WP060691

PER CAPITA INCOMES IN SOUTH CAROLINA: CONVERGING, DIVERGING OR

STANDING STILL?•

by

Philip Maxwell,Visiting International Scholar, Clemson University; James C. Hite, Alumni Professor, Agricultural Economics and Rural Sociology and Senior Fellow,

Strom Thurmond Institute; and Brett Dalton, Research Associate, Strom Thurmond Institute.

August 1991

*We wish to thank Bruce Yandle, Director, Strom Thurmond Institute and Mark Henry, Professor

Agricultural Economics and Rural Sociology for their comments on an earlier version of this paper.

INTRODUCTION

Between 1929 and 1975 regional per capita incomes converged notably in the United States. During this time the average incomes of the 12 southeastern states1rose from just over 50 percent to nearly 85 percent of the national mean. In 1929 South Carolina was the poorest state with mean incomes only 38 percent of the U.S. average. It was not until 1948 that the state's per capita income levels reached 50 percent of the national mean. By 1976, however, the South Carolina's mean income had risen to just in excess of 77 percent of the U.S. average (see Figure 1).

This dramatic change came about particularly because of outmigration of displaced rural blacks to northern and mid-west states and a process of rural industrialization in which the proportion of South Carolina's employment in manufacturing (particularly in the textile industry) made it the second most industrialized state in the nation. By 1969 30 percent of the state's population was employed in manufacturing, and agricul­tural employment had already fallen to just over 6 percent. Manufacturing wages were not high, but they exceeded those on farms, and per capita incomes in the state tended to increase at a faster rate than nationally.

Figure 1 Per Capita Personal Incomes-South Carolina,

the Southeast and the U.S. 1976-1988

120

Percent of 110national

average 100

90

80

70

60

50

40 1930 1940 1950 1960

Year

1These are Alabama, Arkansas, Florida, Georgia, Kentucky, Louisiana, Mississippi, North Carolina, South Carolina, Tennessee, Virginia and West Virginia.

states

1970 1980 1990

1

Since the mid-1970s regional per capita incomes in the United States have begun to diverge again. Several commentators have considered this phenomenon in recent papers [(e.g. Ray andRittenoure (1987),Coughlin andMandelbaum(1988, 1989),Amos (1988, 1989) and Rowley, Redmand and Angle (1991)]. In doing so they have suggested a range of possible explanations focusing on the changing structure of the population, theories of long wave cycles and so on.

Ascanbeseenfrom Table 1 and Figure l,meanincomesinSouthCarolina oscillated between the 76.3 and 78.4 percent of the national mean between 1976 and 1988. There was, therefore, little significant change in the state's mean income relative to the national average during this period.

By contrast, per capita personal incomes in the 12 southeastern states rose slowly as a percentage of the national mean. On the surface, therefore, it might appear that South Carolina's economic re-emergence has stalled. It should be noted, however, that per capita incomes in the state have been rising at about the same rate as nationally over this period.

Of course, mean income levels provide only one part of the picture of the general welfare of any state. It must also be remembered that the cost of living in the southern states is less than in much of the rest of the U.S. Using estimates from Fournier and Rasmussen (1986) for 1980, cost of living differences appeared to increase real per capita incomes in South Carolina from about 77 to 86 percent of the country average.

Table 1 Mean Per Capita Personal Incomes in South Carolina

the Southeast and the United States 1976-1988.

Year Mean Per Caeita Personal Incomes South Carolina/ South Carolina/ S. Carolina Southeast U.S. U.S. Southeast

1976 5127 5623 6651 77.1 91.1 1977 5562 6161 7294 76.3 90.3 1978 6057 6663 7772 77.9 90.9 1979 6719 7399 8651 77.7 90.8 1980 7389 8148 9494 77.8 90.7 1981 8158 9104 10544 77.4 89.6 1982 8605 9659 11113 77.4 89.1 1983 9168 10215 11687 78.4 89.8 1984 10157 11367 13114 77.5 89.4 1985 10738 12056 13908 77.2 89.1 1986 11313 12695 14608 77.4 89.1 1987 12027 13499 15482 77.7 89.1 1988 12764 14331 16444 77.6 89.1

Source: South Carolina Statistical Abstract (several issues).

