Progress and Challenges in Reducing Economic Distress in Appalachia

An Analysis of National and Regional Trends Since 1960

By

Lawrence E. Wood

Penn State, Department of Geography

and

Gregory A. Bischak, Ph.D.

Senior Economist ARC

January 2000

Appalachian Regional Commission*

Washington, DC

* The views expressed in this report are those of the authors and do not reflect the views of

the Appalachian Regional Commission.
Executive Summary

Progress and Challenges in Reducing Economic Distress in Appalachia:

An Analysis of National and Regional Trends Since 1960

This report presents an analysis of the changes in the number of distressed

counties in Appalachia and the entire United States for the census years 1960,

1970, 1980, and 1990 based on the Appalachian Regional Commission's (ARC)

current distress measure. Distressed counties are those with poverty and

unemployment rates one and a half times the national rates and with per capita

incomes that are two-thirds or less than the national rate. The findings fill a critical

gap in the research on Appalachia by identifying the number of distressed counties

in Appalachia prior to the inception of the ARC, as well as throughout much of

the ARC's existence. Furthermore, by determining the total number of distressed

counties in the entire United States, this research provides a benchmark for

socioeconomic conditions in Appalachia relative to the rest of the nation.

Second, this report identifies macroeconomic and regional trends that are

associated with both distress and improvement in Appalachia as well as the entire

United States from 1960 to 1990.

Third, this report analyzes the socioeconomic factors that are associated with

long-term distress, as well as factors that predict whether a county moved out of

distress in the region.

Key Findings

The central finding of this analysis is the significant improvement in the

Appalachian Region since 1960, as the number of distressed counties in

Appalachia has decreased by more than half during the years studied. The number

of ARC counties identified as distressed declined sharply from 214 in 1960 to 161

in 1970 and to 78 in 1980. These gains, however, were eroded during the 1980s as

the number of distressed counties rose in 1990 to 106. Of the 214 counties that

were distressed in 1960, 98 counties remained distressed and 116 were no longer

distressed by 1990. The general decline in distressed counties in Appalachia from

1960 to 1980, as well as the rise in the number of distressed counties between

1980 and 1990, clearly mirrors national trends.

This report also finds, however, that approximately one-quarter of the

Appalachian counties that were distressed almost four decades ago remain

distressed today. Furthermore, while the number of distressed counties in both

Appalachia and the United States decreased dramatically between 1960 and 1980,

a significant reversal occurred between 1980 and 1990 as the number of distressed

counties both nationally and within the Appalachian Region began rising. Thus, an

important component of this research is to determine the factors associated with
the number of persistently distressed counties in Appalachia, as well as the rise in

distress levels between 1980 and 1990.

The changes in regional and national distress levels can be attributed to several

macroeconomic national and international trends, as well as changes in public

policies that are largely outside the scope and influence of the ARC. Full

employment policies and the initiation of large-scale federal poverty alleviation

and economic development programs set the stage for major reductions in national

distress levels. The rise in distress levels nationally and regionally were associated

with the rising inflation and energy price changes in the mid-1970s and early

1980s, and with corresponding shifts in public policy toward anti-inflation policies

and away from full employment policies. These macroeconomic factors had a

pronounced effect on manufacturing and extractive industries, which in turn

affected the Appalachian economy. Nationally, the long-term rise in household

income and wage inequality are other factors associated with rising distress levels

since the 1980s.

Within the Appalachian Region, however, the results of the analysis of the

region’s county-level economies have identified a number of significant factors

that are associated with the movement of counties out of distressed status

compared with persistently distressed counties:

• A higher share of manufacturing employment, particularly in the

South;

• Counties that became part of metropolitan areas, particularly in the

South;

• A more diversified economy as reflected by a nonspecialized local

economy;

• Higher educational attainment rates for both high school completion

and some college;

• A higher percentage of the population living in urban areas (i.e.,

towns and small cities); and

• The ability of a county to attract retirees to establish residency.

In addition, this research identified several factors that were associated with

persistent distressed status as compared with counties that moved out of distress:

• A higher share of mining employment (half of the persistently distressed

 counties were mining-dependent);

• A higher share of minority populations;

• A higher share of children and elderly dependent populations; and

• A higher dependence on government transfer payments.
Policy Implications

A number of policy issues are raised by these findings. While manufacturing

played a generally positive role in the past for reducing distress, the prospects for

the future role of manufacturing are decidedly different. Indeed, the outlook is

good only for the most productive, capital-intensive manufacturing sectors that are

supported by a complex of high technology suppliers, and professional services in

such fields as engineering, product design, marketing, and finance.

Another issue is the vulnerability of coal-dependent counties to the fluctuations of

energy prices and the demand for coal. The rising distress in the coal-dependent

counties points to the need for greater economic diversification efforts to widen

the economic base.

Educational attainment is another prominent factor in predicting improvement.

Future trends in the knowledge-based economy leave little doubt that educational

attainment will continue to be a key factor in improving the prospects for

distressed counties. Another important policy issue is the potential role of

urbanized centers such as towns and small cities in improving the economic

prospects of distressed counties.

The overarching issue that stands out, however, is the fact that so much of the

improvement in both Appalachia and the rest of the United States occurred during

a period when national policy was supportive of full employment and poverty

alleviation efforts. This finding suggests that regional economic development is

most likely to take place when national policies create the conditions to support it.

As such, addressing persistent distress would seem to require a renewed national

commitment, similar to the one that inspired the establishment of the ARC and the

regional development policies of the 1960s.
1

 I. Introduction

Since 1965, the Appalachian Regional Commission (ARC) has attempted to

improve the socioeconomic conditions in Appalachia. While the ARC originally focused

its efforts on developing the more prosperous areas of the Appalachian Region, in the

early 1980s the Commission began targeting what it termed "distressed counties" for

increased assistance.1 The ARC's distress indicator compares the socioeconomic status

of Appalachian counties with national rates of poverty, unemployment, and per capita

income.∗ The Commission’s distress measures are similar to measures used by other

federal and state agencies.2

 This report presents, for the first time, an analysis of the

changes in the number of distressed counties in Appalachia and the entire United States

for the census years 1960, 1970, 1980, and 1990 based on the ARC's current distress

measure. This analysis fills a critical gap in the research on Appalachia by identifying

the number of distressed counties in Appalachia prior to the inception of the ARC, as

well as throughout much of the ARC's existence. Furthermore, by determining the total

number of distressed counties in the entire United States, this research provides a

benchmark for socioeconomic conditions in Appalachia relative to the rest of the nation,

and further affords a means of identifying macro and regional trends that are associated

with both distress and improvement in Appalachia as well as the entire United States

from 1960 to 1990.

The central finding of this analysis is the significant improvement in the

Appalachian Region since 1960, as the number of distressed counties in Appalachia has

decreased by more than half during the years studied. This report also finds, however,

that approximately one-quarter of the Appalachian counties that were distressed almost

four decades ago remain distressed today. Furthermore, while the number of distressed

counties in both Appalachia and the United States decreased dramatically between 1960

and 1980, a significant reversal occurred between 1980 and 1990 as the number of

distressed counties both nationally and within the Appalachian Region began rising.

 

∗ Distress designations are developed annually by the ARC and are based on county poverty rates

and three-year unemployment rates that are 150 percent or more than the national average, and

per capita market income (i.e., per capita income less transfer payments) that is two-thirds or less

than the national average.
2

Thus, an important component of this research is to determine the factors associated with

the number of persistently distressed counties in Appalachia, as well as the rise in distress

levels between 1980 and 1990. Identifying such conditions should prove useful in

assessing the effectiveness and broader policy context of the ARC’s programs. The

results of this research clearly suggest that regional factors, macroeconomic influences,

and national policy trends have all influenced county-level distress status in Appalachia.

The factors associated with the improvement throughout much of the region, as well as

the persistent distressed status of many Appalachian counties, bring into relief a number

of policy considerations that the ARC and other government agencies should consider

when attempting to improve socioeconomic conditions in Appalachia and elsewhere.

II. Overview of Economic Policies in the Appalachian Region Since 1960

Macroeconomic and Policy Factors Affecting the Appalachian Region

Before discussing the individual policy measures of the ARC, it is important to

understand that socioeconomic change in the Appalachian Region is highly sensitive to

national policies and macroeconomic factors that are largely beyond the scope of the

ARC and other development agencies. A variety of macroeconomic factors especially

influence Appalachia. For example, the Appalachian economy has historically been

more susceptible to the adverse impacts of recession than other areas of the country, in

large part because of a heavy concentration of recession-prone manufacturing and

construction-dependent industries in the region.3

 Also, much of Appalachia, especially

the coal-producing region of Central Appalachia, is sensitive to energy-related factors.

Changing demand for coal from energy-intensive industries as well as price fluctuations

for coal and other energy-related resources have profound effects on the Central

Appalachian economy.4 Another macroeconomic factor that has particularly influenced

Appalachia's economy over the past few decades includes the growing inequality of

income distribution both nationally and regionally.5

 Also, industrial relocation strategies

of manufacturing firms have had a major effect on the changes within the region,

 
3

resulting in relatively high entry rates of manufacturing plants in both Central and

Southern Appalachia, but high exit rates and job loss in the northern part of the region

during the 1970s and 1980s. More recently, there has been evidence of a reversal of

trends, with higher exit rates of manufacturing establishments in the central and southern

parts of the region, particularly in labor-intensive sectors. Plant closures and relocations

within the region have increasingly reflected the influence of trade-liberalization policies

of recent years.6

Policy measures, ranging from broad-scale strategies such as Johnson's "Great

Society" programs of the 1960s to individual environmental or international trade

regulation policies, have also strongly affected the Appalachian Region. To be sure, the

ARC was established during the "Great Society" era, a time when federal government

policy measures supported development in distressed regions. The more general concern

for social welfare in the 1960s burgeoned into wide-scale poverty alleviation efforts in

the 1970s focused on improving access to healthcare, education, and employment. Such

large-scale federal efforts have probably contributed to the changes in the number of

distressed counties in Appalachia as well as the United States over time.

Chart 17

Federal Poverty Expenditures as a Percent of GDP 

1962-2000

0.00%

0.50%

1.00%

1.50%

2.00%

2.50%

3.00%

3.50%

4.00%

19621964196619681970197219741976197819801982198419861988199019921994199619982000

YEARS
4

Chart 28

Indeed, the decline in the number of distressed counties between 1960 and 1980, and then

the rise in the number of distressed counties between 1980 and 1990 clearly mirror the

rise and fall of federal poverty alleviation expenditures as a percentage of gross domestic

product, (GDP) as shown in Chart 1. The cutting of what were perceived as "big

government" programs and the corresponding decline in both poverty alleviation and

economic development expenditures in the 1980s have likely exacerbated some of the

problems in the region. Furthermore, as Chart 2 shows, federal economic development

expenditures have never recovered to the 1978 peak real-spending levels even after the

increases of the 1990s.

Another prominent macroeconomic policy factor was the shift away from the full

employment policies of the 1960s and early 1970s, toward inflation-fighting policies

spearheaded by higher interest rates and the strong dollar policy of the early 1980s. The

inflation-fighting regime brought about a sequence of recessions that shocked many of

the older manufacturing sectors of the northern Appalachian Region and generated higher

levels of structural unemployment.9

 In another vein, federal policies have generally

Federal Economic Development Spending 1962-2000

Thousands of 1992 Dollars

$0

$2,000

$4,000

$6,000

$8,000

$10,000

$12,000

$14,000

$16,000

$18,000

$20,000

1962 1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000

Years
5

resulted in federal expenditures in Appalachia being below the national per capita

average.10 In sum, multiple macroeconomic and policy factors are affecting the

Appalachian Region, a thorough discussion of which is beyond the scope of this report.

It is important to realize, however, that rather than being isolated, Appalachia and the

programs of the ARC are highly influenced by macroeconomic and policy factors that are

beyond the scope of the Commission.

The Origin of the ARC

Throughout most of this century, Appalachia has been a region with some of the

largest concentrations of impoverished people living in the United States.11 The report by

the President’s Appalachian Regional Commission (PARC) in 1964 identified much of

this poverty as stemming from Appalachia's relative isolation from the rest of the

country.12 Perhaps ironically, the report noted that federal government investments had

largely bypassed the Appalachian Region, potentially exacerbating such isolation.13

However, in the 1960s this changed, when the federal government became explicitly and

in many ways uniquely concerned with Appalachia's economic and social well-being.

In the early 1960s, there was wide bipartisan agreement in Congress that

problems of lagging regions could not be resolved by private initiative alone.14 At that

time, the federal government made a previously unparalleled commitment to regional

development. This commitment was reflected in, amongst other things, the establishment

of the Area Redevelopment Administration (ARA). Inaugurated in 1961, the ARA was

representative of the federal government's increased concern and commitment to

supporting programs designed to improve socioeconomic conditions both regionally and

nationally. The ARA set a new precedent for federal government aid to poor regions.15

However, while the ostensible goal of the agency was to help regions such as Appalachia,

many federal, state, and local-level Appalachian politicians were dissatisfied with ARA

programs and the lack of attention that the agency was giving Appalachia.16

In 1963, amidst Appalachian governors' growing discontent with federal aid

programs, record floods in Central Appalachia, and increased media attention on
6

Appalachian poverty, President Kennedy fulfilled his campaign promise to address

Appalachia's social and economic woes by creating the PARC. The PARC was

designated to assess Appalachia's socioeconomic conditions and to develop a

"comprehensive action program for the economic development of the Appalachian

Region."17 Not surprisingly, the PARC determined that Appalachia lagged behind the

rest of the United States; according to the PARC report, the "realities of deprivation" in

Appalachia included low income, high unemployment, lack of urbanization, and deficits

in both educational attainment and living standards such as housing quality.18 The PARC

report, if not the concern that led to the initiation of the PARC itself, resulted in the

passage of the Appalachian Regional Development Act (ARDA). The ARDA, much of

which was based upon the PARC's recommendations, had four principal titles: Title I

established the ARC; Title II specified major programs, including highway, health,

vocational education, housing, and sewage treatment programs; Title III defined local

development districts (LDDs), which were multi-county districts through which most

ARC programs, except the highway program, were to be proposed and implemented; and

Title IV defined the Appalachian Region.19 By 1967, ARC-defined Appalachia included

397 counties in 13 states. In the mid-1980s, two more counties were added, and in fiscal

year (FY) 1999, Congress added seven counties to bring the total of ARC counties to

406.

