aHT39 2

.A53 îd States

rtment of

julture

Economic

Research

Service

Rural

Development

Research Report

Number 55

Will Employment

Growth Benefit All

Households? A Case

Study in Nine

Nonmetro Kentucky

Counties

Donald K. Larson

Claudia K. White
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Wilt Employment Growth Benefit All Households? A Case Study In Nine

Nonmetro Kentucky Counties, by Donald K. Larson and Claudia K. White,

Agriculture and Rural Economics Division, Economic Research Service, U.S.

Department of Agriculture. Rural Development Research Report No. 55.

Abstract

Overall employment growth in a rural area will probably not benefit all households

or residents in that area. In a nine-county area of south-central Kentucky, rapid

employment growth between 1974 and 1979 did create new job opportunities.

However, only 18 percent of the households had members who took advantage

of new jobs. The employment growth also did not reduce the area's overall poverty

level. About as many households fell into poverty as left the poverty ranks during

the study period. Some population groups, such as households headed by women,

remained economically disadvantaged despite the area's growth. Other groups,

such as the elderly, maintained their income status by relying on public and private

income transfer programs.

Keywords: Rural employment growth, households, income status, poverty status,

female heads of households, elderly heads of households, longer term residents,

regression model.

Acknowledgments

Linda M. Ghelfi and Maurice R. Landes helped design the study. Douglas Kleweno

and Lawrence S. Williams developed the sample and survey materials. Howard

Utter was the field data collection coordinator in the Louisville, Kentucky, office of

the Statistical Reporting Service (SRS). Robert Coltrane and Thomas A. Cariin

supervised the study, and Donald K. Larson was the project leader. The authors

extend their appreciation to all enumerator supervisors and enumerators whose

tireless efforts in obtaining completed interviews made this report possible. Joe

Blackwel! developed the variance program for statistical testing. Clevie Gladney

and John Baumgartner developed appropriate computer tapes for analyzing the

data, and Joyce Su provided programming assistance. Sharon Jonesand Dorothy

Atkins programmed the data for figure 2. Sharon Davis and Linda Rail typed the

various drafts of the report.

Washington, DC 20005-4788 January 1986

IN
Contents

Page

Summary ..... ,\ v

Glossary vi

JntrodUGirofî ..... 1

Study Site and Data . 2

Methodology ........ 2

Households . . . ... ......................... 2

Relative Income Status . ...... . . 2

Characteristics of Moijséholds . . 3

Analytical Procedures. 6

Factors Affecting Household Income Status 8

Overall Change in Income Status . 9

Distribution of Effeeis. 9

Households Apart from Employment 10

Households Headed by Women, January 1980 11

Alleviating Poverty . 13

Household Poverty Status, 1974-79 13

Household Atthbules by Poverty Status . . 14

Households Escaping Poverty . 16

Households Poor in both 1974 and 1979 ................ 16

Households Entering Poverty 16

Summary on Poverty . . 17

ImpHcations 17

References . 18

Appendix: Regression Models 21

IV
Summary

Overall employment growth in a rural area will probably not benefit all households

or residents in that area. In a nine-county area of south-central Kentucky, rapid

employment growth between 1974 and 1979 did create new job opportunities.

However, only 18 percent of the households had members who took advantage

of the new jobs. Employment growth thus does not benefit all households, nor

does it reducethe area's overall poverty leveL About as many households fell into

poverty as left the poverty ranks during the study period.

An estimated 44,340 longer term resident households in rural Kentucky that were

demographically similar to all U.S. nonmetro households were analyzed. Here are

some of the authors' specific findings:

• For households located in the study area continuously between 1974 and

1979, their average relative income level changed very little as a result ofthe

area's employment growth. Although 28 percent reported improved relative

incomes, another 22 percent lost ground when household members either

retired or reduced their annual work hours.

• Households headed by elderly persons maintained their relative incomes

because they were dependent on public or private income assistance

programs which were indexed to the Consumer Price Index.

• Households headed by women had a limited benefit from the area's employment growth even though that growth increased the number ofjobs available

to women. Most of the women who benefited from the job growth lived in

households headed by men.

• Expanded job opportunities benefited a limited number of poor households

but did not lower the area's overall poverty level. About 21 percent of the

longer term resident households were classed as poor in both 1974 and 1979.
Glossary

Statrstical testing and primary sampting unit:

Significant difference — A eomparison between two

variables was statistteaily significant at the 95-percent

confidence level In most cases when the observed

difference was greater than twotimes the standarij error

ofthe difference. The variables tested were in the form

of totals, ratios, percentages, dollar values, and so forth.

Prin)ary sanipling unit — Primary sampling uni^ts

(PSU's) are associated with the frame sample. For the

list frame, establishments were the PSU's; for the area

frame, land segments of varying size were the PSU's.

PSU^s serve as the base for deriving variances, as

opposed to observations, in a multiframesurvey design.

Household and related terms:

Household — A group of persons not necessarily

related by blood or marriage, whose usual place of

residence is in a house, an apartment, agroup of rooms,

or a single room occupied as separate living quarters.

Existing household — The household existed in both

1974 and 1979 regardless of its location, and the head

or spouse or both in 1974 were still present during

January 1980.

Longer term residents — Members of those households who lived in the nine-county area during both 1974

and 1979 where the head or spouse or both in 1974

were still present during January 1980.

Newer residents — Members of those households

existed in both 1974 and 1979, but the household was

located outside the study site in 1974. Head or spouse

or both in 1974 were still present during January 1980.

New households — Households which did not exist in

1974, and households wherethe head or spouseor both

in 1974 were not thehead ofthe household in January

1980.

Linked households — The household contained at

least one person who was employed by a list frame

establishment that participated in the survey.

Nonllnked households — The household contained no

members who wereemployed by a listframe establishment that participated in the survey. All adult members

ofthehousehold were eitherall unempiüyedvt)ut ofthe

labor force, self-employed, employed by an establishment not on the list, employed by an establishment on

the list that refused to participate in the survey, or

employed outside the study site.

Persistently low Income couniy — The county's per

capita income was In the lowest fifth of all nonmetro

counties in 1969and 1979.

Surwy sample design:

List frame — The listframesample was comprised of a

list of private-sector establishments and government

units located in the nine-county area. A subsampie of

employees was drawn from the surveyed list frame

establishments which subsequently became the list

frame sample of households.

Area^frame — Theareaframeconsistedof a two- stage

stratified cluster sample, where the first stage involved

sampling segments and the second stage involved

sampling establishments and households. The area

frame provided asample of establishments andhouseholds not identifiedby the listframe. Thearea frameand

list frame together represented the totaf popuiation of

establishments and households.
Will Employment Growth Benefit All Households?

A Case Study in Nine Nonmetro Kentucky Counties

Donald K. Larson and Claudia K. White'

Introduction

Many local officials in nonmetro areas welcome employment expansion because it is perceived to improve the

general well-being of local residents. Enhancing the

well-being of all rural residents, particularly the disadvantaged, is one major objective of Federal rural development efforts (46).^ Income is frequently used to reflect

household or family well-being, and changes in income

are often used as a measure ofthe effects of employment

growth (24). Exactly how employment growth is distributed among the population and the resulting effect on

income distribution, however, have not been fully

explored, even though some segments of a population

may not benefit from increased job opportunities

(20,28,31),

We identified the variables that explained changes in

household income status between 1974-79 in a ninecounty area in south-central Kentucky. "Income status"

represents a relative measure ofthe income relationship

between households. We examined the role that employment expansion played in explaining the change in

income status. The period 1974-79 saw rapid employment growth in the study area. We gave special attention

to the extent that growth in job opportunities affected the

area's economically disadvantaged households, particularly longer term households that existed in the study

site in both 1974 and 1979. The 1979 data, collected in

January 1980, are the most recent available for a study

of this nature in nonmetro Kentucky.

* The authors are economists in the Agriculture and Rural Economics

Division, Economic Research Service, U.S. Department of Agriculture,

Washington, DC.

^ Italicized numbers in parentheses identify items in the References

at the end of this report.

Employment growth is considered an important instrument for removing rural areas from economic stagnation

and enhancing the general well-being of rural residents.

While employment expansion will increase aggregate

income (30), two questions remain. How will that increased income be distributed? What effect will it have

on the income status relationship one household, especially a longer term household, has with other households

in the same genera! area?

Many nonmetro communities or areas have gained in

aggregate or per capita income (7,3,12,16,23,25,27,

30). When a research focus shifts to the effects of

employment growth on individual or household income,

the outcomes vary considerably. Studies that have

focused on income distribution suggest some segments

of the population received little or no income gains from

employment growth (1, 2, 5, 18, 23, 25, 26, 29). For

example, there was no change in income gains by heads

of households in an area where employment grew

compared with a nongrowth area (1). Yet, other studies

have shown a more equal income distribution resulting

from expandedjob opportunities f9,17,19,24,32,47).

Some earlier studies attempted a distributional analysis

of employment growth by using aggregate income

distribution data, but the findings were questionable

because factors other than employment growth can alter

income distribution among population segments (28,

33). For example. Government transfer payments measured on a per capita basis grew nearly 200 percent'

between 1969-77 in the nonmetro South (14). These

payments could affect the distribution of income without

employment expansion. While these earlier studies have

provided useful insights and plowed unbroken ground,

empirical gaps still remain concerning the distributive

effects from employment growth, particularly the effects
Donald K. Larson and Claudia K. White

on household ¡ncome status and poverty status. Given

the diversity annong nonmetro areas, findings may vary

widely. Thus, generalizations about the distributional

effects of employment growth on househotó income

status require an examination of different nonmetro

areas. This study attempts to fill one part ofthat empirical

gap on the distribution of benefits resulti^ng from rapid

employment growth by studying one type of nonmetro

economy.