2

The size of South Carolina's output and population also have been growing at rates faster than the national average. Between 1976 and 1988 the state's population rose from 2,773,000 to 3,493,000-an increase of 26 percent. The population of the United States rose by only 15.4 percent over the same period. Similarly, employment has been growing at a faster rate than nationally-by 37.7 percent in South Carolina as opposed to 29.5 percent nationally between 1976 and 1988.

It is also instructive to reflect on mean income per head in South Carolina from an international perspective. According to the World Bank (1990), mean per capita incomes2 in the U.S. placed the country fourth on the "world league" table out of 121 reporting countries (see Table 2). If considered as a separate economy, South Carolina would rank thirteenth on this table--above several affluent countries such as, the Netherlands, Belgium, Italy, the United Kingdom, Australia and New Zealand. This picture would seem likely to improve if we could compute a league table which took account of costs of living.

Table 2 Mean Per Capita Incomes in South Carolina in an International Context 1988

Country GDP per Capita ($U.S.) Rank

Switzerland 27500 1 Japan 21020 2 Norway 19990 3 United States 19840 4 Sweden 19300 5 Finland 18590 6 Germany (West) 18480 7 Denmark 18450 8 Canada 16960 9 France 16090 10 United Arab Emirates 15770 11 Austria 15470 12 South Carolina 15276 13 Netherlands 14520 14 Belgium 14490 15 Kuwait 13400 16 Italy 13330 17 United Kingdom 12810 18 Australia 12340 19 New Zealand 10000 20

Source: World Bank, World Development Report 1990, p. 179.

21n this exercise we use GDP per capita rather than personal income per capita and assume that GDP per capita in South Carolina in 1988 was 77.6 percent of the U.S. average.

3

While South Carolina's recent economic development compared to the rest of the country is an interesting topic in its own right, it provides only the background for this paper. Our interest is to examine recent movements of personal per capita income within the state-particularly at county level. In the next section we consider the extent of these movements using some simple measures of income convergence to assist our analysis. We then seek explanations for some of the changes which have been taking place in the third section. The final part of the paper contains some concluding remarks.

INCOMEDATAATCOUNTYLEVEL

Since our interest is in recent income movements in the 46 counties within the state, we must consider mean personal income levels at a number of points since the mid-1970s. Mean personal income per capita data for four years-1976, 1980, 1984 and 1988-appear in Table 3. These data are stated as a percentage of the state's mean per capita level of personal income for each year.

One way to analyze these data is to use a categorization suggested by Coughlin and Mandelbaum (1988). They identified the U.S. states in terms of whether their mean per capita incomes, in relation to an unweighted national mean, were downwardly diverg­ing (DD), upwardly converging (UC), downwardly converging (DC), or upwardly diverging (UD).3 States where no significant change (NSC) had occurred in per capita incomes were also included in their taxonomy. Inclusion of this category requires an arbitrary judgment about what constitutes a significant change. While there is some question about the validity of such measurements about an unweighted mean, this approach is promising in its potential for enhancing understanding of some of the processes which drive relative changes. We have, therefore, applied it to the 46 counties of South Carolina between 1976 and 1988, using the state's personal income per capita as our reference mean. The initial results are shown in the final column of Table 3 and are mapped in Figure 2. We define the no significant change category as applying to those regions where there was less than a two percent movement in household per capita income relative to the state mean between 1976 and 1988.

As can be seen from Table 4, over the period 21 counties were diverging from the mean while 15 converged. Ten counties showed no significant change. A possible

3 States with downwardly diverging incomes initially had mean incomes below the national mean. At the end of the period these incomes were even less in percentage terms than they had been at the beginning. States with upwardly converging mean incomes began with their means below the national mean but moved towards the national mean over the period of study. Downwardly converging states had mean incomes initially above the national mean and moved down towards it. Upwardly diverging states began with mean incomes above the national mean. Their incomes became greater as a percentage of the national mean over the study period.

