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Federal Reserve Bank of Cleveland
Economic Review




ISSN 0013-0281

Summer 1981

Summer 1981
Federal Reserve Bank of Cleveland
Economic Review
Contents
The New Procedure...................................................................................................1
E.J. Stevens discusses the new procedure introduced by the Federal Reserve
in October 1979 to achieve money-growth objectives, focusing on the supply
of nonborrowed reserves. Weekly nonborrowed-reserve objectives accom­
modate expected seasonal and some offsetting week-to-week variations in the
demand for money. Otherwise off-target money growth is accommodated only
through the discount window, with consequent repercussions on the federalfunds rate and other rates. Persistent deviations of money from target auto­
matically cause interest-rate movements that tend to counteract the devi­
ations, reinforced or dampened by discretionary adjustments in the non­
borrowed-reserve objective and the discount rate. Experience with the new
procedure in 1980-81 demonstrates the willingness of the Federal Open
Market Committee to tolerate substantial interest-rate variations to achieve
noninflationary money growth.
Mortgage Redlining: Some New Evidence........................................................ 18
Despite the passage o f several laws in the past decade to outlaw discrimi­
nation in credit markets, the U.S. regulatory and judicial bodies are still
struggling to agree on a precise definition of discrimination and how it can
be prevented. Some financial institutions, particularly those in urban areas,
have been accused o f severely restricting their mortgage-lending activity
in certain poor and/or black neighborhoods—a practice referred to as redlining.
Focusing on Cleveland, Ohio, authors R obert B. Avery and Thomas M. Buynak
examine the empirical relationship between mortgage lending and neigh­
borhood racial characteristics, controlling for demand and risk factors.

Economic Review is published quarterly by the Research Department of the Federal
Reserve Bank of Cleveland, P.O. Box 6387, Cleveland, Ohio 44101. Telephone: (216)
579-2000. Editor: Pat Wren. Graphics: Mike Whipkey. Typesetting: Sally Chunat.
Opinions stated in the Economic Review are those of the authors and not necessarily
those of the Federal 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 materials to the editor.



The New Procedure
by E.J. Stevens
The Federal Reserve began setting money-growth
targets in 1970. Dissatisfied with its marksmanship
in the 1970s, it introduced a new procedure for
achieving money-growth targets in October 1979.
Because the Federal Reserve does not issue all of the
money it seeks to control, it must employ a tech­
nique that will induce the public—
including con­
sumers, businesses, banks, and other deposit-issuing
institutions—to demand and supply the targeted
quantity of money. The Federal Open Market Com­
mittee (FOMC) sets policy at periodic meetings
during the year, typically choosing long-term (fourthquarter to fourth-quarter) money-growth targets at
two meetings and shorter-term target paths at each
meeting. Instructions from these meetings guide daily
open-market operations of the trading desk as it
manages the supply o f depository-institution reserves.
A major difference between the old and new proce­
dures lies in the form of these instructions, contained
in the FOMC policy directives.1
This article describes the new reserve-targeting
procedure, briefly characterizes policy implementa­
tion with the procedure in 1980-81, and examines
some suggested modifications to the procedure.

I. Old and New: An Overview
Prior to October 1979, the FOMC directed the
trading desk to maintain the federal-funds rate within
a narrow band estimated by the FOMC to be con­
sistent with desired money growth. In addition, the
directive specified how the trading desk should adjust
1. The policy directive issued at an FOMC meeting is con­
tained in the “Record of Policy Actions of the Federal Open
Market Committee” released on the Friday following the
next meeting and published in the Federal Reserve Bulletin.



the level of the funds rate when incoming informa­
tion showed a deviation of money growth from a de­
sired range. The rationale for using the funds rate to
control money growth was that variations in this
interest rate indicate variations in the price of holding
non-interest-bearing and flxed-rate money balances.
An increase in the funds rate and associated moneymarket rates thus tends to reduce money demand
and retard money growth, while a decrease has the
opposite effect.
The old procedure for controlling money growth
riveted the attention of both the Federal Reserve
and the financial markets on the funds rate. If the
rate tended to drift up or down during the day and
the trading desk responded by adding or withdrawing
reserves, then the market was able to infer the desired
funds rate. If, on the other hand, the rate were al­
lowed to move up or down to a new trading range
w ithout intervention, or if the desk intervened to
move the rate to a new range, then the market had
a signal that the desired funds rate was changing. In this
way, market participants’ expectations about moneymarket conditions and money growth were contin­
uously reinforced or changed by policy operations.
Under the old procedure the funds rate tended to
move too slowly to maintain money growth within
target ranges. By the time the funds rate moved up
or down enough to correct deviations of money
growth from a range around the target path, cum­
ulative deviations from the path were large and
targets often were missed.
The new procedure focuses day-to-day on the
quantity of nonborrowed reserves rather than the
level of the funds rate. The FOMC establishes longE.J. Stevens is an economic advisor with the Federal Reserve
Bank o f Cleveland.

2

Economic Review □ Summer 1981

run and short-run money targets, as before, and indi­
cates a broad federal-funds rate range that is thought
to be consistent with those targets. However, the
FOMC specifies neither a level of the funds rate to be
maintained when money growth is on the desired
path, nor an am ount by which the funds rate should
move if money growth deviates from that target path.
Instead, the trading desk is directed to maintain a
supply o f nonborrowed reserves estimated to be
consistent with the target path for money growth and
a residual am ount of discount-window borrowing. If
actual money growth turns out to be above or below
the FOMC’s target path, targeted nonborrowed
reserves will supply a smaller or larger portion of total
reserve demand. In effect, the new procedure requires
that reserve needs caused by above-target money
growth be financed at the discount window, while
shortfalls of reserve needs caused by below-target
money growth reduce the am ount depository institu­
tions must borrow at the discount window. Given the
demand for required reserves and some demand for
excess reserves, borrowed reserves must make up the
difference between the targeted supply of nonbor­
rowed reserves and the demand for total reserves.
Emphasis on the quantity of nonborrowed reserves
does not mean that policy actions have no influence
on interest rates in general, or the funds rate in partic­
ular. When money grows at a rate different from the
target rate, adherence to a predetermined path for
nonborrowed reserves implies that interest rates
will be forced up or down in the market for bank re­
serves. For example, when money runs above target,
reserve demands expand, and reserves must be ob­
tained from the window. This causes the funds rate
to rise because, given the limited amount and fre­
quency o f adjustment credit the Federal Reserve
will extend to any borrower, institutions are reluc­
tant to borrow from the discount window and would
rather borrow in the federal-funds market even at
a higher interest rate. The larger the am ount of ad­
justm ent borrowing that institutions must do, and
the longer they must do it, the larger is the premium
they are willing to pay in the funds m arket, as mea­
sured by the spread o f the funds rate above the dis­
count rate, in order to avoid further borrowing from
the discount window (see figure 1).
Thus, a major difference between the old and
new procedures is the way the funds rate is deter­



mined. Rather than having the trading desk maintain
a target level of the funds rate through open-market
operations, the new procedure relies on the market to
establish the funds rate. The rate settles at whatever
spread above or below the discount rate is required to
overcome the reluctance of reserve-holding institu­
tions to borrow an am ount from the discount win­
dow equal to the difference between their aggregate
demand for total reserves and the supply of nonbor­
rowed reserves.
Major features of the new procedure are the de­
termination of the quantities of both total and
nonborrowed reserves for a reserve-requirement main­
tenance period (currently one week) and the funds
rate (see figure 2). The simple framework in figure 2
illustrates how the funds rate is determined in the
short run, but not how money targets are achieved in
the longer run. Essentially, the quantity of nonbor­
rowed reserves and the level of the discount rate must
be managed over a series of many weeks so that the
funds rate and related money-market rates will pro­
duce the targeted quantity of money. The details
of this management process describe monetary
policymaking under the new procedure.

II. The Details
Mechanics of policymaking under the new proce­
dure can be described in five steps, each step repre­
senting a translation of policy from less to more
specificity. Step one translates FOMC economic
policy into money-growth target ranges for a year.
Step two translates those annual-growth ranges into
a target path for seasonally adjusted levels of the
monetary aggregates for the time period between
FOMC meetings. Neither of these first two steps
differs substantially from the old procedure, but
the next three do. Step three translates targeted
money paths into an objective for the average nonseasonally adjusted level of total and nonborrowed
reserves for the inter-FOMC meeting period. Step
four translates those inter-meeting objectives into
a trading desk supply objective for the average level
of nonborrowed reserves in a reserve-maintenance
week. Step five translates that weekly objective
into a daily program for open-market operations
of the trading desk in the money market.

Federal Reserve Bank of Cleveland

Fig.l Discount Window Borrowing and the Rate Spread
Data plotted m onthly
Billions o f dollars

The association between discount borrowing and the rate spread that was apparent under the old
procedure has continued under the new procedure, although the direction of causality has been
reversed. Prior to October 1979, the FOMC determined the funds rate, and, given the discount rate,
a higher rate spread overcame reluctance to borrow; the rate spread determined borrowing. Since
then, the FOMC has determined the nonborrowed-reserve path. Given the demand for reserves in the
short run, a higher need for borrowed reserves forces the funds rate to rise; the aggregate amount of
borrowing determines the rate spread.



3

4

Economic Review □ Summer 1981
Fig. 2 The Federal Funds Rate
Given a demand for total reserves, T R greater
than the supply o f nonborrowed reserves maintained
by the desk, N B R *, and given the discount rate,
R D q , there is some level of the funds rate, R F q ,
that would equilibrate the market for reserves in a
reserve-maintenance week by overcoming the reluc­
tance of institutions to borrow at the discount win­
dow.1 This relationship is shown as TRS . Discount
borrowing would equal T R Q - N B R *.
Clearly, both the level of the funds rate and the
am ount o f borrowed reserves depend on the setting
of the policy instrum ent, N B R *, as well as on the
level o f the discount r a t e , / ^ . For example, suppose
TR® and N B R * were unchanged but the discount
rate were not R D q but a lower rate, R D l - The re­
lationship between the funds rate and the quantity
of reserves to be borrowed would shift down to
c
T R X, because it would take a lower funds rate to
overcome reluctance to borrow any given amount of re­
serves at the lower discount rate. The equilibrium
1. 77?^ is drawn as a vertical line on the assumption that the
interest elasticity of demand for total reserves is negligible
within a reserve maintenance week. Lagged-reserve accounting
assures that the required reserve component of total reserves
is completely interest inelastic during the reserve period; de­
posits two weeks ago cannot be altered this week. If 77? Qis
not vertical, it must reflect the interest elasticity of excess
reserves: this would impart only a slight degree of curvature
to 77?Q because excess reserves normally total less than
,
1 percent of total reserves.

funds rate would therefore be R F l , a lower rate
than R F q because of the lower discount rate. Al­
ternatively, suppose the discount rate were at the
original level, R Dq , and demand for total reserves
were unchanged at TR® but that the trading desk
maintained a larger quantity of nonborrowed re­
serves, N B R *. The resulting funds rate is much
the same as that from a reduction in the discount
rate. Given the demand for total reserves, the
equilibrium funds rate would be lower, reflecting
the smaller amount of borrowing to be induced.

Step One

Step Two

This step is the FOMC process of setting target
ranges for growth o f money and credit aggregates.
The Full Employment and Balanced Growth Act
of 1978 (Humphrey-Hawkins) requires that these
target ranges be reported to Congress each year in
February. An update of the current year’s targets
and a preliminary view of the following year’s tar­
gets are presented in July of each year. Reflecting
uncertainty about the exact relationship between
money and economic conditions and about the pre­
cision of monetary control, these targets are ex­
pressed as a range within which growth rates of
aggregates should He, expressed on a fourth-quarter
to fourth-quarter basis (see figure 3).

