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Redman, John M.Metro/Nonmetro Funding Allocation Under Title II-A,Job Training Partnership Act.Economic Research Service (DOA), Washington, DC.Agriculture and Rural Economy Div.Nov 9042p.
ERS-NASS, P.O. Box 1608, Rockville, MD 20849-1608(AGES 9071, $8).Reports Evaluative/Feasibility (142)
MF01/PCO2 Plus Postage.*Economically Disadvantaged; *Employment Programs;Federal Programs; Financial Support; *Job Training;Poverty; *Resource Allocation; *Rural Economics;*Rural Urban Differences; Unemployment*Job Training Partnership Act 1982 Title IIA
The Job Training Partnership Act (JTPA) Title II-Aprogram is the main federal effort to enhance the employability ofeconomically disadvantaged youths and adults. The amount of fundsallotted to each state is determined by a formula that allocatestwo-thirds of available funds on the basis of relative unemploymentlevels and one-third on the basis of the number of disadvantagedpersons in each state. This allocation formula produced a rise inexpenditures per member of the civilian labor force and expendituresper disadvantaged person in Service Delivery Areas (SDA's) in ruralareas between July 1987 and June 1988. This was due to the unusuallyhigh unemployment rates experienced by many nonmetro areas at thetime. The current regional distribution of JTPA funds was comparedwith distributions obtained from application of two alternativeformulas using measures of economic disadvantage (unweighted andweighted by the poverty rates). Application of either alternativeproduced a substantial reallocation of program activity amongregions. Under either alternative, however, the New York/New Jerseyregion would receive substantially larger allocations, and theindustrial Midwest would experience a substantial reduction. If oneused the number of disadvantaged living in the SDA as the soleallocation criterion, metro SDA's enjoyed a measurable increase inJTPA funds. Metro/nonmetro differences in unemployment rates havebeen steadily diminishing. Therefore, nonmetro areas may be betterserved during the 1990's by a new funding formula emphasizing povertyrates more than unemployment rates. The report contains numeroustables. (KS)
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United StatesDepartment ofAgriculture
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Metro/Nonmetro FundingAllocation Under Title II-AlJob Training Partnership ActJohn M. Redman
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Metro/Nonmetro Funding Allocation Under Title 11-A, Job TrainingPartnership Act. By John M. Redman. Agriculture and Rural EconomyDivision, Economic Research Service, U.S. Department ofAgriculture. Staff Report No. AGES 9071.
Abstract
The Job Training Partnership Act's (JTPA) Title lI -A Program isthe main Federal effort to enhance the employability of theeconomically disadvantaged. Relying primarily on unemploymentrates, the JTPA allocation formula produced higher expendituresper disadvantaged person in the more rural areas between July1987 and June 1988. This was due to the unusually highunemployment rates experienced by many nonmetro areas at thetime. Metro/nonmetro differences in unemployment rates have beensteadily declining, however, so that this funding advantage israpidly diminishing. Nonmetro areas may be better served duringthe 1990's by a new funding formula emphasizing poverty ratesmore than unemployment rates.
Keywords: Job Training Partnership Act, nonmetro economics,rural economics, unemployment, poverty rate.
Acknowledgments
The author thanks David Sears, Norman Reid, Richard Reeder, PaulSwaim, and Patrick Sullivan of ERS, Greg Knorr of the U.S.Department of Labor, and Jose Figueroa of the National Governors'Association for their helpful comments. The author is alsoindebted to Lisa Mendelson of ERS and Gail Bourchers of the U.S.Department of Labor for their extensive assistance in databasedevelopment and data analysis.
1301 New York Avenue, NW.Washington, DC 20015 -4788 November 1990
iii
Contents
Summary v
Introduction 1
Overview of the JTPA Title II-A Program 1
Distribution of Program Activity by State and SDA Type 6
Relationship of Program Activity Levels to Size ofLabor Force, Unemployment, and Economic Disadvantage 12
"'Alternative Allocation Scenarios 21
Conclusions 24
iv
summary
The Job Training Partnership Act (JTPA) Title II-A program is themain Federal effort to enhance the employability of economicallydisadvantaged youths and adults. Administered by the U.S.Department of Labor (DoL), it is of particular importance to themany communities that have no other ongoing source of trainingfunds and whose local revenue bases are too small to supportsustained independent efforts.