Study Site and Data

This report's data represent a cross-section of households residing in Clay, Clinton, Knox, Laurel, McCreary,

Pulaski, Russell, Wayne, and Whitley counties in Kentucky during January 1980 (fig. 1).^ The area in 1980

had approximately 76,400 households with 226,800

people (34,35,45). Between 1970 and 1980, the area's

population grew about 30 percent, 2.5 times the national

growth rate. The areahad a very small minority population. Between 1970 and 1979, employment increased

44 percent, with the greatest employment growth in

manufacturing, wholesale and retail trade, mining, and

services (6). Although this area's service sector expanded rapidly during our study period (1974-79), the

local economy dependedheavily on manufacturing. The

area's agricultural sector was a relatively small source

of employment. All the counties except Laurel County

were classed as persistently low-income counties in

1969 (8). Six counties (Ctay, Clinton, Knox, McCreary,

Russell, and Wayne) retained this designation in 1979,

despitethe area's impressive employment growth during

the seventies (15).

Methodology

We examined two aspects of the local population inour

nine-county study area: households and the relative

income status of those households.

Households

The individual, household, family, and community are

units frequently used in past research efforts for studying

the effects of employment growth on incomedistribution

(4, 9, 10, 17, 19, 21). For this report the household is

the appropriate unit for analysis because about 10

percent of the surveyed units contained persons living

togettier who were unrelated; family, by definition,

Figure 1

Counties in Kentucky study area

Vv/ \' ^ /Whitley

Clinton)Monticello yMcCrearyiyviiiiarrisburgV

' «Albany A.-uu.^.. ^.«„S • i

comprises persons who are related by blood or marriage.

The sample households are representative of the community in January 1980, butwe do not havearepresentative sample ofthe communities' households for 1974.

The individual is too narrow a concept because itignores

customary dependency relationships among individuals

in a household. For example, the decision on how

income is spent often stems from joint decisions of

housetiold members. Also, earnings from two or more

working members are often pooled in a household unit;

thus, the incomeof a single member may not reflect the

relative economic status of all members of the household.

Relative Income Status

Researchers have developed several methods of

measuring economic status (4, 10, 11, 13, 21, 38, 39).

We decided that the most appropriate measure for our

analysis was a ratio of total nominal household income

divided by an appropriate U.S. official poverty threshold

value.^ This measure represents a household's relative

income status that has the following general form:

Relative income status =

HNIi HNIi

HPT HPTi

^ For details about the sample design, see (6). The survey used a

randomîy stratified mufti pie-frame design.

^ The Bureau of the Census' standard poverty íhreshoíds for 1974

and 1979 were used as the ratios' denominators (36, 37).
Will Employment Growth Benefit All Households?

where

HNI = total nomina! income of houseliold, all

sources,

HPT = U.S. official poverty level for household In

analysis,

i = 1979, the year ofthe survey data on income,

and

j = 1974, the survey's base time period.

The surveyed households had an estimated combined

aggregate income of about $737 million for 1979. Most

of that, about 80 percent of the $737 million, came from

various wage and self-employed jobs held by household

members in all households and in households which

were not poor (fig. 2, charts A and B). Although income

from retirement was relatively small overall, this income

source was important among households where members did not work during 1979.

A similar measure has been used in a recent research

project conducted by the University of Michigan (10,21).

This ratio takes into account both the effects of changes

in income status (such as employment) and household

composition (such as number of household members);

this latter effect is not reflected by total money income

(21). By using the U.S. official poverty standards in the

denominator, the ratio further accounts for household

economies of scale in consumption and other basic needs.

Characteristics of Households

The Kentucky household survey represents an estimated

61,250 households in January 1980, containing nearly

175,000 persons of all ages (table 1 ). The area's households were about 99 percent white and not of Hispanic

origin. The households averaged 2.8 persons, which was

similar to the national average size of all nonmetro

households. Nearly 75 percent of the household members were of labor force age, that is, adults 16 years of

age and older at the time of the survey (6).

Mean household income in the study site for 1979 was

about $12,000, less than $5,000 below the mean for all

U.S. nonmetro households (40). Over half of the surveyed households had a total income in 1979 under

$10,000; the median income was $9,500 (table 1 ). The

surveyed households contained an average of 1.1

Income earners, well below the national average of 1.6

(41). Among the surveyed households, 28.5 percent had

no earners in 1979, more than double the national level

of 14 percent (41). Nearly 28 percent of the surveyed

households were classed as poor in 1979, more than

double the 12-percent level for all U.S. nonmetro areas

and much higher than the 18-percent rate for nonmetro

Kentucky in 1979 (36). The relatively high number of

households without any earner contributed to the relatively low average household income and the relatively

high incidence of poverty among the surveyed households for 1979. Also, wage levels of most of the area's

employers were below the national average (6).

Compared with nonpoor households, poor households

had a different pattern of income sources in 1979.

Aggregate income came about equally from earnings

and retirement sources among households classed as

poor in 1979 (fig. 2, chart C). Income from earnings and

retirement made up 35 percent and 32 percent, respectively, of the aggregate income received by poor households. Public assistance was also an important source

of economic support among poor households at more

than 20 percent of aggregate income.

Most of the surveyed heads of households were men

who had less than a high school education (table 1).

Household heads were on average 48 years old and had

finished just less than 10 years of formal schooling.

Nearly 25 percent of the area's household heads were

classed as elderly; that is, the head was 65 years or

older at the time or the survey. The area's percentage

of households headed by elderly persons closely resembled that for the Kentucky and U.S nonmetro areas in

^979 (42, 44).

The central objective of the analysis is to determine how

the area's longer term resident households, those

sample households located in the study site in both 1974

and 1979, benefited from the area's employment

growth,"* These households are one of the concerns of

rural economic development policy. Some jobs created

during this 5-year period were taken by persons in newly

formed households as well as persons in existing households. Among all surveyed households, about 15 percent, or 9,270 were "newly formed households," that is

the household unit did not exist in 1974 (table 2). These

households included two groups. The first were households formed after 1974. The household head was

typically a married man, a new entrant to the labor force,

and 22 to 29 years old. If children were present in the

"* A household was defined to exist in both time periods if the head

in 1979 was also the head in 1974 or was the spouse of a deceased

1974 head. No 1974 income data were collected for households which

did not conform to this rule.
Donald K. Larson and Claudia K. White

Table 1 —Household charactenstics, nine-county Kentucky area, nonmetro Kentucky, and U.S. nonmetro areas, January 1980

Characteristics Unit Nine-county

Kentucky area

Nonmetro

Kentucky""

U.S.

nonmetro^

Total households Number 61,520 689,090 19,912,700

Total persons, all ages do. 174,930 1,972,700 55,516,190

Household economic status, 1979:

Total income—^

Mean Dollars 11,980 15,080 16,930

Median do. 9,500 11,960 14,040

Jnconae status ratio—^

Mean Ratio 2.12 NA NA

Median do. 1.58 NA NA

Poverty status—^

Poor Percent 27.6 18.3 12.0

Not poor do. 72.4 81.7 88.0

Earners in household:

None do. 28.5 16.9 14.1

One do. 38.3 38.1 33.5

Two do. 29.0 37.1 41.4

Three or more do. 4.2 7.9 10.8

Average number of earners Number 1.1 1.4^ 1.6

Size of household:

One person Percent 14.9 18.3 20.9

Two persons do. 36.6 30.7 32.2

Three persons do. 20.4 20.2 17.4

Four persons do. 16.6 17.0 15.7

Five or more persons do. 11.5 13.8 13.9

Average size Number 2.8 2.9 2.8

Head of household:

SexMate Percent 81.2 77.2 75.5

Female do. 18.8 22.8 24.5

Age, 1979—

16-34 years do. 28.9 29.6 28.8

35-54 years do. 32.9 31.5 31.0

55-64 years do. 13.8 15.6 16.1

65 years and older do. 24.4 23.3 24.1

Average age of head Years 48.5 NA NA

Educationlevel, 1979—

Lessthanhighschool Percent 59.9 NA 55.8

High school do. 23.7 NA 13.5

Beyond high school do. 16.4 NA 21.0

Average years of schooling completed Years 9.8 NA NA

NA = Not available.

'Source: {44, 45).

^Source: {40, 41, 43).

^Total income before deductions received by all household members from all sources except the sale of land, buildings, stocks, or other capital

assets during the year.

"^Total household income divided by an appropriate U.S. official poverty threshold value for each household.

^We used the Bureau of the Census standard poverty thresholds for 1979 to determine poverty status of the surveyed households (36).

^Estimated.
Figure 2

Distribution of Aggregate Total Household Income by Source

A. All Households

Earnings^

Unemployment and

worker's compensation

B. Households That Were Not Poor

C. Poor Households

12.6%

10.7%

21.6%

3.1%

35.0%

^2-

Public assistance'

Retirement^

Other income"*

1/ Wage and salary earnings: net income frona nonfarm

business, partnership, or professional practice; net

income from a farm business.

2/ Aid to Families with Dependent Children, Federal and

State Supplemental Security Income, and other public

assistance.

3/ Social Security, railroad retirement, private pension and

annuities. Government employee pensions, and

military retirement

4/ Veterans' payments, interest on savings bonds, alimony.

dividends, child support, net rental income or

royalties, estates or trusts, and any other sources

not reported.
Donald K. Larson and Ctaudia K. White

household, they were 5 years old or younger. These

households made up about 72 percent of all households

in the newly formed category. The second group, or 28

percent, included households in which the head in

January 1980 was not the head in 1974.^ There was

one exception to this second rule. If the current head

was the widowed spouse of the household's head in

1974, who had since died, these households were

placed in the existing household category.

Nine percent of the surveyed households were newer

residents, that is, the household existed in both 1974

and 1980, but it was located outside the study site in

1974 (table 2). Typically, these households were headed

by a man between 29 and 40 years oíd, who was, on

average, better educated than heads of longer term

resident households. However, the newer household

heads did not have as much education as heads of newly

formed households. The study site's job growth did

provide employment opportunities for persons in these

newer resident households (6).

