United States

Department of

Agriculture

Economic

Research

Service

Rural

Development

Research Report

Number 48

Natural Resource

Dependence, Rural

Development, and

Rural Poverty

Kenneth L Deavers and David L. Brown

j-?*:;*--i; ;v'4'7é%;;v
Natural Resource Dependence, Rural Development, and Rural Poverty. By

Kenneth L. Deavers and David L Brown. Economic Development Division,

Economic Research Service, U.S. Department of Agriculture. Rural Development

Research Report No. 48.

Abstract

Rural poverty and population decline are now only weakly connected with a rural

county's economic dependence on agriculture, mining, or Federal landownership.

Thus, natural resource dependent counties are not the principal target for programs designed to relieve population decline and low-income problems in rural

Âm.erica. This report examines the influence of natural resource dependence on

rural income levels and recent population growth.

Keywords: Population, income, poverty, natural resources, mining, Federal lands,

agriculture, rural policy.

Acknowledgments

This work could not have been accomplished without the efforts of several of our

colleagues in EDD. Peggy Ross and Bernai Green have major responsibility for

developing the data base for the county classification scheme which is the key

analytical construct used in this paper. Bob Hoppe leads the EDD project on the

geography of poverty and gave freely of his time and knowledge in our analysis

of persistently low-income areas. Calvin Beale's Insightful review of an earlier

draft is appreciated. Mary Haygood did a superb job in typing the manuscript.

This study was originally prepared for the Resources for the Future Conference

on Rural Development, Poverty and Natural Resources held at the Airlie House in

July 1983.

Washington, D.C. 20250 July 1985

m
Contents

Page

Summary v

Introduction ......_................ = . 1

The 1970s in Perspective ,..,....., 1

Population Disiribution 1

Economic Structure 2

Income and Poverty .. = ..........,.....,. 3

Classifying Rural Diversity............. 4

Definition and Geographic Location 5

Comparative Profile of County Classes 6

Expiainlng Intercounty Variations 10

Population Change .....................,......_.... 10

Income Level 12

Summary of Findings , 13

Rural Pofiey Directions 14

References 15

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IV
Summary

Contrary to our expectations, rural counties that are economically dependent on

farming, mining, or have a high proportion of federally owned land have not

grown more slowly and are not poorer than all nonmetro counties. But,

dependence on agriculture continues to be a strong negative factor In their

population growth. This study examines the influence of natural resource

dependence on recent population growth and rural income levels. A county is

natural resource dependent If at least 20 percent of its labor and proprietors' income is derived from farming or mining or if at least 33 percent of its land is

federally owned.

Because our analysis provided no convincing evidence that a county's

dependence on farming, mining, or federally owned land affected community income, we chose to focus directly on persistently poor rural counties regardless

of their natural resource dependence. While these poor counties do not differ

from the nonmetro average in their industrial profile, they do differ in their location and population profile. They have comparatively low levels of schooling, high

levels of work-limiting disability, and a high rate of age dependency (children and

the elderly as a fraction of the total population). They also have a very high

percentage of blacks and are located principally in the South. Highlights of the

study include:

• Among all nonmetro counties, and in most natural resource dependent

counties, 1970-80 population growth was higher in areas that had previously been growing, that are classified as retirement areas, that have access

to a metro area and an interstate highway, and are located in the South or

West.

• Among all nonmetro counties, population growth was lower in highly urbanized nonmetro counties; in areas heavily dependent on manufacturing,

agriculture, and mining; and in areas in which blacks are a large proportion of the population.

® Of the natural resource counties, only those dependent on farming trailed

nonmetro counties in median family income as of 1980. And, they trailed

by less than $1,000.

• The poverty rates of the natural resource dependent counties were comparable to all rural counties.
Natural Resource Dependence, Rural

Development, and Rural Poverty

Kenneth L. Deavers and David L. Brown*

Introduction

Rural areas' population growth, location, level of

economic activity, and social v^ell-being depend less on

natural resource endownnents than on such factors as

transportation, communication, labor force

characteristics, and urbanization. Nevertheless, many

rural areas continue to be much more dependent than

the Nation as a whole on natural resource based activities, such as farming and mining.

First we look at the changes rural America experienced

in the 1970's. Then, within this framework we consider

how natural resource related activities influenced rural

development^ Understanding the economic and social

viability of rural areas requires an understanding of the

changing role of their natural resource base in development. We measure rural development by population

change and current income leve!. We examine these

and other measures of structure and change among

rural areas and compare areas dependent on natural

resource based activities to all rural counties. We question whether natural resource dependence contributed

importantly to recent rural population change and what

its role is in explaining geographic differences in the incidence of rural poverty.

The 1970's In Perspective

The enormous change rural America has experienced in

the past 25 years culminated in the 1970's: the population growth rate of nonmetropolitan areas exceeded

*Deavers is Director, Economic Development Division, ERS.

Brown is Associate Director, Economic Development Division,

ERS.

""The terms rural and nonmetropolitan are used interchangeably in this report; however, all data presented are by

nonmetropolitan-metropoHtan (SMSA) county status as announced in 1974 based on the results of the 1970 Census. We

use the Standard Metropolitan Statistical Area (SMSA) definition rather than the more current Metropolitan Statistical Area

(MSA) delineation because our interest is in change during the

decade of the 1970's, not current status. The new MSA

delineation includes numerous counties as metro which were

nonmetro in 1974, thus affecting measures of decade change.

that in metropolitan areas, reversing a century of net

outmigration from rural areas; the overall industrial mix

of metro and nonmetro areas became very similar as a

result of the long-term decline in resource-based

employment and increases in manufacturing, services,

and government; and rural poverty and disadvantage

were reduced. However, chronic poverty continued in

selected areas and for some population groups, and

overall progress in reducirig rural/urban income differences ceased in the mid-1970's.

Population Distribution

For the first time in this century, the rate of population

growth of nonmetro areas exceeded that of metro areas

(table 1). Between 1970 and 1980, nonmetro counties

grew by 15.7 perceiit compared with 9.9 percent for

SMSA counties. The reverse was true between 1960 and

1970 when metro areas grew by 17 percent and their

nonmetro counterparts grew by only 4.3 percent.

Remote and completely rural areas shared the 1970-80

nonmetro growth advantage with areas that are partly

urban or dominated by nearby cities.

This dramatic turnaround is principally a product of

changes in migration behavior; both reduced rural outmigration and increased inmigration. Also, women in

rural areas had substantially fewer children during the

1970's, making the rural birthrate more similar to that

of urban areas. Consequently, differential fertility was

less of a force in creating differences in population

growth rates between the residential sectors. Previously, natural increase (births minus deaths) had been a

more important determinant of differential growth between urban and rural areas.

