of two different kinds of failure
to pay. One would be the inability of a non­
settling participant to cover its debit position,
either by funding its account with the settling
bank or by a loan from that bank. The other
would be the inability of a settling bank to
fund its account at the Federal Reserve Bank.
Locating the risk of loss in these hypothet­
ical situations involves identifying how settle­
ment is handled if one of the participants is
unable to make settlement. CHIPS’ Rule 13
specifies the series of steps for operating under
such circumstances. First, more time can be
granted, in effect extending the end of the day
beyond the appointed settlement time (nor­
mally 5:45 pm). This extension may be granted
by the clearinghouse because a settling bank
notifies the clearinghouse of its unwilling­
ness to settle for one of the non-settling par-

5. Deletion of trans­
actions does not re­
lieve the participant
of its obligation
to make those pay­
ments, according to
Rule 13.

ticipants for whom it would otherwise be
obligated to settle, or because a settling bank
notifies the clearinghouse that it is unable
to cover its own debit position by settlement
time. The extra time would allow a non-settling
participant to seek funding and/or an alter­
native settling bank, or would allow a settling
participant to secure funds. If, despite extra
time, a participant is still unable to settle,
the day’s transactions of that participant
(both payments and receipts) can be deleted
from the settlement.5 This means that the
aggregate net debit or credit position of each
remaining participant will change by the
amount of its bilateral net credit or debit for
the day’s transactions with the deleted insti­
tution. The remaining participants might
then settle, if those with increased net debit
positions have or can acquire sufficient funds
to cover their new, larger settlement obliga­
tions. The deleted institution would then be­
come the legal quarry of a host of unhappy
customers, other banks and their customers,
the clearinghouse, and regulatory authorities.

Box 3 The Benefits of
a Net-Settlement System

Suppose 120 banks agree to send and receive payment
messages among themselves during the day and to settle
only the net amounts due to and due from one another
at the end of the day, using deposit balances at Reserve
Banks as the medium of settlement.
At the end of the day, each of the 120 banks either owes
or is owed by each of the 119 other banks. Thus, there
will be 7,140 (half of 120 X 119) pairs of net credit and
debit positions, or bilateral net positions, to be settled.
In the absence of a net-settlement system, settlement of
these 7,140 positions would involve a payment by each
of the debit position banks to each of the corresponding
credit position banks.
With a net-settlement agreement, settlement requires
only 120 payments, some into and some out of the set­
tlement account at a Reserve Bank. Those owing more
than they are owed (at least one bank) pay that “netnet” amount to the settlement account; those that are
owed more than they owe are paid that “net-net” amount
from the settlement account. When settlement is com­
plete, the settlement account is exhausted because the
sum of all banks’ positions is precisely zero: what each
bank owed was what another bank was owed.

6

Federal Reserve Bank of Cleveland




The possibility of deleting payments helps
to clarify the difference between provisional
and final payment. Payments made via inter­
bank net settlement networks for large-dollar
payments are provisional until settlement
is complete. This comes at the end of the day,
when funding of the settlement account by
net debit position banks is complete and pay­
ments have been sent from the settlement
account to the banks in net credit positions.
Between the morning opening of a network
and evening settlement, payments are provi­
sional in the sense that the receiving bank
may not actually receive credit to its deposit
account at a Reserve Bank. Those who use
the proceeds of such payments without any
other guarantee are exposed to the risk that
the payment will not become final because of
settlement failure.
Settlement risk is more narrowly focused in
CashWire and CHESS. All participants in
these systems are settling banks using their
own accounts at Reserve Banks to pay to
or receive from the settlement account. Also,
at least as an interim matter, all CashWire
participants guarantee irrevocable availabil­
ity of funds to their receiving customers. Set­
tlement risk is thus absorbed by the partic­
ipating banks in CashWire, while it is shared
with the customers of participating banks
in CHIPS.

II. The Nature of Risk Exposure
Bilateral Risk Exposure
Identifying how losses might be realized in
large-dollar transfer systems is not the same
as evaluating the extent of risk exposure of
any individual participant in those systems.
Bilateral settlement risk exposure may be
thought of as the expected value of the cost to
a participant of a settlement failure by a par­

6 . The discussion
here proceeds as
though credit is
being extended by
the receiving bank
to the paying bank ,
rather than to the
customers of the
receiving bank. This
initial presumption
is relaxed in the
next section.

ticular counterparty bank. Aggregate settle­
ment risk exposure of a bank is the sum of
the expected values of the cost of settlement
failure evaluated across all counterparties
in a large-dollar transfer system. Conceptually,
then, a bank would measure its bilateral set­
tlement risk exposure as the expected value of
the unrecoverable portion of its bilateral set­
tlement position (net credit) with respect to
the *th other bank. This risk exposure of one
bank to another, ignoring any interdependence
among all banks, has two ingredients.6 One
is the actual dollar value of the bilateral net
credit extended by B to the ith bank in a par­
ticular payment system during a day; the
other is the expected value of the percentage
of this position that will not be recovered.
Consider first the dollar value of the bilat­
eral net credit extended by B to i. This amount
will vary each day and during the day with
the ebb and flow of payments to and from one
another, and can be represented symbolic­
ally as $Bi.
Next, consider the unrecovered percen­
tage of the bilateral net credit extended by
one bank to another. That a bank is unable to
settle at the end of a day would impose a cost
on its net creditors in the form of interest
foregone on the unsettled position for the
period of time the position remained unset­
tled. Of course, this cost might be recovered,
in effect writing an ex post loan and then being
repaid, but costs of negotiating and litigation
would remain. Alternatively, if the bank had
failed, there might be some delay before its
obligations were settled, involving both admin­
istrative and waiting costs. Finally, the un­
settled position might turn out to be unrecov­
erable in part, in total, or (including litigation
and waiting) more than total.
All of this potential write-down is what
is imagined to underlie each participant’s esti­
mate or expectation of the percentage unre­
covered of each net bilateral credit position

Economic Review • Fall 1984




linking it to another bank. Further, it seems
plausible that these estimates are not made
with certainty, but are better imagined as
being distributed across a potentially wide
spectrum of values, ranging from just above
zero (complete recovery) to more than 100 per­
cent (no recovery plus costs of waiting and
litigation). The probability of any particular
percentage, j, actually being realized from
the ith bank could then be stated as A
whole spectrum of such probabilities of per­
centage unrecovered would exist, with their
distribution tightly clustered near zero for
counterparty banks of good repute and long
relationship, and less tightly clustered, more
evenly spread above zero for less reputable,
less well-known counterparties.
Combining the bilateral net credit position
and the probability of percentage unrecovered,
settlement-risk exposure of bank B to the
ith counterparty bank can be represented by
the weighted average of all possible outcomes,
E (X B i) =

j> 0

Lest this characterization of risk exposure
seem too remote from the real world, recognize
that something like this risk-exposure calcu­
lation must be employed by any bank that
makes loans. The expected return on a loan
must incorporate both the explicit yield and the
likelihood of costs on nonrepayment. In the
large-dollar transfer system case, there is credit
extended (the net bilateral credit position, $Bi)
but no explicit yield because the credit is to
be repaid before the end of the day and, with
few exceptions, interest is charged only on
loans with maturities of overnight or longer.
For this reason the net bilateral credit posi­
tion is often referred to as daylight credit
extended by B to i, or as Vs daylight over­
draft with B.

Sharing
Risk exposure of B to i is affected by some­
thing in addition to the bilateral credit posi­
tion and the creditworthiness of i as per­
ceived by B. This additional matter involves
the degree to which others share B ’s exposure
to i. The more widely shared an exposure is,
the better for B in two distinct ways. The
first would be the extent to which funds, $b
are at risk. As in a case in which B is receiv­
ing payments from i for the accounts of a num­
ber of customers, B ’s exposure is reduced to
the extent that its customers might both share
litigation and collection costs as well as bear
the burden of amounts that are ultimately
unrecoverable. In a more limited way, some
cost sharing might be possible among a num­
ber of banks all of whom were in net credit
position when i failed to settle.
The second way would skew the spectrum
of probabilities of percentage unrecovered
toward zero. More widespread sharing of
exposure may benefit B in that more numer­
ous sources of independent scrutiny of fs
creditworthiness may reduce the chances of
i s pursuing imprudent courses of action. This
is no more than the fooling-all-of-the-peopleall-of-the-time impossibility theorem at work.
In this application, the theorem reflects the
increasing likelihood that (true) adverse infor­
mation will become available to counterpar­
ties as the number of counterparties increases.
The power of information in constraining
behavior and reducing risk exposure depends
in part on who gets the information. A single
customer of a bank, receiving adverse infor­
mation about another bank from which pay­
ments might be received, can simply refuse to
do business with customers of the suspect
bank or request payment in some safer means.
While this may be a prudent course of action
for the payee, it has only limited power to
force constructive change in the suspect bank,
which may be able to ignore the qualms of

Federal Reserve Bank of Cleveland




one or a few isolated alarmists among its
many customers, only some of whom may
switch to a more sound bank. Less likely is
a bank to be able to ignore the qualms of one
or a few counterparty banks representing
the interests of many customers. Banks are
in a better position to profit from, and there­
fore would likely be more aggressive in seeking,
information about the creditworthiness of
counterparty banks. Similarly, the power
of information to constrain risky behavior is
likely to be greater when in the hands of a
bank than in the hands of a customer. It is the
credit judgments of other banks that provide
the foundation of a bank’s liquidity, deter­
mining its ability to obtain short-term fund­
ing in the interbank money market. Counter­
party banks would be more likely to maintain
a truly less risky posture, including smaller
aggregate daylight overdrafts, when other
banks have continuing daily incentive to dis­
cover their creditworthiness.

Systemic Risk
All of the foregoing discussion of risk expo­
sure implicitly has assumed that a settlement
failure is an isolated event; that losses because
of a settlement failure would be small enough
that banks could absorb the resulting unex­
pected loss of funds without themselves being
unable to settle. Upon investigation, this is
an overly strong assumption that ignores the
interdependence of participants in a payment
system and the resulting vulnerability of
many banks directly or indirectly to a single
counterparty’s failure to settle.
Vulnerability to counterparty failure re­
flects both the speed with which a bank
must gain access to cash and the likely scar­
city of cash. An unexpected settlement failure
would occur at the end of a day when most

banks have finished matching their sources
with uses of cash through purchases and sales
of funds in the money market. Unexpected
non-repayment of a daylight credit then
removes one expected source of cash, which
must be replaced before the close of Fedwire
prevents further transfers of cash that day.
Even though the Fedwire facility might be
kept open beyond the normal 6 pm close if there
were trouble, emergency financing arrange­
ments would have to be made in an hour or
so, or before the next morning.
Speedy access to cash might be sought in a
bank’s own balance at a Reserve Bank. This
would require no action, because the cash
already would be on deposit and, for reserve
requirement purposes, the unexpected drain
might be offset by larger cash holdings
over future days. However, for many of the
nation’s largest money center banks, the size
of daylight overdrafts is many times larger
than their own or any counterparty bank’s
normal overnight reserve deposit position.
For this reason, cash balances would be inad­
equate in preventing vulnerability to a coun­
terparty failure. If insufficient cash is avail­
able in the bank’s own account, then steps
might be taken to sell liquid assets. However,
many banks would have difficulty doing this
because liquid assets would already have been
serving as collateral for other purposes and
therefore be unavailable. Their alternative
would then be to borrow. Whether borrow­
ing or, in exceptional cases, selling unpledged
liquid assets, the challenge is both to find
other banks with the required amount of cash
as well as to convince them to make the cash
available. Which of these hurdles—finding
cash or acquiring it—would be the more trou­
blesome is a debatable matter, for neither
would be easy.
Finding banks with cash may be difficult,
given the limited stock of cash on which
the U.S. financial system operates. The rele­
vant concept of cash is, again, in the form of
deposit account balances at Federal Reserve
Banks (because they can be transferred via Fed­
wire before the end of the day). Vault cash
Economic Review • Fall 1984




is unlikely to help, being of limited amount,
cumbersome denomination, dispersed location,
and probably sealed in time-locked vaults.
Deposit balances at correspondent banks
would be useful to a single bank, but their
use would merely relocate the cash shortage
to the correspondent bank. In this sense, the
search for end-of-day cash is one of musical
chairs in which the cash needs (players) are
no larger than the available stock (chairs), but
matching need with available stock will be
accompanied by pandemonium, and the pan­
demonium may last longer than the few hours
available to settle. Clearly, there is almost
no excess cash in the system to be mobilized
on short notice if by excess we mean excess
reserve deposits. Excess reserves are widely
distributed as “small change” across the
entire banking system; if they were available
to be mobilized into sellable quantities, the
federal funds rate would already have induced
their owners to bring them to market before
the end of the day.
The total reserve deposits of banks with
cash may be available to lend to those w ith­
out cash to the extent that reduced holdings
one day can be offset by enlarged holdings (or
reduced requirements) later in a two-week
reserve maintenance period or by carry-over
of deficiencies into the next period. Further,
just as one bank must cover an unrepaid
daylight credit in the event of a settlement
failure, so, too, other banks will have un­
expected cash surpluses because of unsettled
payments to the failed institution. On balance,
the surpluses are less than the deficits only
in the amount of the funding gap that triggered
the initial bank failure. In general, then, suf­
ficient cash will exist in the aggregate, but
its redistribution must be accomplished very
quickly, after the time at which most m ar­
kets have begun to close, and subject to the
perceived creditworthiness of deficit banks.
The difficulty arises, therefore, not just
in the scarcity of total cash but in the distri­
bution of unexpected cash deficits and sur­

pluses across banks. If a bank with an unex­
pected deficit does not have established credit
lines with a surplus bank or the surplus banks
do not have management authorization to
| sell funds to the deficit bank, then a speedy
redistribution of cash would be very difficult—
perhaps impossible—by transactions among
these banks late in the day in the money mar­
ket. Intermediary banks, having authority
to lend to the deficit bank and to whom the
surplus banks will lend, would then be required
to complete the process that would prevent a
wave of systemic failures. The reliability of
these market mechanisms would presumably
depend importantly on the degree to which
confidence in normal credit judgments about
deficit banks could overcome a prudent incli­
nation of surplus banks to seek safety in cash
in the midst of waves of market talk occa­
sioned by an unexpected bank failure.
Of course, this is just the setting—a “liquid­
ity crisis”—in which a central bank lender
of last resort might play a constructive role.
Systemic risk—of a cascade of settlement fail­
ures—can be eliminated by isolating the ini­
tiating settlement failure, preventing it from
forcing unexpected cash deficits on other
banks, which in turn could force unexpected
deficits on still other banks, and so on. The
lender of last resort might isolate the prob­
lem in one of several ways. It might lend to a
bank that would otherwise initiate a settle­
ment failure, or to second-round banks with
unexpected deficits produced by the settlement
failure, or to banks that would be willing to
lend to the second-round banks. However, the
central bank may face constraints on its lend­
ing. For example, it may be prevented from
making loans to foreign institutions or to
banks without adequate collateral or to in­
solvent banks. Such constraints would influ­
ence which set of banks became the focus of
last-resort-lending activity in isolating settle­
ment failure and eliminating systemic fail­
ures. Beyond these institutional considerations,
however, is an important issue to be faced
in designing settlement-risk-management pol­

Federal Reserve Bank of Cleveland




icy, involving the degree to which risk expo­
sure is concentrated on banks in the pay­
ment system.