The following report examines metro/nonmetro funding allocationsunder Title II-L during program year (PY) 87 (July 1987 throughJune 1988). Four major questions are addressed:
1. What is the current program structure, particularly thedistribution of program activity and funding between metroand nonmetro areas under the existing method of allocation?
2. How does spending per member of the civilian labor force,per unemployed person, and per economically disadvantagedperson vary between metro and nonmetro areas?
3. What factors are most important in determining spendingpatterns?
4. How do these patterns compare with those produced byallocation formulas relying more heavily on other measuresof economic disadvantage?
During PY87, the Title II-A program had 610 Service DeliveryAreas (SDA's). These are the program's local administrativeunits. Of these 610 SDA's, 261 (43 percent) were entirely inmetropolitan areas (called metro SDA's). Another 129 (about 21percent) were wholly in nonmetro areas (nonmetro SDA's). Theremaining 220 (36 percent) contained both metro and nonmetroareas. Of these, 136 (22 percent of the 610) had less than halfof their population living in nonmetro areas (metro dominantSDA's). The other 84 SDA's (14 percent of the 610) had more thanhalf of their population living in nonmetro areas (nonmetrodominant SDA's).
Most program activity was concentrated in fewer than 20 States.Among the nonmetro dominant and nonmetro SDA's, 17 Statesaccounted for two-thirds of the program terminees (the program'sname for participants who completed training or otherwise leftthe program). Ten of the 14 largest programs are among these 17.
The typical program was of similar size (measured in terms ofcosts and participant numbers) in the metro, metro dominant, andnonmetro dominant SDA categories. The average nonmetro programwas considerably smaller.
There was a smooth decline from metro to metro dominant tononmetro dominant to nonmetro SDA's in average population densityand prevailing wage rates and a smooth increase in unemploymentand poverty rates.
Expenditures per disadvantaged person (that is, a person definedas disadvantaged in Title II-A of the Job Training PartnershipAct) varied widely across SDA's. Disadvantaged individuals livingin different SDA's consequently faced very different odds ofreceiving training.
The unemployment rate appears to be the key factor in explainingnational patterns of expenditure per labor force member and perdisadvantaged person. This appears to have particularly benefitedthe more rural SDA's because they had unusually high unemploymentrates during the period studied. When the unemployment rate iscontrolled for, the number of economically disadvantaged personsliving in an SDA was negatively associated with SDA expendituresper disadvantaged person.
SDA's with lower expenditures per local disadvantaged person wereoften those with a higher percentage of local families livingbelow the poverty line. This suggests that jurisdictions withmore severe problems frequently receive a lower relative level ofJTPA support.
The current regional distribution of JTPA funds was compared withdistributions obtained from application of two alternativeformulas utilizing measures of economic disadvantage only.Application of either alternative produced a substantialreallocation of program activity among regions. Under eitheralternative, however, the New York/New Jersey region wouldreceive substantially larger allocations, and the industrialMidwest would experience a substantial reduction.
If one uses the number of disadvantaged living in the SDA as thesole allocation criterion, metro SDA's enjoyed a measurableincrease in JTPA funds. If one uses a formula that includes boththe SDA poverty rate and the number of disadvantaged, nonmetrodominant SDA's experienced a substantial funding increase at theexpense of a slight reduction in funding for the other threecategories.
For those who work in rural development, the conclusions suggestthat, by virtue of its reliance on unemployment rates, thecurrent JTPA allocation formula produced higher expenditures perdisadvantaged person in the more rural SDA's during the studyperiod. This is a direct result of the unusually highunemployment rates in many nonmetro areas at the time.