Noneconomic factors or other factors not related tojobs

are frequently cited as reasons for relocation (18, 22,

48). About 80 percent ofthe newer resident households,

those that moved to the area between 1974 and 1980,

reportedthey moved for reasons which were not directly

related tojobs or money. As a group, these households

reported lower average nominal and real incomes in

1979 than they had in 1974. Nearly 20 percent contained

members wfiotook a wage cut. Thus, their income status

was affected by some events unrelated to the study site's

expansion of jobs.

About 76 percent of ali surveyed households were

classed as longer term resident households (table 2).

Heads ofthese households weretypically male, over 50

years old, and had less than a high school education.

The 1979 average income status for tbese households

did not differ significantly from that of newiy formed

households, but it was significantly below that reported

by the newer resident households.

Analytical Procedures

We examined in two phases the hypothesis that employment growth in the study site affected household income

status. The first phase involved a multiple regression

analysis to identify which factors best explained changes

in household income status. The second phase was a

tabular analysis showing the dynamics, or the disthbutional consequences, of those factors that significantly

explained change in household income status.

We used seven categories of independent variables

drawn from other research studies to explain changes

in household income status (5, 9, 10, 19, 21, 30). The

variables reflected household structure, employment

status, unearned sources of income, 1974 income levels,

residency, demographic characteristics of the head of

the household, and employer characteristics. We were

particularly interested in the influence of employment

status and employer characteristics in explaining

changes in househoid income status. The remaining

variables act as control variables; we knew from previous

research that these variables affect changes in household income status, and we wanted to account for their

effect in the regression model. To do so, we used a

weighted least-squares multiple regression analysis; we

transformed the expanded estimates so that the new

weights summed to the number of raw observations.^

The dependent variable was the change in household

relative income status, which was defined in the section

describing the methodology.

We performed the regression analysis in two stages.

The first stage involvedanalyzing changes in household

income status among those households linked with

employers. These households were a smaller subset of

the existing, longer term resident households. This stage

was necessary to determine whether any employer

characteristics were associated with changes in household income status. The Appendix presents a detailed

explanation of the regression models. The first stage

regression model contained five independent variables

that were significant toward explaining changes in

income status (app. table 1). Household size was one

variable, and an increase in size resulted in adecline in

income status. Three employment-related variables

were also highly significant. Changes in number of

workers within household, total annual hours worked by

household members, and household head's real weekly

wages were positively associated with changes in

^ These households experienced a major structural or compositionat

change between 1974 and 1979. Because household connposition

change has a considerable effect on change in income (21), 1974

income data were not collected from these households.

^ We reseated the expanded estimates to overcome the problem of

generating greatly reduced standard errors on the regression coefficients. For further details on this method, see (7).
Will Employment Growth Benefit All Households?

Table 2—Characteristics of newly formed and existing households, January 1980

Unit

Newly

formed

household^

Existing households

Characteristics Newer term

resident^

Longer term

resident^

Total households Number 9,270 5,530 46,720

Household economic status, 1979:

Total income—"^

Mean

Median

Dollars

do.

11,120

8,590

13,500

11,180

11,970

9,490

Income status ratio—^

Mean

Median

Ratio

do.

2.17

1.58

2.23

1.82

2.10

1.54

Poverty status—^

Poor

Not poor

Percent

do.

26.8

73.2

15.5

84.5

29.2

70.8

Earners in household:

None

One

Two

Three or more

Average number of earners

do.

do.

do.

do.

Number

13.6

47.8

36.9

1.7^

1.3

14.8^

42.9

37.1

5.2^

1.4

33.3

35.6

26.4

4.7

1.0

Size of household:

One person

Two persons

Three persons

Four persons

Five or more persons

Average size

Percent

do.

do.

do.

do.

Number

16.6

41.5

24.6

11.5

5.7^

2.5

6.9^

26.5

24.6

22.1

19.9

3.4

15.5

36.9

19.0

16.9

11.7

2.8

Head of household:

SexMate

Female

Percent

do.

70.2

29.8

90.5

9.5^

82.3

17.7

Age, 1979—

16-34 years

35-54 years

55-64 years

65 years and older

Average age

do.

do.

do.

do.

Years

81.4

15.3

2.1^

1.3^

28.8

36.2

36.1

14.8^

12.9^

42.3

17.7

36.0

16.0

30.3

53.1

Education, 1979—

Less than high school

High school

Beyond high school

Average years of completed schooling

Percent

do.

do.

Years

39.1

38.4

22.5

11.4

55.9

23.9

20.2

10.8

64.5

20.7

14.8

9.4

^ Newly formed after 1974—did not exist during 1974.

^The household existed outside the study area during 1974.

^The household existed within the study area during 1974.

"^Total income before deductions received by ail household members from ail sources except the sale of land, buildings, stocks, or other capital

assets during the year.

^Total household income divided by an appropriate U.S. official poverty threshold value for each household.

^The Bureau of the Census standard poverty thresholds for 1979 were used to determine poverty status of the survey households (36).

^Estimate based on fewer than 10 unweighted observations.
Donald K. Larson and Claudia K. White

income status. For example, a household's relative

income status improved when more members were

working in 1979 than were working in 1974. The fifth

independent variable was households whose real 1974

income was $19,000 or more. This variable had a

significantly negative coefficient that indicates these

households had smaller income status changes than

households in the third compared group.

None of the employer characteristics was significantly

associated with explaining changes in a household's

relative income status in the first stage regression model

(app. table 1). We observed substantial variation in

wages paid full-time workers by establishment type, size,

general wage level, and employment growth status.

Because employer-linked households were widely

scattered among these different employer characteristics, variations among these groups probably do not

explain changes in a household's relative income status.

Few ofthe linked workers changed employers over the

study periods. Thus, the employment growth process

accommodated new entrants to the labor force but did

not cause massive job changes for those employed in

both time periods.

The second-stage regression analysis differed from the

first in two important ways. First, the employer characteristics were dropped as independent variables. Second, unlinked households were added to see if their

inclusion altered the significance of the remaining variables. This second stage included not only linked households, but also households where members were either

all unemployed, out of the labor force, self-employed,

employed by establishments not on the list, employed

by establishments on the list that refused to participate

in the survey, or employed outside the study site. Ail the

variables that were significant in the first regression

analysis were also significant in the second regression

analysis (app. table 2).

Change in the household size variable had a negative

sign (app. table 2); with all other variables held constant,

an increase in household size results in a decline in

income status. An opposite effect would occur with a

decrease in household size. Changes in household income status and three other variables^change in employment, change in annual hours worked, and change

in head's weekly real wage—were positively related.

Thus, income status improved when additional household members became employed, already employed

members worked more hours in 1979 than 1974, or the

head's weekly wage level rose faster than the inflation

rate over the 5-year period. The highest 1974 household

real income level variable (the $19,000 and over group)

was negatively related to omitted class of households,

that is, the third 1974 household real income group.

However, regression model 2 contained two additional

independent variables that were significant. Households

headed by women and households reporting "other

income" in 1979 but not in 1974 were significant variables

in explaining changes in income status (app. table 2).

The first of these two had a negative relationship with

change in incomestatus andthe second hadapositive

association. We presented only five ofthe seven significant variables in the tabular analysis. Households

reporting "other income" in 1979 but not in 1974 were

excluded because the number of observations was not

sufficientto draw any conclusions. Wealso excluded the

variable representing the highest category of 1974

household real income. This variable had a negative

relationship caused by persons leaving the work force,

such as retirement. Had all four 1974 household real

income variable categories been significant with their

observed signs (app. table 2), then household income

status would have been more equally distributed among

the households. This situation would have then warrantedan examination aboutthe role the area's employment growth played in equalizing income status.

Factors Affecting Household Income Status

Employment growth is viewed by many Federal, State,

and local government officials as one important way to

improve the income of all rural residents (46). The "all"

implies that gains in income induced by employment

expansion will be distributed equally among the residents

and thus significantly improvethe overall income status

level. We studied 44,340 longer term resident households to determine whether or not employment growth

in the Kentucky site was accompanied by a significant

change in the average household income status between

1974 and 1979. We eliminated 2,380 longer term resident

households (about 5 percent) from the analysis because

of nonresponses regarding 1974 household income

data. These nonresponses were a random event and

not associated with any particular primary sampling unit

or household characteristic.

Most of the longer term resident households we analyzed

showed no appreciable change in income status between

1974 and 1979. Second, only a relatively small portion
Will Employment Growth Benefit All Households?

of these households benefited directly from the area's

expansion of jobs. However, the regression analysis

shows those households that did benefit from employment growth had their income status gain significantly

over the 5-year period.

Overall Change in Income Status

There was no significant relationship between the area's

growth in job opportunities and the overall change in

Income status among the longer term resident households (table 3). The mean ratio change of -0.03 did not

differ significantly from zero. This finding supports other

research on this same topic (5, 23). About 62 percent

of these households had little or no change in their

relative income status over the 5-year period. These

findings also show that gains in income status among

some households can be offset by declines among other

households. The same proportion of households experienced large income status gains as experienced large

income status losses. Researchers who used aggregate

level data and arrived at a similar conclusion—industrial

growth has no significant effect on household income—

seemingly overlooked this result, that not all households

will experience positive income gains during a period of

employment expansion.

Table 3—Distribution of longer term resident households

by change in relative income status, 1974-79

Item Unit Longer term

resident households

Total Number 44,340

Mean change in income

status (1979 ratio

minus 1974) Ratio^ -0.03

Change in income status,

1974-79^ Percent 100.0

Large decrease do. 3.6

Moderate decrease do. 16.5

Little orno change do. 62.4

Moderate increase do. 13.6

Large increase do. 3.9

^The average value of the differences between the 1979 poverty

status and that for 1974.

^Poverty status change levels were defined as:

(a) Large decrease, ratio difference was equal to or less than

-1.900;

(b) Moderatedecrease, ratio difference was-0.600 to -1.899;

(c) Little or no change, ratio difference was -0.599 to +0.599;

(d) Moderate increase, ratio difference was f 0.600 to + 1.899;

(e) Large increase, ratio difference was equal to or greater than

+ 1.900.

