Full text of Economic Policy Review (Federal Reserve Bank of New York) : July 1975, Vol. 57, No. 7

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FEDERAL RESERVE BANK OF NEW YORK

147

T h e B u s in e s s S it u a tio n
Evidence continues to accumulate that recessionary
forces in the economy are dissipating. Indeed, the
end of the worst postwar recession either is close
at hand or already has occurred. The new composite index
of leading indicators posted a substantial gain in May,
following a very large rise in the preceding month and a
small advance in March. In the past, this index has
typically led upturns in general economic activity by only
two months or so. Elimination of the remaining overhang
of inventories would lay the groundwork for an economic
recovery, and progress «on this front also has been made
lately. In April the book value of manufacturing and trade
inventories plunged by $1.8 billion, exceeding the average
decline recorded in the two previous months. Industrial
production slipped a bit further in May; however, the
output of consumer goods increased for the second con­
secutive month. New orders for durable goods rose
strongly in May, as did retail sales. Housing starts have
shown modest improvement, and inroads have been made
lately in reducing the backlog of unsold homes. Total
employment rose in June for the third successive month,
and the unemployment rate declined to 8.6 percent of
the civilian labor force, down from 9.2 percent in May.
However, the decline in joblessness was probably the
result of statistical problems and therefore is an overstate­
ment of the improvement in labor market conditions.
Recent price trends have been generally encouraging.
While fuel prices have increased rather sharply in the past
few months, other prices seem to be leveling off. Con­
sumer prices rose at only a 4.2 percent annual rate in
May, with prices of nonfood commodities edging up at a
2.4 percent rate. This was the smallest such rise in twentytwo months, and it resulted entirely from higher prices for
consumer power and fuel. Wholesale prices declined at a
1.7 percent annual rate in June, as prices of farm products
and related items decreased at a 16.5 percent annual rate.
Prices of industrial commodities rose at a faster rate than
in the last several months. Despite this acceleration, under­
lying inflationary pressures remain moderate since more
than half the 4.6 percent rise in industrial commodity
prices in June was attributable to higher energy prices.




IN D U ST R IA L PR O D U C TIO N , LEADING IN D IC A TO R S,
O RDER S, A N D INVENTORIES

Industrial production declined for the eighth consecutive
month in May (see Chart I), leaving output in the nation’s
factories, mines, and utilities 13 percent below the level
attained last September. Including the modest 0.3 percent
May slippage, the current slide in production now amounts
to the longest sustained drop in seventeen years. None­
theless, compared with the 8 percent contraction in
production averaged in the first quarter of this year, the
mildness of the declines in April and May seems to be
pointing toward a bottoming-out of the current contraction.
The decline in May resulted chiefly from a further fall in the
production of business equipment and materials. Output of
consumer goods, on the other hand, increased for the
second successive month, as production of durable
goods advanced sharply. Stepped-up production of auto­
mobiles accounted for most of the rise, although output
of appliances and furniture also rose during the month. In
June the output of passenger cars continued to increase
to the highest level since last November.
In May the Government’s revised index of leading
economic indicators rose 2.1 percent, a somewhat smaller
increase than the advance posted in the previous month.
The index currently stands at its highest level since last
November, but it is still 25 percent below the peak
registered in the middle of 1973. Nonetheless, the leading
indicators have increased for three consecutive months,
the most sustained advance since July 1973. In the past,
a three-month rise after a sustained decline has invariably
been followed by the end of a recession, so that the most
recent increase strongly suggests the current economic
downturn is ending. Of the ten indicators available for
May, eight rose while the remaining two were unchanged.
New orders for durable goods rose $498 million in
May, continuing an uptrend that initially surfaced last
February (see Chart II). However, the rise was neither
so large as the surge in April nor so broadly based. Much
of the May increase was centered in orders for primary
metals, while bookings for machinery and capital goods

148

MONTHLY REVIEW, JULY 1975

rose only moderately. Orders for household durable goods
were essentially unchanged during May, as were bookings
for transportation equipment. Shipments of durables de­
clined during the month, but they still remained higher than
the level of new orders. Consequently, the backlog of un­
filled orders dropped for the eighth consecutive month.
The book value of total business inventories fell in
April by $1.9 billion. This decline was slightly more than
that recorded in the preceding month, and it marks the first
time since 1961 that stocks have fallen for three consecu­
tive months. Business sales, meanwhile, climbed 2.1
percent in April, after falling in four of the five previous
months. Consequently, the ratio of inventories to sales
equaled 1.65 months in April, down from 1.7 months in
March. At this level, the stock-sales ratio in April was at
its lowest reading since last November though still well
above the 1.46 months of sales reached one year ago.
The accelerating pace of inventory liquidation was
fairly widespread. In April, inventories held by manufac­
turers fell $1 billion, and in May the reduction was
even larger. At the wholesale level, stocks fell by about
$0.5 billion in April, which was well above the decumu­
lation averaged in the previous three months. Retailers,
on the other hand, worked off inventories at only a frac­
tion of the rate recorded earlier in the year. Stocks of
nondurable goods at retail outlets were liquidated at a
rapid rate, but inventories of durable goods, which

Chart II

ORDERS AND SHIPMENTS OF MANUFACTURED
DURABLE G O ODS
Billions of dollars

Seasonally adjusted

llions of dollars

So u rc e : U nited S ta te s D e p a rtm e n t o f C o m m e rce , B u rea u o f the C e n su s.

dropped sharply in the January-March period, were essen­
tially unchanged in April because of a renewed buildup
in stocks of unsold automobiles.
Chart I

INDUSTRIAL PRODUCTION
Seasonally adjusted; 1967=100

S o u rc e :

B oard of G o v e rn o rs of the F e d e r a l R e se rv e Syste m .




P E R SO N A L INCOME, C O N SU M E R D E M A N D , A N D
RESIDENTIAL. C O N S T R U C T IO N

Personal income rose $9.3 billion in May, as both
public and private sector payrolls expanded. The increase
was the largest since last September and, coupled with
the distribution of tax rebates and lower withholding
rates, may provide a boost to consumer spending.
Government payrolls rose modestly in May, but private
sector wage and salary disbursements increased by a hefty
$3.4 billion. Virtually all of this was concentrated in
the service and distribution industries. Manufactur­
ing payrolls edged up only slightly in May, remaining well
below the level of last January. Moreover, this small
increase was centered in expanded payrolls of nondurable
goods producers, as wage and salary outlays of durable
goods producers continued to contract.
Consumer demand at retail outlets climbed 2.2 percent
in May, as expenditures on both durable and nondurable

149

FEDERAL RESERVE BANK OF NEW YORK

goods registered impressive gains. Current-dollar sales
have increased in five of the last six months, with the
most recent advance the largest in percentage terms since
January. Spending on durable goods rose $377 mil­
lion in May primarily because of higher outlays for auto­
mobiles. Although passenger car sales are still depressed,
demand has slowly but steadily picked up in recent
months. Auto sales jumped 8.8 percent to 6.2 million
units in May and, in June, sales rose to the highest level
since February. Finally, spending on nondurables jumped
by more than $600 million in May, the sharpest monthly
advance in nearly two years.
The housing picture also appears to have brightened in
May. Housing starts rose 14 percent in May to a season­
ally adjusted 1.1 million units, the highest level in eight
months. Moreover, newly issued building permits rose
for the second consecutive month in May and are now
higher than at any time since last August. But, while a
housing recovery seems to be in progress, residential
construction activity has been extremely weak and the
number of housing starts in May was 23 percent below
the year-earlier level. However, the upturn may strengthen
somewhat in coming months, since the volume of unsold
homes has been reduced sharply. In April, sales of new
single-family homes jumped 25 percent as the recently
passed tax credit for new-home purchases went into effect.
Combined with a further reduction in the number of
homes available for sale, the backlog fell to 8.1 months in
April, the lowest level in almost two years.

movements in farm prices at the wholesale level.
Wholesale prices declined at a seasonally adjusted 1.7
percent annual rate in June, after rising in each of the
previous two months. The easing in prices was due
entirely to a 16.5 percent annual-rate decline in prices
of farm products and processed foods and feeds. Prices
of livestock and poultry continued rising in June, but
these increases were offset by fairly large declines in
prices of the major feed grains. Industrial commodity
prices advanced at a 4.6 percent annual rate in June,
somewhat faster than in the last few months. Nevertheless,
this does not appear to signal a broad resurgence in
inflationary pressures since the acceleration mainly
reflected higher energy prices. Indeed, industrial com­
modity prices excluding power and fuel rose at only a
2.2 percent annual rate in June. Increases in energy
prices also contributed significantly to a 6.4 percent rise
in crude material prices in that month. Since energy
prices began rising again rapidly three months ago, whole­
sale prices of crude materials have jumped at a 14.1
percent annual rate,
Movements in crude material prices typically parallel
changes in spot prices of industrial commodities. For ex­
ample, beginning in 1972 and extending through four
months of 1974, the run-up in commodity prices was
matched by sharp increases in prices of crude materials
(see Chart III). Dramatic increases in scrap metal prices
were principally responsible for this commodity price

PRICE D E V E L O P M E N T S

Consumer prices rose at a 4.2 percent seasonally
adjusted annual rate in May, as the rate of price increase
of nonfood commodities and services moderated con­
siderably. Over the three months ended in May, retail
prices advanced at a 4.9 percent annual rate, the smallest
three-month rise since the period ended January 1973.
Nonfood commodity prices edged up at only a 2.4 percent
annual rate in May, the smallest increase in twenty-two
months. Consumer energy prices rose sharply in May,
however, and, if these are excluded, nonfood commodity
prices were unchanged in the month. Meanwhile, increases
in the cost of medical care and rents pushed prices of
services up at a 2.9 percent annual rate in May, the
smallest advance in nearly two years. Food prices, on the
other hand, have started to increase more rapidly. In May,
retail food prices rose at a 6.3 percent annual rate, a
somewhat more rapid rate than in April. This accel­
eration, which was attributable to large hikes in prices
of meats and poultry, was not surprising in light of recent




Chart III

PRICES OF INDUSTRIAL MATERIALS
Monthly; 1967:= 100

Percent
240

Percent
|240

220 -

220

Spot industrial /
commodities /

200

200

180

180 ~

160

_

_
/

/ v

140

120 -

100

W holesale crude
m aterials*

140

y

- i 120

1 ! 1 1 1 1 II 1 1 1
1972

i 1111111! m

1 1 1 1 1I II 1 1 1

i i 1 11

1973

1974

1975

* S e a s o n a lly a d ju ste d .
S o u rc e :

160

U nite d Sta te s D e p a rtm e n t o f L a b o r, B u re a u o f L a b o r Sta tistics.

