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In T h i s Is s u e :
W a g e s a n d U n e m p lo y m e n t :
A State A n a ly sis o f th e P h illip s C u rv e
B a n k in g N o te s : B u sin e ss L o a n s in R e c e s s io n
D is tric t B u sin e ss C o n d it io n s

Fed eral R eserve B a n k O f A tla n ta
Fe d e ra l R e s e rve S ta tio n
A tla n ta , G e o rg ia 3 0 3 0 3

B U L K

R A T E

U .S . P O S T A G E -

PAID
A t la n t a . G e o r g ia

A d d re s s C o rre c tio n




R e q u e s te d

P e r m it N o . 2 9 2

W a g e s a n d U n e m p lo y m e n t :
A

S t a t e A n a ly s is o f

t h e P h illip s C u r v e
b y W illia m D . T o a l
The concept of a market is basic to our economic system. Demands for
goods and services meet suppliers of those goods and services and exchange
takes place. The marketplace determines the price at which this exchange
occurs— the price that leaves the market with no glut or shortage. W e generally
consider the labor market to be one of the more efficiently functioning
markets. Here demands for labor meet suppliers; and a wage rate, the price
of labor services, is determined when workers are hired. When supply of
labor exceeds demand, wages tend to rise more slowly or they may even
decline; when labor is scarce, wage rates tend to increase. The most reflective
measure of labor supply relative to demand is the unemployment rate. The
higher this rate, the greater the quantity of labor supplied exceeds the
quantity demanded. Consequently, an efficiently operating labor market would
suggest that (other things equal) higher unemployment rates would correspond
with slower wage growth and lower rates with faster wage rises.1
This theoretical concept of a labor market has been tested in several countries.
The first test was undertaken in the late Fifties in Great Britain by a British
economist, A. W. Phillips; this wage/unemployment rate relationship was
publicized in the Sixties as the Phillips Curve.2 (Nominal wages instead of
real wages were used, however.) Phillips found close ties between the rate
of change of wages and the unemployment rate; that is, greater increases in
Note: This article presents a preliminary report on the author’s study of subnational wage
equations still in progress. Joseph E. Rossman, Jr., was helpful with the early development
of the analysis.
’Of c o u rs e la b o r m a rk e ts do h a v e im p e rfe c tio n s a n d a re n o t c o m p le te ly h o m o g e n e o u s.
L ab o r d iffe rs by sk ills, e d u c a tio n , in n a te a b ility , a n d o th e r fa c to rs . C o n se q u e n tly , w e sh o u ld
n o t e x p e c t th e re la tio n s h ip b e tw e e n w a g e c h a n g e s a n d th e u n e m p lo y m e n t ra te to b e p e rfe c t.
S till, th e r e s h o u ld b e s o m e n e g a tiv e re la tio n s h ip b e tw e e n w a g e c h a n g e s a n d th e
u n e m p lo y m e n t ra te .
2A. W. P h illip s, “T h e R e la tio n s h ip B etw e e n U n e m p lo y m e n t a n d th e R a te of C h a n g e of M oney
W age R a te s in th e U n ite d K ingdom , 1862-1 9 5 7 ,” E c o n o m ic a , 25 (1958), pp. 283-308.

Monthly Review, Vol. LX, No. 7. Free subscription and additional copies available

upon request to the Research Department, Federal Reserve Bank of Atlanta,
Atlanta, Georgia 30303. Material herein may be reprinted or abstracted provided
this Review, the Bank, and the author are credited. Please provide this Bank's
Research Department with a copy of any publication in which such material is
reprinted.

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JU 1 7 , MONTHLY REVIEW
LY 9 5

wages corresponded with lower unemployment
rates and conversely. This relationship was extended
to the U. S.; studies conducted here in the early
and late Sixties roughly verified this type of
relationship in this economy.
More recently, however, the traditional relation­
ship between wages and unemployment rates
has gone awry. The growth in nominal wages has
continued to escalate though the unemployment
rate has risen in the late Sixties and early Seventies.
In economic terms, we have strayed from the
Phillips Curve, or the Phillips Curve has shifted.
The question is "W hy?" Recent articles have given
us a variety of answers to this question. Changes
in labor market composition and expectations
about the future rate of inflation are two of the
more frequently mentioned explanations. Another
group of economists doubts whether, in the long
run, any Phillips Curve exists at all; they believe
in a natural rate of unemployment from which
any deviation will lead to accelerating wage
increases or decreases. Another explanation, not
precluding but perhaps complementing these others,
is the geographic dispersion of labor markets and
unemployment. If more than one labor market
exists and these markets differ, then changes in
the dispersion of unemployment across these
markets could shift the national Phillips Curve.
Subnational Labor Markets
People may migrate from one region to another
in response to job availabilities or regional wage
differences. This response is not immediate,
however, partly because migration costs are
involved. Labor markets would seem to exist,
then, at a subnational level, whether regional,
state, substate, metropolitan area, or city.3 This
article will examine labor markets differentiated
by geographic divisions to see if supply and demand
forces yield a relationship between wage changes
and unemployment rates. The most likely
geographic division seems to be by state. Labor
markets are probably influenced by right-to-work,
unemployment insurance, and other state laws
that vary widely. In practical terms, data are readily
available by state.4 This study seeks answers to the
following questions: Do wage-unemployment
rate relationships exist at a state level? Do they
differ among states and, if so, why?

3O ne c o u ld a rg u e th e p ro p e r g e o g ra p h ic a l re fe re n c e s fo r
la b o r m a rk e ts a t s o m e le n g th . S ee, fo r e x a m p le , Lloyd C.
R eynolds, T he S tr u c tu re of L ab o r M ark ets (N ew York:
H a rp e r & B ro th e rs, 1951).
‘O th e r s tu d ie s h av e e x a m in e d d iff e r e n t ty p e s of lab o r
m a rk e ts . S ee, fo r e x a m p le , R ich ard C. M arcis a n d J. David
R eed, “J o in t E s tim a tio n of th e D e te rm in a n ts of W ag es in
S u b re g io n a l L ab o r M ark ets in th e U n ite d S ta te s : 1 9 6 1 -1 9 7 2 ,”
J o u rn a l of R eg io n al S c ie n c e , Vol. 14, No. 2, 1974.