The FOMC chooses a short-run target path for
one or more monetary aggregates (M). Each is related
to the annual-target range for that M and is consistent
with the comparable path selected for every other tar­
geted M. A short-run money target implies a time
path of interest rates likely to be consistent with
growth of money demand at the target rate.
The FOMC has considerable discretion in choosing
short-run target paths at FOMC meetings during the
year. For example, if the FOMC started a year by
targeting the midpoint of the long-run range, but
money growth substantially exceeded that path
one quarter into the year, then the FOMC could
adopt a short-run target path to regain the original




Federal Reserve Bank of Cleveland

5

growth only rarely follows the short-run target paths.
Nonetheless, under present procedures, deviations of
actual money growth from short-run paths auto­
matically trigger market reactions, tending to return
money growth to path. The next three steps define
those reactions.
Step Three

path anywhere from one quarter to three quarters

later. Alternatively, the FOMC could adopt a shortrun path that never regained the m idpoint, but re­
mained within the original target-growth range.
The choice among alternative short-run paths pre­
sumably reflects some judgment about the actual situ­
ation, such as whether a strengthening real economy
or shifting demands for financial instruments were at
work, or whether it would be too costly to achieve
a desired adjustment in money within the remaining
months of the year. The possibilities for short-run
paths are illustrated by actual M-1B paths for inter­
meeting periods chosen by the FOMC during 1980-81
(see figure 4).
Short-run target paths link policy actions and
actual money growth during the course of the year
to the target range for money growth over the whole
year. Because money growth does not respond
quickly to reserve-management operations, money



The two preceding steps occur in the FOMC,
both organizationally and chronologically prior to
involvement of the trading desk. These steps usually
result in three decisions that define FOMC policy
over an inter-meeting period: the short-run target
money path for M-1B; an initial assumption about
residual borrowing; and a federal-funds rate range.
The first two are the basis for constructing a nonborrowed-reserve path to guide inter-meeting openmarket operations of the trading desk. The funds-rate
range provides a trigger for FOMC reconsideration of
m oney, total reserve, and nonborrowed-reserve
target paths if expectations about market conditions
at the time of the meeting are not fulfilled: if the
average funds rate threatens to fall outside the stipu­
lated range, then the desk notifies the chairman.2
The short-run path for money growth is trans­
lated into a path value for the average level of total
reserves during an inter-meeting period. Predeter­
mined seasonal factors are used to derive the inter­
meeting average and weekly non-seasonally adjusted
target paths of money and total reserves from the
seasonally adjusted money path in the FOMC direc­
tive. The non-seasonally adjusted total-reserve path is
obtained after projecting the currency component of
2. Until December 1980 the directive indicated that the
FOMC sought reserve aggregates consistent with its money
targets, provided that the weekly average federal-funds
rate remained within a stipulated range. Starting in De­
cember 1980, the directive specified that if fluctuations
in the federal-funds rate “taken over a period of time”
within the stipulated range were likely to be inconsistent
with the money and reserve paths, then the chairman might
seek supplementary instructions from the FOMC. The
May 1981 and subsequent directives stated that the chair­
man might consult with the FOMC if “pursuit of the mone­
tary objectives and reserve paths” were “likely to be as­
sociated with a federal-funds rate persistently outside”
the stipulated range. More recent directives also indicate
that the FOMC sought reserve aggregates consistent with
its M-1B targets provided that M-2 growth remained “around
the upper limit of, or moves within, its range for the year.”

6

Economic Review □ Summer 1981

Fig. 4 M-1B and Inter-Meeting Paths:

1980-81

Billions o f dollars

At each o f its meetings since January 1980, the
FOMC has chosen a short-run target path for M-l B
growth that can be related to the long-run growthrate target range.1 Each o f the short-run paths
chosen at meetings from February through August
1980 would have brought the level of M-l B toward
the m idpoint o f the 4 percent to 6.5 percent longrun growth-rate range in 1980. At the September



meeting, the short-run path was above the long-run
midpoint but would have kept year-end M-1B below
the upper end of the long-run range. The short-run

1. Target paths are specified in the “Record of Policy
Actions of the Federal Open Market Committee” for each
meeting. The record is released after the next meeting and
subsequently published in the Federal Reserve Bulletin.

Federal Reserve Bank of Cleveland

•path chosen at the October and November meetings
would have placed M-1B above the fourth-quarter
level and somewhat above the December level im­
plied by the upper limit o f the original long-run tar­
get range (w ithout any upward adjustment o f that
range to reflect unexpected growth o f other check­
able deposits).
At the December meeting, with the 1980 outcome
essentially impervious to policy influence, the shortrun path adopted lay along the midpoint of the pre­
liminary long-run target range for 1981. At the fol­
lowing meeting in February 1981, the long-run
range for 1981 was confirmed, and the short-run
path adopted would have brought the level o f M-1B
up to the m idpoint of the long-run range early in
the fourth quarter o f 1981. The short-run maximumgrowth path chosen at the March 1981 meeting
would have placed M-1B above the lower limit of
the long-run range in the third quarter of 1981,
although still below the m idpoint at year-end. The
directive adopted at the May 1981 meeting called
for M-1B growth of 3 percent “ or less” from April
to June; in fact, M-1B declined at a 6.7 percent rate
from April to June, and this is assumed to have been
the short-run path.
In the accompanying figure, the m onth desig­
nated on each short-run target path refers to the
meeting date at which that path was chosen. The
path shown was from the most recent m onth for
which the committee had data to the endpoint
m onth of the target path chosen. At the March
1980 meeting, for example, the path chosen speci­
fied a 5 percent rate o f M-1B growth from December
to June; the March path, therefore, was based on
the actual February level o f M-1B and ended at a
June level 5 percent (ar) above December. The
actual levels o f M-1B shown do not incorporate
benchmark revisions, because this information was
not available to the FOMC at the time decisions
were made. The long-run target ranges are discon­
tinuous, shifting at the months when benchmark
revisions o f base-period data were incorporated
into target setting. Reflecting the way in which the
actual targets were set, 1981 data are adjusted for
substitution o f other checkable deposits for nonM-1B assets (as described in the Board o f Governors
press release H.6).



7

money and the levels of required and excess reserves
consistent with the deposit component of the money
path and projected levels of non-M-lB reservable lia­
bilities. Depository-institution reserves, in the form of
vault cash and deposit balances at Federal Reserve
Banks, as specified by Regulation D, must equal a per­
centage of an institution’s deposit liabilities plus any
amount that institutions choose to keep in excess
of requirements.
The initial nonborrowed-reserve path is deter­
mined by the difference between the total reserve
path and an initial assumption about the level of
residual adjustment borrowing.3 Given the discount
rate, the combination of these two sources of re­
serves would be expected to result in a funds rate
and other money-market rates consistent with growth
of money demand along the target path. However,
if a gap opens between actual money growth and
the inter-meeting path, a comparable gap would open
between the actual level of reserve demand and the
path for average total reserves during the inter­
meeting period. This reserve gap is the volume of re­
serves required to accommodate the excess (or not
required because of the deficiency) of targeted de­
posits above (below) the levels consistent with the
money path (see figure 5).
A total reserve objective cannot be m et—a re­
serve gap will exist—as long as money growth is not
on path. This is because required reserves are prede­
termined by the deposit level two weeks earlier.
A nonborrowed-reserve objective can be achieved,
however, because accommodation of the reserve gap
occurs at the discount window. When a positive gap
develops (total reserves in excess of path), institutions
are forced to borrow more; in an effort to avoid in­
creased borrowing, the funds rate is bid up until re­
luctance to borrow at the discount window is over­
come. Moreover, a higher level of the funds rate and
other money-market rates serves to dampen the de­
mand for money. In subsequent reserve periods,
this will bring money and total reserves back toward
the target path, other things equal. As a negative
gap develops, the opposite automatic adjustment
takes place.
3. Adjustment borrowing excludes seasonal and special
loans for extended periods of time that, for policy-implementation purposes, are analogous to nonborrowed reserves.

8

Economic Review □ Summer 1981
Fig. 5 Money and Reserve Gaps
At meeting 1 the FOMC adopts a m onth­
ly target path for seasonally adjusted money
(M *). Reserve requirements determine a re­
quired reserve path consistent with M *
after taking account of seasonal factors,
expected holdings o f currency, and non-M-lB
reservable liabilities. The addition of ex­
pected holdings of excess reserves then
produces a non-seasonally adjusted path for
total reserves for the inter-meeting period
(77?*). The path for nonborrowed reserves
(NBR *) is derived by subtracting an initial
residual borrowing assumption that, given the
prevailing discount rate, would be expected
to result in a level of the funds rate con­
sistent with demand for money equal to the
target path.
Actual levels of money (M), of course,
might differ from M *, reflecting short-run
variations around the trend rate of growth of
money demand, shifts in money demand, or
the effects on money demand of unexpected
changes in economic activity or interest
rates. Actual demand for total reserves (77?)
would exceed TR * if the actual level of
A
money (M) exceeded M *. Nonetheless, the
procedure would call for only providing
nonborrowed reserves o f N B R * so that

Billions of dollars

sa-seasonaUy adjusted
nsa-non-seasonally adjusted

Step Four
As the inter-meeting period progresses, the desk
aims at the inter-meeting nonborrowed-reserve ob­
jective, subject to technical corrections and judg­
mental adjustments.4
4. These technical corrections and judgmental adjustments
are made by the staff to implement the directive of the
FOMC. The FOMC itself may hold interim meetings (typi­
cally by telephone) and decide to amend the directive,
which might then change the inter-meeting total and/or
nonborrowed-reserve objectives. Such interim meetings
can be triggered as inconsistencies develop between the
money paths and funds-rate range. When such inconsistencies
occurred in 1980-81, the FOMC typically agreed to amend
the funds-rate range rather than the money paths. On the
one occasion when the money paths were amended, the
funds rate remained outside the directive range despite
the amendment.



A

actual borrowing (TR - N B R *) would have to ex­
ceed the residual borrowing assumption by the entire
amount of the reserve gap, equal to the difference
between TR and TR*.
Technical corrections to the inter-meeting totalreserve objective may be made each week of the
inter-meeting period, based on incoming information.
Tabulation of an additional week’s money and re­
serve data makes it possible to improve estimates
of the simple multiplier relationship between total
reserves and money. More or less reserves may be
required than when objectives initially were set, be­
cause of unforeseen shifts in the levels of excess re­
serves and of non-M-lB reservable deposits or in the
distribution of a given level of deposits between high
and low reserve-requirement instruments and insti­
tutions. Similarly, unforeseen variations in cur­
rency holdings alter the volume of deposits and re­
quired reserves consistent with the money path. All
these multiplier corrections change the total-reserve
objective. With the residual-borrowing assumption

Federal Reserve Bank of Cleveland
unchanged, they change the nonborrowed-reserve
objective by the same am ount.
Judgmental adjustments of the inter-meeting nonborrowed-reserve objective might take place for
three reasons. First, in the very short run and typi­
cally at the end o f a reserve-maintenance week,
intentional misses o f the nonborrowed objective
are sometimes preferred to forcing a sharp change
in money-market conditions. For example, bor­
rowing for the first six days o f a reserve-mainten­
ance week might be substantially above the amount
thought to be consistent with actual total-reserve
needs and the nonborrowed objective for the week;
yet it might be consistent with the reserve objective
and money-market conditions foreseen for future
weeks. Hitting the nonborrowed target for the week
would be likely to produce substantial excess re­
serves and a decline in the funds rate that might
tend to mislead the m arket about policy objectives.
Therefore, intentionally undershooting the non­
borrowed objective may be preferable. This amounts
to a short-run judgment to adjust the nonborrowedreserve objective by revising the residual-borrowing
assumption, while leaving the total-reserve objec­
tive unchanged.
Second, the residual-borrowing assumption may
be revised to reflect an apparent shift in demand for
borrowed reserves (given the discount rate). For ex­
ample, suppose that the rate spread associated with
adjustment borrowing were persistently higher
than the spread assumed in prior settings o f the
residual-borrowing assumption; other things being
equal, money growth then would be expected to
fall short o f the path consistent with the initial
nonborrowed-reserve objective, suggesting the need
for an adjustment in that objective. Such an adjust­
ment represents a revision o f the residual-borrowing
assumption that leaves the total-reserve objective
unaltered but adjusts the nonborrowed objective.
Third, it might be decided that actual money
and total-reserve growth were not returning to path
promptly enough. Therefore, the nonborrowedreserve objective might be changed to reinforce
the automatic effect o f the reserve gap in altering
money-market conditions to control money growth.
In summary, technical corrections and judgmental
adjustments to the inter-meeting nonborrowedreserve objective may occur each week. They take



9

two forms. Technical corrections revise both total and
nonborrowed-reserve objectives by equal amounts,
leaving the residual-borrowing assumption unchanged.
Judgmental adjustments revise this residual-borrowing
assumption to change the mix of borrowed and non­
borrowed reserves, but leave the total-reserve ob­
jective unchanged.
Although the desk supplies nonborrowed re­
serves between FOMC meetings in a weekly pattern
that averages to the inter-meeting objective, this
weekly pattern mimics the actual weekly pattern in
non-seasonally adjusted total-reserve demand. Money,
whether on or off target path, does not grow at a
steady rate week-by-week before seasonal adjustment.
The actual process is complex, but an outline of the
m ethod of deriving the weekly nonborrowed-reserve
objective for any week consistent with the adjusted
inter-meeting period objective is relatively simple.
The target-path average for total reserves is subtracted
from the average of actual and projected weekly
total-reserve demands for the inter-meeting period.
This defines the average reserve gap that must be
financed at the discount window, in addition to the
assumed amount of residual borrowing as modified
by any judgmental adjustments to the nonborrowedreserve objective. The reserve gap (positive or nega­
tive) plus residual borrowing, when multiplied by the
number of weeks in the period, define the projected
sum of weekly total borrowed reserves for the entire
inter-meeting period. Subtracting the sum of weekly
actual borrowing in prior weeks of the inter-meeting
period and then dividing by the number of weeks re­
maining in the period defines average weekly bor­
rowing in current and subsequent weeks of the period
that would be consistent with the average nonbor­
rowed-reserve objective for the entire inter-meeting
period. Subtracting this amount of average weekly
borrowing from projected total-reserve demand for
the current week provides the nonborrowed-reserve
objective for the week.5
Step Five
The chronology of desk operations during a week
starts on Thursday, when a new reserve-accounting
5. Note that this process of setting weekly nonborrowedreserve objectives contains a correction for any past error in
setting the weekly level of nonborrowed reserves that is
distributed over succeeding weeks o f the target period.