4

Table 3 Mean Per Capita Personal Incomes in South Carolina Counties Relative to State

and National Averages-1976, 1980, 1984 and 1988

Percentage of State Mean

County 1976 1980 1984 1988 Move't 1976-88

Abbeville 89.1 83.5 83 85.4 DD Aiken 113.4 107.6 113.4 105.9 DC Allendale 59.9 63.2 66.8 78 UC Anderson 103.9 99.1 97.7 97.2 DD Bamberg 74.8 69.5 72.2 70.3 DD Barnwell 86.4 89.1 94.1 92 UC Beaufort 113.9 118.1 115.7 119 UD Berkeley 78.4 87.1 87 86 UC Calhoun 90.5 86.5 93.1 88.9 NSC Charleston 108.3 106.7 105.7 102.6 DC Cherokee 91.3 98.6 98.2 106.4 UD Chester 93.2 97.3 97.6 82.7 DD Chesterfield 84.7 84.7 89.2 86.5 NSC Clarendon 61.7 64 69.6 70.4 UC Colleton 76.2 76.8 75.5 78.1 NSC Darlington 90 85.1 83.9 83.5 DD Dillon 73.3 67.4 68.4 69.6 DD Dorchester 94.5 100.2 96.5 94.1 NSC Edgefield 87.3 83 76.5 79.7 DD Fairfield 86.4 78.6 78.9 89.3 UC Florence 97.2 93.8 95 93.6 DD Georgetown 88 88.5 85.8 86.7 NSC Greenville 114.9 117.4 116.6 119.3 UD Greenwood 104.1 105 102.3 103.5 NSC Hampton 84.9 83 83.7 83.2 NSC Horry 94.3 98.5 99 100.1 UC Jasper 67 76.9 80.4 77.9 UC Kershaw 104.2 106.9 102.9 98.8 DC Lancaster 91.8 91.7 90 89.1 DD Laurens 98.2 98.3 95.5 98.8 NSC Lee 72 63.2 75.9 65.3 DD Lexington 104.5 115.6 115.8 115.8 UD McCormick 71.7 72.4 78.2 85.7 UC Marion 86.7 77 78 76.1 DD Marlboro 74 67.8 67.1 67.9 DD Newberry 105 106.8 107.1 97.6 DC Oconee 94.6 100.1 101.7 105.6 UD Orangeburg 82.9 81.9 81.5 82.3 NSC Pickens 97 101.7 101.2 100.2 UC Richland 120.6 113.7 113.3 113.2 DC Saluda 77.5 84.7 84.1 84.8 UC Spartanburg 108.2 107.3 106.4 109.4 NSC Sumter 86.4 83.1 82.5 82.4 DD Union 93.2 88 84.3 82.7 DD Williamsburg 72.8 66.2 67.7 70.1 DD York 103 110.7 113.1 112.8 UD

5

FIGURE 2

~

County Average Income Relal:ive to Stal:e Average

1976-1988

$+l+!+l Downwardly Convergent

Downwardly Divergent

Upwardly Divergent

(":~":~":~":~i Upwardly Convergent

.___~I No Signiticsrit Chsrige

implication of this observation is that the per capita personal incomes of the state's counties were tending to diverge from the mean. Assessing whether this has been so requires allowance to be made for the contributions of counties according to their respective populations.

Table 4 Summary of Changes in Household Income Per Capita

South Carolina Counties 1976-1988

Relative Movement 1976-86

No significant change (NSC) 10 Upwardly diverging (UD) 6 Downwardly converging (DC) 5 Upwardly converging (UC) 10 Downwardly diverging (DD) 15

Total Counties 46

6

One way to measure this is to compute values of the weighted mean deviation (Mw) for all counties over an extended period. This is a measure of the extent of absolute variation ofmean county incomes around the state mean, taking account of the different populations of each county.

The formula for Mw is

where yi is the per capita income of the i th county, y is the per capita income of the state, and fi/n is the proportion of the state's population which resides in the ith county. A falling value of Mw indicates convergence of incomes while a rising value suggests income divergence. A useful property of Mw is that it is additively decomposable. Hence the contributions of counties diverging and converging from the mean can be easily identified.

We estimated values for Mw annually between 1969 and 1988. These are plotted in Figure 3. After falling by about 25 percent between 1969 and 197 4, M w remained stable until 1980. It rose slowly between 1980 and 1985 and then became stable once more. While it is clear that there was an upward trend in Mw in the counties of South Carolina between 1976 and 1988, the trend was very gradual and disappears in the last few observations plotted.