FEDERAL RESERVE BANK O ATLANTA
F



Results
In testing these questions, we found a significant
relationship between wage changes and unemploy­
ment rates for fifteen of the forty-five states
examined.5 The relationships in these fifteen states
fitted the conventional theory except in one case;
that is, high unemployment rates were associated
with slow growth in wages and low rates with
faster wage growth. (Only manufacturing wages
were used in these tests. Other tests were run on
a more inclusive wage measure, estimated nonfarm
wage changes; the results were generally the same.
The method used in estimating these relationships
and those developed below is described in the
Appendix.)
In most of these fifteen states, manufacturing
wages were more sensitive to unemployment rate
changes than when a national Phillips relationship
was tested. The only exceptions were Florida and
Kansas.
To examine whether state wage changes were
more responsive to national labor market conditions
than to state markets, we substituted the national
unemployment rate for each state's unemployment
rate. Only five states showed a significant
relationship between manufacturing wage changes
and national unemployment rates. These results
generally support the view that state labor markets
are more important than national labor markets
in explaining state wage changes. And these
results also suggest that subnational labor markets
do exist.
When a lagged inflation variable was added
to each state's wage equation, it had a significant
impact on wage changes in over two-thirds of the
states examined. This inflation variable was
inserted to see the impact of expectations about
inflation on wages and the extent to which workers
adjust wages to past inflation. The state unemploy­
ment rate remained a significant influence on wages
in most of those cases where it had been before
adding the inflation variable. However, this
extended version of the Phillips relationship
improved substantially the wage equation's
explanatory power; on average, over 50 percent of
wage changes were explained by this extended
equation.6

“A laska, H aw aii, N orth D akota, New H a m p sh ire, a n d
V e rm o n t w e re o m itte d b e c a u s e d a ta fo r th e s e s ta t e s w e re
n o t a v a ila b le . Only 12 o b s e rv a tio n s w e re a v a ila b le , c o v erin g
th e y e a rs from 1951 to 1972.
eA v a ria tio n of th e P h illip s re la tio n s h ip in c lu d e s c h a n g e s
in th e u n e m p lo y m e n t ra te a s a m e a s u re of e x p e c ta tio n s of
c h a n g e s in la b o r m a rk e t c o n d itio n s a lo n g w ith th e
u n e m p lo y m e n t ra te its e lf a n d a n in flatio n v a ria b le . W hen
th is v a ria b le w a s in c lu d e d in th e s ta t e e q u a tio n s , it w a s
s ig n ific a n t fo r th ir te e n s ta te s . T h is v a ria tio n of t h e P h illip s
re la tio n s h ip w ill n o t b e c o n s id e re d f u r th e r here, how ever.

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State Variations
The most surprising result of this study is how
much these Phillips Curve relationships vary
among states. In general, the response of wages
to unemployment rates was most significant and
strongest among the southeastern states (see
Map 1). Both the explanatory power and response
of wages to unemployment rates appear, according
to these tests, to be larger than the response
and explanatory power of national wages to the
national unemployment rate. The extent of wage
changes explained by the unemployment rate in
southeastern states was as much as 79 percent
in North Carolina and as low as 19 percent in
Mississippi and Florida.
Adding the inflation factor, the state unemploy­
ment rate remained significant in explaining wage
changes for many southeastern states. In this
case, the inflation factor also appeared to be an
important influence on wages for some southeastern
states. But manufacturing wages seemed to be
most sensitive to past price changes in the
heavily industrialized midwestern and northeastern
states. In fact, the results in some of these states

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suggest that workers are able not only to catch
up with but run ahead of inflation.
W hy Do State Wage Equations Differ?
That Phillips relationships on the state level are
not the same as the national Phillips Curve (if
one exists) is not surprising. On a subnational
level, other options than wage changes are
available for labor market adjustment.7 Labor
migration provides one such alternative; capital
flows, another. Allowing for time, capital will
move from areas of labor shortage to areas of
surplus in order to maximize its return. The
movement of labor and capital across international
borders is more difficult than across state borders
and is less likely to allow labor market adjustment.
Consequently, one might expect migration
of labor and capital across state borders to dampen
the impact of unemployment rates on state wage

7S e e David E. K aun, "W age A d ju s tm e n t in th e A p p a lac h ia n
S ta te s ,” S o u th e rn E co n o m ic Jo u rn a l, Vol. XXXII (O cto b er
1965), p. 227.

JU 1 7 , MONTHLY REVIEW
LY 9 5

changes. Actually, the test results suggest the
opposite. The estimated equations, when
significant, show wages responding more sharply
to unemployment rates at the state level than
the national. However, the lack of a significant
relationship between nominal wages and the
unemployment rate in two-thirds of the states
examined may be related to adjustments through
these long-run migration flows.
Besides the influence of these long-run ad­
justments, wage/unemployment rate relationships
may vary among states for many other reasons.8
Geography, as noted earlier, seems to be an
important factor. But why? One reason seems to
be that labor supply conditions vary among states.
Labor supply is influenced by many factors, includ­
ing the size and location of a state. A state bordering
on more populous areas may have access to a large
outside pool of workers; the wage response to
any change in unemployment may then be small
because workers can move more easily in or out of
the state. Other factors affecting labor supply,
particularly manufacturing labor, are the proportions
of the labor force in agriculture and low-wage
nonmanufacturing industries. The larger these pro­
portions, the less wages will probably respond to
labor market changes. Instead, workers might move
between the nonmanufacturing and manufacturing
sectors in response to varying labor market condi­
tions. Hence, the size of a state's agricultural and
nonmanufacturing sectors may affect the extent to
which manufacturing wages respond to its unem­
ployment rate.
The degree of structural unemployment in a state
may also influence labor supply and, therefore, the
wage/unemployment rate relationship.9 Structural
unemployment is not easily distinguishable from
that resulting from education, lack of skills, and
other demographic or industry-mix characteristics.
However, the more structural unemployment, the
more overstated is the employable labor supply, re­
sulting in sharper wage increases for any unemploy­
ment rate. Finally, many have argued that the degree
of unionization among states can influence labor
supply. Consequently, differences in the extent of
unionization among states may cause differences in
state labor supply.

8S o m e of th e s e fo rc e s a re s k e tc h e d by W illiam P. A lb re c h t, Jr.,
in “T h e R e la tio n s h ip B etw een W age C h a n g e s a n d
U n e m p lo y m e n t in M etro p o lita n a n d In d u s tria l L abor
M ark e ts,” Yale E co n o m ic E ssay s, Vol. 6 (1969), pp. 315-320.

. . s o m e g ro u p s h av e p e rs is te n tly h ig h u n e m p lo y m e n t
th a t te n d s to b e of lo n g d u ra tio n . . . . S u c h u n e m p lo y m e n t
is o fte n re fe rre d to a s s tru c tu ra l. . . . S tru c tu ra l
u n e m p lo y m e n t r e p re s e n ts im p e rfe c t la b o r m a rk e t a d ju s tm e n t
a s a re s u lt of s o m e b a rrie r to t h e m o b ility of r e s o u rc e s .”
E co n o m ic R e p o rt of th e P r e s id e n t, U n ited S ta te s G o v e rn m e n t
P rin tin g O ffice, W ash in g to n : 1975, pp. 89-90.
FEDERAL RESERVE BANK OF ATLANTA



Differences in labor demand related to differences
in industry mix can also affect the wage/unemploy­
ment rate relationship. Those states with more
industries producing for a national market may
show wage changes more closely related to national
than state unemployment rates. At the same time,
industry mix and unionization should show much
the same influence since certain industries, such as
steel and automaking, are more likely to be union­
ized than others. Consequently, it may be impossiable to separate the impact of unionization and
industry mix on state Phillips Curve relationships.
The findings of this study do lead us to some
tentative observations, however, about geographic
differences in Phillips Curves. The southeastern
states, in general, have the most significant and
sensitive wage/unemployment rate relationships.
Beyond geographic location, what other important
influences explain this? Are there any characteristics
distinctive to this region that may account
for this clustering?
The one striking feature of both southeastern
states and those other states where wage/unem­
ployment rate relationships were significant was
that they were generally the least unionized. O f the
fifteen states with significant wage/unemployment
rate relationships, only Kentucky and New Jersey
had a degree of unionization approaching the
national average (31 percent of the labor force);
most of the other thirteen states were far below
that. On the other hand, most of the heavily union­
ized states (except New Jersey) had insignificant
Phillips Curves (see Map 2). To draw a firm con­
clusion from this bit of evidence is difficult since,
as mentioned, the extent of unionization may be
related to industry mix. Nevertheless, there does
seem to be some evidence to warrant making the
following observation: Those states which are less
unionized appear to have the most significant
Phillips Curves. This observation, though only
tentative, has not been supported by some other
empirical studies.10
One other point is worth noting. The extent of
unionization seems to correlate closely with those
states in which wages are most responsive to the
lagged inflation variable. Past price increases appear
to have had the largest impact on wages in the
heavily unionized midwestern and northeastern
states. On the other hand, in none of the lessunionized southeastern states were wage changes
nearly as sensitive to past inflation rates. This would
suggest at the least that the stronger bargaining
position of labor in the more heavily unionized
states can apparently adjust wages to past inflation

10S e e A lb re c h t’s s tu d y of m e tro p o lita n a re a P h illip s C urves,
op. c it., pp. 318-319.

