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Inthis issue:
The Distribution of Southeastern Income

District Business Conditions

Banking Notes: Banking at Midyear




T h e D is t r ib u t io n o f
S o u th e a ste rn

In c o m e

by William D. Toal
" T h r e e fu n d a m e n ta l p rin c ip le s o f e q u ity c o n c e r n in g the d is trib u tio n o f in c o m e
are w id e ly a c c e p t e d : th o se w h o p r o d u c e the sa m e a m o u n t s h o u ld b e r e w a rd e d
e q u a lly (h o riz o n ta l e q u ity ); th o se w h o p r o d u c e m o re s h o u ld b e r e w a rd e d m o re
(ve rtica l e q u ity ) ; a n d n o in d iv id u a l o r h o u s e h o ld s h o u ld b e f o r c e d to fall b e lo w
s o m e m in im u m sta n d a rd o f c o n s u m p tio n re g a rd le ss o f p r o d u c tiv e p o te n tia l.
A lth o u g h th e re is fairly g e n e ra l a g re e m e n t o n th e se p rin c ip le s , the d e sira b ility o f
an y g iv e n a m o u n t o f in e q u a lity in the in c o m e d is trib u tio n re m a in s a m a tter o f
p e rs o n a l ju d g m e n t a n d o f so c ia l a n d p o litic a l d e b a te ."

(The A n n u a l Report o f the C o u n c il o f E co n om ic Advisers, 1974)
T w o questions are of im portance in evaluating an e c o n o m y's perform ance:
G iven lim ited resources, ho w m uch is bein g produ ced and w h o gets the benefits
o f this produ ction? H o w m uch is produ ced gets m ost o f the attention. For
example, the rapid grow th of the Southeast has received m uch publicity.
How ever, this region still produces less per person (m easured by per capita
incom e) than the national average.1 In other w ords, total produ ction or incom e
per person is sm aller in the Southeast than nationally. But w hat ab ou t the
distribution o f Southeastern production and incom e? H o w is the inco m e pie
sliced and h o w evenly cut are the slices, especially w hen contrasted to national
incom e distribution?
This article exam ines the distribution of Southeastern incom e, first c o m p a rin g
it to the U. S. as a w hole. It explores w hy geograph ic differences in incom e
distribution still exist. Finally, the article throw s light on w hat happened to
incom e distribution du ring the Sixties and why.
W h y the Interest in the In c o m e Pie?
The o p tim u m distribution of incom e is debatable. But m any believe that
w hatever the overall size of the incom e pie, the m ore evenly it is cut, the
higher the level of ec o n o m ic w ell-being. Is the Southeast's inco m e pie
b e c o m in g m ore evenly sliced over tim e? If so, w hat forces are responsible? This
is of general interest, but particularly in the Southeast.
D istribution of incom e m ay also have im portant im plications for eco n o m ic
growth. States or regions can obtain outside capital for e c o n o m ic grow th
m uch m ore easily than a country. By the sam e token, som e econo m ists believe
a less even distribution of incom e m ay reduce co nsum e r sp e n d in g and, as a
1
The Southeast, as defined here, includes those states entirely or partially within the Sixth Federal
Reserve District— Alabama, Florida, Georgia, Louisiana, Mississippi, and Tennessee.

M onthly Review, V o l. LIX, N o . 8.

Free su b s c rip tio n and a d d itio n a l c o p ie s a va ila b le
u p o n req u est to the Research D e p a rtm e n t, Federal R eserve Bank o f A tla n ta,
A tla n ta, G e o rg ia 30303.

114




A U G U S T 1974, M O N T H L Y R E V IE W

CHART I

Family Income Distribution (1969)

M edian F a m ily Incom e
(th o u s. $)

E 3 Total

-1 0

8

6

4

2

0
U. S.

Ala.

Fla.

Ga.

La.

Miss.

Tenn.

Gini Index of Family Income Concentration (1969)

Total

La.

Miss.

Tenn.

U.S.

Ala.

Fla.

Ga.

.364

.393

.398

.381

.403

.427

.390

.362

.371

.380

.379

White

.353

.365

.388

Black

.397

.416

.389

.401

.429

.435

.400

Urban

.357

.384

.396

.382

.396

.400

.377

Rural Nonfarm

.363

.380

.390

.369

.402

.418

.377

Rural Farm

.414

.419

.425

.420

.478

.472

.419

consequence, divert resources into capital invest­
m ent; this w o u ld boo st ec o n o m ic grow th.2
H o w the incom e pie is sliced, therefore, m ay
have im plications for both ec o n o m ic w ell-b eing
and grow th. A m ore uneven distribution o f incom e
m ight reduce w ell-b ein g in the short run but m ay
accelerate e co n o m ic grow th, w hich eventually
w o u ld lead to greater w ell-being. How ever, at any

2
The relationship, if any, between the distribution of income,
savings, and economic growth in the Southeastern states will be
examined in a forthcoming article.

FE D ER A L R ES E R V E BANK O F A TLA N TA




given time, a specific distribution of incom e m ay
result in a trade-off of less grow th for m ore w e ll­
being or vice versa.
The G in i Index
This study draws on data from the 1970 C en su s of
P opu lation and utilizes the G ini index of incom e
concentration. Briefly, this index measures the area
between a line o f perfect incom e equality and a
line of actual incom e inequality (called the Lorenz
Curve). This area, shaped like a banana, grow s
bigger as incom e inequality increases. C o n se-

115

quently, the higher the index, the greater the
inequality in incom e.3
This study uses the fam ily as the basic incom ereceiving unit, since fam ily incom e is considered a
better m easure o f e co n o m ic w e ll-b e in g than per
capita incom e. The G ini index has several lim ita­
tions, however: Before-tax incom e, representative
o f a single year (1969), is used and n on m o n e y
incom e sources are not accounted for.
W he re the Southeast Stands
A s w e m ight expect, the Southeast's incom e w as
less evenly distributed than the nation's at the turn
of the decade (1969). The chart points out that
each Southeastern state had low er than national
average fam ily incom es. T o som e views, low er
incom e areas typically have m ore uneven
distributions. This is indeed the case in the
Southeast (see chart). W h a t is surprising is just how
uneven this distribution is in each state. M ississip p i
has the m ost uneven distribution in the nation;
overall, the six Southeastern states are am o n g
the bottom nine in the country in this respect.

W h y Such U neven Distribu tion ?
W h a t are som e of the forces affecting incom e
distribution and h o w w ell d o these forces explain
the Southeast's uneven distribution? Several studies
have throw n light on these questions.4 So m e o f the
m ost notable factors were level o f eco n o m ic
developm ent, racial m ake-up, extent o f urbaniza­
tion, and im portance o f different incom e types
(i.e., the functional distribution of incom e). In som e
of these studies, age and educational levels, as
well as occupational m akeup o f the labor force,
were fou n d to be related to incom e distribution.
In seeing ho w these factors apply to the Southeast,
particular attention w ill be paid to eco n o m ic
developm ent, racial mix, urban-rural m ake-up, and
incom e sources.
M a n y o f the forces m entioned above and their
im portance to the Southeast are sh ow n in Table 1.
N o n e is perfectly associated with incom e distribu­
tion (show n in the first line); but, let us see
just w hat influence, if any, e co n o m ic developm ent,
racial m ake-up, rural-urban mix, and sources of

3 more complete description of the Gini index and its graphic
A
interpretation is given in the Appendix.
4
See: Almand Al-Samarrie and Herman P. Miller, "State Differentials
in Income Concentration," The American Economic Review, Vol.
LVII, No. 1 March 1967, pp. 59-72; D. V. Aigner and A. V. Heins,
,
"On the Determinants of Income Equality," American Economic
Review, Vol. LVII, No. 1 March 1967, pp. 175-181; James E
,
.
Jonish and James B. Kau, "State Differentials in Income
Inequality," Review of Social Economy, Vol. 31, No. 2, October
1973, pp. 179-190; and Tom S. Sale, III, "Interstate Analysis of the
Size Distribution of Family Income, 1950-1970," Southern
Economic Journal, Vol. 40, No. 3 January 1974, pp. 434-441.
,
116




incom e have on the Southeast's uneven incom e
distribution.
Eco n om ic D e ve lo p m e n t
D o e s higher e c o n o m ic d eve lopm en t tend to
equalize an area's distribution o f incom e? A num ber
of studies have exam ined this relationship, often
with conflicting results.5 How ever, greater m obility,
both geo graphic and industrial, greater w age
standardization (through unionization), m ore
education, and the d e clin in g im portance o f
agriculture generally go with higher ec o n o m ic
developm ent. A n d each o f these characteristics
w o u ld seem to contribute to eq u alizin g the slices
o f the incom e pie.
D o w e find this relationship between incom e
distribution and ec o n o m ic d eve lopm en t w hen w e
exam ine the Southeast? The answ er is yes and
maybe. T w o o f the m ore frequently used measures
o f e co n o m ic d eve lo pm en t are average incom e and
im portance o f m anufacturing, though neither
measures e c o n o m ic d eve lo p m en t perfectly. W h e n
applied to the Southeast, however, both sh o w
this region to be less deve loped than the nation as
a w hole (see Table 1, lines 2 and 3). Looked at
strictly on a regional basis, then, the Southeast
is less deve loped e co n o m ica lly and has a m ore
uneven incom e distribution than the nation as a
w hole. How ever, in individual Southeastern states,
any relationship between incom e distribution and
e co n o m ic deve lo pm en t is loose at best. The m ost
one can say is that those states w ith higher
eco n o m ic deve lo pm en t (approxim ated by incom e
and m anufacturing im portance) generally have
som ew hat m ore evenly sliced incom e pies.6