Concentration of Risk
There is a fundamental tension between
two means of managing settlement risk in a
payment system. One would seek to concen­
trate risk exposure on banks; the other would
seek to distribute exposure more broadly
over banks, their customers, and the lender
of last resort.
Concentrating risk exposure on banks is
promoted, as we have seen, when banks guar­
antee irrevocable availability of funds to their
customers. The result should be incentives
for banks to monitor carefully the condition
of counterparty banks and to manage day­
light credit extensions to those counterpar­
ties. At the same time, banks would have
incentives to monitor their own market rep­
utations and to protect those reputations
through prudent banking practices, including
management of their use of daylight credit.
Concentrating risk exposure could also be
promoted by the lender of last resort through
a “hands-off” attitude toward systemic risk.
This would require a credible policy of unwill­
ingness to be pressured into eleventh-hour
lending even to otherwise sound institutions
suffering the repercussions of a settlement
failure. Knowledge that the lender of last
resort would not intervene should create
incentives for sound banks to manage care­
fully their bilateral net credit extensions
across all payment networks as well as their
net debit positions across networks. Scrupu­
lous management of these daylight credit
extensions would aim at narrowing the size
of possible unexpected end-of-day financing
needs to levels commensurate with access to
cash available in the system to meet them.

This management might involve minimizing
daylight credit extensions by careful control
of the timing of payments relative to receipts,
by lengthening the m aturity of bank financ­
ing to reduce daily payments and receipts,
and by increased holdings of cash to act as
a buffer stock.
Distributing, rather than concentrating,
risk exposure can be promoted if banks hold
customers liable for funds provisionally cred­
ited to their accounts but not delivered be­
cause of settlement failure. Perhaps more
important, distributing risk exposure can be
promoted if the lender of last resort follows
a policy of lending freely to banks in circum­
stances that might otherwise threaten sys­
temic settlement failures.
There are important differences between
concentrating and distributing risk as a means
of managing settlement risks in a payment
network, although both may be effective in
achieving a low incidence of settlement fail­
ures. Concentration of exposure relies primar­
ily on market pressures within the banking
industry. Banks will wish to conserve their own
liquidity by shunning normal reliance on
volatile sources of funds, maintaining a good
ability to borrow should unexpected settle­
ment problems arise. This may also serve to
economize on their daylight overdrafts by
reducing the need to repay overnight funds
each day before fresh funds have been received.
Liquidity conservation will be encouraged
by other banks that will be carefully manag­
ing daylight credit extensions and the quality
of the banks to which such credit might be
extended. Distributing exposure relies more
heavily on bank customers and supervisory
authorities to promote prudent banking prac­
tices, and ultimately on the intervention of
the lender of last resort to prevent settlement
failures. Clearly, distributing exposure cre­
ates a moral hazard, in the sense that a cred­
ible commitment by the lender of last resort
to prevent systemic settlement failures will
make redundant many management and mon­
itoring efforts of banks. This will reduce the
liquidity of the banking system and raise
chances that imprudent practices will go un­
Economic Review • Fall 1984




detected and uncorrected. In combination, both
effects will increase the probability that the
lender of last resort will have to intervene.

III. The Current Concern

Both banks and the Federal Reserve are con­
cerned about risk exposure on large-dollar
transfer systems. What is not clear is whether
this reflects a recent discovery of a longstand­
ing and stable exposure, or an awareness of
recent growth in that exposure. The evidence
presented in what follows argues that it is
the latter, the awareness of significant growth
of settlement-risk exposure, that underlies
the current concern.
Degrees of settlement-risk exposure cannot
be measured. Creditworthiness cannot be
modeled by an exact science; the expected
value of the unrecovered percentage of a
bilateral net credit position necessarily lies
in the eye and mind of its beholder. Bilateral
and aggregate net credit and debit positions
on a payment system during a day may be
recorded by individual banks, but have only
recently begun to be recorded by operators
of the payment systems. Therefore, any his­
torical evaluation of exposure must rely on
inferences drawn from indirect evidence bear­
ing on creditworthiness, bilateral and aggre­
gate net credit and debit positions of indi­
vidual banks, and systemic risk.

Individual Bank Risk
The dollar volume of daylight credit extended
apparently has been growing rapidly since
at least 1970. The dollar volume of largedollar payments grew at a 24 percent com­
pound annual rate from 1970 through 1983,
almost 2M> times the rate of growth of the
value of national income and output over the
same period. All but 3 percentage points of

this volume expansion was in the number of
transactions rather than in their average
value. This was quite different from national
income and output, where inflation-adjusted
output grew only 3 percent, while the aver­
age value (price) of output grew 7 percent. In
itself, growth in the number and value of
transactions does not necessarily require
growth in daylight credit extended. It is pos­
sible that, with increasingly careful control of
the timing of payments relative to receipts,
banks could have accommodated a larger
value of payments with no increase in day­
light credit—that is, without using larger bilat­
Fig. 1 Large-Dollar Transfers M ade or
Settled through Reserve Deposit Accounts
Billions of dollars
bUU
1

1 Fedwire

f i j j l CHIPS

2

500
--- 1 CashWire
1____ | and CHESS
1

mmmm Reserve deposit

H H

account balances

400

30 0

20 0

100

0
1970

1983

SOURCE: Board of Governors of the Federal Reserve System.

Federal Reserve Bank of Cleveland



eral net credit extensions during a day to
make payments.
Sequencing—delaying payments until re­
ceipts arrive—is an alternative to daylight
overdrafts in covering payments. It is an
approximation of a “realtime” accounting
system in which payments could only be
made if a sufficient balance were on hand at
the instant the payment were ordered. Pay­
ments accounting is not typically “realtime,”
but “batched” overnight. Daylight overdrafts
arise if payments are ordered before the re­
ceipts come in that will leave a positive cash
balance. In principle, the total stock of cash in
the banking system could be as little as a
single dollar, as long as that dollar were used
and reused over 500 billion times during the
day. In practice, with a total stock of deposit
balances at Federal Reserve Banks of a little
more than $20 billion, the average dollar would
have to turn over only about 26 times daily
to be used and reused in completing over
$500 billion of large-dollar transfers. This is
up from only IV times daily as recently as
1970 (see figure 1). Nonetheless, the feat of
turning over the stock of cash 26 times daily
would indeed be prodigious if each payment
were made against an adequate cash balance
in “realtime,” so that dollars were actually
used and reused 26 times. Sequencing would
require that initial payments be made up to
the limit of the opening cash balance, but
further payments be delayed until sufficient
receipts accumulated to fund them. Alterna­
tively, the feat of 26 times per day turnover is
not at all prodigious if daylight overdrafts
can be used. Payments far in excess of open­
ing cash balances could be made with the
expectation of covering them with offsetting
receipts later in the day before settlement.
Increasingly powerful computer and tele­
communications technology might have made
it possible for banks to sequence payments
carefully as the volume of transfers grew,

7. The Federal Re­
serve Bank of New
York maintains
an on-line monitor
of positions of Edge
Act customers and
restricts their day­
light overdrafts.
Starting in 1984,
an ex post monitor
was put in place for
all Fedwire users.

13

thereby avoiding increased daylight overdrafts.
Corporate cash management became a so­
phisticated science during this period. Indeed,
the spread of cash management had as a
by-product some of the rapid growth in wire
transfer volume. Moreover, computerized
telecommunications for wire transfer, inte­
grated with realtime accounting systems, did
make it possible to build into banks’ systems
preset limits on daylight credit extensions
to customers. This had a counterpart in
the “store and forward” environment of the
CHIPS system. Banks could store payment
messages in the system until such time as
they were prepared to authorize a payment,
when the payment would be released and the
transaction completed. Beyond this, how­
ever, there is little to suggest the application
of sophisticated technology to the problem
of sequencing inter-bank payments traffic to
enable banks or networks to control their
net bilateral or aggregate daylight credit or
debit positions.
Lack of evidence of attempts to sequence
inter-bank wire payments is not surpris­
ing. Investing resources in managing the
sequencing of payments would be likely only
if there were some clear incentive to do so.
In fact, incentives to manage daylight credit
positions have been weak in the large-dollar
transfer systems.
Fedwire, until recently, had no systemwide
mechanism for monitoring daylight credit
extended to banks.7 With no restrictions on
their daylight overdrafts, efficient manage­
ment of commercial bank operations had every
incentive to use large daylight overdrafts to
reduce other costs. For example, large banks
routinely finance themselves by buying over­
night funds from many other banks and fi­
nancial institutions (aggregating over $100 bil­
lion daily in mid-1984). Just as routinely, the
banks can prepare the necessary list of repay­
ment messages at the end of a day for auto­
mated telecommunications transm ittal on the
following day. The first job each morning,

Economic Review • Fall 1984




before competing uses of people and equip­
ment intervened, would be to activate the
system to transm it the string of repayments.
The result would be efficient work flow and
a routine drawing down of the bank’s Federal
Reserve deposit account balance at the open­
ing of business each morning. If overnight
sources of funds normally exceeded reserve
deposit balances (reserve deposits of all banks
amounted to about $20 billion in mid-1984),
then the result would be an immediate day­
light overdraft that would last until fresh over­
night funding had been bought and received.
The incentive structure in CHIPS has been
somewhat different. Settling banks have
had an interest in the amount of daylight credit
provisionally extended to their respondent
banks participating in CHIPS. Indeed, the
“store and forward” mode of operation made
it possible to set dollar limits on the net credit
extended to a customer by a bank, whether
the customer were a large nonfinancial cor­
poration making trade payments or a respon­
dent bank paying for money or foreign ex­
change market purchases. Another indication
of settling participants’ interest in control­
ling risk exposure may be found in the change
in CHIPS finality from 1:00 pm of the next
day, first to 10:00 am of the next day (in 1979)
and then to 6:30 pm of the same day (in 1981).
Shortening this time gap had the effect of
substantially reducing the duration of settlement-risk exposures.
These efforts by settling banks to control
their own potential credit-risk exposure to
customers might also be viewed as efforts to
control settlement risk. Any limitation on
credit extended through payments made for a
customer is also a limit on daylight indebted­
ness of the paying bank to other participants
in the network. Until recently, however, these
incentives were not reflected in any network
limit on bilateral credit or debit positions,
or in a bank’s ability to set a limit on bilateral
or aggregate credit extended on the system.

CashWire and CHESS do have both bilateral
net credit limits and sender net debit caps,
but these cannot be attributed to any incen­
tives operating within the group of partic­
ipants, because they are an interim require­
ment of the Federal Reserve for net settlement
of the networks. CashWire also requires cus­
tomer guarantees.
The conclusion that one draws is that the
bilateral and aggregate net credit positions
generated on large-dollar payment systems
have been growing rapidly over the years
since at least 1970. Payments volume grew
rapidly; the cash position of the banking
system using these payment networks did
not grow at all; incentives for participating
banks to sequence their own transactions to
avoid reliance on daylight credit were weak, at
best. If risk exposures were not growing, it
could only have been because the creditworthi­
ness of participants was improving enough
to offset growing daylight credit usage.
The creditworthiness of system partici­
pants probably was not improving. In addi­
tion to a general weakening in capital posi­
tions of the U.S. banking system, two specific
developments suggest this conclusion. One
has to do with the range of institutions eligi­
ble for direct access to Fedwire and the second
with the burgeoning role of foreign partici­
pants in the daily flow of inter-bank largedollar payments.
Prior to 1980, access to Fedwire was re­
stricted to member banks, a (declining) sub­
set of depository institutions that included
all national banks plus those state banks that
chose to become members. With passage of
the Depository Institutions Deregulation and
Monetary Control Act of 1980, access was
broadened to include all commercial banks,
thrift institutions, and credit unions eligible
for federal deposit insurance. Without argu­
ing that any particular newly eligible institu­
tions were less creditworthy than any mem­
ber banks, it is still possible to argue that Fed­
eral Reserve risk exposure increased. More

Federal Reserve Bank of Cleveland



institutions, supervised by a more diverse set
of regulatory authorities, entering new mar­
kets and (for some) entering the twilight of
viable operation during 1981-82, surely could
have reduced the average creditworthiness
of the set of institutions eligible to use Fed­
wire. How much Federal Reserve risk expo­
sure actually increased as a result is impos­
sible to quantify. Actually, it may not have
been a substantial increase. Most of the newly
eligible institutions did not avail themselves
of access to Fedwire or any of the other largedollar payment systems.
A more important increase in risk exposure
was the result of growing international inter­
bank volume. The 1970s first saw U.S. banks
follow U.S. multinational corporations abroad
and then become immersed in recycling petro
dollars through the world banking system.
CHIPS dollar volume was growing at a 35 per­
cent annual rate starting in 1970. Between
mid-1978, when current data reporting began,
and the end of 1983, U.S. banks’ own claims
on foreigners were growing at a 30 percent
annual rate; overnight Eurodollar deposit
holdings were growing at a 50 percent annual
rate starting in 1977. The burgeoning daily
flow of payments through CHIPS involving
New York-based subsidiaries of foreign banks
was a likely source of increased risk exposure.
Foreign-owned institutions handling the trans­
actions of foreign-based banking establish­
ments subject to unfamiliar legal and regula­
tory systems necessarily injected uncertainty
and new risks into banking relationships.