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rates more readily and are, therefore, better able to
maintain real wages.
Conclusion and Implications
Many economists have long considered Phillips'
expressed relationship between wage changes and
the unemployment rate too simplistic. Just two
years after Phillips wrote his famous article, one
study pointed out that the distribution of unem­
ployment between various markets in an economy,
as well as the level of unemployment itself, could
influence aggregate wage changes and shift the
aggregate Phillips Curve .11 Unemployment disper­
sion and its impact on aggregate wage changes have
been examined in several contexts— by labor force
groups, by industrial sectors, and by geographic
regions (as this article does ).12 A more complete
analysis might consider all aspects of unemployment
” R ichard G. Lipsey, "T h e R elatio n B etw een U n e m p lo y m e n t
a n d th e R ate of C h an g e of M oney W age R a te s in th e
U nited K ingdom , 1862-1951: A F u rth e r A n a ly sis,”
E c o n o m ic a , F e b ru a ry 1960, p. 19.
12S ee, fo r e x am p le, G eo rg e L. Perry, “ C h a n g in g L abor
M ark ets a n d In fla tio n ," B ro o k in g s P a p e rs on E co n o m ic

10
1




dispersion, but this was clearly beyond the scope
of this study.
The tentative results obtained show Phillips-type
relationships existing in one-third of the states
examined. Previous studies have not always
confirmed subnational wage equations; in fact,
some have argued they do not exist.13 This study,
however, suggests that forces of labor supply and
demand do operate at the state level and affect
state wage changes, supporting the claim of sub­
national labor markets.
The results also show substantial differences in
state Phillips Curves, with southeastern states gen­
erally having the most significant and responsive
wage equations. Some evidence, though not con­
clusive, suggests that the extent of unionization may
influence these interstate differences. Whatever the

A ctivity, 3:1970, pp. 411-441; S an fo rd V. B erg a n d T h o m as
R. D alton, “ S e c to ra l E m p lo y m en t a n d S h ifts in th e A g g re g a te
P h illip s C u rv e ,’’ S o u th e rn E co n o m ic J o u rn a l, Vol. 41,
April 1975, pp. 593-601; G. C. A rchibald, “T he P h illip s
C urve a n d th e D istrib u tio n of U n e m p lo y m e n t," A m erican
E co n o m ic R eview , P a p e rs a n d P ro c e e d in g s, Vol. LIX, May
1969.
13M arcis a n d R eed, op. c it., pp. 205-206.

JU 1 7 , MONTHLY REVIEW
LY 9 5

reason for these differences, these subnational
Phillips Curves and their variation implies that
national wage/unemployment rate relationships
are probably very unstable unless unemployment
dispersion or distribution is also considered. As
pointed out in an earlier study, subnational
Phillips Curves are very difficult to aggregate into
a stable national curve.14
Although the notion of a simple national curve

14S e e L ipsey, op. c it., p p. 16-19.

is appealing, it is naive. Much evidence, including
the experience of the past few years, disproves such
a simple relationship. This analysis indicates that
the uneven impact of the business cycle in different
regions and states could be at least partially re­
sponsible for the unstable national Phillips Curve,
in other words, diverse subnational labor markets
(as observed by the tested state Phillips Curves)
act with the uneven geographic impact of changes
in economic activity to affect national wage
changes. The simple Phillips Curve concept does
not consider these factors, ■

Appendix

Correlation and regression analyses were used to estimate
several forms of Phillips Curve equations for the fortyfive states for which data were available. Annual data
from 1961 to 1972 were used. This allowed only twelve
observations, an obvious limitation. However, the lack
of seasonally adjusted monthly or quarterly data
precluded using these alternatives. Work is presently
underway reestimating several of the equations with
quarterly data using seasonal dummy variables; this will
sharply increase the number of observations available.
The forms of the equations estimated are as follows:
W f = a +b

1
U Rj
1

W t = a + b r r rr + cP u -1
s
UR,

w t = a + b u F + c P - - i + d i uR;
percent change from previous year in
manufacturing average hourly earnings
in state i.
1
= reciprocal of the annual average unem­
UR;
ployment rate for state i.
p*
ru -1 percent change from previous year in the
s
U. S. Consumer Price Index lagged
one year.

where W ;

1
A — —

=

c h a n g e in t h e r e c i p r o c a l o f t h e a n n u a l
a v e r a g e u n e m p l o y m e n t r a t e i n s t a t e i.

a ,b ,c ,d =

e s tim a t e d c o n s t a n t a n d

re sp o n se co e f­

fic ie n t s .

The reciprocal form of the unemployment rate variable
was used, as in many studies of the national Phillips
Curve. It is generally believed that the negative
relationship between percentage wage changes and the
unemployment rate is not linear, hence, the reciprocal
form of the unemployment rate variable. Tests were also
run using the direct unemployment rate; however, the
reciprocal form generally gave better results.
Tests were also run using lagged values of the
unemployment rate variable. But, except for isolated
cases, the current value of the unemployment rate
proved more satisfactory. In the cases referred to in

FEDERAL RESERVE BANK O ATLANTA
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the text where the impact of national labor market
conditions on state wage changes was estimated, the
national unemployment rate was simply substituted for
the state unemployment rate. In the simple Phillips
Curve case, the equation took the following form:
Wf = a + b
where

UR,

_1_

UR,

the reciprocal of the annual
average unemployment rate for
the U. S.

The second equation listed gives an enlarged version
of the Phillips Curve with a price variable added. Price
data generally do not exist on a state level. Hence, the
U. S. Consumer Price Index was used for each state's
wage equation. This assumes, realistically enough, that
the rate of inflation is very similar in all regions and
states of the country. The price variable is lagged one
year. It is assumed that inflationary expectations rather
than inflation itself affect wage changes; inflationary
expectations are roughly estimated by the previous
year's actual inflation rate. (This is admittedly a very
rough approximation.)
The third equation adds a variable for changes in
unemployment rates which are assumed to measure
labor market expectations (see footnote 5 in text). All
the equations described were reestimated using U. S.
Department of Commerce wage and salary data for
nonfarm industries standardized for number of nonfarm
wage and salary workers. These data provided broader
coverage than the U. S. Department of Labor series on
manufacturing average hourly earnings used in the rest
of the study. The results, though somewhat less
significant, were generally unchanged with this
reestimation. State unemployment rate data were based
on the old place-of-work methodology and not on the
new place-of-residence estimating methodology.
A sufficient back series of these data is not as yet
available.
Statistical results are not reported in detail here. The
accompanying maps give some summary results. Detailed
regression equations are available upon request.