10

Economic Review □ Summer 1981

period begins. Thursday’s desk program must be
tentative, however, because inform ation required
to adjust inter-meeting reserve objectives usually
is not available until Friday morning. On Friday,
the nonborrowed-reserve objective for the current
reserve-maintenance week normally can be set,
reflecting any technical corrections and judgmental
adjustments to the inter-meeting reserve objectives
and offsetting any target miss in the previous week.
Each morning, the target for the week is compared
with fresh estimates of the supply o f reserves for
the week. Any difference between target and esti­
mated supply defines the estimated open-market
operations for the day (adjusted for the number of
days that reserves are affected) that would be re­
quired to achieve the weekly nonborrowed-reserve
objective; this estimate is one basis for the desk’s mar­
ket program for the day. This program is discussed
each day with FOMC staff in a morning telephone
conference call monitored by one o f the four nonNew York Federal Reserve Bank presidents who
are voting members o f the FOMC.
Estimates o f the average daily supply of reserves
for a reserve-maintenance week are updated daily
by the staff o f the Federal Reserve Bank of New
York and, independently, by the staff o f the Board
of Governors. These estimates involve projections
of market factors supplying and absorbing reserve
funds, some o f which are highly volatile day to day
and therefore impart significant uncertainty to the
estimated open-market operations required to achieve
the weekly nonborrowed-reserve objective. The desk
program for operations in the market on any day is
therefore not necessarily a duplicate of the day’s
estimate of over- or undersupply of nonborrowed
reserves. Seasoned judgm ent, plus qualitative and
sometimes fragmentary additional inform ation, is
an indispensible foundation for daily open-market
operations o f the desk.

III. The New Procedure in Practice
The new reserve-targeting procedure involves daily
activities by the trading desk that will lead to control
of nonborrowed reserves. A nonborrowed-reserve
target, however, is merely that portion of totalreserve demand n o t supplied by adjustment borrow­
ing: total-reserve demand minus the reserve gap



forced into the discount window equals the totalreserve path; the total-reserve path minus residual
borrowing equals the nonborrowed-reserve path.
The essentials of the new procedure for imple­
menting monetary policy therefore are contained
in the two determinants of total-adjustment bor­
rowing at the discount window. One is the calculated
reserve gap created by the excess or shortfall of money
relative to the FOMC’s target path. This reserve gap
is an automatic element of policy that, taken by
itself, would cause borrowing to rise or fall as money
growth exceeded or fell below the target path. The
other determinant of total-adjustment borrowing
is the residual amount that is built into the non­
borrowed-reserve path for an inter-meeting period.
This residual borrowing is a discretionary aspect
of policy, combining an initial borrowing assumption
and inter-meeting judgmental adjustments to the non­
borrowed-reserve path that are not made to the total
reserve path.
These automatic and residual determinants of
borrowing are not part of the policy record, but
they can be approximated from published data
(see figure 6). The automatic component is mea­
sured by the gap between actual total reserves and
a total-reserve path estimated to have been con­
sistent with the short-run money path chosen by the
FOMC. The residual component can be approxi­
mated by the difference between total-adjustment
borrowing and the automatic component. These
ex post measures provide an empirical framework
for reviewing policy implementation under the
new procedure.
Several cautions must be noted before examining
these measures of policy implementation. First,
reconstruction of the 1980-81 experience with the
reserve-targeting procedure in terms of automatic
and discretionary components of total-adjustment
borrowing obviously is not an exact replica of FOMC
policy intentions.6 In particular, the reconstruction
of policy shown in figure 6 assumes that (1) M-1B
(adjusted for NOW accounts in 1981) was the only
FOMC target; (2) inter-meeting seasonally adjusted
6. For an account of monetary-policy implementation
in 1980 that provides a fuller sense of the intentions, see
“Monetary Policy and Open Market Operations in 1980,”
Quarterly Review, Federal Reserve Bank of New York,
Summer 1981, pp. 56-75.

Federal Reserve Bank of Cleveland
target-money paths grew at the constant rate implied
by the directives, rather than at variable rates (reflec­
ting short-run forecasts) that averaged to that constant
rate; and (3) unintentional pohcy-implementation
errors had a negligible influence on the actual levels
of nonborrowed reserves.7
In addition, these measures are based on actual
values of nonborrowed reserves (plus seasonal and
special borrowing). Consequently, the calculated
values of residual borrowing reflect not only the
initial assumption o f the FOMC about borrowing
as well as judgmental adjustments to a nonborrowedreserve path, but also “ accepted” deviations of non­
borrowed reserves from path.8 Accepted slips be­
tween cup and lip, while useful for nice management
of policy implementation in the short run, should be
added to path levels of nonborrowed reserves when
viewing the cumulative impact o f pohcy implementa­
tion on money-market conditions and money growth.
Therefore, given the simplifying assumptions, the
measures of automatic versus discretionary aspects of
the reserve-management experience provide a useful
basis for analyzing the new procedure. The period
examined begins with the February 1980 FOMC
meeting (when M-1B replaced the old M-l as a target)
and extends until the July 1981 meeting.
Fluctuations in total-adjustment borrowing over
the 17 months ending in early July 1981 roughly
reflect fluctuations in the reserve gap, as the auto­
matic feature o f the reserve-targeting procedure
would suggest (see figure 6). The automatic com­
ponent of borrowing is self-explanatory, reflecting

11

observed deviations of actual money growth from
FOMC short-run targets (see figure 4). However,
sizable movements in the estimated residual-borrowing (RB) component are also apparent. In par­
ticular, RB moved quite sharply from high values
in the spring of 1980 to low values in the summer
before returning to the relatively high values that
persisted more or less until mid-1981. Even within
these major intervals, RB sometimes moved up or
down noticeably from one inter-meeting period to
the next. From either perspective—
i.e., comparing
major intervals or comparing inter-meeting periods
within those intervals—variations in RB suggest that
discretionary adjustments to the am ount of non­
borrowed reserves available to depository institu­
tions may play a significant role in the pohcy process.

7. The stock of nonborrowed reserves can differ from the
policy target because of unintentional implementation errors
arising from inability to find purchasers or sellers of secur­
ities, or mis-estimates of reserve supply, on the last day of
an inter-meeting period. The weekly average absolute value
of this error was only about $63 million in 1980, less than
two-tenths of 1 percent of the nonborrowed-reserve ob­
jective. See “Monetary Pohcy and Open Market Operations
in 1980,” Quarterly Review, Federal Reserve Bank o f New
York, Summer 1981, p. 68.

One way of looking at RB reflects its conceptual
basis: that the funds rate expected to be associated
with the joint values of RB and the discount rate
must be related to desired movements in the quantity
of money demanded. Thus, the level of RB would
reflect the FOMC’s short-run target relative to the
recent trend rate of money growth. Targeting faster
money growth in a stable or declining economy
would require the lower interest rates that a re­
duction in RB would encourage. Similarly, targeting
slower money growth would call for an increase in
RB. Movements in RB over the three major intervals
of the 17 months being reviewed fit this pattern.
At its meetings in February, March, and April 1980,
the FOMC sought 5 percent M-1B growth from the
December 1979 base. At its May, July, and August
1980 meetings, after a precipitous decline in M-1B
and economic activity, the FOMC sought more rapid
short-run money growth, ranging from 7.5 percent
to 8 percent from the April level to 9 percent from
the June level. Then, after the level of M-1B had
moved into, and at times above, the 1980 long-run
target range and also in 1981, the FOMC again sought
more moderate rates of growth, never more rapid
than 6.5 percent.

8. Accepted deviations represent “decisions to tolerate
or even aim for reserve supplies either above or below average
path values.” For a discussion of the rationale for these
market-smoothing events, see Fred J. Levin and Paul Meek,
“Implementing the New Operating Procedures: The View
from the Trading Desk,” in Federal Reserve Staff Study—
Volume I, Board of Governors of the Federal Reserve Sys­
tem, February 1981.

The estimated values of RB mirror these major
adjustments in the FOMC’s money targets. In the
first and third intervals, when money-growth targets
were relatively low, RB averaged $2.2 billion and
$1.3 billion, respectively. But, in the second interval,
when the money-growth targets were relatively high,
RB averaged only $0.2 billion. That the FOMC was




12

Economic Review □ Summer 1981

Fig. 6 Autom atic and Residual Borrowing
Percent

1980

1981

NOTE: Shaded areas indicate periods when surcharge was in effect.
a. The December 5, 1980, FOMC provided trading desk leeway to pursue reserve objectives without being precisely
constrained by the upper limits of the funds-rate range.
b. The May 6, 1981, FOMC recognized the rate might exceed the upper end of the range.

Billions of dollars

1980

1981

NOTE: Dollar values are averages of inter-meeting weeks, plotted at the beginning of the inter-meeting period.




Federal Reserve Bank of Cleveland
Aggregate adjustment borrowing from Federal Reserve Banks is
necessary under the lagged-accounting system as long as total-reserve
needs of depository institutions exceed the volume o f nonborrowed
reserves supplied as a result o f open-market operations o f the trading
desk.1 Allocation of adjustment borrowing into automatic and residual
components is based on the gap between actual total reserves and an
estimate of the inter-meeting path value of total reserves.
The estimates o f an inter-meeting total-reserve path (non-seasonally
adjusted) used here were derived from the short-run money path
(seasonally adjusted and, in 1981, NOW-account adjusted) specified
in the published FOMC directive. Three steps were involved:
1. Weekly values o f a seasonally adjusted money path (M *) for an inter­
meeting period were calculated from a path based on the center of
the most recent m onth for which data were available to the FOMC
and the center o f the endpoint m onth of the growth-rate path
specified in each FOMC directive.
2. Actual weekly non-seasonally adjusted levels o f the currency com­
ponent o f money (C) were subtracted from a weekly non-seasonally
adjusted money path using the published seasonal factors available
at the time. This defined a non-seasonally adjusted deposit path
(M* - C).
3. Non-seasonally adjusted weekly deposit-path levels were multiplied
by a reserve ratio to define weekly path values o f total reserves
( T R *). The reserve ratio was the observed ratio o f actual total re-

(

TR \ Thus,
----------j.
M -C '

TR * = (M* - C) ( J R .. Y

yM - C /
The reserve gap (positive or negative) “borrowed” at the discount
window, G, was measured by the difference between actual and path
total reserves:
G = TR - T R * .
Residual borrowing, R B , was then measured by the difference between
total-adjustment borrowing, B, and gap borrowing:
RB =B —G .
This measure o f residual borrowing estimated from published data
also reflects any unintentional policy implementation errors in hitting
nonborrowed-reserve targets. The actual level o f nonborrowed reserves
can differ from the System target when: (1) the trading desk is unable
to find buyers or sellers with whom to conduct open-market operations
on the last Wednesday o f an inter-meeting period; (2) there are errors
in desk estimates of market factors affecting reserves on the last
Wednesday of an inter-meeting period; (3) the target would require
negative borrowing; and (4) final data differ from preliminary data
because o f interim revisions.
1. Adjustment borrowing excludes seasonal and extended credit.