'Several of the articles mentioned in the previous footnote examine
the influence economic development has on income distribution.
They refer to this hypothesized relationship as the Kuznets thesis,
based on Simon Kuznets' empirical observations on economic
development and income distribution among countries. See Simon
Kuznets, "Economic Growth and Income Inequality," The
American Economic Review, Vol. XLV, March 1955, pp. 1-28;
------------------ z "Quantitative Aspects of the Economic Growth
of Nations: VIII, Distribution of Income By Size," Economic
Development and Cultural Change, January 1963, Part 2, pp. 1-80.
f,For the six Southeastern states, the Spearman rank correlation
coefficient between the Gini index and percent of employment in
manufacturing of -.6000 was considerably higher than the rank
correlation coefficient of the Gini index with median family
income of -.3714. However, neither rank correlation coefficients
are significantly different from zero at the 95-percent level of
confidence.
For the six Southeastern states, percent of employment in
manufacturing may be a poor proxy for economic development,
particularly in Florida. In fact, the rank correlation coefficient
between median family income and percent of employment in
manufacturing is negative. Consequently, this variable may be a
proxy for some force other than economic development, possibly
the extent of unionization as shown in Table 1. The rank correla­
tion between extent of manufacturing and extent of unionization
in the Southeastern states is +.7143.
Using some unpublished county Census data on family income
concentration, a significant inverse rank correlation between
county family incomes and their distributions was found for each
Southeastern state.
A U G U S T 1974, M O N T H L Y R E V IE W

TA BLE 1

FO R CES

IN F L U E N C IN G

TH E

D IS T R IB U T IO N

OF

F A M IL Y

IN C O M E

M ississip p i

Lo u isia n a

Florida

Alabam a

T e n n e sse e

.427(1)

.403(2)

.398(3)

.393(4)

.390(5)

.381(6)

.364

$6,071(6)

7,530(3)

8,267(1)

7,266(5)

7,447(4)

8,167(2)

9,590

% Employed in
Manufacturing

25.9(4)

15.0(5)

14.1(6)

28.6(2)

30.6(1)

27.2(3)

29.9

% of Population
Nonwhite

37.2(1)

30.2(2)

15.8(6)

26.4(3)

16.1(5)

26.1(4)

12.5

% of population
Urban

44.5(6)

66.1(2)

80.5(1)

58.4(5)

58.8(4)

60.3(3)

73.5

% of Income
From property

11.3(4)

15.0(2)

17.4(1)

11.2(5)

11.8(3)

11.1(6)

14.3

% of population
Over 65 Years Old

10.0(2)

8.4(5)

14.5(1)

8.0(6)

9.9

Median School Yrs.
Completed
(25 & over)

10.9(5)

10.8(3)

12.1(1)

10.8(3)

10.6(6)

10.8(3)

12.1

% Nonfarm Labor
Force Unionized

14.9(6)

19.2(3)

15.1(5)

22.6(2)

23.5(1)

17.7(4)

30.9

Gini Index of
Family Income
Concentration
Median Family
Income

9.8(3.5)

9.8(3.5)

Georgia

U. S

*AII sta tis tic s are for 1970 except the G in i index and m edium fam ily incom e data, w hich are for 1969.
Th e n um b ers in p a rentheses are ran kin gs by So utheastern sta te s for each s ta tis tic from highest num erical value to
lowest.
So u rce: U. S. Departm ent of C om m erce

Racial M a k e -u p
D o e s racial m ake-up influence incom e distribution?
O th e r studies have fo u n d blacks not o n ly have
low er average incom es but also m ore unevenly
distributed incom es than whites. These tw o charac­
teristics im ply that a close relationship should
exist between racial m ake-up and overall incom e
distribution. The greater the percent of nonwhites,
the m ore unevenly distributed incom es shou ld be.
This relationship between racial m ake-up and
incom e distribution w o u ld appear to jibe quite well
with the Southeast's incom e distributions. In each
Southeastern state and the nation as a whole,
average incom es of black fam ilies are b e low those
o f white families, and the incom e distribution of
blacks is m ore uneven than for w hites (see chart).
The net result is a close relationship between per­
cent of nonw hite population and distribution of
fam ily incom e. Each Southeastern state has a m ore
uneven incom e distribution and relatively m ore
nonw hites than the U. S. as a whole. A n d even
am o n g the Southeastern states, racial com position
and unevenness o f incom e distribution seem to
m ove together (see Table 1, lines 1 and 4).7
7
The rank correlation coefficient between the Gini family income
concentration index and the percent of the population which is
FE D ER A L R ES E R V E BANK O F ATLA N TA




However, racial m ake-up only partially explains
the Southeast's uneven incom e distribution. Even
w ithin racial groups, fam ily incom es are distributed
m ore unevenly in the Southeast than nationally
(see chart). Consequently, other forces m ust also be
responsible for these differences.
U rbanization
D o e s urbanization affect the distribution of
incom e? T h o ugh it probably does, o p in io n s differ
on exactly h o w and in w hat direction urbanization
im pacts on incom e distribution. O n e view says
that urbanized areas have a m ore even incom e
distribution than rural areas, particularly farms.
Nonfarm w age and salary incom es, m ost of w hich
are earned in urban areas, typically are higher and
m ore evenly distributed than farm incom es. Like­
wise, urban areas generally have som ew hat higher
education levels and greater concentration of
nonwhite for the six Southeastern states was +.6000. Although
of the expected direction, this correlation was again not
significantly different from zero at the 95-percent level of
confidence. Using the unpublished county data mentioned in
footnote 6, a significant rank correlation was found between these
two variables for four of the six Southeastern states, Florida being
a notable exception.
There is yet another facet contributing to the Southeast's more
uneven than national family income distribution: The difference
in family incomes between blacks and whites is greater in the
Southeastern states than it is for the nation as a whole (see chart).
117

w hite-collar workers than rural areas, w hich tends
to make urban incom es m ore evenly distributed.
O n the other hand, urbanization is also seen
to contribute to a m ore uneven incom e distribution
com pared with rural areas. O n e sees m ost
dram atically the contradiction o f poverty am o n g
affluence in cities, where ghettos attest that
urbanization does not, o f itself, even out incom e
distribution.
For the Southeast, urban areas do have m ore
even incom e distribution than farms. W ith som e
exceptions, rural nonfarm areas fall som ew here
in between (see chart). Since the Southeast is
generally less urbanized than the rest of the nation,
one m ight think there is a relationship between
urbanization and incom e distribution. But in lo okin g
at the individual Southeastern states, there appears
to be little if any relationship (see Table 1, lines
1 and 5).
Property In co m e
W hat about the source of incom e itself and its
im pact on a region or state's distribution of incom e?
The im portance of property as an incom e source
w o u ld seem to have a close bearing on distribution.
Property and its incom e is m uch m ore likely to
occur from w indfalls or inheritance, with a bigger
chance that it will be m ore unevenly distributed
than w ages and salaries. It seem s reasonable to
expect that the m ore im portant property incom e is,
the m ore uneven distribution of incom e shou ld be.
This thesis is verified to som e extent in exam ­
ining the individual Southeastern states (see Table
1, lines 1 and 6). It explains particularly well
Florida's uneven incom e distribution. Property
as a source of incom e is very im portant in Florida,
perhaps because of the older average population.
There is apparently a close relationship between
the proportion of a state's over-65 pop ulation and
the im portance of property as an incom e source
(see Table 1, lines 6 and 7).
A n y im plications draw n so far are based on a
very sm all num ber of observations, the six
Southeastern states. A s such, any conclu sion s
draw n are very "iffy "; to enlarge ou r sphere of
observations, we can look at the distribution of
fam ily incom es in thirty-three Southeastern
m etropolitan areas.
M etrop o litan In com e D istribution
There are large differences a m o n g these
m etropolitan areas in incom e distribution. Table 2
show s W est Palm Beach with the m ost uneven
distribution and Atlanta with the m ost even.
Generally, size of incom e, race, and property in­
com e are the three factors associated with these
differences. (Urbanization w as ob vio u sly not a
significant characteristic, since m etropolitan areas
are largely urban.) These results, then, fo llo w closely
118