111

BANKING STATISTICS

Bil. $

DEPOSITS**
Total

- 4 0

-3 6

-

-3 2

* ________

40

_____

AJ

Net Demand

36

— 14

A
/
-

- 2 4

10

A/
— 18

- 2 0

AJ

Time

- 8
— 14

-5
10

Savings

-2

Z

rj

/V

—

A/

A/

I I I I I I I I I I I

D IS T R IC T

I I I I I I I II I I

1974

1975

*F ig u res a re fo r th e la s t W ed n e sd a y of e a c h m o n th
**Daily a v e ra g e fig u re s

LATEST MONTH PLOTTED: MAY

SIXTH

I i i i i i i i i i i

1973

I

6

B A N K IN G

N D T E
5

B u s in e s s L o a n s in R e c e s s i o n
C o m m e r c ia l a n d In d u s tria l L o a n s
|

| J u n e 1 9 7 4 -Ju n e 1975

t~

A nnual
% change

1 J u n e 1 9 6 9 -Ju n e 1970
—

.a

re
i_

3

a

------r r
3
TJ
C
Z

------T - _ I
O
o
-C
£

—
re
0)
cn

[J

10

fc r

-1 0

—

-2 0

* T ra n s p o rta tio n , C o m m u n ic a tio n , a n d P u b lic U tilities
N ote: D ata g a th e re d from la rg e D is tric t b a n k s.

112




JU 1 7 , MONTHLY REVIEW
LY 9 5

A comparison of slack periods in commercial-andindustrial loan activity at Sixth District banks during
the current recession and during the economic slow­
down of 1969-70 yields several interesting results,
some surprising, some not. (Mid-1974 to mid-1975
was used to mark the current period; mid-1969 to
mid-1970 delineates the comparison period. This
permits direct comparison of data which are not
seasonally adjusted.)
As would be expected, business loan activity has
been much weaker during the current recession
than during its predecessor. During the four quarters
since mid-1974, District business loan activity has
declined by 10 percent; it had increased by 5 per­
cent in the four quarters from mid-1969 to mid1970. During the current recession, moreover, busi­
ness loan activity decelerated sharply, with rates of
+ 2, — 1 , — 5, and —6 percent between the
third quarter of 1974 and the second quarter of
1975. In the 1969-70 slowdown, by comparison,
declines occurred in only two of the four quarters,
and then the declines were small.
The fact that business loans have declined much
more markedly at key District banks in this recession
than in the previous one is to be expected for
several reasons. First, the current recession has been
much more severe, both nationally and in the
District, than in 1969-70. The demand for bank
credit by businesses is closely related to the activity
of those businesses themselves, especially their de­
mands for inventory finance and working capital.
Second, banks have generally been more concerned
with building liquidity and improving the quality
of their loan portfolios this time, much more than
in 1969-70. Accordingly, banks have been much
less aggressive as lenders and have brought their
interest rates down rather reluctantly. Third, busi­
nesses have moved increasingly to convert their
short-term bank debt into long-term bond liabilities.
Such a conversion is typical in a recession, but rec­
ord calendars in the corporate bond market testify
to the recent strength of this tendency in the cur­
rent recession.
Looking at the major categories of large banks
lending to businesses during these two recession
periods, however, a more surprising result emerges.
Two of the hardest-hit sectors in the current re­
cession, according to production and employment
data, have been construction and durable goods
manufacturing. Yet District bank lending to heavy
manufacturers and contractors are the only loan
categories which have not declined more during the
1974-75 recession than in 1969-70. Loans to con­
tractors declined both times; but the 10 -percent
decline in 1974-75 was not as severe as the 18-per­
cent drop posted in 1969-70. Most of the difference

T o ta l C o m m e rc ia l a n d I n d u s tr ia l L o a n s

o/o c h a n g e

N. S. A.

-

-

t

r

T

=

5

-5

r

- -1 0
I

III

IV
1969

I

I

II
1970

N ote: D ata g a th e re d from

III

IV
1974

I

I
1975

la rg e D istric t b a n k s.

in these two numbers was concentrated in compar­
ing the third calendar quarters of 1969 and 1974. In
durable goods manufacturing, bank loans increased
at about 10 percent during the 1969-70 period and
8 percent during the current period.
In five other broad categories of business bor­
rowers, as evidenced by the chart on the opposite
page, the 1974-75 drop-off has been much more
severe than in 1969-70. Nondurable manufacturing
firms— dominated by textiles in the Sixth District—
and the service industry showed substantial drops,
but the wholesale and retail trade categories showed
the largest comparative declines in 1974-75, com ­
pared with no growth during the previous recession.
The remaining sectors— transportation, communica­
tion, and public utilities— posted a small decline
during each of the recessions.
W IL L IA M N . C O X , III

An e a rlie r a n a ly s is by Sally Loving, c o o rd in a to r of fin a n c ia l
s ta tis tic s , w a s h e lp fu l in p re p a rin g th is N ote.

FED
ERAL RESERVE BANK O ATLANTA
F



13
1

S ix t h D is t r ic t S t a t is t ic s
S e a s o n a lly

A d ju s te d

(A ll d a ta a r e i n d e x e s , u n le s s in d i c a t e d o t h e r w is e .)
L a t e s t M onth
1975

O ne
M onth
Ago

Tw o
M onths
Ago

One
Year
Ago

U n e m p lo ym e n t R a te
(P e rc e n t of W ork F o r c e ) ......................... M ay
Avg. W e e k ly H rs. in M fg. (H rs .) . . . M ay

S IX T H D IS T R IC T
IN C O M E A N D S P E N D IN G
M a n u fa c tu rin g P a y ro lls
F a rm C a sh R e c e ip ts . .

. A p ril
. A p ril
, A p ril

172.7
172
227
165

170.1
224
391
177

168.2
214
308
188

In s ta lm e n t C re d it at B a n k s * (M il.$ )
. May
. M ay

628
640

. M ay
. M ay

129.9
108.0
107.6
103.6
9 9.4

5 52 r
629 r

522
604

175.3
173
188
179

68
6
579

E M P L O Y M E N T A N D P R O D U C T IO N
N o n fa rm E m p l o y m e n t ...............................
M a n u fa c tu rin g
............................................
N o n d u ra b le G o o d s ...............................
F o o d ...............................................................
T e x t i l e s ..................................................
A p p are l
..................................................
Paper
........................................................
P rin tin g and P u b lis h in g
. .
C h e m i c a l s ............................................
D u ra b le G o o d s ......................................
L b r ., Wood P ro d s ., F u rn . & F ix ..
Sto n e , C la y , and G la s s . . .
P r im a ry M e t a l s ...............................
F a b ric a te d M e t a l s .........................
M a c h i n e r y ............................................
T ra n sp o rta tio n Eiquip m ent
N o n m a n u fa c t u r in g ......................................
C o n s t r u c t i o n ......................................