13

aware of the interest-rate connec­
tion between RB and its money tar­
gets may be inferred from the con­
current adjustments in the discount
rate and, with some lag, the range
of the funds rate expected to be
associated with those targets (see
figure 6). Major movements of RB
and the discount rate in 1980
reinforced each other in seeking
first to stimulate and then to
restrain money demand.
A second way of looking at RB
focuses on short-run changes in the
level of RB within each major
interval as discretionary supple­
ments to the automatic stabilizing
feature of the reserve-targeting
procedure. This casts a somewhat
different light on 1980-81 ex­
perience, as changes in RB at times
reinforced, and at other times
dampened, the effects of automatic
operation of the procedure on non­
borrowed reserves.
In the first interval, covering 15
weeks of three inter-meeting peri­
ods from the February until the
May meetings, the FOMC set a
series of short-run money-growth
paths that lay close to the midpoint
of its long-run target range for
1980. The actual level of M-1B
moved from above path early in the
interval to a level far below path at
the end. Estimated RB, while
relatively high on the whole,
declined over the interval, tending
to reinforce the automatic pro­
cedure in reducing borrowing, ad­
ding to growth of nonborrowed
reserves and easing money-market
conditions.
A contrasting pattern emerged in
the second interval, covering the 17
weeks of three inter-meeting pe­
riods from the May until the
September 1980 meetings. The

14

Economic Review □ Summer 1981

FOMC set a series of short-run money-growth paths
aiming at rapid money growth, consistent with
restoring the level o f M-1B to the m idpoint of the
long-run range before year-end. The actual level of
M-1B, however, moved from below path initially to a
level substantially above path so that adjustment
borrowing increased automatically. While initially
relatively low, estimated RB moved to even lower
values over the interval, tending to dampen the
effects of the automatic procedure by adding to
growth o f nonborrowed reserves and easing moneym arket conditions.
The third interval, covering forty-two weeks of
seven inter-meeting periods, contained four relatively
distinct phases. The inter-meeting periods from the
September until the November 1980 FOMC meetings
represented a transition. The money-growth path
was reduced in two steps from the 9 percent path
set in August to the 5 percent path set in October.
Because the actual level of M-1B remained above
these slower-growth paths, a relatively stable amount
of reserve-gap borrowing was automatically main­
tained. At the same time, estimated RB increased
dramatically, consistent with the reduction in shortrun money-growth targets, and resulted in a sub­
stantial reduction in nonborrowed-reserve growth
and a tightening of money-market conditions.
A marked shortfall of M-1B below path then
developed during the 19 weeks from the November
1980 meeting until the March 1981 meeting. Esti­
mated RB remained relatively constant so that the
shortfall automatically produced a substantial re­
duction in adjustment borrowing that neither rein­
forced nor dampened the nonborrowed-reserve paths
derived from the short-run money-growth paths.
A marked excess o f M-1B growth then developed
during the seven weeks between the March and
May 1981 FOMC meetings. The FOMC had agreed
to accept money growth at or below a 5.5 percent
path, but actual money growth was above path.
Nevertheless, estimated RB declined somewhat,
tending to dampen the automatic impact on bor­
rowing o f the April money bulge and adding to the
nonborrowed-reserve objective.
Finally, in the seven weeks ending at the July
1981 FOMC meeting, short-run money-growth
targets for M-1B were effectively reduced as the
FOMC agreed to accept money growth below a



3 percent growth path from the high April M-1B
level. M-1B declined from April to June, and, as­
suming that the FOMC accepted all o f this decline,
there was no gap between actual and target money
growth. The marked increase in estimated RB thus
represented a downward adjustment to the non­
borrowed-reserve objective consistent with a reduced
short-run money-growth path.
Experience since February 1980 thus demon­
strates the several ways in which discretionary adjust­
ments in RB and nonborrowed-reserve objectives
have supplemented the automatic element o f the
reserve-targeting procedure. In three intervals—
roughly during May 1980, September/October
1980, and May 1981—substantial changes in esti­
mated RB, accompanied by adjustments in the dis­
count rate, mirrored major adjustments in the
FOMC’s short-run money targets. Over the inter­
vening portions of the whole period under review, the
setting of RB sometimes reinforced (February to
April 1980) and sometimes dampened (June to
September 1980; April 1981) the impacts o f auto­
matic operation o f the reserve-targeting procedure on
nonborrowed reserves and money-market conditions.
At other times (notably November 1980 to March
1981), the setting o f RB was essentially unchanged,
allowing variations in money growth from the target
path to show through in adjustment borrowing and
money-market conditions with no noticeable discre­
tionary alteration of nonborrowed-reserve targets.

IV. Suggested Modifications
of the New Procedure
Confusion and uncertainty are probably inevitable
consequences of any change in policy implementa­
tion, and especially with the basic changes that oc­
curred in October 1979. Much of the initial con­
fusion has cleared up, however, as both the System
and market observers have had an opportunity to
watch the new procedure work under a variety of
circumstances. Indeed, the experience of the first
17 m onths already has been used as the basis for
suggestions to modify the procedure.
A theme running through many current dis­
cussions of policy implementation is how closely
money growth should be expected to approach a
short-run target path. It is difficult—perhaps impos­

Federal Reserve Bank of Cleveland
sible—to conceive of a policy-implementation pro­
cedure that could maintain money on a target path
at all times, at least as money is currently defined.
Demands for money and total reserves are set in
the marketplace; a policy procedure simply deter­
mines the quantity or the price o f reserves.
The reserve-targeting procedure influences the
funds-rate price o f reserves in the short run by con­
trolling growth o f nonborrowed reserves. Price then
operates through demands for money and total re­
serves to adjust quantity toward a target path in the
longer run. Two aspects of this price-quantity se­
quence are notew orthy in the current procedure.
First, the procedure can maintain neither money
nor total reserves on target path in the short run.
In any reserve-maintenance week the System is ef­
fectively precluded from supplying reserve balances
in any amount less than the total o f required plus
excess reserves demanded by depository institutions.
If institutions cannot acquire sufficient reserves to
meet reserve requirements within the reserve-maintenance period, they will be penalized or have reserve
deficiencies carried over to the next week. Either
mechanism amounts to a temporary adjustment of
reserves, in effect expanding supply (albeit at a
penalty price) or deferring demand. Similarly, if
the System were to attem pt to maintain reserves in
excess of demand, institutions would repay discount
borrowing or, if no borrowing existed, would simply
accum ulate excess reserves. This am ounts to a tem ­
porary contraction o f supply to meet demand. In
the short space of the reserve-maintenance week,
with lagged-reserve accounting and a lender-of-lastresort discount facility, the only mechanism by which
the System can alter the effective supply of reserves
is to have acted ahead of time to alter the quantity
of money.
Second, while the procedure contains an auto­
matic stabilizer, it is not an autom atic pilot. That is,
the procedure does not assure that price will adjust
by an amount necessary to eliminate a deviation
between actual and target growth of money and
total reserves within an inter-meeting period or even
a series of inter-meeting periods. The automatic
component of the procedure promises a prom pt
movement of borrowing and the funds rate in the
right direction, but not necessarily by the right
amount. Successful management of the discount



15

rate and residual borrowing is required to achieve
target-growth rates.
Suggestions for modifications in the reservetargeting procedure fall into two major categories.
Some would tighten the automatic connection be­
tween a deviation of money from its target path and
adjustments to the price of reserves, with the expec­
tation that demand for total reserves would be brought
back to target with more certainty. Others would
tighten Federal Reserve direct control of total-reserve
supply, forcing more immediate adjustment in the
price of reserves to prevent deviation of total-reserve
demand from target.
Examples of the first approach include more de­
liberate manipulation of nonborrowed-reserve targets
and the discount rate. Nonborrowed reserves could be
adjusted to manage the rate spread when money de­
parts from target path.9 Adjustments to residual
borrowing that reinforced or dampened rate effects
of a reserve gap have been a common feature of the
reserve-targe ting experience. These adjustments to
the nonborrowed-reserve objective might be institu­
tionalized by explicit operating rules, for example,
linking the level of residual borrowing to the dura­
tion of a reserve gap or to a particular rate spread
relative to the reserve gap. The discount rate also
could be linked to the size and duration of a reserve
gap. One suggestion is to expand the surcharge
concept by specifying an explicit credit line for
each depository institution, but with higher sur­
charges for larger drawings on the credit line. Varia­
tions in adjustment borrowing automatically pro­
duced by deviations from target-money growth would
be expected to translate into a rate spread roughly de­
termined by the surcharge schedule. The steeper
the scheduled escalation of the surcharge with re­
spect to drawings on the line, the more pronounced
would be the reaction of market rates to off-target
money growth, and, therefore, the more quickly
money demand might move back toward target.
9. Experience suggests that the aggregate weekly relationship
of the rate spread to borrowing has been considerably less
predictable since October 1979 than was the relationship of
borrowing to the rate spread prior to October 1979. See
Peter Keir, “Impact of Discount Policy Procedures on the Ef­
fectiveness of Reserve Targeting,” in Federal Reserve Staff
Study—
Volume I, Board of Governors of the Federal Re­
serve System, February 1981.

16

Economic Review □ Summer 1981

Examples of the other approach include sug­
gestions to adopt a more contemporaneous reserveaccounting system and a penalty discount rate. The
current two-week lag precludes depository insti­
tutions from adjusting their reservable liabilities
and reserve requirements to conform to the avail­
able supply o f reserves. Consequently, they must
borrow from the discount window whatever portion
of total-reserve needs are not forthcoming as non­
borrowed reserves. Contemporaneous reserve ac­
counting would make it possible for depository insti­
tutions to contract or expand total assets and mone­
tary liabilities to m atch the volume o f reserves being
supplied by the Federal Reserve.10 In addition,
if the discount rate were always at a penalty level
above market rates, the desk could expect to be more
successful in hitting a total-reserve target from weekto-week, because discount borrowing would usually
be a less attractive alternative than scaling down
assets and liabilities when reserves were scarce.11
10. Contemporaneous reserve accounting would probably
not hasten the adjustment by a full two weeks, because
the information lag in setting the weekly nonborrowedreserve objective is not that long with lagged-reserve ac­
counting. Projections of deposit growth are used early in
an inter-meeting period to derive a weekly nonborrowedreserve path. In a four-week period, for example, paths
derived on Friday of the first week are based on the actual
currency and deposit data published that evening for the
week ending nine days earlier, plus preliminary data re­
ceived for the week ending two days earlier, plus projections
for the next two weeks. By Friday o f the third week of a
four-week inter-meeting period, no projections are neces­
sary: reserve paths are derived from three week’s published
data plus one week’s preliminary data. In addition, judg­
mental adjustments to the nonborrowed path may be made
in the last week of a period to incorporate information about
money growth that will determine reserve needs in the first
week of the next period. See Peter Keir, “Impact of Discount
Policy Procedures on the Effectiveness of Reserve Targeting,”
p. 14; and Fred J. Levin and Paul Meek, “Implementing
the New Operating Procedures: The View from the Trading
Desk,” p. 7.
11. Discount borrowing still could prevent short-run
achievement of a total-reserve target under what is called
contemporaneous reserve accounting. Proposals envision
a one- or two-day lag between reserve computation and
reserve maintenance to allow time for computation and
reporting (see Federal Reserve press release, June 4, 1980).
Total-reserve demand would still be predetermined on the
last one or two days of the maintenance period, with devia­
tions of total-reserve demand from nonborrowed supply
requiring accommodation at the discount window.



V. Conclusion
Where there’s a will to achieve money-growth
targets, there’s a way; indeed, there are innumerable
ways. For almost a decade the FOMC relied on daily
management of the federal-funds rate, accommo­
dating most short-term variations in money growth
above or below its money target and only gradually
moving the funds rate when off-target growth seemed
likely to persist. Whether the fault of will or way,
money-growth targets were missed persistently in
1977 and 1978.
At another extreme, the FOMC might adopt
true contemporaneous reserve accounting, cease
lending for reserve-adjustment purposes (or set the
discount rate at a penalty level for effective elimi­
nation of borrowed reserves), and simply feed non­
borrowed reserves into the financial system at a
steady predetermined rate. This would force the
market to accommodate (by foresight in accumulat­
ing excess reserves) or eliminate (by variations in in­
terest rates) all potential deviations of money above
or below a path consistent with the target supply
of reserves.
The actual procedure adopted in October 1979
lies between these two extremes. Tne nonborrowedreserve path accommodates expected seasonal and
some offsetting week-to-week variations in the
quantity of money, but otherwise is designed to
accommodate off-target money growth only through
the discount window with consequent repercussions
on the federal-funds rate and other rates. Persistent
deviations from target path automatically cause
interest-rate movements that tend to counteract
the deviations, reinforced or dampened by discre­
tionary adjustments in the residual-borrowing as­
sumption made in setting and resetting the nonbor­
rowed-reserve target path.
Will this way of controlling money growth work
better? The experience of 1980 suggests that it can.
Despite enormous unpredicted movements in money
demand apparently caused by credit controls, and
accompanied by substantial adjustments to the
residual-borrowing assumption and nonborrowedreserve paths, and after appropriate adjustments to
reflect unexpected growth of new interest-bearing
transaction accounts, the Humphrey-Hawkins M-1B
target range for 1980 was exceeded by only 0.25 per­

Federal Reserve Bank of Cleveland
cent. Results are, o f course, not final for 1981.
As of summer, the desired low end of the target
range seemed achievable, although apparent shifts
to non-M-lB transaction balances made even that
modest target questionable. Certainly 1980 and
1981 experience have demonstrated the increasing
willingness of the FOMC to tolerate the auto­
matic stabilizing feature o f the reserve-targeting
procedure and substantially greater interest-rate
variations than ever experienced under the pre­
vious procedure.