Systemic Risk
The conclusion to be drawn must be that, both
on account of growing daylight credit exten­
sions and on account of the widening set of
banking institutions whose creditworthiness

is relevant, individual risk exposures of par­
ticipants in large-dollar transfer systems has
been growing. Systemic risk exposure is not
necessarily driven by these individual expo­
sures, however. Mechanisms to isolate the
impact of a settlement failure might have been
strengthened or weakened, offsetting or aug­
menting the effects of growing daylight credit
extensions and the changing creditworthi­
ness of individual banks. Nonetheless, it would
appear that systemic risk has also been grow­
ing in recent years.
Systemic risk is absent from Fedwire because
of the finality of Fedwire payments. Since
1970, the percentage of the dollar volume of
large-dollar-value payments made on Fedwire
has declined from 88 percent to 54 percent,
suggesting substantial growth of systemic risk
exposure. Moreover, the shift from next-day
to same-day CHIPS settlement completed
in 1981 might be interpreted as a further in­
crease in systemic exposure in one important
sense. Participants did reduce the duration
of their bilateral exposures to settlement risk,
and the shift to same-day settlement was de­
signed for that purpose. However, systemic
risk exposure may have been increased because
of the shortened time available during which
banks, in the event of a settlement failure,
could develop alternative financing arrange­
ments. This would be the case if a participant’s
ultimate inability to settle were known or
strongly suspected before normal settlement
hour, so that the period between the end of
a day’s activity and settlement could be used
by otherwise sound banks to find alterna­
tive funds in the cash markets.
Whether individual bank participants would
have recognized the potentially offsetting in­
crease in systemic risk exposure when their
individual exposures were reduced cannot be
determined. Their own systemic risk expo­
sure would depend as well on the extent to
which Federal Reserve Banks’ lending could

Economic Review • Fall 1984



be expected to isolate settlement failure
and control systemic risk.
That systemic risk has increased seems
clear. Whether the exposure is that of private
financial institutions and their customers
or that of the Federal Reserve Banks is not so
clear. The distribution could only be deter­
mined by experience with failures, which does
not exist and no one wants, or by a binding
commitment by the Federal Reserve about how
it would act in the event of a failure, which
is fraught with difficulty.
A lender of last resort could state its commit­
ment not to lend in the event of a settlement
failure, thereby attempting to concentrate
systemic risk exposure squarely on private
institutions. That such a commitment could
be credible is itself incredible, given the panicavoiding objective of a central bank lender of
last resort. Ambiguity might be the most that
could be gained from such an approach, cre­
ating a minimal sense of systemic risk expo­
sure in private institution managements and
some minimal risk-controlling behavior. On
the other hand, a stated commitment to isolate
all institutions from the impacts of a settle­
ment failure, while more credible than a pledge
of inaction, carries with it the moral hazard
that private institutions will have weak incen­
tives to consider systemic risk in their con­
trol practices.

Recent Proposals
Silence about settlement-risk exposure was
a reasonable Federal Reserve policy when cash
balances equaled or exceeded all of a day’s
payments on Fedwire, when Fedwire was the
dominant large-dollar transfer system, and
when supervisory oversight of member banks
provided a monitor of the creditworthiness

current interest of bankers and the Federal
Reserve in assuring prudent management
of settlement-risk exposure by private finan­
cial institutions and their customers and
by the Federal Reserve.
Two matters seem central to prudent man­
agement of settlement-risk exposures. One is
the ability of participants to maintain limits
on their own bilateral net credit and aggre­
gate debit positions. This involves both infor­
mation systems that track those positions
and control over their size. Improved positionmonitoring capabilities are being developed
by the respective large-dollar payment systems
that may provide the necessary information;
proposals are being considered that would
result in debit and credit limits, either selfimposed or derived from uniform rules.
The other matter is the recognition of settlement-risk exposure. Supervisory examina­
tion may assure that banks have settlementrisk-management procedures in place, but risk
unperceived will go unmanaged. Ambiguity
about who is at risk in making large-dollar
payments clouds this perception. The Federal
Reserve is at risk in extending daylight credit
on Fedwire and must manage its exposure.
In the absence of receiver guarantees, banks
IV. Conclusion
and their customers are both at risk in mak­
ing payments on net settlement systems.
Settlement risk is real, although actual set­
tlement failures have been nonexistent. Rec­ Whether either party, but especially custom­
ers, clearly perceives the full extent of its
ords of bilateral daylight credit positions
are beginning to be kept, but evaluating risk exposure is hard to determine. Systemic risk
exposure cannot be unambiguously located,
exposures will always be judgmental. This
but must be managed by the Federal Reserve
is because the creditworthiness of “borrow­
jointly to protect the resilience of the bank­
ers” is a subjective judgment and because
ing system to an unexpected settlement fail­
the incidence of systemic risk depends on
the reaction of the lender of last resort to an ure and the discipline of a grudging lender
actual settlement failure. It seems clear, none­ of last resort.
theless, that both individual and systemic
settlement risk exposure have increased rap­
idly in recent years. This has prompted the

of all participants in Fedwire. Recently, how­
ever, risk exposure has grown rapidly, both
individual and systemic. Uniform procedures
for examination have been adopted by the Fed­
eral Financial Institution Examination Coun­
cil that seek to assure, among other things,
that financial institution managers are aware
of settlement-risk exposure. Beyond that,
the Federal Reserve has sought comment on
three principal risk-management devices (re­
ceiver guarantees, bilateral net credit limits,
and sender net debit caps) that might be used
singly or in combination by network partici­
pants, by network managements, and/or
by regulators seeking to assure prudent set­
tlement-risk management.
The Federal Reserve clearly has a large
stake in this. Its own bilateral credit risk has
been growing rapidly, unshared with its de­
positor banks because of Fedwire finality of
payment. Its systemic risk exposure has also
grown rapidly because its lender-of-last-resort
function implies an obligation to isolate the
impacts of a settlement failure. A prudent
central bank, no less than a prudent private
bank, must manage its risk exposure.

Federal Reserve Bank of Cleveland



Economic advisor
Roger H. Hinderliter
researches capital
investment and bus­
iness finance for the
Federal Reserve
Bank of Cleveland.
1. Business earnings
may be measured
relatively with re­
spect to the value
of total output (capi­
tal’s share of the
proceeds from pro­
duction and sales);
the replacement
value (current cost)
of the capital stock
(the rate of return
on capital); or net
worth (the rate of
return on equity).
The rate of return
on equity is impor­
tant only if the divi­
sion of earnings be­
tween equity hold­
ers and debt holders
is an issue. Thus,
while the rate of re­
turn on equity may
be a critical mea­
sure for evaluating
the performance of
an individual firm ,
it is less useful in
evaluating the over­
all performance of
capital assets. The
other two ratios are
closely linked, and
most efforts to track
the earnings prob­
lem have concen­
trated on them.

17

Sources of Change in
Rates of Return on
Capital: 1952-82
by Roger H. Hinderliter

Economic Review • Fall 1984




Business earnings are the reward to capital
from current production and sale of goods
and services. As such, they reflect the per­
formance of existing capital in an uncertain
economic environment. Business earnings
also are a major influence on investment deci­
sions of firms and on the willingness of indi­
viduals and institutions to help finance invest­
ment by purchasing debt or equity issued by
firms. Funds raised by businesses in capital
markets are invested in new capital assets in
expectation of future earnings from the assets’
productive use. If past expectations were
unfulfilled in current earnings, further invest­
ment would become less attractive, and, in
time, output growth, creation of new jobs, and
living standards might suffer. Thus, while
measuring the performance of existing capi­
tal assets, business earnings also might be an
important indicator of the nation’s future
economic health.
Beginning in the late 1960s, the economy of
the United States was beset by a number of
related problems threatening future prosper­
ity. These problems included falling labor
productivity growth, accelerating inflation,
sharp increases in energy costs, and an appar­
ent decline in relative business earnings.
Earnings are measured in relative terms as
the rate of return on capital or capital’s share
of nominal output.1 In studying the perfor­
mance of corporate business, economists gen­
erally have concluded that relative earnings
declined sharply in the late 1960s and, if not
falling further, at least remained low during
the 1970s. Declining relative earnings are not
unambiguously a signal of weakness and dis­
appointed expectations. They could reflect, for
example, the disappearance in the 1960s of
capital scarcity accumulated during the De­
pression and war years. Although economists
agree that the rate of return and the capital
share fell, there is little agreement over the
sources and implications of the decline.

2. This brief review
of past studies high­
lights fundamental
issues. A more tho­
rough evaluation of
the literature is pro­
vided by Scanlon
(1981).

18

In an early attempt to track the earnings
performance of corporations, Okun and Perry
(1970) attributed the initial decline in the capi­
tal share, between 1965 and 1969, to a rise
in labor cost relative to output price and to
poor labor productivity growth. These forces
were viewed from the perspective of 1970
as transitory. Somewhat later, Nordhaus (1974)
concluded that a longer-term, more perma­
nent decline in the capital share had occurred.
He suggested the decline reflected the effects
of higher levels of investment achieved after
World War II. This investment was made
possible by a lower cost of capital associated
with declining corporate tax rates and a falling
risk premium on corporate equity as the De­
pression became a more distant memory.
Nordhaus’ conclusion was supported by
additional research results. Kopcke (1978)
estimated a “normal” rate of return from a
productivity model based on a Cobb-Douglas
production function and also found that a
longer-term decline was indicated. Lovell (1978)
examined a number of relative earnings con­
cepts and, after accounting for cyclical fluc­
tuations and productivity growth, concluded
that a downward trend characterized earn­
ings patterns. Other studies, however, pro­
duced contradictory results. Working with
gross and net (of depreciation) rates of return
on capital, Feldstein and Summers (1977)
found lower earnings in the 1970s probably
resulted from a variety of factors—wage-price
controls, rising inflation, and larger fluctu­
ations in capacity utilization—none of which
would confirm a long-term downward trend.
Runyon (1979) compared the approach of Nord­
haus with that of Feldstein and Summers
and also concluded that a secular decline in
relative business earnings was not supported.2
In short, the decline of relative business
earnings may have been the result of tempo­
rary reversible disturbances without last­
ing effect on investment, a sustainable down­
ward trend possibly constraining investment
over a longer period, or a complex mixture

Federal Reserve Bank of Cleveland




of short-run and long-run factors with equally
mixed implications for investment. The strong
recovery in investment that began in 1983 is
an encouraging sign of an improved invest­
ment environment. Many industries, even
manufacturing industries widely regarded as
inefficient high-cost producers, now are mak­
ing or planning large investments in tech­
nologically advanced capital assets. A pro­
longed and successful investment program
depends heavily on whether business earnings
justify the effort over a longer period of time.
Thus, any judgment on the promise of the
current recovery depends on unraveling the
mysteries surrounding earnings patterns
in the past. This study approaches that task
in five stages.
A method of evaluating earnings perfor­
mance is proposed in section I. The rate of
return on capital and capital’s share of nom­
inal output are joined together and the result­
ing expression defining the rate of return
is decomposed into a margin effect (which cap­
tures interactions among the output price, the
replacement price of capital, and unit costs)
and a multiplier effect (which captures inter­
actions between capacity utilization and
capital productivity).
In section II, estimates of before- and after­
tax net rates of return and their margin and
multiplier components are presented for total
business (corporate and noncorporate busi­
nesses). One benefit of a total business frame­
work is that GNP, the normal unit of account
in discussions of economic performance, be­
comes the relevant measure of output in the
calculations. Thus, the estimates can be related
to other issues—the productivity slowdown,
economic growth potential, and the trans­
mission of policy actions, for example—that
have an economy-wide focus. Moreover, while
the noncorporate sector has always been much
smaller than the corporate sector, it still is
a significant force in creating jobs and con­
trolling capital. Because most studies of busi­

3. Feldstein and
Summers (1977)
speculated that coun­
tervailing differences
in tax treatment
and risk made the
noncorporate rate of
return indetermi­
nate relative to the
corporate rate in
theory. In one em ­
pirical study that
included noncorpo­
rate business (the
nonfarm component),
Bosworth (1982) re­
solved the indeter­
minacy in favor of
lower noncorporate
rates of return (in­
creasingly so in the
1970s). However,
Bosworth’s estimates
of the capital com­
ponent of total non­
corporate earnings
(capital plus labor)
seem to have placed
a disproportionate
share of cyclical and
secular weakness in
the 1970s on capital
earnings (see below,
appendix 1).
4. Holland and
Myers (1979) include
capital gains (or
losses) in estimates
of after-tax rates
of return. They fin d
that individual years
can be greatly af­
fected, but over a
longer period the
average rate of re­
turn is little changed
by the capital gains
calculation. This
is to be expected if
relative price move­
ments are such that
gains and losses
roughly balance
overtime. The esti­
mates by Holland
and Myers excluded
land, which severely
limits capital-gains
potential.

ness earnings have focused on the larger cor­
porate sector, it is unclear to what extent
noncorporate businesses shared in any earn­
ings difficulties that emerged in the postwar
period. Noncorporate business has undergone
a striking metamorphosis over these years.
It has been transformed from a largely agrar­
ian sector to a largely service-producing sec­
tor, and these structural dynamics are one
element affecting rates of return.3
The before- and after-tax rates of return
are re-estimated in section III under the counterfactual hypothesis of a constant relative
price of capital. Eisner (1980) argued that rel­
ative price changes during inflationary peri­
ods create capital gains for owners of existing
capital assets, and these are appropriately
treated as income. Rates of return measured
with respect to replacement value may under­
state earnings performance, because the rela­
tive price of capital does change, especially
when land is included in the capital stock, and
gains typically are not included in income.4
A model for evaluating changes in rates of
return that attempts to identify and quantify
specific sources of change is proposed in sec­
tion IV. Apart from relative price increases
and cyclical variation in capital utilization,
slower capital productivity growth and a one­
time distortion of the relationship between
output price and unit costs in the late 1960s,
as first noted by Okun and Perry, contrib­
uted to the fall in observed rates of return.
The extent to which these forces represent a
permanent erosion of business earnings is
considered in section V. The emphasis in this
study is not one of providing better numeri­
cal estimates of rates of return. Although there
are interesting differences between the esti­
mates developed here covering total business
and prior estimates of corporate rates of
return, judgments about the significance of
these differences are hazardous and necessar­
ily speculative. The overall pattern of move­
ments in rates of return found here is quite
similar to evidence from past studies. The
major departure of this study is the attempt
to identify and quantify the sources of change
in this pattern of behavior.