Figure 3 Mw Estimates of Personal Income Per Head

of South Carolina Counties 1969-1988

13

MW \ 12

.............I\11

\ )......._10

) "'-' I

V" 9

8

7

6

5 1965 1970 1975 1980 1985 1990

7

SOME FURTHER ANALYSIS

Some appreciation of trends towards convergence or divergence of county per capita incomes may be uncovered by an assessment of the economic structure of regions. A useful starting point is to appeal to an accepted typology of such regions. One attempt to conduct this exercise for counties in the United States has been undertaken by researchers at the United States Department of Agriculture. [(Ross and Green(1985), Bender et al. (1985) and Hady and Ross (1990)]. The USDA system initially classifies counties according to whether they are metropolitan or non-metropolitan. It then identifies non-metro counties as farming-dependent, manufacturing-dependent, mining-dependent, government-dependent, federal lands, retirement, poverty or unclassified. (A brief description of this classification appears in Appendix A.) Categorizations are not mutually exclusive, but as we shall see in the next diagram, they can be made that way by appropriate combination of characteristics.

Details of the USDA classification for the 46 South Carolina counties also appear in Appendix A. Several points stand out.

(i) There is the relatively large number of counties defined as metro­politan-12 of 46. Four of these are in the Greenville-Spartanburg­Anderson area, three are in and around Charleston and two are in the Columbia area. The remaining three are Florence, York (which borders Charlotte) and Aiken (which borders Augusta). To an outsider observing a state with three medium size cities-one on the coast, one in mid-state and one in the upstate-this seems a rather liberal definition of the term "metropolitan."

(ii) The state had no farming-dependent or mining-dependent coun­ties in 1986.

(iii) Twenty-three counties were manufacturing-dependent. Since sev­eral of the so-called metropolitan counties also have significant manufacturing activity, the state's commitment to manufacturing stands out.

(iv) Almost one third of the non-metropolitan counties (12 of 34) were poverty counties.

(v) Almost half of the non-metropolitan counties were classified in more than one way.

A summary of this classification appears in Figure 4.

8

26.09%

El Metropolitan

11111 Manufacturing

6.52?o rfil1 Manufacturing & Poverty

~ Poverty

D Government

1111 Retirement

~ Retirement & Other

El Other Mixed

E'.J Unclassified

Figure 4 A Classification of South Carolina Counties

4 .35?o 4.35%

34. 78%

The relative movements of per capita incomes in each of the county groupings are reported in Table 5. The changing population shares of each of the county types also appear in this table. We have noted already that population growth in the state was substantially higher than the U.S. average between 1976 and 1988. Against this background several points can be made.

First, even though the proportion of the population residing in the so-called metropolitan counties grew by 1.6 percent, per capita incomes in these 12 counties relative to the state average hardly moved at all. Conversely, while the non-metropoli­tan population declined in percentage terms, their per capita incomes-relative to the state mean-also remained remarkably constant at around 89 percent of the state mean. Since South Carolina's per capita income relative to the national average also hardly moved, county incomes in a general sense do seem to have been standing still.

Within the metropolitan counties, population shares changed mainly in the seven counties outside of, or bordering, the three main areas, i.e., Greenville-Spartanburg, Charleston and Columbia. There was an upward divergence of incomes from the mean in Greenville-Spartanburg, and downward convergence in the other two centers. Because of these movements Greenville-Spartanburg apparently edged ahead of Co­lumbia as the most affluent part of the state. In the seven other metro counties, mean

9

personal incomes moved marginally upward from just below to just above the state average.

Among the non-metropolitan counties, incomes of the manufacturing-dependent group changed little-staying slightly above 90 percent in both 1976 and 1988. The percentage of population in these rural counties did, however, fall. Those four manufacturing counties, also classified as poverty counties, did comparatively worse than the others with mean incomes falling to around 70 percent of the state mean.

The five poverty counties which were not manufacturing-dependent experienced little change in their incomes. What is clear is that there were nine poor counties in South Carolina whose mean incomes averaged only about 70 percent of the state mean or less than 55 percent of the national mean. As a group these counties changed little between 1976 and 1988. Their poverty remains apparently endemic. During this era the population of these counties grew marginally but their share of the state's total population fell from 7.4 percent in 1976 to 6.6 percent in 1988.

The four retirement counties provide some contrast. Their populations grew and so did their average incomes. Retirees might intuitively be expected to reduce the

Table 5 Movement of Per Capita Incomes by Type of County-South Carolina 1976 -1988

Population share ( percent )

Income as% state mean Change

..