Metro/nonmetro differences in unemployment rates have recentlybeen declining, however, so the funding advantage provided by useof unemployment rates may be rapidly diminishing. In contrast,the metro/nonmetro poverty rate differential, defined in terms ofthe percentage of individuals living below the poverty line, hasincreased. In the future, heavier reliance on the poverty rateto allocate JTPA funds may thus offer nonmetro areas a fundingadvantage of comparable size and (probably) of greater stabilitythan that afforded in recent years by the unemployment rate.
vi
Metro/Nonmetro FundingAllocation Under Title II-A,
Job Training Partnership ActJohn M. Redman
Introduction
This report examines the subject of metro/nonmetro fundingallocation under Title II-A of the Job Training Partnership Act(JTPA) during program year (PY) 87 (July 1987 through June 1988).
Four major questions will be considered:
1. What is the current program structure, particularly thedistribution of program activity/funding between metro andnonmetro areas under the existing all cation mechanism?
2. How does spending per member of the civilian labor force,per unemployed person, and per economically disadvantagedperson vary between metro and nonmetro areas?
3. What factors are most important in determining spendingpatterns?
4. How do these patterns compare with those produced byallocation formulas relying more heavily on other measures
of economic disadvantage?
Since the metro/nonmetro dimension of the Title II-A program has
not so far received serious study, this analysis may proveparticularly useful for those who work in the field of rural
economic development.
Overview of The JTPA Title II-A Program
The Title II-A program, technically titled "Training Services forthe Disadvantaged: Adult and Youth Programs," was authorized in1982 as part of the original Job Training Partnership Actlegislative package. This package also included summer youthemployment and training programs (Title II-B), employment andtraining services for dislocated workers (Title III), services
for native Americans and migrant and seasonal farmworkers (Title
IV-A), the Job Corps (Title IV-B), and veterans' employmentprograms (Title IV-C).
Administered by the U.S. Department of Labor (DoL), Title II-A is
the major Federal program designed to enhance the employabilityof the economically disadvantaged through training services.
1
0
Total local expenditure of Federal funds under Title II-A wasabout $1.6 billion in PY87.
The definition of economically disadvantaged used to determine anindividual's eligibility for Title II-A services is given in thelegislation, which specifies six different categories ofeligibles:
1. An individual who receives, or who is a member of a familythat receives, cash welfare payments under a Federal, State,or local welfare program. These programs include Aid toFamilies with Dependent Children, General Assistance, andRefugee Assistance.
2. Individuals whose total family income for the 6 monthsprior to program application was less than the poverty levelor less than 70 percent of the "lower living standard"income level,2 whichever was higher.
3. An individual receiving food stamps.
4. A homeless person as defined under the McKinney HomelessAssistance Act.
5. A foster child on whose behalf State or local governmentpayments are made.
6. Low-income handicapped individuals whose own income is lessthan the income thresholds in number 2 above but whosefamily income exceeds those thresholds.
Title II-A funds are provided as block grants to the States,which administer the JTPA structure. The program's localadministrative districts are termed "Service Delivery Areas" orSDA's. The State is allowed broad discretion in defining SDAboundaries. This has resulted in wide variation across States in
Exclusive of unemployment compensation, child supportpayments, and welfare payments.
2The "lower living standard income" is defined in thelegislation as "that income level (adjusted for regional,metropolitan, urban and rural differences and family size)determined annually by the Secretary [of Labor] based on the mostrecent 'lower living family budget' issued by the Secretary."This budget, in turn, was developed by the Bureau of LaborStatistics (BLS) as an alternative measure of poverty levelincome. Its computation was discontinued several years ago,however. The annual adjustments called for by the legislation arethus adjustments to the last budget issued by BLS. Caseworkers atthe SDA level are provided both poverty line and lower livingstandard income levels for assessing individual eligibility. Theeligibility determination is then made by applying the higher ofthe two measures to the individual's reported family income.
2
the number of SDA's within the State and the average SDApopulation. There were 610 SDA's during PY87.
The amount allotted to each State is determined by a formula thatallocates two-thirds of available funds on the basis of relativeunemployment levels3 and one-third on the basis of the number ofdisadvantaged persons in each State. Seventy-eight percent of theblock grant funding received by each State must be allocated tothe 3DA's by the same formula used to distribute funds across theStates. These funds are termed "basic formula" funds. Theremaining 22 percent is available for State "set-aside"activities:4
1. Eight (of the 22) percent to State education agencies foreducation and training services to eligible participantsthrough cooperative agreements.