.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
,

M ay
M ay
M ay
M ay
M ay
M ay
M ay
M ay
M ay
May
M ay
May
May
M ay
M ay
M ay
M ay
M ay
May
May
May
Ju n e

S e r v i c e s ..................................................
F e d e ra l G o v e rn m e n t . . . .
S ta te and L o c a l G o v e rn m e n t
F a rm E m p lo y m e n t ............................................
U n e m p lo ym e n t R a te
May
(P e rc e n t of W ork F o rc e ) . . . .
In su re d U n e m p lo ym e n t
(P e rc e n t of C ov. E m p . ) ......................... . May
Avg. W e e k ly H rs. in M fg. (H rs .) . . . May
C o n s tru c tio n C o n tra c ts* - ......................... . M ay
R e s i d e n t i a l ......................................................... . May
A ll o t h e r ............................................................... . M ay
C otto n C o n s u m p t i o n * * ............................... . A p ril
M a n u fa c tu rin g P ro d u c tio n
. . . . . A p ril
N o n d u ra b le G o o d s ..................................... . A p ril
Food
........................................................ . A p ril
T e x t i l e s .................................................. . A p ril
A p p a rel
.................................................. . A p ril
Paper
........................................................ . A p ril
P r in tin g and P u b lis h in g . . . A p ril
. A p ril
. A p ril
. A p ril
. A p ril
F u rn itu re and F ix t u r e s . .
. A p ril
S to n e , C la y , and G la s s . .
P rim a ry M e t a l s .........................
. A p ril
. A p ril
F a b ric a te d M e ta ls . . . .
. A p ril
N o n e le c tric a l M a ch in e ry
. A p ril
E le c tr ic a l M a c h in e ry
. .
T ra n sp o rta tio n E q u ip m e n t
. A p ril

105.7
124.0
106.1
108.5
94.1
115.8
101.4

129.8
107.7
106.7
104.5
9 7.3
101.7
104.6
123.7
105.4
108.9
9 4.4
116.6
102.9

105.0
125.0
105.7
109.5
9 4.0
116.6
103.9

146.9
98.7
137.6
127.0
123.5
134.5
149.9
155.1
105.6
143.9
7 8.5

148.9
97.6
137.6
132.6
123.4
134.3
150.0
153.9
105.4
143.3
79.1

150.4
97.5
138.4
136.4
123.6
135.1
150.3
154.3
106.0
143.5
78.5

10 .6
2

130.3
107.5
105.9
104.5
9 5.2

101.1

12 .0 121.0 121.8
0

9.7

6
.8

39.1
182
134
228
58
140 .4
142.5
135.0
135.6
118.2
132.3
125.6
159.5
137.9
139.5
115.8
137.5

101.1
111.2

148.8
240.7

12 .0
2

10
.2
6 .9
3 8.7
163
133
191
54
139.7
142.5
135.8
135.9
117.7
132.1
126.3
160.6
135.0
129.3
114.0
134.0
101.4
111.3
150.5
2 26.2
122.5

10
.1
6 .7
38.6
224
131
316
53
141.4
144.6
135.6
1 36.9
120.9
133.7
127.3
159.7
136.6
126.2
117.1
142.3
102.7

112.6

153.8
227 .8

121.8

134.6
119.3
116.2
106.0
114.4
115.0
114.6
132.3
109.2
123.2

111.2

133.1
114.7
133.5
164.7
108.7
140.0
153.9
128.2
138.9
153.9
153.6
104.2
137.2
7 8 .4 r

. May
, M ay

270
251

. May

22
2

193
300

267
250
219
192
3 08 r

276
255

O ne
M o nth
Ago

O ne
Year
Ago

10.2
3 8 .4

9 .2
3 9.0

Tw o
M o n th s
Ago

4 .6
4 0 .5

267
214
294

251
206
2 60

F IN A N C E A N D B A N K IN G
M em b er B a n k L o a n s ............................................ M ay
M em b er B a n k D e p o s i t s ................................M ay
B a n k D e b i t s * * .........................................................M ay

269
218
300

2 65
2 16
309r

F L O R ID A

M a n u fa c tu rin g P a y ro lls
................................May
F a rm C a s h R e c e i p t s ............................................ A p ril

212

178.1
3 09

180 .7
2 49

184 .5
169

M ay
M ay
M ay
M ay
Ju n e

149 .5
117 .3
155.7
1 45 .8
7 7.0

149 .2
117 .5
155.3
1 5 6 .9
7 2.7

149 .8
117 .2
156.1
162.1
7 0 .9

157 .0
1 28 .6
162.4
2 08 .5
8 3 .4 r

M ay
M ay

12.3
3 9.3

3 9 .0

10.7
3 9 .9

5 .4
4 0.1

M em b er B a n k L o a n s .........................
M em b er B a n k D e p o sits . . . .
B a n k D e b i t s * * ......................................

M ay
M ay
M ay

2 94
248
317

288
2 40
303

301
2 42
3 09

309
247
301

M a n u fa c tu rin g P a y ro lls
. . .
F a rm C a sh R e c e i p t s .........................

M ay
A p ril

159.1
188

154.7

202

149.1
2 18

1 66 .5
181

M ay
M ay
M ay
M ay
Ju n e

124.7
9 9.5
136.2
1 22 .4
103.7

124.3
9 8.7
136 .0
123.5
103 .9

125.1
9 7 .8
1 37 .6
128 .2
103.7

1 31 .0

M ay
M ay

9 .7
3 9 .2

10.5
3 8 .7

11.5
3 7 .9

4 .1
4 0 .0

M ay
M ay
M ay

252
195
352

248
195
381

250
191
353

266
196
327

M ay
A p ril

163 .0
131

166 .2
239

1 69 .4
181

156 .6
170

M ay
M ay
M ay
M ay
Ju n e

119 .6
1 05 .4

1 20 .9
107 .4
123.7
107 .6
7 4 .8

121.0
10 .6
0

M ay
M ay

7 .6
3 8.2

M ay
M ay
M ay

179 .0

EM P LO YM EN T
N o n fa rm

E m p lo y m e n t

U n e m p lo y m e n t R a te
(P e rc e n t of W ork F o rc e ) . .
Avg. W e e k ly H rs. in M fg. (H rs .)

12.2

F IN A N C E A N D B A N K IN G

EM P LO YM EN T
4 .7

2
.2

40.1
228
219
237
76
147.8
1 47.9
134.6
145.8
137.7
136.0
136.1
157.5
147.8
150.9
150.1
154.9
108.1
128.6
147.6
242.7
127.6

F IN A N C E AN D B A N K IN G
Loan s*
A ll M e m b er B a n k s ...............................
La rg e B a n k s ............................................
D e p o sits*
A ll M em b er B a n k s ...............................
La rg e B a n k s ............................................
B a n k D e b its * / * *
......................................

L a t e s t M onth
1975

274
257

219
193
303

215
186
285

170.6
233

185.2
193

N o n fa rm E m p lo y m e n t . . . .
M a n u fa c tu rin g
................................
N o n m a n u fa c tu rin g
. . . .
C o n s t r u c t i o n ................................
F a rm E m p lo y m e n t
.........................
U n e m p lo y m e n t R a te
(P e rc e n t of W ork F o rc e ) . .
A vg. W e e k ly H rs. in Mfg. (H rs .)

112.2

139 .6
1 47 .2
93. r

6

F IN A N C E AN D B A N K IN G
M em b er B a n k L o a n s .........................
M em b er B a n k D e p o sits . . .
B a n k D e b i t s * * ......................................