19

Economic Review • Fall 1984




I. The Rate of Return on Capital

The rate of return on capital is a measure of
relative business earnings derived from capi­
tal budgeting theory. In principle, it compares
the discounted present value of the expected
future earnings stream to the current cost
of capital assets. Thus, the rate of return is a
useful guide in choosing among investment
projects. Those projects that offer the highest
rates of return are implemented, and those
projects with relatively low rates of return
are discarded.
The rate of return also is useful as an indi­
cator of the performance of existing capital.
As such, it represents an average rather
than a marginal rate and is defined as cur­
rent nominal business earnings divided by the
replacement value of the capital stock. This
measure can be defined before or after taxes,
and on a net or gross basis depending on
whether a fully depreciated or an undepre­
ciated capital stock is entered in the denom­
inator. The choice between net and gross cap­
ital stocks is governed by the way capital
affects output. If capital becomes less efficient
in production over time, if it gradually wears
out year-by-year, the net concept is appropriate
and, correspondingly, earnings are measured
net of depreciation or capital consumption.
Measurement of the average rate of return
on capital rests on a capital maintenance
theory of income. Nominal earnings in the
numerator are the residual gain from the
current year’s production and sale of goods
and services, after deducting labor and other
costs and providing for the maintenance of
capital assets at their replacement value. Nom­
inal earnings include profits and rents (with
appropriate capital consumption and inven­
tory valuation adjustments) of the corporate
and noncorporate business sectors. Noncorpo­
rate profits are estimated from total noncor­
porate earnings by assuming the owners of
these businesses are paid the average wage in
their industry after correcting for the effects
of cyclical and secular changes in labor market

conditions. The correction (detailed in appen­
dix 1) is designed to avoid placing the entire
burden of cyclical and secular weakness in
the economy on capital earnings. In addition
to rents that are embedded in profit figures,
rental income exclusive of rents on owneroccupied nonfarm housing is included in the
numerator of the rate-of-return ratio. Because
the division of gains between equity and debt
Fig. 1

holders is not an issue in rate-of-return cal­
culations, net interest payments are added
to nominal earnings.5
The nominal earnings stream —profits plus
interest plus rent—is a broad-based measure of
the returns to business capital. The denomi­
nator of the rate of return ratio accordingly is
defined to include the broad set of capital
assets generating this stream. The relevant

Rates of R eturn on C apital

Nominal
output

Less claims
on output

Equals business earnings
Business
Earnings

Labor
Compensation

Compensation of
employees and
noncorporate
business owners
\
O ther Business
Paym ents

= Before-tax
earnings

Indirect business
taxes and trans­
fers, less govern-

Less business
income taxes

m ent subsidies

V

Corporate profits
and capital earn­
ings of noncorpo­
rate businesses,
rent (excluding
overhead), and
net interest (ex­
cluding overhead)

............. >

= Aftertax
earnings

Capital Costs
Capital consumption on repro­
ducible business
capital

X—.............'
Overhead Costs

N.

Labor compensa­
tion and other
charges in govern­
ment, households,
and nonprofit
institutions
\

Federal Reserve Bank of Cleveland



' s

. „ ,,
Divided
by
value of
capital

Value of
Capital
Current cost of
reproducible
capital (plant,
equipment, and
rental housing),
inventory stocks,
and land

„

Equals rates
of return on
capital

5. See, for example,
Walton (1981).
Lovell (1978) sug­
gests that including
interest also may
help correct for the
financial distortions
of inflation, which
otherwise tend to
understate earnings
by raising interest
charges without a
corresponding reduc­
tion in the real value
of outstanding debt.

21

capital stock is the sum of business invento­
ries, plant and equipment, tenant-occupied res­
idential housing, and land used for business
purposes. Among these components, only land
presents difficult measurement problems. In
past studies of business earnings, a variety
of simplifying assumptions have been em­
ployed to deal with these problems, among
them ignoring land altogether. Here, the basic
land series for rate of return calculations are
the market value estimates from the flow-offunds balance sheets. Real value of land stocks
and the corresponding price indexes, which
are needed for margin and multiplier calcula­
tions, are estimated from the sketchy data
available on agricultural land, land transi­
tion ratios, and land ownership (see appen­
dix 2). The resulting estimates suggest a
nearly constant real value of business land,
produced by a reduction of farm land at about
0.5 percent per year and an increase in non­
farm business land at about the same rate be­
tween 1952 and 1982. Land prices increased
rapidly, especially in the 1970s.
A schematic view of the derivation of rates
of return is shown in figure 1. Starting from
nominal GNP, labor and other superior claims
are deducted, leaving business earnings as
the residual claim. The ratio of this earnings
stream (before or after taxes) to the value of
the capital stock determines rates of return.
Formally, the definition of the before-tax rate
of return can be stated as follows:
Ei
( 1)
Rt =-7T
Vt
CPFTt + NCPFTt + NINTt + RENTt
KPRt (INVt + FlXt + LANDt)

Economic Review • Fall 1984




where
E = nominal business earnings—
sum of corporate profits, non­
corporate profits, net interest,
and rent,
V = replacement value of capital—
(weighted average) capital price
index times sum of real values
of inventories, fixed reproducible
capital, and land.
The alternative measure of relative busi­
ness earnings examined in the studies cited
above is defined as the earnings stream
divided by nominal output or GNR This is
the share of nominal output generated dur­
ing the year claimed by the business owners
of capital. It is related to the rate of return
on capital in the following manner:
Et
GNPt
A
X
(2 )
Vt
Vt GNPt
The rate of return is equal to the capital
share times the ratio of nominal output to the
value of the capital stock. If the components
of equation (2) are rearranged slightly, the
rate of return becomes:
x —
(3) A .

vt Qt v,
—

/ QPRi - UCS,\
= (
KPRl ) x (QQt * OK).

where

QPR, KPR = price indexes of output
(real GNP) and real cap­
ital stock, respectively,
UCS = total unit cost of pro­
ducing output,
QQ = ratio of actual output
to potential output,
QK = ratio of potential output
to real capital stock.

6 . The QK ratio is
a hybrid measure in
that it relates poten­
tial output to actual
capital. Perhaps a
more appropriate
measure of long-term
capital productivity
would be potential
output divided by
potential (cyclically
adjusted) capital.
This would require
a separate estimate
of potential capi­
tal, one coyisistent
with the chosen mea­
sure of potential out­
put. Deviation of
actual capital from
potential capital then
would become a third
component of the
earnings multiplier.
No significant cycli­
cal variation in the
QK ratio was de­
tected, however, and
this refinement was
not made.

7. The major source
of data used in this
study is the national
income and product
accounts. The ac­
counts provide esti­
mates of earnings,
prices, costs, out­
put, and inventory
stocks. Fixed repro­
ducible capital stocks
are from the Com­
merce Department’s
tangible wealth esti­
mates. Land stocks
and prices are esti­
mated from several
underlying data
sources, as described
in appendix2. Poten­
tial output is from
Clark (1983). All
data are mid-year
values. Capital-stock
data reported endof-year are shifted to
mid-year by simple
averaging.
22

The first component on the right-hand side
of the final expression in equation (3) is the
earnings margin. This margin includes nomi­
nal variables relating the spread between out­
put price and unit costs to the replacement
price of capital. Thus, the price of capital rel­
ative to the price of output is an important
determinant of the margin effect on the rate
of return. Unit costs are divided into four
groups (as identified in figure 1) for before­
tax estimates of the rate of return. These are
labor compensation, other business payments,
capital costs, and overhead costs. Labor com­
pensation is the payment for labor services in
the corporate and noncorporate business sec­
tors. Other business payments include indi­
rect business taxes and business transfer
payments. Capital costs are the depreciation
charges (capital consumption with capital
consumption adjustment) on the fixed repro­
ducible portion of the business capital stock.
Finally, overhead costs include compensation
paid in government, households, and nonprofit
institutions, and rents, interest, and other
charges on owner-occupied residential hous­
ing and the fixed capital of nonprofit institu­
tions. Government, households, and nonprofit
institutions produce no earnings, but they
perform functions necessary for the ongoing
activities of earnings centers. Government
provides the legal system, national defense,
and rules and regulations for society’s organ­
ization and well-being. The household is the
fundamental organizational unit of society,
performing many functions that support the
earnings centers. Nonprofit institutions like­
wise perform a variety of needed functions
definitionally outside the domain of earnings
centers. Hence, they are treated as the over­
head component of the national economy. Bus­
iness income taxes, of course, are deducted
along with the above costs to calculate the
after-tax rate of return.
The second component on the right-hand
side of equation (3) is the earnings multiplier.
The earnings multiplier includes real vari­

Federal Reserve Bank of Cleveland




ables, measuring capacity utilization and cap­
ital productivity. These components, which
together measure the efficiency of the capital
stock in producing output, essentially deter­
mine how a given earnings margin will be
transformed into a rate of return. The ratio
of actual output to potential output (the QQ
ratio) captures the effects of capacity util­
ization on the rate of return. High capacity
utilization (larger values of the QQ ratio) sup­
ports a higher rate of return by stretching
the margin over a more efficient volume of out­
put. The ratio of potential output to the real
capital stock (the QK ratio) is a measure of
capital productivity. Higher capital productiv­
ity boosts earnings by squeezing larger poten­
tial (full-capacity) volumes out of a given
capital stock?

II. Tracking the Rate of Return

Before-tax (BXR) and after-tax (AXR) aver­
age net rates of return on capital, calculated
from the definition of equation (1) for the
total business sector, are plotted in figure 27
The estimates cover the period from 1952,
when any distortions from World War II and
its aftermath might be expected to have dissi­
pated, to 1982, the latest year for which com­
plete and compatible earnings and capital stock
data were available. This is a period of rich
economic experience. It includes episodes of
stable economic growth and episodes of accel­
erating inflation; structural changes in out­
put and business organization and cyclical
swings of major proportions; wage-price con­
trols in the early 1970s and periodic tax
changes, the most sweeping of which came
in 1981.
In the early part of the period, both before­
tax and after-tax estimates were relatively
stable. BXR declined slightly, and AXR
changed even less, except for cyclical fluctu­

8 . Kopcke (1978)
and other researchers
argue that after tax
estimates of the rate
of return are more
revealing measures
of performance. Be­
cause taxes are levied
on reported earnings
rather than economic
earnings (with cap­
ital consumption and
inventory valuation
adjustments), effective tax rates increase
during a period of
accelerating infla­
tion, possibly distort­
ing before-tax esti­
mates relative to their
after-tax counter­
parts. When interest
was included with
earnings, however,
AXR and BXR gen­
erally moved together,
and A XR fell only
marginally faster
than BXR between
1965 and 1978.

ations produced by recessions in 1954, 1958,
and 1960. In the early 1960s both measures
rose sharply, reaching 30-year highs of 11.2 per­
cent (BXR) and 8.0 percent (AXR) in 1965.
After 1965, a sustained erosion in both mea­
sures is clearly indicated. Cycle peaks in 1973,
1978, and 1981 were progressively lower than
previous peaks. In 1981 BXR was 7.5 per­
cent, about two-thirds of its mid-1960s record
high, while AXR had declined to 5.8 percent.
In the recession year of 1982, BXR fell to a
historic low of 6.5 percent. The after-tax mea­
sure recorded its record low (5.0 percent) in
1980, prior to the tax legislation of 1981. In­
deed, AXR increased relative to BXR prior to
1965 and after 1978, especially in 1982 when
the effects of the Economic Recovery Tax Act
of 1981 became significant.8
Comparison of the rates of return shown
in figure 2 with the results of other studies is
hazardous because of substantial differences
in methods of variable estimation. With this
caveat in mind, it can be noted that the pat­
terns of change in BXR and AXR are similar
to those found by other researchers. The bulge

Fig. 2

Percent
14 -

Rates of R eturn on Capital

12 10 8
6
4
2
0
1952

23

1962

-------AXR




1972

--------BXR

1982

in the mid-1960s and the decline thereafter
are pieces of the earnings puzzle common to
virtually all estimates of the rate of return.
It also appears that the decline is somewhat
less pronounced (at least through the late
1970s) in the estimates presented here. For
example, Feldstein and Summer’s (1977)
before-tax estimates of the net corporate rate
of return are higher than BXR throughout
the 1950s and 1960s, by 2.4 percentage points
near the peak (1964-66). This gap diminishes
in the 1970s, and, in several years, particu­
larly 1973-75, BXR exceeds Feldstein and
Summer’s corporate rate. Although these
comparisons are highly provisional, it does
not appear that a general deterioration of
noncorporate rates of return relative to cor­
porate rates in the 1970s, noted by Bosworth (1982), is supported here.
Noncorporate business was in sharp tran­
sition throughout the postwar period, a tran­
sition with roots reaching back into the De­
pression years of the 1930s. In 1952,39 percent
of all noncorporate entrepreneurs operated
agricultural businesses, and 19 percent were in
the service and finance industries. By 1982,
the composition was reversed. Over the same
period, farm earnings (labor plus capital) fell
from about one-third to about one-fifth of total
noncorporate earnings. Thus, by the 1970s
the marginal farm businesses in the noncor­
porate sector, probably characterized by low
rates of return on capital, were substantially
reduced in number and influence on earnings,
and services had supplanted agriculture as
the dominant force in the noncorporate busi­
ness structure.
Structural transition in the noncorpor­
ate sector probably contributed stability to
capital earnings in the sector. Certainly, non­
corporate businesses performed less well
than corporations in the 1950s and 1960s,
because their capital earnings did not match
the corporate pace. In the early 1950s (1952-54),
noncorporate business profits were about
43 percent of corporate profits. By the late
1960s (1967-69), the profit proportion had de­
clined to 24 percent, but it fell only slightly