100

150

MONTHLY REVIEW, JULY 1975

spiral. The spot metals index, which accounts for approxi­
mately one half of the entire industrial spot price index,
rose more than 80 percent from the middle of 1973 to
mid-1974. This was characterized by nearly a threefold in­
crease in the price of scrap steel as well as significant
increases in the prices of other metals. Prices of textiles
and other raw industrial commodities, meanwhile, rose
only modestly. By May of last year, market pressures
began softening somewhat, and spot prices started falling,
while the rise in crude material prices leveled off. Since
November both series generally have moved together, but
in May and June industrial spot prices fell while prices of
crude materials spurted somewhat.
There are several factors which account for much of
the discrepancy in these movements. Unlike wholesale
prices, spot market prices are not seasonally adjusted.
Also, the various commodities included in the spot mar­
ket index are equally important, while the relative impor­
tance of each wholesale crude material commodity varies.
Indeed, scrap metal prices amount to only about 20
percent of the wholesale price index for crude materials
but nearly one half of the spot price index. Thus, if metal
prices are rising or falling very rapidly while other prices
are registering small changes, the spot price index will be
affected more than wholesale crude materials.
More broadly, it should be emphasized that the com­
position of the two series differs. In particular, prices of
crude petroleum and bituminous coal are excluded from
the spot price index but are part of the wholesale crude
materials index. Conversely, prices of textiles are included
in the spot market index, but they do not appear in the
index for wholesale crude materials. These differences
became very significant beginning in the summer of 1974,
when a huge gap in the two measures opened up. A
plunge in metal prices and a moderate drop in prices of
textiles pushed spot prices down sharply. However, a
similar decline in wholesale crude material prices was
prevented by sharp increases in energy prices. More re­
cently, further increases in energy prices have again caused
spot and wholesale prices to move in opposite directions.




In fact, a rise in energy prices accounts for most of the
increase in prices of crude materials during May. If energy
prices are excluded, crude material prices barely changed
at all in that month. Hence, the rise in prices of crude
materials does not alter the fact that inflationary pressures
are moderating. Certainly the recent movement in indus­
trial spot prices suggests that the market for most basic
commodities is still rather weak.
LABOR MARKET DEV ELO PM ENTS

Unemployment declined to 8.6 percent of the civilian
labor force in June, after reaching 9.2 percent in the
preceding month. This was the first drop in more than one
year, and the jobless rate is now the lowest since Feb­
ruary. Whether this does in fact mark a definite improve­
ment in labor market conditions is questionable, though,
since the unemployment rate has been distorted by faulty
seasonal adjustment procedures in the last two months.
Subsequent revision will probably show that the jobless
figures initially reported were too high in May and too
low in June. Nevertheless, the total number of employed
persons did rise again in June, although not by as much
as in May, and most of the major categories of workers
experienced lower unemployment in June. On the other
hand, the percentage of those unemployed for more than
fifteen weeks rose to 3.1 percent of the civilian labor force,
the highest since the series began in 1948.
The separate survey of nonfarm establishments suggests
that the labor picture was essentially unchanged in June.
Total payroll employment edged up slightly during the
month, as payrolls in the trade, finance, and services
industries all increased. Government payrolls also expanded
slightly in June, but this may not persist in light of recent
budget cutbacks among states and localities. Meanwhile,
the number of employees in construction fell by 52,000
persons in June. Manufacturing employment also declined
slightly, after rising in May. The drop in June, however,
was not nearly so large as the declines in manufacturing
payrolls registered earlier in the year.

FEDERAL RESERVE BANK OF NEW YORK

151

T h e M o n e y a n d B o n d M a r k e t s in J u n e
Long-term interest rates declined moderately in June,
but virtually all short-term rates and yields on intermediateterm Government securities rose substantially. As the
month opened, all sectors of the credit market displayed
a hesitant tone, with upward pressure on rates stemming
in part from market disappointment that the Federal funds
rate did not decline further. A major rally in the Treasury
bill market and all the coupon markets emerged upon
announcement of a reduction in the volume of Treasury
bill financing in June. By midmonth the yields on threeand six-month Treasury bills had fallen to their lowest
levels in over two and one-half years. Demand proved dis­
appointing at the lower yield levels, and announcements
of the Treasury’s plans to borrow considerably in the bill
market in July caused a sharp, rapid retracing of previous
declines. Market participants also became increasingly
concerned about the rapid growth of the money supply
and the persistent uptrend in the Federal funds rate. By
the end of the month the yield on the three-month Trea­
sury bill was 66 basis points above its level of 5.20
percent at the end of May.
In contrast to the fluctuating movements of Treasury
bill yields, virtually all private money market rates moved
steadily higher over the course of the month. Notably,
the effective rate on Federal funds in June averaged 33
basis points above its average level in May, the first
monthly increase in this rate since July of last year. Other
money market rates displayed similar increases.
The announcement early in the month projecting less
near-term borrowing by the Treasury caused intermediateterm Government yields to fall sharply, but this decline
was virtually erased when the Treasury subsequently an­
nounced that it would borrow $9.4 billion in the bill mar­
ket and the intermediate-term coupon sector prior to the
August refunding. At the same time, the absence of im­
mediate Treasury plans to offer further long-term bonds per­
mitted that sector of the Government market to sustain
the rate decline that had occurred earlier. The long-term
Government market and the private long-term debt mar­
ket also benefited from publication of data on wholesale




and consumer prices which suggested an abatement of
inflationary pressures. In the corporate market, where the
volume of new offerings remained very high, most major
issues offered early in the month sold out quickly at yields
well below those on comparable securities offered in the
preceding month. Resistance to some issues emerged
toward the close of June in the wake of the rise in the
Federal funds rate and the continuing heavy volume of of­
ferings. The municipal market benefited initially from the
favorable impact of the outlook for inflation which was
augmented as the market gained confidence that New York
City would avoid default on its debt due June 11. The
tone of the municipal market deteriorated near the end
of the month, however, as the calendar remained heavy.
Preliminary data suggest that the narrow and broad
money supply measures grew very rapidly in June. The
rapid growth of these monetary aggregates was partially
due to the effects of tax rebates by the Treasury and the
special social security payments made during the month.
Banks continued to allow a large volume of certificates of
deposit (CDs) to run off in June as loan demand re­
mained weak. Despite this, the bank credit proxy posted a
sizable increase on the strength of demand and consumertype time deposit growth.
THE MONEY MARKET AND
THE M ONETARY AGGREGATES

Demand for short-term credit continued to be weak
during June, a month typically characterized by strong
credit demands. At weekly reporting commercial banks in
New York City, business loans rose just $7 million in the
four weeks ended June 25. Moreover, business loans
(including loans sold to affiliates) at weekly reporting
banks in New York City increased only $92 million during
the statement week ended June 18, which included the
June 15 tax date. By contrast, in the preceding three years,
business loan growth had averaged $516 million in the
statement week including the June 15 tax date. The vol­
ume of nonfinancial commercial paper outstanding

MONTHLY REVIEW, JULY 1975

152

Chart I

SELECTED INTEREST RATES
April-June 1975
M ONEY MARKET RATES

April

May

Percent

BOND MARKET RATES

April

May

June

Note: Data are shown for business days only.
M ONEY MARKET RATES QUOTED: Prime commercial loan rate at most major banks;
offering rates (quoted in terms of rate of discount) on 90- to 119-day prime commercial
paper quoted by three of the five dealers that report their rates, or the midpoint of
the range quoted if no consensus is available; the effective rate on Federal funds
(the rate most representative of the transactions executed); closing bid rates (quoted
in terms of rate of discount) on newest outstanding three-month Treasury bills.
BOND MARKET YIELDS QUOTED: Yields on new A aa-rcted public utility bonds are based
on prices asked by underwriting syndicates, adjusted to make them equivalent to a

decreased $673 million in the four weeks ended June 25,
after having decreased $913 million in the four weeks
ended May 28.
The persistent sluggishness of loan demand prompted re­
ductions in commercial banks’ prime lending rates in early
June. A major New York City bank, which uses a formula
as a guide in determining its prime rate, announced a re­
duction from 7 percent to 6% percent at the end of the
initial calendar week of the month. The following Monday,
most other major money-center banks lowered their prime
rate from 1X percent to 7 percent (see Chart I).
A
Other money market rates generally rose in June, par­
ticularly during the last half of the period. The Federal
funds rate averaged 5.55 percent during the month, up 33




standard Aaa-rated bond of at least twenty years' maturity; daily averages of
yields on seasoned Aaa-rated corporate bonds; daily averages of yields on
long -term Government securities (bonds due or callable in ten years or more)
and on Government securities due in three to five years, computed on the basis
of closing bid prices; Thursday averages of yields on twenty seasoned twentyyear tax-exempt bonds (carrying Moody's ratings of A aa, A a, A, and Baa).
Sources: Federal Reserve Bank of New York, Board of Governors of the Federal
Reserve System, Moody's Investors Service, Inc., and The Bond Buyer.