17

Finally, this review of reserve targeting should
be placed in a larger context. The new procedure
is simply a central-bank operating technique for
monetary targeting. Discussion and debate about
this technique should not be allowed to obscure
more fundamental questions about what an ap­
propriate monetary growth rate is, what m one­
tary or other aggregate (s) to target, and whether
m onetary targeting itself is an appropriate centralbanking control device, especially in an era of
far-reaching financial market innovation.

Mortgage Redlining: Some New Evidence
by Robert B. Avery and Thomas M. Buynak
Several laws have been passed in the last decade
to outlaw discrimination in credit markets and to
correct for the perceived failure of the market to
distribute credit equitably. At the federal level,
the most notable of these acts are the Fair Housing
Act o f 1968, the Equal Credit O pportunity Act of
1974 (amended in 1976), the Home Mortgage Dis­
closure Act of 1977, and the Community Reinvest­
m ent Act of 1977. Despite this legislation, the
regulatory and judicial bodies are still struggling to
agree on a precise definition o f discrimination and on
how it can be prevented. Particular concern has
focused on housing and mortgage credit because of
the sheer size of these markets. Debate has centered
on allegations that financial institutions, particularly
in urban areas, have severely limited their mortgagelending activity in certain poor and/or black neigh­
borhoods, a practice commonly called redlining.
One factor that has hampered attem pts to establish
definitive regulatory procedures regarding discrimina­
tion and redlining is the absence of a clear-cut under­
standing of current lending practices and patterns.
Congress recognized the need for empirical study
when it passed the Home Mortgage Disclosure Act
(HMDA) and the Community Reinvestment Act
(CRA). The HMDA requires commercial banks,
m utual savings banks, and savings and loan associa­
tions in urban areas to disclose data publicly on their
mortgage and home-improvement lending by census
tract. The CRA requires financial institutions to dem­
onstrate that they adequately serve the credit needs
of their communities and provides the opportunity
for protestants to challenge such claims (see Buynak
1981 and Canner and Cleaver 1980).
This paper utilizes HMDA data to investigate
a number o f issues underlying the redlining debate.
Although the study focuses on Cleveland, Ohio,
the site o f a number of recent CRA protests, the



findings and methodology may have relevance for
other similar areas. The remainder of this paper
reports the results of an empirical investigation of
mortgage lending in Cleveland from 1977 to 1979.
The empirical relationship between mortgage lending
and neighborhood racial characteristics is estimated,
controlling for demand and risk factors. Although
similar in design to several preceding studies, this
paper differs from most because of its particularly
rich data set. The data include virtually all mortgage
loans made during the three-year period in the cen­
tral county of the Cleveland SMSA, an area charac­
terized by substantial racial and economic hetero­
geneity. As a proxy for neighborhood credit needs,
all residential real-estate title transfers made during
the same period were collected and aggregated by
census tract (as were the mortgage loans). In addition,
court foreclosure filings were collected by tract to
control more explicitly for risk factors. The data
were utilized to estimate several sets of cross-sectional
and inter-temporal regressions relating the mortgage
lending of banks, savings and loan associations,
and mortgage bankers to neighborhood (tract)
racial and demographic factors controlling for mea­
sures of credit need and risk. The results are pre­
sented in Section III, along with a detailed discus­
sion of the data and methodology. These are pre­
ceded by a review of other studies in Section I and
a discussion of the empirical setting in Section II.
Section IV summarizes and interprets the findings.
Robert Avery is an assistant professor o f economics at
Carnegie-Mellon University and a consultant with the Fed­
eral Reserve Bank o f Cleveland; Thomas Buynak is an eco­
nomic analyst with the Federal Reserve Bank o f Cleveland.
The authors would like to thank the following persons
for their assistance and comments: Kathy Begy, Glenn
Canner, Sally Chunat, Bob Eisenbeis, Dave Fogg, Joe Hotz,
Carolyn Kramer, Sue Preston, Steve Ruetschi, Mark Sniderman, Paul Watro, and Mike Whipkey.

Federal Reserve Bank o f Cleveland

I. Why Redlining?
There are a number o f reasons to explain a correla­
tion between neighborhood characteristics, particu­
larly racial, and the type and am ount o f mortgage
lending. It is not the purpose o f this paper to argue
the positive and negative aspects o f these theories
or to speculate as to which are the most plausible.
However, it may be useful to discuss some o f the
prevalent theories and to review briefly previous
empirical findings. Throughout this paper the word
redlining denotes a correlation between the racial
composition o f a neighborhood and the type and
amount of mortgage lending resulting from dif­
ferential lending policies. This definition makes no
statem ent about the explicit lines o f causality or
legality and thus may differ from the usage o f others.
Theories o f Redlining
Several arguments have been advanced to explain
a possible correlation between neighborhood racial
composition and mortgage lending. One argument is
that there are lenders who treat borrowers differently,
based on factors other than cost or risk. Two sources
are suggested for such discrimination. Lenders could
practice non-economic or “irrational” discrimination;
or, as Barth, Cordes, and Yezer (1979) argue, they
simply could dislike lending in certain neighborhoods
and thus treat certain borrowers differently. Alterna­
tively, lenders acting either individually or collusively
could engage in classical price discrimination. Price
discrimination occurs when borrowers are charged
different prices based on demand rather than cost
(or risk) factors. If borrowers have different elastic­
ities of demand, a monopolist lender could earn
higher profits if he could charge different prices.
If lenders were to discriminate by setting higher
credit standards and/or prices for blacks (as indi­
viduals) because they think that blacks have less
elastic demand for credit, fewer loans to blacks
would result (see Masulis 1981). Such price dis­
crimination would have the appearance of redlining—
either in loan quantities or mortgage terms—and
would be most pronounced in all-black neighborhoods.
Guttentag and Wachter (1980) argue that the dis­
crimination hypotheses are not likely to be appro­
priate. They assert that the large number o f lenders
and competitive m arket conditions make it unlikely



19

that discriminatory conditions would prevail in
general, although they might apply to individual
lenders. Similarly, they argue that the differential
demand elasticities and collusive behavior required
for classical price discrimination are unlikely to be
present in banking markets.
A second set of explanations for an expected
correlation between neighborhood characteristics
and mortgage-lending patterns assumes that lenders
do differentiate among borrowers, but only on the
basis of cost or risk factors. If, for example, lowincome applicants were more likely to be black and
also were perceived by lenders to be more risky,
one would expect a statistical correlation between
loan availability and race, even in the absence of
discriminatory behavior on the part of lenders.
Similarly, borrower-loan demand may be related to
other factors, such as income or family stability,
that also are correlated with race (see Canner 1979);
thus, in the aggregate blacks may appear to demand
fewer loans because, on average, they are poorer, not
because they are charged different prices. This might
also affect the instruments used in lending. Lowincome borrowers who purchase cheaper housing,
for example, may be more likely to receive homeimprovement or installment-loan financing because of
the high fixed transactions costs involved in mortgage
loans. If blacks were more likely to purchase lowerpriced homes, one might draw a correlation between
race and the type of lending. In any of these cases,
one would expect that neighborhood characteristics,
as aggregates of individual characteristics, would also
be correlated with loan availability. Guttentag and
Wachter (1980) point out that lenders, in recog­
nizing this statistical correlation, may use an appli­
cant’s neighborhood as a proxy for risk variables,
which for cost purposes are not collected for in­
dividual borrowers. These arguments suggest that
neighborhood racial characteristics may be used
as proxies for individual applicant factors, such as
income, associated with loan risk or demand. Thus,
when these other factors are properly controlled,
the statistical correlation between neighborhood
race and loan availability should disappear. If this
were the case, then this situation would not con­
stitute redlining as earlier defined.
Although not generally cited in the redlining
literature, additional theories argue that there may

20

Economic Review □ Summer 1981

be a statistical correlation between the racial com­
position of a neighborhood and credit availability,
even if one properly controls for all individual char­
acteristics. Bailey (1959), Mills (1972), and many
others have developed urban-housing “prejudice”
models based on the assumption that whites would
be willing to pay higher prices to live in all-white
neighborhoods rather than live in neighborhoods
with blacks. These models generally imply perfectly
segregated neighborhoods separated by what Bailey
termed a “black border.” The willingness of some
whites to pay for their prejudice implies that perunit housing prices would be lower in all-black
neighborhoods and in white areas nearest to the
black border. Mieszkowski (1979), among others,
concludes that these models imply that middleincome blacks would devote a smaller portion of
their income to housing. Black borrowers, there­
fore, should be more attractive to lenders because
they would be better risks than middle-income
white borrowers.
Most o f the applications of the Bailey-Mills model
assume a constant proportion o f whites to blacks.
Very different conclusions about the relative attrac­
tiveness o f black and white borrowers can be derived
by relaxing this assumption. The Bailey-Mills model
implies that the relative price o f black to white
housing is a decreasing function o f the proportion of
the population that is black. Thus, if the assumption
is made that the percentage of black population is
rising, this would imply that the relative price of
black to white housing would fall. Transition areas
near the black border also would have lower relative
prices. The relative price of black housing would
fall even if the growth of the black population (and
the change in prices) were fully anticipated by
home buyers.
The implications of this version o f the prejudice
model are the opposite of those o f the simpler
models. Since relative home prices in black neighbor­
hoods (even those already 100 percent black) theoret­
ically would fall as the percentage o f blacks in the area
rises, the value of black houses as collateral would be
lower; lenders thus would be willing to lend less.
Similarly, relative housing prices in all-white areas
far removed from the black border would be ex­
pected to rise, offering more attractive lending col­
lateral. In effect, the racial composition of a neigh­



borhood becomes a proxy for expected future price
changes and hence for the value of loan collateral.
Previous Empirical Work
Each of the redlining theories has somewhat
different empirical implications. The discrimination
theories suggest that the number of blacks in a neigh­
borhood should determine the lending policies,
even when income and other demographic factors
are taken into account. Although gross correlations
may exist between race and the volume of mortgage
credit, theories based on risk and demand factors
imply that this relationship should disappear when
other demographics are considered. Finally, some
versions of the Bailey-Mills model suggest that it is
the change in racial composition, rather than levels,
that is relevant—that lending in integrated and all­
black neighborhoods would be relatively more at­
tractive in stable areas than in areas where the racial
composition is changing.
Although not necessarily designed to discrim­
inate among these hypotheses, there have been a
number of empirical redlining studies by both com­
m unity action groups and researchers (see Benston
1979, 1981 and King 1980). These studies can be
divided roughly into two categories: one type utilizes
HMDA and census data and deals with aggregate
mortgage-lending patterns across neighborhoods,
while the second focuses on individual borrowers
and differences in specific mortgage terms (e.g.,
downpayments, interest rates). Nearly 25 cities
nationwide have been examined using one or both of
these approaches.1 Since this study builds heavily
on these earlier works, a brief discussion of some
of the key findings from representative cases may
prove useful.
The objective of most of the aggregate HMDAbased studies (and this one as well) has been to esti­
mate not only the gross relationship between race
and mortgage credit, but to identify the particular
effects stemming from supply, or the actions o f the
lender. To do this properly requires the specification
of both supply and demand equations and a meaning­
ful m ethod of separating their effects. Unfortunately,
1. Areas that have been examined include Boston, New York
City, Syracuse, Rochester, Buffalo, Pittsburgh, Toledo, Flint
(Mich.), Chicago, Louisville, Miami, San Antonio, Los An­
geles, Oakland, and Sacramento.