2. Six percent for (a) incentive grants to SDA's that exceedprogram performance standards and (b) technical assistanceto SDA's.
3. Five percent for auditing and general programadministration.
4. Three percent for special training for persons aged 55and over who are economically disadvantaged.
Of the basic Title II-A formula funds received by the SDA fromthe State, 70 percent must be spent on training. Of the remaining30 percent, no more than 15 percent may be spent foradministrative costs. The other 15 percent is for supportservices for program participants (such as child care costs or
3Technically, there are two unemployment-based measures. Eachis used to allocate one-third of total program funding among theStates. The first measure is defined as "the relative number ofunemployed individuals residing in areas of substantialunemployment in each State as compared to the total number ofsuch unemployed individuals in all such areas of substantialunemployment in all the States." An area of substantialunemployment is defined, in turn, as "any area of sufficient sizeand scope to sustain a program under part A of Title II of theAct and which has an average rate of unemployment of at least 6.5percent for the most recent twelve months as determined by theSecretary [of Labor]." The second unemployment measure is "therelative excess number of unemployed individuals who reside ineach State as compared to the total excess number of unemployedindividuals in all the States." Excess number means the"...number of unemployed individuals in excess of 4.5 percent ofthe civilian labor force in the State ..." or "...the number ofunemployed individuals in excess of 4.5 percent of the civilianlabor force in areas of substantial unemployment in each State."
4There is no information at the national level on how theseset-aside funds are allocated between metro and nonmetro areas.
3
transportation). Forty percent of the dollars received must bespent on youth programs, and up to 10 percent may be spent onnondisadvantaged individuals with other important barriers toemployment (such as the handicapped or ex-offenders).
Within the SDA, the Private Industry Council (PIC) is the chiefadministrative unit. The PIC is to "provide policy guidance for,and exercise oversight with respect to, activities under the jobtraining plan tor its service delivery area in partnership withthe unit or units of general local government within its servicedeliver- area" (Sec. 103(a) of the act). A majority of the Pr'member 'i.p consists of representatives of the private sector, butit must also have local representation from organized labor,educational and rehabilitation agencies, community-basedorganizations, local economic development agencies, and thepublic employment service. This membership blend is intended topromote close program ties to the private business community,while maintaining direct input from other key institutions.
The PIC must work closely with local elected officials becauseany plan it develops must be approved by the chief electedofficial(s) of each general unit of government within the SDA orby their representative(s). The plan must, in addition, bereviewed and approved by the governor. This rather elaborateprocess is intended to produce a plan that has received broadreview and political support and thus stands a gond chance ofeffective, sustained implementation.
Besides approving the local plans, the governor has primaryresponsibility for ongoing administrative oversight. The governoralso manages the State set-aside programs.
Table 1 provides basic information on the PY86 organizationalstructure and size of SDA's on a State-by-State basis.5 A reviewof these structures suggests that States have taken five basic
5Program data for PY 1986 and 1987 were obtained from the U.S.Department of Labor (DoL). The program year runs from July 1through June 30 with PY87 ending on June 30, 1988. Data arereported to DoL by the individual States. The States, in turn,receive data from each of the local SDA's, the program's basicadministrative unit. The standard reporting form used by allSDA's is called the JTPA Annual Status Report (JASR). The JASRprovides information on activity levels, participantcharacteristics, and program cost. Population data used in thisreport to estimate the percentage of an SDA's total nonmetropopulation in 1986 are county- and minor civil division (MCD)-level estimates from the Bureau of the Census. Counties weredesignated as metro or nonmetro depending on whether they werewithin a metropolitan statistical area (MSA) as defined by theOffice of Management and Budget (OMB) in 1983.