Distribution of Effects

The area's impressive job growth between 1974-79 was

distributed among a relatively small proportion of the

longer term resident households. Only 18 percent of

these households had more workers in 1979 than in

1974 (table 4). Most ofthe longer term resident households were highly stable over the 5-year period. For

example, almost 45 percent ofthese households had no

change in number of members working. Household size

remained unchanged among nearly 65 percent ofthese

households. However, as verified by both the regression

and tabular analyses, when a change took place, such

as in employment or annual hours worked, a household's

income status was significantly altered, either positively

or negatively depending on direction of the change.

Despite the area's impressive job growth, some longer

term resident households exhibited changes that ran

counterto what one would expectfrom economic growth.

For example, almost 10 percent of these households

reported a decline in number of household members

working (table 4). Twelve percent of the households

reported reduced total annual hours worked, and nearly

10 percent reported a decline in the head's real weekly

wage. This dynamic nature of employment status

changes among some households can produce a negligible overall net effect on the area's average household

income status.

In summary, the lack of a relationship between income

status and the area's employment growth may be

explained in at least three ways. First, employment

among existing longer term resident households was

generally stable. And, the expanded and contracted

employment efforts of the 5-year period resulted in an

insignificant change in overall relative income status.

Second, about 28 percent of the households we analyzed

had members who were not employed at anytime during

the entire 5-year period. Thus, household income status

hinged upon unearned sources of income, that is income

sources that were apartfrom the expansion of the area's

employment activity. Third, the survey data do not

provide sufficient information to consider how newly

formed households affected the overall average household income status. These households, which were

excluded from the analysis, have claims on the area's

employment growth and thus on the total income generated in the study area. However, there was no 1974

base income available for the newly formed households.
Donald K. Larson and Claudia K. White

Also, we do not have any data on households that were

located in the area during 1974 but left before 1979.

Households Apart from Employment

The literature suggests that individuals who do not

benefit from the area's economic expansion may find

themselves in a relatively poorer economic situation after

employment opportunities expand (30, 31). This argument carries over to households by implying that households containing persons who do not benefit from an

area's employment growth may be relatively worse off

economically after, than before, employment opportunities grew. About 28 percent of the longer term

resident households were not directly affected by the

area's employment growth because the head was not

employed in both 1974 and 1979 (table 4). Inthe households with fewer workers, most often the head withdrew

from the labor force after 1974 primarily to retire. This

assertion merits attention because households that are

adversely affected by employment growth should be the

focus of policy and programs seeking to improve their

income status.

Table 4—Distribution of existing, longer term resident households by factors affecting household Income status, 1974-7S

item

Total

Factors affecting household income status

between 1974-79:

Employment status and change—^

No change in number working

More workers

Fewer workers

None working in 1974 and 1979

Total annual hours worked status and

change—"^

Large decrease ( -1,000 or more hours)

Moderate decrease ( - 200 to - 999 hours)

Little or no change ( -199 to 199 hours)

Moderate increase (200 to 999 hours)

Large increase (1,000 hours or more)

Not applicable households^

Head's real weekly wage status and change—

Large decrease ( - $100 or more)

Moderate decrease ( - $30 to - $99)

Little, no change {- $29 to $29)

Moderate increase ($30 to $99)

Large i ncrease ($100 or more)

Not applicable households^

Household size status and change—

Nochange

More members

Fewer members

Longer term

resident households

Mean value change in income-status

ratios, 1974-79

Number

44,340

Percent

44.8

17.8

9.8

27.6

4.1

7.9

23.5

5.9

3.4

55.2

3.4

6.1

15.1

12.0

4.8

58.6

64.5

15.1

20.4

Ratio value

-0.03^

-.160

.433^

-.5503

.067

-1.108^

- .288^

-.222^

.554^

.465^

.075

-.800^

-.200^

.072

.147^

.605^

-.082

- .052

-.440^

.343^

^An average of the differences between the 1979 income status and that for 1974.

^Household members' change in employment status.

^The change differed significantly from zero.

^Change in annual hours worked pertains only to households where there was no change in members' employment status.

^Statisticai test not performed because there were fewer than 30 unweighted observations.

^Households where employment status among members changed between 1974-79 and includes households where no member was working

in both years.

^Includes those heads who were self-employed and heads who were not employed.

10
Will Employment Growth Benefit All Households?

The analysis indicates that income status for households

where the head was not employed in January 1980 was

not significantly altered between 1974 and 1979. The

income status for households with a nonworking head

was significantly lower than that for households with

employed heads in both 1974 and 1979 (table 5). But,

the income status gap between households with employed and with nonworking household heads did not

widen over the 5-year period. Why didn't the relative

income status decline for those households with nonworking heads? We tried to answer this question by

examining selected economic and noneconomic charactenstics.

The regression analysis results show that change in

income status among households headed by elderly

persons was not significantly different from households

where the head was 35 to 54 years old/ For the Kentucky

study site, nonworking heads generally were males,

elderly, and had less than a high school education (table

6). Their major source of economic support came from

nonearned income sources. For example, about 80

percent of the households with nonworking heads

reported that income came from retirement-related

sources, largely Social Security. As expected, public

assistance as an income source was also more prevalent

among households where the head was not working.

Social Security and Supplemental Security Income (the

public assistance reported by most households headed

by elderly persons) are indexed by the national Consumer Price Index, thus helping the elderly to maintain

real income levels over time.

^ The class of household heads 35 to 54 years old was the omitted

group against which the household income status changes were tested

(app. table 2).

Table 5—Relative income status among existing,

longer term resident households by

head's employment status, 1974 and 1979

Average income status ratio for—^

Item

1974 1979 Difference

1979-74

Head's employment status:

Not working January 1980

Working January 1980

Ratio value

1.269 1.217 -0.0522

2.712 2.729 .017^

^Income status was defined as total household income divided by

its appropriate U.S. official poverty threshold.

^The difference between income status for 1974 and 1979 was not

significantly different from zero.

Some households with nonworking heads contained

other members, most often the spouse, who were

working and who contributed substantially to household

income. Wages of these working household members

kept pace with general inflation over the 5-year period.

Some households declined in size-had fewer members

to support-thus, their income status improved. These

factors together contributed to the finding that households headed by a nonworker maintained their relative

income status; that is, they were not in a relatively poorer

economic position than before employment growth took

place over the 5-year study period.

These nonworking household heads can be generally

considered as noncompetitors forjobs in the area's labor

market (30). The nonworking household heads' age

structure suggests that many were probably retired or

engaged in housework (table 7). Only a very small group

were in the area's labor force but unemployed. Poor

health was reported as a major factor limiting the ability

to work by almost 51 percent ofthe nonworking household heads. Old age and poor health often go together.

Among most male household heads under age 60,

however, a health problem or condition was severe

enough to prevent them from seeking employment

during 1979. "Not interested in paid employment" was

the next most important reason given by nonworking

heads of households for not seeking employment. Most

of these persons listed their current activity as retired.

Households Headed by Women, January 1980

The regression analysis shows that households headed

by women had a significantly smaller change in income

status over the 1974-79 period than did households

headed by men (app. table 2). Over this 5-year period,

the overall income status gap widened considerably

between households headed by men and those headed

by women. The average change in household income

status among households headed by women was

negative and signficantly different from zero (table 8).

However, the widened income status gap between these

groups was primarily the result of change in a household's composition. About 25 percent ofthe women who

headed households in January 1980 were widowed

sometime after 1974. Thus, the death of a male head of

household could reduce the household income status in

two ways: (1) by reducing the household's flow of

earnings if he was working in 1974 or (2) by reducing

the benefits paid to the surviving spouse if the deceased

head was retired in 1974. No data are available on the

11
Table 6—Selected characteristics of existing, longer term resident households,

by not working head and employed head, January 1980

Characteristics

Total housetiolds

Headofiiousehold:

SexMale

Female

Age—

Under 35 years

35-54 years

55-64 years

65 years and older

Average age

Education completed—

Less than high school

High school

Beyond high school

Average years of completed schooling

Households reporting income from:

Earnings^

Unemployment and workers' compensation

Public assistance"^

Retirements^

Other®

Average money income, 1979

Average income status ratio for 1979

Longer term resident householdsUnit

Number

Total Head networking,

January 1980

Employed head,

January 1980

44,340 17,750

Percent 83.2 70.0

do. 16.8 30.0

do. 17.7 4.5^

do. 36.5 15.5

do. 15.1 13.4

do. 30.7 66.6

Years 53.0 65.8

Percent 65.1 86.8

do. 21.1 7.5

do. 13.8 5.7

Years 9.3 7.6

Percent^ 66.8 17.0

do. 10.2 10.5

do. 17.2 37.7

do. 39.9 80.3

do. 27.7 32.5

Dollars

Ratio

12,050

2.1

5,950

1.2

26,590

92.0

8.0

26.5

50.5

16.2

6.7

44.5

50.7

30.2

19.1

10.5

100.0

10.0

3.4

12.9

24.4

16,120

2.7

^Estimate based on fewer than 10 unweighted observations.

^Income received from wages and salaries and net self-employment from farm or nonfarm businesses.

^Because some households received income from more than one source, percentages wilt not add to 100.

"^Includes payments from Aid to Families with Dependent Children (AFDC), Supplemental Security Income (SSI), or other State or local public

assistance.

^Income received from benefits such as Social Security; railroad retirement; or private, Government, or military pensions or annuities.

^includes veterans' payments, interest on savings or bonds, alimony, dividends or stocks, child support, net rental income or royalties, estates

or trusts, and any other source not already reported.

Table 7—Nonworking heads of existing, longer term resident households In January 1980:

Current activity and reason not working

Item Unit Longer term resident household

heads not working in January 1980

Total

Current activity:

Going to school

Housework

Retired

Voluntary work

Unemployed

Other

Reasons not looking for work

Discouraged worker^

III health

Not interested in paid employment

Interested in paid empioyment, but could not work"*

Number

Percent

do.

do.

do.

do.

do.