basis points from its average in May. The rate on 90- to
119-day dealer-placed commercial paper increased from
5.38 percent at the end of May to 6.25 percent at the end
of June. Similarly, the yield on 90-day commercial bank
CDs in the secondary market closed the month at 5.93
percent, up 37 basis points from its end-of-May level.
Most money market rates have fluctuated in a narrow
range during the last several months, after dropping sharply
from mid-1974 through early spring of this year. The rate
on Federal funds, for example, fell from a peak of about
14 percent reached at the beginning of July 1974 to about
5lA percent in April and has generally fluctuated between
5 percent and 6 percent since that time. Most other money
market rates have exhibited a similar pattern.

FEDERAL RESERVE BANK OF NEW YORK

Preliminary data suggest that the growth of the narrow
money supply (M J—private demand deposits adjusted plus
currency outside commercial banks— accelerated sharply
during June. Seasonally adjusted, the average level of Mi
in the four weeks ended June 25 was 18.8 percent, on an
annual basis, above the four-week average value four
weeks earlier. This rapid growth of Mx arose, to some
extent, from the disbursement by the Treasury of tax
rebates and from the special social security payments
made during the month. Coupled with the substantial
growth in May, the average level of seasonally adjusted Mx
in the four weeks ended June 25 was 10.8 percent, on an
annual basis, above its seasonally adjusted average level in
the four weeks ended thirteen weeks earlier (see Chart
II). The recent expansion of Mi appears somewhat less
rapid when viewed over a longer time frame. Compared
with its four-week average in the interval ended twenty-six
weeks earlier, Mi grew at a seasonally adjusted annual rate
of 6.5 percent in the four weeks ended June 25.
Depositors continued to find yields on consumer-type
time and savings accounts attractive relative to those
available on open market instruments, and the outstand­
ing volume of these accounts rose rapidly in June. As a
result, M2 which includes these deposits plus Mx
—
—was
19.4 percent higher on a seasonally adjusted annual basis
in the four weeks ended June 25 than it had been
in the four-week period ended four weeks earlier. The
average level of commercial bank large negotiable CDs
outstanding declined at a seasonally adjusted annual rate
of 27.3 percent over the same period. Despite this decline,
the growth of the adjusted bank credit proxy— all deposits
at member banks subject to reserve requirements plus
certain nondeposit sources of funds—was also rapid in
June. Its seasonally adjusted average level in the four
weeks ended June 25 was 17.4 percent higher, on an
annual basis, than its average level in the preceding fourweek period. Member banks continued to make little use
of the discount window, and borrowings equaled $97
million in June (see Table I).

153

Table 1
FACTORS TENDING TO INCREASE OR DECREASE
MEMBER BANK RESERVES, JUNE 1975
In millions of dollars; (+ ) denotes increase
and (—) decrease in excess reserves
Changes in daily averages—
week ended

Net
changes

Factors
June
4

June
11

June
25

June
18

“ Market” factors
M em b er

b an k

O peratin g

req u ired

reserves

tr a n sa c tio n s

o p era tio n s*

146

+

+ 4 ,0 2 3

-f

—

331

+ 1 ,6 4 8

......................................

841

454

+ 1 ,3 7 0

............

....................................

F e d e r a l R eserve flo a t
T reasu ry

............... —

(su b to ta l)

--

7

2

+

18

+ 4 ,0 3 1

+

337

—

27

— 560

— 3,063

+ 2 ,3 2 3

—

195

+

152

— 2,763

+ 3 ,2 5 3
+

G o ld a n d fo r eig n a c c o u n t ............................. —

4

27

—

48

+

—

233

—

504

—

232

—

292

............................................................ —

372

+

+

123

C urrency o u tsid e
O ther

F ed eral

a n d c a p ita l
T o ta l

" m a rk et”

banks

R eserve

fa c to rs

...............................

+

63

38
1,261

lia b ilitie s
470

_

82

+ 1 ,2 2 4

+ 4 ,4 7 7

-

848

— 3,090

+ 1 ,7 6 3

— 1,364

— 4,744

+ 1 ,1 0 8

+ 2 ,6 7 7

— 2,323

+ 1 ,4 7 7

— 1,233

...............................

+

139

Direct Federal Reserve credit
transactions
O pen m ark et o p era tio n s

(s u b to ta l)

............

O u trigh t h o ld in g s :
—

837

> 2,680
—

+

807

......................................

—

9

—

27

-

26

F e d e r a l a gen cy o b lig a tio n s ..........................

—

54

—

3

T reasu ry se c u r itie s

...........................................

B a n k er s' a cc ep ta n ces

—

7

—

69

—

-

57

879

R e p u rc h a se ag re em e n ts:
T reasu ry se c u r itie s

...........................................

—

568

— 1,640

+

307

+1,022

—

......................................

+

53

—

119

+

3

+

106

+

43

F e d e r a l a g en cy o b lig a tio n s ..........................

+

51

—

275

+

17

+

79

—

128

—

46

+

40

+

+

104

_

1

+

114 +

B a n k e r s’ a cc ep ta n ces

M em b er b a n k b orrow in gs
S e a s o n a l b o rro w in g s!

.................................

......................................

O ther F e d e r a l R eserve assets}: ........................

—
—

1

+

325

— 1,039

Excess reserves! ........................................... +

185

+
—

2
48

— 4,838

+ 1 ,2 6 2

—

+

361

414

110
—

—

25

+

416

+ 2 ,8 1 2

— 1,803

—

—

278

40

Monthly
averages!

Daily average levels

Member bank:
T o ta l reserves, in c lu d in g v a u lt c a s h j ..........

THE G O V ERNM ENT SECURITIES M ARKET

The tone of the Government securities market in June
was dominated largely by anticipations and announcements
regarding Treasury borrowing plans. An optimistic atmo­
sphere emerged soon after the first regular bill auction,
when the Treasury announced plans to reduce its borrow­
ings at the second and third bill auctions of the month,
and rates plummeted dramatically in response. The lower
rate levels attained proved to be unsustainable, however,
and announcements of further borrowing in the bill and




34,543

33,728

34,978

34,732

34,495

R e q u ired reserves .....................................................

34,197

33,743

34,584

34,611

34,284

E x c e s s reserves

.........................................................

15

399

121

213

84

38

78

188

97

......................................

9

11

10

10

10

N on b orrow ed reserves ...........................................

34,459

3 3,690

34,900

34,544

34,398

N e t carry-over, e x c ess or d eficit (— ) | | . . . .

36

42

124

23

T o ta l b orrow in gs

346

.....................................................

S e a so n a l b o rro w in g s!

—

—

N o te : B e c a u se o f ro u n d in g , figu res do n o t n e c e ssa r ily a d d to to ta ls.
* I n c lu d e s ch a n g es in T reasu ry curren cy a n d ca sh ,
t I n c lu d e d in to t a l m em ber b ank borrow ings.

t

I n c lu d e s a sse ts d en o m in a ted in fo r eig n curren cies.

§ A verage for four w eeks en d ed J u n e 25, 1975.
|| N o t re flec ted in d a ta above.

109

154

MONTHLY REVIEW, JULY 1975

Chart II

CHANGES IN MONETARY AND CREDIT AGGREGATES
Seasonally adjusted annual rates
Percent

Percent
15

1

Ml

1
/\

\\

J

/ \

From 52
weeks earlier

J

From 13
weeks earlier

1 j 1 1 1 1 1 1 1 1 I 1 1 1 1 11
M2

11

1
1

From 52
weeks earliei

,-rsv

\

__

1 It

15

|
/




in bids was received for the $2 billion in notes of­
fered. Investors were also disappointed that the average
issuing rate was not lower than the 6.61 percent set.
The concern of participants in the intermediate portion
of the market increased when the Treasury announced
that included in the $9.4 billion it planned to raise
between July 1 and August 15 was a $1.75 billion fouryear note issue and a $1.5 billion two-year note issue. At
the same time, the long-term sector of the market was
encouraged by the absence of any long-term issue in the
Treasury’s financing plans. In this environment, inter­
mediate rates rose sharply while long-term rates remained
stable. The four-year note payable July 9 was auctioned
on June 25. Investor interest was keen, and the note was
awarded at an average rate of 7.83 percent. At the close
of the month, the index of yields on intermediate-term
Government securities stood at 7.56 percent, up 23 basis