9. I f no adjust­
ment for labor mar­
ket conditions had
been made (that is,
if noncorporate bus­
iness owners were
paid the average
wage without quali­
fication), the profit
proportion in the
late 1970s would
have been about
12 percent rather
than 2 2 percent,
suggesting a deterio­
ration as noted by
Bos it’o rth (1982).
Noncorporate prof­
its and rates of
return in 1980-82
then would have
been negative.
10 . See, for example,
Eisner (1980) and
Cagan and Lipsey
(1978).

in the 1970s, to 22 percent by the end of the
decade (1977-79). More stable profits coupled
with traditionally slower growth of capital
(at replacement value) would have supported
noncorporate rates of return in the 1970s. In
1980-82, however, the noncorporate sector
collapsed. Even with considerable allowance
being made to insulate capital earnings from
slack labor market conditions, the profit
proportion fell sharply in these years, to about
9 percent; hence, the extremely low rates of
return of this period apparently were concen­
trated in the noncorporate sector.9
Following the definition of equation (3), the
rate of return on capital can be decomposed
into the margin effect, which accounts for
the influence of prices and unit costs, and the
multiplier effect, which accounts for the influ­
ence of capacity utilization and capital pro­
ductivity. Before-tax (.BXM) and after-tax
(.A XM) earnings margins are shown in figure 3.
The earnings multiplier {MULT), cycling
about the productivity ratio (QK) as capacity
utilization rises and falls, is shown in figure 4.
There can be little doubt that a long-term
margin squeeze was a substantial contributor
to falling rates of return. Even in 1965, the
record year for rates of return, the before-tax
margin fell short of previous peaks, and sub­
sequent peaks continued to exhibit deteri­
oration. The after-tax margin reached an
all-time high in 1965, but steadily declined
thereafter. The sharpest declines in both
margins occurred in the late 1960s (1965-70).
Contributions to rates of return from the
earnings multiplier can be separated into
three periods. The first, from 1952 to 1964,
was a period of rapid growth in the multiplier,
produced by sharply rising capital productiv­
ity. Although relatively low capacity utili­
zation limited the effect on rates of return in
many of these years, the rapid growth offset
much of the erosion of margins and paved
the way for record rates of return in the mid1960s. In the late 1960s the multiplier plateaued at a high level. Capacity utilization
was quite high, but capital productivity was
not growing. The multiplier in the 1970s was
characterized by irregular growth in capital
Federal Reserve Bank of Cleveland




productivity and large cyclical swings in
capacity utilization.

III. Constant Relative
Price Estimates

The persistent decline in both before- and
after-tax margins, which would virtually fore­
close all doubt about trend movements in rates
of return were it not for the partially offset­
ting increases in the mutliplier, raises an
important question about rate-of-return mea­
surement. Rates of return are based on replace­
ment value of the capital stock, and earnings
margins correspondingly are measured rela­
tive to the replacement price of capital. If
the capital price increases faster than the
output price, such that the relative price of
capital increases, should account be taken of
the capital gains accruing to the owners of
capital assets?
Two types of capital gains can be identi­
fied. Nominal capital gains on inventories and
fixed reproducible capital are removed from
earnings by the inventory valuation and capi­
tal consumption adjustments. These adjust­
ments are necessary because otherwise earn­
ings would be distorted by amounts properly
reflecting current economic costs of capital
maintenance—replacement of inventories,
plant, and equipment. During inflationary
periods both the inventory valuation adjust­
ment and the capital consumption adjust­
ment lower reported earnings, often by sizable
amounts. In 1979-81, for example, the peak
of the last inflationary spiral, the two adjust­
ments lowered business earnings by an aver­
age of $67 billion a year. This produced a
before-tax rate of return that averaged 1.5 per­
centage points less than would have been
estimated without the adjustments.
Price increases need not be and usually are
not equally distributed among all price indexes.
Although nominal gains are excluded from
earnings, many researchers contend that rel­
ative price changes create real capital gains,
which augment earnings.10Thus, if the replace­

ment price of capital rises faster than the
output price, the relative price change creates
a real capital gain for the business owners
Fig. 3

E arnings M argins

Percent

1952

Fig. 4

1962

------- AXM

1972

------- BXM

E arnings M ultiplier

Ratio

25

Economic Review • Fall 1984




1982

of capital assets. This gain simply reflects the
fact that existing capital has risen in value,
and because the owners of capital have use of
higher-valued assets (at no additional cost),
allowance should be made in earnings. Con­
versely, a decline in the relative price of capital
results in a capital loss and a reduction in
earnings. With no accounting for real capital
gains, rates of return and earnings margins
almost certainly would exhibit a downward
trend during periods of prolonged acceler­
ating inflation such as the 1970s. Replacement
prices of fixed reproducible capital, and espe­
cially land prices, tend to outpace the gen­
eral price level under such conditions. If rel­
ative price movements are the major factor
depressing estimated rates of return through
the margin effect, it is at least arguable that
no meaningful decline occurred.
A number of difficult problems arise in
estimating real capital gains. Usually, no sale
of capital assets takes place so a true picture
of capital gains is unavailable from market
data. Eisner (1980) develops a revaluation ap­
proach to estimating real capital gains. The
carryover capital stock (that portion of the
stock in use from one period to the next)
is valued first at actual replacement prices
and then at a simulated price that is limited
to the increase in the general price level.
The difference between the first and second
of these formulations is an estimate of real
capital gains. Holland and Myers (1979) esti­
mate corporate rates of return that include
real capital gains from revaluations of repro­
ducible capital stocks. These gains raise rates
of return in the early 1950s (increasing the
after-tax rate of return by an average of
2.5 percentage points between 1951 and 1956),
but have less effect thereafter. If revaluations
were included in the rate of return estimates
computed here for the total business sector,
both before-tax and after-tax estimates would
be higher in the 1970s (through 1979) by an
average of 2.5 percentage points.

The larger gains in the 1970s found here,
compared with Holland and Myers’ estimates
(through 1976), reflect the importance of land
in computing capital gains. In the 1970s, when
gains were accruing to both land and repro­
ducible capital, the gains on land accounted
for about 72 percent of the total. However, the
movements in the relative price of reproduc­
ible capital imply substantially smaller gains
in the 1950s, and substantially larger gains
Fig. 5 Constant-Relative-Price Rates
of R etu rn on C apital
P ercent

15

10

5

0

1952

1962

------- AXRC

1972

1982

------- BXRC

Table 1

C apital Productivity Grow th

Period

(potential
output per unit
of capital)

Potential
output

Capital
stock

1952-64

1.88
(0.53)

3.61
(0.10)

1.70
(0.47)

1965-70

0.01
(0.29)
0.95
(0.71)

3.44
(0.09)
3.48
(0.10)

3.43
(0.29)
2.51
(0.71)

Average rate in percent per annum
QK

1971-82

NOTE: Standard deviations are in parentheses.

Federal Reserve Bank of Cleveland



in the 1970s, than those estimated by Holland
and Myers. Apart from differences in the rel­
evant business sectors, and therefore in the
measurement of the variables used to esti­
mate capital gains, differences between out­
put prices used in revaluation and methods of
estimating gains on inventory stocks seem
to account for these results. Eisner’s (1980)
net revaluations of reproducible capital were
generally larger in the 1970s (through 1977)
than those estimated here.
Scanlon (1980) points out that an alterna­
tive approach to revaluation is to assume that
capital and output prices move together, thus
entirely submerging the capital gains ques­
tion. This assumption will not do, of course,
as long as the relative price of capital clearly is
not constant. It may be made operational,
as a counterfactual experiment, by limiting
capital price increases to increases in the
output price, thus creating a synthetic capi­
tal price that remains constant relative to the
output price. Variation in rates of return and
earnings margins that remain must result from
forces other than changes in relative prices.
Before-tax (BXRC) and after-tax (AXRC)
rates of return on capital estimated with a
constant relative price of capital are shown in
figure 5. As expected, constant-relative-price
rates of return are higher than the variable
price estimates for most of the period 1952-82.
The gap widens in the 1970s, indicating that
failure to take account of relative price changes
and potential capital gains that accompany
them is an important force behind the appar­
ent decline in rates of return after 1965. Wider
cycles are evident in BXRC in the 1970s, but
the level is about the same as the 1950s. Indeed,
the bulge in rates of return during the 1960s
stands out in these estimates. The after-tax
measure, AXRC, rises in the 1970s despite
greater cyclical variations.

11. See, for example,
Nordhaus (1974)
and Kopcke (1978).
12. The causal fac­
tors in the capital
productivity decline
are not known with
any precision. Bern­
stein (1980) suggests
“w illful'’and “in ­
escapable” errors in
capital-stock m an­
agement (associated
with increasing atten­
tion given to shortrun profit perfor­
mance in the first
instance, and energy
price increases and
pollution abatement
requirements in the
second) produced
. the wrong stock
in the wrong place
at the wrong time.”
Baxter (1978) fu r ­
ther speculates that
falling research
and development
expenditures and
heightened empha­
sis on replacement
investment may
have aided the de­
cline. No single fac­
tor seems capable of
accounting for the
tim ing of the sharp
decline in 1965
(prior to energy
problems and m an­
dated capital expen­
ditures) and the
partial reversal of
capital productivity
growth after 1970.
This question, part
of the wider mystery
surrounding the be­
havior of produc­
tivity, is left to fu ­
ture research.
13. For a description
of spline functions,
see Poirier (1976).

27

IV. Sources of Change
in Rates of Return

As outlined above, estimating the pattern
of long-term change in the rate of return on
capital generally has been approached by
searching for statistically significant trends
in models that also standardize for cyclical
variation. Results from these efforts have been
mixed and have revealed little about under­
lying sources of change. The trend coefficients
have had no clear interpretation, and sorting
out different short-run trends within a longer
period often has been an arbitrary process.
Advancing beyond simple trend/cycle models
depends on an ability to assign trend effects
in some systematic way to the margin and
multiplier components of the rate of return.
This, in turn, depends on how output price is
determined as a markup over unit costs, which
governs long-term change in the margin, and
on the capital-output relationships that char­
acterize long-term growth paths. Markup rules
and capital-output relationships can be mod­
eled explicitly with considerable rigor.11 In this
study, where isolating the sources of change
in rates of return is of paramount interest, an
approach retaining the simplicity of trend/
cycle models, though enhancing interpretability, is followed.
The behavior of the QK ratio shown in
figure 4 suggests three different regimes of
capital productivity growth: 1952-64,1965-70,
and 1971-82. These regimes are identified in
table 1. It is evident that slower capital pro­
ductivity growth in the periods 1965-70 and
1971-82 is associated with faster growth
in capital stock, the denominator of the pro­
ductivity ratio, in those periods compared
with the 1950s and early 1960s. Potential out­
put grew at about the same rate in all three
periods, despite the acceleration in capitalstock growth. Other researchers, using dif­
ferent methodologies, have found broadly
similar behavior in the relationship between
output and capital. Bosworth (1982) estimated
a capital output ratio adjusted for cyclical
change, and found it rising in the late 1960s
Economic Review • Fall 1984




and 1970s (implying the inverse, comparable
with the QK ratio, fell). Bernstein (1983) noted
a flat capital-output ratio after 1965 for nonfinancial corporations, while Baxter (1978)
measured a declining output-equipment ratio
(without adjustment for the cycle) in manu­
facturing from 1965 on. The major re s u ltfaster capital-stock growth after 1965 did not
produce commensurate increases in potential
output—is the same, which had to depress
rates of return on capital.12
If changes in the rate of growth of capital
productivity identify periods of different
underlying trend growth, rates of return
can be estimated from a linear spline model
(see table 2).13 Trend coefficients in the model
are interpreted as long-term growth rates,
depending on the rate of capital productivity
growth in each period, and the margin drift
that characterizes the behavior of earnings
margins in each period (see appendix 3). Mar­
gin drift accounts for long-term growth in the
earnings margin as determined by the price
markup rule that best approximates pricing
strategy for the aggregate economy. In gen­
eral, margin drift is expected to be greater
than or equal to zero. Thus, estimated trend
coefficients are expected to be greater than
or equal to observed capital productivity
growth in each period.
Estimates of trend coefficients for all rate
of return concepts employed here are shown
in table 2. The coefficients displayed are max­
imum likelihood estimates with first- and
second-order autocorrelation corrections. The
model appears to fit the data veiy well. All
individual coefficient estimates are signif­
icantly different from zero at the 1 percent
level. Estimates of /S4 suggest considerable cyc­
lical sensitivity in rates of return. The elas­
tic response corresponds to the direct effect
from changing output volume (unitary elasti­
city) and the indirect effect of the cycle on
prices and costs in the earnings margin (elas­
tic). An increase in the QQ ratio from reces­
sion levels (95 percent) to boom levels (105 per­
cent) increases rates of return from 30 per­
cent (AXR) to 33 percent (BXRC).

14. I f margin drift
were approximately
constant (not neces­
sarily zero), the sum
of the trend shift
coefficients (fc, @3)
should not differ
significantly from
the differential
in capital produc­
tivity growth rates
between 1952-64 and
1971-82 (appropri­
ately signed). Based
on restricted regres­
sion V-tests, the dif­
ference is statistically
significant (at 5 per­
cent) in variablerelative-price equa­
tions, but not in
constant-relativeprice equations.