TA BLE

2

M ETRO P O LITA N A R EA FA M ILY IN CO M E
D IS T R IB U T IO N (1969)
Gini Index of Fa m ily
Incom e C on cen tration

M etropolitan
Area
ALABAM A

.378
.361
.375
.379
.398
.398

Birmingham
Gadsden
Huntsville
Mobile
Montgomery
Tuscaloosa
FLO R ID A

Fort Lauderdale
Gainesville
Jacksonville
Miami
Orlando
Pensacola
Tallahassee
Tampa-St. Petersburg
West Palm Beach

.399
.403
.370
.410
.364
.362
.408
.383
.424

G EO R G IA

.386
.352
.365
.379
.367
.376

Albany
Atlanta
Augusta
Columbus
Macon
Savannah
LO U ISIA N A

.366
.408
.356
.399
.398
.389

Baton Rouge
Lafayette
Lake Charles
Monroe
New Orleans
Shreveport
M IS S IS S IP P I

.362
.398

Biloxi-Gulfport
Jackson
TEN N ESSEE

.361
.376
.386
.365

Chattanooga
Knoxville
Memphis
Nashville-Davidson
Source: U. S. Department of Commerce

the inferences draw n w hen w e m ade state-bystate com parisons. How ever, these characteristics
actually explain only a little m ore than one-third
of the difference in m etropolitan area incom e
distributions.
Property incom e is a particularly im portant
influence in Florida's m etropolitan areas, where
property incom e is abn o rm ally large and distribu­
tion is m ost uneven. W e st Palm Beach is a case
in point.
C h a n ge s In D istribu tion
Are there any signs that the Southeast's incom e
pie may becom e m ore evenly distributed in the
A U G U S T 1974, M O N T H L Y R EV IEW

years ahead? Recent changes give us a clue. W e see
that in the Sixties a m ovem ent tow ard m ore even
incom e distribution in the Southeast did occur.
In fact, in the past decade, distribution changed
m ore in this region than for the U. S. as a w hole.
Each Southeastern state sh ow ed som e m ovem ent
tow ard m ore even incom e distributions, with the
largest changes taking place in M ississip p i and
Georgia. O n ly Florida sh ow ed very little change.
This m ove tow ard m ore equal fam ily incom e
was not shared by every other state in the U. S.;
in fact, there w as only a slight m ove tow ard less
inequality nationally. In twelve states fam ily incom e
distribution actually grew m ore uneven. C o n se ­
quently, the Southeast's m ove tow ard m ore even
distribution of the fam ily incom e pie is all the
m ore impressive. These changes shou ld continue
if the past is any indication of the future.
W h y These C h ange s?
M a n y o f the sam e factors that influence geographic
incom e distribution m ay have been responsible for
the change in the Southeast's incom e distribution
in the Sixties. For example, the fastest gro w in g
Southeastern states (measured by fam ily incom e)
also experienced the biggest drop in incom e
inequality. M ississip p i w as the leading exam ple
fo llo w ed by the other five states, m atching grow th
in incom e with reductions in inequality; next to
M ississip p i w as Georgia, then Tennessee, A labam a,
Louisiana, and Florida (see Table 3). In co m e grow th
has apparently had som e impact, then, on lessening
incom e inequality in Southeastern states. (At least
differences in individual state grow th rates
correspond to incom e distribution changes.)
The Southeast's ch an gin g racial m ake-up also
may have been responsible for ch an gin g incom e
patterns. In the Sixties, each Southeastern state's
nonw hite pop ulation declined as a percent of total
population. This is in o p p ositio n to w hat happened
nationally, where the nonw hite percentage in­
creased. These changes are related to m igration
patterns, particularly by blacks. Each Southeastern
state w as a net loser of blacks through m igration
in the Sixties; the rest of the country, recipients of
this m igration, generally gained blacks.
Because blacks have low er and m ore uneven
incom es than whites, w e sh ou ld then expect to
find a close relationship between black o u t­
m igration and any change in incom e distribution.
This seem s to be true for every Southeastern state.
M ississip pi, with the sharpest change in fam ily
incom e inequality, had the greatest black o u t­
m igration rate. Florida, on the other hand, had
the sm allest m igration and the least change in
distribution. Thus, black out-m igration and a general
narrow ing of the black and white fam ily incom e
gap are additional elem ents in reducing So u th ­
FE D ER A L R ES E R V E BANK O F A TLA N TA




TA BLE 3

CHANGES IN FAMILY INCOME DISTRIBUTION
Gini Index
of Family Income
Distribution
1969

Percent Change
In Median Family
Income
(1969/1959)

1959*

Change

Mississippi

.427

.466

-.039

110.5%

Georgia

.381

.418

-.037

94.1

Tennessee

.390

.424

-.034

88.6

Alabama

.393

.424

-.031

84.6

Louisiana

.403

.420

-.017

76.3

Florida

.398

.399

-.001

75.1

U. S.

.364

.371

-.007

69.4

1959 are obtained from the Al-Samarrie
p. 63.

eastern incom e inequality.8
C ontin u ed urbanization and declin in g farm
em ploym ent were still other contributing in­
fluences. T ho ugh still less urbanized than the nation
as a w hole, the Southeast's rapid urbanization
and sharp farm em ploym ent decline in the Sixties
probably aided the m ovem ent tow ard m ore equal
incom es. Also, a general reduction in the incom e
difference between urban and rural areas helped
reduce inequality.
Sum m ary and Im plications
Incom e rem ains less evenly distributed in the
Southeast than in the rest of the nation. But in the
Sixties, this region m ade significant progress in
raising incom e levels closer to the national average
and in spreading incom e m ore evenly th roughout
its population. This m ove tow ard a m ore even
incom e distribution w as actually faster than
nationally. But substantial geographic differences
remain. Inco m e in the Southeast w as m ost uneven
in M ississip p i and least in Georgia. How ever,
incom es in all six states were a m o n g the m ost
unevenly distributed in the nation. The Southeast's
rural areas generally show ed m ore uneven

K course this out-migration is itself related to other influences
Of
such as higher wages and job availability in other parts of the
country. Indirectly these higher wages in other regions may be
partially responsible for the changes in Southeastern family income
distribution.
Furthermore, this black out-migration may be responsible for the
close association of the growth in family incomes and changes in
the distribution of these incomes. That is, this out-migration
affects both the growth in average family income levels and the
changes in the distribution of income and is responsible for the
latter two factors moving so closely together.
119

distributions than urban areas, although there
were exceptions. There were also sharp differences
am o n g m etropolitan areas, though incom e was
generally m ore evenly distributed than in n on ­
m etropolitan areas. Despite rather high incom es,
m etropolitan areas in Florida had greater inequality
than those in the other five states.
Trying to explain these differences, we reached
co nclu sio n s sim ilar to other researchers. Race and,
to a m uch lesser extent, urbanization were in­
fluencing factors. How ever, even after these factors
are considered, regional and state differences re­
main. W e fo u n d incom e and extent of m anu fac­
turing— influences reflecting e co n o m ic d e ve lo p ­
ment— to be other determ inants o f incom e
distribution. The im portance o f property incom e
w as likewise closely associated with inequality,
particularly in m etropolitan areas.
Inco m e grow th appeared closely related to
changes in incom e distribution in the Sixties. Also,
the change in racial m ake-up o f the population,
associated with black m igration, w as fou n d to have
a particularly strong influence. Those areas with
the largest black out-m igration show ed the sharpest
changes (toward less inequality).
This study further sh ow ed that incom e differ­
ences between the Southeast and the rest o f the

120




nation and a m o n g the Southeastern states and
m etropolitan areas cannot be entirely explained
by the social, dem ographic, and e c o n o m ic influ­
ences m entioned. Indeed, they fail to account
for even the greatest portion o f these differences
and changes. O n e cannot underestim ate the im pact
mere chance and the historical deve lo pm en t of
institutions in the region have had on incom e
distribution. The Southeast's agrarian background,
co up led with its delayed industrialization and past
reliance on the institution o f slavery, prob ab ly
still has an im pact on distribution.9
How ever, as e c o n o m ic deve lopm en t continues
and per capita incom e approaches national levels,
this incom e becom es m ore evenly distributed.
A s a result, the pop ulatio n increasingly shares in
the region's ec o n o m ic grow th, as w as the case
in the Sixties. W e can prob ab ly expect ec o n o m ic
developm ent in the Southeast to continue this
trend tow ard m ore even incom e distribution in
the years ahead, with a net result o f greater
overall eco n o m ic w ell-being. ■

8
Thomas R Atkinson, “Money Income Distribution — South vs.
.
Non-South," Southern Economic Journal, Vol. XXIII, July 1956,
pp. 26-27.