L

intermediate sectors pressed rates upward quickly. Long­
term Government securities yields remained firm at the
lower rates attained, as that sector of the market was
relieved by the absence of further long-term bond bor­
rowing in the immediate future.
The bill market displayed a hesitant tone initially, and
this prompted a slight increase in the average rates on
three- and six-month bills at the first regular weekly
auction of the month. A firmer tone began to manifest
itself subsequent to the auction when it was announced
that $300 million less would be raised at the following
auction. The market improved even further when it was
later announced that the Treasury would offer only $4.5
billion in bills at the June 16 auction in return for $6 bil­
lion in bills maturing on June 19. Rates moved down at
the June 16 auction, as market participants contemplated
this net repayment, and the average issuing rates for the
three- and six-month bills were set at 4.77 percent and
5.13 percent, respectively (see Table II), down 44 basis
points and 34 basis points from the rates set at the last
auction in May. Market participants were disappointed,
however, that tenders for bills were spread over an un­
usually wide range and that post-auction demand was not
so strong as anticipated. The market weakened the follow­
ing day, when interest in the two-year note auction was
less enthusiastic than had been expected. It deteriorated
even further later that week, when the Treasury announced
plans to raise $9.4 billion of new cash between July 1 and
August 15. Included in those plans were increases in the
volume of offerings at the weekly bill auctions, beginning
with the last regular weekly auction in June, and the raising
of $600 million in new cash at the auction of 52-week bills
in late June. Upward rate pressure also followed System
action to absorb reserves on Friday, June 20, through
matched sale-purchase agreements at a time when money
market participants expected the System to supply re­
serves. In the wake of these developments, rates rose
sharply. Yields on the three-month, six-month, and 52week bills closed the month up 66, 68, and 65 basis
points, respectively, from their end-of-May levels of
5.20 percent, 5.44 percent, and 5.78 percent.
The announcements of the reduction in the supply of
bills early in the month had a positive influence upon the
coupon sector of the Government securities market. And
this sector also benefited from reports suggesting an
abatement of inflation. Rates on most issues fell through
midmonth, when an upward correction began to take
hold. Investors and dealers were disheartened with the
wide range of tenders at the June 16 bill auction and
the unexpectedly low volume of bids at the two-year note
auction on June 17. At that auction, only $2.6 billion

10

1

From 13
weeks earlier

1 11

I I I

1 1J 1 1 1

—

1

1

1

I I

I..1

1

1

1

5
0

N o te: G ro w th ra te s a re co m p u te d on the b a s is o f fo u r-w e e k a v e r a g e s o f d a ily
fig u re s fo r p e rio d s e n d e d in the statem e n t w e e k plo tte d , 13 w e e k s e a rlie r an d
52 w e e k s e a rlie r . The late st statem e n t w e e k plotted is Ju n e 2 5, 1 97 5.
Ml = C u r re n c y p lu s a d ju ste d d e m a n d d e p o sits h e ld by the p u b lic .
M 2 = M l p lu s co m m e rc ia l b a n k s a v in g s a n d tim e d e p o sits ho ld b y the p u b lic , less
n e g o tia b le c e rtific a te s o f de po si? issu e d in d e n o m in a tio n s o f $ 1 0 0 ,0 0 0 or m ore.
A d ju s t e d b a n k c re d it p r o x y = T o ta l m em ber b a n k d e p o s its s u b je c t to re se rve
re q u ire m e n ts plus n o n d e p o sit so u rc e s o f fu n d s, such as E u ro -d o lla r
b o rr o w in g s a n d the p ro c e e d s of co m m e rc ia l p a p e r issu e d by b a n k h o ld in g
co m p a n ie s or ofher a tfilia tc s .
S o u rc e :

B o a rd o f G o v e rn o rs of the F e d e ra l R e se rv e Systorri.

FEDERAL RESERVE BANK OF NEW YORK

points from its closing level in May. In contrast, the long­
term Government bond yield index was down 15 points
at 6.86 percent at the end of June.
Developments in the market for Federal agency obliga­
tions paralleled those in the intermediate sector of the
Government securities market. Rates fell initially in the
generally optimistic trading atmosphere, which prevailed
early in the month, but then retraced earlier declines when
the Government’s borrowing plans for the July 1-August
15 period were announced. A further dampening factor in
the agency market was the unexpected announcement by
the Federal National Mortgage Association (FNMA) of
its plans to market $300 million in nine-year notes dated
June 26. The notes carried an 8.2 percent coupon and
were placed slowly. Earlier in the month, a Banks for
Cooperatives offering of $423.7 million of 5.65 percent
bonds due January 5, 1976 was very well received when
priced at par. A concurrent Federal Intermediate Credit
Bank offering of $1.3 billion was also very well received.
That offering consisted of $738.5 million of 5.8 percent
bonds due April 1, 1976 and $531 million of 7.4 percent
bonds due in four and one-half years. A Federal Land
Bank $390.5 million offering of 8.10 percent bonds due in
ten years was also very well received when priced at par.
Yields declined at the first two FNMA mortgage com­
mitment auctions held in June, but the yield on FNMA
commitments to purchase insured mortgages rose at the
June 30 auction. At these auctions, held every other
Monday, mortgage originators bid for four-month com­
mitments from FNMA to purchase insured and conven­
tional mortgages. Yields at these auctions and the volume
of offerings to FNMA rose substantially in March and
April, reflecting expectations of higher interest rates over
the four-month horizon. These expectations stemmed in
turn from the market’s impression that the large volume
of Federal borrowing would cause a sharp rise in interest
rates. Beginning in late May and continuing through June,
these expectations were revised in view of the overall
stability of interest rate levels. At the last FNMA mort­
gage auction in June, the yield on four-month com­
mitments on insured mortgages was set at 9.07 percent.
Even though this was slightly above the yield set on in­
sured mortgage commitments at the preceding auction,
it was still 22 basis points below the 9.29 percent rate
on insured mortgages set at the May 5 auction.
THE OTHER SECURITIES M ARK ETS

Both the corporate and municipal bond markets im­
proved in June. These markets sustained strong rallies
through the middle of the month, largely in response to




155

Table II
AVERAGE ISSUING RATES
AT REGULAR TREASURY BILL AUCTIONS*
In percent
Weekly auction dates— June 1975
Maturity

1
June
2

June
9

!

June

16

June
23

June
30

T h r ee-m o n th .............................................

5.258

5.080

4.767

5.665

6.009

S ix -m o n th ..................................................

5 .505

5.283

5.129

5.935

6.262

Monthly auction dates— April-June 1975
April
2
F ifty -tw o w e e k s ........................................

April
30

May
28

June
24

6.475

6.400

5.803

6.292

* In terest rates 011 b ills are q u oted in term s of a 3 0 0 -d a y year, w ith th e d isc o u n ts
from par a s th e retu rn on th e fa c e am o u n t of th e b ills p ayab le a t m a tu r ity . B o n d
y ie ld e q u iv a le n ts, re la ted to th e a m o u n t a ctu a lly in v e sted , w ou ld be s lig h tly high er.

the near-term decline in the volume of Treasury offerings
and the reported reductions in the rate of inflation. In the
municipal market, a further impetus to higher prices was
provided by the temporary resolution of New York City’s
liquidity problems. The city had been in danger of default­
ing on $792 million in notes and interest due June 11.
The possible default on these securities was avoided when
the New York State legislature enacted legislation estab­
lishing the Municipal Assistance Corporation (MAC).
Among its various powers and responsibilities, the cor­
poration is authorized to issue up to $3 billion in long­
term debt in order to repay a like amount of the city’s
short-term debt. Upon enactment of the legislation es­
tablishing the MAC, funds were made available to the city
to pay off its maturing debt through a combination of
rollovers of outstanding loans, advances from New York
State, and incoming city revenues. The initial issue by the
MAC of a record $1 billion of tax-exempt bonds on June
30 sold slowly despite offering yields ranging from 6.5
percent in 1977 to 9.5 percent in 1990.
With the exception of the MAC offering, the largest
tax-exempt issue of the month was a $450 million offering
by Massachusetts sold on June 30. The state’s credit
rating had been lowered to A -l earlier in the month in
view of the recent frequency of its offerings and the state’s
budget deficit. The issue was comprised of equal $90
million amounts maturing in 1976-80. It was priced to
yield from 4.75 percent in 1976 to 5.8 percent in 1980 and
was virtually sold out on the day it was offered. Among

156

MONTHLY REVIEW, JULY 1975

the other major municipal bond offerings of the month
were $100 million offerings by the State of California and
the State of Connecticut. The $100 million Aaa-rated
California offering reached the market early in the month
and incurred an average issuing cost of 5.84 percent for
maturities running from 1976 to 1995. The bonds were
reoffered by the underwriters to yield from 3.60 percent
to 6.40 percent and were about 70 percent sold by the
end of the first day of trading. The Connecticut issue,
which was marketed a week later, fared better even
though one of the rating agencies had lowered the rating
of Connecticut’s debt to Aa in view of the state’s budget
deficit. The issue was awarded at a net interest cost of
5.64 percent for the same maturity range as the California
offering. The Connecticut issue was almost entirely sold on
the first day of trading after it was reoffered to yield from
3.50 percent to 6.10 percent.
The largest corporate debt offering of the month was
a $300 million issue of thirty-year bonds by Standard
Oil Co. of Indiana, which came to market on June 12.
The Aaa-rated issue carries an 8% percent coupon and is
protected for ten years against early redemption. When
priced to yield 8.47 percent, the issue sold out quickly.
In contrast, during May, Aaa-rated industrial offerings
of the same maturity by Texaco Incorporated and Shell
Oil Company were priced to yield 8.95 percent and 8.82
percent, respectively. The following week, Monsanto Com­
pany, whose debt securities carry an Aa rating, offered a
package consisting of $175 million of twenty-five year
bonds and $100 million of ten-year notes. The twenty-five
year bonds, which carry an 8 V2 percent coupon and tenyear call protection, were offered to the public at 8.55
percent, just 8 basis points above the yield on the Aaarated Standard Oil issue. They were sold out by the end