Region Type No. 1976 1988 1976 1988 1976-88

Metropolitan of which 12 58.9 60.5 107.5 107.6 NSC Greenville-Spartanburg 2 15.9 15.2 112.0 116.9 UD Richland-Lexington 2 12.9 13.1 115.2 111.9 DC Charleston 1 - 9.2 9.3 108.3 102.6 DC Other 7 20.9 22.9 99.1 101.0 UC/UD

Non-Metropolitan 34 41.1 39.5 89.0 89.2 NSC

Manufacturing 15 19.3 17.4 93.3 92.2 NSC Manufacturing/Poverty 4 3.8 3.4 77.4 70.4 DD Poverty 5 3.6 3.2 68.0 71.8 UC Retirement 4 8.2 9.6 97.8 101.2 UC/UD Government 1 2.9 2.8 86.4 82.4 DD Other Mixed 2 1.0 0.8 81.9 91.5 UC Unclassified 3 2.3 2.1 79.3 82.9 UC

Total 46 100.0 100.0 100.0 100.0

average incomes of regions. This appears not to be the case in South Carolina.4 Perhaps by moving to the state, this group has had the effect of raising South Carolina's per capita income as well as doing the same in the state from which they have come.

No counties are currently farming-dependent according to the USDA classification. Despite this our view was that we should consider those counties which consistently had 10 percent or more of their income from farming as a group for further analysis. There were no counties in this group. Between 1985 and 1988 only two counties­Edgefield and Saluda-consistently exceeded five percent of personal income from farming.

Before completing a review of county types, some attention should be paid to external influences. Since there are no major cities in South Carolina, Atlanta particu­larly (and Charlotte to a lesser extent) provides an additional focal point for the state economy. Movements of personal income per capita in Atlanta-relative to the state mean in South Carolina-might also be incorporated into our analysis. Some relevant levels are as follows:

Year Per capita personal income Atlanta SMSA as in Atlanta SMSA Percentage of South

Carolina average

. 1976 6716 136.2 1987 17293 143.7

As in Greenville-Spartanburg, personal incomes in the Atlanta MSA showed significant upward divergence. Atlanta's emergence as a major international center with strong growth in corporate, financial and other producer services activities may have crowded out development of the smaller metropolitan areas in South Carolina. In any event, its prosperity must be seen as exerting some influence on the economic development of South Carolina.

As a final exercise it is useful to decompose our Mw estimates of per capita income variability for the counties of South Carolina. The value of Mw increased from 10.2 in 1976 to 11.6 in 1988. The decomposition by county type appears in Table 6 for the years 1976, 1980, 1984 and 1988.

Although it is not dramatic, the increased contribution of metropolitan areas to income divergence between 1976 and 1988 stands out. This is due in large part to the growing percentage of the State's population living in these counties and not to their

4A similar observation has been made in Drabenstott and Gibson (1988) for all of the rural U.S.

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.. Table 6

The Contributions of Different County Types to Mw Estimates of Personal In-come per Capita Income Convergence: South Carolina 1976 -1988

County Type 1976 1980 1984 1988 .11976-88 (# of counties) ·

Total Value of Mw 10.20 10.51 11.46 11.60 1.20

Metropolitan (12) of which Greenville/Spartanburg Richland/Lexington Charleston

5.07 1.71 1.65 0.40

5.18 1.95 1.46 0.52

5.22 1.83 1.56 0.45

6.09 2.33 1.87 0.22

1.02 0.62 0.22

-0.18

Non-metropolitan (34) of which Manufacturing (15) Manuf/Poverty (4) Poverty (5) Retirement (4) Government (1) Other Mixed (2) Unclassified (3)

5.13

1.71 0.98 1.02 0.56 0.41 0.14 0.29

5.33

1.77 1.02 1.05 0.57 0.44 0.14 0.34

6.24

1.81 1.02 0.93 0.71 0.44 0.07 0.38

5.51

1.84 1.01 0.89 0.83 0.49 0.08 0.36

0.40

0.13 0.03

-0.13 0.27 0.08

-0.06 0.07 •

incomes diverging upward from the State mean (see Table 5). The contributions of the Greenville-Spartanburg and Columbia areas to this increase stand out. With the exception of theretirement counties which also increased their contribution, there were no other changes of note. Manufacturing, manufacturing/poverty, government and unclassified counties all increased marginally. Poverty counties and "other mixed" counties fell marginally.