The ARC's attempt to develop Appalachia is perhaps the most comprehensive

regional development effort ever undertaken in this country.20 Since 1965, the ARC,

along with state and local governments in Appalachia, has spent more than $15 billion on

economic and social development programs throughout the Appalachian Region.21

Highways have received the majority of these expenditures; the remaining funds have

supported what the ARC terms "area development" projects. Such projects are aimed at

promoting business and community development and improving education, health,

housing quality, and infrastructure.22
7

ARC Policy: From Growth Centers to Distressed Counties

From its inception, the ARC endorsed a growth center strategy.23 This policy was

designed to promote economic growth and development in Appalachia's urban areas and

was implemented as a result of the mandate in the ARDA for the ARC "to concentrate its

investments in areas with a significant potential for future growth where the return on

public dollars invested will be the greatest."24 The ARC's growth center policy supported

the development of Appalachia's urban centers. According to growth center theory,

development in these urban centers, or growth centers, would eventually "trickle down"

to the region's rural and more economically disadvantaged areas.25 The growth center

concept was influenced by regional development theory prevalent in the 1960s and was a

strategy employed by many governments throughout the world at that time.26

Largely because of the Commission's growth center policy, urban areas in the

Appalachian Region received the majority of ARC funds throughout the early years of

the Commission's existence.27 By the mid-1970s it became evident that the ARC was no

longer implementing its original growth center policy, largely because of the political

difficulties associated with concentrating public investments in relatively few places.28

Nonetheless, the most impoverished areas of the Appalachian Region continued to

receive relatively little attention throughout the 1970s.29 In the early 1980s this changed.

In 1981, Congress requested a report from the ARC outlining "a plan for finishing up

ARC programs in a reasonable period of time."30 Faced with what the Appalachian

governors and ARC staff members perceived as a serious threat that the federal

government would dissolve the ARC, the report submitted to Congress was in many ways

designed to further justify and preserve the Commission. Included in the report's "FinishUp Program" were various policy measures, including a Distressed Counties Program.

The seeds of the Distressed Counties Program—a program now almost two decades in

existence—were sown in the following wording in the report:

More than 900,000 Appalachians live in the 60 most distressed and

underdeveloped counties in the Region. . . . Many of the communities in

these counties still lack even the most basic facilities, and the lack of these

facilities limits the opportunities to meet housing needs. The proportion of
8

housing without adequate plumbing is three times the national average.

Poverty and unemployment rates are disproportionately high. The

communities lack some of the most basic facilities and the resources to

provide them. . . . There has been some criticism of the ARC in the past

for failure to provide sufficient help to the most distressed counties in the

region. The Appalachian Regional Development Act, however,

established the ARC as an economic development agency and requires it

to focus its investments where they can be expected to bring about the

highest economic development returns. Few of these investment

opportunities are found in the most distressed and underdeveloped

counties.31

Though the ARC's continued existence remained seriously threatened throughout the

1980s and funding appropriations to the Commission were significantly curtailed,

especially during the Reagan years, the ARC continues to operate today, and the

Distressed Counties Program has become one of the Commission's more eminent

undertakings.

III. The ARC Distressed Counties Program

The Distressed Counties Program was adopted as ARC policy and made effective

at the beginning of FY 1983.32 The policy established a 20 percent allocation of Area

Development funds for projects in distressed counties and 20 percent match rates by state

and/or local governments. To identify distressed counties, the Commission selected

variables that were not susceptible to short-term variation. For example, to minimize the

influence of potential short-term fluctuations in unemployment in determining distressed

status, the ARC decided to use three-year average unemployment rates. In sum, when

determining what variables to use to define distress, the ARC hoped to select variables

that would identify counties with the structurally weakest economies.

Initially, the ARC selected the following criteria:

• Unemployment rate (three-year average);

• Poverty rate;

• Per capita market income (PCMI, which is income excluding transfer

payments); and

• Infant mortality (three-year average).
9

Counties were ranked among all ARC counties and had to be in the lowest quartiles in at

least three of the four categories to qualify as distressed.

In FY 1988, the Commission discontinued using infant mortality as a measure of

distress because the region’s rate had converged to the national rate. In addition, the

remaining indicators were indexed to national averages.33Furthermore, the Commission

added a second and third economic designation for middle and competitive counties, and

it set 50 and 70 percent matching rates respectively for projects in middle and

competitive counties. Each state designated competitive counties in its state plan using

the following criteria:

• Poverty rates at or below national averages;

• Three-year unemployment rates at or below national averages; and

• Per capita market income no less than 80 percent of the national average.

Furthermore, the Commission began tracking its counties using a five-category system:

severely distressed; distressed; middle; strong; and very strong. These additional

categories, however, were not used for allocation or funding purposes.

In FY 1995, the Commission modified its distress designation.34 If a county had a

poverty rate that was at least 200 percent of the national average, then it would need to

match only one of the two remaining criteria (150 percent unemployment or two-thirds

PCMI) to be considered distressed. In FY 1997, the Commission added a fourth

designation for attainment counties that reached or were better than national averages for

all three criteria. The Commission annually determines all four economic categories:

distressed, transitional, competitive, and attainment. Currently, Area Development

distress allocations are 30 percent, and attainment counties are ineligible for Area

Development funds. 35

One of the biggest concerns that the ARC has with the distress indicator is the

inconsistent lack of dependable poverty data—data to determine official poverty rates are

collected only once every ten years, during the U.S. Census.36 Nonetheless, the ARC

believes that its distress measure has proven to be a sufficiently objective and reasonable

measure on which to base both policy and appropriations.37 Furthermore, according to
10

the ARC, "the selection criteria are understood and intended by the Commission to be

very conservative but appropriate in view of the very limited funds available."38 Indeed,

the "very limited funds" made available to the ARC since the early 1980s have likely

hindered the Commission's ability to thoroughly address the problems of the region's

distressed counties. As Chart 3 shows, compared with the earlier years of the program,

the ARC began receiving scant appropriations from Congress in the early 1980s,

coinciding

Chart 339

with the inauguration of the Distressed Counties Program. In the 1980s, the Reagan

administration and much of the American public had become wary of "big" government

programs, and funding to the ARC and similar types of programs significantly decreased.

Under the Bush administration there was a slight increase in appropriations to the ARC

and then a larger increase under the Clinton administration; nonetheless, current

appropriations to the Commission remain low compared with funds received during the

earlier years of the program.

ARC Highway & Area Development Funding, 1966-2000

Millions of 1992 Dollars

0

200

400

600

800

1000

1200

1400

1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000

YEARS

Highway Funding

AREA Funding
11

As mentioned, the ARC currently allocates up to 30 percent of all Area

Development funds specifically for distressed county projects.40 Almost any project

addressing a development need in a distressed county is eligible for funding, with the

ARC providing up to 80 percent of project costs in distressed counties.41 However, states

can use other ARC appropriations that are not specifically designated for distressed

counties to fund projects in distressed counties. According to the ARC, total spending on

single-county grants to distressed counties from fiscal years 1983 through 1999 has been

$266 million, representing about 42 percent of all single-county grants.42 In addition,

$297 million in multi-county grants have been awarded throughout the region over the

1983-1999 period, but it is not possible to break out the historical trends for distressed

and non-distressed multi-county areas.43

The ARC is not unique in its efforts to aid areas of special need. Agencies such

as the U.S. Department of Agriculture (USDA), the Economic Development

Administration, and the Tennessee Valley Authority address what might be considered

individually distressed areas within their jurisdictions. In fact, the jurisdictions of many

of these agencies overlap with that of the ARC. Furthermore, all 13 Appalachian states

make special provisions for economically distressed areas. Such programs address a

wide range of geographic units, from entire counties to small communities, and most

agencies use at least one or all of the same indicators that the ARC uses to measure

distress.44 In sum, the Distressed Counties Program can be considered the ARC's attempt

to identify and support the most socially and economically disadvantaged areas within the

Appalachian Region.

IV. Analysis of Economic Distress in Appalachia: 1960 to 1990

There have been a number of analyses in the academic literature regarding the

ARC and its programs, and the ARC itself has written literally hundreds of reports

pertaining to its own programs and policies. Much of the early research written about the

ARC was critical, particularly of the Commission's policies.45 However, more recent
12

research has commended the ARC and has associated a significant share of the

socioeconomic improvement in Appalachia with the agency's efforts.46 Aside from inhouse analyses by the ARC—primarily to designate distressed counties for funding

purposes—there are relatively few analyses of the ARC's Distressed Counties Program.

To date, Amy Glasmeier and Kurt Fuellhart provide the most thorough account of the

Distressed Counties Program.47 Their report, among other things, identifies

socioeconomic characteristics associated with distressed counties in Appalachia since

1980. According to their research, factors associated with counties being distressed

include low levels of educational attainment; a high percentage of young, single mothers;

a large elderly population; and a low percentage of income from both the manufacturing

and retail sectors. Their research also demonstrates various locational characteristics

associated with distress; counties located either in or adjacent to metropolitan areas, in

the southern part of the ARC Region, or on the edge of Appalachia have been typically

less likely to be distressed than other counties in the region.

This report builds upon previous socioeconomic assessments of Appalachia.

First, it presents an analysis of data for the years 1960, 1970, 1980, and 1990 to

determine the number of distressed counties in the United States and in Appalachia.

Prior to this report, no research identified distress in Appalachia using a consistent

measure over such an extended period. Second, this report attempts to determine factors

associated with long-term distress as well as a county's ability to move out of distress in

the region. Third, this report provides an extensive historical analysis of distress in

Appalachia. It is important to note that this report considers only the 399 counties that

were part of the ARC Region during the period studied (see maps 1-5 in Appendix B),

though the distressed status of the counties that were recently added to the ARC Region

is included in Appendix A. Explicit details regarding the research methodology as well

as information concerning the data used in this analysis are included in Appendices C

and D.
13

Number of Distressed Counties in Appalachia and the United States 1960-1990

In order to benchmark the changes in distress levels within Appalachia and the

nation over the 1960 to 1990 period, the ARC’s current distress criteria were applied to

data on all the counties in the United States for the decennial census years 1960, 1970,

1980, and 1990.∗

 As a result, comparable distress levels could be computed for the two

decades prior to the inception of ARC’s Distressed Counties Program (see Appendix C).

In addition, national distress trends could be examined over the 30-year period, thereby

revealing trends within the nation and the Appalachian Region.

Tremendous progress was made in reducing the number of distressed counties

within the Appalachian Region over the 1960-80 period. The number of ARC counties

designated as distressed declined sharply from 214 in 1960, to 161 in 1970, to 78 in 1980.

These gains, however, were eroded during the 1980s as the number of distressed counties

rose in 1990 to 106.48 Of the 214 counties that were distressed in 1960, 98 counties

remained distressed and 116 were no longer distressed by 1990. Throughout the

remainder of this report, the counties that were distressed in both 1960 and 1990 will be

referred to as “persistently distressed” counties, while counties that were distressed in

1960 but no longer distressed in 1990 will be referred to as having moved out of

distressed status. Sixty-one counties were distressed in all years and can be referred to as

the hard core of persistently distressed counties.

The number of distressed counties by state is presented below in Table 1, and

Maps 1-6 in Appendix B indicate the location of distressed counties in the Appalachian

Region. A listing of all of the distressed counties in Appalachia by year is included in

Appendix A.

 

∗

 The criteria were virtually the same with one exception, as the unemployment rate was based on a singleyear rate rather than the three-year average normally used. This was done because comparable data was not

available for the years just prior to and after each of the decennial years.
14

Table 1

Distressed Counties by State

STATE

TOTAL ARC

COUNTIES 1960 1970 1980 19901

DIST. 1960

AND 1990

DIST. 1960,

NOT 1990

AL 35 24 13 2 1 1 23

GA 35 14 3 1 0 0 14

KY 49 44 41 34 38 38 6

MD 3 110001

MS 21 20 19 7 10 10 10

NC 29 15 13 3 2 2 13

NY 14 0 0 0 0 0 0

OH 29 7 6 2 11 7 0

PA 52 2 0 0 2 1 1

SC 6 000000

TN 50 37 27 17 7 7 30

VA 21 14 8 1 5 5 9

WV 55 36 30 11 30 27 9

Total 399 214 161 78 106 98 116

1

 Note that the number of distressed counties in 1990 differs from the number officially designated by ARC as distressed counties

because distress levels were frozen during the 1988-1992 period while the Commission awaited new poverty rate data from the 1990

census.

For a detailed description of the data sources, see Appendix D.

For Distressed Thresholds, see Appendix C.

The general decline in distressed counties in Appalachia from 1960 to 1980, as

well as the rise in the number of distressed counties between 1980 and 1990, clearly

mirrors national trends, as indicated in Table 2 below. Furthermore, as maps 7 and 8 in

Appendix B reveal, the greatest decrease in distress, both within Appalachia as well as

nationally, occurred in the southern region of the United States.

