Economic indicator maps for rural development in the Pacific West

34 Pages·1996·2.5 MB·English

by  McGinnis, Wendy J

Archive Document
Historic,
Do not assume content reflects current
scientific knowledge, policies, or practices.

Economic Maps
United States Indicator
Department
of Agriculture
Deveiopment
Forest Service for Rurai
Intermountain
Research Station in the Pacific West
General Technical
Report INT-GTR-328
January 1996
Wendy
J. iVIcGinnIs
Ervin G. Schuster
Walter L. Stewart
The Authors Research Summary
WendyJ. McGinnis is an e(x>nomistwiththe Social and Legislation and policy require the U.S. Departmentof
Economic Values Program, Pacific Northwest Research Agriculture, Forest Service to help diversify the econo-
Station, Forest Service, U.S. Departmentof Agriculture, mies and improve the well-being of rural America. This
in Portland, OR. She did her undergraduate work atthe document provides county-level information on 12 eco-
University of Colorado and received a master's degree nomic indicators, including economic diversity and rec-
in economics from the University of Washington. Her reation dependency, from both national and regional
research team focuses on social and economic change perspectives forthe Pacific West States of Alaska,
in the rural Northwest. Washington, Oregon, and California.
Ervin G. Schuster is Principal Economist and Project
Leader of the Economics of Multiple Use Management Contents Page
on Forest Lands Research Work Unit, Intermountain
Research Station, Forest Service, U.S. Departmentof Introduction 1
Agriculture, in Missoula, MT. He studied forestry and Economic Dependency and Proximity
economincs atthe University of Minnesota and Iowa to National Forests 2
State University, where he received a Ph.D. degree in Rural Population 4
forest economics. His research focuses on timber sale Net Migration 6
design and appraisal, forest plan implementation, and Per Capita Income 8
rural development. Poverty 10
Unemployment 12
Walter L. Stewart is Regional Economistforthe South-
western Region, Forest Service, U.S. Department of Federal Wildland Ownership 14
Agriculture, headquartered in Albuquerque, MM. He Direct Wildland Dependency 16
holds degrees in economics from Berea College and Economic Diversity 18
Timber Dependency 20
Ohio University. His Ph.D. degree is from the College
Recreation Dependency 22
of Natural Resources, Colorado State University. His
principal interests are economic analysis of National Wildland Earnings Change 24
Forest management programs and rural development. References 26
Intermountain Research Station
32425th Street
Ogden, UT84401
Economic Maps
Indicator for Rurai
Deveiopment West
in tiie Pacific
Wendy J. McGinnis
Ervin G. Schuster
Walter L. Stewart
"high priority" in the Forest Service and is a"highly
Introduction
relevant" part ofits mission (Robertson 1990).
ForestService researchintendstobe "fullpartici-
The U.S. Department ofAgriculture, Forest Ser-
pants in providingthe scientific and technological
vice has been Hnked to rural communities since its
supportforthe overall Forest Service effort"through
beginnings. Timber supply and otherIoceJ consider-
the national research program. EnhancingRural
ationswere included in the originalrationale for set-
America (Sesco 1991). Part ofthe technological sup-
ting aside public domain as forestreserves (16U.S.C.
475). Earlyconcernwas also reflectedbypassage of portisinformationoncommunityproximitytoNational
Forests, economic dependency, economic disadvantage,
revenue-sharinglegislation in 1908; 25 percent of
and similar matters. This documentprovides that
Forest Service receipts were returned to States for
informationfrom a spatial perspective. Ovir approach
use bythe counties (16 U.S.C. 500). Formost ofthis
focusesless on specific levels ofeconomic indicators
century, however, the primaryForest Service tie to
than onthe geographicalproximity andjuxtaposition
local economies has beenthrough attemptingto pro-
ofindicators. Ourinterest is less in identifyingthe
vide a stable timber supply.
countywiththehighestorlowestindicatorvaluethan
Recently, the Forest Service has adopted an ex-
in displaying"pockets" or "clusters" ofcounties with
panded role inrural development. In 1990, Congress
passed the National Forest-Dependent RureJ Com- similar characteristics. This is done through 12 sets
ofmaps, each providing avisual display ofcounty-
munities Economic DiversificationAct. Its purpose
levelinformationforanimportanteconomicindicator,
includes assistingrural communities located in or
from boththe national and regional perspectives.
nearNational Forests, which are economically de-
Eachnational map displays 3,094 county-like govern-
pendent on forestresources or are likelyto be eco-
mentalunits (including parishes in Louisiana and
nomically disadvantaged byland-managementprac- boroughs or census areas inAlaska). Anationalmap
tices (7 U.S.C.A. 6601-6617). Also, in 1990, Chief
showingthe location ofForest Service Regions is
Dale Robertson accepted a strategic plan for rural
shownbelow. The Pacific West region consists of