of the first day of the offering. The ten-year notes carry
an 8 percent coupon and are protected for seven years
against early redemption. They also sold out rapidly when
priced at par.
Two Bell System bond issues came to market in
June. Early in the month, a New England Telephone
& Telegraph Co. offering of $175 million in thirty-five
year notes carrying a 9Vi percent coupon was marketed
at a yield of 9.475 percent, a rate at which they sold
out quickly. The relatively high yield on the issue reflected
the diverse ratings accorded New England Telephone
by the rating agencies. Moody’s maintained the company’s
Aaa rating, but Standard & Poor’s gave the company
an Aa-1 rating in view of the company’s relatively low
debt-coverage ratio. The bonds are protected against
call for five years. Later in the month, Northwestern
Bell Telephone Company, whose debt has an Aaa rating,
encountered stiff market resistance to a $150 million
offering of 8% percent bonds due in 2012. The issue,
which is protected against call for five years, was ap­
parently priced ahead of the market when reoffered by
the underwriters to yield 8.65 percent. Only about 50
percent of the issue sold out on the day it was offered, and
the supply overhang tempered the market rally.
Overall, the improved tone of the corporate and munic­
ipal bond markets brought the Federal Reserve Board’s
index of yields on recently offered Aaa-rated corporate
securities down to 9.41 percent by the end of June, com­
pared with 9.70 percent at the end of May. The weekly
Bond Buyer index of twenty bond yields on twenty-year
tax-exempt bonds dropped 9 basis points to 7 percent. The
Blue List of dealers’ advertised inventories fell $54
million from its level of $614 million at the end of the
preceding month.

FEDERAL RESERVE BANK OF NEW YORK

157

T o w a r d E a rly W a r n in g o f C h a n g e s in B a n k s ’ F in a n c ia l
C o n d itio n : A P r o g r e s s R e p o r t
By L e o n

K o r o b o w a n d D a v id P . S t u h r *

It has always been the responsibility of bank supervi­
sors to identify and investigate a weakening financial
situation at any bank under their jurisdiction and to
require bank management to take remedial action. An
important supervisory aid in fulfilling this responsibility is
the on-site examination, and practically all the nation’s
banks are subject to on-site examinations at regular inter­
vals. Yet, it is clearly desirable for bank regulatory
authorities to have current information on a bank’s under­
lying financial condition in the periods between examina­
tions. To some extent, this need is met by the detailed
balance-sheet and operating data that are reported by the
banks to regulatory authorities and by other financial
information which is available generally. Recently this
current financial information has begun to be probed
systematically for possible u s q in developing early warn­
ing indicators to assist bank supervisors. The events of
the recent past, when a few large banks had to be
absorbed by other banks, have reemphasized the need for
a continuing effort to improve our techniques for identify­
ing a deteriorating situation at an early stage.
The Banking Studies Department of the Federal Re­
serve Bank of New York has been engaged in ongoing

* Leon Korobow is Manager of the Banking Studies Depart­
ment of the Federal Reserve Bank of New York. David P. Stuhr
is an economist in the Banking Studies Department and Associate
Professor of Finance at Rutgers University. The authors want to
acknowledge the contribution to this project made by their col­
leagues at the Federal Reserve Bank of New York. They wish to
note particularly the substantial contributions of Daniel Martin,
senior banking research analyst in the Banking Studies Depart­
ment, Robert Van Wicklen, market research analyst in the Securi­
ties Department, George R. Juncker, chief of the Bank Analysis
Division, Richard W. Nelson, chief of the Banking Studies Divi­
sion, and Christopher Kell, of the Data Services Function. The
authors, however, take full responsibility for this paper.




research to develop a statistical procedure that would aid
in the evaluation of the financial soundness or weakness
of banks from a specific set of financial variables. The
initial results of these efforts, reported elsewhere, are
promising.1 In brief, they show that financial variables
obtained from empirical data can be used in a discrim­
inant function to distinguish, with a high degree of accu­
racy, between banks that were accorded high summary
(or composite) ratings by bank supervisory authorities
and banks that were given low summary ratings.
The purpose of this paper is to report the results of
further research into the use of statistical procedures,
including discriminant analysis, to provide bank supervi­
sory authorities with advance warning of possible de­
terioration in the financial condition of banks under their
jurisdiction. The overall thrust of our research has been
to identify banks that are potentially vulnerable to finan­
cial difficulty, compared with those that can be considered
resistant. One of our aims is to provide an indication of a
bank’s ability to withstand adverse economic or financial
developments from data that are regularly available
without an on-site examination. Through these ap­
proaches, we believe efficiencies can be achieved in the
allocation of supervisory resources devoted to preserving
and encouraging a sound and competitive banking sys­
tem. The results thus far indicate that the statistical

1 See David P. Stuhr and Robert Van Wicklen, “Rating the
Financial Condition of Banks: A Statistical Approach to Aid
Bank Supervision”, Monthly Review (Federal Reserve Bank of
New York, September 1974). pages 233-38. See also Joseph F.
Sinkey, Jr., and David A. Walker, “Problem Banks: Identification
and Characteristics”, Journal of Bank Research (Bank Administra­
tion Institute, Winter 1975), and Joseph F. Sinkey, Jr., “A Mul­
tivariate Statistical Analysis of the Character of Problem Banks”,
The Journal of Finance (American Finance Association, March
1975).

158

MONTHLY REVIEW, JULY 1975

Since the analysis was designed to separate two distinct
groupings (i.e., financially sound vs. weak), we expected
— as proved to be the case— that the discriminant scores
of banks given an intermediate summary rating by super­
HOW D ISC RIM INANT A N A L Y SIS CAN
visory personnel (i.e., a rating of “2” ) would, in general,
BE U SE D TO C L A SSIFY B A N K S
fall between the scores of the high and low groups.
In this earlier work, the discriminant functions were
The latest results of the discriminant project are very
much an outgrowth of the work described in the Sep­ obtained from data for 1967 and 1968. After studying
tember 1974 Monthly Review. It is useful, therefore, to the discriminating power of many types of variables
summarize how discriminant analysis was applied in the thought to be important factors in determining financial
earlier research. In brief, discriminant analysis is a pro­ soundness or weakness as defined by supervisory person­
cedure for studying two or more distinct groups of nel, we concluded that eight variables yielded superior
observations. This process involves the estimation of an discrimination with respect to the ability of a discriminant
equation that simultaneously takes into account the effects function to distinguish between the two broad groups
of the variables considered to be important in distinguish­ (i.e., sound and weak) based on the summary ratings
ing between the groups. Once the equation is estimated, it given banks by supervisory personnel. Several of
can be used to classify individual observations in a group these variables were intended to measure each of the
by multiplying the values of the variables in the equation factors considered by bank supervisors to be important
by their respective coefficients and obtaining a “discrim­ determinants of bank soundness. For example, certain
inant score” for the particular observation. The dis­ aspects of general bank management ability were included.
criminant score determines the group into which the Net income before taxes, as a percentage of total capital,
observation is classified.2
and dividends, also as a percentage of total capital, were
The coefficients for the variables are determined so as expected to reflect overall bank performance. Further,
to maximize the squared difference between the mean bank borrowing (e.g., gross purchases of Federal funds)
scores of the groups, relative to the degree of variability as a percentage of total capital was designed to capture
of the scores within each group. A small difference in one type of risk exposure. Asset quality was measured by
means, relative to this variability, will result in a large the ratio of classified loans and securities plus one half of
overlap between the distributions of the discriminant scores specially mentioned loans to total loans and securities.
and a relatively high probability that the function will not (This information was obtained from examination reports
classify correctly.
of state-chartered member and national banks.) Capital
In the early phase of the work, banks that received adequacy was measured by the ratio of total capital to
a high summary rating (“ 1” ) from Federal Reserve Bank total assets. Three other variables were introduced to hold
of New York supervisory personnel over a specified period constant several major factors that could be expected to
formed a group of banks considered financially sound, affect the financial condition of a bank: (1) total deposits,
and banks that received a low (“3” or “4” ) summary suggesting that a large bank can benefit from portfolio
rating were considered the weak group. A sample of banks diversification and, with its greater resources, may be in a
from each of these two respective groups was chosen, and position to attract highly qualified personnel; (2) net occu­
various data pertaining to these banks were employed to pancy expense as a percentage of net income, introduced
estimate a discriminant function. (Banks with interme­ as a proxy for branch structure as well as the efficiency
diate (“2”) summary ratings were not used to estimate the of that structure; and (3) the loan-asset ratio, to measure
function.) With the sample data chosen, a discriminant the risks inherent in the asset portfolio.
function was estimated by means of a computer program
Earlier this year we employed these same discriminant
that calculated weights for the given set of financial vari­ functions, as estimated from data for 1967 and 1968, to
ables being used in the function. Once the function was obtain discriminant scores for the state-chartered member
computed, it was used to calculate a discriminant score for banks in the Second Federal Reserve District by entering
each member bank in the Second Federal Reserve District. 1974 data for the variables in the function. We had two
purposes in mind: first, to test whether the same dis­
criminant functions with coefficients developed from the
data for 1967 and 1968 could distinguish the banks that
had high summary ratings in 1974 from those that had
2 See Stuhr and Van Wicklen, op. cit., pages 235-36, and the ref­
erences cited therein.
low summary ratings and, second, to investigate in­

procedures described in this article can make a significant
contribution to this objective.