Table 2

Distressed Counties in Appalachia and the United States

YEAR U.S. 1 APPALACHIA

1960 676 214

1970 557 161

1980 286 78

1990 325 106

For a detailed description of the data sources, see Appendix D

For Distressed Thresholds see Appendix C.

1

 Does not include ARC counties

Individual Distress Measures and Corresponding Policy Trends

There are a few trends potentially hidden within the broader distress measure that

underscore some of the problems that the ARC faces in attempting to improve the
15

socioeconomic conditions throughout much of the Appalachian Region. For example,

many of the counties that had moved out of distress by 1990 still did not compare

favorably with national averages in terms of unemployment, poverty, and income (Table

3). Poverty levels in these counties were considerably above the national average in

1990, while PCMI in many of these counties was less than two-thirds the national

average at that time. Indeed, a number of counties that emerged from distress between

1960 and 1990 remained, in 1990, precipitously close to becoming distressed again.

Rates of poverty, unemployment, and PCMI, when considered together, however, were

not enough to qualify these counties as distressed in 1990. Nonetheless, in many cases

two of the distress indicators often exceeded the individual distressed standards. It is also

important to note that the counties that eventually moved out of distress had much lower

rates of poverty and unemployment and higher PCMI in 1960 than the counties that

remained distressed. It appears that the counties in Appalachia that emerged from

distress actually had a head start: they were not as distressed in 1960 as the counties that

remained distressed over time. This is an important factor to consider when assessing the

ability of counties to move out of distressed status.

Table 3

Individual Distressed Variables by Year

U.S. AVERAGE

APPALACHIAN

AVERAGE

DISTRESSED 1960,

NOT 1990

DISTRESSED 1960

AND 1990

PCMI 1960 $1,639 $1,267 $828 $769

PCMI 1970 $3,490 $2,718 $2,074 $1,745

PCMI 1980 $7,909 $6,339 $5,143 $4,887

PCMI 1990 $15,636 $12,125 $10,251 $7,773

Poverty 1960 22.10% 31.13% 49.88% 53.42%

Poverty 1970 13.74% 18.13% 27.10% 35.87%

Poverty 1980 12.40% 14.01% 18.50% 22.94%

Poverty 1990 13.12% 15.23% 17.52% 28.01%

Unemployment 1960 5.14% 6.77% 6.40% 9.87%

Unemployment 1970 4.37% 4.46% 4.85% 6.90%

Unemployment 1980 6.52% 7.73% 7.89% 10.94%

Unemployment 1990 6.31% 6.82% 6.56% 12.24%

For a detailed description of the data sources, see Appendix D.

For Distressed Thresholds, see Appendix C.

The individual distressed measures indicate far worse conditions for the

persistently distressed counties. The unemployment rates in these counties were

alarmingly high throughout the period studied and were exceptionally higher in 1990 than
16

they were in 1960. Furthermore, 1980 and 1990 poverty rates in the persistently

distressed counties indicate that these counties might be losing ground not only to the rest

of the United States but to the rest of Appalachia as well: between 1980 and 1990,

poverty rates increased from 23 to 28 percent in the persistently distressed counties, while

poverty rates in the rest of Appalachia increased at a much lower rate. The relatively

poor economic conditions in the persistently distressed counties are further signified by

the fact that in 1990 such counties had less than half the national average in PCMI.

However, it is also important not to overlook much of the improvement that has taken

place in many of these distressed counties over the past few decades that is not reflected

in the distress measure. For example, other analyses have demonstrated tremendous

improvement in housing quality and healthcare throughout the entire Appalachian Region

since the inception of the ARC.49

To summarize, while there has been a tremendous decline in the number of

distressed counties in Appalachia since 1960, many of the counties that emerged from

distress during that time still did not have employment, poverty, and income rates that

compared favorably with national averages in 1990. Furthermore, many of the

persistently distressed counties, according to some indicators, gained little if any ground

compared with the rest of the nation between 1960 and 1990.

It is important to note that changes in poverty and unemployment rates both

regionally and nationally correlate with the changes in poverty alleviation expenditures

and full employment policies of the federal government. As poverty expenditures rose

throughout the 1960s and 1970s, poverty rates fell, and as such expenditures as a share of

gross national product leveled off and actually declined between 1980 and 1990, poverty

rates began rising. There are similar trends regarding the federal government's full

employment policies as unemployment data in Table 3 show: unemployment rates fell

across the board in 1970 and then rose thereafter, corresponding to the peak and decline

of such employment policies.

Individual distress indicators as well as levels of distress closely mirror trends in

national policy. Moreover, distress trends in Appalachia mirrors ARC spending, with

relatively high expenditures and corresponding improvement in the number of distressed

counties until the 1980s. The increase in the number of distressed Appalachian counties
17

parallels the substantial decline in ARC expenditures beginning in the 1980s. However,

distress in Appalachia should not be understood as entirely related to ARC efforts.

Indeed, the variation in distress levels is best understood as a result of the interaction of

various complex socioeconomic trends, macroeconomic factors, and federal-level

policies, including the policies of the ARC. The ARC was a small but significant part of

the aforementioned federal government economic development and poverty alleviation

efforts that began in the early to mid-1960s. Taken together, federal government and

ARC efforts as well as macroeconomic factors provide a fairly clear context in which to

understand the patterns of distress both regionally and nationally. As the next section of

this report shows, a number of factors and policy measures are related to trends in distress

levels.

Regional, Macroeconomic, and Policy Trends Affecting Distress

There were distinct regional trends in Appalachia in terms of distressed status

during the period studied. Close to three-quarters of the Appalachian counties that

moved out of distress between 1960 and 1990 were in Southern Appalachia. This subregion showed a steady decrease in the number of distressed counties, even between 1980

and 1990 when the total number of distressed counties in all of Appalachia rose

dramatically. The decline in the number of distressed counties in Southern Appalachia

between 1960 and 1990 was at least partially the result of broader regional and

macroeconomic trends, and is related to the overall decline in distressed counties between

1960 and 1990 in the southern United States.

One of the explanatory factors regarding the precipitous decline in the number of

distressed counties in the southern ARC region is the post-World War II economic

growth in the South.50 Increased industrialization and urbanization in the region have

fueled much of this growth. The number of jobs in manufacturing has steadily grown in

the southern United States over the past half-century, and along with this growth has

come economic improvement for many counties in the region, as manufacturing jobs

have often supplanted low-wage, agricultural jobs.51 Many of the counties that emerged

from distress in the southern ARC region had consistent growth in manufacturing jobs
18

throughout the period studied. However, simply because a county had high rates of

manufacturing jobs and was able to emerge from distress does not mean that its

socioeconomic conditions compared favorably with either the rest of the nation or even

much of Appalachia. The growth in manufacturing in the South was in many respects the

result of manufacturing firms seeking out lower wage, non-unionized workers and

favorable business climates. The results have simply been, for the most part, an increase

in low-wage, low-skilled manufacturing jobs in the region. Indeed, manufacturing jobs

in Southern Appalachia, relative to such jobs elsewhere in the United States, generally

pay lower wages.52 Moreover, the status of manufacturing jobs in the South, and rural

America in general, is becoming increasingly precarious, as the same factors that

originally contributed to manufacturing relocating to the South—low wages and

favorable business climates—are leading firms beyond the nation's borders. To be sure,

"globalization" has already exposed a number of communities in Appalachia to

considerable job loss, as manufacturing plants are increasingly considering locations

almost anywhere in the world.53 Nonetheless, it is important to keep in mind that an

increase in manufacturing jobs has generally improved the economic conditions in

Southern Appalachia, leading to the decline in distress in the region over the past few

decades. The southern Appalachian Region has also particularly benefited from

demographic and economic spillover effects from some of the growing cities in the

South, including Atlanta, Charlotte, Memphis, and Nashville, which have been some of

the fastest growing cities in the country during the second half of this century.54

The success throughout much of the South is in stark contrast to a number of

counties, especially in Kentucky, West Virginia, and Mississippi, that have remained

persistently distressed over time. More than three-quarters of the ARC counties in

Kentucky and close to half of the ARC counties in both West Virginia and Mississippi

were distressed in both 1960 and 1990. The spatial patterns of persistent pockets of

distress in both Appalachia and the nation are depicted in Map 8 in Appendix B.

The poor economic conditions in Central Appalachia can be attributed to a variety

of factors, including the region's relative isolation from major urban areas and its rugged

terrain, which adversely affects the accessibility to jobs as well as the ability of the region

to attract employment opportunities. In addition, the region's continued dependence on
19

extractive industries, particularly coal mining, has defined and limited the options for a

diversified economy. A number of the counties that had emerged from distress by 1980

but then fell back into distress in 1990 were in Central Appalachia, especially West

Virginia. This decline and then reversal in distressed status can at least be partially

explained by the coal industry boom in the 1970s, relating to the oil crises of 1973 and

1979, and the subsequent bust of coal prices in the 1980s and 1990s.55 Boom and bust

cycles have historically had correspondingly positive and negative impacts upon Central

Appalachia, and many of the Central Appalachian counties that were not distressed in

1980 but had become distressed again in 1990 were "coal counties" in Kentucky, West

Virginia, and Virginia. West Virginia, the victim of the decline not only in coal prices

but also in manufacturing jobs moving out of the state, saw its number of distressed

counties increase from 11 to 30 between 1980 and 1990.

Outside the Appalachian Region, persistent distress stands out in the Mississippi

Delta Region (see Map 8). This persistence of distress in the Delta Region reflects the

historical reliance upon low-wage agricultural employment, the lack of economic

diversification , the relatively high poverty rates of African Americans living in the

region, and the legacy of cultural and economic discrimination.56

A third trend is the consistent lack of distressed counties in the North, especially

in New York and Pennsylvania. The Northeastern United States has historically had a

stronger economy and been more urbanized than the rest of Appalachia as well as the rest

of the United States.57 However, there was a dramatic increase in the number of

distressed counties in Ohio between 1980 and 1990, from two to eleven, as well as an

increase from zero to two distressed counties in Pennsylvania during that time. Much of

this distress is the result of manufacturing jobs leaving the North, otherwise known as the

rust-belt effect.58 Some counties in Ohio, Pennsylvania, and West Virginia saw the

percentage of jobs in manufacturing in their counties decrease dramatically during the

period studied, and the erosion of the northern manufacturing base has had an especially

adverse effect on communities throughout the northern Appalachian states. In fact,

trends in manufacturing that have helped diminish the number of distressed counties in

Southern Appalachia have increased the number of distressed counties in the North.

Furthermore, in contrast to the growing population of the South, many northern
20

Appalachian counties are experiencing steady outmigration. In general, however, the

northern Appalachian sub-region fared well in terms of distressed counties throughout the

period studied.

To summarize, distressed status in Appalachia is best understood in the context of

a variety of trends, including what may be considered regional trends specific to the

north, central, and southern Appalachian sub-regions. A range of regional,

macroeconomic, and policy factors have been presented in this and previous sections as

factors that have had a major impact on distressed levels. Furthermore, additional

macroeconomic trends have likely had an adverse impact on distressed status both in

Appalachia and the nation during the period studied, including the lack of real wage

growth in many unskilled manufacturing and service-sector jobs since the mid-1970s, and

the general widening of income inequality both nationally and regionally.59 While these

factors and the previously related macroeconomic trends and policy measures have not

been analyzed statistically for this report, they have been widely commented upon as

sources fueling trends in poverty both nationally and regionally.60 A separate statistical

analysis of these trends, though beyond the scope of this research, is certainly an area

worthy of future research consideration. The next section of this report will use statistical

analyses to further explore some of these macroeconomic trends. It will also attempt to

determine other factors that may be associated with distress in the Appalachian Region.

Other Factors Associated with Distress

To corroborate some of the trends that are apparent in the analysis of the number

and general location of distressed counties over time, this section of the report uses

statistical modeling techniques to determine factors associated with persistent distress and

a county's ability to move out of distressed status. It does not examine these factors

controlling for the influence of the previously mentioned macroeconomic and policy

trends, though acknowledges that such factors have likely influenced distressed status.

Logistic regression and statistical comparisons of means are the two types of statistical

analyses used in the analysis below. In general, logistic regression analysis estimates the

effects of different variables on the probability of a certain type of outcome, which in the
21

case of this research is the probability of a county either remaining distressed or moving

out of distressed status. Two models are developed: one that can be broadly

characterized as the socioeconomic model and one that can be characterized as the

economic structure model. These models test only persistently distressed counties and

counties that have moved out of distress; thus, they do not include Appalachian counties

that were never distressed. In addition to the logistic regression models, other statistical

tests, primarily involving the comparison of means, are also used to analyze factors that

may contribute to distress or the movement out of distress. Explanations of all the

statistical techniques used in this analysis, along with the various assumptions

incorporated in the modeling, are included in Appendix C. In sum, the statistical

analyses, taken in context with the previously mentioned macroeconomic and policy

trends, provide an indication of factors that have been associated with both the declining

number of distressed counties in the Appalachian Region and the inability of some

Appalachian counties to emerge from distress between 1960 and 1990.

The results of the logistic regression analyses support some of the earlier

hypotheses concerning macroeconomic factors, while providing further insight regarding

factors associated with distress in the Appalachian Region. Both the socioeconomic and

the economic structure logistic regression models had exceptionally high prediction

rates.61 According to the socioeconomic model (see Appendix C, Model 1) factors

contributing to a county moving out of distress between 1960 and 1990 included high

rates of employment in manufacturing; high educational attainment rates; a high

percentage of the population living in urban areas; a low percentage of minorities; and a

county's location in the southern Appalachian sub-region. According to the economic

structure model (see Appendix C, Model 2), the factors associated with a county moving

out of distressed status were a county's ability to attract retirees; high levels of

manufacturing; and location in a metropolitan area. Factors associated with counties

remaining distressed were high levels of employment in mining or government.