4
Table 1-- Organizational and size characteristics of SDA's by State, PY86
PY86 1986
SDA organization number State Mean pop. Mean pop.of SDA's population per SDA per SDA type
Number
Single-State SDA's: 7 1,010,000
Delaware 632,700 632,700Dist. Columbia 626,100 626,100North Dakota 679,300 679,300South Carolina 3,375,300 3,375,300South Dakota 708,000 708,000Vermont 541,100 541,100Wyoming 507,500 507,500
Modified single-State SDA's: 28 609,574
Alabama 3 4,052,300 1,350,767Alaska 3 533,600 177,867Maine 2 1,173,600 586,800Mississippi 3 2,625,500 875,167Montana 2 818,800 409,400Nebraska 3 1,597,800 532,600Nevn,lit 2 963,200 481,600New Hampshire 2 1,026,900 513,450New Mexico 3 1,479,800 493,267Rhode Island 3 975,000 325,000West Virginia 2 1,918,800 959,400
County-based SDA's: 155 310,678
Colorado 10 3,266,700 326,670Hawaii 4 1,062,300 265,575Idaho 6 1,001,500 167,083Indiana 17 5,503,600 323,741Iowa 16 2,850,800 178,175Kansas 5 2,460,400 492,080Kentucky 9 3,727,900 414,211Maryland 10 4,463,300 446,330North Carolina 26 6,331,600 243,523Tennessee 14 4,802,900 343,064Utah 9 1,665,300 185,033Washington 12 4,462,500 371,875Wisconsin 17 4,784,800 281,459
Modified county-based SDA's: 396 375,674
Arizona 16 3,279,700 204,981Arkansas 10 2,372,200 237,220California 51 26,981,000 529,039Florida 24 11,674,900 486,454Georgia 18 6,104,300 339,128Illinois 26 11,553,200 444,354Louisiana 17 4,501,300 264,782Michigan 26 9,144,600 351,715Minnesota 17 4,213,900 247,876Missouri 15 5,066,000 337,733New Jersey 17 7,619,600 448,212New York 34 17,772,100 522,709Ohio 30 10,752,500 358,417Oklahoma 12 3,305,600 275,467Oregon 7 2,697,900 385,414Pennsylvania 28 11,889,200 424,614Texas 34 16,682,100 490,650Virginia 14 5,781,200 413,371
Town-based SDA States: 24 371,547
Connecticut 9 3,188,700 354,300Massachusetts 15 5,831,900 388,793
U.S. total, 1986 610 241,037,800 395,144
Source: JTPA Annual Status Report data, as compiled by the U.S. Department of Labor,Office of Strategic Planning and Policy Development.
5
CI /3 i
app:oaches6 to defining their SDA jurisdictions. Theseapproaches are:
1. The single-State SDA--all areas in the State are in oneSDA. These SDA's had, on average, about 2-1/2 times the U.S.mean SDA population.
2. The modified single-State SDA--most of the physical areaof the State is in a single SDA, but selected metro areasare designated as separate SDA's. The average SDA populationin these States was about 1-1/2 times the U.S. mean.
3. County-based SDA's--SDA jurisdictional boundaries aredefined exclusively in terms of county boundaries. Thenumber of counties in each SDA varies widely within andbetween States. Average SDA size in these States was about80 percent of the U.S. mean.
4. Modified county-based SDA's--SDA's are defined principallyby county boundary, but selected urbanized areas withinindividual counties, such as a large city, are designated asseparate SDA's. The balance of the affected counties areplaced in different SDA's. Average SDA size was slightlybelow the national mean.
5. Town-based SDA's--Connecticut and Massachusetts define theirSDA's principally in terms of town rather than countyboundaries. SDA average size was also slightly below thenational mean.
No one has examined SDA jurisdictional boundaries across theNation to see how closely they correspond to local labor marketareas.
Distribution of Program Activity by State and SDA Type
Tables 2, 3, and 4 present data regarding the distribution ofprogram activity by what I call SDA type. These categories aredefined in terms of the percentage of total 1986 SDA populationliving in nonmetro areas. Four types7 were defined as follows:
1. Metro--zero percent of the SDA population living innonmetro areas.
2. Metro dominant--0.01 to 49.99 percent of the SDA populationliving in nonmetro areas.
6These categories were developed by the author for descriptivepurposes only. There are no such regulatory definitions.
7These categories were also developed for this study only.There are no such regulatory definitions.