Number

Percent

do.

do.

do.

17,750

0.3^

12.1

65.6

2.3^

2.6^

17.1

17,290^

7.8

50.8

40.1

1.3^

''Estimate based on fewer than 10 unweighted observations.

^Excludes 460 households where head was unemployed in January 1980.

^Includes household heads who had stopped looking for work because they believed none was available.

'^Includes household heads who were interested in paid employment but had to care for a chifd or a sick or aged adult or who had no transportation

to and from a work place.

12
Will Employment Growth Benefit All Households?

Table 8—Household relative income status and money income among existing longer term resident

households by head's sex and composition status of the household, 1974 and 1979

Total

households

Average householdItem Income status^ Money income

1974 1979 Difference

(1974-79) 1974 1979 Difference

(1974-79)

Number

36,890

7,450

Percent

74.8

25.2

_ _ ^^Dcifi/-\ i/^liId- - n/^/ZoKc Damanf

Households headed by:

Men (both years)

Women

Both years^

Sometime after 1974^

2.269 2.267 -0.002^

1.523 1.354 -.169^

1.447 1.371 -.076^

1.746 1.303 -.443^

9,070

4,880

4,250

6,730

13,230

6,200

6,290

5,930

45.9

27.0

48.0

-11.9

Mncome status was defined for each year as total household income divided by its appropriate U.S. official poverty threshold.

^The value did not differ significantly from zero.

^The value did differ significantly from zero.

"^Statistical test not performed because there were less than 30 unweighted observations. There were, however, more than 10 unweighted

observations which provides some validity to the finding.

^The household was headed by the same woman in 1974 and in 1979.

^The household was headed by a man in 1974, but his widow took over sometime after 1974.

employment status ofthe former head of the household

in 1974. However, the change in income status among

households headed by women in both 1974 and 1979

did not differ significantly from that of households headed

by men. Past research has shown that major compositional changes, such as change in marital status, greatly

alter a household's income status (21).

While the employment growth provided jobs for women

in the area, the benefits ofjob expansion were less likely

to affect households headed by women (6). Among the

longer term resident households reporting persons

entering the labor force between 1974 and 1979, 12

percent were households headed by women as of

January 1980.^ Most women entering the labor force

during the study period lived in a household headed by

a man.

As expected from past evidence, there was a sharp

income disparity between households headed by men

and those headed by women (table 8). Women who

headed households were most often not working, were

elderly (65 years or older), and were more likely dependent on retirement benefits or public assistance for income

" There were too few observations to draw any conclusions about

how employment growth affected the income status of households

headed by women widowed sometime after 1974.

support (table 9). The proportion of households headed

by women reporting earnings for 1979 was just over half

thatfor households headed by men. Households headed

by women were typically smaller and had fewer persons

of labor force age than households headed by men.

Alleviating Poverty

Rural economic development often has been advocated

as a means to aid the economically disadvantaged (46).

The analysis that follows, based on the longer term

resident households in our Kentucky study area, indicates that employment growth had a limited effect on

alleviating poverty.

Household Poverty Status, 1974-79

We used Federal poverty thresholds to identify impoverished longer term resident households in both 1974

and 1979 (36, 37). About 21 percent of the surveyed

households were "poor" in both 1974 and 1979 (table

10) ; the proportion of poor households for 1979 did not

differ significantly from that for 1974. These poor households represented about three-fourths of the poor in

either 1974 or in 1979 or in both years. About 3,400

households escaped poverty between 1974 and 1979,

but about an equal number became poor over the same

13
Donald K. Larson and Claudia K. White

Table 9—Selected characteristics of existing, longer term resident households by sex of head, January 1980

Unit

Longer term resident households—

Characteristics

Total Men as heads Women as heads

Total households Number 44,340 36,890 7,450

Persons per household, average do. 2.8 3.0 1.8

Work status:

Head employed, January 1980

Head not employed, January 1980

Percent

do.

70.0

30.0

66.3

33.7

28.6

71.4

Age of head:

Under 35 years

35-54 years

55-64 years

65 years and older

Average age

do.

do.

do.

do.

Years

17.7

36.5

15.1

30.7

53.0

19.8

38.9

15.1

26.1

51.2

7.6^

24.3

14.7

53.4

62.1

Education of head:

Less than high school

High school

Beyond high school

Average years of completed schooling

Percent

do.

do.

Years

65.1

21.1

13.8

9.3

62.5

23.5

14.0

9.4

77.9

9.2'

13.0

8.9

Households receiving income from:

Earnings^

Unemployment and workers' compensation

Public assistance^

Retirement^

Other^

Percent^

do.

do.

do.

do.

66.8

10.2

17.2

39.9

27.7

72.5

10.8

13.3

35.1

27.8

38.7

7.4'

36.4

63.3

26.9

^Estimate based on fewer than 10 unweighted observations.

^Income received from wages and salaries and net self-employment income from farm or nonfarm business.

^Because some households received income from more than one source, percentages will not add to 100.

"^Includes payments from Aid to Families with Dependent Children (AFDC), Supptemental Security Income (SSI), or other State or local public

assistance.

^Income received from benefits such as Social Security; railroad retirement; or private, Government, or military pensions or annuities.

^Includes veterans' payments, interest on savrngs or bonds, alimony, dividends or stocks, child support, net rental income or royalties, estates,

or trusts, and any other source not already reported.

Table 10—Existing, longer term resident households by

poverty status, 1974 and 1979^

Item Longer term

resident households

Poverty

status in 1979

Poor Not poor

Total

Poverty status in 1974

Poor

Not poor

Number

44,340 12,940 31,400

12,780 9,390 3,390

31,560 3,550 28,010

^ Poverty thresholds were derived using the U.S. Census official levels

for the years 1974 and 1979 and based on the following criteria: sex and

age of the head of the household, size of the household, and total

household money income {36, 37).

time period; the number of households escaping poverty

did not differ significantly from the number of households

entering poverty between 1974 and 1979.

Household Attributes by Poverty Status

Old age, low education, femaie heads, and low employment rates are attributes typically associated with a poor

household (21,36,37). The longerterm resident households classed as poor in 1974 or 1979 or both years

exhibited many of these characteristics (table 11). Within

households that either remained in, escaped, or entered

poverty between 1974 and 1979, the head typically was

older and had a lower educational attainment than heads

among households classed as never poor.

Households classed as poor both years and those

entering poverty had a lower average number of earners

per household. Also, these households had no member

employed in higher paying executive, administrative,

managerial, or professional occupations. Households

headed by women were more likely to be poor, and more

14
Will Employment Growth Benefit All Households?

Table 11—Selected characteristics of existing longer term resident households by poverty status, 1974-79

Poverty status

Characteristics Unit

Longer term

resident

households

Remained

in poverty,

Escaped

poverty.

Entered

poverty.

Not in

poverty,

1974-79^ 1974-79^ 1974-79^ 1974-79^

Total Number 44,340 9,390 3,390 3,550 28,010

Average size of household do. 2.8 2.7 2.5 2.7 2.9

Average number of earners in

household, 1979 do. 1 .4 .4 .8 1.3

Income-status ratio:^

1979 average Index 2.11 .62 1.44 .73 2.87

1974 average do. 2.14 .61 .68 1.57 2.91

Change in income status ratio,

1979-74 do. -.03 .01 .76 -.84 -.04

Head of household:

Sex of headMale Percent 83.2 72.4 85.5 62.3 88.9

Female do. 16.8 27.6 14.5 37.7 11.1

Age, 1979—

16-34 years do. 17.7 11.6 9.7^ 13.0^ 21.4

35-54 years do. 36.5 28.9 21.3^ 33.3 41.2

55-64 years do. 15.1 14.6 11.5^ 10.9® 16.3

65 years and older do. 30.7 44.9 57.5 42.8 21.1

Average age Years 53.0 57.9 62.5 58.4 49.6

Education level, 1979—

Less than high school Percent 65.0 91.3 82.0 82.3 52.0

High school do. 21.1 6.2^ 6.8^ 17.7® 28.3

Beyond high school do. 13.9 2.5^ 11.2^ 0 19.7

Average years of completed

schooling Years 9.3 7.3 8.1 7.6 10.4

Major occupation, 1979—

Executive, administrative,

managerial, professional Percent 7.6 0 0 0 12.1

Technical, marketing,

sales, clerical, service do. 21.9 11.4 16.5^ 8.5® 27.8

Production and related

occupations do. 30.4 13.5 26.0 22.2 37.6

Head not employed'^ do. 40.1 75.1 57.5 69.3 22.5

Source of income, 1979:®

Earnings^ Percent 66.8 34.3 44.5 33.3 84.7

Unemployment and workers'

compensation do. 10.2 5.9^ 4.1^ 12.4® 12.1

Public assistance"* ° do. 17.2 52.3 20.6® 30.4 3.3

Retirements^ do. 39.9 53.5 66.4 49.0 30.9

Other^^ do. 27.6 25.3 31.3 11.8® 30.0

^Households classed as poor in both 1974 and 1979. ^Households classed as poor in 1974, but not poor in 1979. ^Households classed as

not poor in 1974, but poor in 1979. "^Households classed as not poor in either 1974 or 1979. ^Income status ratio defined as total household

income divided by appropriate Federal poverty threshold value. ^Estimate based on fewer than 10 unweighted observations. ^Head was not

employed in either 1979 or in both 1974 and 1979. ^Because some households received income from more than one source, percentages will

not add to 100. ^Income received from wages and salaries and net self-employment income from farm or nonfarm business. ^^Includes payments

from Aid to Families with Dependent Children (AFDC), Supplemental Security Income (SSI), or other State or local publiG assistance. ^ ^ Income

received from benefits such as Social Security; railroad retirement; or private, Government, or military pensions or annuities. ^ ^Includes veterans'

payments, interest on savings or bonds, alimony, dividends or stocks, child support, net rental income or royalties, estates or trusts, and any other

source not already reported.