EM P LO YM EN T
N o n fa rm E m p lo y m e n t . . . .
M a n u fa c tu rin g
................................
N o n m a n u fa c t u r in g .........................
C o n s t r u c t i o n ................................
F a rm E m p lo y m e n t ................................
U n e m p lo y m e n t R a te
(P e rc e n t of W o rk F o rc e ) . .
Avg. W e e k ly H rs. in M fg. (H rs .)

122.6
10
2.8
7 2.6

120
.2
1 07 .2
122.9
105.5
7 5.7

8
.1

118 .9
108 .4

7 8 .6 r

6
.1

3 8.5

8 .4
3 9 .5

3 9 .8

246
206
249

253
207
261

261
207
2 59

2 55
189
2 29

M ay
A p ril

196.9
173

195.5
233

193 .0
215

197 .5
197

M ay
M ay
M ay
M ay
Ju n e

126.3
119 .4
129.5
117 .8
5 9.6

126.4
118 .4
130.1
125 .9
6 3.5

127 .5
119 .5
131.2
135 .0
5 8.3

1 31 .8
1 34 .5
130 .6
151.1
6 9 .9 r

F IN A N C E A N D B A N K IN G
M em b er B a n k L o a n s * . . . .
M em b er B a n k D e p o sits* . . .
B a n k D e b i t s * / * * ......................................

A LA B A M A
M IS S IS S IP P I
. May

178.8
193

171.2
204

EM P LO YM EN T
N o n farm E m p lo y m e n t
M a n u fa c tu rin g
. .
N o n m a n u fa c tu rin g
C o n s tru c tio n
. .

14
1



IN C O M E
M a n u fa c tu rin g P a y ro lls
. . .
F a rm C a s h R e c e i p t s .........................
EM P LO YM EN T

. May
. May

118.8
107.5
124.0
129.2
72.3

118.4
106.6
123.8
129.6
73.0

118.5
105.8
124.3
131.2
74.6

122.4
118.4
124.2
142.2
7 0.4

N o n fa rm E m p lo y m e n t . . . .
M a n u fa c tu rin g
...............................
N o n m a n u fa c t u r in g .........................
C o n s t r u c t i o n ................................
F a rm E m p lo y m e n t ................................

JU 1 7 , MONTHLY REVIEW
LY 9 5

O ne
M onth
Ago

L a t e s t M onth
U n e m p lo y m e n t R a te
(P e rc e n t o f W o rk F o rc e ) . .
A vg. W e e k ly H rs. in M fg. (H rs .)

O ne
Year
Ago

Tw o
M o nths
Ago

O ne
M onth
Ago

L a t e s t M onth

Tw o
M o nth s
Ago

O ne
Year
Ago

E M P LO YM EN T
. M av
. May

7.4
3 8.9

8 .4
3 8.8

8.5
38.1

3.2
3 9.8

M em ber B an k Lo an s* . . . .
M em b er B a n k D e p o sits* . . .
B a n k D e b i t s * / * * ......................................

. May

262
218
257

248
217
259

266
217
255

171.6
197

167.0
244

221

125.5
107.5
135.5
1 38.4

129.0
119.3
1 34 .4
135.8
7 8 .9 r

8 .5
3 9.5

8 .9
3 9.2

9.6
3 6.3

4 .1
4 0 .3

277
223
244

274

291
224
276

261
203
274

. M ay
. Ju n e

177.3
186

268

125 .4
107.1
135.5
137.2

. M ay
. M ay

256

173.5
158

. M ay
. May

E m p lo y m e n t

N o n m a n u fa c tu rin g
C o n s tru c tio n

125.1
107.3
135.0
130.7

. May
. M ay

N o n farm

F IN A N C E A N D B A N K IN G

U n e m p lo ym e n t R a te

8.6 8.0 8.6
6
8
8

TEN N ESSEE
F IN A N C E A N D B A N K IN G
M a n u fa c tu rin g P a y r o l l s ......................................M ay
F a rm C a s h R e c e i p t s ............................................A p ril

• F o r S ix th D is t ric t a re a o n ly ; o th e r to ta ls fo r e n tir e s ix s ta te s

* * D a ily a v e ra g e b a s is

t P r e lim in a r y d a ta

r-R e v ise d

20
2
258

N .A . N ot a v a ila b le

Note: All indexes: 1967 = 100.
S o u rce s :
M a n u fa c tu rin g p ro d u ctio n e s tim a te d by t h is B a n k ; n o n fa rm , m fg. an d n o n m fg . e m p ., m fg . p a y ro lls an d h o u rs, an d u n e m p ., U .S . D ept, o f L a b o r an d co o p e ra tin g
s ta te a g e n c ie s ; cotto n c o n su m p tio n , U .S . B u re a u of C e n s u s ; c o n s tru c tio n c o n t ra c t s , F . W. Dodge D iv ., M cG ra w -H ill In fo rm atio n S y s te m s C o .; fa rm c a s h re c e ip ts an d
farm e m p ., U .S .D .A . O th e r in d e x e s based on d a ta c o lle c te d by th is B a n k . A ll in d e x e s c a lc u la te d by t h is B a n k ,
'D a ta b e n ch m a rk e d to Ju n e 1971 R e p o rt o f C o n d itio n .

D e b it s to D e m a n d D e p o s it A c c o
I n s u r e d C o m m e r c i a l B a n k s in t h e S i x t h D i s t r i c t
(In

Th o u sa n d s

of

D o lla rs )

P e r c e n t C h an g e

M ay
1975
from
May
1975

A p ril
1975

May
1974

A pr.
1975

M ay
1974

ST A N D A R D M ET R O P O L IT A N
S T A T IS T IC A L A R E A S '
B irm in g h a m
. . .
G ad sd e n
. . . .
H u n ts v ille . . . .
M o b i l e .........................
M o ntg o m ery . . .
T u sc a lo o sa
. , .

.

5 ,6 5 4 ,7 2 4
104,785
381,091
1 ,4 41 ,4 46
7 7 4 ,5 4 5
2 9 2 ,6 8 9

5 ,8 15 ,7 46
107,2 92
4 02 ,4 0 9
1 ,5 1 0 ,2 2 9
8 6 0 ,1 7 0
2 7 4 ,7 8 9

4 ,7 9 0 ,8 4 6
112,073
4 0 3 ,8 5 9
1 ,3 21 ,1 31
7 3 0 ,7 0 4
260 ,3 31

8 7 4 ,4 1 8
4 5 8 ,0 3 6

9 0 9 ,5 8 9
5 4 3 ,2 37

1 ,8 33 ,8 01
4 3 2 ,4 1 3
2 3 7 ,8 2 0
5 ,0 6 5 ,4 7 9

-

3

+ 23

+ 7

8 4 3 ,8 2 9
4 5 3 ,2 9 2

- 4
-1 6

+ 4
+

+
+

2 ,1 97 ,9 21
4 7 7 ,6 9 5
2 8 5 ,1 1 7
5 ,0 61 ,6 61

1 ,9 76 ,0 33
4 0 0 ,6 7 8
2 8 2 ,6 4 5
5 ,6 0 5 ,4 8 7

—17
- 9
-17
+

- 7
+
-16

- 5
+
+
- 3

4 3 5 ,2 5 9
7 ,1 7 0 ,5 0 8
1 ,6 74 ,6 52
530 ,0 95
5 7 5 ,6 6 9
1,2 29 ,8 32
4 ,2 7 5 ,9 3 8
1 ,1 39 ,0 69