A U G U S T 1974, M O N T H L Y R EV IEW

A P P E N D IX

M e a s u r in g In c o m e D is t r ib u t io n

H o w d o w e m easure incom e distribution? The
m ost frequently used m ethod is to rely on data
furnished by the C en su s o f Population, w hich gives
the num ber of fam ilies or persons in different
incom e intervals (see Chart A-1). Here the num ber
and percent o f fam ilies and the percent o f fam ily
incom e for each incom e interval are show n.
C o m p ariso n s can then be m ade of the percent of
fam ily incom e and percent o f fam ilies in various
incom e intervals for different geograph ic units
or for the sam e unit at different points in time.
For example, c om parin g the data in Chart A-1 with
sim ilar data for the U. S. as a w ho le (not show n),
w e find that in 1969 the Southeast had both a
greater percentage o f fam ilies and o f fam ily incom e
in the low est interval (i.e., less than $1,000) w hile
it had a sm aller percentage of both fam ilies and

_

_

_

_

_

_

_

fam ily incom e in the highest incom e interval (i.e.,
greater than $25,000). This of itself does not tell us
m uch about differences in incom e distribution
between the Southeast and the U. S., since the
Southeast's m edian fam ily incom e is low er than
the nation's. O n ly w hen equal percentages o f fam i­
lies are used to com pare percentages of total fam ily
incom e can a m eaningful com parison abou t d if­
ferences in incom e distribution be obtained. Chart
A-2 show s such a standardization by grap hin g the
cum ulative percent of families. If perfect equality in
fam ily incom e w as present, any given percent of
fam ilies w o u ld have the sam e percent of fam ily
income. For example, 10 percent o f the fam ilies
w o u ld have 10 percent of the income. In other
words, a perfectly even distribution o f incom e, in
w hich everyone received the sam e incom e, w ou ld

_

C H A R T A-1

Distribution of Southeastern Family Income (1969)
Incom e Interval

Percen t of Fa m ily Incom e

Num ber
of Fa m ilie s

Less than $1000

233184

$1000 — $1999

352643

$2000

— $2999

381393

$3000

— $3999

410215

$4000

— $4999

415147

$5000

— $5999

441939

$6000 — $6999

435313

$7000

— $7999

432062

$8000

— $8999

416151

$9000 — - $9999

10

181919

$25000 +
15

445391

$20000 - $24999

A

148480

$15000 - $19999

I J

197976

$14000 - $14999

J

272218

$13000 - $13999

J

286842

$12000 - $12999

I

352906

$11000 — $11999

I____I

367803

$10000 - $10999

• LJL

Percen t of Fa m ily U nits

191031

■

X ,.

l l IA

10

S o u r c e : 1 9 7 0 C e n s u s of P o p u la t io n

FE D ER A L R ES ER V E BAN K O F ATLA N TA




121

C H A R T A -2

Lorenz Curves and Income Inequality
P e r c e n t of F a m ily In c o m e

c.

Percent of Family Units

appear as the straight line rising from the origin
of the graph at a forty-five degree angle. The
actual data from Chart A-1, plotted in cum ulative
percentages, is sh ow n by the colored line in
Chart A-2-a. Here w e can see that 20 percent of
" the ho useho lds obtain far less than 20 percent
o f the total fam ily incom e; 40 percent of the
families, far less than 40 percent of the total
fam ily incom e, etc. Thus, incom e is distributed
m uch less equally than if perfect equality were
122




d.

present. In general, the greater this graphed line
is bow ed aw ay from the straight forty-five degree
line, the greater is the inequality in incom e distri­
bution. This line, w hich plots cum ulative percent­
ages of families, is called a Lorenz Curve. Plotted
in black is the Lorenz Curve for the United States
derived from national data sim ilar to that show n
in Chart A-1 for the Southeast. A s can be seen
from these graphic measures, in 1969 the nation's
distribution of fam ily incom e w as m ore even than
A U G U S T 1974, M O N T H L Y R E V IE W

that of the Southeast. A s lo n g as these Lorenz
Curves d o not intersect, they give us a clear
com parison of incom e distribution. The curve
w hich is m ore bo w ed out, in this case the So u th ­
east's curve, represents the m ore unequal state of
inequality in incom e distribution.
Chart A -2 -b reproduces the Southeast's Lorenz
C urve for both 1969 and 1959. The m ore bow ed
1959 curve indicates that fam ily incom e distribution
has grow n m ore even in the Sixties. Chart A -2 -c
show s Lorenz Curves for w hite and black So u th ­
eastern fam ilies in 1969. The m ore bo w ed Lorenz
Curve for blacks show s their incom e to be less
evenly distributed than w hite fam ily incom e.
W h e n Lorenz Curves intersect, com parison s

of incom e distribution becom e m ore uncertain.
In these cases, a quantifiable m easure of incom e
distribution is needed. The G ini concentration
index is derived from the Lorenz Curve. It measures
a ratio of the area between the straight forty-five
degree line and the Lorenz Curve, the shaded area
in Chart A-2-d, to the total area b ou nde d under
the straight forty-five degree line. The higher this
index, the m ore concentrated or uneven the
distribution of incom e. In 1969, the Southeast's
G ini concentration index w as .395, as com pared to
.364 for the U. S. These indexes confirm the
graphic approach show n in Chart A-2. T h ro ughou t
the b o d y of this article, G ini concentration indexes
have been used to analyze fam ily incom e
distribution.

J u ly 12, 1974

B a n k
A n n o u n c e m e n ts

PEO PLES B A N K O F G R A C E V IL L E
Graceville, Florida

Opened for business as a par-remitting nonmember. Officers:
Robert F McRae, Sr., chairman; Donald R. Graham, presi­
.
dent; Marvin T. Dixon, cashier. Capital, $250,000; surplus
and other funds, $200,000.

Ju n e 13, 1974
THE C O U N T Y B A N K
Palmetto, Florida

Opened for business as a par-remitting nonmember.
Ju n e 17, 1974

Ju ly 15, 1974
B A N K O F V IC K S B U R G
Vicksburg, Mississippi

Opened for business as a par-remitting nonmember.

FIRST C IT IZ E N S B A N K
Fayetteville, Georgia

Opened for business as a par-remitting nonmember. Officers:
T. B. McLeod, president; Alton D. Brown, chairman of
the board; Travis R Hardy, vice president; H. Crawford
.
Hewell, cashier. Capital, $525,000; surplus and other
funds, $247,000.
J u ly 1, 1974
A M E R IC A N C IT Y B A N K
Tullahoma, Tennessee

Opened for business as a par-remitting nonmember. Officers:
Duane Thorpe, president; George S. Vibbert, Jr., vice
president. Capital, $400,000; surplus and other funds,
$400,000.

Ju ly 15, 1974
U N IT E D S O U T H E R N B A N K O F M O R R IS O N
M orrison, Tennessee

Opened for business as a par-remitting nonmember.

Ju ly 17, 1974
A T L A N T IC W E S T S ID E B A N K O F
PALM BEACH C O U N T Y
West Palm Beach, Florida

Opened for business as a par-remitting nonmember.

J u ly 1, 1974

Ju ly 24, 1974

EAST R ID G E C IT Y B A N K

G A D SD EN M ALL BANK

East Ridge, Tennessee

Gadsden, Alabama

Opened for business as a par-remitting nonmember.

Opened for business as a par-remitting nonmember.

J u ly 10, 1974
BARNETT B A N K O F N O R T H P E N S A C O L A
Pensacola, Florida

Opened for business as a par-remitting nonmember. Officers:
Allan L McLeod, Jr., president; Mary Lor Hobby, vice
.
president and cashier; Rudolph Polise, Jr., assistant vice
president. Capital, $400,000; surplus and other funds,

$200,000.

F E D ER A L R ES E R V E BANK O F ATLA N TA




Ju ly 25, 1974
BANK OF C A N T O N M EN T
Cantonment, Florida

Opened for business as a par-remitting nonmember. Officers:
J Barnett Jones, president; Ms. Willigem Crocker, vice
.
president and cashier. Capital, $370,000; surplus and other
funds, $555,000.

