Research notes on socioeconomic siting dynamics

003840121/78/C6O1-0)153/$02 M/O

RESEARCH NOTES ON SOCIOECONOMIC SITING DYNAMICS HUGH Bums

81 McDonnell,

A. MCCOY

P.O. Box 173, Kansas

City.

MO 64141.

U.S.A.

and

JOSEPH University

of Missouri,

F. SINGER

Kansas

City.

MO 64110,

U.S.A

Abstract-The inclusron of socioeconomic considerations in the process of mdustrial location/siting analysis has received limited attention in recent years. More commonly the social and economic impacts associated with the constructron and operation of a major project emerge only after a prime site has been selected. This result serves to characteristically delimit advance socioeconomic planning and prevents a full and complete examination of relative cost-benefit alternatives. Impacted communities and the mitigatron problems they pose can be insurmountable wheh addressed after the fact. This article will discuss a strategy for socioeconomic inputs to project sttmg and outline a model that has been utilized for the purpose of instigating potenttal socioeconomic Impacts at the earliest possible stage within the industrial location siting process.

In recent years there has been a growing awareness of the need to provide front-end assessment of the sociocultural and economic factors related to alternative site development considerations. In contrast to the socioeconomic impact assessment of the positive and negative factors present in prime site development (which is commonly identified in the project environmental impact statement), specific recommendations can and should be developed at the earliest possible planning stage. Previously, it was believed that if housing, employment, and food were available, other infra-structural amenities would unconcerningly evolve over time to meet human needs. Yet, experience suggests that in-depth preliminary planning could have signaled the potential degree of socioeconomic disintegration that is inevitably present when sudden growth and rapid change takes place. A community’s “quality of life”, while a complex ordinal approximation, can be profiled in a more concerned process of site delineation. The effort involves the examination of several general economic conditions, as well as a number of sociocultural characteristics that are significantly related to community mental health, physical well-being and experienced levels of living. These attributes become the raw data for the development of a Socioeconomic Status Index Score used to compare community profiles.

tions,

and government agency offices help explain the levels of interpersonal interaction and communication linkages which are important in the formulation of community attitudes toward social, economic and political change. These dimensions can be further divided into those relationships which are “active-economic” in contast to those that are “passive-facilitative” and those which are formal-transmittional relative to those linkages that are loosely structural and noninstitutional (see Singer[l]; Sismondo[2]; Eberts[3]). Generally, social scientists have identified four basic types of community structure: (I) high levels of economic activity within and beyond community boundaries with well-developed institutional behavior patterns; (2) the highly activeeconomic community with limited social linkages; (3) the community having limited economic differentiation (homogeneous work patterns) with strong interaction and institutional linkages; and (4) those communities with little active-economic differentiation and limited linkages throughout its social environment (White and Lang[41). Community compatibility with rapid socioeconomic change is most adaptive in the first type of situation, while the fourth case represents a community in a critically disadvantaged position to deal with growth and development.

LEVELS OF GENERALIZATION

A typical initial project siting investigation, from a examines the general socioeconomic prospective, economic conditions in a multi-county or regional area. This gross area is usually defined in terms of the service or potential service area of the client. Population dimensions for each county are examined for the following characteristics:

DEVELOPING SITELOCATION PROFILES

Throughout the project siting process, the focus of socioeconomic investigation shifts from an examination of general population characteristics to the identification of community structural differentiation and concomitant sociocultural linkages. These include the number and degree of institutional relationships, as well as the complexity of a community in terms of its social behavior. Clearly, the nature of a community’s educational system, the number and kind of retail and wholesale establishments, recreational opportunities, health and welfare services, religious organizations, fraternal and service associations, professional and labor organiza-

Population Item Per Square Mile Net Migration Rate Replacement Index 153

Measure Number/Square Mile In/Out Migration Birth/Death Rate

154

HUGH

A.

MCCOY

and JOSEPH

Per cent Average

Urban Median Age Education Item Median School Years Completed Enrolled in School College Educated

F SINGER

collar jobs) employments to professional or technical occupational positions. In the table that follows. major occupational groups were weighed by a number which, when multiplied by 1000. represents the 1975 median earnings for each major occupational group in the county. An index score combining the social and economic status elements of occupation was calculated by multiplying the group weights by the percent of workers in each occupational category. The 1975 labor force in Alpha County contained 7473 persons with an unemployment rate of 4.5%. The nature and extent of the area’s occupational structure is presented in Table 2. Although the county experienced a 17.7% growth in its labor force, labor mobility as measured by the occupational status index score showed a 2.0% decrease. In other words, even though there are more jobs, they are at relatively lower levels of socioeconomic benefit in terms of occupational status and median income levels. Each of the potential counties under consideration can again be ranked in terms of the nature and direction of labor mobility, as well as median earnings.