The term "turnaround" means that for the first time in

the 20th century the rate of population growth of the

entire nonmetro sector exceeded that of the metro

category. It does not mean that all nonmetro counties

previously had declining population, or that all those

that had declining population are now growing. Almost

1,100 nonmetro counties grew during the 1960's, and

446 nonmetro counties that lost population during the
Oeavars and Brown

1960's also lost population during the 1970's, The rural

turnaround occurred because many previously growing

nonmetro counties increased their rates of growth, and

850 counties with previously declining populations

slowed their rates of decline or reversed to population

gain (4).^ The reasons for the metro=nonmetro turn=

around are diverse and hard to generalize, but some

root causes are identifiable:

Residential preferences have been realized.

Economic and community changes have made it

feasible for many citizens to achieve their goal of

a more rural lifestyle. Residential preference

surveys have consistently demonstrated a

substantial discontinuity between the size of current community of residence of many Americans

and the size of place they prefer {25).

Changes in the structure of agriculture have

slowed. More than 40 years of outmovement,

totaling about 30 million people, have greatly

reduced the potential for further farm outmigration as a source of urban growth.

Nonextractive economic activities have decentralized. The economic character of rural life has

diversified. Trade, services (including government),

and manufacturing have become the primary employers. This transformation of the rural economy

has retained many workers in rural areas who

otherwise might have migrated to urban jobs, and

it has attracted urban workers to rural work and

residence.

Rural life has modernized. The stereotype of rural

areas as backward and isolated is no longer accurate. Electricity, telephone service, all-weather

roads, cable television, and centralized water and

sewer systems have modernized rural life.

^Italicized numbers in parenthèses refer to items Hated in

the References section at the end of this report.

Other highly industrialized and urbanized nations

shared in the U.S. experience of population decentralization during the 1970's. This has led many social

scientists to hypothesize that population decentralization is part of a natural process of convergence between urban and rural areas in advanced societies (2,

22, 23). ít seems unlikely that the 1970^s were an aberration, or should be interpreted as a break in long-term

rural developm.ent trends. However, post-1980 data suggest that metro and nonmetro areas are now growing at

about the same rate, with metro areas having a slightly

higher rate (g 19).

Economic Structure

The movement of people and jobs to nonmetro counties

has accelerated changes the rural economy has undergone in recent decades. Since World War II, the structure of nonmetro employment has become increasingly

diverse and decreasingly agricultural. In fact, the

percentage of employment in farming has been declining since 1920 when over 70 percent of all U.S. workers

were employed in agriculture. By 1920, this figure had

fallen to a little over 25 percent, and by 1940, only 17

percent of the labor force was in farming. By 1979, the

Table 1—Population change by metropolitan status and size of largest city

Population

Area 1980 1970 1960 1970-80 1960-70

Thousands—— —-Percentage change—

Total

Metro^

Nonmetro

226,505

163,503

63,002

203,301

148.877

54,424

179,323

127,191

52,132

11.4

9.8

15.8

13.4

17.0

4.4

Adjacent counties^

Nonadjacent counties

With city of 10,000 or more^

With no city of 10,000

32,901

30,101

13,642

16,458

28,031

26,394

11,910

14,484

26,113

26,019

11,132

14,887

17.4

14.0

14.5

13.6

7.0

1.4

7.0

-2.7

^Metropolitan status as of 1974.

^Nonmetropolitan counties adjacent to SMSA's.

^Counties with a city of 10,000 or more population in 1970.

Source: Tabulated from 1970 and 1980 Census computer tapes.
Natural Resource Dependence, Rural Development, and Rural Poverty

most inclusive definition of agricultural workers (wage

and salary, self-employed, and unpaid family) totaled

only 3.4 percent of the U.S. work force. Even in

nonmetro areas, this percentage dropped from almost

14 percent in 1950 to 8 percent in 1979.

Although agriculture is not the primary rural employer

nationwide, in nearly 700 counties located mainly In the

Great Plains and Corn Belt, 20 percent or more of labor

and proprietors' income was derived from agriculture in

1977-79. No other single industry is as important a

source of labor and proprietors' income in as large a

grouping of rural counties. However, the decline in the

relative role of agriculture is dramatically illustrated by

the fact that in 1950 over 2,000 counties had a similar

dependence on agricultural income (13).

In contrast, manufacturing accounts for nearly 25 percent of all nonmetro employment, trade and government each account for about 16 percent, and services

account for 11 percent. While these nontraditional industrial categories now make up a larger proportion of

nonmetropolitan employment than before, the change

has been a gradual evolution, not a recent and

dramatic shift. In 1950 for instance, manufacturing was

already a major rural employer, accounting for 20 percent of all nonmetro jobs {24).

Most observers view these changes as diversifying the

industrial structure of rural America. That characterization is accurate for rural areas taken as a whole. But it

can be seriously misleading when applied to individual

rural areas. Rural economies are sufficiently small that

the process of development does not lead typically to

diversification in particular communities. At the county

level, for example, few rural economies have a balance

of agriculture, mining, manufacturing, services, and

government; instead, these activities tend to concentrate in separate locations. The extent to which rural

areas specialize in particular economic activities provides an important insight into the possible direction of

rural policy. We will return to this point later.

Broad industrial classification summaries, such as

manufacturing, hide many important compositional differences. Unpublished data from the Bureau of

Economic Analysis show that in 1979 low-wage, laborintensive industries such as textiles, apparel, leather,

and lumber products accounted for about 33 percent of

nonmetro manufacturing employment nationally, but

nearly 50 percent of nonmetro manufacturing employment in the South. Although these percentages are

lower than a decade earlier, they do suggest that the

future performance of rural manufacturing employment

may differ significantly among regions. The South is

especially likely to face serious foreign competition in

its efforts to sustain a significant portion of the industrial employment it successfully attracted in the

past 30 years.

Income and Poverty

The ratio of nonmetro to metro income has increased

significantly from previous decades, when dramatic differences in economic status were a major explanation

of rural outmigration. In 1950, nonmetro median family

income was 33 percent below the metro median. By

1973, nonmetro median family income had increased to

$16,000, only 20 percent below the metro figure. This

ratio of nonmetro to metro income continues, and there

has been no subsequent narrowing of the gap. Nonmetro income has improved because of increased formal educational attainment, industrial growth and

diversification, off-farm employment by farm family

members, increased labor force participation by rural

women, reduced discrimination against racial

minorities, and the growth of government transfer pro=

grams (5, 6, 10, 18).

Despite the narrowing of metro-nonmetro income differences, rural problems persist. Rural America continues to have a disproportionate share of the poverty;

34 percent of the Nation's poor people reside in

nonmetro counties compared with only 28 percent of

the Nation's total population {21).