The other statistical tests in this analysis were consistent with findings of the

logistic regression analysis. The remainder of this section will describe in greater detail

the factors associated with distress as determined by the statistical methods used in this

analysis. For the sake of clarity, rather than considering the individual models and
22

statistical analyses in turn, the following analysis will generally discuss the various

factors that were determined by the statistical tests to be influential in determining

distressed status in Appalachian counties over time.

Locational and Demographic Factors

The socioeconomic logistic regression model clearly indicates that one of the

factors associated with a county's ability to emerge from distressed status is its location in

the southern part of the ARC region. A county's location in the southern sub-region of

Appalachia was the most influential variable in predicting distressed status in the

socioeconomic model. As previously mentioned, more than 75 percent of the counties in

Appalachia that emerged from distress between 1960 and 1990 were in the southern part

of the region. Thus, the socioeconomic model further confirms that a county's ability to

emerge from distress was significantly enhanced by its location in Southern Appalachia.

While regional trends certainly have had an impact upon distressed status in the

Appalachian Region, other locational factors also seem to be influential in determining

distress. Counties that became part of a metropolitan area clearly had an easier time

emerging from distress than counties that had not become part of a metropolitan area

(Table 4). Seventeen of the counties that were distressed in 1960 but no longer

Table 4

Locational Characteristics of Appalachian Counties

APPALACHIA

DISTRESSED 1960,

NOT 1990

DISTRESSED 1960

AND 1990

% Urban Pop. 1960 47.21% 22.52% 15.14%

 % Urban Pop.19901

47.22% 24.25% 15.39%

Metro County 1963 42 2 1

Metro County 19931

109 19 3

Adjacent to Metro County

1993

137 38 29

1 t < 0.05 (comparison between distressed 1960/1990 and distressed 1960/not 1990)

For a detailed description of the data sources, see Appendix D.

distressed in 1990 had become officially designated metropolitan counties during that

time. Many of these counties had grown because of the urban spread effects from

southern cities in and outside the Appalachian Region, such as Atlanta, Birmingham,

Chattanooga, and Knoxville, that experienced tremendous growth during the period
23

studied. Metropolitan counties with populations ranging between 250,000 and 1 million

were the most likely of all metropolitan counties to have emerged from distress.

While counties that became parts of metropolitan areas saw their income,

employment, and poverty rates improve to the point where they were no longer

distressed, a more interesting finding may be that metropolitan adjacency was not a

significant factor in a county's ability to emerge from distress. Indeed, counties adjacent

to metropolitan areas did not necessarily fare any better than counties that were not

adjacent to metropolitan areas. Moreover, the a review of the data reveals that a number

of counties that were neither part of a metropolitan area nor adjacent to a metropolitan

area nonetheless managed to successfully move out of distressed status during the period

studied. Such a finding is important because Appalachia is relatively more rural than the

rest of the United States, providing hope for a number of counties that have little

possibility of benefiting from metropolitan growth.62

The percentage of people living in urban areas, as shown in Table 4, highlights

the rural nature of Appalachia. By 1990, 75 percent of the American population was

living in what the census defined as an urban area; but this number was remarkably lower

in Appalachia (47 percent) and even more so in the persistently distressed counties (15

percent). According to the census, urban areas are generally "places" with 2,500 people

or more. It is important to understand the differences between urban and metropolitan

areas, and likewise rural and nonmetropolitan areas: urban areas are not necessarily

metropolitan areas or parts of metropolitan areas; and nonmetropolitan areas are not

necessarily rural. In the case of Appalachian nonmetropolitan counties, such “urban"

areas largely refer to towns with populations of 2,500 or more, and small cities with

populations below 50,000.

The results of the socioeconomic model confirm the relative importance of rural

locations in determining distressed status. The results indicate that counties moving out

of distress typically had a greater percentage of people living in “urban areas” than

counties that remained distressed. While a number of nonmetropolitan counties and

adjacent nonmetropolitan counties were able to emerge from distress, it seems that the

likelihood of such counties emerging from distress is increased when it has a greater

percentage of its population living in "urban areas." In sum, though counties do not
24

necessarily need to be proximate to metropolitan areas to increase their chances of

emerging from distress, counties with a greater majority of people living in what may be

considered urban areas are more likely to have emerged from distress than counties with

fewer people living in urban areas. Not surprisingly, it is the most rural counties in

Appalachia, counties with a relatively dispersed population, that have remained

persistently distressed over time.

Employment by Type of Industry and Distress

Employment by industry is also an important factor relating to a county's ability

to emerge from distress as indicated by both logistic regression models and the variables

included in Tables 5 and 6. The socioeconomic model indicated that counties with a

lower percentage of the workforce employed in manufacturing were less likely to emerge

from distress than counties with higher rates of the workforce employed in

manufacturing.

Table 5

USDA Economic Research Service Economic Typology Variables

APPALACHIAN

TOTAL

DISTRESSED 1960,

NOT 1990

DISTRESSED 1960

AND 1990

Farming Dependent 62 2

Mining Dependent1

41 4 30

Manufacturing Dependent1

121 48 18

Government Dependent1

23 5 14

Services Dependent 31 10 8

Non-Specialized1

177 47 26 1 t < 0.05 (comparison between distressed 1960/1990 and distressed 1960/not 1990)

For a detailed description of the data sources, see Appendix D.

The economic structure model provided similar results, indicating that

manufacturing-dependent counties were more likely to have emerged from distress than

counties that were not manufacturing dependent. In short, counties with a high

percentage of the workforce employed in manufacturing showed a tremendous ability to

emerge from distress. As previously mentioned, however, an increase in manufacturing

jobs, though providing the ability to lift counties out of distressed status, has not

necessarily brought wages in many Appalachian counties up to the levels of the national

average. While increased employment in manufacturing has enabled many counties in
25

the Appalachia Region to move out of distress, it does not necessarily improve

socioeconomic conditions to the point where they compare favorably with national

averages. In other words, manufacturing may be a prescription for counties moving out

of distress, but it is not necessarily a sufficient condition for overall economic prosperity.

This finding implies that wage-based competition in industrial recruitment may have

long-term negative impacts upon a community's economy.

While manufacturing may be associated with counties moving out of distressed

status, this research indicates that a high percentage of jobs in mining is associated with

counties remaining distressed. Though not significant in the socioeconomic model, the

economic structure model suggests that mining-dependent counties were more likely to

remain distressed over time.63 Many of the Central Appalachian counties that have

remained persistently distressed, especially in Kentucky, West Virginia, and

Southwestern Virginia, are considered coal-dependent counties by the UDSA Economic

Research Service (ERS).64 In fact, most of the mining-dependent counties in the region,

75 percent of the total, were persistently distressed. Though coal mining per se does not

result in a county being distressed, research elsewhere regarding "coal counties" has

demonstrated that, in general, such counties lag behind even neighboring counties in real

per capita income, income distribution, income variability, percentage of families below

the poverty line, unemployment, variability of unemployment, and such social measures

as infant mortality and high school dropout rates. 65 Such research concludes that these

poor socioeconomic conditions serve to discourage residents from making human capital

investments that could potentially improve their conditions in the future.

Table 6

Percentage Employed by Industry

U.S.

AVERAGE

APPALACHIAN

AVERAGE

DISTRESSED 1960,

NOT 1990

DISTRESSED 1960

AND 1990

Services 19601

55.38% 47.96% 41.52% 45.98%

Services 19901

72.75% 65.91% 56.40% 63.32%

Manufacturing 19601

27.69% 32.79% 27.49% 15.46%

Manufacturing 19901

17.69% 23.41% 30.43% 17.48%

Mining 19601

1.01% 3.39% 2.87% 16.90%

Mining 19901

.63% 1.52% 1.29% 8.92%

Ag, Fish, Forest 1960 6.69% 7.14% 18.77% 13.33%

Ag, Fish, Forest 1990 2.69% 2.34% 3.90% 3.01% 1 t < 0.05 (comparison between distressed 1960/1990 and distressed 1960/not 1990)

For a detailed description of the data sources, see Appendix D.
26

While the percentage employed in service-based jobs is not statistically

significant in either of the logistic regression models, persistently distressed counties in

the region have a higher percentage of service jobs than the counties that have moved out

of distress, which suggests that many of the service-based jobs in such counties pay low

wages. Indeed, research elsewhere has suggested that service jobs pay lower wages than

other types of jobs in rural areas, and the change in industrial structure from

manufacturing to service-based employment in rural areas had cut average pay in such

areas by 3 percent in the early 1980s.66 However, individual types of employment aside,

possibly the most important characteristic associated with distress is the extent of

employment diversification within a county. Most of the counties that were never

distressed—and hence have historically had better socioeconomic characteristics than

both the persistently distressed counties and the counties that moved out of distress—are

considered "nonspecialized" by the ERS, implying greater economic diversity in such

counties, or at least a lack of dependence upon a specific industry. Furthermore, there

was a statistical difference between the persistently distressed counties and the counties

that had moved out of distress in terms of specialization, as the number of counties that

had emerged from distress and were nonspecialized was significantly greater than the

number of counties that remained distressed and were nonspecialized.

Social Factors Associated with Distress

A variety of social factors were associated with a county either remaining

distressed or having the ability to move out of distress. Educational attainment rates were

significantly correlated with a county's ability to move out of distress, as demonstrated in

the socioeconomic model, as well as in the statistical comparison of means. In the

socioeconomic model, high school educational attainment rates were used as a proxy for

educational rates in general, and as the results in Table 7 indicate as such rates improved,

the chances decreased that a county would be persistently distressed. What may be the

most interesting finding in terms of educational attainment is that in 1960 there was no

significant statistical difference regarding the percentage of the population who had some
27

college between the counties that would remain distressed and the counties that would

eventually emerge from distress. But by 1990 this had changed—college educational

attainment rates had significantly improved in the counties that had moved out of distress

when compared with counties that remained distressed. A variety of factors could explain

such change. Perhaps an increase in higher-skilled jobs drew educated people to the

counties that emerged from distress, while it is also likely that such counties were better

able to retain their more educated constituents. Thus, while it is difficult to ascertain

causal relationships using statistical modeling, it is nonetheless clear that there was a

correlation between educational attainment rates within a county and a county's ability to

emerge from distress.

Table 7

 Education Characteristics of Appalachian Counties

APPALACHIAN

AVERAGE

DISTRESSED 1960,

NOT 1990

DISTRESSED 1960

AND 1990

12+ yrs. of education 19601

32.84% 21.99% 20.54%

12+ yrs. of education 19901

63.87% 58.55% 54.26%

 Some College 1960 11.33% 8.22% 7.52%

 Some College 1990* 33.33% 26.95% 21.37% 1 t < 0.05 (comparison between distressed 1960/1990 and distressed 1960/not 1990)

For a detailed description of the data sources, see Appendix D.

Another social factor related to distress was race, especially for counties in the

South. Southern Appalachian counties with a relatively high percentage of blacks were

far less likely to emerge from distress than counties with predominantly white

populations. The counties that moved out of distress in Southern Appalachia had

nonwhite populations of 11 and 9 percent in 1960 and 1990 respectively, while the

counties in Southern Appalachia that remained distressed had nonwhite populations of 38

and 33 percent in those same years.

The population’s age distribution was another factor that contributed to a county

remaining distressed according to the socioeconomic model. Counties that remained

distressed in 1990 had a higher percentage of children and the elderly residing in their

counties than the counties that had emerged from distress. People in these two age

groups are often considered dependents, as they typically do not participate in the

workforce. Indeed, as Table 8 shows, persistently distressed counties are those that are
28

Table 8

USDA Economic Research Service Policy Typology Variables

APPALACHIAN

TOTAL

DISTRESSED 1960,

NOT 1990

DISTRESSED 1960

AND 1990

Retirement Destination1

20 14 2

Federal Lands 23 13 5

Transfer Dependent1

85 9 67

Commuter Dependent 69 27 24 1 t < 0.05 (comparison between distressed 1960/1990 and distressed 1960/not 1990)

For a detailed description of the data sources, see Appendix D

highly dependent on federal transfer payments. A greater percentage of the population in

these categories indicates a higher percentage of dependents per worker in a county,

which is typically less conducive to strong economic conditions as there is a lower

percentage of people participating in the labor force. However, it is important to realize

that a higher percentage of the elderly is not always the sign of weak economic

conditions. The economic structure model indicated that counties that were serving as

retirement destinations were more likely to move out of distressed status than counties

that were not. Such counties typically attract relatively wealthy retirees and are often

endowed with amenities that make them tourist destinations as well. Finally, it is

interesting to note that neither a high share of federal ownership of land in a county nor

high levels of commuting dependence proved to be significantly associated with changes

in distressed status or persistent distress.

As the foregoing analysis shows, a variety of factors are associated with a

county's ability to move out of distressed status, ranging from the impact of

macroeconomic factors to amenities that may attract retirees or tourists. This analysis of

county-level factors associated with distress, combined with the aforementioned

macroeconomic and policy-related issues, provides a complex yet relatively clear

indication of why many of the counties in the Appalachian Region were able to emerge

from distress between 1960 and 1990, while others remained distressed during that same

period.
29

V. Conclusions

Tremendous progress was made in reducing the number of distressed counties

within the Appalachian Region between 1960 and 1980 as the number declined sharply

from 214 in 1960 to 152 in 1970 and to 79 in 1980. These gains, however, were eroded

during the 1980s as the number of distressed counties rose steadily to 106 in 1990. Of

the 214 counties that were distressed in 1960, 98 counties remained distressed and 116

were no longer distressed by 1990.