Measure Average Per cent Per cent

Those counties with large populations and population densities, positive migration and replacement rates. increasing urbanization, stable or declining median ages and higher education levels are potentially more changeoriented and growth accommodating. This initial ranking of countires can be further supplemented by the development of “dependency ratios”. Dependency ratios illustrate the nature and changing responsibility of the principal working-age population for the socioeconomic care of children, as well as persons 65 yr and older. In a statistical sense, an inverse relation exists between dependency and the socioeconomic capability to meet household responsibilities. The ratios in Table 1 are based on the number of persons either 17 yr of age and under or 65 yr and older, per 100 persons aged l8yr through 64 yr. Persons 65 and older are considered to be of retirement age, and children under I8 are considered too young to be effectively employed. Each of the example study areas exhibits a high proportion of dependents when compared to the national average: however, for Beta County, the higher-thannormal “dependency” is primarily due to the disproportionate representation of the aged in the county, while persons under I8 yr of age are somewhat underrepresented. This can be contrasted with Gamma-Delta County area where the presence of a substantial proportion of youth-age people in the population accounts for a rather large dependence ratio. Although Alpha and Beta Counties both have a high proportion of dependents. Alpha County would be considered more economically disadvantaged to the extent that retirement-aged members of the population have retirement incomes for socioeconomic support.

UNDEREMPLOYMENT

While the concept of unemployment expresses the number of labor force participants in search of jobs, measures of unemployment do not adequately indicate the real nature of area labor force (resource) utilization. This is expecially true for areas with greater agricultural dependency and limited diversification of industry. A more effective measure of labor resource utilization (or the lack of it) is underemployment. The U.S. Bureau of Labor Statistics considers 260days per year as a full employment standard for measuring how well the area’s labor force is being employed in economic activity. Table 3 presents an example of the duration of employment for all workers 16 yr of age and over in Delta County. Approximately 50% of the total labor force worked less than 250 days. The average duration of employment was only 174 days for female workers and 208 days for male workers. Thus, there is substantial slack in labor force utilization to accompany a greater than normal unemployment rate of 7.8 for the county’s labor force. Delta County is the lowest of the study areas in terms of the overall average duration of employment, as well as in the effective utilization of female labor force participants. At this pomt, the analyst can identify those counties which would stand to benefii most through increased jobs and enhanced service employment opportunities

INCOME AND EMPLOYMENT CHARACTERISTICS

Labor economists have long employed measures of labor force mobility in order to characterize the socioeconomic effects of occupational change and the concomitant adjustments in earnings. It is possible for a member of the labor force to move up or improve his occupational status while at the same time realizing a decrease in earnings; although, higher income is usually associated with the movement from lower order (blue-

Table I. Dependence ratios by county. Dependents Per 100 Persons 18-65 Alpha

County

Beta

County

Gma

and

Delta

Co.

State United

SOUrCe:

States

U.S.

Census

Bureau,

% of Dependents Under 18 65 & Over

197s

in

% of Dependents Total Population

91

89.6

10.4

52.0

98

60.1

39.9

58.1

75

90.1

9.9

41.5

70

73.4

26.6

35.3

63

75.3

24.7

38.8

Population

Esrmates

Series,

PC(Z)-lOB,

1975.

Table

3. Duration

of employment

by all workers

Less Than 135 Days NO.

16 years of age and over (Delta

13!5to250 Days (%I

NO.

County)’

Over 250 Days (%I

NO.