FEDERAL RESERVE BANK OF NEW YORK

stances in which banks that had received high or intermedi­
ate summary ratings from supervisory personnel in 1974
nonetheless received low scores from the discriminant
functions. In these latter cases, either the functions were
in error or, on the contrary, were suggesting weakness in
advance of a change in the banks’ respective summary
ratings.
With regard to the first objective, we found that the
discriminant functions correctly classified all the banks
with low summary ratings and virtually all the banks with
high summary ratings. With regard to the second objec­
tive, we found that several banks having intermediate sum­
mary ratings in 1974 received low discriminant scores
when 1974 data were entered for these banks in both the
1967 and 1968 functions estimated earlier. On further
investigation we found that most of them were being
subjected to special scrutiny by supervisory personnel. In
general, our analysis indicated that the failure of the dis­
criminant score to confirm a bank’s current summary
rating was cause for further investigation of the bank’s
condition, particularly when the discriminant score was
suggestive of a weakening situation.
DEVELOPING AN EARLY W ARNING PR O C E D U R E
PROBLEMS IN OBTAINING APPROPRIATE DATA AND SAMPLE

The experience with the 1967 and 1968 discrimi­
nant functions just described clearly showed that certain
financial statistics can be used successfully to classify
banks according to the summary ratings given by
supervisory personnel. Moreover, these functions also
demonstrated an ability to anticipate changes in a bank’s
summary rating. The apparent misclassifications of several
banks that had not been given low summary ratings
by supervisory personnel were validated when these
banks’ ratings subsequently were downgraded. Thus, there
seemed to be significant evidence to suggest that there
are decided differences between banks that are sound
financially and likely to remain so for some time in the
future and banks that, while enjoying a high or inter­
mediate summary rating in any current period, may be
vulnerable to deterioration in the future.
In extending the earlier research, our objective has been
to develop a statistical procedure or function that could
provide an accurate indication of a bank’s “resistance” or
“vulnerability” to financial difficulty in the future. The pos­
sible use of the earlier discriminant functions to identify
banks that are either “resistant” or “vulnerable”, however,
raised a number of questions. First, it was evident that the
quality-of-assets variable based on data from on-site ex­
aminations was very important in distinguishing banks with
ba nk s.




159

high summary ratings from those with low summary rat­
ings in any current period. It was not clear whether resis­
tance or vulnerability could be determined accurately
from the information in an examination report many
months old. Data for the quality-of-assets variable would
normally be available only after an on-site examination
was completed. Thus, it would usually not be possible to
obtain discriminant scores more than once annually if such
data were needed in the discriminant function.
One approach to remove the dependence on examina­
tion data was to investigate proxy variables for the qualityof-assets variable, i.e., to use regularly reported financial
data to obtain variables that were sensitive indicators of
a potential decline in a bank’s asset quality. We expected
such variables to contribute to low discriminant scores for
those banks that were vulnerable to general economic
adversity and likely to be accorded low summary ratings
in the future, even though the banks’ current summary
ratings might indicate high or intermediate appraisals by
supervisory personnel. In other words, we reasoned that
a good early warning function might be likely to accord
low discriminant scores to banks with intermediate or even
high summary ratings in the current period, if those banks
evidenced vulnerability that could result in low summary
ratings in the future.
A second problem in using the functions we estimated
earlier deals with the samples that might be used to dis­
tinguish between banks that are resistant to financial
difficulty and those that are potentially vulnerable. In the
earlier work, discriminant functions were estimated from
sample banks grouped according to high and low summary
ratings awarded by supervisory personnel. A discriminant
function based on the data of such sample banks might be
expected to emphasize variables that are important in
making that distinction. While it is reasonable to expect
that banks with high summary ratings can be considered
resistant to financial difficulty and banks with low ratings
nonresistant, we believed it possible that sample data from
such banks might tend to reflect differences that are im­
portant in simulating current summary ratings given
by supervisory personnel. Since our goal is to detect
banks that are vulnerable to a weakening in their financial
condition in the future, rather than merely to simulate the
current summary ratings determined by supervisory per­
sonnel, we decided to explore a method of defining
resistant and vulnerable banks independently of these
supervisory ratings. We expected that a sampling of banks
that are relatively resistant to financial difficulty as dis­
tinguished from banks that are potentially vulnerable might
yield different information than that obtained from bank
samples based on high and low current summary ratings.

MONTHLY REVIEW, JULY 1975

160

DEFINING RESISTANCE AND VULNERABILITY INDEPENDENTLY

We investigated a number of
financial variables, excluding data from examination re­
ports, which most bank analysts and bank supervisors
would agree are important indicators of bank perfor­
mance and financial strength. Our initial set of variables
included many that were studied at an earlier stage in
estimating discriminant functions to classify banks accord­
ing to their current summary ratings, whether or not these
variables had proved useful in making that distinction.
These variables were included in this analysis if there was
a theoretical basis for believing that high or low values of
the variable would be suggestive of resistance to financial
difficulty or of potential vulnerability. For example, liquid­
ity variables that had not proved useful in classifying
banks in a current year by means of discriminant analysis
were investigated on the grounds that bank illiquidity may
indicate a willingness of bank management to undertake
above-average risk. Further, the return on loans was
added as a proxy for the quality-of-assets variable, since
the former variable is likely to be correlated with, and
possibly be a leading indicator of, actual loan losses. A
higher than average nominal return can represent compen­
sation for possible increased losses in the future if eco­
nomic conditions become adverse. The full set of variables,
described below, is intended to be sensitive to a bank’s:
(a) management quality, as indicated by income earned
and dividends paid; (b) efficiency, as indicated by oper­
ating expenses in relation to revenues; (c) capital
adequacy, as reflected in gross capital to total assets and in
gross capital to total loans; (d) risk exposure, as reflected
in the bank’s use of Federal funds and other such bor­
rowed funds, but exclusive of certificates of deposit,
average interest cost of time and savings deposits, the level
of total loans in relation to total assets, the rate of return
on loans, and the ratio of commercial and industrial loans
to total loans; (e) liquidity, as reflected in a bank’s hold­
ings of United States Government securities; and (f) size,
as measured by total deposits.
The variables described above were employed to de­
fine two distinct groups of banks, one that is resistant to
adverse economic conditions and one that is vul­
nerable, without resort to supervisory ratings.3 In using
of

s u p e r v is o r y

r a t in g s.

specific variables for this purpose, we expected that the
independent effects of certain of them (those listed be­
low denoted by a plus sign) would be positively asso­
ciated with resistance to financial difficulty, while others
(denoted by a minus sign) would be positively associated
with vulnerability.
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
(10)
(11)
(12)

Net income before taxes/Total capital
Dividends/Total capital
Gross capital/Total assets
Holdings of Government securities/Total assets
Size, in terms of deposits
Operating expenses/Total revenues
Loans/Gross capital
Gross Federal funds purchased and other
such borrowed funds/Total capital
Loans/Total assets
Commercial and industrial loans/Total loans
Rate of return on loans (as a proxy for risk)
Average interest rate paid on time and savings
deposits

+
+
+
+
+
—
—
—
—
—
—
—

These variables were combined by means of a relatively
simple index procedure. First, we calculated the mean and
standard deviation of each variable in order to obtain a
measure of each bank’s performance in relation to a large
number of other banks with respect to the particular
variable. Then we subtracted from the specific value of
each variable for each bank the overall mean of that
variable and divided the result by the standard deviation.
The resulting standardized deviations were summed for
each bank.4 The sums then were arrayed from high­
est to lowest, forming a ranking in which we expected the
resistant banks to be at the top and the vulnerable banks
at the bottom. This ranking was used in two ways, as
described further below: (1) to place banks with low rank­
ings in a group designated as vulnerable and to place banks
with high rankings in a group designated as resistant and
(2) to obtain samples of banks from which a function was
estimated for the purpose of dividing banks into these two
groups.5

4 This procedure implies an equal weighting of all the variables.
3 The variables just described are not meant to be an exhaustive
5 The discussion of these two groups does not include an inde­
list of indicators of resistance to financial difficulty or vulner­
pendent test of resistance or vulnerability, but rather focuses on
ability. It is likely that other variables may be important discrim­
how this approach can improve the efficiency with which super­
inators.
visory resources are allocated.




FEDERAL RESERVE BANK OF NEW YORK
t h e p e r i o d a n d t h e d a t a . The period studied covered
1969 to early 1975, years in which there were significant
financial strains in our economy and a deterioration in the
financial condition of some banks that consequently
were given low summary ratings. Financial data were
obtained from the Reports of Income and Reports of
Condition for all banks in the Second Federal Reserve
District for 1969-71. Information from examination re­
ports was employed for 1968.6 In addition, the summary
ratings for all the member banks in the Second District
were obtained from Federal Reserve Bank of New York
supervisory personnel for the period 1969 to early 1975.