Persistent distress remains a considerable problem; approximately one-quarter of

the Appalachian counties remain distressed today. The Appalachian trends clearly

mirrors national trends as the number of distressed counties in the rest of the United

States fell from 676 in 1960 to 286 in 1980, and then steadily rose to 325 in 1990. By the

year 2000 there will be 355 distressed counties outside Appalachia.

The rise in regional and national distress levels can be attributed to several

macroeconomic national and international trends, as well as changes in public policies

that are largely outside the scope and influence of the ARC.

• The inflation and energy price increases of 1970s, coupled with the anti-inflation and

strong dollar policies of the early 1980s, brought about a sequence of recessions that

shocked many of the traditional employment sectors of the Appalachian Region and

generated higher levels of structural unemployment.

• Anti-inflation policies also shifted national economic policies away from the full

employment policies prevalent during the 30 years after World War II.

• The energy boom in the 1970s and bust in the 1980s particularly affected the region’s

coal-mining sectors.

• Federal poverty alleviation spending as a share of the national economy fell sharply

in the 1980s but recovered in the 1990s, while federal economic development funding

fell sharply in the 1980s but did not fully recover.

• Household income and industrial wage inequality have increased nationally, and

these trends have particularly affected regions that are overrepresented in lower-wage

sectors.
30

Within the Appalachian Region, however, the results of the analysis of the

region’s county-level economies have identified a number of significant factors that are

associated with the movement of counties out of distressed status compared with

persistently distressed counties:

• A higher share of manufacturing employment;

• Counties that became part of metropolitan areas, particularly in the South;

• A more diversified economy as reflected by a nonspecialized local economy;

• Higher educational attainment rates for both high school completion and some

college;

• A higher percentage of the population living in urban areas (i.e., towns and small

cities); and

• The ability of a county to attract retirees to establish residency.

In addition, this research identified several factors that were associated with persistent

distressed status as compared with counties that moved out of distress:

• A higher share of mining employment (half of the persistently distressed counties

were mining dependent);

• A higher share of minority populations;

• A higher share of children and elderly dependent populations; and

• A higher dependence on government transfer payments.

Key Issues

A variety of issues are associated with the changing status of distress within the

Appalachian Region, including macroeconomic and policy factors, as well as local

factors such as location, education, and the role of economic diversification. Many of

these factors are beyond the control of regional and local economic development

institutions. Some factors, however, can be influenced over the longer term by regional

and local development institutions, particularly educational achievement levels, and the

extent of economic diversification. One factor that stands out as potentially subject to

regional and local influence is the extent of manufacturing and the degree of economic
31

diversification in local economy. Clearly, the overall evidence shows that a high share of

manufacturing employment is a good predictor of improvement during the period

between 1960 and 1990; yet the story varies by sub-region. In the northern sub-region the

absence of many distressed counties, coupled with the high degree of economic

diversification in 1960, masks much of the hardship that the northern sub-region

experienced with the loss of manufacturing employment. By contrast, the relatively high

levels of distress in the southern sub-region were improved by the movement of

manufacturing employment into the South. Yet today many of these same industries are

vulnerable to the impacts of plant relocation and exports. So while manufacturing may

have played a positive role in the past for reducing distress, the prospects for the future

role of manufacturing are decidedly different. Indeed, the outlook is good only for the

most productive, capital-intensive manufacturing sectors that are supported by a complex

of high technology suppliers and professional services in such fields as engineering,

product design, marketing, and finance.

Another issue is the vulnerability of coal-dependent counties to the fluctuations of

energy prices and the demand for coal. The rising distress in the coal-dependent counties

points to the need for greater economic diversification efforts to widen the economic

base.

Educational attainment is another prominent factor in predicting improvement.

Future trends in the knowledge-based economy leave little doubt that educational

attainment will continue to be a key factor for improving the prospects for distressed

counties. Perhaps the only concern for local officials is the oft-repeated problem that the

most educated students often leave the distressed counties for better opportunities in more

prosperous areas. Some states have sought to retain this educated talent by providing

entrepreneurial education in order to highlight prospects for local business opportunities

that could create economic anchors in the communities.

Another issue that emerges is the relative importance of urbanized areas in

distressed counties, including the influence of towns and small cities. The foregoing

findings indicate that these urbanized centers play a vital role in the economic base of

distressed counties. It may be that past efforts to revitalize these smaller urban centers
32

have paid off, although the foregoing analysis does not provide enough information to

indicate how this may have played out. Clearly, more research is needed on this issue.

The overarching issue, however, is that so much of the improvement in both

Appalachia and the rest of the United States occurred during a period when national

policy was supportive of full employment and poverty alleviation efforts. This fact

suggests that regional economic development is most likely to take place when national

policies create the conditions to support it.

This research also indicates the number of distressed counties in the region has

generally been rising since the early 1980s, and many Appalachian counties that had

seemingly emerged from distress have again become distressed. In FY 2000 there were

111 distressed counties in the region, although partly because new counties have been

added to the region. This rise in distress is especially worrisome considering the

economic growth that has taken place in the United States throughout the past decade.

In the 1990s, major changes have occurred in national policy and macroeconomic

factors that have altered the conditions under which the ARC program is being

implemented. One striking change is that as of December 1999, the nation is near full

employment with a national unemployment rate at a 30-year low. In addition, poverty

alleviation expenditures have risen to all-time highs under the Clinton administrationso

why has distress widened both nationally and regionally?

Several factors specific to the Appalachian Region’s economy suggest an answer.

First, import penetration and plant relocation in labor-intensive industries have had a

disproportionate impact on Appalachia, and Southern Appalachia in particular, because

the regional economy is over-represented in such sectors. Second, income and wage

inequality continues to be a problem for the region. Income inequality has widened both

nationally and regionally, and despite a period of strong economic growth and low

unemployment, 1997 national income figures indicate that there has been no moderation

of income inequality.67 Within the region, wage pressures have mounted on laborintensive industries affected by plant closures as there is downward pressure on the

remaining workforce in these sectors. Indeed, while job creation has been robust during

the past ten years, the issue of job quality remains a major concern. Recent analysis of

Appalachian employment by job quality in metropolitan areas presents a mixed picture.
33

For 1997, female employment was over-represented in less skilled jobs, while male

employment had a relatively higher percentage share of higher skilled employment as

compared with smaller metropolitan areas elsewhere in the United States.68 Nonetheless,

the data also show an earnings gap for both males and females for all types of jobs,

ranging from less skilled to elite jobs.

Third, the industrial mix of the overall economy remains over-represented in

lower wage manufacturing, service, tobacco farming, and extractive sectors, and underrepresented in the high growth, high-wage sectors. For instance, Appalachian

employment in occupations focused on the design, programming, maintenance, and

repair of computing and communications technologies has grown robustly during the past

ten years to 350,000 high-tech workers, but still stands at less than 5 percent of all

information technology (IT) jobs nationally (far below the region's 7.2 percent share of

national employment). And while IT jobs are forecast to grow to 417,000 by 2006, this

share will represent a declining share of the nation's IT job base.69

Another factor is that the region's population is aging at a rate greater than the

nation as a whole. Partly, this more rapid aging is a result of continued out-migration of

youth, but the net effect is to increase the dependent, non-working share of the

population, thereby depressing per capita income. Finally, while poverty alleviation

programs have expanded in the past several years, reaching historic highs, federal

economic development funding remains far below the historic high point, with 1999

inflation-adjusted levels amounting to only 38 percent of 1978 levels.70 Thus, the

national effort to fund economic development has lessened, leaving distressed regions

with fewer resources to catch up with the rapidly growing national economy. Taken

together, these factors probably account for the rise in distress during the economic

expansion of the 1990s.

Policy Implications

These findings and trends imply a need for a greater policy focus on economic

diversification efforts, particularly cultivating job creation in the high-growth, higher

wage sectors, including the professional service sectors. Obviously, this is easier said
34

than done. But the strategic challenge is focusing on developing businesses that demand

jobs with higher skills and pay. Meanwhile, the changing role of manufacturing in a

diversified economy means that retaining manufacturing in a local economy will require

a greater emphasis on stimulating business formation in so-called producer services, such

as engineering, product design, marketing, finance, and information services.

The role of urbanized areas in distressed counties also highlights the need to

rethink investments for revitalizing the towns and cities in these counties so that they are

positioned to attract businesses, particularly those providing professional and business

services. While many economic developers have focused on the need for laying the

foundations for a high-tech infrastructure in nonmetropolitan areas, there is little solid

research to guide such efforts. In addition, more needs to be known about the urban

amenities that are needed in towns and small cities to attract and retain professionals in

such areas.

Another implication of this research is the increasing importance of education and

human capital development in the knowledge-based economy. Distressed areas cannot

compete without additional resources being devoted to improving educational

achievement at all levels. Given the limited local resources for education, such an

expanded effort must rely on outside funds from the federal and state levels. In addition,

given the growing share of dependent populations in the region, increased investments in

job training and skills upgrading will help expand the effective labor supply. Moreover,

additional adult educational opportunities would help expand employment for the

underemployed. Furthermore, such employment and training investments will enhance

productivity of existing industry and thereby improve the job creation and retention

potential of the region.

These findings also suggest that while there has been considerable economic

growth and social progress in the Appalachian Region, regional development efforts are

most effective when implemented in a context of accommodating macroeconomic trends

and supportive national policies. In light of the trends in federal economic development

funding, there seems to be a case for expanding the national effort for distressed areas as

the federal commitment has not kept pace with the growth in GDP.
35

In conclusion, despite remarkable improvement in Appalachia's number of

distressed counties between 1960 and 1990, a significant number of counties in the region

still are distressed and have remained persistently distressed over time. To seriously

address such persistent distress, as well as the growing divide between the major

metropolitan areas and non-metropolitan regions, the ARC and other regional

development agencies will likely need more federal government support. A renewed

commitment similar to the one that inspired the establishment of the ARC and the

regional development policies of the 1960s is an important step for seriously addressing

the socioeconomic problems of Appalachia's distressed counties. Poverty, low wages,

and limited employment opportunities are a way of life for many people in such counties,

and the embedded nature of distress in such places requires a strategic national and