123

BANKING STATISTICS
B illio n $
D E P O S IT S * *

C R E D IT *

- 40

- 36

- 36

- 24

- 14

- 20
*
- 8

Loans
& Investments

-

- 10

40

Loans (net)
Other Securities

- 10
_

U.S. Gov’t. Securities

- 4
Savings

- 6
III I I II I I II I II I I I I II I II I 1II I I
j

J

DJ

J

1973

DJ

I I I II I I II
J
J

J

1974

1973

1975

D IS T R IC T

B A N K IN G

B a n k in g

I II

II

I Ii I I I
DJ
J

1974

1975

•Figures are for the last W ednesday of each month
•D aily average figures

LATEST MONTH PLOTTED: JULY

S IX T H

I I I I I I I II
DJ
J

at

N D TE5

M id y e a r

S IX T H D I S T R IC T M E M B E R B A N K L O A N S
( S e a s o n a ll y A d ju s t e d )
Ju n e 1974
Am ount
(m illion $)
D IS T R IC T ........................................

. 28,447.0

+

7.5

ALABAM A

. 3,770.9
205.7
. 1,766.9
182.9
660.4
637.2

+
+
+
+
+
+

7.9
6.8
9.4
9.4
6.7
2.3

F L O R I D A ........................................

.
.
.
.

9,657.9
1,117.3
4,416.9
1,328.9
240.2
. 2,574.2

+ 8.7
+ 4.1
+ 8.1
+ 5.3
+ 5.3
+ 14.8

M I S S I S S I P P I * ..............................

. 1,484.5
995.2
322.0
82.4

+ 1.2
+ 0.5
+ 6.7
+ 11.8

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

Anniston-Gadsden . . . .
..............
Birmingham
Dothan ......................
M o b ile .......................
Montgomery ..............

Jacksonville
..............
M i a m i .......................
Orlando ....................
Pensacola .................
Tampa-St. Petersburg . .
Jackson ....................
Hattiesburg-Laurel-Meridian
N a t c h e z ....................

Am ount
(m illion $)

% Change
F irs t Half
1974

6,200.9
4,785.7
392.1
268.9
249.0
470.2
141.8

+ 7.1
+ 9.8
+ 3.5
+ 11.7
— 0.8
+ 0.6
+ 7.6

Alexandria-Lake Charles
Baton Rouge ...........
Lafayette-Iberia-Houma
New O r le a n s ...........

3,402.4
318.0
503.1
235.4
2,367.8

+ 6.7
+ 7.1
+ 11.7
+ 16.0
+ 3.0

Chattanooga
Knoxville .

3,930.4
777.7
598.5
2,673.0
151.0

+ 7.9
+ 17.7
+ 8.2
+ 6.7
+ 10.4

% Change
F irs t Half
1974
G EO R G IA

Augusta . .
Columbus
Macon . . .
Savannah
South Georgia
LO U ISIA N A *

Tri-Cities

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

NOTE: Figures shown are for trade and banking areas, which include several counties surrounding central cities.
Boundaries of some areas do not coincide with state lines.
♦Represents that portion of the state in the Sixth District.

124




A U G U S T 1974, M O N T H L Y R EV IEW

District m em ber banks expanded their loans a solid
7.5 percent du ring the first six m onths o f 1974. The
$2.0-billion net increase in loans reflected strong
dem an ds for bank funds, especially by businesses.
Even this large credit extension, however, did not
approach the extraordinary 13-percent pace w hich
banks set in the sam e m onths of 1973.
In seeking lendable funds to meet these tem ­
pered but still robust credit dem ands, m em ber
banks m ade increased use o f large negotiable C D 's
and n on dep o sit sources of funds. A s seen in the
chart, such liabilities at large banks reached $3.3
billion in June, surpassing the historically high levels
achieved the previous year. The strong increase in
C D 's reflected bankers' com petitive efforts to make
up for the relatively slo w grow th of dem and de­
posits and consum er savings deposits.
The co m binatio n o f strong borrow er dem and for
bank funds and sluggish grow th in the m ore tradi­
tional deposit sources of bank funds also placed u p ­
w ard pressure on bank loan rates, both nationally
and in the Southeast. The prim e rate, after declining
in February and M arch to 83A percent, increased in
eight rapid steps, begin n in g in late M arch, and
reached H V 2 percent in M ay. The prim e rate in­
creased further to 12 percent d u ring July.
W h ile total loan grow th at this region's banks
kept pace with the strong national expansion, the
co m p o sitio n of loan dem and differed. W h ile h ead­
lines focused on exceptional business loan grow th
at large banks nationally, District business loans
rem ained sluggish in the early m onths of the year.
Strong local dem an d for real estate loans, however,
took up the slack.
In April, though, District banks faced a surge
in com m ercial loan dem and not o nly from their
local custom ers, but also from national custom ers
w ho began draw in g heavily on previously c o m ­
mitted lines o f credit at regional banks. Business
loans accelerated at a seasonally adjusted 26-percent
annual rate before d ro p p in g back sharply in M a y
and June.
The April spillover from national business loan
dem and contributed to loan grow th prim arily in
large regional centers such as Atlanta, N e w Orleans,
Nashville, Tam pa, and Birm ingham . The table show s
that the grow th rate of total loans, though, was
equally strong in other trade areas such as Dothan,
C o lu m b u s, Baton Rouge, C hattanooga, and TriCities because of local consum er and real estate
dem ands. Also, agricultural lending in these areas
rebounded from last fall's substantial loan payoffs.
In contrast to the loan behavior, District bank
dem and deposits increased only 2.6 percent in the
first half o f 1974. Savings deposit grow th w as also
moderate. O th er tim e deposits, in contrast, ad ­
vanced a strong 10.1 percent, led by a $160-m illion
increase in consum e r four-year certificates through
M a y and the rapid bu ild -u p of large m oney market
C D 's. Bankers actively com peted for C D 's as a subFE D E R A L R ESER V E BANK O F ATLA N TA




S o u rce s o f Fu n d s

1973

Bil. $

1974

*32 large banks
**AII member banks

stitute for dem and deposits. The shift to C D 's was
enhanced by the Board of G overn ors' reduction of
the m arginal reserve requirement on C D 's from 11
percent to 8 percent last Decem ber.
After declin in g early this year, C D interest rates
rose rapidly b e gin n in g in M arch as banks sou ght
to attract funds to replace a large vo lu m e of C D 's
m aturing that m onth and to accom m odate the g ro w ­
ing April loan dem and. After rising to 11V4 per­
cent in M ay, short-term C D rates eased to 11 per­
cent by June. These rates surged upw ard again later
in the month.
In addition to the certificates of deposit, banks
also relied heavily on b orrow in gs both from the
Federal Reserve and from other banks in the Federal
funds market. Borrow ings from the Federal Reserve
Bank reached a high daily average of $251 m illion
in June. Net Federal funds purchases also shot up
to a M a y high of $971 m illion, boosted by country
banks that sharply reduced funds sales as they
sou ght to meet increased local loan dem ands.
N o t only were m em ber banks able to ac co m ­
m odate a large vo lu m e of new loans d u rin g the
first half of the year, but they also added to their
investments by $266 m illion. A lth o u gh h o ldin gs
of U. S. G overn m ent securities declined $5 m illion,
an unusual $271-m illion increase occurred prim arily
in state and m unicipal obligations. C oun try banks
were especially strong purchasers of tax-exempt
securities until April, w hen their h o ldings leveled
off.
In sum, Southeastern banks have provided funds
for strong local loan dem ands and also acco m ­
m odated national business loan custom ers w ho
faced unusual credit needs. H igh loan interest rates
reflected the increase in the dem and for bank credit,
but banks were able to meet the dem and principal­
ly through a record increase in large certificates of
deposit
C H A R L E S D . SALLEY
125

S i x t h

D i s t r i c t

S t a t i s t i c s

Seasonally Adjusted
(All data are indexes, unless indicated otherwise.)
L a te st M o n th
197 4

O ne
M onth
A go

Two
M o n th s
A go

One
Year
A go

S T D T IC
IXH IS R T

U n e m p lo y m e n t R a te 2
(P e rc e n t o f W o rk F o rce ) . .
Avg. W e e k ly H rs. in M fg . (H rs.)