15
Donald K, Larson and Claudia K. White

households headed by women entered than escaped

poverty over the study period.

A household's poverty status can change from year to

year depending on changes in any number of economic

and noneconomic factors ft0, 13, 27J.^ The nine-county

Kentucky household data support this finding that being

poor need not be a permanent condition. Because a few

households changed their poverty status between 1974

and 1979, we will examine whether the area's employment growth aided these households in changing their

poverty situation.

Households Escaping Poverty

Among the area's 3,390 households that were poor in

1974 but not poor by 1979, the area's employment

growth was but one of several factors that lifted them

out of poverty. About 29 percent of these households

had an increase in the number of household members

working between 1974 and 1979 (table 12). The heads

ofthese households were most often a person under 65

years of age.

About 30percent ofthese 3,390 households had fewer

members to support in 1979 than in 1974. As a group,

average household size for 1979 did not differ significantly among the four poverty status groups shown in

table 11. When a member leaves a houseJioid, the

poverty threshold applied to that household is lower. If

there is little or no change in household income as a

result ofthe member's leaving, then the household can

escape poverty.^ ° Nearly half ofthe households escaping

poverty had no one working in either 1974 or 1979;

among these households the head was 65 years and

older. Participation in the public welfare programs,

mainly SSI, seemingly raised these households from

poverty.''^

Households Poor in both 1974 and 1979

Government transfer payments, or public assistance, do

not always assure that a household can escape from

^ The terms "temporary" and "permanent" poor often appear in the

literature to distinguish between cases that move in and out ot poverty

from cases seemingly trapped in poverty (21). Annual data are required

to make these distinctions, but annual income data were not collected

for the years between 1974 and 1979 in the Kentucky survey. Although

these distinctions could not be exactly identified from the survey data,

the two point estimates suggest that both temporary and permanent

members of the poverty population probably exist in the study site.

^ ° The number of households receiving public assistance payments

was too small to draw any conclusions.

^^ These households did not report having SSI payments in 1974

but did so in 1979.

poverty. But, Government transfer payments may have

kept the poverty gap from widening over the period.

Among the 9,390 longer term resident households

classed as poor in both 1974 and 1979 (table 11 ), about

37 percent received public assistance payments in 1974;

by 1979, 52 percent reported this source of income.

While these percentages differed significantly, the

average income status ratios of 0.61 in 1974 and 0.62

in 1979 did not differ significantly. Nearly 65 percent of

the households reportedly receiving public assistance

payments in 1979 were poor in both years.

Among the longer term resident households classed as

poor In 1974 and 1979, 32 percent had at least one

member who was employed during 1979 (table 12).^^

About 42 percent ofthese working-poor households had

members ofthe household who entered the labor force

after 1974. Among these households with members in

the area's labor market, the household heads typically

were male, were under 65 years of age, had less than

an eighth grade education, and frequently were working

for wages at or below the 1979 U.S. minimum wage.

Their relatively low educational attainment probably was

afactor limiting the wages they received. Also, none of

the heads of these households reported having participated in a formal job training program.

Providing support for fewer household members did not

necessarily lift ahousehold out of poverty. Amongthose

households where the number of members declined

between 1974 and 1979, about 29 percent were classed

as poor in both years (table 12). As househoid size

declined over this period, the household's Income

situation also deteriorated, suggesting possibly thatthe

member who leftthe household was working in 1974or

that public assistance payments were reduced by an

amount that kept the household in poverty/^

Households Entering Poverty

An estimated 3,500 households became poor by 1979

(table 11). Three events seemingly caused these households, which were not poor in 1974, to become poor by

^^ These households can be referred to as containing the area's

"working poor." Overall, these households were about 7 percent of all

of the area's longer term resident households (table 12).

^^ There were too few households in this group reporting public

assistance payments in both 1979 and 1974 to draw any conclusions

about these effects on change in household income status.

16
Will Employment Growth Benefit All Households?

Table 12—Existing longer term resident household employment and household size, by poverty status, 1974-79

Longer term

resident

household

Poverty status, 1974 and 1979

Item Remained

in poverty,

1974^79^

Escaped

poverty,

1974-79^

Entered

poverty,

1974-79^

Not in

poverty,

1974-79^

Tota!

Employment status of household members:

Number of earners did not change

More earners

Fewer earners

No earners both periods

Household size;

Same number of members

More members

Fewer members

Number

44,340 9,390 3,390 3,550 28,010

Percent

44.8 18.8 14.2^ 25.6 59.6

17.8 13.4 28.6 5.4^ 19.5

9.8 9.3 8.6^ 26.2 8.1

27.6 57.5 48.6 42.8 12.8

64.5 61.2 62.8 65.6 65.7

15.1 10.8 6.8^ 16.9^ 17.3

20.4 28.0 30.4 17.5^ 17.0

^Households classed as poor in both 1974 and 1979.

^Households classed as poor in 1974, but not poor in 1979.

^Households classed as not poor in 1974, but poor in 1979.

'^Households classed as not poor in either 1974 or 1979.

^Estimate based on fewer than 10 unweighted observations.

1979. First, about a quarter ofthese households reported

thatthe number of members working declined between

1974 artd 1979. This withdrawal from the work force was

generally associated with retirement. Second, among

those households where members' employment status

was unchanged over the 5-year period, total hours

worked declined. A health condition lasting part of 1979

seemingly explained the reduction in hours worked

between 1974 and 1979. Third, among the 1,520 households having no member working in the area's labor

force, reduced survivor benefits seemingly caused entry

into the poor group for many households headed by

recently widowed women; there were too few male

heads of household in this group to draw any conclusions

about why they entered the poor category.

Summary on Poverty

For some households, employment gains reduced

poverty. For others, employment gains will not necessarily reduce poverty or reduce dependence upon public

assistance programs. Many poor households were

headed by an elderly person who, in all likelihood, would

not seek employment even if it were available. Thus, the

traditional public assistance programs and Social Security should provide economic support for the elderly

within a growth area. These programs did, in fact, assist

some households headed by elderly persons to escape

poverty. Promoting employment growth will not necessarily lift out of poverty households containing the

"working poor," particulariy if these persons have limited

education or job skills. Thus, based on the nine-county

study area's findings, a supplemental income or wage

subsidy program will be needed to improve the economic

plightofthe working poor. However, employment gains

assistedsome households in their escape from poverty.

This group was about 2 percent of all the households

analyzed, supporting the findingthatthe area's employment growth had but a limited effect on poverty.

Implications

Employment growth, in and ofitself, had positiveeffects

on the Kentucky study area, accommodating population

growth by providing jobs for persons in newly formed

households and existing households which moved into

the areaafter 1974. The growth didnot adversely affect

existing longer term resident households as a group

because they were ableto maintain their income status.

The employment growth in the area's economy provided

new services to the community and, in general, transformed the area from an environment of economic

decline to one of economic growth.

Results from this study demonstrate why overall employment growth probably will not benefit all households or

residents in a given area. For example, our study area

had an elderly population typical of that in many other

17
Donald K. Larson and Cfaudia K. White

nonmetro areas. Unlike younger residents, older people

compete less often in the labor market and are usually

unable to take advantage of new job opportunities. The

income transfer system seemed to be important in

maintaining the elderly's income status. For household

members already in the labor force, economic expansion

probably will not substantially raise their income levels

unless labor is in short supply and area wage rates

increase. During the study period, some longer term

resident households did benefit as additional members

entered the labor force. But, other households had

members who quit working or reduced the number of

hours at work for any number of reasons including

retirement. Thus, household composition and employment dynamics explain why the average income status

did not change significantly between 1974 and 1979.

Economic development measured by employment

growth is frequently proposed as a means of improving

the economic well-being of all rural residents, particuiarty

the poor. Employment growth during the seventies in the

study area was impressive, but it was not sufficient to

change the relative income status of the area's households (15). Understanding the relationship between

employment growth and relative Incomestatus is particularly important because many Government programs

use relative income as an indicator of need for public

attention.

Efforts by local governments or community organizations

to expand employment need not adversely affect relative

income status among vulnerable households within the

population if an income transfer system remains in place.

Expanding employment, while enabling some households to escape poverty, will not necessarily reduce

overall poverty because a substantial share ofthe poor

cannot work because of age or job-limiting illness or

disability. If an economic policy is to reduce the relative

economic status differences among household subgroups, particularly households headed by women and

households considered to be poor, maintaining current

income security programs is necessary while stimu^âting

employment growth.

References

(2) Bender, L. D., B. L. Green, and R. R. Gampbeil.

"Trickledown and Leakage in the War on Poverty,"

Growth and Change, Vol. 2, No. 4, Oct. 1971, p. 38.

(3) Bertrand, Alvin L., and Harold Osborne. "Rural Industrialization: A Situational Analysis," Rural

Sociology, Vol. 23, No. 4, Feb. 1960, pp. 387-93.

(4) Bloomquist, L E., and Gene F. Summers. "Organization of Production and Community Income Distributions," American Sociological Review, Vol. 47,

No. 4, June 1982, pp. 325-38.

(5) Clemente, Frank, and Gene F. Summers. Large

Industries in Small Towns: Who Benefits? Working

Paper RID 73.9. Univ. of Wisconsin, Feb. 1973.

(6) Daberkow, Stan G., Donald K. Larson, Robert Coltrane, and Tbomas A. Carlin. Distribution of Employment Growth in Nine Kentucky Counties.

RDRR-41. U.S. Dept. of Agr., Econ/Res. Serv.,

Aug. 1984.

(7) Daberkow, Stan. "Regression Analysis With Complex Survey Data: A Comparison of Estimation

Techniques." Paper presented at American Agricultural Economic Association meeting, Ithaca, NY,

Aug. 1984.

(8) Davis, Thomas F. Persistent Low-Income Counties

in Nonmetro America. RDRR-12. U.S. Dept. of Agr.,

Econ. Res. Serv., May 1979.