SUMMARY AND CONCLUSION

Unlike the country in general where per capita incomes diverged, there was little change in the distribution of the county per capita incomes in South Carolina between 1976 and 1988.

Use of the classification of income movements suggested by Coughlin and Mandelbaum, provides useful initial insights into the individual experiences of South Carolina's counties. Between 1976 and 1988, 21 counties diverged from the average, 15 were converging, and 10 showed no significant change.

12

• The value of the Mw index edged slightly upwards from around 10 to 11.6 over the period. By applying elements of the USDA's suggested county typology to South Carolina's counties, we found that the Greenville-Spartanburg and Columbia areas and the four retirement counties were largely responsible for the increased income diver­gence which did take place. Because agriculture plays such a small role in South Carolina's economy, any contribution from that area was minimal.

In the context of the U.S. debate, Amos (1989) has postulated that greater divergence in state per capita mean personal incomes maybe due to a long wave process, the trough of which occurred in the early 1980s. In the upswing of this cycle, which may now have been taking place for almost a decade, he argues that income inequality at sub-national regional level will increase.

In the Amos scenario one might expect large urban areas to be responsible for much of the increase in the inequality of per capita incomes since technical innovations have their initial impact in big cities. Our findings identify some increase in the Greenville­Spartanburg and Columbia areas. But because there are no major metropolises within the state these changes are less likely to appear. Ifone appends the experience of Atlanta to South Carolina, an enhanced picture emerges. It is particularly notable that the Atlanta area which now has a population approaching 3 million-about 75 percent of South Carolina's total-diverged upwardly from the South Carolina mean by more than 7 percentage points.

• The relative stability of per capita incomes in South Carolina between 1976 and 1988 seems largely to have been a function of the state's economic structure--dominated by textile and related manufacturing, with an agricultural sector which has largely disappeared, but without any major metropolises. In this period, the U.S., Japan and other Western economies experienced a long upward trend in economic activity. Many major cities had economic booms, with strong growth in fields such as finance, property and other business services, and continued growth in other areas of final services provision such as heal th andeducation. The smaller cities of South Carolina shared only partly in this prosperity. Manufacturing in the state struggled in a competitive world environment but the state's amenable climate and low living costs attracted a growing population of retired families.

As we approach the beginning of a new century the income trends of the past 15 years seem likely to continue. Manufacturing will struggle to keep competitive. Poverty will remain a problem in several parts of the state. Agriculture will continue to fade away. More retirees will settle here. South Carolina will be attractive to many as an industrial and residential destination. The implications of such a scenario for movements in relative income variation within the state are difficult to assess fully.

Reduction of rural poverty levels would require major policy intervention by government. In a restrictive fiscal environment this is unlikely to happen. Wide variations in agricultural income are no longer a problem for the state. With strong

13

management, manufacturing should retain its competitive edge. Incomes in the area seem unlikely to change. Larger streams of retirees than previously will settle here since states like Florida now have very large populations and less hospitable living environ­ments. For a state whose mean income was less than the national average, this would imply greater income divergence. Such is not the case in South Carolina because mean incomes seem unlikely to rise much in excess of 80 percent of the national average. Unless new trends emerge, neither income convergence nor income divergence seem likely over the next decade. In a relative sense South Carolina will continue to "stand still." This is not necessarily a bad thing since there is something to be said for a regional economy maintaining its position in a growth environment. Furthermore, if costs of living remain low and quality of life indicators show some improvement, the state's relative position will remain close to the national average.

•

14

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REFERENCES

Amos, Orley. uunbalanced Regional Growth and Regional Income Inequality in the Latter Stages of Development." Regional Science and Urban Economics, 18: 549-566. 1988.

"An Inquiry into the Causes of Increasing Regional Income Inequality in the United States." The Review of Regional Studies. 19 (2): 1-13. 1989.

Bender, Lloyd B., et al. The Diverse Social and Economic Structure of Nonmetropolitan America, RDRR-49. U.S. Department of Agriculture, Economic Research Ser­vice. September, 1985.

Coughlin, Cletus C. and Thomas B. Mandelbaum. ''Why have State Per Capita Incomes Diverged Recently?" Federal Reserve Bank of St. Louis Review. 70 (5): September­October, 24-36. 1988.