A dramatic indicator of the persistent gap between

metro and nonmetro income is that nearly all of the Nation's poorest counties are nonmetro, and poverty is a

persistent condition in these areas. In fact, of the

lowest income quintile In 1950, less than 20 percent of

the counties had escaped that low-income category by

1979(72).

Rural poverty is not uniformly distributed among

regions or subgroups of the rural population. Nearly 60

percent of the rural poor live in the South where 21 percent of the rural population failed to earn incomes

above the official poverty level in 1981. The incidence

of southern rural poverty is like that in older, large

cities such as Detroit, Chicago, Boston, and Baltimore.

However, rural poverty is not restricted to the South. A

large number of rural counties in the Northeast have

substantial poor populations. But, because their overall

populations are large, they do not have a high Incidence of poverty {8).

Rural poverty falls disproportionately on minorities.

Forty-two percent of rural blacks (more than 10 percentage points higher than for metro blacks) and 28
Deavers and Brown

percent of rural Hispanics were poor in 1981 compared

with 13 percent of whites. However, wiiites, because

they are a nnajority population, constitute a numerical

majority of the rurai poor. The incidence of rural poverty is almost 20 percent among elderly households and

over 40 percent for female-headed households with no

husband present.^

Despite workforce participation, many rural families are

unable to earn enough income to rise from poverty.

This fact is often neglected. In 1981, almost 70 percent

of nonmetro poor households contained at least one

worker, and almost 33 percent had two or more members in the work force. Work-limiting disability contributes importantly to low rural income. Over 10 percent

of working age rural people report they have a disability

that limits their ability to work, and the proportion increases to almost 15 percent in persistently low-income

counties.

In most post-World War II recessions, rural workers

have fared somewhat better than their urban counterparts. For example, during the recession of 1974-75,

nonmetro workers had consistently lower unemployment rates than did workers in metro areas, although

the nonmetro rate did exceed the metro rate at the

recession's peak for one quarter in 1975. During the

1980-83 recession, however, the nonmetro unemployment rate consistently exceeded the metro rate. In the

winter quarter of 1983, at the height of the recession, the

nonmetro unemployment rate was 12 percent compared

with 10.8 percent in SMSA counties. Adjustments for

discouraged and part-time workers, both of whom area

larger percentage of the rural labor force, would increase the nonmetro disadvantage even more. This

reversal is doubtless related to the continuing evolution

of the rural economy, and its increasingly close ties with

the U.S. and world economies.

The income effect of recession-related unemployment

is dramatic. The nonmetro poverty rate dropped from

19.2 percent (11.9 million persons) in 1970 to 15.4 percent (8.6 million persons) in 1980, but increased to 18.3

percent (13.5 million persons) in 1983 (27).

In summary, metro-nonmetro income differences have

diminished, but persistent gaps remain. Poor people in

rural America have many forms of disadvantage; poor

^Research at the institute for Research on Poverty, University of Wisconsin, demonstrates that adjusting the nnoney income of the elderly for durabie assets, tax advantages, and

household size and composition significantly reduces the differences in their economic status relative to that of younger

persons (7).

housing, low educational attainment, few marketable

vocational skills, poorer health, and higher rates of

work-limiting disability (75). In addition, they frequently

live in isolated communities that lack enough local

resources to support needed facilities and services.

These communities chronically underinvest in human

capital and facilities; inadequate educationalopportunity, poor health care, substandard housing, lack of

public water and sewer systems, and other such conditions are prevalent. The chronic underinvestment in

human and community resources in poor rural areas

constrains many individuals from improving their

material well-being.

Classifying Rural Diversity

Some participants in the dialogue on rural policy have

inappropriately concluded that every rural area is so

different from every other rural area that there is no

need for (and no real possibility of) national rural

development policy and programming. The Economic

Development Division of ERS has embarked on a research project aimed at providing new social,

economic, and political content to our categorization.

Rural America is enormously diverse, but recent

research demonstrates that most rural areas can be aggregated into a relatively small number of ''types" (17).

This categorization contributes to a better understanding

of what rural areas have in common as well as how they

differ. This classification scheme allows a substantial

comparison of rural social, demographic, and economic

information. Because it focuses on a relatively small

number of county types, rather than on the full range of

individual rural conditions, the classification scheme

increases understanding of the sociodemographic and

economic setting within which particular public

policies and programs are likely to be most important

to rural development in particular environments.

We have aggregated rural areas into seven categories

based on an area's dependence on broad classes of

economic activities: agriculture, manufacturing, mining,

and government. The categories also contain social

dimensions: persistent poverty and growth of retirement population. The proportion of land in Federal

ownership is also included.

These seven categories do not contain all nonmetro

counties and they are not mutually exclusive. But nearly

75 percent of nonmetro counties (1,782) are included,

and overlap among the county classes is not great

(table 2). The largest pairwise overlap among the seven

county types is the 43 agricultural counties that are

also categorized as persistent poverty counties.
Natural Resource Dependence, Rural Development, and Rural Poverty

Table 2—-Pairwise overlaps among county classes

County pairs

Farming and Federal lands

Farming and poverty

Farming and mining

Farming and government

Federal lands and poverty

Federal lands and farming

Federal lands and government

Poverty and government

Mining and government

Total overlaps

Frequency

22

43

10

32

5

36

39

24

3

228

Definition and Geograpliic Location

We will focus on the four county types that are directly

concerned with natural resource dependence

(agriculture, nnining, Federal lands), and on persistent

poverty. The categories are defined as follows (see fig.

1-4 for geographic locations):

^ Agriculture: Twenty percent or more of labor and

proprietors' income derived from agriculture in

1977-79 and in selected time periods since 1950.

This category contains 656 nonmetro counties.

• Mining: Twenty percent or more of labor and proprietors' income derived from mining. This

category contains 199 nonmetro counties.

Figure 1

Agricultural Counties
Deavers ând Brown

« Federal lands: At least 33 percent of a county's

land in Federal ownership. This category contains

245 nonmetro counties.

• Persistently tow-income: In the lowest quintiie of

nonmetro income in 1949, 1959, 1969, and 1979.

This category contains 242 nonmetro counties.

Agricultural counties are concentrated in the Great

Plains (both northern and southern) and In the western

Corn Belt. Smaller groupings are located in the Pacific

Northwest and California, and in the Piedmont, Black

Belt, Delta, and Ozark subregions of the South. Mining

counties are concentrated in Appalachia, Texas,

Oklahoma, the Louisiana Gulf Coast, the Northern

Great Plains, the Rockies, and the Southwest. Most

Federal land counties are located west of the Great

Plains, although Federal ownership of land Is notably

low in Oregon and in Washington State, except for its

northern tier of counties. A few Federal land counties

are located In Appalachia and in the Ozarks. Ninety-two

percent of persistently low=income counties are in the

South. They are concentrated in Appalachia, the Black

Belt, the Delta, and in the Ozark-Ouachita Plateau. A

few low-income counties are scattered in the Southwest and the Northern Plains, reflecting the location of

American Indian and Hispanic populations.