161

avoiding such misclassification errors.
In specifying the relative importance of these mis­
classification errors, we recognized that the value to bank
supervisors of the procedures we investigated had to be
based on the ability to identify the banks that received
low summary ratings from supervisory personnel over the
period studied, including those that had low ratings in
the initial year of the period as well as those that received
low ratings in subsequent years. In this regard, we ex­
pected most of the banks receiving low summary ratings
during the period studied would be in the bank group
designated vulnerable, along with a number of banks
having intermediate summary ratings and perhaps a very
SEPARATING BANKS INTO VULNERABLE AND RESISTANT
small number of banks with high summary ratings. In
c l a s s e s . Several alternative procedures were employed to
contrast, we expected the resistant group to consist of
divide all the member banks in the Second Federal Reserve very few banks with low summary ratings, most of the
District into two groups— i.e., resistant and vulnerable— in banks with high summary ratings, and the remainder
each of the several selected years. The multivariate rank­ comprised of banks with intermediate summary ratings.
In aiming at this objective, we proceeded on the assump­
ing, based on the twelve variables described earlier, and
a function based on that ranking were used to separate tion that the cost of failing to classify as vulnerable a bank
banks into resistant and vulnerable groups in each of those that subsequently received a low summary rating from
years. In addition, for comparative purposes, discriminant supervisory personnel is considerably greater than the cost
functions were estimated from a sample of banks that of misclassifying as vulnerable a bank that will retain a
were given high and low summary ratings by supervisory high or intermediate supervisory rating. It is clear that
personnel in the selected years. One function employing early warning of a weakening situation could facilitate the
examination data was estimated for 1969, and one without introduction of timely corrective measures which could
such information was estimated for each of the years help to preserve the institution in question as an ongoing
1969, 1970, and 1971. All these procedures yielded dis­ entity. The social costs involved in a bank failure would
criminant or rank scores for all the member banks in each seem far greater than the costs involved in investigating
a potentially vulnerable bank only to find no evident signs
of the years studied.
Once these scores or rankings were obtained, it was nec­ of weakness.
Accordingly, we attached a high cost to the failure to
essary to determine a cutoff point that divided the banks
into the two groups. Before describing in detail how this identify a vulnerable bank that subsequently received a
cutoff point was determined, it is useful to note that the low summary rating, and these costs were deemed to
separation between banks deemed resistant and those con­ increase with the size of the bank. These costs were con­
sidered vulnerable can be expected to be imperfect. Thus, sidered substantially higher than the cost of misclassifying
any decision rule establishing a cutoff point between re­ as vulnerable a bank that retained a high or intermediate
sistant and vulnerable banks will be associated with a supervisory rating. To help measure these costs, we es­
particular probability that some banks which are financially tablished a cost function which reflected the estimated
resistant will be included in the vulnerable group, and a dollar costs of examining banks of varying size. That is,
particular probability that some banks which are vulner­ the cost function reflected not only the social costs in­
able will be included in the resistant group. Given the volved in the failure to identify banks that subsequently
probability of error, the decision rule involves some judg­ deteriorated in financial condition, but also recognized that
ment *of the relative importance to bank supervisors of examining a large bank is much more costly than examin­
ing a small one. By this means, we ensured that the pro­
cedures employed would be likely to identify correctly a
large percentage of the banks that received low summary
ratings between 1969 and early 1975, although it also
6 Examination data for member banks in the Second Federal meant that the size of the bank group designated vulner­
Reserve District for 1969 instead of 1968 would have been more
able would be relatively large, depending on the efficiency
desirable, but these data were not readily available at the time of
of the particular procedure.
publication.




162

MONTHLY REVIEW, JULY 1975

MINIMIZING THE COST OF CLASSIFICATION ERRORS. It is im­
portant to remember that no information was avail­
able in 1969, or in any of the initial years of the
subperiods studied, regarding the probability of a function
failing to include in the bank group designated
vulnerable those banks that would actually receive low
summary ratings in the subsequent years. We, therefore,
made use of the distribution of the scores or rankings
of the banks that subsequently received low summary
ratings during each of the periods studied to establish
a cutoff score that minimized the cost of misclassification
errors. The use of this information in no way changed
any of the scores or relative positions of the banks in
the rankings.
The cost-minimizing cutoff score or rank was obtained
for each of the procedures employed by calculating the
cost of calling a bank vulnerable when, in fact, it sub­
sequently retained a high or intermediate summary rating
and the cost of assigning to the resistant group a bank that
subsequently received a low summary rating. The cost
was calculated for all decision rules, ranging from desig­
nating all banks as vulnerable to designating all
banks as resistant. Each cost calculation assumed that
all banks designated vulnerable would be examined
and all banks deemed resistant would not be examined.7
In each of the calculations the classification errors
{i.e., the percentage of banks called vulnerable that
did not subsequently receive low summary ratings and
the percentage of banks called resistant that did receive
low ratings) were weighted by a factor from a cost func­
tion and the total cost of all the errors was calculated.8
The cutoff score that minimized this cost was considered
a guide to the efficiency of each of the procedures em­
ployed. To avoid possible bias in these calculations, all the

7 It is important to note that a bank’s presence in the vulner­
able group which did not subsequently receive low summary
ratings is not necessarily an indication of error, inasmuch as the
banks involved may have been vulnerable at the time of estima­
tion of the function but, in the intervening years, improved their
condition so that they would no longer be considered vulnerable
if the function were reestimated. Further, a vulnerable bank
may not manifest the signs of deterioration that would warrant a
low summary rating from supervisory personnel as long as gen­
eral economic or other conditions are favorable. Nonetheless, the
vulnerability of banks is a matter of concern to bank supervisors,
since any adverse change in the overall economic environment is
likely to impact most severely on the banks that are vulnerable.
8 The total cost of misclassification errors is as follow s:
m
n
TC = 2 (cost r:w )i + 2 (cost v:s)j
i= 1
j= 1




sample banks from which functions were estimated were
removed from the resistant and vulnerable bank groupings
into which all member banks in the Second Federal Re­
serve District were divided by means of the scores ob­
tained from those functions.9
POSSIBILITIES FOR GAINS IN EFFICIENCY IN THE ALLOCA­
o f s u p e r v i s o r y r e s o u r c e s . Were supervisory re­
sources allocated only to the bank group designated
vulnerable— assuming that an efficient cutoff score could
be obtained from past experience—the procedures
described in this article could lead to sizable economic
efficiencies, compared with examining each member bank
once a year. Such annual examinations would be indicated
by these procedures, if the discriminant scores or rankings
of the banks that received low summary ratings were ran­
domly distributed. The possible gains in efficiency are
suggested by a comparison of the total costs of the classifi­
cation errors from use of the procedures described in this
article with once-a-year examinations of all banks,

TION

Footnote 8 (continued):
where:
TC = Total cost
m = Number of banks receiving low summary ratings
classified as resistant
(c o str.w ); = Cost of classifying as resistant the ith bank when it
receives a low summary rating
n = Number of banks with high summary ratings clas­
sified as vulnerable
(c o stv :s)j = Cost of classifying as vulnerable the jth bank when
it retains a high or intermediate summary rating.
We assumed that the cost of correct classification is zero. This
implies that the examination costs associated with correctly classi­
fied vulnerable banks are at least matched by the benefits in arrest­
ing the deterioration. It is possible that such benefits exceed the
cost of examination but, in the absence of a concrete measure of
those benefits, we assumed that detection of a deteriorating situa­
tion offsets the examination costs. In effect, the v:s error results
in conducting an examination when one was not required and the
r:w error in the failure to conduct an examination when one was
required. The cost of the v:s error for a given bank is based on
the cost of examining the bank, and the cost of the r:w error is a
multiple of the examination cost for the particular bank to reflect
the greater social cost of the r:w error. To find the cost-minimizing
cutoff point, the value of TC was computed for every possible
decision rule, ranging from classifying all banks as vulnerable to
classifying all banks as resistant for each function or procedure.
9 The ability of each of the functions to identify banks that re­
ceived low summary ratings was evaluated, in effect, on a “holdout”
group. While biased results are likely where the same observations
are chosen both to estimate and to test a function, the ranking
procedure does not use the same criterion for choosing these two
samples. Therefore, it was not theoretically necessary in connection
with the function based on our ranking procedure to exclude the
estimation sample from the test sample, though we did so none­
theless.

FEDERAL RESERVE BANK OF NEW YORK

taking into account that examination costs and the cost of
misclassification errors both are related to bank size.10 It
should be noted that the gain in efficiency does not repre­
sent a comparable percentage reduction in total examina­
tion costs; as noted earlier, the costs of examining
vulnerable banks that receive low summary ratings are
deemed to be offset by the benefits of detection, while the
costs of failing to classify correctly a bank that subse­
quently receives a low summary rating are considered
substantially higher than the costs of examining that par­
ticular bank.
Much would depend, of course, on reasonable stability
in the relationships measured by the functions or bank
rankings employed; the results described below suggest
that there is such stability. However, the decision rule to
examine only banks designated vulnerable is not realistic.
It tends to overstate the relative gain in efficiency from
adoption of the rule, since there would of necessity be a
continuing need for some schedule of on-site examinations
—probably less frequently than annually—to obtain first­
hand information on the financial condition of other than
vulnerable banks and to implement corrective measures
where needed. In addition, supervisory authorities might
wish to examine certain vulnerable banks more frequently
than once a year, so that implicit cost savings would be
realized through more effective use of supervisory re­
sources rather than through reductions in actual expendi­
tures. Nonetheless, the standard employed is a useful base
for evaluating the efficiency of the approaches discussed
in this article.
THE R E SU L T S OF ALTERNATIVE P R O C E D U R E S

Four functions or procedures, each falling into one of
two categories were tested for their ability to identify
banks that received low summary ratings in the period
1969 through early 1975. Two functions were estimated
from sample data obtained from banks that had either
high or low summary ratings as determined by supervisory
personnel in 1969 and in the initial years of several sub-

i° When supervisory resources are apportioned to all banks,
based on size, all present and future weak banks are detected, but
all resistant banks are “unnecessarily” examined. Then the total
R
cost of classification errors is 2 (cost v :s )k, where R is the total
k= 1
number of banks (from both the groups designated resistant and
vulnerable) that did not subsequently receive low summary ratings
from supervisory personnel.