(9) Deaton, Brady J., and Maurice R. Landes. "Rural

Industrialization and the Changing Distribution of

Family Incomes," American Journal of Agricultural

Economics, Vol. 60, No. 5, Dec. 1978, pp; 950-54;

(10) Duncan, Greg J., and James N. Morgan. "Persistence and Change in Economic Status andthe Role

of Changing Family Composition," Five Thousand

American families—Patterns of Economic Progress, Vol. 9, Ed. Martha S. Hill, Daniel H. Hill, and

James N. Morgan. Univ. of Michigan, 1981.

(11 ) Garfinkel, Irwin, and Robert H. Haveman. Earnings

Capacity, Poverty, and Inequality. New York:

Academic Press, 1977.

(1) Beck, E. M., Louis E. Dotson, and Gene F. Summers. "Effects of Industrial Development on Heads

of Households," Growth and Change, Vol. 4, No.

3, July 1973, pp. 16-19.

(12) Garrison, Charles B. The Impact of New Industry

on Local Government Finances in Five Small

Towns in Kentucky. AER-191. U.S. Dept. of Agr.,

Econ. Res. Serv., Sept. 1970.

18
Will Employment Growth Benefit All Housetiolds?

(13) Gordan, David M. Theories ofPoverty and Underemployment Lexington, MA: D.C. Heath and

Company, 1972.

(14) Hoppe, Robert A., and William E. Saupe. Transfer

Payments In Nonmetropolitan Areas. ERS Staff

Report No. AGES820827. U.S. Dept. of Agr., Econ.

Res. Serv., Sept. 1982.

(15) Hoppe, Robert A. "Some Persistenly Low-Income

Counties Make Advances," Rural Devlopment

Perspectives, Vol. 1, Issue 2, Feb. 1985, pp. 30-35.

(16) Jordan, Max F. Rural Industrialization in the Ozarks.

AER-123. U.S. Dept. of Agr., Econ. Res. Serv.,

Nov. 1967.

(17) Klindt, Thomas H., Maurice R. Landes, and Brady

J, Deaton. Impact ofNew Manufacturing Plants In

Rural Areas of Tennessee on Employee Family

Income Distribution. Agr. Exp. Sta. Bull. 603. Univ.

of Tennessee, July 1981.

(18) Kuehn, John A., Lloyd Bender, Bernai Green, and

Herbert Hoover. Impact of Job Development on

Poverty In Four Developing Areas. AER-225. U.S.

Dept. of Agr., Econ. Res. Serv., June 1972.

(19) Landes, Maurice R. "Variables Affecting the Distributive Impact of Employment in New Manufacturing industry in Rural Tennessee." Unpublished

masters thesis. Univ. of Tennessee, June 1979.

(20) Mertan, Robert K. Social Theory and Social Structure. Glencoe, IL: The Free Press, 1949.

(21) Morgan, James N. "Change in Global Measures,"

Five Thousand American Families—Patterns of

Economic Progress. Vol. 1. Univ. of Michigan,

1974, pp. 11-98.

(22) Olsen, D., and J. Kuehn. Migrant Response to

Industrialization In Four Rural Areas, 1965-1970.

AER-270. U.S. Dept. of Agr., Econ. Res. Serv.,

Sept. 1974.

(23) Seyler, H. L. "Industrialization and Household

Income Levels In Nonmetropolitan Areas," Nonmetropolitan Industrialization. Ed. Richard E. Lonsdale

and H. L. Seyler. New York: John Wiley and Sons,

1979.

(24) Shaffer, Ron. E. "The General Economic Impact of

Industrial Growth on the Private Sector of Nonmetropolitan Communities," Nonmetropolitan Industrialization. Ed. Richard E. Lonsdale and H. L.

Seyler. New York: John Wiley and Sons, 1979.

(25) Sizer, Leonard, and William B. Clifford. Rural

Industrialization. Agr. Exp. Sta. Bull. 521. West

Virginia Univ., Mar. 1966.

(26) Smith, Eldon D. "Restrictions on Policy Alternatives

Relating To Underdeveloped Regions of Developed

Counties " Journaiof Farm Economics, Vol. 48, No.

5, Dec. 1966, pp. 1227-31.

(27) Stevens, J. B., and L. T. Wallace. ImpactofIndustrial Development on Howard County, Indiana. Agr.

Exp. Sta. Bull. 784. Purdue Univ., Aug. 1964.

(28) Summers, G., and others. Industrial Invasion of

Nonmetropolitan American. New York: Praeger

Publishers, 1976.

(29) Summers, Gene F. Large Industry in a Rural Area:

Demographic Economics and Social Impacts.

Working paper RID 73.19. Univ. of Wisconsin,

1973.

(30) , and Frank Clement, "Industrial

Development, Income Distribution, and Public

Policy," Rural Sociology, Vol. 41, No. 2, Summer

1976, pp. 248-86.

(31) Taylor, Lee, and Arthur R. Jones. Rural Life and

Urbanized Society. New York: Oxford Univ. Press,

1964.

(32) Till, Thomas E., Jr. "Industrialization and Poverty

in Southern Nonmetropolitan Labor Markets,"

Growth and Change, Vol. 5, No. 1, Jan. 1974, pp.

18-24.

(33) Tweeten, Luther, and G. L. Brinkman. Micropolitan

Development: Theory and Practice of GreaterRural Economic Development. Ames: Iowa State

Univ. Press, 1976.

(34) U.S.Department of Commerce, Bureau of the

Census. Census of Population, 1980. Standard

Tape File No. 3, Feb. 1982.

19
Donald K. Larson and Claudia K. White

(35) . "General Population Characteristics, Kentucky," 7970 Census of Population.

Sept. 1971.

(36) , Characteristics ofthe Population

Below the Poverty Level: 1979. Current Population

Reports, Series P-60, No, 130. Dec. 1981.

(37) . Characteristics ofthe Population

(38)

Below the Poverty Level: 1974. Current Population

Reports, Series P-60, No. 102. Jan. 1976.

. Alternative Methods For Valumg

(39)

SelectedIn-Kind Transfer Benefits and Measuring

Their Effect on Poverty. Technical Paper 50. Mar.

1982.

. Estimates of Poverty Including

(40)

the Value of Noncash Benefits: 1979 to 19B2.

Technical Paper 51, Feb. 1984.

. Money Income of Households

(41)

in the United States: 1979. Current Population

Reports, Series P-60, No. 126. June 1981.

. Unpublished data from the

March 1980 current population survey.

(42)

(43)

. General Housing Characteristics for the United States and Regions: 1979.

Current Housing Report, Series H-150-79, Part A.

July 1981.

. General Social and Economic

(44)

Characteristics: United States Summary. PC80-1 -

C1, July 1983.

General Social and Economic

Characteristics: Kentucky. PC80-1 -CI9. July 1983.

(45) . General Population Characteristics: Kentucky, PC80-1-B19. Aug. 1982.

(46) U.S. House of Representatives. Congressional

Rural Caucus. Objectives of Rural Development ]

Policy Act of 1980, PL 96-355. May 16, 1984.

(47) West, Jerry G., and Resell Maier. "tncome Distribution in Consequences of Rural Industrialization."

Paper presented at American Agricultural

Economics Association annual meeting, Aug. 1975.

(48) White, Stephen E. "Return Migration to Appalachian

Kentucky: An Atypical Case of Nonmetropolltan

Migration Reversal," Rural Sociology, Vol. 48, No.

3, Fall 1983, pp. 471-91.

20
Will Employment Growth Benefit All Households?

Appendix: Regression Models

The dependent variable was a ratio of a household's

nominal Income divided by an appropriate U.S. official

poverty threshold. The change In a household's relative

Income status was defined as the 1979 income status

ratio minus the 1974 income status ratio.

Regression Model 1

Multiple regression model 1, which was used to identify

factors that Influenced household income status, had the

general form of

CHWBR = f (CHS, CE, SI, 174, RES, D, EC) (1)

where:

CHWBR = change in household relative income

status/

CHS = household structural variables,

CE = employment-related change variables,

SI = unearned-income source changes,

174 = household income levels in 1974,

RES = residency status of head of household,

D = demographic characteristics of head of

household, and

EC = employer (or establishment)

characteristics.

This model focused only on the linked households.'' The

regression model was used only to identify significant

associations between the dependent and independent

variables. Because our concern was with only those

independent variables that greatly influenced changes

in household relative income status, we will only focus

on these variables in the discussion below.

The independent variables which were significantly

associated with changes in household income status

were: CHGSIZ, change in number of household members living within the household; CHGEAR, change in

the employment status of household members; CHGHRS,

changes in total annual hours worked by household

members whose employment status did not change

between 1974 and 1979; CHGHWG, change in real wage

^ See glossary for definition of "linked households."

^ The 1974 weekly wages of the head of the household were

transformed to 1979 dollars using the national CPI, and the household's

1974 income was similarly adjusted to 1979 levels using the CPI.

ofthe head of the household; and RTHI5, household real

income level in 1974 that was $19,000 and over.^ All

change variables (prefix CHG ) were measured

in a continuous manner as opposed to a discrete (0,1)

variable often used in regression analysis. Thus, changes

in these variables could havea negative value, zero (0)

for a no change situation, or a positive value. The variable

RTHI5 was a discrete (0, 1) variable. A one (1) designated, for example, the household's 1974 real income (in

1979 dollars) as $19,000 or over (RTHI5).

Size of household was one variable used to reflect

household structure. An increase in household size

(CHGSIZ) represented a decline in income status over

the 5-year period. Relative income status increased

when there were fewer household members being

supported in 1979 than 1974. Several variables were

used in the model to reflect employment and employmentrelated changes. Absolute change in number of household members employed (CHGEAR) between 1974 and

1979 improved relative income status when the number

working increased.

Among households where members were employed but

CHGEAR was equal to zero, an increase in hours worked

(CHGHRS) helped raisethe household's income status.

When the household head's real wage (CHGHWG)

increased, the household's relative income status also

increased. The variable RTHI5 was one of several

variables used to measure changes in income status

accruing to households with different levels of 1974

household income expressed in real (1979) dollars.