The major points of interest are the trend,
coefficients (J3lt 02>P ), and their sums, which
are estimates of underlying growth in rates
of return for the periods 1952-64, 1965-70,
and 1971-82. In 1952-64, the estimates of pl
imply rate-of-return growth ranged from about
1.6 percent a year (BXR) to about 3.5 percent
a year (AXRC). The sharp downward shift
(02) in the late 1960s produced significantly
negative growth rates (/^ + 02) in all mea­
sures of the rate of return in 1965-70. The
shift was reversed (03) in the 1970s, but in
1971-82 only constant-relative-price rates of
return grew at a pace significantly different
from zero (/^ + 02 + 03).
The trend coefficients quantify the com­
bined effects of capital productivity growth
and margin drift on rates of return. Although
the trend shifts were controlled by observed
changes in productivity growth, coefficient
estimates also reveal the importance of margin
drift in determining the course of rates of
return. Quite different growth patterns are
implied by the coefficients estimated from
variable-relative-price and constant-relativeprice measures of the rate of return. To disen­
3

Table 2 M ax im um Likelihood Estimates
of Rate of Return G row th

From the process described in appendix 3, the rate
of return on capital over three regimes of capital
productivity growth may be expressed as follows:
R, R 0TT(l nYQQU,
where
t = time,
r = rM+ (sum of growth rates of earn­
ings margin and capital productiv­
ity ratio),
i = index denoting three periods of capital
productivity growth.
The parameters of this equation—R0, rit and A—are
estimated from a linear spline function:
=

+

1=1

Federal Reserve Bank of Cleveland



tangle the productivity and drift components,
the estimated trend coefficients can be com­
pared with mean values of productivity growth
rates (table 1). That is, the trend coefficient
estimates can be tested against the hypothe­
sis of zero margin drift.
The rate of growth of BXR was significantly
lower than productivity growth alone would
suggest in each of the three periods, imply­
ing negative margin drift over the entire 30
years. Setting aside 1965-70 for the moment,
the appearance of negative drift in these esti­
mates reflects only the increasing relative
price of capital in both 1952-64 and 1971-82,
with a steeper increase, of course, in the latter
period. When holding the relative price con­
stant (BXRC), estimated growth rates in
1952-64 and 1971-82 were significantly greater
than could be accounted for by productivity
growth alone, indicating positive margin drift
and a pricing strategy that does not exclude
rapidly rising unit costs from the markup func­
tion. However, the difference between growth
rates in 1952-64 and 1971-82 is accounted
for by the capital productivity growth differ­
ential between the two periods. Thus, margin

Ini?, = fio + + fcTS + P3TSS
+ 04ln QQt + n,
where
T = linear trend (T = 1, 2 ,..., 31),
TS = shift in trend at 1965 (TS = T-12),
TSS = shift in trend at 1971 (TSS = T-18),
n = random error,
and
00 = \nR0,
01 = ln(l + ri),
02 = shift in 1 + r at 1965,
01-< 02 “ ln(l + r2),
03 = shift in 1 + rat 1971,
01 + 02 HK03 “ ln(l + r3),
04 = X.

15. The early stages
of the labor produc­
tivity slowdown ac­
counted for only a
fraction of the in­
crease in unit labor
compensation rela­
tive to output price in
1965-70 (Okun and
Perry 1970). Rela­
tive increases in the
compensation rate,
perhaps induced by
the long duration of
high capacity utili­
zation, accounted
for the remainder.
Wage -p rice co ntrols,
followed by deep re­
cessions in 1973-75
and 1981-82, could
have curtailed rela­
tive increases in the
compensation rate
and partially offset
even greater deteri­
oration of labor prod­
uctivity in 1971-82.

drift in BXRC was positive, which is accept­
able from the standpoint of pricing strategy,
and also was approximately constant from
1952-64 to 1971-82.14Similar results are implied
by the after-tax trend coefficients. Estimated
growth rates of after-tax rates of return were
higher than their before-tax counterparts
in both 1952-64 and 1971-82, although the
differential narrowed slightly in the 1970s.
Declining tax costs in the 1950s at least kept
AXR growing apace of BXRC, but this cor­
respondence was broken in the 1970s.
The sharp downward shift and the result­
ing negative growth rates in all measures
of the rate of return in 1965-70 cannot be
explained by a combination of changing cap­
ital productivity growth and constant margin
drift. Although capital productivity growth
was essentially zero, it did not become neg­
ative, on average, for the period. Yet even
constant-relative-price rates of return exhib­
ited substantial negative growth rates, sug­
gesting a restructuring of the spreads between
Rate of return

Coefficient

BXR

BXRC

AXR

AXRC

0o

-2.4445*
(0.0136)

-2.4643*
(0.0202)

-2.9279*
(0.0235)

-2.9464*
(0.0185)

01

0.0158*
(0.0016)

0.0255*
(0.0024)

0.0255*
(0.0028)

0.0352*
(0.0022)

02

-0.0602*
(0.0045)

-0.0731*
(0.0066)

-0.0735*
(0.0078)

-0.0873*
(0.0061)

-0.0445*
(0.0032)

-0.0480*
(0.0047)

-0.0480*
(0.0056)

-0.0525*
(0.0044)

03

0.0433*
(0.0050)

0.0685*
(0.0073)

0.0540*
(0.0087)

0.0810*
(0.0068)

01 + 02 + 03

-0.0012
(0.0021)

0.0205*
(0.0029)

0.0060
(0.0036)

0.0285*
(0.0029)

04

2.7749*
(0.1917)

2.8292*
(0.2539)

2.6137*
(0.3245)

2.7753*
(0.2573)

+ 02

R2

0.995

0.898

0.986

0.989

Pa

-0.586

-0.123

-0.818

-0.636

SE

0.032

0.037

0.050

0.045

NOTE: Standard errors are in parentheses.
* = Significant at 0.01.
a. p = Sum of first- and second-order autocorrelation coefficients.

29

Economic Review • Fall 1984




output price and unit costs depressed earnings.
The contribution of price and unit costs to
changes in earnings spreads is illustrated in
table 3. The average annual percentage change
in price is shown in row 1. Share-weighted
changes in unit costs and earnings spreads
then represent the claims on the price increase.
Clearly, the relationships between price and
unit costs have not been constant in the post­
war period. Price increases averaged 1.93 per­
cent in 1952-64 and accelerated to 7.06 per­
cent in 1971-82. Claims represented by other
business payments (UBC) and overhead costs
(UOC) declined, while capital costs (UKC)
increased. These changes were relatively
steady transformations. Unit labor compen­
sation (ULC), however, rose sharply from
39 percent of the price increase in 1952-64, to
53.7 percent in 1965-70, before falling back to
47.2 percent of the price increase in 1971-82.
Given changes in other unit costs, the reduc­
tion in labor’s claim on price increases in
1971-82 was sufficient to restore the before­
tax spread to the relative position in 1952-64.
(About 12.8 percent of the average price in­
crease went into the before-tax earnings spread
in each period.) After-tax spreads were rela­
tively lower in 1971-82 because unit-tax-cost
reductions of the 1950s were not duplicated in
the 1970s. Thus, the late 1960s was a period
when accelerating labor costs were not marked
up sufficiently to maintain a spread suffi­
cient to cover other costs and provide earn­
ings as well.15

V. Summing Up

Rates of return on capital from the early 1950s
through the early 1980s were influenced by
four sets of factors: changes in capital pro­
ductivity growth; changes in the relative price
of capital; changes in margin drift associ­
ated with disturbances in the price-markup
function; and changes in capacity utilization.

An idea of the relative importance of these
factors can be obtained by asking what a
particular rate of return might have been in
1982 had it grown from its initial value along
alternative growth paths where the separate
effects are controlled. This experiment is
illustrated in table 4 for the before-tax rate
of return. The first entry projects the rate of
return along a driftless and cycle-free path
defined by average capital productivity growth
in 1952-64 extended through 1982. The sec­
ond entry allows average productivity growth
to change as observed in the three sub-periods
Table 3

considered in the analysis, while maintain­
ing the zero drift and cycle assumptions of
the first entry. In the third entry, margin
drift is added but the relative price of capital
is held constant. This incorporates the legacy
of the markup failure in the late 1960s. The
fourth entry allows for a variable relative
price and thus illustrates the effects of infla­
tion-induced increases in the relative price of
capital on the rate of return. Finally, in the
fifth entry, the estimate of BXR in 1982 picks
up the cyclical and random fluctuations of
that year.

Price, U n it Cost, and E arnings Spreads

Spread
component

1965-70

1971-82

Percent of
Rate of increase,
percent per year price increase

Rate of increase,
Percent of
percent per year price increase

—
39.0
9.9
6.5
31.8
12.7

3.87
2.08
0.35
0.35
1.15
-0.06
0.02
-0.08

p

1.93
0.75
0.19
0.13
0.61
0.25
-0.02
0.27

t—
1H

QPR
ULC
UBC
UKC
UOC
BXSPRD
UXC
AXSPRD

1952-64
Percent of
Rate of increase,
percent per year price increase

13.7

—

53.7
8.9
9.1
29.6
-1.5
0.4
-1.9

7.06
3.33
0.46
0.80
1.57
0.90
0.12
0.78

—

47.2
6.5
11.3
22.3
12.8
1.7
11.0

NOTE: Unit costs and earnings spreads are share-weighted average increases, where weights are the ratio of the individual cost or spread com­
ponent to price.

Table 4

Before-tax Rates of R eturn in 1982

For alternative growth assumptions
Growth path

1. Defined by average capital
productivity growth 1952-64,
extended through 1982
2. Defined by average capital
productivity growth 1952-64,
1965-70, and 1971-82
3. Defined by growth coefficients
in column 2, table 2
4. Defined by growth coefficients
in column 1, table 2
5. Before-tax rate, 1982

Rate of return,
percent

Federal Reserve Bank of Cleveland



15.5

12.4
11.3
8.0
6.5

It would be stretching this example be­
yond its bounds to claim that a 15.5 percent
before-tax rate of return on capital was an
attainable goal in 1982. Nevertheless, the rates
illustrated in table 4 indicate the nature and
importance of the changes that distinguished
later years from earlier years in the postwar
period. The difference between the rate of
return in line 1 and line 5 is -9 percentage
points, split about equally between margin
effects and multiplier effects. The smaller mar­
gin and multiplier effects, dealing with the

B H H H H B B H B H H B H IH H a n a M B

legacy of an already reserved change in
price-cost relationships and cyclical fluctu­
ations in capacity utilization, clearly are tran­
sitory. Of the larger effects, the margin com­
ponent reflects a permanent erosion in the
rate of return only if the inflationary expe­
rience of the 1970s is a permanent feature of
the U.S. economic environment. Even under
inflationary conditions, if capital gains on the
existing capital stock are counted in business
earnings, the erosion is offset when these
gains are valued on the same terms as cash
earnings. In a disinflationary environment dif­
ferences associated with changes in the rela­
tive price of capital are narrowed. Declining
capital productivity is more difficult to explain.
Because the decline in productivity was asso­
ciated with an acceleration in capital stock
growth after 1965, achieving capital suffi­
ciency or related explanations seem doubtful.
The puzzle to solve here is one of determining
how the U.S. economy managed to wring so
much output growth out of so little capital
stock growth in the 1950s and early 1960s.

is the relevant one. If owners of noncorporate
businesses are to be paid the average wage,
they are compensated partly as managers,
partly as skilled workers, and partly as un­
skilled workers, depending on the character­
istics of the work force embodied in each indus­
try’s average wage.
To extract the labor component from total
noncorporate earnings, some account must be
taken of cyclical and secular changes affect­
ing labor markets. In the corporate sector
workers are laid off in periods of slack de­
mand to reduce or limit the increase of the
wage bill. Wage rates, however, are affected
less by falling demand and usually continue
to rise during recessions. Controlling labor
costs through layoffs distributes the bur­
den of recession to labor income as well as
capital income.
Noncorporate businesses have similar con­
trol of their hired labor force, but not of their
own amalgamated labor services. Owners of
noncorporate businesses do not lose their jobs
during recessions, except those whose firms
fail. Consequently, paying the owners the
average wage during recessions would mean
Appendix 1 Estimating the
that cyclical weakness in the economy falls
Capital Component of
most heavily on their capital earnings. To
Noncorporate Earnings
avoid this incidence, owners of noncorporate
must take a cut in labor income
In the national income and product accounts, enterprises
when
economic
activity and labor market
noncorporate earnings are not divided into
conditions
weaken.
On the other hand, they
labor and capital components. The entry in
may
be
paid
an
“entrepreneurial
bonus” dur­
the accounts for proprietors’ income is simply ing boom periods when labor markets
are
the owners’ total earnings and therefore in­
tight
and
labor
services
in
short
supply.
cludes both a return for their labor services
A second problem encountered in estim at­
and a return on the capital invested in the
ing
division of total noncorporate earnings
businesses. To estimate the labor-capital divi­ intothe
labor
and capital components is asso­
sion of earnings, the noncorporate business
ciated
with
secular changes in labor markets.
sector could be given the same return on capi­
The
natural
rate of unemployment, or the non­
tal as corporations, thus estimating labor
accelerating
inflation
rate of unemployment,
compensation as a residual. Alternatively,
has
risen
since
the
1950s,
and most of the
owners of the noncorporate businesses could
increase
occurred
in
the
late
1960s and 1970s.
be paid the average wage prevailing in their
industry, thus estimating business earnings on
capital as a residual. Here, the second option

Economic Review • Fall 1984



a. See Phillips
(1962). It appears
that one force behind
the turnabout was
growing num.bers
of women and the
young entering the
noncorporate sector,
two groups whose
employment opportu­
nities might be more
severely curtailed
as the natural rate
rises (Fain 1980).