(%I

Mean Duration of Employment

l”&X score 2

Male Workers

402

16.0

699

28.0

1,416

56.0

208

.80

Female Workers

397

33.0

391

31.0

435

36.0

174

.67

Total workers

799

22.0

1,090

29.0

1,851

49.0

197

.75

that can be expected to result from the planned development project. Active Employment Linkages represent employment by economic firms whose fiscal activity extends beyond community boundaries (exportbase employment in contrast to nonbase service employment). Each study area is assessed for the ratio of employment in base and nonbase sectors to total labor force employment. For purposes of analyses. the following breakdown of economic sectors is frequently utilized: Base Employment Agriculture Mining Manufacturing Railroads Utilities Wholesale Trade State and Federal Government Armed Services

Nonbase Employment Retail Trade Education Local Government Construction Professional Services

Such an employment profile will indicate the more structurally differentiation (higher actively-linked base economic employment) and thus, is more openly receptive to social economic and potential change. Housing Characteristics are among the most basic of human needs and most interactive relative to a com-

munity’s overall level of living. Selected housing characteristics for each study area are examined as shown by example in Table 4. A Housing Characteristics Index Score is developed for each study area relative to the state, region, or nation, as necessary for study analysis. Level of Living Index scores are developed, as a next step in the comparative analysis, utilizing cultural possesssions information available from the Bureau of Census. Table 5 illustrates a typical example. The level-of-living items selected for analysis are intended to describe the changing socioeconomic status of area families by examining five major areas of living comfort. The items can be reorganized into elements of communication, transportation, food preparation and preservation, household management and leisure. By adding the percentage score on the twelve major categories listed, a level-of-living scale of 1200 total points can be established (or 100% on each item). in order to compare the study areas. This index can be further developed by comparing it to state and other aggregate data and applying the formula described above in the housing characteristic section. Social Participation is also an aspect of a communities level of living: it reflects, more definitely than material consumption, the adjustment or performance of the family or living unit in the community. Organizational

HUGHA. !4cCou and

156

Table 4. Selected housmg characteristics’

JOSEPH F. SINGER

for AlphaCounty I%5 and 1975 IPercent)

INa 1

Item

100

781

s

Nu,,,b
llu1lt Llit

vi KI,I\

10 Yr.lr\

Table 5. Cultural possemans

100%

5.7

4.8

93x

18 0

789

168 601

i 0.0

28

198 436

and level of living charactemtics

for Delta

County

1975

100%

3735

.

Stun c Disposal Pu F IlC Sewer

I

Hourtne

100% 154

3.9 8.6

1965 and 1975’ 1965

(Percents

IN0.l

Ilie~ortma

100% 100%

$10,800.n0 62.00

100% 100%

$13,Rnn.n0 68 01) Md,,,,,

100% 2.0 15.4

5072

601 I, 245 747

.

(NO.)

IPercent)

4143

100%

Unttsi

3100 635

83.0 17.0

3273 a24

79.1 19.9

2878 857 3565 2395 3129 1401 2922 1876 488 3314 3048 1938 1110

77.1 22.9 95.4 71.5 93.4 41.5 86.6 55.6 14.5 98.2 91.0 57.9 33.1

2817 1325 3002 1153 3188 1235 3000 59.5 340 3017 3293 2116 1177

68.0 32.0 72.5 31.3 86.7 33.6 81.6 16.2 12.2 82.0 89.3 57.5 32.0

82.1

participation provides a fundamental informational linkage that serves to transmit information and support attitudes toward change, as well as the community decision-making process. Unlike the previous indexes, which were rather quickly developed utilizing the Bureau of the Census publication, the development of a “Social Participation Index Score” requires considerable searching of government, industrial trade, and institutional association publications, as well as direct telephone inquiries for attendance information at amusement, recreation and refigious functions. Nevertheless, a given set of relative population/attendance or membership/participation statistics might include:

69.4

Votes Cast~Registered Voters Presidential Election County Government Bond Elections Bank Deposits and Number-Kind of Accounts Use of Public Transportation School Attendance Religious Attendance Church Services Sunday School Revival and Special Services Recreational Attendance County Fair Motion Picture Shows

Research

notes on socioeconomic

Athletic Contests Parks and Lakes Agricultural Organizations Fraternal and Sorority Memberships Membership Association Meetings Special Interest Clubs and Service Organizations. An index score is developed by selecting the ten or twelve major participation activities, relative to potential membership bases, and combining these to form an overall percentage score for each study area. It is often useful to extend this analysis to differentiate between local, county-level and regional participation. Communrcation Media are an important supporting linkage to a community’s degree of social participation. The number and type of mass media communication available serves to give some focus to the process of mformation diffusion and attitude adoption. The most widely accepted sources of information which compile social and economic data relative to viewing areas include the yearly publications: Broadcasting Yearbook und Television Fact Book. and the comprehensive Standard Rate and Dutu Service publications. By utilizing newspaper and periodical trade statistics, as well as radio and television industry listenership survey data, a “Communications Media Index” score can be developed and employed to rank each study area relative to its informational linkages, openness and awareness of social change. Other Index Scores can be easily constructed to meet the requirements of special survey conditions or geographical problems. These might include a Farm Mechanization Index, Worker Productivity Index, Agricultural Practices Index, and Government Expenditure Index Score, to identify a few. Other overall growth pattern data pertaining to local resources and income distribution, as well as accessible data on criminal activity and levels of aggressiveness, should be examined. COMPARATIVE ANALYSIS OF SITING AREAS