163

periods. These we called the Exam functions.1 Further, a
1
rank index and a function were obtained from our
multivariate ranking procedure. While we believe the
results are suggestive of the efficiencies that could be
realized in the allocation of supervisory resources, we
note that the details of the procedures discussed here are
by no means exhaustive of the possibilities and that we
have not explored fully the ability of each of the functions
or procedures to provide early warning over varying
periods of time.
Exam-1. Using pooled data for state-chartered member
banks and national banks in the Second Federal Reserve
District for 1969, we reestimated a discriminant function
from bank samples grouped according to high and low
summary ratings determined by supervisory personnel for
that year. We used the same estimation techniques and
eight variables described in connection with the original
1967 and 1968 discriminant functions, but selected
the cutoff point as described earlier in this article.
The ability of this function to identify banks that
received low summary ratings is shown in the accompany­
ing table for the period 1969 through early 1975. As
shown in the table, Exam-1 correctly identified about
89 percent of all the banks that received low summary
ratings (after excluding the banks from which the func­
tion was estimated). The group of banks the function
designated as vulnerable (percentage of total member
banks not shown) contained a sizable percentage of banks
that were accorded low summary ratings during the period
under review. The allocation, therefore, of supervisory
resources only to a bank group designated as vulnerable
by this function could be expected to yield a sizable gain
in efficiency, compared with a proportional allocation of
these resources to all member banks in the Second Federal
Reserve District. Data limitations prevented a meaningful
reestimation of this function over any of the subperiods.
In any case, the use of this function requires data that
are available only from on-site examinations.
Exam-2. This function was estimated from sample
banks grouped according to the high and low summary
ratings given by supervisory personnel in each of the
three years 1969-71. However, no variables requiring data
from examination reports were employed. Instead, a num­
ber of proxy variables were used in place of the qualityof-assets variable employed in the Exam-1 function. The

11 The Exam functions were the best performing functions from
among several variations in simulating summary ratings given
banks by supervisory personnel in selected years.

MONTHLY REVIEW, JULY 1975

164

EFFICIENCY RATIOS WITH RESPECT TO IDENTIFICATION OF BANKS THAT HAD LOW SUMMARY RATINGS
IN SELECTED PERIODS, BASED ON SAMPLE DATA FOR INITIAL YEAR OF EACH PERIOD

1969-early 1975

1970-early 1975

Percentage of banks
Functions or procedures employed

Percentage of banks
Per­
centage
gain in
efficiency*

called
vulnerable
that re­
ceived low
summary
ratings

with low
summary
ratings
correctly
identified

88.7

28.7

t

17.2

94.3

19.3

MISR: 11 variables (excludes size)§ .........

34.1

89.7

MISF: 11 variables (excludes operating
expenses) || ......................................................

17.4

76.9

called
vulnerable
that re­
ceived low
summary
ratings

with low
summary
ratings
correctly
identified

Exam-1: 8 variables, including
examination dataf .......................................

19.0

Exam-2: 12 variables! ........

...........

1971-early 1975
Percentage of banks
Per­
centage
gain in
efficiency*

called
vulnerable
that re­
ceived low
summary
ratings

with low
summary
ratings
correctly
identified

$

$

t

t

t

15.4

95.2

25.7

16.6

95.2

34.0

37.3

31.2

92.2

35.4

33.1

96.7

49.1

41.8

13.8

95.0

20.0

15.6

97.4

33.7

Per­
centage
gain in
efficiency*

Sample data based on supervisory
definitions

Sample data based on rank index

Note: Financial data obtained from Reports of Income and Reports of Condition for all member banks in the
Second Federal Reserve District for 1969 through 1971, and from examination reports of state-chartered
member and national banks for 1968; summary ratings of all member banks in the Second Federal Reserve
District obtained from Federal Reserve Bank of New York supervisory personnel for the period 1969 through
early 1975.
* The estimated gain in economic efficiency from the allocation of supervisory resources by the procedures
described in this paper, compared with the allocation of supervisory resources to all banks (see pages 162-63).
t The Exam functions were the best performing functions from among several variations in simulating
summary ratings given banks by Federal Reserve Bank of New York supervisory personnel in
selected years.

t

Not available at the time of publication.

§ MISR = Multivariate index standard ranking.
I MISF = Multivariate index function.
I

function presented in the table is one of several that
showed relatively consistent results over the entire period
and in each of the subperiods (after the banks used to
estimate the function were excluded). As can be seen in
the table, gains in efficiency varied from about 19 percent
over the period 1969-early 1975 to 34 percent for the
shorter subperiods.
MULTIVARIATE INDEX STANDARD RANKING (MISR).




As de­

scribed earlier, standardized deviations for the twelve
variables for each of the member banks in the Second
Federal Reserve District in 1969, 1970, and 1971 were
added for each bank, and all the banks placed in order
according to each bank’s value in this multivariate index.
The cutoff point to separate the vulnerable banks from
those that were resistant was determined, as explained
earlier, to minimize the costs of misclassification errors.
The MISR shown here omits size from the index, since

FEDERAL RESERVE BANK OF NEW YORK

the eleven-variable index yielded somewhat more con­
sistent percentage gains in efficiency between 1969 and
early 1975 and in the subperiods studied. As can be seen
in the table, these efficiencies varied from 35 percent to
49 percent.

165

ceived low summary ratings during the period studied. In
evaluating the discriminant techniques employed in this
manner, we minimized the costs of classification errors as
described earlier; these procedures do not utilize any statis­
tical probabilities based on a discriminant function.
The discriminant technique was employed in conjunc­
THE FUNCTION BASED ON THE MULTIVARIATE RANKING
tion with the MISR to yield a function (MISF) as
(m i s f ). The MISR provided reasonably good separation
follows. Several alternative segments of the ranking were
throughout most of the period studied. However, each of sampled to obtain data from which to estimate a func­
the variables influenced the ranking process with equal tion. This function then was used to obtain scores for
weight, and it seems reasonable to suppose that some vari­ all the banks in the Second Federal Reserve District
ables may be more important than others in defining resis­ for selected years, with banks in the estimation group
tant and vulnerable banks. Further, the number of variables excluded from the overall list. The results reported here
in the ranking used thus far would not be expected to be are based on a random sample drawn from the bottom
the most complete or efficient set for purposes of defining and top 10 percent of the MISR ranking. Entering all
resistant and vulnerable banks. It is likely that other vari­ twelve variables stepwise in a predetermined order, we
ables in addition to those employed could be useful. Also, found that one variable— i.e., operating expenses-total
it is likely that a smaller subset of the variables used in any revenues— impeded the function’s ability to identify vul­
initial ranking would be sufficient to achieve the desired nerable banks that subsequently received low summary
separation. To explore these possibilities, we raised the ratings over the entire period 1969-early 1975 once the
question whether discriminant analysis might be of aid.
other eleven variables were entered. Therefore, the func­
To utilize the statistical tests available in discriminant tion was employed without that variable. The results show
analysis, it is necessary to show that the sample is com­ a potential gain in efficiency of nearly 42 percent, over the
posed of independent groups. Relating this requirement to entire period 1969-early 1975, with some tendency for the
our MISR, it means that the presence of independently dis­ gains to diminish in the subperiods near the end of the full
tributed groups of vulnerable and resistant banks would period under review. The results suggest that the MISF,
have to be established. Using the MISR ranking described along with the MISR, merit further attention as alternative
above as a guide, we attempted to determine if “natural approaches to the identification of banks that can be con­
groups” of vulnerable and resistant banks could be identi­ sidered vulnerable in the event of economic strains or
fied. Natural groupings in the MISR rankings might be uncertainties.
evidenced in the data comprising the ranking, provided
the procedure and the data were sensitive enough to de­
CONCLUDING C O M M E N T S
tect such natural groupings. We expected that banks per­
forming in the extreme high and low ranges of the ranks
To sum up, the results of the analysis thus far suggest
might represent separate distributions of banks with unique that it is possible to identify vulnerable banks in advance
characteristics, each with its own mean standard of be­ of a significant deterioration in their financial condition
by several alternative procedures. This early identification
havior as measured by its multivariate rank.
In our preliminary research aimed at identifying dis­ could yield significant efficiencies through allocation of
tinctly defined groups, the evidence was mixed, based on supervisory resources to those sectors of the banking in­
relatively simple methods. Nonetheless, there is a reason­ dustry where there is evidence of significant vulnerability
able presumption that resistant banks are markedly dif­ to economic difficulties. Effective use of the approaches
ferent from banks that are vulnerable and that such natural described here would, of course, depend on there being a
groups can be identified. In any event, the analysis did significant measure of confidence in the accuracy of the
not depend on the statistical probabilities derived from separation between resistant and vulnerable banks ob­
the discriminant functions but rather provided a way of tained through the procedures described in this article.
weighting our variables. We decided, therefore, to explore Although more work is needed in this area, we believe the
discriminant techniques to evaluate the overall importance analysis presented here can help to improve the efficiency
of the variables in the MISR in identifying banks that re­ with which supervisory resources are deployed.