32

One estimate, constructed by Clark (1983,
table 5) for modeling potential GNP, shows
this underlying unemployment rate rising
from 4.5 percent in 1954 to 7 percent in 1978,
before easing slightly in the early 1980s. As
long-term labor market conditions deterio­
rated, the number of full-time partners and
proprietors in the noncorporate sector (re­
ported in the national income and product
accounts) reacted in a curious way. Noncor­
porate business owners declined from 1952 to
1967 at about 2 percent a year, largely as the
result of an exodus from farming that began
in the 1930s. Between 1967 and 1972, the
number of full-time noncorporate owners was
roughly constant, increasing at about 1.5 per­
cent a year thereafter. This change in non­
corporate business formation and retention
slowed the decline in relative (to employ­
ment in private industry) noncorporate own­
ership from about 3.3 percent a year to about
0.5 percent a year on average beginning
in the late 1960s.
One reason why the noncorporate sector
turned around as it did may be that increas­
ing long-term weakness in labor markets dis­
couraged people from a career of working for
wages. When job availability is diminished
on a long-term basis, the noncorporate sector
may serve as the employer of last resort. This
suggests, however, that labor earnings poten­
tial in the noncorporate sector may not be
as great as the average wage implies. Certainly,
the notion of hidden unemployment in the
noncorporate sector is not new, even applied to
highly developed economies.3 If owners of non­
corporate enterprises were paid the average
wage during periods when long-term labor
market conditions are deteriorating, then just
as in the case of cyclical fluctuations the bur­
den of limited earnings capacity would fall
most heavily on the capital component.
To adjust for the effects of cyclical and secu­
lar distortions of the composition of noncor­
porate earnings, we estimated a simple inter­
active model of the ratio of full-time owners

Federal Reserve Bank of Cleveland




of noncorporate businesses to full-time em­
ployees in private industry. Using maximum
likelihood techniques, this employment ratio
was regressed on a time trend and measures of
long- and short-term labor market conditions:
(A.l) InRFTE = -0.0551 - 0.0837T
(0.1681) (0.0059)
+ 0.0517LT- 1.2392L
(0.0052) (0.1618)
+ 0.1090S + e.
(0.0121)

R2 = 0.981p = 0.682S£ = 0.014
(Standard errors are in parentheses.)
where
RFTE = partners and proprietors
devoting substantially full
time to their businesses divided
by full-time equivalent em­
ployees in private industry,
L = measure of long-term labor
market conditions: natural
rate of unemployment divided
by minimum natural rate
achieved in period 1952-82,
S = measure of short-term labor
market conditions: difference
between actual and natural
rates of unemployment divided
by natural rate.
In this model the sum (-0.0551 - 1.2392L)
defines the intercept for each level of the nat­
ural rate of unemployment. The trend com­
ponent (-0.0837T) captures the long-term
decline in the full-time equivalents ratio, and
the interaction term (0.0517L7) retards the
trend rate of decline as the natural rate rises.
The effects of short-term cyclical fluctuations
are captured by (0.1090S).
To estimate the labor component of total
noncorporate earnings, an adjusted full-

b. This admittedly
is somewhat arbi­
trary. It suggests
that any deviation
from the period m in­
im um natural rate,
if uncorrected, dis­
torts the labor capi­
tal division of non­
corporate earnings,
but that the m in­
im um determines
an appropriate base
line division. Several
alternatives were
explored, including
replacing the m in­
im um with a trend
value of the natural
rate, and making
no adjustment at
all. In 1982, the esti­
mate of the before­
tax rate of return
was 6.5 percent. If
a trend value of the
natural rate had
been used, the rate
would have been
lower, 6 . 0 percent;
if no adjustment
had been made, the
estimate would have
been 5.4 percent.
c. In the tax calcu­
lations income mea­
sures were converted
to taxable income
equivalents. The
relationship between
personal income in
the national income
and product accounts
and taxable income
(adjustedgross in­
come) is illustrated
by Hinrichs (1975).
Noncorporate capi­
tal earnings and rent
were approximated
on an A G I basis by
removing the capital
consumption and
inventory valuation
adjustments and all
imputations made
in the national
income accounts.
33

employment equivalents ratio, ARFTE, was
calculated by setting the actual rate of un­
employment equal to the natural rate, and both
equal to the minimum natural rate. That is,
all labor market fluctuations about the mini­
mum natural rate were removed.b The labor
component of total noncorporate earnings
was calculated from ARFTE as follows:
NCLC = (ARFTE * EPI * W)w,
where
NCLC = noncorporate labor
composition,
EPI = full-time equivalent employ­
ees in private industry,
W = average wage, weighted by
distribution of partners and
proprietors by industry,
w - markup on wages for other
labor compensation (pension
and profit sharing).
When ARFTE exceeds RFTE, the owners
of noncorporate enterprises receive the entre­
preneurial bonus (that is, they earn more
than the average wage for their labor ser­
vices); when ARFTE is less than RFTE, their
wages are cut. In the 1970s, the implied wage
cut progressively widened, and by 1982 it
amounted to nearly 30 percent of the average
wage. Even with this allowance for changes
in labor market conditions, capital earnings in
the noncorporate sector declined sharply rel­
ative to labor earnings in the early 1980s. Cap­
ital earnings generally exceeded 30 percent
of total noncorporate earnings prior to 1979.
This proportion fell to an average of 13 per­
cent between 1980 and 1982, and, in the reces­
sion year of 1982, capital earnings were about
3 percent of total noncorporate earnings.
A final problem of estimating the division of
total noncorporate earnings into labor and
capital components relates to taxes. To calcu­
late the after-tax rate of return, taxes also
must be apportioned to labor and capital earn­
ings. The first step here was to estimate the
tax liability on total noncorporate earnings and

Economic Review • Fall 1984




rent. This was done by computing the ratio
of total noncorporate earnings plus rent to
personal income and multiplying the result by
personal taxes paid (federal, state, and local).0
The resulting tax liability then was distrib­
uted to capital (including rents) and labor
according to their proportions in the aggre­
gate. The effective tax rate on capital earnings
was 12.4 percent in 1952 and was relatively
constant until the late 1960s. Thereafter, the
effective tax rate rose to about 20 percent in the
early 1980s. For years when comparisons can
be made, these tax rates are similar to esti­
mates made by other researchers (Kahn 1964).

Appendix 2 Estimates of
Land Prices and Real Values

One of the most challenging problems in con­
structing estimates of the rate of return on
capital is to derive adequate measures of
land. Land is an integral part of the capital
stock, along with inventories and fixed repro­
ducible capital, and business earnings must
be evaluated relative to its value as well as
the value of the reproducible assets. Nom­
inal land value is the product of market price
(which is equal to the replacement price for
nonreproducible assets such as land) and the
quantity of land in use. The analysis of rates
of return developed here requires estimates
not only of nominal land value, for computing
rates of return, but a separation of this value
into price and real value (quantity), for com­
puting the margin and multiplier effects on
rates of return.
Detailed statistical information on land
prices is restricted to farm land (Goldsmith
1982). Past studies of the rate of return filled
the information gap in a variety of ways: by
ignoring land altogether (Lovell 1978); by
linking nominal land value to the value of
structures on the land (Feldstein and Sum­
mers 1977, following Goldsmith 1962 and Den­

d. As an example of
this calculation, in
1980, 710,390 pri­
vate single-family
housing units were
authorized, which
also means 710,390
structures were
authorized, mostly
for owner occupancy.
A t the same time,
53,768 two-family
units were autho­
rized, or 26,884
structures, half of
which were pre­
sumably for rental.
Three or more fa m ­
ily units contributed
39,895 structures,
virtually all for ren­
tal. Thus, there
were 777,169 struc­
tures authorized,
53,337of which were
for rental or busi­
ness use, a ratio of
6.9 percent. See U.S.
Department of Com­
merce, Bureau of
the Census, Housing
Units Authorized
by Building Perm its
and Public Con­
tracts: Annual 1980,
July 1981, table 2 ,
p. 4.

34

ison 1974); by using book-value (historical
price) data from income-tax records (Holland
and Myers 1979); and by combining incometax data, benchmark estimates from propertytax-assessment records, and price distribu­
tion assumptions such as uniform land prices
across sectors (Fraumeni and Jorgenson 1980).
The few attempts to estimate land prices
outside the farm sector (Milgram 1973) have
not produced continuing time series beyond
the limits of the study.
Market value estimates of farm and non­
farm business land recently have been devel­
oped in the Board of Governors (1983) flowof-funds national balance sheets. These data
provide the variables necessary for estim at­
ing rates of return and are the starting point
for separating values into price and real value
components. Acreage in farm production is
monitored and reported by the U.S. Depart­
ment of Agriculture (1983). The data on acreage
allow an average dollar price per acre to be
computed from the market value estimates of
farm land in the flow-of-funds balance sheets.
Thus, real value of the farm land (1972 dol­
lars) and a simple price-relative index can be
computed. The price index increases from
0.321 in 1952 to 3.396 in 1982, an annual rate
of increase of about 8 percent, compared with
about 4 percent for the GNP deflator. The
most rapid increase, of course, took place in
the 1970s. Between 1970 and 1981, the price
index on farm land rose by about 14 percent a
year; in 1982, the price index declined. Real
value of the farm land stock declined by about
0.5 percent a year between 1952 and 1982.
As indicated by the variety of approaches
used in other studies to estimate land values,
only a rough-and-ready approximation of non­
farm land price and quantity components
can be developed. In this study, it is assumed
that all changes in nonfarm business land
use were transfers from agricultural use. This
is approximately true, judging from the little
information available on land transition. An
Agriculture Department photographic inter­
pretation study of land transition in 53 rapidly
growing counties throughout the United States
between 1961 and 1970 indicated that over
Federal Reserve Bank of Cleveland




90 percent of the land entering nonfarm bus­
iness use, including forests, was withdrawn
from agricultural use (Zeimetz 1976). It is
not certain, of course, that data drawn from
such a small sample is representative of the
United States as a whole, but it is likely that
land transition has been concentrated in
fast-growth areas.
From transition matrixes compiled from
the photographic evidence, it appears that the
transition rate from agricultural to commer­
cial and industrial use was about 20 percent;
that is, for every 100 acres withdrawn from
agriculture, 20 acres was shifted into com­
mercial and industrial use. The highest tran­
sition rate (58 percent) was into residential
use and another 18 percent of the loss in agri­
cultural land was diverted into transporta­
tion and recreation uses. Commercial and
industrial businesses include a large propor­
tion of total business enterprises, but do
not exhaust the total. Some portion of the
land transferred to transportation and recre­
ation uses may represent a business gain,
but the largest exclusion is the rental compo­
nent of the residential transfer.
An examination of housing units authorized
since the mid-1960s suggests that an average
of about 6.5 percent of new structures was
multi-family dwellings.d Multi-unit structures
naturally are more land-intensive than single­
unit structures. Two-family structures may
use only marginally more land, while large
apartm ent buildings can use several times the
land of the typical single-family home. There
is no way of precisely determining intensity
differentials, but an intensity coefficient of 2
was used here. This assumes two-family struc­
tures are equal to single-family structures in
land use, three- and four-family structures
are twice as land-intensive, and five- or more
family structures are three times as land­
intensive. Thus, about 13 percent of the land
transferred into residential use should be
counted in the business sector. This raises
the transition ratio from 20 percent to 28 per­
cent, and implies a total transition to non­

farm business use of about 47 million acres
between 1952 and 1982.
A survey of private landownership in 1978
indicated that nonfarm land in some form
of business organization (proprietorship, part­
nership, or corporation) amounted to about
30 percent of the land in farm use (see USDA
1979). From the farm acreage data cited above,
this would imply about 312 million acres in
nonfarm business use in 1978. Using the tran­
sition ratio of 28 percent and the estimates
of changes in farm acreage, nonfarm business
land acreage can be estimated for 1952-82.
From the market-value balance-sheet esti­
mates, the price index and real value compo­
nents also can be constructed. In 1972, the
estimated average price per acre of nonfarm
business land was $886.70, nearly 5 times the
average price of farm land. The price index of
nonfarm business land increased from 0.416
in 1952 to 2.779 in 1982, implying an annual
rate of increase of about 6.5 percent. The real
value of nonfarm business land increased by
about 0.5 percent a year. Although estimates of
nonfarm business land prices are consider­
ably higher than farm land prices, the rate of
increase is less rapid, though still faster than
the rate of increase in the GNP deflator. This is
reasonable if improvements to the land limit
the price inflation.

Appendix 3 A Technical Note
on Margin Drift

Consider rate-of-return behavior as a growth
process:
(A.2) Rt = Ro(l + r)‘QQ)e,
Rt - rate of return in current period,
Rq = rate of return in base period,
r = “normalized” (invariant with
respect to cyclical and random
disturbances) growth rate,
QQ)t = allowance for cyclical and
random movements in R
(e > 0 fluctuates randomly
about 1).
From the definition of equation (3) in the
text, the rate of return also is expressed as the
Economic Review • Fall 1984



product of the earnings margin (M) and the
earnings multiplier (m), and the rate of growth
(r) can be viewed as the sum of the growth
rates of these two components.
(A.3) r = rM+ rm
-

rM

+

yqq

+

yqk -

In the sense of a normalized long-term
growth rate, the middle term in equation (A.3)
is zero. The capacity ratio rises and falls as
the economy moves through expansion and re­
cession phases of the business cycle (these
effects on the rate of return are captured by
QQKin equation (A.2)), but does not grow over
time. In the long term, only contributions from
the margin and capital productivity influence
rate-of-return growth. This can be shown
directly as follows: Let Ro be defined such
that QQo = 1 (i.e., the initial value is a fullemployment level). From equations (3) and (4)
in the text, the normalized growth rate of
the rate of return must be:
<A'4) (1 + rV = MrRQoQQKe
£ K‘The earnings margin and capital productivity
have grown from the base period at normal­
ized rates of tm and tqk, respectively. In addi­
tion, the margin fluctuates cyclically and
randomly, while capital productivity fluctu­
ates randomly about its normalized growth
path. Thus,
(A.5) (1 + r)f
= [Mp(l + rMyQQat u]QQt[QKo(l + rQK)‘w]
0

RoQQ/ e

= (1 + rM)l(1 + rQKy,
where
t = uw,
k = (1 + a), a > 0.
Thus,
(A.6) r = rM+ rQK + rMrQK,
where
rM rQK ~ small second-order effects.