America, stating, that rural developmenthas a
Forest Service Regions 5, 6, and 10.
1
Figure la shows the distribution ofcounties thatmeet
Economic Dependency and Proximity to boththe 100-mileandeconomic-dependencycriteria. Nearly
National Forests all ofthe counties inthe West and the upper Lake States
meetboth criteria; mostofthe counties inthe Nation's
The National Forest-DependentRural Communities agricultural heartland meet neither.
Economic DiversificationActof1990 has a substantial Ofthe 3,094 counties mapped, 76 percentare inForest
effecton the Forest Service's rural developmentprogram. Service's Southern and Eastern Regions (R-8 and R-9); of
It provides for assistance to rural communities inornear the 2,238 coimties meetingthe 100-mile criterion, 78 per-
National Forests, that are economicallydependenton for- cent are in the Southern and Eastern Regions; and ofthe
estandotherwildland resources, orthat are likely tobe 1,150 counties meetingboth the 100-mile and 15 percent
economicallydisadvantagedbyland management prac- dependencycriteria, about 66 percent are in the Southern
tices. Rural communities include towns and counties (or and Eastern Regions.
similarunits ofgeneral purpose localgovernment) that USES Total Within ...and 15 percent
meetthe followingcriteria.
Region counties 100 miles dependency
• Towns musthave populations of10,000 orless. 1 122 99 85
• Counties must notbe within a Metropolitan 2 345 118 110
Statistical Area. 3 48 48 38
• Counties containingthe community mustderive at 4 88 88 73
least 15 percentoftheirtotal (direct plus indirect) 5 63 50 22
income from wildland-related industries. 6 75 75 62
• Atown orcountymustbe within 100 miles ofa 8 1,300 1,047 499
National Forestboundary. 9 1,037 706 255
Information on National Forestproximitywere com- 10 23 12 11
piled by Forest Service rural development specialists. Total 3,094 2,238 1,150
Wildland-related industries include the timber, grazing,
Figure lbshowsamoredetailedpresentationofthedistri-
mining, and recreation industries, alongwith related Fed-
butionofcounties withintheregion, intermsofthe 100-mile
eral employment. Direct wildland-related earnings infor-
mationwas developed for 1990 bythe U.S. Bureau ofEco- andthe 15-percentdependencycriteria. Unlike figure la,
nomicAnalysis (USDC-BEA 1992) and theU.S. Office of eachcriterion is displayed separately. Counties meeting
Personnel Management(0PM 1992). Indirectearnings boththe 100-mile(shading) andthe 15-percentdependency
were estimated withmultipliers produced bythe Bureau (crosshatched)areshownwiththedarkestshadingpattern;
ofEconomicAnalysis' Regional Input-OutputModeling counties meetingneithercriterion are shown in white.
System (RIMS).
2
Figure 1b—County proximityto National Forest lands and 1990total wildlanddependency.
purposes; forexample, a county where 90 percentofthe
Rural Population
populationlives in a town of3,000 would be considered 90
percenturban. The definitionhelps distinguish the most
Rural areas share several characteristics distinguishing
ruralcounties. Italsorevealsthatsome counties withlarge
themfromurban places—lowerpopulation density, greater
population centers, particularlylarge western counties,
distances to trade centers and transportation corridors, alsohave a substantial numberofpeople livingin less
higherprobabilityofspecializationinnatural resource in-
densely settled areas orsmaller communities.
dustries, and different social structures. Thesecharacteris- The listingbelow shows thatthe Northern Region (R-1)
ticscanbebothchallengesandassetsforruraldevelopment.
ofthe Forest Service has the highest percentage ofrural
Rural areas can be identified onthe basis ofthe percent-
population, nearly 50 percent, andthe Pacific Southwest
age ofits population thatcorresponds torural residents
as defined bythe USDC Bureau ofthe Census: Region(R-5)hasthesmallestproportion,lessthan8percent.
USFS Percentrural
Urbanresidentsarepersonslivinginurbanizedareas(central
citiesandsurroundingdenselysettledterritorywithacombined Region population
populationofatleast50,000)andpersonslivinginplaceswith 1 48.3
populationsof2,500ormoreoutsideurbanizedareas;everyone
elseisaruralresident. 2 28.0
3 16.8
Rural population rates were based onthe 1990 Decennial
Census (USDC-BOC 1993c). 4 19.3
5 7.5
Figure 2a displaysthe 2,127 counties (69 percent) where
6 25.8
50 percentor more ofthe population is rural. Overall, 25
8 31.7
percentofthe U.S. population is rural. The 75 percentof
9 24.8
thepopulationlivinginurbanareasoccupyonlyabout3per-
10 32.5
centoftheland area. The urban populationisconcentrated
Total 24.9
in a small numberofcounties, such as CookCounty, IL
(Chicago), and LosAngeles County, CA(LosAngeles). Most Figure 2b shows the percentage ofrural population for
counties have more than 50 percentrural population. All counties in the region. The shadingranges from none (less
ofthe population in manycounties is rural. The Census than 25 percentrural population)to the darkest shading
Bureau definition ofrural maybe toorestrictive forsome (75 percentormore rural population).
Figure2a—Rural population rate, 1990.
4