Comparative Profile of County Classes

A comparison of the four categories of counties that

are either natural resource dependent and/or persistently poor reveals that although these counties differ in

some ways from the average for all nonmetro counties,

in other ways they are very similar.

Figure 2

Mining Counties
Natural Resource Dependence, Rural Development, and Rural Poverty

Demographic. The four categories of counties thai are

either natural resource dependent or persistently poor

are smaller and less urbanized than all nonnnetro counties taken together (table 3). Farnn counties and persistently low-inconne counties have especially sparse

populations. Not even 5 percent of these counties contain a place of 10,000 or nnore population. The mining

and Federal lands categories are more highly urbanized,

but still sparsely populated compared with the total

nonmetro sector. The four county groups are also relatively isolated from nearby large population centers.

Less than a quarter of Federal land counties and less

than a third of farming and persistently low-income

counties are adjacent to an SMSÂ. The figure for all

nonmetro counties is almost 40 percent. Only the

mining category comes close to the nonmetro level of

adjacency. Similarly, all four categories have limited acFigure 3

cess to the interstate highway system when compared

with the norm for all nonmetro counties.

The population growth rate of all four categories during

the 1970's was considerably faster than during the

previous decade. In fact, population declined in three of

the four county classes during the 1960's and is now

growing. This reversal is particularly notable in the mining and persistently low-income classes. Population

growth rates in farm counties improved from minus 7

percent during the 1960's to plus 4 percent during the

1970's, and the rate in Federal land counties improved

from a modest 8 percent during the 1960's to an incredibly high 34 percent in the 1970's.

Income Distribution. Families in the three natural

resource based county classes earned income near or

Federal Land Counties
Deavers and Brown

above the average for a!! nonmetro counties. Farm

counties lagged slightly behind the nonmetro norm of

$15,000, but mining and Federal land counties exceeded the norm by about $1,000. In contrast, persistently

low-income counties lagged behind the nonmetro norm

by about $4,000. The three natural resource based

county groups generally have the same percentage of

people in poverty as all nonmetro counties: about 14 to

18 percent. In contrast, over 25 percent of people in persistently low-income counties failed to earn enough income to exceed the officia! poverty line.

Economic Structure. Economic structure is measured

here by dependence (proportion of labor and proprietors' income) on particular industrial sectors:

agriculture, manufacturing, mining, and government. An

average of about 33 percent of labor and proprietors' income is derived from agriculture in the 656 agricultural

counties. This is twice the level of agricultural

dependence of all nonmetro counties. In contrast,

mining and Federal land counties are below the national

norm in agricultural dependence. Persistently lowincome counties are average in dependence on agriculture as a source of income.

The three natural resource county groupings are below

the national average in dependence on manufacturing.

However, mining and farming counties are especially

low with only 8 and 11 percent of income from manufacturing, respectively, compared with the nonmetro

average of 21 percent. Persistently low-income counties

with 23 percent of income from manufacturing are

slightly more dependent on manufacturing than are all

nonmetro counties.

Figure 4

Persistently Low-Income Counties
Natural Resource Dependence, Rural Development, and Rural Poverty

Mining accounts for less than 5 percent of nonmetro income nationwide, but for over 35 percent of income in

mining counties. While over 8 percent of income is

from mining in counties with a high level of Federal

ownership of land, mining accounts for only a very

small proportion of income in farming and persistently

low-income counties.

Government employment provides $1 out of every $6 of

labor and proprietors' income in nonmetro America.

Federal land and persistently low-income counties are

particularly dependent on this source of income, with

over 20 percent of their income from government

employment. This dependence probably reflects the importance of Federal land, water, and other resource

management activities In Federal land counties, and

the managemient of social welfare programs in poverty

counties. Farming and mining counties are only slightly

less dependent on the government sector, with 16 percent of income from government employment.

Human Capital. The natural resource based county

groups are similar in their socioeconomic composition.

All have relatively high levels of formal educational at=

tainment, about 60 percent of adults have completed

high school; about 40 percent of the total population in

each county class is employed; and about 10 percent of

labor force age persons report a work-limiting disability. These figures are comparable to nonmetro areas

taken as a whole. However, the natural resource

classes are somewhat different than all nonmetro counties In age and race composition. The population is

substantially younger in mining and Federal land counties and slightly older in farm counties than in the total

nonmetro population. The percentage of nonwhites is

below the nonmetro norm in all three natural resource

categories. Overall, these population characteristics appear to contribute to the relatively high levels of family

income in natural resource based counties.

Table 3—Comparative profile of county classes

County cliässes

Couniy attributes

Units Nonmetro

totan Farming Mining

199

Federal

land

245

Persistent

poverty

Counties No. 2,424 656 242

Total population, 1980 1,000 63,002 7,851 3,822 5,143 3,672

Demographic and locational:

Mean population, 1980 Do. 26.0 12.0 20.0 22.1 15.1

Population change, 1970-80 Percent 14.6 4.1 21.6 33.9 14.3

Population change, 1960-70 Do. 1.2 = 6.9 -3.3 8.3 -3.5

With city of 10,000 or rmore, 1970 Do. 21.4 3.8 11.6 17.1 1.7

Adjacent to SMSA Do. 39.4 30.3 35.7 23.3 30.6

Access to interstate highway, 1970 Do. 21.3 13.6 14.1 17.1 14.5

Income distribution:

Median family income, 1979 Dollars 15,778 15,010 17,019 16,716 11,923

Families in poverty, 1979 Percent 22.8 23.2 23.8 16.6 46.0

Economic structure, 1978:

Income from—

Agriculture Do. 15.2 33.3 6.5 11.1 14.6

Manufacturing Do. 20.5 10.5 7.9 15.7 22.7

Mining Do. 4.8 2.2 35.7 8.4 4.3

Government Do. 16.8 15.6 13.5 20.9 20.6

Human capital, 1980:

Completed high school Do. 57.6 58.3 56.0 68.6 41.9

Employment to population ratio Do. 39.1 39.4 37.7 39.5 33.2

Work-limiting disability Do. 10.3 9,6 10.7 9.7 14.6

Nonwhite Do. 11.3 8.9 7.5 7.3 26.3

65 years and over Do. 14.0 15.7 11.5 11.3 13.5

^Nonmetro status as of 1974.

Sources of data: Tabulated from 1970 and 1980 Censuses of Population; unpublished data from, the Bureau of Economic

Analysis.
Deavers and Brown

In contrast, persistently low-income counties have a

distinctly different population profile. Only 41 percent

of adults have completed high school, only 33 percent

of the total population is employed, and almost 15 percent of the labor force age population has a worklimiting disability. Over 25 percent of the population in

persistently low-income counties is black. This distinctly

different population profile in low-income counties contributes to their high rate of poverty.