Having examined various general economic conditions and the principal social-cultural characteristics for each of the study areas (Table 61, the analyst must now prepare a ranking of the study areas based on the research findings. A study area “Socioeconomic Status Index Score” can be calculated by combining several of the socio-cultural characteristic index values and comparing these between potential siting areas, as well as overtime, in order to establish the changing nature of the conditions these scores represent. The next step is to further examine area ranking by introducing the principal explanatory conditions associated with the sociocultural characteristics. Table General

Economic

Population Age

Characteristics

Dependency

Labor

Mobility

Occupational Underemployment Employment Unemployment

Selection of Specific Sites Each of the many potential

Sociocultural Housing

and

Social scores

Linkage Ratio

Scores

Index

Participation

Communication Labor

Characteristics

Index

Ratios

Index

sites within

and measurement

Level-of-Living

status

157

The structural dimensions of each study area are initially reflected by the general economic conditions present. Although social scientists agree to the importance of a large population in diminishing the potential impacts of rapid growth and development, it is more important to examine the characteristic profile of area residents. Clearly a healthy, more highly educated, more urban than rural open-country, growing and lower median aged population is more conducive to social change. Yet, this observation needs to be modified in light of age dependency considerations and the existing nature of the area labor market. The degree of dependency is an important socioeconomic force for understanding the need to participate in political-economic change. The young will anticipate employment opportunities as their minimum education reaches completion, while the aged may view impending change as threatening to their retirement and the way of life it brings. Each study area is ranked in terms of the nature of its labor market activity. First, relative to its base employment (the active socioeconomic linkages associated with firms engaged in broad marketing relationships) and then in terms of the degrees of unemployment and underemployment of labor resources that exist. Some of these employment conditions may have been produced by the natural process of upward labor mobility in which some labor force particpants are displaced by the more skilled and more productive. On the other hand, it is entirely possible to discover a declining labor market with lowering occupational status conditions associated with high levels of unemployment and underemployment. The analyst will eventually find himself confronted with an important economic development question that lies somewhere between that study area ranked highest in terms of its high structural differentiation and strong sociocultural linkages and the study area which is the opposite. Although the first ranked area will be most adaptive to development, another study area with perhaps a higher degree of dependency, a somewhat slower growing or leveled-off labor market. and a higher degree of unemployment and underemployment may benefit most from the socioeconomic stimulus provided by a industrial or energy development project. major However, this question most frequently arises at the next level of generalization. the township and specific site levels. Nevertheless, at this point in the socioeconomic siting consideration process. a recommendation can be made regarding the best county for location considerations.

6. Data classification

Condition

sitmg dynamics

Index

Media

Productivity

Farm

Practices

Farm

Mechanization

Index Index

Index Index

a given county

HUGH A. MCCOY and JOSEPH F. SINGER

158

bonding capacity, are assessed. Additional detailed information concerning housing, educational, medical and recreational facilities is introduced in order to more fully anticipate potential developmental impacts and adaptation problems. At this point. matrices-depicting the general socioeconomical conditions and sociocultural institutional characteristics--can be constructed for each potential site area and the affected communities (see Figs. 1 and

(usually selected relative to land use restrictions) will receive the same analysis as described above. Data is developed from Bureau of Census computer tapes, first at the enumeration district summary tabulation level and then, as the analysis becomes more site specific, at a site geographic level employing longitude and latitude dimensions and a given radius around each site. This later process is accomplished by estimating the proportion of each statistical geographic entity that falls within the specified circle around the potential site. As the analysis proceeds toward the identification of a specific site (from a socioeconomic perspective), additional socioeconomic data is included, particularly government sector information. The nature and extent of government finance and expenditures, including the present status of jurisdictional boundaries and local