regional effort to solve the problem of persistent distress.
36

VI. Appendix A: ARC Distressed Counties by Year

1960 Distressed Counties (214)

AL BIBB KY ELLIOTT MS NOXUBEE TN HAWKINS

AL BLOUNT KY ESTILL MS OKTIBBEHA TN JACKSON

AL CHEROKEE KY FLEMING MS PONTOTOC TN JOHNSON

AL CHILTON KY FLOYD MS PRENTISS TN MC MINN

AL CLAY KY GREENUP MS TIPPAH TN MACON

AL CLEBURNE KY HARLAN MS TISHOMINGO TN MARION

AL COOSA KY JACKSON MS UNION TN MEIGS

AL CULLMAN KY JOHNSON MS WEBSTER TN MONROE

AL DE KALB KY KNOTT MS WINSTON TN MORGAN

AL ELMORE KY KNOX NC ALLEGHANY TN OVERTON

AL FAYETTE KY LAUREL NC ASHE TN PICKETT

AL FRANKLIN KY LAWRENCE NC AVERY TN POLK

AL JACKSON KY LEE NC CHEROKEE TN PUTNAM

AL LAMAR KY LESLIE NC CLAY TN RHEA

AL LAWRENCE KY LETCHER NC GRAHAM TN SCOTT

AL LIMESTONE KY LEWIS NC JACKSON TN SEQUATCHIE

AL MARION KY LINCOLN NC MACON TN SEVIER

AL PICKENS KY MC CREARY NC MADISON TN SMITH

AL RANDOLPH KY MADISON NC MITCHELL TN UNICOI

AL ST. CLAIR KY MAGOFFIN NC POLK TN UNION

AL SHELBY KY MARTIN NC SWAIN TN VAN BUREN

AL TALLADEGA KY MENIFEE NC WATAUGA TN WARREN

AL WALKER KY MONROE NC WILKES TN WHITE

AL WINSTON KY MORGAN NC YANCEY VA BATH

GA DADE KY OWSLEY OH ADAMS VA BLAND

GA DAWSON KY PERRY OH GALLIA VA BUCHANAN

GA FANNIN KY PIKE OH JACKSON VA CARROLL

GA FRANKLIN KY POWELL OH MEIGS VA DICKENSON

GA GILMER KY PULASKI OH MONROE VA FLOYD

GA HEARD KY ROCKCASTLE OH PIKE VA GRAYSON

GA LUMPKIN KY ROWAN OH VINTON VA HIGHLAND

GA MADISON KY RUSSELL PA FAYETTE VA LEE

GA MURRAY KY WAYNE PA HUNTINGDON VA RUSSELL

GA PICKENS KY WHITLEY TN BLEDSOE VA SCOTT

GA RABUN KY WOLFE TN CAMPBELL VA TAZEWELL

GA TOWNS MD GARRETT TN CANNON VA WISE

GA UNION MS ALCORN TN CARTER VA WYTHE

GA WHITE MS BENTON TN CLAIBORNE WV BARBOUR

KY ADAIR MS CALHOUN TN CLAY WV BOONE

KY BATH MS CHICKASAW TN COCKE WV BRAXTON

KY BELL MS CHOCTAW TN CUMBERLAND WV CALHOUN

KY BREATHITT MS CLAY TN DE KALB WV CLAY

KY CARTER MS ITAWAMBA TN FENTRESS WV DODDRIDGE

KY CASEY MS KEMPER TN GRAINGER WV FAYETTE

KY CLAY MS LOWNDES TN GREENE WV GILMER

KY CLINTON MS MARSHALL TN GRUNDY WV GRANT

KY CUMBERLAND MS MONROE TN HANCOCK WV GREENBRIER
37

1960 Continued

WV HAMPSHIRE WV MINGO WV RALEIGH WV UPSHUR

WV HARDY WV MONROE WV RANDOLPH WV WAYNE

WV LINCOLN WV MORGAN WV RITCHIE WV WEBSTER

WV LOGAN WV NICHOLAS WV ROANE WV WIRT

WV MC DOWELL WV PENDLETON WV SUMMERS WV WYOMING

WV MASON WV POCAHONTAS WV TAYLOR

WV MERCER WV PRESTON WV TUCKER

1970 Distressed Counties (161)

AL BIBB KY LEWIS MS WINSTON TN MONROE

AL CHILTON KY LINCOLN NC ALLEGHANY TN MORGAN

AL CLAY KY MC CREARY NC ASHE TN OVERTON

AL COOSA KY MAGOFFIN NC AVERY TN PICKETT

AL DE KALB KY MARTIN NC CHEROKEE TN RHEA

AL ELMORE KY MENIFEE NC CLAY TN SCOTT

AL FAYETTE KY MONROE NC GRAHAM TN SEQUATCHIE

AL FRANKLIN KY MORGAN NC JACKSON TN UNICOI

AL JACKSON KY OWSLEY NC MACON TN UNION

AL LAMAR KY PERRY NC MADISON VA BATH

AL LAWRENCE KY PIKE NC MITCHELL VA BLAND

AL PICKENS KY POWELL NC SWAIN VA BUCHANAN

AL RANDOLPH KY PULASKI NC WATAUGA VA DICKENSON

GA GILMER KY ROCKCASTLE NC YANCEY VA LEE

GA TOWNS KY ROWAN OH ADAMS VA RUSSELL

GA UNION KY RUSSELL OH JACKSON VA SCOTT

KY ADAIR KY WAYNE OH MEIGS VA WISE

KY BATH KY WHITLEY OH NOBLE WV BARBOUR

KY BELL KY WOLFE OH PIKE WV BOONE

KY BREATHITT MD GARRETT OH VINTON WV BRAXTON

KY CARTER MS ALCORN TN BLEDSOE WV CALHOUN

KY CASEY MS BENTON TN CAMPBELL WV CLAY

KY CLAY MS CALHOUN TN CANNON WV DODDRIDGE

KY CLINTON MS CHICKASAW TN CARTER WV FAYETTE

KY CUMBERLAND MS CHOCTAW TN CLAIBORNE WV GILMER

KY ELLIOTT MS CLAY TN CLAY WV GRANT

KY ESTILL MS KEMPER TN COCKE WV HAMPSHIRE

KY FLOYD MS LOWNDES TN CUMBERLAND WV HARDY

KY HARLAN MS MARSHALL TN FENTRESS WV LEWIS

KY JACKSON MS MONROE TN GRAINGER WV LINCOLN

KY JOHNSON MS NOXUBEE TN GREENE WV LOGAN

KY KNOTT MS OKTIBBEHA TN GRUNDY WV MC DOWELL

KY KNOX MS PONTOTOC TN HANCOCK WV MASON

KY LAUREL MS PRENTISS TN JACKSON WV MINGO

KY LAWRENCE MS TIPPAH TN JOHNSON WV MONROE

KY LEE MS TISHOMINGO TN MACON WV NICHOLAS

KY LESLIE MS UNION TN MARION WV PENDLETON

KY LETCHER MS WEBSTER TN MEIGS WV POCAHONTAS
38

1970 Continued

WV PRESTON WV ROANE WV UPSHUR

WV RANDOLPH WV SUMMERS WV WEBSTER

WV RITCHIE WV TUCKER WV WIRT

1980 Distressed Counties (78)

AL LAWRENCE KY LESLIE MS MARSHALL TN MONROE

AL PICKENS KY LETCHER MS NOXUBEE TN MORGAN

GA UNION KY LEWIS MS OKTIBBEHA TN OVERTON

KY ADAIR KY LINCOLN MS WINSTON TN PICKETT

KY BATH KY MC CREARY NC GRAHAM TN SCOTT

KY BELL KY MAGOFFIN NC MADISON TN SEQUATCHIE

KY BREATHITT KY MENIFEE NC SWAIN VA LEE

KY CARTER KY MONROE OH ADAMS WV BARBOUR

KY CASEY KY MORGAN OH PIKE WV BRAXTON

KY CLAY KY OWSLEY TN CAMPBELL WV CALHOUN

KY CLINTON KY POWELL TN CLAIBORNE WV CLAY

KY CUMBERLAND KY PULASKI TN CLAY WV DODDRIDGE

KY ELLIOTT KY ROCKCASTLE TN COCKE WV LINCOLN

KY ESTILL KY RUSSELL TN CUMBERLAND WV MC DOWELL

KY HARLAN KY WAYNE TN FENTRESS WV MINGO

KY JACKSON KY WHITLEY TN GRAINGER WV SUMMERS

KY KNOTT KY WOLFE TN GRUNDY WV WAYNE

KY KNOX MS BENTON TN HANCOCK WV WEBSTER

KY LAWRENCE MS CHOCTAW TN JACKSON

KY LEE MS KEMPER TN JOHNSON

1990 Distressed Counties (106)

AL PICKENS KY LAWRENCE KY WAYNE OH HARRISON

KY BATH KY LEE KY WHITLEY OH JACKSON

KY BELL KY LESLIE KY WOLFE OH LAWRENCE

KY BREATHITT KY LETCHER MS BENTON OH MEIGS

KY CARTER KY LEWIS MS CHOCTAW OH MONROE

KY CASEY KY LINCOLN MS CLAY OH PIKE

KY CLAY KY MC CREARY MS KEMPER OH SCIOTO

KY CLINTON KY MAGOFFIN MS MARSHALL OH VINTON

KY CUMBERLAND KY MARTIN MS NOXUBEE PA FAYETTE

KY ELLIOTT KY MENIFEE MS OKTIBBEHA PA GREENE

KY ESTILL KY MONROE MS TISHOMINGO TN CAMPBELL

KY FLOYD KY MORGAN MS WEBSTER TN COCKE

KY HARLAN KY OWSLEY MS WINSTON TN FENTRESS

KY JACKSON KY PERRY NC GRAHAM TN HANCOCK

KY JOHNSON KY PIKE NC SWAIN TN JOHNSON

KY KNOTT KY POWELL OH ADAMS TN MORGAN

KY KNOX KY ROCKCASTLE OH ATHENS TN SCOTT

KY LAUREL KY ROWAN OH GALLIA VA BUCHANAN
39

1990 Continued

VA DICKENSON WV DODDRIDGE WV MINGO WV TAYLOR

VA LEE WV FAYETTE WV MONROE WV UPSHUR

VA RUSSELL WV GILMER WV NICHOLAS WV WAYNE

VA WISE WV JACKSON WV POCAHONTAS WV WEBSTER

WV BARBOUR WV LEWIS WV RALEIGH WV WETZEL

WV BOONE WV LINCOLN WV RANDOLPH WV WIRT

WV BRAXTON WV LOGAN WV RITCHIE WV WYOMING

WV CALHOUN WV MC DOWELL WV ROANE

WV CLAY WV MASON WV SUMMERS

Distressed 1960 and 1990 (98)

AL PICKENS KY MAGOFFIN NC SWAIN WV CLAY

KY BATH KY MARTIN OH ADAMS WV DODDRIDGE

KY BELL KY MENIFEE OH GALLIA WV FAYETTE

KY BREATHITT KY MONROE OH JACKSON WV GILMER

KY CARTER KY MORGAN OH MEIGS WV LINCOLN

KY CASEY KY OWSLEY OH MONROE WV LOGAN

KY CLAY KY PERRY OH PIKE WV MC DOWELL

KY CLINTON KY PIKE OH VINTON WV MASON

KY CUMBERLAND KY POWELL PA FAYETTE WV MINGO

KY ELLIOTT KY ROCKCASTLE TN CAMPBELL WV MONROE

KY ESTILL KY ROWAN TN COCKE WV NICHOLAS

KY FLOYD KY WAYNE TN FENTRESS WV POCAHONTAS

KY HARLAN KY WHITLEY TN HANCOCK WV RALEIGH

KY JACKSON KY WOLFE TN JOHNSON WV RANDOLPH

KY JOHNSON MS BENTON TN MORGAN WV RITCHIE

KY KNOTT MS CHOCTAW TN SCOTT WV ROANE

KY KNOX MS CLAY VA BUCHANAN WV SUMMERS

KY LAUREL MS KEMPER VA DICKENSON WV TAYLOR

KY LAWRENCE MS MARSHALL VA LEE WV UPSHUR

KY LEE MS NOXUBEE VA RUSSELL WV WAYNE

KY LESLIE MS OKTIBBEHA VA WISE WV WEBSTER

KY LETCHER MS TISHOMINGO WV BARBOUR WV WIRT

KY LEWIS MS WEBSTER WV BOONE WV WYOMING

KY LINCOLN MS WINSTON WV BRAXTON

KY MC CREARY NC GRAHAM WV CALHOUN

Distressed 1960, Not Distressed 1990 (116)

AL BIBB AL CULLMAN AL LAWRENCE AL WALKER

AL BLOUNT AL DE KALB AL LIMESTONE AL WINSTON

AL CHEROKEE AL ELMORE AL MARION GA DADE

AL CHILTON AL FAYETTE AL RANDOLPH GA DAWSON

AL CLAY AL FRANKLIN AL ST. CLAIR GA FANNIN

AL CLEBURNE AL JACKSON AL SHELBY GA FRANKLIN

AL COOSA AL LAMAR AL TALLADEGA GA GILMER
40

Distressed 1960, Not Distressed 1990 Continued

GA HEARD MS PONTOTOC TN CLAY TN UNION

GA LUMPKIN MS PRENTISS TN CUMBERLAND TN VAN BUREN

GA MADISON MS TIPPAH TN DE KALB TN WARREN

GA MURRAY MS UNION TN GRAINGER TN WHITE

GA PICKENS NC ALLEGHANY TN GREENE VA BATH

GA RABUN NC ASHE TN GRUNDY VA BLAND

GA TOWNS NC AVERY TN HAWKINS VA CARROLL

GA UNION NC CHEROKEE TN JACKSON VA FLOYD

GA WHITE NC CLAY TN MC MINN VA GRAYSON

KY ADAIR NC JACKSON TN MACON VA HIGHLAND

KY FLEMING NC MACON TN MARION VA SCOTT

KY GREENUP NC MADISON TN MEIGS VA TAZEWELL

KY MADISON NC MITCHELL TN MONROE VA WYTHE

KY PULASKI NC POLK TN OVERTON WV GRANT

KY RUSSELL NC WATAUGA TN PICKETT WV GREENBRIER

MD GARRETT NC WILKES TN POLK WV HAMPSHIRE

MS ALCORN NC YANCEY TN PUTNAM WV HARDY

MS CALHOUN PA HUNTINGDON TN RHEA WV MERCER

MS CHICKASAW TN BLEDSOE TN SEQUATCHIE WV MORGAN

MS ITAWAMBA TN CANNON TN SEVIER WV PENDLETON

MS LOWNDES TN CARTER TN SMITH WV PRESTON

MS MONROE TN CLAIBORNE TN UNICOI WV TUCKER

Distressed 1960, 1970, 1980, 1990 (61)

AL PICKENS KY LEE MS BENTON TN MORGAN

KY BATH KY LESLIE MS CHOCTAW TN SCOTT

KY BELL KY LETCHER MS KEMPER VA LEE

KY BREATHITT KY LEWIS MS MARSHALL WV BARBOUR

KY CARTER KY LINCOLN MS NOXUBEE WV BRAXTON

KY CASEY KY MC CREARY MS OKTIBBEHA WV CALHOUN

KY CLAY KY MAGOFFIN MS WINSTON WV CLAY

KY CLINTON KY MENIFEE NC GRAHAM WV DODDRIDGE

KY CUMBERLAND KY MONROE NC SWAIN WV LINCOLN

KY ELLIOTT KY MORGAN OH ADAMS WV MC DOWELL

KY ESTILL KY OWSLEY OH PIKE WV MINGO

KY HARLAN KY POWELL TN CAMPBELL WV SUMMERS

KY JACKSON KY ROCKCASTLE TN COCKE WV WEBSTER

KY KNOTT KY WAYNE TN FENTRESS

KY KNOX KY WHITLEY TN HANCOCK

KY LAWRENCE KY WOLFE TN JOHNSON
41

Distressed Status of Counties Added to Region in FY 1999

Distressed 1960: Hale, AL; Macon, AL; Elbert, GA; Hart, GA; Yalobusha, MS

Distressed 1970: Hale, AL; Macon, AL; Elbert, GA; Yalobusha, MS

Distressed 1980: Hale, AL; Macon, AL

Distressed 1990: Macon, AL; Yalobusha, MS

Thus, based on ARC’s current definitions and projecting back for all 406 counties in the

region, the number of distressed counties by year was as follows:

1960: 219

1970: 165

1980: 80

1990: 109

In FY 2000 there are 111 distressed counties in the currently defined ARC Region.
42

VII. Appendix B: Maps 1-8
New York

Pennsylvania

Ohio

West 

 Virginia

Maryland

Virginia

Kentucky

Tennessee

North Carolina

South Carolina

Alabama

Georgia

Mississippi

Data Sources:

Unemployment: Census data from USDA, Economic Research Service (ERS), 1960;

Poverty: Office of Economic Opportunity data from USDA, ERS, 1960; 

Income: U.S. Department of Commerce, Bureau of the Census, 1960. 