6
Tab
le 2
-Dis
trib
utio
n of
PY
87 a
dult
term
inee
s by
Sta
te, b
ySD
A ty
pe, r
anke
d by
sum
of
term
inee
sin
non
met
ro a
nd n
onm
etro
dom
inan
t SD
A's
Stat
e
Tot
al te
rmin
ees
per
SDA
type
Tot
alte
nnin
ees
Met
ron=
261
Met
rodo
min
ant
n=13
6
Non
met
rodo
min
ant
Non
met
ron=
84n=
129
Ter
min
ee p
erce
nt o
f St
ate
tota
l
Met
ron=
261
Met
rodo
min
ant
n=13
6
Non
met
rodo
min
ant
Non
met
ron=
84n=
129
Sum
of
nonm
etro
& n
onm
etro
Perc
ent o
fdo
min
ant
tota
lte
rmin
ees
Cum
ulat
ive
perc
ent
Mis
siss
ippi
Nor
th C
arol
ina
Ten
ness
eeA
rkan
sas
Ken
tuck
yW
isco
nsin
Mic
higa
nL
ouis
iana
Ohi
oIl
linoi
sIn
dian
aM
isso
uri
Okl
ahom
aT
exas
Min
neso
taW
est V
irgi
nia
Geo
rgia
Vir
gini
aN
ew Y
ork
Penn
sylv
ania
Ore
gon
Cal
ifor
nia
Iow
aSo
uth
Dak
ota
Ari
zona
Was
hing
ton
Mon
tana
Idah
oK
ansa
sC
olor
ado
Mai
neN
ew M
exic
oN
ebra
ska
Ver
mon
tN
orth
Dak
ota
Wyo
min
gU
tah
Ala
ska
New
Ham
pshi
reFl
orid
aM
aryl
and
Haw
aii
Con
nect
icut
Sout
h C
arol
ina
Rho
de I
slan
dN
ew J
erse
yN
evad
aM
assa
chus
etts
Dis
tric
t of
Col
umbi
aD
elaw
are
Ala
bam
a
Tot
al
10,1
5512
,000
11,9
287,
118
8,25
410
,415
23,3
1211
,700
25,1
7625
,610
10,7
539,
659
6,73
425
,166
9,79
94,
778
8,94
67,
083
34,3
5620
,134
7,13
533
,387
5,96
12,
318
5,11
19,
413
1,93
62,
639
2,65
26,
935
1,78
72,
195
2,18
21,
219
982
960
2,71
181
856
821
,560
8,77
91,
205
2,66
35,
945
1.00
07,
732
1,67
54,
606
1,78
81,
156
9,81
6
441,
910
1,29
13,
203
1,95
416
31,
075
2,88
613
,222
4,42
513
,018
14,6
962,
842
3,96
62,
423
10,8
473,
075
374
2,46
91,
122
30,4
4512
,049
3,29
027
,389
0 02,
873
4,65
0 0 023
54,
300
182
717
662 0 0 0
118 0 75
10,9
537,
481
859
1,89
8 065
37,
732 0
4,07
91,
788 0
3,53
1
209,
010
Num
ber 0
1,55
53,
926
1,02
21,
549
2,07
64,
717
2,26
47,
452
6,22
33,
548
1,37
9 010
,156
2,64
132
52,
539
2,31
937
84,
821
874
3,13
83,
129 0 0
2,54
5 075
858
51,
019 0 0
150 0 0 0
1,74
227
8 010
,126 824 0
610
5,94
534
7 01,
675
527 0
1,15
66,
285
100,
603
8,86
43,
249
3,22
32,
856
4,74
63,
790
1,18
83,
550
2,56
045
93,
654
1,15
32,
844
2,92
82,
978
4,07
92,
796
2,86
11,
412
1,35
1 0 036
52,
318 0
1,34
81,
530 0
1,29
8 01,
605
1,38
51,
370
1,21
998
296
0 0 049
3 012
0 015
5 0 0 0 0 0 0 0 0
75,6
89
03,
993
2,82
53,
077
884