____. "Have Federal Spending and Taxation Contributed to the Divergence of State Per Capita Incomes in the 1980s?" Federal Reserve Bank of St. Louis Review. 71(4): July-August, 29-42. 1989.

Drabenstott, Mark and Lynn Gibson eds. Rural America in Transition. Federal Reserve Bank of Kansas City Research Division. 1988.

Fournier, Gary M. and David M. Rasmussen. "Real Economic Development in the South: The Implications of Regional Cost of Living Differences." The Review of Regional Studies. 16(1): 6-13. 1986.

Hady, Thomas F., and Peggy F. Ross. An Update: The Diverse Social and Economic Structure of Nonmetropolitan America. Economic Research Service, U.S. Depart­ment of Agriculture, Staff Report No. AGES 9036. May, 1990.

Ray, Cadwell L. and R. Lynn Rittenoure. "Recent Regional Growth: More Inequality." Economic Development Quarterly. August, 240-248. 1987.

Ross, Peggy J. and Bernal L. Green. Procedures for Developing a Policy-Oriented Classification of Nonmetropolitan Counties. ERS Staff Report No. AGES850308. U.S. Department of Agriculture, Economic Research Service. November, 1988. 1985.

Rowley, Thomas D., John M. Redman, and John Angle. The Rapid Rise in State Per Capita Income Inequality in the 1980's: Sources and Prospects. USDA Economic Research Service, Staff Report AGES 9104. January, 21. 1991. .

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South Carolina Division of Research and Statistical Services. South Carolina Statistical Abstract. Columbia (selected issues).

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•

Williamson, Jeffrey. "Regional Inequality and the Process of National Development: A Description of the Patterns." Economic Development and Cultural Change. 13: 3-84. 1965.

World Bank. World Development Report 1990. Oxford: Oxford University Press. 1990.

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APPENDIX A

• THE U.S. DEPARTMENT OF AGRICULTURE TYPOLOGY OF COUNTIES

This categorization divides counties into the following groups:

Metropolitan counties: These are defined according to the official Office of Management and Budget definition based on the 1980 Census.

The Non-metropolitan counties are then classified as follows:

Farming-dependent counties: A farming county is one in which farming contributed a weighted annual average of 20 percent or more to total labor and proprietor income between 1981 and 1985.

Manufacturing-dependent counties: A manufacturing county is one in which manufacturing contributed 30 percent or more to total labor and proprietor income in 1986.

Mining-dependent counties: A mining county is one in which mining contrib­uted 20 percent or more to total labor and proprietor income in 1986.

Government-dependent counties: A government county is one in which local, • state and federal payrolls contributed 25 percent or more to total labor and

proprietor income in 1986.

Federal lands counties: A federal lands county is one in which federal land was 33 percent or more of total land area in 1977.

Retirement counties: A retirement county is one with 15 percent or more net immigration of people aged 60 or over from 1970 to 1980.

Poverty counties: A poverty county in one ranking in the lowest per capita income quintile in 1950, 1959, 1969 and 1979.

Unclassified counties: An unclassified county is one which fell into none of the above county types in 1986.

,

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According to this categorization the situation in South Carolina and the U.S. can be described by Table Al below.

Table Al

County Type South Carolina United States

Metropolitan 12 712

Non-metropolitan 34 2357 of which Farming 0 512 Manufacturing 25 553 Mining 0 124 Government 5 347 Federal lands 2 243 Poverty 10 239 Retirement 4 480 Unclassified 4 519

•

A more detailed analysis of counties is reported in Table A2 on the following page.

18

/ •

TableA2

County Metro Man Fed'l Lands Gov't Poor Retire Unclass.

Abbeville X Aiken X Allendale X Anderson Bamberg X X Barnwell X X X Beaufort X X Berkeley X Calhoun X Charleston X Cherokee X Chester X Chesterfield X Clarendon X Colleton X Darlington X Dillon X X Dorchester X Edgefield X Fairfield X Florence X Georgetown X X• Greenville X Greenwood X

• Hampton X Horry X Jasper X Kershaw X Lancaster X X Laurens X Lee X X X Lexington X McCormick X X X Marion X x-Marlboro X X Newberry X Oconee X Orangeburg X Pickens X Richland X Saluda -X Spartanburg X Sumter X Union X Williamsburg X X , York X

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