The question now becomes one of deter­
mining the nature of long-term growth in the
earnings margin and capital productivity.
Once cyclical and random movements in the
margin are accounted for, a nonzero drift may
remain, depending on the price markup rule
that best approximates pricing strategy for
the aggregate economy. To illustrate margin
drift, consider the case where the relative
price of capital is held constant (as in BXRC
and AXRC), and output price is determined
as a markup on a subset of total unit costs
(for example, unit labor costs). Unit costs are
normalized for cyclical and random variation
in the markup function, and the earnings
margin corresponding to the growth rate rM
would be defined as follows:
(A.7) Mt
= (1 +/>)(! + g j ) t U io - { 1 + g t) l U io - ( 1 + g e ) ‘ Ueo

(1 +/>)(1 +gi)tUio

where

p = price markup,
Ui = unit costs included in markup
function (subscript 0 denotes
base period),
gi = growth rate of included unit costs,
Ue = normalized unit costs excluded
from markup function,
ge = growth rate of excluded unit costs.
The continuous change in the normal mar­
gin with respect to time is given by
(A-8) at

r

-U eo

1

L (i+ » « J
X [ln(l + ge) - ln(l + gi)]

X
If growth rates of unit costs and the price
markup are constant, the following possibili­
ties characterize change in the normal margin

Federal Reserve Bank of Cleveland




, v ~dM
n If. , ge = gi.
(a)
jF = 0,
dM > if Se < gi,
dt — 0, as / increases.
(c) dM < 0, if e > g i,
dt — -00, as t increases.
In case (a), no drift in the earnings margin
is indicated; hence, the normalized growth
rate (rM) would be zero. In case (b), however,
a positive drift is indicated, gradually becom­
ing smaller over time. When the difference
between growth rates of included and excluded
unit cost is fairly small, margin drift is also
small but narrows very gradually (i.e., approx­
imately constant for relatively long periods).
Finally, if those unit costs excluded from
the markup function grow faster than included
unit costs, as in case (c), the normal margin
would continuously deteriorate over time.
This could not be descriptive of pricing strat­
egy over any extended period, but it could
describe a transition period of price-cost re­
alignment. Negative drift would be possible
in variable relative-capital-price margins, even
if g i> g e- Increases in the replacement price
of capital pull the margin down; the faster
the capital price rises relative to the output
price, the more likely the possibility of nega­
tive margin drift.
(b)

8

References

Baxter, John D. “W hat’s Behind Falling Prod­
uctivity of Equipment?” Iron Age, Decem­
ber 11, 1978, pp. 27-30.
Bernstein, Peter L. “Capital Stock and Man­
agement Decisions,” Journal of Post Keynes­
ian Economics, Fall 1983, pp. 20-38.
Board of Governors, Federal Reserve System.
Balance Sheets for the U. S. Economy
1945-82. Washington, DC: October 1983.
Bosworth, Barry P. “Capital Formation and
Economic Policy,” Brookings Papers on
Economic Activity, 2:1982, pp. 273-326.
Cagan, Phillip, and Robert E. Lipsey. The Fi­
nancial Effects of Inflation. Cambridge, MA:
Ballinger Publishing Company, 1978.

Clark, Peter K. “A Kalman Filtering Approach
to the Estimation of Potential GNP,” Pro­
cessed. Revised, November 1983.
Denison, Edward F. Accounting for United
States Economic Growth 1929-1969. Wash­
ington, DC: Brookings Institution, 1974.
Eisner, Robert. “Capital Gains and Income:
Real Changes in Value of Capital in the
United States, 1946-77,” in Dan Usher, Ed.,
The Measurement of Capital. Chicago: Uni­
versity of Chicago Press, 1980, pp. 175-342.
Fain, T. Scott. “Self-employed Americans:
Their Number Has Increased,” Monthly
Labor Review, November 1980, pp. 3-8.
Feldstein, Martin S., and Lawrence Sum­
mers. “Is the Rate of Profit Falling?”
Brookings Papers on Economic Activity,
1:1977, pp. 211-27.
Fraumeni, Barbara M., and Dale W. Jorgen­
son. “The Role of Capital in U.S. Economic
Growth, 1948-1976,” in George M. Von
Furstenberg, Ed., Capital, Efficiency, and
Growth. Cambridge, MA: Ballinger Publish­
ing Company, 1980, pp. 9-250.
Goldsmith, Raymond W. The National Wealth
of the United States in the Postwar Period.
Princeton: Princeton University Press, 1962.
______ The National Balance Sheet of the
United States 1953-1980. Chicago: Univer­
sity of Chicago Press, 1982.
Hinrichs, John C. “The Relationship between
Personal Income and Taxable Income,”
Survey of Current Business, February 1975.
Holland, Daniel M., and Stewart C. Myers.
“Trends in Corporate Profitability and
Capital Costs,” in Robert Lindsey, Ed., The
Nation s Capital Needs: Three Studies. New
York: Committee for Economic Develop­
ment, 1979, pp. 103-88.
Kahn, C. Harry. Business and Professional In­
come Under the Personal Income Tax. Prince­
ton, NJ: Princeton University Press, 1964.
Kopcke, Richard W. “The Decline in Corpo­
rate Profitability,” New England Economic
Review, Federal Reserve Bank of Boston,
May/June 1978, pp. 36-60.
Economic Review • Fall 1984



Lovell, Michael C. “The Profit Picture: Trends
and Cycles,” Brookings Papers on Economic
Activity, 3:1978, pp. 769-88.
Milgram, Grace. “Estimates of the Value of
Land in the United States Held by Various
Sectors of the Economy, Annually, 1952 to
1968,” in Raymond W. Goldsmith, Ed., Insti­
tutional Investors and Corporate Stock—A
Background Study, New York: Columbia
University Press, 1973, pp. 343-77.
Nordhaus, William D. “The Falling Share of
Profits,” Brookings Papers on Economic
Activity, 1:1974, pp. 169-208.
Okun, Arthur M., and George L. Perry. “Notes
and Numbers on the Profits Squeeze,”
Brookings Papers on Economic Activity,
3:1970, pp. 466-72.
Phillips, Joseph D. The Self-employed in the
United States. Urbana, IL: University of
Illinois Press, 1962.
Poirier, Dale J. The Econometrics of Structural
Change. Amsterdam: North-Holland Pub­
lishing Company, 1976.
Runyon, Herbert. “Profits: A Declining Share
to Capital?” Business Economics, vol. XIV,
no. 4 (September 1979), pp. 85-94.
Scanlon, Martha S. “Postwar Trends in Cor­
porate Rates of Return” Public Policy and
Capital Formation. Board of Governors of
the Federal Reserve System, April 1981,
pp. 75-87.
U.S. Department of Agriculture, Who Owns
the Land? A Preliminary Report of a U.S.
Landownership Survey, September 1979.
U.S. Department of Agriculture, Economic
Indicators of the Farm Sector. Income and
Balance Sheet Statistics, 1983.
Walton, John. “Capital Maintenance and the
Measurement of Corporate Income,” Re­
view of Income and Wealth, series 27, no. 2
(June 1981), pp. 109-35.
Zeimetz, Kathryn A., et al. Dynamics of Land
Use in Fast Growth Areas, U.S. Department
of Agriculture, April 1976.

This working
paper complements
James G. Hoehn and
William C. Gruben,
with Thomas B.
Fomby, Some Time
Series Methods of
Forecasting the
Texas Economy,
Working Paper
8402, Federal Re­
serve Bank of Dallas,
May 1984. James G.
Hoehn is an econo­
mist with the Fed­
eral Reserve Bank
of Cleveland.

1. Anderson, Paul A.

"Help for the Re­
gional Forecaster:
Vector Autoregres­
s i o n Quarterly
Review, Federal Re­
serve Bank of M inne­
apolis, vol. 3, no. 3
(Summer 1979),
pp. 2-7; and Kuprianov, Anatoli, and
William Lupoletti.
“The Economic Out­
look for Fifth Dis­
trict States in 1984:
Forecasts from Vec­
tor Autoregression
Models,” Economic
Review, Federal
Reserve Bank of
Richmond, vol. 70/1
(January/February
1984), pp. 12-23.
2. Ashley, Rich­
ard A., C.W.J.
Granger, and
R. Schmalensee.
‘Advertising and
Aggregate Con­
sumption: An
Analysis of Cau­
sality,” Econometrica, vol. 48,
no. 5 (1980),
pp. 1149-67.

38

Working Paper
Review
James G. Hoehn
A Regional Economic Forecasting
Procedure A pplied to Texas

Working Paper 8402.
September 1984. 45 pp. Bibliography.

In this paper economist James G. Hoehn pro­
poses and implements a relatively simple
method for building a multivariate autore­
gressive forecasting model for regional eco­
nomic time series. The method used is a time
series approach requiring little a priori or
theoretical knowledge, as in the building of
structural econometric models. In this way, the
method is similar to the so-called vector auto­
regression (VAR) models of Anderson and
Kuprianov and Lupoletti.1However, the way
variables are chosen to be included and the
way relationships are estimated involve more
hypothesis tests and less prior knowledge.
We applied the method to the problem of
forecasting quarterly growth rates of seven
Texas variables that were seasonally adjusted.
Each of the seven variables was related to
its own past two observations in a simple re­
gression equation to determine whether lagged
values would aid forecasts. Then, two lagged
growth rates of other regional and national
variables were added to the equation to con­
struct Granger causality tests. Such tests sug­
gested whether inclusion of the other regional
and national variables was likely to improve

Federal Reserve Bank of Cleveland




forecasts. After the series of causality tests
was completed, a list of variables was sug­
gested as likely candidates for inclusion in
the forecasting equation for each Texas vari­
able. This list was trimmed, and lag speci­
fications were chosen, using the criteria of
minimizing the standard error of the equa­
tion and the principle of parsimony. The re­
sulting equations, although chosen on statis­
tical grounds alone, conformed reasonably
well to intuitions about the regional economy
and its relations with the national economy.
Of 14 national variables tried, inclusion of
4 appeared to capture most of the information—
the index of leading indicators, the index of
coincident indicators, the producer price index,
and the federal funds rate.
Out of sample, the model was found to
forecast consistently better (lower root mean
square error) than benchmark univariate
autoregressive integrated moving average
(ARIMA) models, sometimes substantially bet­
ter. In some cases, the improvement was sta­
tistically significant at the 0.05 level, despite
the shortness of the forecasting sample, accord­
ing to a test adapted from Ashley, Granger,
and Schmalensee.2 The model was reasonably
stable as re-estimated over the out-of-sample
period, and its forecasts could not be system­
atically improved by combining them with
ARIMA forecasts.
The results of the study are subject to a
number of caveats common to statistical
studies. Nevertheless, results suggest that
the proposed forecasting procedure can pro­
vide systematically better forecasts than uni­
variate ARIMAs. Such systematically better
forecasts apparently have not been delivered
by the complex simultaneous equation models
or by other time series methods. The proce­
dure proposed requires only ordinary least
squares regressions. A by-product of model
building is insight into the regional economy
and the strength of various leading relation­
ships in the data. The method can easily
be applied to other regional economies, and
we have begun building a model for Ohio.

The working paper
series is published
by the Research
Department of the
Federal Reserve
Bank of Cleveland
to stimulate discus­
sion and critical
comment. Copies
of worki ng papers,
either future or past
issues, are avail­
able through our
Public Inform a­
tion Department,
Federal Reserve
Bank of Cleveland,
PO. Box 6387, Cleve­
land, OH 44101;
(216) 579-2048.

Working Paper
Series

8304
Forecasting the Money S upply in
Time Series M odels
Michael L. Bagshaw and William T. Gavin

December 1983, 23 pp.
8101
The W elfare Im plications of A lternative
U n em plo y m ent Insurance Plans

Mark S. Sniderman
April 1981, 20 pp.
8201

M u ltib a n k H olding C om pany O rg an iza­
tional Structure and Perform ance

Gary Whalen
March 1982, 30 pp.
8202

S tability in a M odel of StaggeredReserve A ccounting

Michael L. Bagshaw and William T. Gavin
August 1982, 27 pp.
8203
A M icro View of the Transactions
M oney M arket

Mark A. Zupan
September 1982, 31 pp.
8301

Non-Nested Specification Tests and the
In term e diate Target for M onetary Policy

Mitsuru Toida and William T. Gavin
June 1983, 14 pp.
8302

H olding Com pany O rganizational
Form a nd Efficiency

Gary Whalen
July 1983, 20 pp.
8303

Extension of G ranger C ausality in
M ultivariate Time Series M odels

Michael L. Bagshaw
August 1983, 11 pp.

8401
Economic Estim ates of U rban
Infrastructure Needs

Paul Gary Wyckoff
June 1984, 36 pp.
8402

A Regional Economic Forecasting
Procedure A pplied to Texas

James G. Hoehn
September 1984, 45 pp.
8403

Forecasting Using Contem poraneous
Correlations
Michael L. Bagshaw

September 1984, 17 pp.

8404
D ollar Intervention and the
Deutschem ark-D ollar Exchange Rate:
A D aily Time-Series Model

Owen F. Humpage
September 1984, 28 pp.
8405

Velocity: A M ultivariate
Time-Series A pproach
Michael L. Bagshaw and William

November 1984, 29 pp.
8406

M onetary Policy a nd Real
Interest Rates: New Evidence
from the Money Stock Announcem ents

William T. Gavin and Nicholas V. Karamouzis
December 1984, 43 pp.
8407

M onetary Policy Regimes: A Synthesis
of the M onetary Control a nd R atio nal
Expectations Literatures

James G. Hoehn
December 1984, 60 pp.

39

Economic Review • Fall 1984




T. Gavin

Economic Review
is published quar­
terly by the Research
Department of the
Federal Reserve Bank
of Cleveland. Copies
of the issues listed
here are available
through our Public
Information Depart­
ment, 216/579-2048.

Economic Review
Winter 1983

“Location and Reinvestment:
The Youngstown Steel District”
Robert H. Schnorbus
“Thrifts and the Competitive Analysis
of Bank Mergers”
Paul R. Watro
Working Paper Review:
Stability in a Model of Staggered Reserve Accounting
Michael L. Bagshaw and William T. Gavin
Spring 1983

“Money Demand: Cash Management
and Deregulation”
John B. Carlson
“Divisia Monetary Aggregates: Would They
Be More Palatable than the Traditional
Simple-Sum Stews?”
Mark A. Zupan

Fall 1983

“Plant Closings and Worker Dislocation”
Daniel A. Littman and Myung-Hoon Lee
“Prevailing Wage Laws, the Federal
Reserve, and the Service Contract Act”
Mark S. Sniderman
Working Paper Review:
Forecasting the Money Supply
in Time Series Models
Michael L. Bagshaw and William T. Gavin
Winter 1984

“Reflections on Money and Inflation”
William T. Gavin
“The Outlook for Inflation”
K.J. Kowalewski and Michael F Bryan
Spring 1984

“Estimating Infrastructure Needs:
Methods and Controversies”
Paul Gary Wyckoff
“Nonbanking Operations of
Bank Holding Companies”
Gary Whalen
Summer 1984

“The Implementation of Industrial Policy”
Daniel A. Littman
“Voluntary Export Restraints:
The Cost of Building Walls”
Michael F. Bryan and Owen F. Humpage
Working Paper Review:
Dollar Intervention and the DeutschemarkDollar Exchange Rate: A Daily
Time-Series Model
Owen F. Humpage

Federal Reserve Bank of Cleveland