Lake County, CO, hadthe highestnet out-migration
Net Migration
(—43.5 percent). Netin-migrationis strongly associated
with metropolitan areas (such as Portland and Dallas)
Netmigrationis the differencebetweenin-migration andadjacentcounties, amenity-producingareas (such as
(peoplemovingintoanarea)andout-migration(people mov-
the Coeur d'Alene area ofIdaho and the Brainerd area
ingoutofan area). Ifthere aremore out-migrants thanin- ofMinnesota), andretirementareas (such asArizona and
migramtsduringaspecifiedtimeperiod,theareahasnetout-
Florida).
migration; ifthere are more in-migrants, the area has net The listingbelow shows thatthe Northern (R-1), Rocky
in-migration. Areas lose population through out-migration
Mountain(R-2), andEastern Regions (R-9)experiencednet
because ofa lack ofjobs. The numberofjobs may actually
out-migration between 1980 and 1990, with the Northern
decline, orthe rate orkinds ofnewjobscreated maynot
Region displayingthe highest out-migration rate. Other
accommodate everyone seekingwork. People also migrate
regions showed netin-migration, withthe Southwest Re-
seekingquality-of-life attributes—favorableclimate, ameni-
gion(R-3) displayingthe highestrate:
ties, andlowercost-of-living; most migrants seekingthese
attributes have traditionallybeen retirees. USFS Percentnet
Because direct counts ofin- and out-migrants aregener- Region migration
allynot available, netmigration is calculated from other 1 -8.0
data: beginningand endingpopulations, totalbirths, and 2 -2.4
total deaths. Ifbeginningpopulation plus births minus 3 12.5
deaths is greaterthan the endingpopulation, there is net 4 5.8
out-migration; ifless, there is net in-migration. Netin- 5 10.9
migration does notnecessarily imply an increasing popu- 6 5.3
lation, and netout-migrationdoes notnecessarilyimplya 8 5.4
decreasingpopidation. Owr 1980to 1990netmigrationrates 9 -3.0
werebased onthe U.S. Bureauofthe Census netmigration 10 9.4
estimates forthe period (USDC-BOC 1993a). The 1980 to
Figure 3bprovides a more detailed, regional breakdown
1990 netmigration rate depicts netmigrationas apercent-
ofnet migration, dividingout-migration into categories of
age ofthe 1980 population.
greater andlessthan 10 percent. Unshaded areas repre-
Figure 3adisplays 1980to 1990 netmigrationrates rela-
sentcounties with net in-migration duringthe 1980's. The
tive to the 1980 population, showingthat mostcounties
darkestareas depictcounties where netout-migrationto-
(64 percent) experiencednetout-migration. FlaglerCounty,
taled atleast 10 percentofthe county's 1980 population.
FL, had the highestnet in-migration (+163.2 percent) and
Figure 3a—Net migration rate from 1980 to 1989.
6