Federal Reserve Bank of Cleveland
it is virtually impossible to come up with variables
that would affect supply and not demand. For this
reason virtually all previous studies (and this one as
well) have relied on reduced-form analysis—
i.e., re­
gressing measures of mortgage-loan activity against
race and all other variables thought to be related to
either supply or demand. While unable to provide
specific inform ation on supply effects, these equa­
tions can show the relationship between race and
the type and quantity o f mortgage lending while
controlling for income, housing stock, and other
demographics. This inform ation still may be useful
for discriminating among redlining hypotheses;
however, since the equations, at best, only crudely
identify supply factors, they must be carefully in­
terpreted before drawing any policy conclusions.
The critical differentiating factor among aggre­
gate HMDA-based studies is the quality o f the data
used to control for factors other than race. One
study that stands out was done by Hutchinson,
Ostas, and Reed (1977 and Ostas, Reed, and H utch­
inson 1979), who examined a subset o f Toledo,
Ohio, savings and loan associations. They found that
racial composition was not correlated with the total
number of loans extended within a neighborhood,
but it was related to the ratio o f conventional to
government-insured loans. They concluded that
lenders substitute riskless government contracts in
those areas perceived to have the greatest risk. Canner
(1979) conducted a similar but more comprehensive
analysis of mortgage lending in Boston, Massachu­
setts. Using various indexes o f mortgage-loan activity
(e.g., the number o f conventional loans to total trans­
actions in a census tract), he found that, other things
being equal, the racial composition o f Boston neigh­
borhoods affected the num ber o f loans issued by in­
stitutional lenders. However, he also found that non­
banking businesses and other private individual lenders
filled some o f the “mortgage gap” in all-black (al­
though not integrated) neighborhoods. These loans
were often made with nontraditional instruments
such as land-installment contracts.
Schafer’s (1978, chap. 5) comprehensive exami­
nation of New York City differs in that it explicitly
compares two different types o f neighborhoods.
Neighborhoods were separated into alleged redlined
and non-redlined areas, and separate models were
estimated for each data set. The coefficients esti­



21

mated from the non-redlined data were multiplied
by the values of the independent variables o f the
redlined neighborhoods generating predicted funding
for the alleged redlined areas. A comparison of the
predicted values with the actual loans revealed that
fewer loans were made available than predicted in
some redlined neighborhoods.
There have been fewer studies that have used
individual borrowers as the unit of observation,
primarily because of data limitations.2 One of the
better studies is Benston, Horsky, and Weingartner’s (1978) examination of three years of indi­
vidual mortgage terms in two Rochester, New York,
neighborhoods. One area was an allegedly redlined
(by lenders) area, and the other served as a control
(non-redlined) area. After adjusting for housing
characteristics, such as age and selling price, they
found that the mortgage terms in the two areas
were not significantly different. Schafer’s (1978,
chap. 6) similar study of New York City contains
mixed results, but some evidence was found that
neighborhood characteristics affect loan terms.
King (1980, sect. 6) analyzed mortgage applications
o f federally insured savings and loan associations
for evidence of discrimination related to age, race,
sex, marital status, and property location in the
SMSAs of Miami, Florida; San Antonio, Texas;
and Toledo, Ohio. The results of his study, similar
to those of Benston, Horsky, and Weingartner, did
not support the hypothesis that lending terms were
related to discriminatory factors after adjusting for
neighborhood and borrower characteristics.

II. Empirical Setting
The empirical analysis focuses on Cuyahoga
County, which is the central county of the Cleveland
SMSA. The county encompasses Cleveland and 54
suburban communities divided into 357 census tracts,
335 of which are used in the study.3 This area was
2. Lending institutions in the states of Massachusetts, New
York, and California are required to disclose data on individ­
ual loan terms along with other borrower neighborhood
and property information.
3. Twenty-two tracts were excluded, because they had a
1970 population of less than 300. Almost all deleted tracts
were in Cleveland’s sparsely inhabited downtown and in­
dustrial flats area.

22

Economic Review □ Summer 1981

Table 1 Demographic Characteristics of Cleveland
Total
population,
thousands
Cuyahoga County
City of Cleveland
Suburbs

1970
1,721
751
970

1980
1,498
574
924

Black population
as a percent of
total population
1970
19.1
38.3
4.2

1980
22.7
43.8
9.7

Median
family
income,
dollars
11,309
9,107
14,643

Housing
stock,
1-4 family,
thousands

Percent of
total houses
built prior
to 1939

Owneroccupancy
rate as percent
o f 1-4 family units

454
206
248

48.9
73.3
28.4

51.7
40.9
68.0

NOTE: Unless otherwise noted, the data are for 1970; only 1980 population demographic data have been released to date.

Table 2 Distribution of 1977-79 Housing-Related Loans in Cleveland

Financial
institutions

Number of
institutions,
1979

FHA mortgage
loans, 1977-79

Total mortgage
loans, 1977-79

Home-improvement
loans, 1977-79

Number Average

Number Average

Number Average

Number Average

11,690 $42,091
57,690 37,068
5,425 32,019

38,925 $4,828
5,662 7,084
-

74,805

44,587

Conventional mort­
gage loans, 1977-79

Commercial banks
Savings and loans
Mortgage bankers3

10
27
29

11,582
56,065
-

$42,169
37,034

108
1,625
5,425

$33,703
38,235
32,019

All financial
institutions

66

67,647

37,913

7,158

33,456

37,487

5,114

a. The few conventional loans extended by mortgage bankers do not fall under the reporting requirements of HMDA and,
hence, are not included in these figures.

selected for two reasons. First, it is o f particular con­
cern to the F ourth Federal Reserve District, as the
majority o f CRA protests received in this district
involve Cleveland-based institutions. Second, it offers
a particularly well-suited environment to investigate
redlining. The county is a good approximation of
the service area o f the 37 banks and savings and
loan associations included in the study.4 As a group,
these banks and savings and loans make over 80 per­
cent o f their mortgage loans within the county. The
county also has a large, growing black population
that is for the most part segregated. Since most of the
SMSA’s commuting suburbs are contained within the
county, the data set offers the potential to separate
the effects o f racial patterns from those generated by
income or other neighborhood characteristics.
4. During the period o f study, Ohio was classified as a
limited branch state. Commercial banks were permitted to
branch only within the county in which they were head­
quartered, and savings and loan associations were geo­
graphically restricted to branching within a 100-mile radius
of their home offices.



The population of the county has declined steadily
over the past decade. As shown in table 1, most of the
population loss has been from the city. Whereas the
county’s white population has fallen since 1970,
its black population has risen slightly. Although
the percentage of blacks within the city has risen,
there has been a decline in the actual number of
black city residents. The increase in the county’s
black population has occurred in the suburbs, where
the percentage o f blacks has more than doubled
in the past 10 years.
There are a num ber of significant differences
between the city and its surrounding suburbs. The
city was almost completely developed by the 1930s,
as nearly 80 percent of its housing stock was built
prior to 1939. According to the Department of
Housing and Urban Development (HUD) definition, al­
most 60 percent of the city’s 204 census tracts are clas­
sified as low-to-moderate income neighborhoods versus
only 4 percent o f the county’s 153 suburban tracts.
Both the city and the suburbs have similar racial
patterns (see figure 1). A clear east-west racial split

Federal Reserve Bank of Cleveland
exists; the city’s black population is concentrated
in the eastern portion, and most suburban blacks
reside in the northeastern and southeastern suburbs.
For the county as a whole, 80 percent of the area’s
white population lives in neighborhoods that are less
than 10 percent black; 73 percent o f the county’s
black population lives in neighborhoods that are
greater than 90 percent black.
Ten commercial banks and 27 savings and loan
associations were headquartered in the county from
1977 through 1979. Twelve of the 37 institutions
(six of each lender type) control over $900 million
in assets. Virtually all of the roughly 75,000 home
mortgages and approximately 45,000 home-improvement loans issued in the county during the threeyear period under study were extended by these
institutions or one o f 29 mortgage bankers. As shown
in table 2, savings and loans accounted for the major­
ity of mortgages extended over the three-year period,
while commercial banks extended most of the homeimprovement loans. The average value of mortgages
extended by banks was slightly higher than that for
savings and loans and significantly higher than that
for mortgage bankers. For home-improvement loans,
the average value extended by savings and loans was
one and one-half times that extended by banks. Fed­
erally insured Federal Housing Act/Veterans’ Admin­
istration (FHA/VA) loans represented 10 percent of
the total number of county-wide mortgage loans
over the 1977-79 period, with mortgage bankers
accounting for over 75 percent o f this total.

III. Empirical Results
This study addresses the empirical issues related to
redlining by using two different sets o f multivariate
regressions. One set relates the levels o f six different
measures of loan activity to the racial composition
of Cleveland neighborhoods (tracts), controlling
for income, risk, and other nonracial neighborhood
characteristics. The second set relates the change in
the same six dependent variables to the change and
lagged changes in the racial composition of neighbor­
hoods. Each of these regressions has a similar form,
relating different dependent variables to a common
set of independent variables. Because the quality of
data has been a controversial topic in the redlining
literature (see Benston 1979, 1981), the preparation



23

of data is discussed in greater detail than might nor­
mally be the case. The actual variables used are listed in
table 3, along with variable means and standard devia­
tions for the total sample and seven subsamples.
D ependent Variables
The dependent variables are based primarily on
loan data reported under the Home Mortgage Dis­
closure Act by all Cuyahoga County banks and
savings and loan associations for the years 1977-79.
Total mortgage and home-improvement loans for
the three-year period were aggregated by census
tract separately for reporting banks and savings
and loans. FHA and VA data also were used to
calculate federally insured mortgage loans made by
mortgage bankers and also were aggregated by tract
for the same period.5 Although these figures exclude
loans made by out-of-county financial institutions,
conventional mortgage banker loans, and loans by pri­
vate individuals, they appear to account for almost all
Cuyahoga County mortgages made during this period.
Taken by themselves, raw figures on mortgage
lending activity would be misleading indicators of
loan availability because of differences in neighbor­
hood turnover rates. As a crude measure of potential
“loan needs,” the total number of housing deed
transfers was aggregated by tract for the three-year
period using data collected from the Cuyahoga
County Auditor’s office. Measures of loan activity
(number of loans) were then deflated by deed trans­
fers and multiplied by 100 for each tract. The resulting
variables, which formed the actual dependent vari­
ables for this study, could be thought of as percent­
ages of the transfers in each tract financed by dif­
ferent institutions. Variables were constructed to
reflect mortgage loans issued by (1) banks, (2) sav­
ings and loans, (3) mortgage bankers, (4) total m ort­
gage loans, and (5) total home-improvement loans.
A sixth dependent variable was constructed by de­
flating the total dollar value of mortgage and homeimprovement loans by the total dollar value of
owner-occupied one-to-four unit housing stock as
measured in the 1970 census (1977 dollars) and
5. Unfortunately, only the city location of mortgage banker
VA loans was available. The distribution of the similar non­
subsidized (Section 203) FHA mortgage banker loans,
therefore, was used to assign VA loans randomly to census
tracts within cities.

24

Economic Review □ Summer 1981

multiplying by 100. This variable is a crude measure
of the percentage of the value of each neighborhood
financed by equity lending each year.
If “loan needs” were accurately measured by the
deed-transfer variable, then the first five dependent
variables would be constrained to lie between 0 per­
cent and 100 percent. U nfortunately, in many neigh­
borhoods the number of loans exceeded the number
of transfers because o f widespread issuance of second
mortgages. Similarly, although efforts were made to
eliminate them , some transfers that generally do not
require financing, such as those resulting from divorce
or death, still remain in the data. For these reasons, the
dependent variables are only approximate measures
o f the percentage o f “loan needs” actually financed.
Independent Variables
Independent variables were drawn primarily from
the 1970 U.S. Census of Population and Housing.
Three variables were used to characterize neighbor­
hood income: (1) median yearly family income; (2)
percentage o f tract families with income below the
official poverty line ($3,743 for a family of four in
1969); and (3) percentage of employed persons
within the tract who were professionals or managers.
Four census variables were selected to control for
neighborhood housing characteristics: (1) median
value of owner-occupied one-to-four unit houses;
(2) real percentage change in median value of owneroccupied housing from 1970 to 1977 ;6 (3) percent­
age o f owner-occupied housing built before 1939;
and (4) percentage o f one-to-four unit structures
that were owner-occupied. Both the income and
housing values were expressed in 1977 dollars for
comparability with mortgage figures. One particular
concern with these variables is th at, unlike other
variables in the study, they were measured as of
1970 instead o f 1977-79. Thus, particularly in
changing neighborhoods, they may be inaccurate
measures of 1977 conditions.
An eighth independent variable was selected
to control for risk differences across neighborhoods.
County records o f foreclosure filings were collected
for the years 1973-79 and aggregated by the census
tract o f the cited property. This variable then was
6. The 1977 value was estimated from the median price of
houses sold in each tract in 1977.