4 7 8 ,9 7 3
7 ,7 56 ,1 51
1,7 29 ,6 27
5 11 ,6 59
6 10 ,1 6 2
1 ,0 14 ,9 88
4 ,6 7 0 ,5 7 0
1 ,2 68 ,6 76

4 6 6 ,3 6 7
7 ,5 17 ,5 73
1 ,6 19 ,7 76
5 30 ,7 49
592 ,7 22
1 ,0 09 ,1 32
4 ,2 8 7 ,0 7 5
1 ,3 52 ,4 58

- 9
- 3
+ 4
+
-

- 7
- 5
+ 3
- 3
+
-1 6

+ 3
+
+
+
-

A lb a n y
.........................
A t l a n t a .........................
A u g u s t a .........................
C o lu m b u s . . .
M aco n
.........................
Savannah
. . . .

1 9 2 ,1 82
. 1 9,93 6,67 1
6 6 4 ,2 6 4
4 8 6 ,2 3 7
8 4 5 ,7 2 0
. 1 ,0 6 1 ,4 1 8

191 ,4 76
2 3 ,1 9 1 ,3 7 2
6 6 0 ,0 4 3
5 0 3 ,3 2 4
86 2 ,5 8 0
1 ,0 2 2 ,5 8 8

2 1 9 ,8 8 0
1 9 ,7 1 1 ,3 3 2
6 7 4 ,3 9 9
5 1 8 ,6 9 6
8 9 5 ,0 9 5
6 4 5 ,4 0 4

A le x a n d ria
. . .
B a to n R o uge
L a fa y e tte
. . . .
L a k e C h a rle s
New O rle a n s . . .

3 2 2 ,2 5 3
1 ,8 9 4 ,0 6 9
4 0 3 ,0 7 1
2 9 6 ,6 6 0
5 ,5 5 1 ,5 5 6

3 1 6 ,6 8 2
1 ,9 9 5 ,5 2 6
4 2 1 ,3 2 7
29 1 ,0 5 0
5 ,7 6 9 ,5 0 2

295 ,8 41
1 ,7 9 9 ,2 3 5
325 ,5 21
2 8 0 ,1 0 7
5 ,3 0 7 ,8 9 0

+
- 5
- 4
+
- 4

2 9 5 ,4 5 7
1 ,7 0 5 ,8 4 0

3 1 2 ,7 6 8
1 ,7 1 0 ,0 5 0

2 6 0 ,5 23
1 ,7 8 4 ,1 8 4

-

1 ,2 54 ,6 22
1 ,4 92 ,2 63
4 ,3 2 1 ,9 5 0

1 .2 8 3 ,4 1 0
1 ,5 7 7 ,5 6 8
4 ,7 0 3 ,6 7 8

1 ,5 3 0 ,7 0 0
2 ,0 6 9 ,1 6 6
4 ,0 8 0 ,6 5 4

122 ,6 84

121,924

125,657

B a rto w -L a k e la n d W in te r H a ven
D ayto n a B e a c h . .
F t. L a u d e rd a le H o llyw o od . . . .
F t. M yers . . . .
G a in e s v ille
. . .
Ja c k s o n v ille . .
.
M elbourneT itu s v ille - C o c o a
.........................
M iam i
O r l a n d o .........................
P e n s a c o la . . .
S a ra so ta
. . . .
T a lla h a s s e e
. . . .
T a m p a -S t. Pete.
.
W. P a lm B e ac h
.

.

.

B ilo x i- G u lfp o rt . .
Ja c k s o n .........................
C h atta n o o g a . .
K n o x v ille
. . . .
N a s h v ille
. . . .

.
.
.

. . . .

5
5

-10

- 0
6 + 15
+
22
6 + 14
12 + 8

1

8
0 -10

8

8
12
8
1

2
1
0 12
6
1
21 2 6
2
8 0 1
-10
6
+ 0 —13
- 6
-1 4
+ 1 + 5
+ 1 - 2 + 6
- 3 - 6 + 0
- 2 - 6 + 8
+ 4

2

2

-

6
0
2
5
8

+

1

)T H E R C E N T E R S
A n n isto n

2

-t-64

+ 67

+ 9
+ 5
+ 24
+
+ 5

+
+ 30
+ 32
+
+

+ 13
- 4

+ 17
+

10

6 11
11

-1 8
-2 8
+

6
-11
- 8

6

-

+ 15

2

+ 7

'C o n fo rm s to S M S A d e fin itio n s a s of D e c e m b e r 31, 1972.
- D is tric t p o rtio n o n ly ,
r-revised
F ig u re s fo r so m e a re a s d iffe r s lig h tly from p re lim in a ry fig u re s p u b lis h e d in " B a n k

FEDERAL RESERVE BANK O ATLANTA
F



Year
to
d a te
5 m o s.
1975
M ay
fro m
1974 197.4

M ay
1975
fro m
A p ril
1975

M ay
1974

A p r.
1975

1 8 9 ,5 17
8 2,55 1

1 9 5 ,7 19
9 1 ,7 9 4

2 1 4 ,4 6 8
8 1,27 1

-10

B ra d e n to n
. .
M onroe C o u n ty
O c a l a .........................
S t. A u g u stin e
S t. P e te rs b u rg h
Tam pa
. . . .

1 94,913
1 3 5 ,3 08
2 4 1 ,0 3 5
4 3 ,8 6 0
9 7 7 ,4 7 3
2 ,3 1 9 ,6 1 3

2 1 4 ,2 83
1 25 .3 98
2 5 1 ,7 7 2
4 6 ,2 9 6
1 ,1 0 6 ,0 8 8
2 ,4 5 6 ,8 6 6

2 2 5 ,1 0 8
9 6 ,5 9 8
1 9 6 ,7 2 4
5 4 ,7 1 8
1 ,0 90 ,2 77
2 ,1 3 9 ,9 8 5

- 9
+
- 4
- 5

A th e n s
. . . .
B ru n s w ic k
. .
D alto n
. . . .
E lb e rto n
. . .
G a in e s v ille
. .
G riffin
. . . .
L a G ra n g e
. . .
N ew n a n . . . .
R o m e .........................
V a ld o sta
. . .

1 72 ,3 83
1 19 ,9 97
1 77 ,0 22
2 7 ,9 0 9
1 6 0 ,1 89
7 5,74 3
4 0 ,3 3 7
4 4 ,1 5 6
1 62 ,1 52
1 1 6 ,6 34

1 6 9 ,4 88
1 24,973
1 8 0 ,9 2 4
2 8 ,5 0 0
176 ,8 55
7 7 ,5 3 8
3 8,34 5
50,241
1 6 5 ,6 20
1 18,224

1 69 ,4 74
1 0 4 ,6 39
192 ,7 99
2 3,95 2
151 ,8 97
9 1 ,1 0 3
4 5 ,8 6 9
55,351
161 ,6 07
1 13 ,4 46

A b b e v ille
. .
B u n k ie
. . . .
Ham m ond . .
New Ib e ria
.
P la q u e m in e
.
T h ib o d a u x . .