The income status of households in RTHI5 on average

significan^tly declined over this period compared with the

omitted group of housefiolds. However, their loss was

highly relatedto a household member who left the labor

force for any number of reasons.

These fivevariables were highly significant atthe 99-percent level based on the regression model results. The

linked household regression results are shown in appendix table 1. For the regression model, a rescaling of the

expanded estimates was necessary to overcome the

problem of generating greatly reduced standard errors

on the coefficients (7). A rescaling factor was obtained

by dividing the unweighted (raw) observations by the

expanded estimate fora particular population subgroup

being considered in the analysis. The expanded observations were multiplied by the rescaling factor.

21
DonaW K. Larson and Claudia K. White

Regresston Model 2

The second multiple regression nnoder had the same

general form of the first model, but it differed in two

important ways. First, the employer characteristics (EC)

were dropped as independent variables. Second, the

nonlinked households were added to determine if their

inclusion altered the significance of the remaining variables. All variables significant in model T were significant

in model 2, However, two additional variables in model

2 were significant in explaining changes in income status

(app. table 2). These two variables were households

headed by women (HDSÊX) and the number of householdsreporting "otherincome" in 1979 bul none in 1974

(INCOTI).

The variables HDSEX and INCOTI were discrete (0,1)

variables. A one designated a household headed by a

woman (HDSEX) and a household reporting "other

income" in 1979 but none in 1974 (INCOTI), respectively.

The variable INCOTI was one of several variables used

to measure the effects from sources of unearned income

on housefiold income status. However, the actual

numbers of households where INCOTI equaliedone was

too small to be includedin the analysis presented in tfie

text.

Sex of head (HOSEX) was oneoftwo variables usedto

reflect household structure. There was a substantial

income gap between households headed by men and

women. This variable was used in the analysis to test

whether or not this gap widened wKen employment

opportunities expanded between 1974-79/Women

heads of households are often viewed as tDeIng unable

totake advantage of an increase in employment opportunities. The finding indicates that thegap did wíde^^only

between households headed by men andtliose headed

by women who were recently widowed over the study's

5-year period. Thus, compositional changes placed

these households headed by women in arelatively

poorer economic position.

22
Appendix table 1—Resutts of regression anatysis on changes in household Income status^

Variable

Regression coefficients

Unstandardized^ Standardized

Household structure:

Change in size of households, absolute number -0.4402^ -0.2620

Households headed by women, discrete 1,0 value;

0 = male head; 1 = female head -.5750 -.0024

Employment related:

Change in employment status of persons in the household, continuous value .3665^ .1783

Change in total annual hours worked by all household members where

the employment status remained unchanged, continuous value .0004^ .1540

Change in head's real weeklywage, measured continuously in dollars .0018^ .1391

Change in head's occupation among four major occupational groups,

discrete 1,0 value;1 = change, 0 = no change -.3283 -.0982

Sources of unearned income:

Household reported transfer payments in 1979 but not in 1974 .2397 .0402

Household reported transfer payments in both years, no change .0978 .0190

Household reported transfer payments in 1974 but not in 1979 -.5813 -.0548

Household reported other incomein 1979, none in 1974 .5875 .1186

Household reported other income in both years .4285 .0991

Household reported other income in 1974, none in 1979 -.4423 -.0391

Household income status, 1974 {1979 dollars) :

$ 3,519 or less .3932 .0544

$ 3.520-$7,799 .4394 .1093

$12,0Ö0-$18,999 -.2589 -.0826

$19,000 or more -1.1341^ -.3194

Head's residency status:

Head was early inmigrant"^ -.0264 -.0071

Characteristics of head of household:

Age, under 35 years .2142 .0660

Age, 55-64 years .1035 .0247

Age, 65 years and older -.7000 -.1151

Less than high school education -.3630 -.1215

High school education -.3837 -.1284

Change in head's health status, discrete value; -1 = good in 1974

but poor in 1979,0 = no change, +1 = poor in 1974 but good in 1979 -.2610 -.0768

Establishment (employer) characteristics:

Average weekly wages paid full-time employeesLess than $181 -.1679 -.0547

$181-$221 .1455 .0459

Type of establishment—^

Goods-producing - .2645 - .0857

Services-producing -.1608 -.0521

Size of estabiishment—

1-19 paid employees -.0334 -.0110

Employment change—

New establishments .2689 .0477

Growth establishments .2181 .0716

Regression constant term .1006

Adjusted coefficient of multiple determination (R^) .2048

F value^ 4.4017^

Number of original or unweighted observations 437

^Results based on those households linked with employers and excludes households not reporting income for any year.

^Regression values expressedin terms of the dependent variable as the difference in relative household income status between 1974 and 1979.

^The variable was significant at the 99-percent level of confidence.

"^The head of the household moved to the study site between January 1, 1965, and December 31, 1974.

^Goods-producing establishments included manufacturing, construction, and mining industries. Service-producing included establishments in

the private sector engaged in wholesale and retail trade; TCPU (transportation, communications, and public utilities); FIRE (finance, insurance,

and real estate); and all other services, including hotels, personal, business, amusement, health care, legal practice, education, and social service.

^Tests the hypothesis that all parameters are zero except for the intercept.

23
Donald K. Larson and Claudia K. White

Appendix table 2—ResuUs of régression analysis on changes in household income status^

Variable

Regression coefficients

Unstandardized^ Standardized

Household structure:

Continuous variable measuring absolutechange in

number of persons in the household -0.3750^ - 0.2359

A discrete variable where a female head of household equals a one - .3909^ -.1109

Employment:

Continuous variable measuring absolute change in

employment status of persons in the household (CHGEäR) .3771^ .1756

Continuous variable where CHGEAR = 0, measuring change

in total annual hours worked by members in the household .0004^ .1700

Continuous variable measuring absolute change in

weeklywage rate of head of household .0027^ .1219

Discrete variable measuring change in occupation of head of household -.2195 -.0672

Unearned sources of income:

Household reporting transfer|>ayments in 1979 but not in 1974 -.0268 -.0078

Household reporting transfer payments in both years .0591 .0220

Household reporting transfer payments in 1974, not in 1979 -.2916 -.0349

Household reporting otherincome in 1979, none in 1974 .5036^ .1131

Household reporting other income in bothyears .3377 .0984

Household reporting other income in 1974, none in 1979 -.2672 -.0281

Household income in 1974 (1979 dollars):

$ 3,519 or less .3139 .1010

$ 3,520-$7,799 .2052 .0663

$12.QG0-$18,999 -.2533 -.0798

$19,000 or more -1.1075^ -.2803

Head's residency status:

Head was early inmigrant^ .0470 .0138

Characteristics of head of household (discretevariables):

Age, under 35 years .1144 .0332

Age, 55-64 years -.0131 -.0036

Age, 65 years and older -.1791 -.0627

Less than high school education -.3221 -.1166

High school education -.3176 -.0984

Change in head's health status, discrete value; -1 = good in 1974

but poor in 1979,0 = nochange, +1 = poorin 1974 but good in 1979 .0829 .0354

Regression constant term .3623

Adjusted coefficient of multiple determination (R^) .2006

Rvalue^ 6.4252^

Number of original or unweighted observations 520

^Results based on existing longer term resident households, excluding households which did not report househoid income for 1974.

^Regression values expressed in terms of the dependent variable as the difference in relative household income status between 1974-79.

^The variable was significant at the 99-percent level of confidence.

^The head of the household moved to the study site between January 1, 1965, and December 31, 1974.

^Tests the hypothesis that all parameters are zero except for the intercept.

ÙU.S. GOVERNMENT PRINTING OFFICE: 19 8 6-490-920-^0027

24
Economic Growth is Good For Everyone. Right?

Not necessarily, according to recent findings from USDA's Economic Research Service. Find

out from these related reports just what can happen when rapid economic growth comes to

a rural area.

Distribution of Employment Growth in 10 Georgia

Counties: A Case Study, by James D.

Schaub and Victor J. Oliveira. SN: 001-019-00412-6.

Rapid economic growth in a 10-county rural area in

south Georgia during 1976-81 favored employment

of whites, men, and inmigrants. They earned higher

average weekly salaries than blacks, women, and

long-term residents. This study of growth in a mixed

manufacturing- and agricultural-based economy flows

from a research project on the impacts of economic

expansion in nonmetro economies with different industrial bases. The Georgia area's job growth was

greatest in the trades and services sectors. Few

businesses used public sector funds to start or expand their operations. Government employed 25 percent of the area's wage and salary workers.

Distribution of Employment Growtti in Nine Kentucliy Counties: A Case Study, by Stan G.

Daberkow, Donald K. Larson, Robert Coltrane, and

Thomas A. Carlin. SN: 001-019-00337-5.

Rapid employment growth between 1974 and 1979

in a nine-county study area of south central Kentucky provided job opportunities both for local

residents and for persons with limited labor force experience. But, recent inmigrants held a disproportionate share of better paying executive jobs. This

case study, which examines the distributional effects

of rapid employment growth in a nonmetro area,

shows that inmigrants also held a disproportionate

share of jobs in growing business establishments.

Although manufacturing was the major economic

force in the study area in January 1980, jobs in the

private service sector increased more than in other

sectors.

Distribution of Rural Employment Growtfi by Race:

A Case Study, by Victor J. Oliveira.

SN: 001-019-00422-3.

Whites benefit more from rural economic growth

than do blacks, based on the findings of a survey of

adults in 10 rural counties in southern Georgia. From

1976-81, a period of rapid employment growth, the

percentage of white women with jobs in the study

area increased, while the percentage of black men

with jobs actually decreased. Among employed persons, whites increased their share of higher wage

jobs. Persons who moved into the area obtained

higher paying jobs than did other residents; these inmigrants, most of whom were white, generally took

larger shares of the new jobs than did long-term

residents of both racial groups. Improving the education and job training of poor residents, especially

blacks, is essential to distributing economic benefits

more equally.

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