Fig. 1 Racial Composition of Cuyahoga County3

□
□

< 10% black in 1970 and 1977.b

EMI

< 10% black in 1970; 10% to 50% black in 1977.

■

10% to 50% black in 1970 and 1977.

a. The heavy black border designates the city of Cleveland.
b. The 1970 data are from U.S. Census of Population and Housing;
1977 data are from the Cuyahoga Plan of Ohio, Inc.

iii

BSQ



Federal Reserve Bank of Cleveland

25

26

Economic Review □ Summer 1981

Table 3 Sample Means of Variables
Standard deviations in parentheses
Tracts sorted by percent black in 1970 and 1977
Symbol

sample

(A)

(B)

(C)

(D)

(E)

(F)

(G)

Number of tracts

TRACTS3

335

201

29

13

19

14

17

42

Bank mortgage loans
to transfers, percent

TOTBNK3

14.1
(13.2)

17.7
(14.1)

16.2
(9.7)

14.4
(13.2)

6.7
(4.7)

8.4
(12.4)

3.2
(3.2)

5.2
(5.8)

S&L mortgage loans to
transfers, percent

TOTS&L3

71.4
(36.2)

89.1
(27.3)

70.2
(27.8)

67.4
(51.8)

44.6
(19.3)

29.6
(20.8)

33.0
(19.1)

30.6
(22.7)

Nonbank mortgage loans
to transfers, percent

TOTOTH3

11.3
(18.6)

5.5
(10.1)

8.4
(10.6)

8.4
(18.0)

27.7
(21.0)

18.4
(18.7)

38.5
(40.5)

21.4
(21.8)

Total mortgage loans
to transfers, percent

TOTALL3

96.9
(42.1)

112.3
(32.4)

94.7
(35.9)

90.1
(62.1)

79.1
(26.3)

56.5
(35.5)

74.7
(56.4)

57.2
(40.7)

Total home-improvement loans
to transfers, percent

TOTHI3

93.6
(73.8)

57.4
(20.3)

63.5
(23.7)

103.8
(72.7)

116.3
(38.2)

161.6
(83.7)

177.2 218.0
(85.8) (83.6)

Total loan dollars to total value
owner-occupied housing, percent

T 0T L 0$3

31.7
(66.6)

34.5
(80.2)

35.7
(43.5)

31.1
(20.5)

53.5
(76.5)

20.4
(13.3)

18.2
(8.0)

15.0
(5.8)

Percent black, 1977

%BLK77b

28.9
(38.7)

1.9
(2.1)

22.2
(9.5)

33.2
(10.2)

73.4
(11.3)

83.6
(7.0)

93.2
(1.6)

97.1
(2.6)

Change in black, 1970-77, percent

CNG%BLb

6.3
(12.1)

1.5
(2.0)

19.1
(9.5)

4.5
(11.3)

42.4
(11.8)

12.4
(14.9)

12.5
(8.6)

0.1
(2.1)

1970 median family income,
thousands of 1977 dollars

MEDINC0

18.7
(7.2)

21.1
(7.2)

19.3
(5.7)

17.7
(6.8)

16.0
(3.8)

12.7
(3.6)

13.5
(3.7)

12.2
(4.6)

1970 median value owner-occupied
house, thousands of 1977 dollars

MEDVAL0

33.7
(15.1)

38.4
(15.9)

33.4
(13.5)

30.7
(14.2)

29.5
(10.1)

21.9
(6.1)

22.8
(5.5)

22.7
(6.8)

Change in median real value
of house, 1970-77, percent

CNG%VA3

-1 .0
(40.1)

12.0
(34.3)

-3 .1 -1 2 .1
(18.8) (30.3)

-0 .0 1
(64.6)

1970 owner-occupied housing
built before 1939, percent

%<1939c

58.6
(33.3)

52.4
(34.4)

60.9
(35.2)

52.3
(35.7)

69.3
(28.1)

74.3
(21.3)

73.5
(21.9)

72.6
(26.8)

1970 families below poverty in­
come, percent

%<POVc

9.9
(11.1)

5.0
(4.3)

7.6
(6.8)

11.8
(12.0)

11.7
(8.6)

22.9
(13.4)

18.6
(11.4)

25.7
(15.0)

1970 workers employed as pro­
fessionals/managers, percent

%PROFc

20.2
(14.6)

23.1
(14.7)

26.3
(16.4)

22.5
(18.4)

22.7
(10.2)

10.3
(5.0)

8.1
(4.1)

8.4
(4.9)

1970 owner-occupied
structures, percent

%OWNOCc

54.0
(25.4)

62.7
(21.7)

52.1
(24.4)

43.8
(26.7)

37.6
(22.2)

33.3
(22.0)

43.1
(28.1)

35.6
(24.6)

1973-79 foreclosure actions per
owner-occupied house, percent

CTYFCd

7.8
(13.4)

2.5
(2.8)

5.2
(3.9)

8.6
(6.1)

25.9
(11.9)

24.3
(24.7)

27.3
(36.2)

12.9
(8.2)

1970 population, thousands

POPULAc

5.1
(3.5)

5.7
(4.0)

4.1
(3.1)

3.3
(2.8)

4.2
(2.3)

4.7
(2.1)

3.6
(1.7)

4.5
(2.0)

Variables

DATA SOURCES:
a. Computed from Cuyahoga County Auditor’s records of
deed transfers compiled by Northeast Ohio Areawide Coordi­
nating Agency and HMDA data averaged for 1977-79.
b. Estimates from Cuyahoga Plan of Ohio, Inc.
c. 1970 census data.
d. Cuyahoga County Court filings.




-1 6 .1 -3 2 .9 -4 0 .8
(63.8) (20.4) (24.5)

KEY:
(A) < 10% black in 1970 and 1977.
(B) < 10% black in 1970; 10% to 50% black in 1977.
(C) 10% to 50% black in 1970 and 1977.
(D) 10% to 50% black in 1970; 50% to 90% black in 1977.
(E) 50% to 90% black in 1970 and 1977.
(F) 50% to 90% black in 1970; > 90% black in 1977.
(G) > 90% black in 1970 and 1977.

Federal Reserve Bank of Cleveland
deflated by the number o f owner-occupied housing
units within the tract and multiplied by 100. As most
foreclosure actions are settled w ithout a formal
trial, this variable vastly overestimates the number
of actual legal foreclosures. Foreclosure filings,
however, seemed to be a much better indicator of
potential mortgage losses than the few cases re­
quiring legal adjudication. Note that this variable re­
flects foreclosures of loans that actually were granted
and thus fails to reflect risk differences already
incorporated by institutions into their credit-screen­
ing procedures.
The final and most im portant explanatory variable
is the characterization of the racial composition of
neighborhoods. A number of different specifications
of this critical variable were considered. Canner (1979),
for example, used the change in percent black as well
as a cubic polynomial for the level of racial composi­
tion. However, the small number of integrated tracts
resulting from the severe nature of Cleveland segre­
gation made such a specification unattractive for
purposes of this study. As an alternative, it was de­
cided to characterize race by seven mutually ex­
clusive neighborhood groupings that differentiated
tracts by both their levels and changes in racial com­
position. Racial composition was measured in 1970
(census figures) and again in 1977 (estimates from the
Cuyahoga Plan o f Ohio, Inc.),7 and tracts were sorted
into the following seven categories:
(1) the percent black was less than 10 percent in
both 1970 and 1977;
(2) the percent black was less than 10 percent in
1970 and between 10 percent and 50 percent
in 1977;
(3) the percent black was between 10 percent and
50 percent in both 1970 and 1977;
(4) the percent black was between 10 percent and
50 percent in 1970 and between 50 percent
and 90 percent in 1977;
7. At the time the study was done, information on racial
composition was available from the 1980 census. However,
it was decided not to use these data, since they might have
been affected by the actions of lenders during the 1977-79
period. The accuracy of the Cuyahoga Plan data can be
attested to by the fact that its 1977 racial figures differed
from the 1980 census figures by an average absolute de­
viation of only 3.4 percent, a number consistent with the
7.6 percent average absolute deviation between the 1970
and 1980 censuses.



27

(5) the percent black was between 50 percent and
90 percent in both 1970 and 1977;
(6) the percent black was between 50 percent and
90 percent in 1970 and over 90 percent in 1977;
(7) the percent black was over 90 percent in both
1970 and 1977.
Before discussing the regression results, the super­
ficial evidence suggested by the gross variable means
in table 3 should be noted. Reading columns from
left to right, commercial bank, savings and loan, and
total mortgage loans as a percent of transfers each
show a significant decline from all-white to all-black
neighborhoods. These gross relationships, however,
might be very misleading, as median income, median
housing value, change in housing value, age of housing
structures, and foreclosure actions all show very
similar patterns. Without controlling for these other
factors, it is impossible to tell whether it is the racial
composition o f neighborhoods that affects loan
availability or other factors correlated with race,
such as income.

Regression Results
Results of the first set of regressions are sum­
marized in table 4. Columns denote dependent vari­
ables, and rows indicate independent variables, which
are identical for each regression. Except for the re­
sults reported in column 7, each regression was
estimated with ordinary least squares using the entire
sample of 335 census tracts. Coefficient estimates
are presented as well as their standard errors (pre­
cision of estimation). Coefficients that are signifi­
cantly different from zero at the 1 percent or 10 per­
cent levels are indicated with asterisks. Note that,
because of the form of the dependent variables, the
coefficients of regressions 1 , 2 , and 3 always sum to
the coefficients of regression 4.
Coefficients for the control variables are listed
in the first nine rows and for the most part con­
form to prior expectations, with some glaring ex­
ceptions. As a general rule, older, poverty-stricken,
nonprofessional, rental-dominated neighborhoods ap­
pear to be significantly less likely to receive loans of
any type. Although these general results hold true,
there are conflicting, inconsistent coefficient signs
in almost every regression. Similarly, median family
income, housing values, and foreclosure rates—vari-

28

Economic Review □ Summer 1981

Table 4 Coefficient Estimates of Static Regressions
Standard errors in parentheses
Dependent variables
Independent
variables
CONSTANT

TOTBNK

TOTS&L

TOTOTH

TOTALL

TOTHI

TOTLOS

TOTALL3

(1)

(2)

(3)

(4)

(5)

(6)

(7)

-17.38**
(2.93)

102.70**
(8.83)

7.07
(5.87)

92.39**
(11.00)

32.90*
(17.05)

154.17**
(25.36)

133.20**
(12.18)

MEDINC

0.78**
(0.15)

-2 .0 0 * *
(0.44)

0.31
(0.29)

-0 .9 1 *
(0.55)

-0 .5 1
(0.85)

1.54
(1.26)

-0 .7 5
(0.47)

MEDVAL

0.34**
(0.08)

0.14
(0.25)

-0 .1 7
(0.17)

0.30
(0.31)

0.18
(0.49)

-2 .0 4 * *
(0.73)

-0 .1 9
(0.30)

CNG%VA

0.016
(0.011)

0.037
(0.034)

-0 .016
(0.023)

0.037
(0.042)

-0.134*
(0.065)

%< 1939

0.026
(0.018)

-0.160**
(0.053)

0.062*
(0.036)

-0 .0 7 2
(0.067)

%<POV

0.31**
(0.06)

-1 .1 7 * *
(0.19)

-0.89**
(0.13)

-1 .7 5 * *
(0.24)

%PROF

0.19**
(0.06)

0.71**
(0.18)

-0 .3 5 * *
(0.12)

0.55*
(0.22)

-0 .0 3 2
(0.027)

0.332**
(0.082)

0.128*
(0.054)

%OWNOC
CTYFC

0.042
(0.039)

-0 .0 2 1
(0.118)

-0 .005
(0.078)

0.428**
(0.102)
0.016
(0.147)

0.368**
(0.103)
-1 .9 6 * *
(0.37)
-0 .3 1
(0.35)
0.465**
(0.158)
-0.531*
(0.228)

0.468**
(0.097)

0.179*
(0.088)

-0.587**
(0.153)

-0.127*
(0.067)

-1 .1 1 *
(0.56)

-2.0 6* *
(0.40)

1.51**
(0.52)

0.71**
(0.21)

-1.261**
(0.234)

0.071
(0.112)

0.336
(0.339)

-0 .6 5 7
(0.499)

D<10, 10-50b

-0 .2 9
(1.44)

-1 5 .45**
(4.35)

6.61*
(2.89)

-9 .1 3 *
(5.42)

13.29
(8.40)

-1 0 .4 2
(12.49)

-6 .8 0
(5.79)

D10-50, 10-50

-0 .5 3
(2.06)

-11.72*
(6.21)

10.55*
(4.13)

-1 .7 1
(7.74)

68.02**
(11.99)

-1 9 .7 4
(17.84)

-1 .2 2
(9.35)

D10-50, 50-90

-8.01**
(1.89)

-33.30**
(5.71)

30.15**
(3.80)

-1 1 .1 6
(7.12)

87.10**
(11.02)

-7 .2 1
(16.40)

1.74
(11-91)

D50-90, 50-90

-2 .1 3
(2.19)

-29.24**
(6.60)

26.21**
(4.39)

-5 .1 5
(8.23)

147.31**
(12.75)

-13.85
(18.96)

8.36
(10.66)

D50-90, >90

-6.10**
(2.10)

-30.57**
(6.33)

40.16**
(4.21)

3.49
(7.89)

149.10**
(12.22)

2.03
(18.18)

29.59**
(10.99)

D>90, >90

-4.75**
(1.61)

-25.19**
(4.86)

30.61**
(3.23)

0.68
(6.06)

198.28**
(9.39)

6.49
(13.96)

9.61
(7.67)

0.74

0.69

0.47

0.64

0.72

0.23

0.84

R2

* Significant at the 10 percent level.
** Significant at the 1 percent level.
a. Weighted by the number of owner-occupied units.
b. These last six independent variables are dummy variables representing different neighborhood racial classifications. As
shown in the key to table 3, the first number represents the percentage black in 1970; the second number represents the
percentage black in 1977.