Explaining Intarcounty Variations

We have looked at the relationship of single factors to

population change and income level. We now investigate the effect of all the factors considered

together, using ordinary least squares regression to

provide a more coherent explanation of demographic

and socioeconomic change in nonmetro areas.

Population Change

Traditional explanations for variations in population

change among areas have concluded that growth is

more likely in areas that: (1) had been previously growing, (2) had a relatively high level of urbanization, (3)

had relatively easy access to nearby larger places, (4)

had a relatively large proportion of their economy involved in manufacturing activities, (5) had relatively

high levels of income and other indicators of socioeconomic status, and (6) were located outside of the

South. The direction of the relationships between

population change and demographic, locational, and

economic base factors has generally remained the

same during the last three decades, but the ex=

planatory power of these factors has diminished over

time. For example, Lichter and Fuguitt demonstrated

positive effects of population density, urbanization, adjacency to larger places, and interstate highways on

rural growth, but they also showed that these effects

were increasingly weak (74). They showed that the

positive effects of growth in manufacturing and recreation employment and the negative effects of agricultural employment have declined. These traditional

demographic and economic base variables explained

much less of the intercounty variation in rural population change during 1970-75 than in 1960-70 or in

1950-60, suggesting that other explanations have

become relatively more important in recent years.

Other research has demonstrated that the relationship

between rural population change and certain explanatory variables reversed direction. Beale showed

that employment in manufacturing and level of urbanization, which had been a positive influence on

growth during 1960-70, were negative factors during

1970-75 (1). And Heaton, Clifford, and Fuguitt showed

that median family income was positively related to

rural migration of persons under 65 years of age during

1950-60 and negatively associated in 1960-70 and

1970-75 (77). Location in the Southern region also

reversed from negative to positive in its effect on

population growth (14).

The ordinary least squares regression of the effects of

county characteristics on population growth during

1970-80 presented in table 4 includes three types of explanatory variables: demographic and locational,

economic base, and population composition and socioeconomic status. The analysis is performed for ail

2,424 nonmetro counties, for the three categories of

natural resource based counties, and for persistently

low-income counties.

The mean rate of population growth among nonmetro

counties was 14.6 percent during the 1970's, with a

standard deviation of over 20 percentage points.^ We

explain almost half of the intercounty variation in

population change in all nonmetro counties and In

farming and persistently low-income counties, and

about 20 to 30 percent of the variance in the mining

and Federal land counties. This is comparable to

previous research. However, it indicates that the

variables we have included in our equations, and/or the

way in which we have measured them, leave much of

the explanation to further research. For example, our

analysis includes no measures of amenities or quality

of life, factors that have been shown to be important in

some previous analyses of rural migration (7 7). Still, our

analysis does a fairly good job of identifying factors

related to rural population growth during the 1970's.

Demographic and Locational Factors. All six of the

demographic and locational variables help to explain

post-1970 rural population change. However, the

magnitude of some effects, and sometimes their sign,

varies among the county types. The positive effects of

population change during 1960-70 on change during the

1970's Is by far the strongest in our analysis. This is

true for the total nonmetro sector and in two of the four

county types. The analysis shows that population

growth tended to be greater in less urbanized counties

during the 1970's. While four of five county classes

share this negative relationship between urbanization

and growth, it is statistically significant in only the

total nonmetro and mining categories. Retirement coun-

^This rate differs from that contained in table 1 since this is

the unweighted nnean of the rates for all counties, while that

in table 1 Is the a-ggregate rate for the entire nonmetro

category.

10
Natural Resource Dependence, Ruraf Development, and Rural Poverty

ty status (having a 10-percent or higher rate of net

migration of persons 65 or older during 1950-70) is also

positively related to the 1970=80 rate of population

growth. Retirement county status is an important determinant of post=1970 population growth in all of the

county classes.

Locational factors also have relatively consistent effects on rural population growth. In most cases the rate

of growth was greater in counties adjacent to SMSA's,

in counties that had an interstate highway within their

borders, and in counties located in the South or West.

Exceptions to this pattern include mining counties,

which tend to grow less rapidly when they are located

near an SMSA, and access to an Interstate highway,

which has a statistically significant effect on growth in

only total nonmetro and mining counties. Also,

southern or western location does not explain differentia! growth among low-income counties because 90 percent of these counties are located in the South.

Economic Base Factors, Dependence on natural

resource related activities (agriculture and mining) has

a negative effect on population growth for all nonmetro

counties. In fact, the strongest negative effect is

among mining and agricultural counties themselves;

the higher the dependence in those counties, the lower

the rate of post-1970 population growth. Dependence

on mining is not a statistically significant factor in the

farming and persistently low-income categories. Population growth is generally lower in counties with a

higher level of dependence on manufacturing. However,

there is one notable exception: manufacturing activity

contributes strongly to growth in farming areas.

Dependence on wage and salary government employment tends to be positively related to rural population

growth, but it is statistically significant only in farming

areas.

Population Composition and Socioaconomic

Status. Wealthier areas and areas with lower percentages of nonwhites have been traditional growth areas

in rural America. Other research Indicates that retirement areas, (areas with higher than average inmigration

of elderly people) grew during the 1970's. Our results

(table 4) show that older age and median family income

are positively related to rural population growth, but the

relationships are very weak and contribute little to our

understanding population growth. Income is only statistically significant in the Federal lands category, and

Table 4—Effects of county characteristics on population growth rate of nonmetropolitan counties, 1970-80^

County characteristics

Effects on population growth rate by county classes

Nonmetro

total Farming Mining Federal

land

Persistent

poverty

0.393* 0.390* 0.119* 0.247* 0.246*

-.139 -.039 -.100** -.090 .051

.160* .191* .196* .115** .183*

.042* .181* -.107** .100** .139*

.036** .029* -.155* =-.032 .012

.292* .319* .139* .150* -.005

-.271* -.077** -.356* -.218* -.160*

-.039 ,034 -.309* -.248* -.070

-.174* .096** -.209* -.326* -.132*

.025 .163* .033 -.119** .038

.043 .042 .088 .121** .022

-.113* -.099* .046 -.065 - .442*

.025 .001 .037 .023 -.020

,468 .506 .217 .288 .487

2,424 656 199 245 242

Demographic and locational:

Percent population change, 1960-70

Percent with city of 10,000 or more

Retirement county^

Adjacent to SMSA

Percent with interstate highway in 1970

South/West regions

Economic base, 1970:

Percent of income from agriculture

Percent of income from mining

Percent of income from manufacture

Percent of income from government

Population composition-socioeconomic status:

Median family income, 1969

Percent nonwhite, 1970

Percent 65 years and older, 1970

R2

Number of counties

* = significant at .01.