Distressed counties have at least 150% of the 

U.S. average unemployment rate of 5.14%,

at least 150% of the U.S. poverty rate of 22.1%, 

and 67% or less of the U.S. per capita market 

income of $1,639, or 200% poverty and one

of the other two distressed indicators.

Economic Status

Distressed (214 counties)

Distressed Counties 

in Appalachia

1960

Map 1
New York

Pennsylvania

Ohio

West 

 Virginia

Maryland

Virginia

Kentucky

Tennessee

North Carolina

South Carolina

Alabama

Georgia

Mississippi

Data Sources:

Unemployment: Census data from USDA, Economic Research Service (ERS), 1970;

Poverty: Census data from USDA, ERS, 1970; 

Income: U.S. Department of Commerce, Bureau of Economic Analysis, 1970. 

Distressed counties have at least 150% of the 

U.S. average unemployment rate of 4.37%,

at least 150% of the U.S. poverty rate of 13.74%, 

and 67% or less of the U.S. per capita market 

income of $3,490, or 200% poverty and one

of the other two distressed indicators.

Economic Status

Distressed (161 counties)

Map 2

Distressed Counties 

in Appalachia

1970
New York

Pennsylvania

Ohio

West 

 Virginia

Maryland

Virginia

Kentucky

Tennessee

North Carolina

South Carolina

Alabama

Georgia

Mississippi

Data Sources:

Unemployment: U.S. Department of Commerce, Bureau of the Census, 1980;

Poverty: U.S. Department of Commerce, Bureau of the Census, 1980; 

Income: U.S. Department of Commerce, Bureau of Economic Analysis, 1980. 

Distressed counties have at least 150% of the 

U.S. average unemployment rate of 6.52%,

at least 150% of the U.S. poverty rate of 12.4%, 

and 67% or less of the U.S. per capita market 

income of $7,909, or 200% poverty and one

of the other two distressed indicators.

Economic Status

Distressed (78 counties)

Map 3

Distressed Counties 

in Appalachia

1980
New York

Pennsylvania

Ohio

West 

 Virginia

Maryland

Virginia

Kentucky

Tennessee

North Carolina

South Carolina

Alabama

Georgia

Mississippi

Distressed (106 counties)

Economic Status

Distressed counties have at least 150% of the 

U.S. average unemployment rate of 6.31%,

at least 150% of the U.S. poverty rate of 13.12%, 

and 67% or less of the U.S. per capita market 

income of $15,636, or 200% poverty and one

of the other two distressed indicators.

Data Sources:

Unemployment: U.S. Department of Commerce, Bureau of the Census, 1990;

Poverty: U.S. Department of Commerce, Bureau of the Census, 1990; 

Income: U.S. Department of Commerce, Bureau of Economic Analysis, 1990. 

Distressed Counties 

in Appalachia

1990

Map 4
New York

Pennsylvania

Ohio

West 

 Virginia

Maryland

Virginia

Kentucky

Tennessee

North Carolina

South Carolina

Alabama

Georgia

Mississippi Persistently distressed counties are those that

meet distressed criteria for both 1960 and 1990.

See maps 1 and 4 for the definition of distressed

counties in those two years. 

Persistently

Distressed Counties 

in Appalachia

1960 and 1990

Map 5

Persistently Distressed 

(98 counties)
New York

Pennsylvania

Ohio

West 

 Virginia

Maryland

Virginia

Kentucky

Tennessee

North Carolina

South Carolina

Alabama

Georgia

Mississippi Core distressed counties are those that

meet distressed criteria for 1960, 1970, 1980, 

and 1990. See maps 1, 2, 3, and 4 for the 

definition of distressed counties in those years. 

Core

Distressed Counties 

in Appalachia

1960, 1970, 1980, and 1990

Map 6

Core Distressed 

(61 counties)
unties in 1960

Distressed Counties in the United States, 1960

Map 7

Distressed counties have at least 150% of the U.S. average unemployment rate of 5.14%,at least 150% of the U.S. poverty rate of 22.1%, and 67% or less of the U.S. per capita market income of $1,639, or 200% poverty and oneof the other two distressed indicators.

nsus data from USDA, Economic Research Service (ERS), 1960;

conomic Opportunity data from USDA, ERS, 1960; 

tment of Commerce, Bureau of the Census, 1960. 
unties in 1990

. Department of Commerce, Bureau of the Census, 1990;

tment of Commerce, Bureau of the Census, 1990; 

tment of Commerce, Bureau of Economic Analysis, 1990. 

Distressed counties have at least 150% of the U.S. average unemployment rate of 6.31%,at least 150% of the U.S. poverty rate of 13.12%, and 67% or less of the U.S. per capita market income of $15,636, or 200% poverty and oneof the other two distressed indicators.

Distressed Counties in the United States, 1990

Map 8
51

VIII. Appendix C: Research Methodology

Distress Indicators

This report uses the ARC's current distress standards to determine the number of distressed counties in

both Appalachia and the entire nation in 1960, 1970, 1980, and 1990. Data to determine distress are drawn from

the U.S. Census, the Bureau of Economic Analysis, and the Office of Economic Opportunity. The indicators used

in this research are the same as the indicators that the ARC currently uses to determine distress with one exception:

unemployment rates are not calculated for three-year periods. Instead, this research calculates unemployment only

for the census years, primarily because it is difficult to get accurate and consistent county-level data for

unemployment for the years surrounding the 1960 census. Further information about data used in this analysis is

included in Appendix D.

Methodology used to determine distressed standards

Raw totals were calculated for each of the variables. For example, the total number of civilian unemployed in any

given year was calculated, as was the total number of people in the civilian labor force. National averages were

then determined using these total figures; for example, for unemployment the number of unemployed would be the

numerator and the civilian labor force the denominator.

Distressed standards were determined by the following calculations:

Poverty 200%: National Average x 2

Poverty 150%: National Average x 3/2

Unemployment 150%: National average x 3/2

PCMI: National Average x 2/3

National Averages and Distressed Standards (in parentheses) for each of the years are as follows:

1960 National Averages

Per Capita Market Income - $1,639.22 ($1,092.81)

Unemployment Rate – 5.14% (7.71%)

Poverty Rate – 22.10 (33.15%; 44.20%)

1970 National Averages

Per Capita Market Income - $3,490.37 ($2,326.91)

Unemployment Rate – 4.37% (6.55%)

Poverty Rate – 13.74% (20.61%; 27.48%)

1980 National Averages

Per Capita Market Income - $7,909.17 ($5,272.78)

Unemployment Rate – 6.52% (9.78%)

Poverty Rate – 12.40 (18.60%; 24.80%)

1990 National Averages

Per Capita Market Income - $15,635.85 ($10,423.90)

Unemployment Rate – 6.31% (9.47%)

Poverty Rate – 13.12% (19.68%; 26.24%)

Statistical Analyses

To determine factors associated with counties either remaining distressed or moving out of distressed

status, this research uses data from the 1960 and 1990 U.S. Censuses as well as the U.S. Department of

Agriculture's Economic Research Service (ERS). A more detailed description of all of the variables used in this
52

analysis is included in Appendix D. Determining factors associated with distress is somewhat limited by the lack

of consistent and available data over time. Nonetheless, a reasonable and fairly consistent set of variables is

available from both the 1960 and 1990 censuses, and it is believed that this report's analysis of such variables

provides a decent indication of factors associated with distress.

Two types of statistical methods are used to determine factors associated with distress. First, a statistical

technique called logistic regression analysis is used to predict the relationship between a single "dependent"

variable and multiple "independent" variables. The independent variables are used to predict the presence or

absence of a characteristic or outcome, which in this case is the presence or absence of economic distress. The

logistic regression techniques used in this analysis are a means of testing the probability of a county remaining or

moving out of distressed status given a set of social, demographic, or economic factors or conditions.71 Each

independent variable entered into the equation is assigned different levels of significance in its ability to predict the

outcome, but its ability to predict such outcome should be understood only as its ability to do so in the context of all

of the variables used in the equation.

In this analysis, variables that are significant at a rate of less than 0.05 are considered significant

contributors to a county's distressed status. R values provide a means for determining an independent variable's

contribution to the outcome relative to the other variables in the equation. R values demonstrate either a positive or

negative association with an outcome, and variables that have R values with higher absolute values (either positive

or negative) contribute more to the outcome than variables whose R values have lower absolute values.

This analysis employed two logistic regression models.

As mentioned in the literature, two models are used in this analysis. One can generally be referred to as

the socioeconomic model. This model includes mostly census information, and most of the variables are at the

ratio scale. The other model, referred to as the economic structure model, uses variables from the ERS, most of

which are nominal. It is believed that, considered in combination, these models give an adequate indication of

factors associated with counties being able to move out of distress or remaining distressed during the period

studied.

The independent variables included in the equations were not randomly selected. Instead, they were

assumed to have a potentially significant correlation with distressed status; the selection of such variables was

based largely upon variables used in previous analyses that have attempted to measure factors associated with

county-level socioeconomic conditions.72 Furthermore, a scatterplot procedure was used to screen the independent

variables for collinearity, and highly correlated variables were not included in the equations. In general, it was

believed that most of the independent variables entered into these equations, which generally all related to social,

demographic, and economic factors, would have either a positive or negative effect on a county's distressed status.

While most of the variables in the equations are self-explanatory, it should be noted that high school education is

used as a proxy for educational attainment rates, and the percentage of the population below 19 is considered a

proxy for age distribution. There are a variety of embedded hypotheses, such as higher rates of educational

attainment will lead to lower chances of a county being distressed, or that a county being located in the southern

part of the Appalachian Region is more likely to have moved out of distress. The results of the logistic regression

models are included below.

Other statistical techniques used in this analysis include comparisons of means, t-tests, and chi-square

tests. The arithmetic mean is simply a measure of average. T-tests and chi-square tests are used to test for

statistically significant differences between groups. A nonsignificant t-test or chi-square test indicates that the

samples are from identical populations, while significant t-tests and chi-square tests indicate that the samples are

from different populations.73 For example, if a t-test indicates that the rates of educational attainment for two

groups of counties, such as persistently distressed counties and counties that have moved out of distress, are

significantly different, then it can be stated that the rates of educational attainment in those counties have been

statistically proven to be different. T-tests are used for ratio or interval data, while chi-square tests are used for

nominal data.
53

Results of Logistic Regression Models

Model 1 (Socioeconomic Model)

Dependent Variable: Distressed County 1960 and 1990

Initial -2 Log Likelihood : 295.15118

Method: Forward Stepwise (Conditional)

Final -2 Log Likelihood: 125.538

Nagelkerke R-squared value: 0.732

Classification table Total Predicted Percent Correct

Distressed 1960/1990 98 86 87.76%

Distressed 1960/Not

1990

116 102 87.93%

Total 214 188 87.85%

Variables in the Equation

Variable B S.E. Wald df Sig R Exp(B)

% Urban Pop. -0.0381 0.0161 5.6299 1 0.0177 -1109 0.9626

High School Education -0.1074 0.0401 7.1665 1 0.0075 -0.1323 0.8981

% Manufacturing -0.1168 0.0291 16.0615 1 0.0001 -0.2183 0.8898

% 19 + Below 0.4084 0.1323 9.5296 1 0.0020 0.1597 1.5044

% Nonwhite 0.0920 0.0311 8.7613 1 0.0031 0.1514 1.0964

South Sub-Region -2.9334 0.6492 20.3145 1 0.0000 -0.2498 0.0532

Constant -1.8112 5.0936 0.1264 1 0.7221

Variables Not in the Equation

Pct. Mining Fed/ADHS Highway Metro Adj. Central Sub-Reg.

Pct. Services

Model 2 (Economic Structure Model)

Dependent Variable: Distressed County 1960 and 1990

Initial -2 Log Likelihood : 295.15118

Method: Forward Stepwise (Conditional)

Final -2 Log Likelihood: 233.571

Nagelkerke R-squared value: .334

Classification Table Total Predicted Percent Correct

Distressed 1960/1990 98 76 77.55%

Distressed 1960/Not

1990

116 74 63.79%

Total 214 150 70.09%

Variables in the Equation

Variable B S.E. Wald df Sig R Exp(B)

Mining Dependent 2.1246 0.5940 12.7940 1 0.0003 1912 8.3699

Manuf. Dependent -0.9510 0.3701 6.6004 1 0.0102 -0.1248 0.3864

Govt. Dependent 1.0239 0.5762 3.1573 1 0.0756 0.0626 2.7840

Retire Destination. -2.1150 0.8217 6.6249 1 0.0101 -1252 0.1206

Beale 2 -2.0206 0.7920 6.5093 1 0.0107 -0.1236 0.1326

Constant 0.0057 0.2462 0.0005 1 0.9814

Variables Not in the Equation

Serv. Dep. Com. Dep. Beale 5 Beale 8

Nonspecialized Beale 3 Beale 6 Beale 9

Fed. Lands Dep. Beale 4 Beale 7
54

IX. Appendix D: Information About Data Used in This Analysis

(For full references see the bibliography.)

Data for Distressed Variables

Unemployment

1960, 1970: Census data from the USDA Economic Research Service (ERS)

1980, 1990: Census data from "USA Counties 1996" CD

Note: "Civilian labor force" and "unemployed civilian labor force" were used to determine unemployment. The ARC bases its distressed

indicator on civilian unemployment.

Poverty

1960*: Office of Economic Opportunity (OEO) data from the ERS

1970: Census data from the ERS

1980, 1990: Census data from "USA Counties 1996" CD

* The census did not measure poverty before 1960. The OEO rates of poverty are considered comparable to the census' measures of poverty.

