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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