** = significant at .05.

"•standardized regression coefficients.

^0-1 variable with low rate (less than 10 percent inmigration at age 65 in 1960-70) of elderly migration as a reference.

11
Deavers and Brown

the percentage of residents 65 years and older only

reaches statistical significance in the total nonnmetro

equation (where over 2,000 counties are included), in

contrast, the percentage of nonwhites has a consistently negative effect on growth. This is somewhat surprising since region is controlled in the analysis, and

most rural blacks live in the South. The "race effect" is

particularly strong in farming and persistently iowincome counties.

In summary, v^e found that nonmetro population growth

is higher in areas that were growing previously, are

classified as retirement counties, have access to an

SMSA and to the interstate highway system, and are

located in the South or West. Conversely, growth tends

to be less in counties that are highly urbanized; depend

on agriculture, mining, or manufacturing for a large proportion of personal income; and in which blacks constitute a relatively large proportion of the population.

The positive associations with previous growth experience, access to an SMSA and access to transportation, and the negative associations of race and

dependence on natural resource based industries are

consistent with previous research on rural population

change. However, the positive associations between

population growth and regional location in the South,

the negative relationships between population growth

and level of urbanization and dependence on manufacturing, and the lack of a positive association between

growth and community income break with past explanations of nonmetro growth.

The 1970-80 population growth of specific county types

is generally explained by factors similar to all nonmetro

counties. Among the notable exceptions, however, are

that government and m.anufacturing are sources of

growth in agricultural areas; that mining areas grow

more rapidly if they are not adjacent to an SMSA; and

that Federal land counties have a lower rate of growth

where dependence on government is relatively low. The

positive effect of manufacturing on population growth

in agricultural areas is an anachronism today. In earlier

times, most of rural America was dominated by agriculture, and manufacturing differentiated growing areas

from declining areas. We suspect that the growth effect

of manufacturing in agricultural areas works through

off-farm job opportunities for farm family members, but

household level analysis will be necessary to determine

this. While the explanation of growth among persistently low-income counties is generally consistent with that

for all nonmetro counties, several factors are not

statistically significant in the low-income analysis: level

of urbanization, access to interstate highway, region,

and dependence on mining.

Income Level

The economic development literature consistently

argues that some measure of income, preferably one

that has a distributional component, is a more ap=

propriate way to assess levels of development than

measures of aggregate economic activity or growth

alone (3). In fact, given the difficulty of measuring other

dimensions of social and economic well-being, income

is often used as the sole indicator of development.

Central place theory provides a strong basis for be=

lieving that urbanization and position in the urban

hierarchy affect development. Similarly, economic base

theory suggests that the sectoral composition of

economic activity affects income levels. We measured

location and role in the urban hierarchy by percent urban, adjacency to an SMSA, and location in the

southern region (table 5). Our measures of economic

base are percentages of labor and proprietors' income

from agriculture, manufacturing, mining, and government. In the analysts of intercounty income variation

for all nonmetro counties, all of these variables are

statistically significant except for the region; and all of

the variables have the expected sign.^

The remainder of our model of area income determination draws principally on human capital theory: explaining income differences by educational attainment,

employment status and disability, age, and race. All

these variables are statistically significant for

nonmetro counties taken as a group, and all have the

expected sign (table 5). Our model of interarea income

explains over 70 percent of the observed variation in

median family income levels among this group of counties. In fact, only for the persistently low-income counties does the model's explanatory power fall significantly below this level.

Comparison of County Groupings. Results of the in

come model are consistent across the county groupings and there are few notable exceptions. Hov^ever, it

is somewhat surprising to find the strong negative

association for the farming counties between their

family income levels and their dependence on farm income. While the farm counties as a group do not lag

seriously behind all nonmetro counties in income level,

agricultural dependence continues to be a developmental liability.

öWe had no a priori basis for expecting the sign of the

government variable to be positive or negative, except that we

do know that government jobs tend to pay relatively low

wages.

12
Natura! Resource Dependence, Rural Development, and Rural Poverty

We were unable to explain the large negative associa=

iion between dependence on government and income

levels in farming and mining counties. But this finding,

combined with the strong positive effects of government dependence on population growth in the farming

group and positive (although not significant) association for mining counties suggests that we need a much

better understanding of the composition of income and

the activities that make up the governmental sector.

The way in which the government counties are spread

across the rural landscape defies easy generalization.

However, it seems clear that most counties'

dependence on government results from some Federal

or State activity. Because such activities are largely administrative, their location is determined by a political

process, not by marketplace factors.

Perhaps the most surprising finding in our income

modeling effort is the fact that increased urbanization

is negatively associated with income levéis for the persistently low-income group. This finding is contrary to

our expectation, and to the findings for all nonmetro

counties and the natural resource groupings. Equally

puzzling is why the age structure variable is not significant in explaining differences in income among the persistently low-income counties. The lack of association

between percent nonwhite and per capita income is

also unexpected, but is probably because the persistently low-income category includes counties with

both very high and very low proportions of black population. This cancels out the race effect in the regression.

That the persistently low-income counties have been

largely outside the mainstream of development for 30

years certainly suggests that they are somehow different. But many of the summary statistics for them are

puzzling, as are a number of the regression results we

obtained. If future rural policy focuses on areawide

rural poverty, we will need a much better understanding

of why these areas are so résistent to change.

Summary of Findings

Over 1,000 nonmetro counties have a continuing

dependence on natural resources, as measured by agriculture, mining, and Federal landholdings. These

resource dependent counties account for about 42 percent of all rural counties, but contain (ess than 25 percent of the total rural population. Thus, these counties

are sparsely settled in comparison to all rural counties.

They are also less likely to be adjacent to an SMSA

and relatively (ess likely to have access to the interstate highway system. Of the natural resource counties, only those with a dependence on farming trailed

all nonmetro counties In median family income as of

1980. And farming counties lagged less than $1,000

Table 5—Effects of county characteristics on Intercounty variation in median family income, 1979^

County characteristics

Effects on median family income by county classes

Nonmetro

totai Farming Mining Federa!

land

Persistent

poverty

Location:

Percent urban, 1980

Adjacent to SMSA

South

Economic base, 1978:

Percent of income from agriculture

Percent of income from manufacture

Percent of income from mining

Percent of income from government

Demographic and human capital, 1980:

Percent of high school graduates

Employment-to-population ratio

Percent reporting disability

Percent 65 years and older

Percent nonwhite

R2

Number of counties

0.109* 0.101* 0.176* 0.226* -0.110^

.167* .213* .063* .058* .112

.025 .064* .041 -.152* .182

-.124* -.185* -.138* -.156* -.190

.103* .057* -.069** .163* .070

.154* .060* -.038 .219* .144

-.084* -.219* -.291 .036 .011

.356* .442* .430* .187* .364

.270* .142* .244* .359* .399

-.197* -.150* -.080 -.049 - .256

-.115* -.121* -.128* -.158* -.055

-.102* -.132* - .078* -.126* -.049

.727 .665 .790 .761 .569

2,424 656 199 245 242

* = significant at .01.