Income

1960: U.S. Bureau of the Census

Note: In 1960, the census determined three types of income: wage and salary income; self-employment income; and other income. In this

analysis, "other income" was used as the proxy for transfer payments. Thus, 1960 PCMI was wage and salary income plus self-employment

income.

1970, 1980, 1990: Bureau of Economic Analysis (BEA) data from the 1996 REIS CD

Note: The BEA income data are considered more accurate than the census data for income. Because census data are actually from the year

preceding the census (e.g., 1970 census data is actually from 1969), 1969, 1979, and 1989 BEA data were used in this analysis. BEA data were

not available for years preceding 1969. To determine PCMI, Transfer Payment Income was subtracted from Total Per Capita Income.

Other Variables Used in the Analysis

1960 Population (age, race, etc.); 1960 Urban Population; 1960 Educational Attainment;* 1960 Employment by

Industry**: Census file tapes, data from the USDA Economic Research Service (ERS)

1990 Population (age, race, etc.); 1990 Urban Population; 1990 Educational Attainment;* 1990 Employment by

Industry**: USA Counties 1996. U.S. Department of Commerce, Bureau of the Census

* Population 25 years and older with 12 or more years of education and population 25 years and older with some college were used to assess

educational attainment.

** Rates were for employed persons by industry; the following were aggregated and considered as services: Transportation, Communications,

and Other Public Utilities; Wholesale and Retail Trade; Finance, Insurance, and Real Estate; Business and Repair Services; Personal,

Entertainment, and Recreation Services; Professional and Related Services; and Public Administration.

ARC Subregion; ADHS and Federal Highways in County: Data from the ARC

Economic Research Service Variables

The ERS, a branch of the United States Department of Agriculture (USDA), has developed a rural typology that

provides a way to identify what it considers important economic and policy characteristics of nonmetropolitan

counties. The ERS and other entities in rural policymaking use the typology. Nonmetro counties are classified as

one of six non-overlapping economic types (farming-dependent, mining-dependent, manufacturing-dependent,

government-dependent, services-dependent, and nonspecialized). Counties are also classified into five overlapping

policy types (retirement-destination, federal lands, commuting, persistent poverty, and transfer-dependent; note that

persistent poverty and transfers-dependent were not used in this analysis because it was assumed that they would be

highly correlated with the distressed indicator).
55

Farming-dependent: Farming contributed a weighted annual average of 20 percent or more of total labor and

proprietor income over the 3 years from 1987 to 1989.

Mining-dependent: Mining contributed a weighted annual average of 15 percent or more of total labor and

proprietor income over the 3 years from 1987 to 1989.

Manufacturing-dependent: Manufacturing contributed a weighted annual average of 30 percent or more of total

labor and proprietor income over the 3 years from 1987 to 1989.

Government-dependent: Government contributed a weighted annual average of 25 percent or more of total labor

and proprietor income over the 3 years from 1987 to 1989.

Services-dependent: Service activities (private and personal services, agricultural services, wholesale and retail

trade, finance and insurance, transportation and public utilities) contributed a weighted annual average of 50

percent or more of total labor and proprietor income over the 3 years from 1987 to 1989.

Nonspecialized: Counties not classified as a specialized economic type over the 3 years from 1987 to 1989.

Retirement-destination: The population age 60 years and over in 1990 increased by 15 percent or more during

1980-90 through inmovement of people.

Federal lands: Federally owned lands made up 30 percent or more of a county's land area in the year 1987.

Commuting: Workers age 16 years and over commuting to jobs outside their county of residence were 40 percent or

more of all the county's workers in 1990.

The ERS also uses what it terms rural-urban continuum codes to classify metro and nonmetro counties. These

codes were used to determine the metropolitan status as well as the metropolitan adjacency status of ARC counties.

The codes are as follows:

Metro

0 - Central counties of metro areas of 1 million population or more

1 - Fringe counties of metro areas of 1 million population or more

2 - Counties in metro areas of 250,000 to 1 million population

3 - Counties in metro areas of fewer than 250,000 population

Nonmetro

4 - Urban population of 20,000 or more, adjacent to a metro area

5 - Urban population of 20,000 or more, not adjacent to a metro area

6 - Urban population of 2,500 to 19,999, adjacent to a metro area

7 - Urban population of 2,500 to 19,999, not adjacent to a metro area

8 - Completely rural or less than 2,500 urban population, adjacent to a metro area

9 - Completely rural or less than 2,500 urban population, not adjacent to a metro area
56

Notes

 

1

 For information concerning the early policies of the ARC, see ARC 1968 and ARC 1970. For information about

the Distressed Counties Program, see ARC 1981b and ARC 1982.

2

 See Fullenbaum and Mariana McNeill, 1995.

3

 See Couto, pp. 41-69.

4 See Freme, Frederick L., and B.D. Hong. US Coal Supply and Demand: 1998 Review. Dept. of Energy, Energy

Information Administration, 1998. Department of Energy’s Annual Energy Outlook 1999, Washington DC, Report

# DOE/EIA-0383(99). Bhatt, Suresh K. Appalachian Coal: An Overview. Mining Engineering, December 1995.

Truman, Jim. Appalachian Coal Markets. Mining Engineering, December 1995.

5

 For an analysis of national trends contributing to growing income and wage inequality see James Galbraith 1998;

for an analysis of Appalachian trends on inequality see McLaughlin et al. 1999, pp. 160-171. [not in bibliography;

please provide a bibliography entry.]

6

 Based upon a range of resources, including Arthur D. Little 1982; Jensen 1998; Papadimitriou 1999; Raitz and

Ulack 1984; and Rothblatt 1971.

7

 These calculations were based on Historical Tables of the Budget of the United States Government, Fiscal Year

1999, Office of Management and Budget Federal Budget, Tables 3.2 and 11.3. Poverty expenditures included

expenditures by the federal government in more than 20 general categories and community and regional

development. All expenditures were deflated using FY 1992 dollars as a basis as derived from table 10.1. The

calculations were done from 1962-2000 to correspond, for the most part, with the time period studied in this report.

8

 Ibid, Table 3.2.

9

 See Couto, pp. 24-29; 32-39; 44-64, for a discussion the impact of these policy changes on industry in the

Appalachian Region. For a discussion of the national policy changes and implications for employment policy,

income inequality, and impacts on cyclical growth see Galbraith 1998, especially chapters 8 and 10.

10 A report to the Commission (Arthur D. Little 1982) indicated that such expenditures were lower in the early

1980s, while Rothblatt 1971 claims that federal expenditures have historically been lower in Appalachia. A more

detailed analysis of federal expenditures per capita would be necessary to clearly indicate such trends.

11 In general, it is believed that Appalachia has historically been a lagging region, and this research gives the same

indication. For other sources, see the PARC report (1964), which discusses Appalachian economic and social

conditions compared with the rest of the nation in the 1960s. Bradshaw 1992, p. 29, suggests that in the 1960s

"Appalachia clearly lagged economically behind the rest of the United States; it had social problems resulting from

isolation and outmigration; its political processes tended to hold back modernization; and its environment was

deteriorating. For further references to Appalachia's lagging conditions see Munro 1969, p. 149, Rothblatt 1971, p.

1, and Moore 1994, p. 316. It is important to note that some writers take issue with Appalachia being referred to as

a "lagging" region. See, for example, Whisnant 1980.

12 PARC 1964, p. XV.

13 Rothblatt 1971, p. 5.

14 Congressional Record 1960.

15 Hansen et al. 1990, pg. 123; Moore 1994, p. 320.
57

 16 Bradshaw 1992, p. 31.

17 PARC 1964, p. II.

18 PARC 1964, pp. 1-18.

19 ARC 1965, pp. 2-32.

20 Widner 1990, p. 299.

21 ARC 1997. Other federal agencies have contributed approximately 10% to the total of $15 billion.

22 ARC 1997.

23 ARC 1968; ARC 1970. These documents indicate the parameters of the ARC's growth center policy.

24 ARC 1965, p. 1.

25 Preston 1971.

26 Preston 1971 discusses the ARC's growth center strategy and its relation to prevalent regional development

theories of the times. For further readings on such theory, see Friedmann 1964 and Hirschman 1958.

27 The ARC's growth center policy was not completely congruent with much of the growth policy theory expressed

in the academic literature of the times. In many ways, it was very different. Nonetheless, through the first five

years of the program approximately 60% of all area development funds went to ARC-designated growth centers

(ARC 1970), and the Appalachian Development Highway System was in many ways designed to link the Region's

growth centers with each other and with urban centers just outside of the region.

28 There is no written documentation that the ARC officially abandoned the policy of developing growth centers.

However, Thoman 1976, pp. 24-26, suggests that by the mid-1970s the ARC no longer strictly supported such a

policy, and Bradshaw 1992 suggests in various parts of his book the political difficulties the ARC had in

implementing such a policy. Rothblatt 1971 discusses the political difficulties with implementing such a policy.

29 ARC 1981a.

30 ARC 1981a, p. 5.

31 ARC 1981a, p. 39.

32 ARC Resolution #538, July 28, 1982.

33 ARC Resolution #583, February 22, 1987.

34 ARC Resolution #624, July 19, 1994.

35 ARC Resolutions #635 & 636, August 20, 1996, and ARC Code Revisions, March 1997. The ARC currently

designates counties as either distressed, transitional, competitive, or attainment. Distressed counties are eligible for

80 percent funding by the ARC, transitional 50 percent, and competitive 30 percent, and attainment counties are not

eligible for ARC funds unless they are part of a multi-county project.

36 Glasmeier and Fuellhart 1999, p. 2.

37 ARC 1989b.
58

 38 ARC 1989b, p. 2.

39 This is based upon expenditures taken from the ARC's 1997 Annual Report. All expenditures are deflated to FY

1992 dollars.

40 ARC 1989b; The ARC currently designates counties as either distressed, transitional, competitive, or attainment.

Distressed counties are eligible for 80 percent funding by the ARC, transitional 50 percent, competitive 30 percent,

and attainment counties are not eligible for ARC funds unless they are part of a multi-county project.

41 ARC 1989a; ARC 1995a.

42 ARC project data file. The single-county distressed grants includes $31 million for the Ritchie Dam project,

which if excluded would bring the total to $235 million.

43 Ibid.

44 Fullenbaum and McNeill 1995.

45 Gauthier 1973; Munro 1969; Whisnant 1980.

46 Isserman 1996b; Isserman and Rephann 1995; Moore 1994.

47 Glasmeier and Fuellhart 1999.

48 For total number of distressed counties including the current total of 406 distressed counties, see Appendix A.

49 Isserman 1996a; Isserman 1996b; Isserman and Rephann 1995; Widner 1990.

50 The improvement in the Southern United States is well-documented. See Hoover and Giarratani 1984 or Raitz

and Ulack 1984 for further reference.

51 Raitz and Ulack 1984.

52Jensen 1998.

53 Jensen 1998.

54 Hansen 1971 wrote much about the demographic spillover effects and the potential for growth of intermediatesized cities.

55 www.eia.doe.gov

56 For additional analysis of the socioeconomic trends in the Mississippi Delta Region see Isserman 1997.

57 Raitz and Ulack 1984; Widner 1990.

58 Harrison and Bluestone 1982 and 1988 and Jensen 1998.

59 Harrison and Bluestone 1982 and 1988; Herzenberg, Alic and Wial 1998; Neill 1997.

60 Galbraith 1998; Harrison and Bluestone 1988; Herzenberg, Alic and Wial 1998; Neill 1997.

61 The socioeconomic model had a prediction rate of 88 percent, while the economic base model had a prediction

rate of 71 percent.
59

 62 It is important to note that there is a difference between the definition of metro and urban, or rural and nonmetro.

A nonmetro county can actually have a high percentage of people living in urban areas. The calculations in this

study indicate that counties with a greater percentage of the population living in urban areas are more likely to

emerge from distress. Thus, nonmetro and nonmetro adjacent counties with low percentages of the population

living in urban areas would probably have a difficult time emerging from distress.

63 Readers may note that in the socioeconomic logistic regression model "percent mining" was not significant while

in the economic structure logistic regression model "mining dependency" was significant. A number of reasons

may help explain why this might have occurred. First, in screening the variables for collinearity, it was found that

percent mining and percent manufacturing were inversely correlated (-.56). Another reason for the apparent

discrepency between the two models may be that in the socioeconomic model percent employed in mining was a

contiuous variable while in the Economic Structure model it was a binary variable.

64 See the county economic typology of the Economic Research Service, 1995.

65 Johnson, Kraybill and Deaton 1989 cited in Galston and Baehler 1995.

66 Porterfield 1990 cited in Galston and Baehler 1995.

67 U.S. Census Bureau: www.census.gov/hhes/income/midclass/midclsan.html (last revised Feb. 3, 1999). Also see

Center on Budget and Policy Priorities 1998, p. 2.

68 These findings are based on a forthcoming study conducted for ARC by the Educational Testing Service.

69 These estimates for IT employment were derived by ARC using the REMI model for the 406-county

Appalachian region. The REMI model is a proprietary model developed by Regional Economic Models Inc. of

Amherst, Mass.

70 Real spending trends for total federal economic development outlays were derived from Table 3.2 for Budget

Function 450 less Disaster Relief as reported in the Historical Tables of the Budget of the United States

Government for Fiscal Year 1999. Figures were expressed in 1992 dollars using the deflators reported in Table 10.1

using the total nondefense deflator.

71 For an even more detailed description of logistic regression, see SPSS 1997.

72 Glasmeier and Fuellhart 1999; Kusmin 1994; Kusmin, Redman and Sears 1996.

73 For a further description of t-tests as well as chi-square tests see Ebdon 1985.
60

 

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