1 8,530
1 6,73 0
1 16 ,3 95
9 5 ,4 4 4
2 7 ,5 6 0
6 8 ,5 0 8

1 9,44 9
1 7,70 8
117 ,8 47
88,38 1
2 9,41 1
74,271

18,172
1 5,15 4
100 ,0 67
7 0 ,9 8 8
2 6 ,9 5 5
4 4 ,4 0 7

.
.

1 47 ,8 66
7 6 ,2 5 0
132 ,6 24
5 3 ,3 8 9

1 49 ,2 10
8 5 ,6 6 3
1 36 ,4 88
6 2 ,9 8 8

1 44 ,4 18
9 2,90 3
135 ,7 05
6 0 ,8 9 5

.
.

186 ,7 95
7 5,69 0
4 2 ,7 0 6

152 ,6 26
8 0 ,5 7 9
5 4,65 0

168 ,0 36
9 3 ,8 4 3
5 1 .0 1 4

B ris to l
. . . .
Jo h n so n C ity
K in g sp o rt . . .

1 46 ,4 50
1 70 ,1 30
3 13 ,7 61

148,181
1 8 1 ,9 29
3 2 6 ,6 3 6

1 46,255
1 81 ,7 74
3 0 3 ,6 3 0

M ay
1975
D o than
S e lm a

+ 18
- 7
+ 9
+
+

.

P e rce n t C h a n t*

Year
to
d ate
5 m os.
1975
from
1974
. . . .
. . . .

H a ttie sb u rg
.
L a u re l
. . . .
M e rid ia n
. .
N a tch e z
. .
P a sc a g o u la M o ss P o in t
V ic k s b u rg
.
Y a zo o C ity
.

S T R IC T T O T A L

.
.
.
.
.
.

.

. 9 1 ,8 1 1 ,4 0 9

9 8 ,2 7 7 ,6 2 8 r 9 0 ,6 6 2 ,8 3 4

A la b a m a
. . .
F lo rid a
. . . .
G eo rg ia . . . .
L o u is ia n a *
. .
M is s is s ip p i. .
Ten n essee:
. .

1 1 ,8 6 5 ,5 5 4
2 8 ,4 9 3 ,6 8 4
2 7 ,4 6 5 ,0 5 8
. 1 0,16 5,28 0
. 3 ,5 7 7 ,2 8 7
. 1 0 .2 4 4 ,5 4 6

1 2 ,3 8 2 ,3 7 5 r 1 0 ,6 2 3 ,5 6 7
3 0 ,0 2 8 ,9 7 2 r 2 8 ,2 8 7 ,3 5 1
3 0 ,6 7 1 ,9 5 4
2 6 ,6 0 1 ,4 2 6
1 0 ,5 7 6 ,3 0 5
9 ,5 8 0 ,3 9 4
3 ,5 9 4 ,9 4 0
3 ,6 4 8 ,9 1 3
1 1 ,0 2 3 ,0 8 2
1 1 ,9 2 1 ,1 8 3

-

3

8

+

-12
2

-

-1 3
+ 40
+ 23

+ 14
+ 9

+ 3

+ 7

+

5

6
1

-20 -22
-12 -10 - 5
6+ 8+ 8
+ 2 + 2 + 1
- 4
+ 15
+ 19
- 2 - 8 -1 3
- 2 + 17
+ 7
- 9
+ 5 + 8
- 2 -1 7
-12
+ 5 -12 - 1 4
-12 -20 - 1 5
- 2 + 0 + 3
- 1 + 3 + 7
- 5 + 2 + 9
- 6 + 10 + 2 8
- 1 + 16 + 30
+ 8 + 34
+ 33
- 6 + 2 + 24
- 8 + 54 + 6 0
- 1 + 2 + 12
-11 - 1 8 - 3
- 3 - 2 + 1
-12 + 3
-1 5
+2
2 + 11 + 5
- 6 -1 9
-12
-22 - 1 6 - 0
- 1 + 0 + 13
- 6 - 6 - 2
-

-

4

'1
- 4
+ 12
- 5 + 1
-10 + 3
- 4
+ 6
- 0 - 2
-

-

7

7

+

+ 7

-14

+ 19
+ 7
+ 17
+ 4
+ 3

0

D e b its an d D ep o sit T u rn o v e r " by B o a rd o f G o v e rn o rs of th e F e d e ra l R e s e rv e S y s te m .

15
1

D is t r ic t B u s in e s s C o n d it io n

* S e a s. a d j. fig u re ; n o t a n in d e x
L a te s t p lo ttin g : May, e x c e p t m fg. p ro d u c tio n a n d fa rm c a s h re c e ip ts , A pril.

Several sectors of the Southeastern economy have improved noticeably. Employment increased amid other
hopeful signs in labor markets. Incomes of manufacturing employees grew, and consumer spending seemed
to strengthen. The value of construction contracts was marginally higher. Rising livestock prices and falling
feed costs improved the agricultural outlook. A weak loan demand is causing banks to purchase securities.
Total nonfarm employment rose in May for the
first time in 1975, while the unemployment rate
registered its first decline in 11 months. Manu­
facturing jobs, stimulated by strength in nondur­
ables, continued to pick up despite a weak durable
goods sector. The average manufacturing worker
put in a longer workweek and received a fatter pay
check. Moderate job gains in most nonmanufactur­
ing industries offset continuing heavy losses in
construction, halting the recent slide in total non­
manufacturing employment.
Consumers appeared to spend more freely, as the
prolonged erosion of total consumer instalment
indebtedness to banks eased substantially during
May. Increasing extensions of automobile credit in
combination with lower repayments were primarily
responsible, although personal loans outstanding
also rose. Home repair and modernization credit
was essentially unchanged, while other consumer
goods credit outstanding continued to decline. In­
comes of persons employed in manufacturing
increased in both April and May. New car registra­
tions fell slightly in April and stood over one
quarter below the year-ago level.
The value of residential construction contracts
gained slightly in May for the third month in suc­
cession. Accompanying this improvement were
continued record deposit inflows at savings and

loan associations and slight declines in mortgage
rates. The value of nonresidential contracts was also
up slightly, on the strength of a large contract for
an electric power plant near Birmingham.
Prices of agricultural products turned upward
slightly in May. Sharply rising livestock, cotton, and
citrus prices were primarily responsible for an in­
crease largely offset by declining grain and soybean
prices. Preliminary data for June indicate that live­
stock prices have continued their upward trend,
with broiler prices advancing most rapidly. Broiler
placements have increased in response to an im­
proved outlook which also reflects lower feed costs.
Indicated wheat production is one-eighth higher
than a year ago, but lower prices have reduced the
value of the crop. Ample rainfall created excellent
growing conditions for crops and pastures through
mid-June.
Loan demand at commercial banks has shown no
signs of reviving. Business loans declined over the
mid-June corporate tax payment date in contrast to
the usual seasonal increase in borrowing. Banks are
continuing to add sizable amounts of government
securities to their portfolios in an attempt to expand
earning assets. Stronger deposit growth has been
centered around net demand deposits and passbook
savings accounts.

N Data on which statem
ote:
ents are based have been adjusted w
henever possible to elim
inate seasonal influences.

16
1




JU 1 7 , MONTHLY REVIEW
LY 9 5