IN C O M E A N D S P E N D IN G
M a n u f a c tu r in g

P a y ro lls

J une
M ay
M ay
M ay

179
215
289

. Ju n e
, Ju n e

L iv e s to c k
......................
In s ta lm e n t C re d it at B a n k s * / 1

,
.
.
,

679
6 25

200

175
173
188
17 9

172
2 03
218
203

168
1 14
23 9
1 84

668 r

6 87
643

132.6
118.5
115.6
106.5
112.4
113.5
112.5
129.0
109.0

129.7
118.1
116.1
102.9
113.6
117.4
113.5
127.7
108.5
121.9
112.9
128.0

Stone , C lay, a n d G la s s .

T ra n sp o rta tio n E q u ip m e n t

Ju n e
Ju n e
Ju n e
Ju n e
Ju n e
Ju n e
Ju n e
June
June
Ju n e
June
Ju n e
June
June
June
June
June
June
Ju n e
Ju n e
Ju n e
June
June
Ju n e
June

132.6
118.1
115.6
103.6

132.4
117.9
115.2
105.9

11 2 .8

112 .6

113.5
113.2
129.3

112 .6

1 1 1 .0
121.3
110.5
128.5
113.3
129.5
157.3

113.1
129.8
108.1
121.3

1 1 1 .0

1 2 1 .8

138.3
81.5

129.7
112.4
131.9
156.8
110.3
137.6
145.6
127.2
137.7
147.4
149.6
104.2
136.8
84.1

111.4
129.4
112.3
133.1
157.2
112.3
137.6
152.9
127.2
137.2
146.9
148.1
103.8
136.4
83.8

4.2

4.3

4.2

2.3
40.4

2.2

2.2

1.8

40.1

39.7
2 25
2 50

40.8
2 67
308
2 26
80
114
288.5
238 .8
185.5
281 .8
286 .8

1 1 1 .1
137.7
143.6
126.1
138.2
147.1
150.3

10 2.8

202

222

214
190
80

2 16
2 28
79

10 1

10 1

299.4
241 .9
189.9
298 .4
294.1

297 .0
243.4
190.0
304.5
293.0
204.5
156.0
323.5
361.3
205.9
186.4
229 .9
273 .9
310.6
468 .8
855.9
392.1

202.6
156.4
311.7
368.1
207.2
177.4
231.1
273.6
310 .9
472.7
865 .8
419 .9

200
86
1 04
300.0
247.7
191.5
301.7
291.9
226 .9
155.9
320.9
362.5
206.3
188.7
216.5
272.2
308.0
478 .9
835.0
416 .0

1 1 1 .8
128.8
152.9
115.1
133.8
145.2
124.5
135.3
144.1
144.1
99.0
131.5
84.0
3.7

2 2 2 .1
161.7
305.9
347 .6
199.6
190.6
207.0
231.0
283.3
435.9
778.1
453 .2

F I N A N C E A N D B A N K IN G
Loans*
. Ju n e
. Ju n e

2 76
259

2 74
257

272
254

2 10

234
21 8

. Ju n e
. Ju n e
. Ju n e

2 15
187
2 88

2 15
186
2 85

181
293

195
173
236

. June
. M ay

D e b it s*/ *

181
255 .4

177
193.1

175
21 7

1 68
61.8

.
.
.
.
.

121.4
117.3
123.3
128.0
81.8

120 .2
117.3
121.5
127.8
66.7

120.3
117.6
121.5
128.8
72.7

119.0
116.4
120.3
129.4
70.1

ALABAMA

EM PLOYM ENT

126




O ne
Year
Ago

June
June

4.1
41.1

4.1
40.6

4.1
40.5

4.0
4 1.4

June
June
June

25 3
20 5
254

251
206
260

249
2 45

214
18 6
2 05

June
M ay

191
244.5

185
169.1

182
175.6

180
213 .8

June
June
June
June
June

153.7
128.7
158.5
201 .7
98.8

152.7
128.4
157.7
198.7
99.1

152.5
128.2
157.2
215 .4
96.2

149.2
126 .9
153.5
204.7

June
June

3.5
40.5

3.6
40.1

3.4
39.7

2.7
40.9

June
June
June

315
24 7
31 2

309
24 6
3 01

306
24 0
311

263
224
270

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

20 2

M a n u f a c t u r in g Payrolls
F a rm C a s h R e c e ip t s .
EM PLOYM ENT
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 2
(P e rc e n t o f W o rk Fo rce) . .
Avg. W e e k ly H rs. in M fg. (H rs.)

10 2.8

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

G E O R G IA
IN C O M E
M a n u f a c tu rin g P a y r o l l s .................. J u n e
F a rm C a s h R e c e i p t s ......................... M a y

169
222 .0

1 67
180.7

163
220 .6

157
177.7

EM PLOYM ENT
N o n fa rm E m p l o y m e n t ......................J u n e
M a n u f a c tu rin g
............................. J u n e
......................J u n e
N o n m a n u f a c t u rin g
C o n s t r u c t i o n ............................. Ju n e
Fa rm E m p lo y m e n t
......................... J u n e
U n e m p lo y m e n t R a te 2
(P e rc e n t of W o rk F o r c e ) .............. J u n e
A vg. W e e k ly H rs. in M fg. (H rs.) . . . J u n e

128.9
111 .4
136.9
140.5
8 3.4

129.9
111 .9
138.1
145.3
92.7

130.0
137.9
146.2
85.9

127.2
113.4
133.6
140.6
80.9

4.5
40.1

5.1
39.9

4.8
39.8

3.9
40.5

269
1 96
3 28

266
1 96
3 27

269
1 86
364

232
182
264

15 8
162.1

157
170 .4

1 54
177.6

15 4
233 .8

116.0
103.8
118.6
85.0
66.4

117.2
105 .4
119.7
89.7

118.1
106.8
120.4
96.8
64.1

114.5
105.0
116.5

6.7
40.0

6.4
40.0

6.2
39.4

6.4
41.6

246
1 89
235

255
189
229

249
189
2 25

214
173
187

11 2 .6

F IN A N C E A N D B A N K IN G
M e m b e r B a n k L o a n s ......................... J u n e
M e m b e r B a n k D e p o s i t s .................. J u n e
B a n k D e b i t s * * .................................June
L O U IS IA N A
IN C O M E
M a n u f a c t u r in g P a y ro lls
.................. Ju n e
F a rm C a s h R e c e i p t s ......................... M a y
EM PLOYM ENT
N o n fa rm E m p l o y m e n t ......................J u n e
M a n u f a c tu rin g
............................. J une
N o n m a n u f a c t u r i n g ......................... J u n e
C o n s t r u c t i o n ............................. J u n e
F a rm E m p l o y m e n t ............................. J u n e
U n e m p lo y m e n t R a te 2
(P e rc e n t of W o rk F o r c e ) .............. J u n e
Avg. W e e k ly H rs. in M fg. (H rs.) . . . J u n e

68.1

86.1
75.7

F IN A N C E A N D B A N K IN G
M e m b e r B a n k L o a n s * ......................J u n e
M e m b e r B a n k D e p o s i t s * .................. J u n e
B a n k D e b i t s * / * * .................................J u n e
M IS S IS S IP P I

IN C O M E

N o n fa rm E m p lo y m e n t
M a n u f a c tu r in g
. .
N o n m a n u f a c t u r in g

TWO
M o n th s
A go

IN C O M E
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.

S ta te a n d L o ca l G o v e rn m e n t
F a rm E m p l o y m e n t .........................
U n e m p lo y m e n t R a te 2
(P e rc e n t o f W o r k Fo rce ) . . . . . J u n e
In s u r e d U n e m p lo y m e n t
(P e rc e n t of Cov. E m p . ) .............. . J u n e
Avg. W e e k ly H rs. in M fg. (H rs.) . . . J u n e
. June
. June
A ll o t h e r ..............
. Ju n e
C otto n C o n s u m p t io n * *
. M ay
Pe trole u m P r o d u c t io n *
. Ju n e
. Feb.
. Feb.
. Feb.
. Feb.
. Feb.
. Feb.
P r in t in g a n d P u b lis h in g
. Feb.
. Feb.
. Feb.
. Feb.
. Feb.
F u rn itu re a n d F ix tu re s
Stone , C lay, a n d G la s s
. Feb.
. Feb.
. Feb.
N o n e le ctrica l M a c h in e r y .
. Feb.
Electrica l M a c h in e r y
. .
. Feb.
T ra n sp o rta tio n E q u ip m e n t
. Feb.