** = significant at .05.

^Standardized regression coefficients.

13
Deavers and Brown

behind. The three groupings of natural resource counties had poverty rates comparabie to a1! rural counties.

Cieariy, natural resource dependence is not an innportant correlate of area income level or incidence of

poverty in rural America in the 1980's. It is equally unsatisfactory in explaining recent population change of

rural counties, with the notable exception of farming

dependence, which continues to be associated with net

outmigratlon from rural areas.

In contrast, persistently poor rural counties do not have

a unique economic base profile; they are very similar to

the nonmetro county average. Forty-three of the poor

rural counties are agriculturally dependent by our

measure, 14 others are mining dependent, and 5 are

Federal lands dependent. Even more (a total of 45) are

dependent on manufacturing and government, and 18

are areas with a significant inmigration of retired people.

What differentiates persistently low-income counties is

their population profile and location, not their

economic base. Most important in that profile is low

levels of schooling, a high percentage of the working

age population v^ho identify themselves as having a

work-limiting disability, a southern location, and the

relatively large percentage of dependents (old and

young combined). The percentage of blacks in these

counties is more than double the average for all

nonmetro counties.

educated, ¡ll-housed, denied access to essential public

facilities and services, was painted vividly by the President's Poverty Commission in its 1968 report, Rural

Poverty in the United States (16). While poverty remains

a serious problem for many rural Americans, there has

been enormous social and economic progress. Thus,

generalized assistance to rural areas based on an

assumed universal disadvantage seems inappropriate.

Rural counties with areawide low personal and family

income are relatively few and geographically concentrated. The persistently low-income counties represent

one delineation of such areas. In these areas, the rural

poor are confronted by a lack of adequate human and

community facilities and are relatively isolated from

other areas that have such facilities. In many cases,

rural institutions (particularly governmental) are unable

or unwilling to provide needed assistance or support for

change. Given the distinct population profile of these

low-income areas (low level of formal education, high

percentage nonwhite, high degree of work-limiting

disability), we v^onder how much of the problem can

reasonably be solved through public and/or private

development efforts alone. Even if such efforts are

carefully targeted, the design of most development programs assumes that their principal benefits will occur

through the creation of more and better job oppor»

tunities.

Rural Policy Directions

The initial results of our efforts to classify rural coun=

ties and to provide a different perspective on the social,

economic, and political meaning of rural in the 1980's

improves the knowledge base for policy and program

development. For example, It seems clear that many

rural areas tend to have a specialized economic base.

Thus, no single sectoral policy will be appropriate in

assisting the development of rural areas. The nonagricultural character of much of rural America is increasingly shaping the future (certainly it was at the heart of

the population turnaround of the 1970's). This presents

a very different setting for development and employment policies than was the case 20 to 30 years ago. A

development policy intended to address the needs of

the entire rural and smalltown population will not succeed if focused primarily on farming and agribusiness

(20).

Federal policy designed to assist rural people and

areas has been a response to perceived and actual

rural disadvantage. The picture of rural America, with

many of its citizens poor, undernourished, underAll of the welfare reform proposals considered in recent

years would have established national minimum payment standards. They would also have made numerous

changes in asset qualification requirements and in

assumptions about family status and labor market

status that would have benefited rural residents. For

many of the rural poor, especially those in States with

low welfare payment levels and In chronically disadvantaged areas of the South, welfare reform is a key issue

for Federal rural policy. No other single policy action

would have as immediate and obvious consequences

for their well-being in terms of their ability to obtain the

goods and services essential to a decent level of living.

Our analysis provided no convincing evidence that dependence on natural resource based activities is an important constraint to population growth. Dependence

on farming or mining has a negative effect on population change in our regression analysis, but other

research has demonstrated that this negative effect

has diminished over time (14), From an aggregate

perspective, dependence on natural resources appears

to be a diminishing disadvantage to community growth.

Similarly, our analysis does not provide clear evidence

that natural resource dependence leads to a lower level

14
Natural Rssourc® Dependence, Rural Development, and Rural Poverty

of community income. Agricultural dependence does

have a negative regression effect on income level, but

the median family income or poverty rate of agricultural

counties is not substantially different from all nonmetro counties. And in the other two natural resource

county classes, income is higher and poverty lower

than in the total nonmetro category. However, individual level analysis might show that rural households

with a substantial proportion of income from natural

resources related pursuits have income problems

meriting specific attention.

For the past 20 years, the principal justification for

Federal rural development programs has been conditions of rural disadvantage. Partly as a consequence of

those programs, but largely because of general economic, demographic, and other changes, conditions in

rural communities have improved significantly. In addition to improved incomes, rural citizens have benefited

from improvements in transportation, communication,

and housing. Despite this, rural poverty persists among

a disproportionate share of our rural citizens and in

large concentrations in a few areas. We suggest that

the connection between rural poverty and natural

resource dependence is weak. It is not appropriate,

however, to conclude that natural resources and poverty are unrelated, or that natural resource policies might

not be an appropriate com.ponent of rural development

policy for some poor areas or individuals. Rather,

natural resource dependent counties are not the principal target for rural development programs which

might ameliorate the problems of the rural poor.

America in Transition. Amos H. Hawley and Sara

M. Mazie(eds.). Chapel Hill: University of North

Carolina Press. 1981.

5. Brown, David L, and Jeanne M. O'Leary. Labor

Force Activity of Women in ¡Metropolitan and Nonmetropolitan America, RDRR-15. U.S. Dept. Agr.,

Econ. Res. Serv., 1975.

6. Brown, David L. "Racial Disparity and Urbanization, 1960 and 1970," Rural Sociology. Vol. 43, No.

3; 403-425. 1978.

7. Danziger, Sheldon, Jacques van der Gan, Eugene

Smolensky, and Michael Taussig. 'Implications of

the Relative Economic Status of the Elderly for

Transfer Policy." Paper prepared for Brookings Institute Conference on Retirement Policy and Aging, Washington, D.C., Dec. 1982.

8. Deavers, Kenneth L., and David L. Brown. "Social

and Economic Trends in Rural America," Rural

Development Background Paper, Washington,

D.C.: The White House. 1979.

9. Engels, Richard A., and Richard Forstall, 'The Experience of the Nonmetropolitan Population Turnaround During the 1980's/' Paper presented to the

Southern Regional Demographic Group, Orlando,

Florida, Oct. 1984.