2). The various linkages within the two matrices are designed to iiiustrate the interaction among the different economic sectors in the siting areas and serve as a tool for evaluating the social and economic capabilities of those areas. In addition to the occupational status and labor mobil-

INFORMATION

LINKAGE

CONTENT

MEASUREMENT i

r-i

INDUSTRY OCCUPATIONS

LABOR MARKET CONOITIONS

COMMUNITY SOCIO-ECONOMIC STRUCTURAL LINKAGES

ENROLLMENTS LEVELS ADVANCED

EDUCATIONAL CHARACTERISTICS t--t--i

i DEPENDENCY DENSITY FLOW VITALITY LOCATION AGE

Fig. 1. General socio-economic

LINKAGE

INFORMATION

conditions matrix.

MEASUREMENT

CONTENT

I

STATISTIC

I

INVENTORY CONDITIONS

POSSESSIONS

TRANSPORTATION UTILITIES CONVENIENCES

~DMMUNITY ACTIVE l3EHAVlDRAL LINKAGES

SOCIOECONOMIC STATUS INDEX SCORE

PARTICIPATION

OCCUPATIONAL RELIGIOUS RECREATIONAL SERVICE

SOCIAL PARTICIPATION INDEX SCORE

t-- VIEWERS COMMUNICATION MEDIA

LISTENERSHIP READERSHIP

Fig. 2 Socio-c~lturai

COMMUNICATIONS MEDIA INDEX SCORE

institutional charactertstlcs

matrix.

Research

notes on socioeconomic

ity index and the index of economic dependency (see Fig. I), other indexes can be developed which will serve as an indication of a specific social or economic trait within the area which, in turn, can be used to develop the overall Socioeconomic Status Index Score (see Fig. 1). The Socioeconomic Status Index Score represents a comprehensive sampling of all the measurements or indexes and serves as a reasonably good tool for evaluating the areas’ socioeconomic assets or liabilities. The raw socioeconomic status index scores can then be utilized for site comparisons in order to establish the suitability of the particular area to absorb rapid growth or development throughout the fabric ot its social economy. After the array of site socioeconomic profiles has been compiled, decisions can be made establishing community type, and specific recommendations for site selection can be supported relative to the overall siting process. Not only will the process ensure that the information will be available for a comprehensive and objective examination of socioeconomic constraints within project siting process, but in addition, such an exhaustive investigation will allow project planners to budget for future investigative or community development efforts which may be necessary in light of principal site selection constraints. Likewise, the process ensures that a data core or base of information has been assembled which will prove to be invaluable in directing the further assessment of the reasons for various socioeconomic conditions as well as in preparation of the final environmental impact statement.

siting dynamics

159 RRFRRRNCRS

F. Singer and J L. Charlton. Uru Socroeconomrc Adju~fment of Rural Households in I/W Arhun.ws Oxrks. Arkansas Agricultural Experiment Station. Bulletin No 767. Sept. 1971. ? Sergio Sismondo. The Meusurement of Derelopmenr. New Brunswtck New Start, Inc , New Brunswtck. Canada (1973) 3 Paul R. Eberts. Trends m Equuliry in /he Norfheust: Major Empiricul Dimensrons. Department of Rural Sociology, Cornell University. Ithaca. N.Y. (1974). I. Joseph

4. Gilbert White and Lang Gottfried. Community mobilization for adaptation to change in rapid growth areas. Energy Dece/opmen/ in the Rocks Moun/urn Regron. Vol. 3. Federation ofRocky Mountain States Inc., (July 1975).

RlRl’HER

READING

John S. Gilmore and Mary K. Duff. Eoomto~vr Grow*rh Management: A Cuse Study of Roth Sprinx,-Green River. Wyoming. Westview Press. Boulder. Colorado (1975). William H. Metzler and J. L. Charlton. Empkoyment und Underemplopmen! of Rural People in the Ozurhs, Arkansas Agricultural Experiment Station, Bulletin No. 604. Nov. 1958. Courtland L. Smith, Thomas C. Hogg and Michael J. Reagan, Economic development: panacea or perplexity for rural areas. Rural Sociology 36(2), 173-186 (1971). The Energy Policy Staff. Office of Science and Technology. Considerations Affecfing Steum Power Plant Sue Selection. May l%9. The Energy Policy Staff, Office of Science and Technology, Electric Power und the Environment. Aug. 1970.