Bank

One
M on th
Ago

661
57 0

5 79 r

E M P L O Y M E N T A N D P R O D U C T IO N

P a p e r .........................
P r in t in g a n d P u b lis h in g

L a te st M o n th
1 97 4

IN C O M E
M a n u f a c t u r in g P a y r o l l s .................. J u n e
Fa rm C a s h R e c e i p t s ......................... M a y

202
191.9

198
197.1

191
2 9 0 .4

17 2
117.8

EM PLOYM ENT
Ju n e
Ju n e
Ju n e
Ju n e
June

. June
. June

129.4
130.6
128.9
127.5
74.0

129.6
130.2
129.4
132.4
78.8

129.5
130.0
129.3
134.3
81.3

126.0
130.2
124.1
129.1
80.9

A U G U S T 1974, M O N T H L Y R E V IE W

One
M onth
Ago

L a te st M o n t h
1974
U n e m p lo y m e n t R a te 2
(P e rc e n t o f W o rk F o rce) . .
Avg. W e e k ly Hre. in M fg. (H rs.)

Two
M o n th s
Ago

O n*
Year
Ago

La te st M o n t h
1974

One
M on th
Ago

TW o
M o n th s
Ago

One
Year
Ago

EMPLOYMENT
Ju n e
J une

3.9
39.8

M e m b e r B a n k L o a n s * ......................J une
M e m b e r B a n k D e p o s i t s * .................. J u n e
B a n k D e b i t s * / * * ................................ J u n e

265
2 19
2 56

3.8
40.7

June
June
Ju n e
June
Ju n e

129.0
119.5
134.5
130.7
87.2

128.1
117.7
133.9
136.0
93.6

128.7
118.6
134.3
140.1
90.5

125.8
118.8
129.7
132.0
92.6

June
June

3.5
40.5

3.6
40.2

3.5
39.4

3.0
40.3

M e m b e r B a n k L o a n s* . . . . . . . June
M e m b e r B a n k D e p o s it s * . . . . . . J u n e
B a n k D e b its*/ *

2 65

261
20 3
274

2 58
2 03
2 65

219
1 82
178

F IN A N C E A N D B A N K IN G
268

25 7
21 6
26 0

21
2
2 56

228
195
219

U n e m p lo y m e n t R a te 2
Avg. W e e k ly H rs. in M fg . (H rs.)

TEN N ESSEE
F IN A N C E A N D B A N K IN G
IN C O M E
Ju n e
M ay

182
277.2

177
186.0

175
205.3

170
252.3

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

* F o r S ix t h D ist ric t are a only; oth e r to ta ls fo r en tire s ix sta te s

20 1
2 64

N.A. N o t a v a ila b le

t P re lim in a ry data

Note: Indexes for bank debits, construction contracts, cotton consumption, employment, farm cash receipts, loans, petroleum
production, and payrolls: 1967 = 100. All other indexes: 1957-59 = 100.
S o u rc e s :
M a n u f a c tu r in g p ro d u ctio n e stim a te d b y t h is B a n k ; non farm , m fg. a n d non m fg. em p., m fg. p a y ro lls a n d hou rs, a n d unem p., U.S. Dept, of L a b o r a n d c o o p e ra tin g
state a g e n c ie s; cotto n c o n su m p t io n , U.S. B u re a u of C e n s u s; c o n stru c tio n c ontrac ts, F. W. D o d g e Div., M c G ra w -H ill In fo rm a tio n S y s t e m s Co.; petrol, prod., U.S. B u re a u of
M in e s; fa rm c a sh re c e ip ts a n d fa rm em p., U .S.D.A. O th er in d e x e s b a se d on data colle c te d b y t h is B a n k . A ll in d e x e s c a lc u la te d b y t h is B an k .
‘ Data b e n c h m a rk e d to J u n e 197 1 R e p ort of C o nd itio n.
U n e m p l o y m e n t rate s fo r all D ist ric t St a t e s except F lo rid a h a v e been e stim a te d u s in g new t e c h n iq u e s d e ve lo p e d b y th e U. S. Dept, of Labor. N e w se a so n a l fa c to rs hav e
been d e ve lo p e d fo r all s ix D ist r ic t States. T h e se new se as. adj. rates are n ot c o m p a ra b le w ith p re v io u s ly p u b lish e d u nem p . rates.

D e b i t s

t o

D e m a n d

D e p o s i t

A c c o u n t s

Insured Commercial Banks in the Sixth District

(In Thousands of Dollars)
P e rc e n t C h a n g e

P e rc e n t C h a n g e

June
1 97 4

M ay
197 4

June
1 97 3

Year
to
June
date
1 97 4 6 m os.
1 97 4
fro m
fro m
June
197 3
1973

M ay
1 97 4

S T A N D A R D M E T R O P O L IT A N
S T A T IS T I C A L A R E A S 2
B irm in g h a m
. . ..
G a d sd e n
. . . .
H u n t sv ille . . . .
M o b ile
..............
M o n t g o m e ry . . .
T u s c a lo o sa
. . .

3 6 0 ,988
1,252,576
650 ,987
242 ,836

4,79 0,846
112,073
4 0 3 ,859
1,321,131
730 ,704
260 ,331

3,323,085
100,427
330 ,191
1,035,244
5 7 7 ,406
21 0 ,117

-

7

+ 13
+ 16

842 ,355
459,651

84 3 ,829
45 3 ,292

716 ,103
34 7 ,569

+

0
1

+ 18
+32

+ 13

1,839,566
343 ,831
2 5 2 ,896
4,91 7,529

1,976,033
40 0 ,6 7 8
282 ,645
5,605,487

1,776,008
3 0 8 ,846
2 4 1 ,649
3,641,502

- 7
-1 4

+
+ 11
+ 5
+35

+ 11
+25
+ 15
+41

491 ,293
7 ,208,788
1,558,489
51 1 ,860
538 ,703
73 4 ,797
. 4,09 6,729
. 1,218,065

4 6 6 ,367
7,517,573
1,619,776
530 ,749
592 ,722
1,009,132
4,28 7,075
1,352,458

4 4 6 ,998
6 ,41 8,014
1,473,773
432 ,957
502,901
7 6 3 ,134
3,81 2,678
1,141,515

+ 5
- 4
- 4
- 4
- 9
-2 7
- 4

10

+10

12

7

+17
+ 12
+14
+ 18
+ 9
+ 11
+ 11

20 7 ,486
18,999,103
591,271
47 4 ,575
774 ,598
625,881

2 1 9 ,880
19,711,332
6 7 4 ,399
518 ,696
895 ,095
64 5 ,4 0 4

1 94,594
15,1 84,118
496,861
4 0 6 ,285
515,173
504,621

+
+25
+ 19
+ 17
+50
+24

+ 12
+32
+26
+20
+52
+16

A le x a n d ria
B a to n R o u g e
. . .
Lafaye tte
. . . .
L a k e C h a r le s
. .
New O r le a n s
. . .

2 7 1 ,428
1,784,110
311 ,731
24 7 ,700
4,852,841

295 ,841
1,799,235
325 ,521
2 8 0 ,107
5,307,890

22 5 ,932
1,295,321
25 4 ,3 0 4

+20

+21
+36
+19

4,086,837

-

9

+38
+23
+16
+ 19

B ilo x i-G u lfp o rt
Jackson . . .

26 7 ,387
1,560,047

2 6 0 ,523
1,78 4,184

268 ,1 2 6
1,390,882

+ 3
-1 3

- 0
+12

+ 1
+22

C h a tta n o o g a . . . .
K n o x v i l l e ..............
N a s h v i l l e ..............

1,308,253
1,929,050
3,903,072

1,53 0,700
2,06 9,166
4 ,08 0,654

1,210,253
846 ,598
3,14 1,170

OTHER C EN T ER S
..............
A n n is to n

118,532

B a rto w -L ake lan d W in te r H ave n
D a y to n a B e a c h
Ft. Lau d e rd a le H o lyw o o d
. . .
Ft. M y e r s . . . .
G a in e s v ille
. . .
J a c k s o n v ille . . .
M e lb o u rn e T itu sv ille -C o c o a
M ia m 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 se e
. . .
Ta m p a -St. Pete
W. P a lm B e a c h

10 0 ,0 21

.

.