10. Fratoe, Frank A. Rural Education and Rural Labor

Force in tiie Seventies. RDRR-5. U.S. Dept. Agr.,

Econ. Stat. Coop. Serv., 1978.

References

1. Beate, Calvin L "The Recent Shift of United

States Population to Nonmetropolitan Areas,

1970-75," international Regional Science Review,

Vol. 2, No. 2: 113-122. 1977.

2. The Revival of Population Growth in Nonmetropolitan America, ERS-605. U.S. Dept. Agr.,

Econ. Res. Serv., 1975.

11. Heaton, Tim B., William B. Clifford, and Glenn V.

Fuguitt. "Temporal Shifts in the Determinants of

Young and Elderly Migration in Nonmetropolitan

Areas," Social Forces. Vol. 60, No. 1: 41-60. 1981.

12. Hoppe, Robert A. *'A Decade of Change in Persistent Low-Income Counties," Paper presented to

the 8th annual meeting of the National Institute

on Social Work in Rural Areas, Cheny,

Washington, July 1981.

3. Beck, E.M., and Neil Smith. "Affluence, Equality

and Poverty in Nonmetropolitan America,

1950-70." Paper presented to the annual meetings

of the Southern Association of Agricultural Scientists. Atlanta, Georgia, 1977.

4. Brown, David L., and Calvin L, Beale. "Diversity in

Post-1970 Population Trends," Nonmetropolitan

13.

14.

Agricultural Counties: Their Location,

Farms and Economies. Staff Report No.

AGESS810213. U.S. Dept. Agr., Econ. Res.

1981.

Serv.,

Lichter, Dan T., and Glenn V. Fuguitt. "The Transition to Nonmetropolitan Population Déconcentration," Demography. Vol. 19, No. 2: 211-221. 1982,

15
Deaversand Brown

15. McCoy, John L, and David L. Brown, "Health Status

Annong Low Income Elderly Persons: Urban-Rural

Differences," Social Security Bulletin, Vol. 41, No. 6:

14-26. 1978.

16. President's National Advisory Commission on Rural

Poverty. Rural Poverty in the United States.

Washington, D.C, 1968.

17. Ross, Peggy, Bernai Green, and Robert Hoppe.

"Classifying Major Socioeconomic Patterns Among

U.S. Nonmetropolitan Counties." Paper presented

at annual meeting of the Rural Sociological Society,

College Station, Texas, 1984.

21. U.S. Department of Commerce, Bureau of the Census. "Money Income and Poverty Status of Families

and Persons in the United States: 1983," Current

Population Reports. P-60, No. 145. 1984.

22. Vining, Daniel. ^'Migration Between the Core and the

Periphery," Scientific American, Pp. 44-53. Dec.

1982.

23. Wardwell, John M. "Toward A Theory of UrbanRural Migration in the Developed World," New

Directions in Urban-Rural Migration: Tfie Population Turnaround In Rural America. David L. Brown

and John M. Wardwell(eds.). New York: Academic

Press. 1980.

18. Smeeding, Tim. "The Antlpoverty Effectiveness of

In-KInd Transfers," Journal of Human Resources.

Vol. 12: 360-378. 1977.

19. Townsend, Binkley. "Who's Growing Faster?"

American Demographics. Vol. 6, No. 8: 11. 1984.

20. U.S. Department of Agriculture, Office of Rural

Development Policy. Better Country: A Strategy for

Rural Development in the 1960's, 1963.

24. Zuiches, James J., and David L. Brown. "The

Changing Character of the Nonmetropolitan

Population, 1950-75," Rural U.S.A.: Persistence

and Change. Thomas R. Ford(ed.). Ames: Iowa

State University Press. 1978.

25. Zuiches, James J. "Residential Preferences and

Migration Theory," New Directions in Urban-Rural

Migration: The Population Turnaround in Rural

America. David L Brown and John M.

Wardwell(eds.). New York; Academic Press. 1980.

16
Other Reports of Interest on Rural Issues

Physicians In Nonmetro Areas During the Seventies shows that the gap between the number of

physicians in nonmetro and metro areas widened

during the seventies, with nonmetro areas lagging by almost 100 physicians per 100,000 population. This report describes availability of physi^

Gians in nonmetro areas in light of population

changes and demand for medical care. RDRR-46.

March 1985. 28 pp. $150. Order SN: 001019-00380-4.

Housing of the Rural Elderly finds that the number of rural elderly households rose 16 percent

between 1974 and 1979 compared with a 10-percent

increase for all U.S. households, based on the

1979 Annual Housing Survey. Most of the U.S.

elderly live in adequate housing, but 27 percent

of the elderly renters and 18 percent of all elderly

living in the South have inadequate housing. In

1979, 15 percent of the rural elderly lived in adequate housing compared with 8 percent of the

urban elderly. RDRR-42. July 1984. 20 pp. $1.50.

Order SN: 001-019-00335-9.

A Profile of Female Farmers in America discusses social and economic characteristics of

female farmers, including age, race, size of

household, farm and off-farm income, types of

farms female farmers most frequently run, and

value of agricultural products sold. Although the

number of U.S. farms is dropping, the number of

female farmers is rising. They tend to run smaller

farms and earn less than their male counterparts.

RDRR-45. January 1985, 32 pp. $1.50. Order SN:

001-019-00378-2.

Chartbook of Nonmetro-Metro Trends is a quick

check on metro and nonmetro socioeconomic

trends. It presents colorful charts, tables, maps,

and text tracing differences in population,

employment, income, poverty, housing, and government betvv/een nonmetro and metro America.

RDRR-43. September 1984. 48 pp. $2.50. Order SN:

001-019-00351-1.

Patterns of Change in the Metro and Nonmetro

Labor Force, 1976-82 reveals that nonmetro areas,

particularly farm areas, lagged behind metro

areas in employment growth during the 1976-82

period. This reversed a pattern of faster nonmetro

growth occurring in the late sixties and early

seventies. RDRR-44. December 1984. 28 pp. $2.00.

Order SN: 001-019-00358-8.

Distribution of Employment Growth in Nine Kentucky Counties: A Case Study shows that people

moving to a nonmetro area held a disproportionate

share of jobs in growing business establishments

and of better paying executive jobs. Manufacturing was the study area's major economic driving

force, but the private service sector (which provided services to the manufacturing sector and to

the area's growing population) was an important

contributor to job growth between 1974 and 1979.

RDRR-41. August 1984. 44 pp. $2.25. Order SN:

001-019-00337-5.

A New Periodical of Rural Ideas

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rural America, subscribe to Rural Development Perspectives. An eclectic mix of rural

information and ideas, with each article

written in a crisp, nontechnical manner,

generously illustrated with photos, maps,

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and a section of charts and maps measuring various rural conditions. It costs only

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