Federal Reserve Bank of Cleveland
ables that a priori one would expect to be impor­
tant—have insignificant coefficients in all but a
few regressions.
The most im portant coefficients for the purposes
of this study are the estimated effects of neighbor­
hood racial composition. Coefficients for the six in­
tegrated and all-black areas of the seven neighbor­
hood classifications are listed in the last six rows of
table 4. These neighborhood coefficients represent
mean shifts (intercept) in the dependent variables
measured against the all-white neighborhoods (less
than 10 percent black in both 1970 and 1977). The
coefficients thus can be directly interpreted as dif­
ferences in the percentage of transfers financed.
One would expect integrated neighborhoods (D1050, 10-50), for example, to have 11.72 percent less
of their transfers fmanced by savings and loans than
comparable all-white neighborhoods.
Although less significant than the raw figures
presented in table 3, it appears that, controlling for
other demographic variables, banks and savings and
loans are still less likely to extend mortgage credit
in integrated and all-black areas (regressions 1 and 2).
Interestingly, changing neighborhoods fare worse
than comparable stable areas, a fact consistent with
arguments suggested earlier. The least attractive
neighborhoods appear to be those shifting from a
majority white in 1970 to a majority black in 1977
(D10-50, 50-90). Note that the magnitude of these
differences, particularly for savings and loans, is
quite large. The average intercept shift of —
30
between all-white and predominantly black neighbor­
hoods represents a drop of one-third in the approxi­
mately 90 percent o f all-white neighborhood trans­
fers financed by savings and loans.
Mortgage bankers appear to have exactly the
opposite pattern as banks and savings and loans
(regression 3). Black neighborhoods appear to be
more, rather than less, likely to receive broker fi­
nancing with most of these FHA/VA governmentinsured loans (75 percent o f FHA/VA loans in the
county originated from mortgage bankers). Thus,
looking at total mortgage lending (regression 4),
the attractiveness of black neighborhoods to m ort­
gage bankers offsets most o f the absence o f bank
and savings and loan lending in these areas. Thus,
on net, only the transitional neighborhoods (D <10,
10-50 and D10-50, 50-90) fare significantly worse



29

than all-white neighborhoods, and these effects
are modest.
Home-improvement loans appear to show similar
patterns to mortgage-banker lending (regression 5).
Black neighborhoods appear to be significantly more
likely to receive home-improvement loans than allwhite neighborhoods (most of these loans are issued
by banks at rates higher than those for first m ort­
gages, with shorter maturities, and are collateralized
by housing Hens). This is particularly true for stable
all-black neighborhoods (D >90, >90). Aggregating all
sources of equity financing, total loan dollars (regres­
sion 6) exhibit a similar pattern to total mortgages
(regression 4). Total funds flowing to the six cate­
gories of integrated and all-black neighborhoods do
not appear to be significantly different from those
flowing to comparable all-white neighborhoods.
The 335 census tracts used in the study were
weighted equally in the six regressions. Because
neighborhoods represent aggregates of different
sizes, however, a case can be made for weighting
observations by various measures of tract size. A
formal basis for this argument is that aggregation
makes it likely that regression errors will be heteroskedastically, rather than identically, distributed.
An attem pt was made to correct for this by weighting
observations by the number of one-to-four unit
owner-occupied houses as a representative measure
of tract size. The regression for total mortgage loans
was then re-run using the weighted observations (re­
gression 7). With one exception, coefficient signs
and significance levels are similar to the unweighted
regression. Interestingly, however, some transitional
neighborhoods (D50-90, > 90) now appear to be
significantly more likely to receive funding than
comparable all-white areas.
Unfortunately, the first set of regressions, which
form the basis for most of the analysis, fails to capi­
talize on the temporal features of the data base. Al­
though three years is a relatively short time in the
slowly changing world of mortgage lending, some
simple dynamic relationships were examined in a
second set of regressions. In particular, yearly changes
in the six measures of loan activity were compared
with changes in neighborhood racial composition
(the only variables for which there were measures
for each year). The contemporaneous change in
racial composition and lagged changes for three

Economic Review □ Summer 1981

30

Table 5 Coefficient Estimates of Dynamic Regressions
Standard errors in parentheses
Dependent variables
Independent
variables2

ATOTBNK

ATOTS&L

ATOTOTH

ATOTALL

ATOTHI

ATOTLO$

ATOTALLb

(1)

(2)

(3)

(4)

(5)

(6)

(7)

1.41
(0.908)

0.03
(6.69)

0.084
(0.786)

0.041
(0.160)

0.094
(0.607)

-0 .5 4 8
(0.450)

-0 .7 5 8
(0.846)

-0 .3 2 2 *
(0.173)

-0 .8 5 2
(0.671)

-0 .2 6 0
(0.142)

-1.252**
(0.418)

-1 .0 8 9
(0.786)

-0 .2 8 7 *
(0.160)

-1.860**
(0.638)

0.225
(0.286)

0.029
(0.122)

0.325
(0.359)

1.017
(0.674)

-0 .0 8 4
(0.138)

0.756
(0.532)

-2.89*
(1.16)

1.42
(2.55)

0.81
(1.08)

-0 .6 6
(3.19)

-6 .8 3
(6.00)

-0 .7 4
(1.22)

2.30
(7.89)

0.01

0.02

0.01

0.02

0.01

0.01

0.10

CONSTANT

1.47*
(0.86)

-0 .0 8 6
(1.888)

-0 .7 3
(0.80)

0.651
(2.37)

Lagged 3
A%BLACK

-0 .047
(0.152)

0.284
(0.334)

-0 .1 7 5
(0.142)

0.062
(0.418)

Lagged 2
A%BLACK

-0 .1 7 8
(0.164)

-0 .3 1 9
(0.359)

-0 .051
(0.153)

Lagged 1
A%BLACK

-0 .0 7 7
(0.152)

-0.914**
(0.334)

0.071
(0.130)

A%BLACK
D1979
R2

-8 .6 1 *
(4.45)

* Significant at the 10 percent level.
** Significant at the 1 percent level.
a. The percentage change in black variables represents the change in the percentage black for the contemporaneous year
and the change in the percentage black for one, two, or three years earlier. The dummy variable represents changes in 1979.
b. Sample uses the 75 integrated census tracts, excluding all tracts below 10 percent or above 90 percent black in both 1970
and 1977.

years were chosen as independent variables. De­
pendent variable changes were measured from 1977
to 1978 and from 1978 to 1979. Thus, each tract
provided two observations, for a total of 670. A
dummy intercept shift differentiated 1978 from 1979
observations. Results for the dynamic regressions
are shown in table 5. Columns again denote de­
pendent variables, and rows designate independent
variables. The few significant coefficients are indi­
cated with asterisks.
The dynamic regression fits are not terribly im ­
pressive. The R2 s are not significantly greater than
chance. There is some mild evidence, however, of
a modest pattern. Lending o f all types appears to
decline one year after a rise in the percentage black
in a neighborhood. This effect is significant for sav­
ings and loans and total lending and is echoed by more
modest declines for two-year lags. Because the data
are dominated by all-white and all-black tracts,
the total lending regression was re-run, using only



the 75 integrated tracts most likely to undergo
racial change (regression 7). Though more signifi­
cant, results were similar to those obtained using
all the tracts. In all cases, the evidence shows some
support for the contention that changing neighbor­
hoods would be the ones more susceptible to lim­
itations in mortgage lending and that lenders might
react to changes in relatively short periods of time.

IV. Conclusions
Controlling for income and other demographic
variables, it appears that neighborhood racial com­
position has little impact on the total number of
deed transfers financed by mortgage loans and on
total housing-related financing. However, it also
appears that the portion o f mortgage financing pro­
vided by banks and savings and loans is significantly
lower in integrated and all-black neighborhoods
than in all-white neighborhoods. This is particularly

Federal Reserve Bank of Cleveland
prevalent in changing neighborhoods where the per­
centage of blacks is rising. On the other hand, black
and racially mixed areas are significantly more likely
to be served by mortgage bankers offering FHA/VA
financing. Similarly, banks and savings and loans
are much more likely to make home-improvement
loans in these areas.
It should be stressed that these findings, like those
of previous redlining studies, are based on reducedform regressions. It is difficult to know whether
there have been sufficient controls for demand and
risk factors such that strong inferences can be drawn
about supply. There is also a concern that the sevenyear to nine-year gap between the lending data and
1970 census tract demographics may have caused
distortions, particularly in changing neighborhoods.
Despite these misgivings, however, the strong cor­
relation between neighborhood racial composition
and the type of lending warrants some discussion.
On the surface, it appears that banks and savings
and loans are not serving the “credit needs” o f black
neighborhoods if the word serve is interpreted to
mean conventional mortgage lending. Indeed, con­
trolling for income and other neighborhood char­
acteristics, financial institutions are significantly less
likely to finance title transfers with conventional
mortgages in black and racially mixed neighborhoods.
This finding would constitute redlining under the
definition used earlier. On the other hand, it appears
that funds are being made available to these neighbor­
hoods either through FHA/VA mortgage-banker fi­
nancing or home-improvement loans.
One explanation for this pattern is that, as argued
earlier, financial institutions may feel that all-black
and/or integrated neighborhoods are more risky than
comparable all-white neighborhoods. Because o f this
higher perceived risk, banks and savings and loans
may reason that they cannot offer conventional
mortgage loans in these areas at the same rates as
in white areas or at rates that can compete with
government-insured and sometimes subsidized loans.
They could, o f course, offer conventional financing
but at higher rates. However, there seems to be a re­
luctance to offer differential interest rates by neigh­
borhood. A more likely alternative would be to offer
the same rate but set higher credit standards in risky
neighborhoods, thus relegating a higher fraction of
the mortgage business to other lenders. Over time,



31

real-estate brokers, recognizing this fact and knowing
the high transactions costs involved in mortgage ap­
plications, would steer high-risk neighborhood clients
to FHA/VA-insured mortgage bankers where applica­
tions more likely would be accepted.
The pattern observed in black neighborhoods
with home-improvement loans is consistent with
this scenario. Home-improvement loans offer a method
of housing-related financing at higher rates and
shorter maturities than first mortgages. If houses are
renovated after, rather than before, their sale, homeimprovement loans allow part of the equity to be
financed at higher rates and also reduce the need
for first-mortgage financing.
Even if it is true that redlining is more a matter
of lender type and price than restrictions on credit
availability, there may still be a case for regulatory
concern. Although houses that change hands in
black areas appear to be as likely to receive financing
as those in comparable white neighborhoods, the
long-term absence of conventional bank and savings
and loan lending in these areas may mean that fewer
houses change hands or that selling prices are lower.
Some also have argued that widespread FHA/VA fi­
nancing may lead to more rapid neighborhood de­
terioration (see King 1980). However, there has been
little or no legal guidance as to which actions con­
stitute discriminatory mortgage lending. It is still not
clear, for example, whether differential lending
policies in white and black neighborhoods by them ­
selves constitute violations of any federal discrimi­
nation law. In the absence o f clear-cut judicial de­
cisions, it is difficult for regulatory bodies to enforce
existing laws that have yet to be tested.

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32

Economic Review □ Summer 1981

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