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

June
197 4

212,866

-

9

-1 1
-1 1
-

5

-1 1

-1 1
-1 2

-1 0
-

6
4

-1 2
- 9
-1 3
- 3
-

8
1
4

-1 2

+31
- 0
+ 9

+21

+
+
+
+
+
+
+

18
7

+30
+ 8
+ 18
+24
+ 14
+27

+22

+20
+17

1 5 + 8
+21
7 +128 +107
4
+24
+27

6+7+7

M ay
197 4

June
1 97 3

M ay
1974

June
197 3

196,279
69,2 15

2 1 4 ,468
81,271

175,024
71,1 48

- 8
-1 5

-

3

+27
+13

210,668
90,5 5 4
197,052
46,665
1,006,707
2,05 1,712

225 ,108
9 6,5 98
196 ,724
5 4,7 18
1,090,277
2,139,985

168,488
7 0,2 10
194,952
4 0,5 42
9 8 8 ,644
1,808,967

- 6
- 6
+ 0
-1 5
- 8
- 4

+25
+29
+ 1
+15
+ 2
+ 13

+17
+53
+ 3
+53
+ 6
+18

159,399
106,463
185,923
24,9 26
145,385
81,750
60,4 47
59,4 70
145,450
108 ,582

169 ,474
104 ,639
192 ,799
23,9 52
151,897
91,103
45,8 69
55,351
161,607
113,446

162,051
96,591
179,908
22,6 67
126 ,714
6 5,9 19
47,5 22
67,223
139 ,004
94,5 83

- 6
+ 2
- 4
+ 4
- 4

-

+ 6
+ 12
+ 5
+16
+ 19
+26
+23

.
.
.
.
.
,

15,822
12,976
84,5 0 9
61,6 06
26,081
39,9 0 4

18,172
15,154
100,067
70,9 88
26,9 55
44,407

16,546
10,882
77,0 54
53,163
25,4 72
3 8,5 04

. . .
. .
. . .
.

147,266
79,7 95
124,962
55,8 12

144 ,418
9 2,9 03
135,705
60,895

133,233
67,402
113 ,730
5 1,2 80

+
-1
-

. .
. . .
. . .

149,798
75,8 86
66,4 70

168,036
93,843
51,0 14

139,563
67,691
48,0 19

-1 1

+

-1 9
+30

+ 12
+38

+ 6
+25
+31

B risto l
. . . .
. .
J o h n so n C ity
. .
K in g sp o rt
. . .

135,088
155,694
277 ,1 9 0

146,255
181 ,774
3 0 3 ,630

114,982
166 ,638
254 ,935

- 8
-1 4
- 9

+ 17
- 7
+ 9

+ 1
+ 7
+ 14

. . . . 8 4 ,5 09,559

9 0 ,6 62,834

71,4 94,120

-

7

+ 18

+23

10,623,567
28,2 87,351
26 ,6 0 1 ,4 2 6
9 ,58 0,394
3,64 8,913
11,921,183

8,040,573
2 4,4 59,076
20,8 7 7 ,6 0 9
7 ,28 4,519
2 ,99 4,069
7 ,83 8,274

- 9
- 4
- 6
- 7
- 8
-1 5

+21
+ 12
+20
+22
+ 12

+24
+ 17
+27

D o th a n
S e lm a

4,352,202

Year
to
date
6 m os.
1974
fro m
197 3

Ju n e
1974
fro m

. .

. . . .
. . . .

B rad e n to n . . .
M o n ro e C o u n ty
O c a l a ..............
St. A u g u st in e
St. P e te rsb u rg .
Tam pa
. . . .

.
.
.
.
.

.
.
.
.
.

Ath e n s
. . . .
B ru n s w ic k . . . .
D alton
. . . .
Elb erton
. . .
G a in e s v ille
. .
G riffin
. . . .
L a G ra n g e
. . .
New nan . . . .
R o m e ..............
V a ld o sta
. . .

.
.
.
.
.
.
.
.
.

.
.
.
.
.
.
.
.
.

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

.
.
.
.
.
.

.
. .
.
.
.
.

H a ttie s b u rg
.
Laurel
. . . .
M e rid ia n
. .
N a tc h e z
. .
P a sc a g o u la M o s s P o in t
V ic k s b u r g . .
Y a zo o C ity
.

stric t

Total

A la b a m a
.
F lorid a
. .
G eorgia
.
L o u is ia n a 1
M is s is s ip p i'
T e n n e sse e1

.
.
.
.
.

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

. . 9,69 0,386
. . 27,2 74,092
25,1 35,230
. 8 ,86 5,699
. . 3,363,521
. . 10,180,631

-1 0
+32
+ 7

-1 0
-

4

-1 3
-1 4
-1 6
-1 3
- 3

-1 0

+ 12

+ 10
+ 3
+ 1C
+15
+24
+27

-1 2

-1 0

+ 5
+15

+ 11
+ 13

- 4
+ 1S
+1C
+ 16
+ 2
+ 4

2

+ 11

4

+ 1S
+ 1C
+ 9

8
8

+30

+10
+23
+14

+20
+ 2
+ 10
+ 11
+13
+13
+ 10

+21
+ 17
+35

‘D istric t p ortion only.
2C o n f o r m s to S M S A d e fin it io n s a s of D e c e m b e r 31, 1972.
r-R e v ise d
F ig u r e s fo r so m e a re a s d iffe r s lig h t ly fro m p re lim in a ry fig u re s p u b lish e d in " B a n k D e b its a n d D e p o sit T u rn o v e r b y B o a rd o f G o v e rn o rs of the Fed e ral R e se rv e Sy stem .

FE D ER A L R ES ER V E BAN K O F A TLA N T A




127

D i s t r i c t

B u s i n e s s

C o n d i t i o n s

19S7-B 9 = 100

— Stat. Adj.

I I I I I I I I I I I I II I II I II I I I I I I I I II II II I
1972
1973
1974

I I I I II I It I I I I I I I I I I I II I I .......... I I I I I
1972
1973
1974

*Seas. adj. figure; not an index
♦♦Unemployment rates are based on new estimating techniques and concepts and are
not comparable with earlier data.
Latest plotting: June, except mfg. production, Feb., and farm cash receipts, May.

Business co n dition s in the Southeast have stabilized at m idsum m er, w ith so m e sectors d isp la y in g im prove­
ment. General labor m arket condition s change d little, but som e indicators o f m anu facturin g activity w ere
positive. C o n su m e r sp e n d in g is h o ld in g up reasonably w ell, w hile grow th in ban k le n d in g is m oderate.
Total value o f construction contracts declined slightly. Hot, dry w eather reduced cro p prospects and pushed
up farm prices in July.
Total le n d in g by m em ber banks in June and early
July ch anged no m ore than usual.
M a jo r banks
posted a 12-percent prim e lending rate early in July
and m aintained it th rou ghou t the rest of the month.
C o n su m e r time and savings deposits were w eak
over the m idyear interest-crediting and reinvest­
m ent date. A t the sam e time, m any large banks are
letting som e m oney market C D 's run off rather
than roll them over at current high rates. D isco u n t
activity receded du ring early July but returned to
previous peak levels later in the month.
G ro w th in consum er sp e n d in g has co m e m ainly
from price increases. Bank instalm ent len ding to
consum ers w as up in June, indeed m ore than in any
previous m onth in 1974, although this gain w as
o nly one half the average m onth last year. The
o nly w eakness w as again centered in auto loans,
w hile grow th of loans outstanding in other cate­
gories w as near normal. A u to sales have turned up
but are still substantially belo w the com parable
year-ago month.
N on farm e m p lo ym e n t rem ained abou t unchanged
in June. Louisiana and M ississip p i had substantial
increases in u nem p loym en t rates. Factory hours
rose; m anufacturing payrolls, boosted by new c o n ­
tract settlements and higher m inim um wages, in­
creased sharply. C ollective bargaining activity is
N ote:

D ata on w h ic h s t a t e m e n t s a r e b a s e d

Digitized1for FRASER
28


h a v e b e en a d ju s t e d

expected to remain heavy the rest o f this year.
Business failures have risen to w ell above year-ago
levels, with the increase centered in retail and c o n ­
struction firms.
There w as little ch an ge in the value o f residential
construction contracts in June, but w eakness in
the nonresidential sector bro u gh t a declin e in value
of total contracts. The value o f residential contracts
rem ained at levels recorded in M a y but w as 30
percent b e lo w year-ago levels. M o rtg ag e
rates
continued to rise. A paucity of large contracts and
continued declines in engineering construction ac­
counted for the w eakness in the nonresidential
sector.
Prices o f farm c o m m o d itie s registered further d e ­
clines in June, but brisk recoveries w ere evident in
July, particularly for h o gs and fed cattle.
Prices
of corn and soybeans have also advanced sharply,
am id reports that dry w eather has drastically
reduced yield prospects. W ith e rin g pastures placed
cattlemen under pressure in som e areas. Prices for
the new tob acco crop are higher than a year ago.
Farm cash receipts continued to lead the year-ago
figure but by a progressively shrin king margin.
Farm credit agencies report increases in loans from
both m onth-earlier and year-ago levels.
w h e n e v e r p o s s ib le to e lim in a t e s e a s o n a l in f lu e n c e s .

A U G U S T 1974, M O N T H L Y R EV IEW