1,66
34,
185
1,46
12,
146
4,23
270
93,
161
1,46
71,
235
1,10
5 01,
142
781
2,12
11,
913
2,97
12,
860
2,46
7 02,
238
870
406
1,88
153
41,
616 0 93 0 0 0 0
851
540 0
481
354
346 0 0 0 0 0 0 0 0 0
56,6
08
13 27 16 2 13 28 57 38 52 57 26 41 36 43 318 28 16 89 60 46 82 0 0 56 49 0 0 9 V 10 33 30 0 0 0 4 0 13 51 85 71 710 65 100 0 89 100 0 36 47
Perc
ent
0 13 33 14 19 20 20 19 30 24 33 14 0 40 27 72E 33
1
24 129
520 0 27 0 29 22 150 0 7 0 0 0 64 34 0
479 0 23 100 35 0
100 11 0
100
64 23
87 27 27 40 57 365 30 10 2 34 12 42 12 30 85 31 40 4 7 0 0 6
100 0 14 79 0 49 0 90 63 63 100
100
100 0 0 87 0 1 0 6 0 0 0 0 0 0 0 0 17
0 33 24 43 11 16 18 12 9 17 7 33 22 5 11 0 13 11 6 10 42 9 410 44 9
21 71 20 23 0 4 0 0 0 0 31 66 0 2 4 29 0 0 0 0 0 0 0 0 0 13
- --
Num
ber
- --
8,86
47,
242
6,04
85,
933
5,63
05,
453
5,37
35,
011
4,70
64,
691
4,36
34,
314
4,31
14,
163
4,08
34,
079"
3,93
83,
642
3,53
33,
264
2,97
12,
860
2,83
22,
318
2,23
82,
218
1,93
61,
881
1,83
21,
616
1,60
51,
478
1,37
01,
219
982
960
851
540
493
481
474
346
155 0 0 0 0 0 0 0 0
132,
297
Perc
ent
6.7
5.5
4.6
4.5
4.3
4.1
4.1
3.8
3.6
3.5
'3.3
3 3
3.3
3.1
3.1
3.1
3.0
2.8
2.7
2.5
2.2
2.2
2.1
1.8
1.7
1.7
1.5
1.4
1.4
1.2
1.2
1.1
1.0 .9 .7 .7 .6 .4 .4 .4 .4 .3 .1 0 0 0 0 0 0 0 0
6.7
12.2
16.7
21.2
25.5
29.6
33.7
37.5
41.0
44.6
47.9
51.1
54.4
57.5
60.6
63.7
66.7
69.4
72.1
74.6
76.8
79.0
81.1
82.9
84.6
86.2
87.7
89.1
90.5
91.7
92.9
94.1
95.1
96.0
96.7
97.5
98.1
98.5
98.9
99.3
99.6
99.9
100.
010
0.0
100.
010
0.0
100.
010
0.0
100.
010
0.0
100.
0
Sour
ce: I
TPA
Ann
ual S
tatu
s R
epor
t dat
a, a
s co
mpi
led
by th
e U
.S. D
epar
tmen
t of
Lab
or,O
ffic
e of
Str
ateg
ic P
lann
ing
and
Polic
y D
evel
opn,
ent.
14B
EST
CO
PY I
MR
E
Tab
le 3
--D
istr
ibut
ion
of P
Y87
wel
fare
adu
lt te
rmin
ees
by S
tate
, by
SDA
type
, ran
ked
by s
um o
f te
rmin
ees
in n
onm
etro
and
non
met
ro d
omin
ant S
DA
's
Stat
e
Tot
al te
rmin
ees
per
SDA
type
Ter
min
ee p
erce
nt o
f St
ate
tota
lSu
m o
fno
nmet
roT
otal
wel
fare
Met
roN
onm
etro
Met
roN
onm
etro
& n
onm
etro
Perc
ent o
fC
umul
ativ
ete
rrni
nces
Met
rodo
min
ant
dom
inan
tN
onm
etro
Met
rodo
min
ant
dom
inan
tN
onm
etro
dom
inan
tto
tal
perc
ent
n=26
1n=
136
n=84
n=12
9n=
261
n=13
6n=
84n=
129
term
inee
s
Num
ber
Perc
ent
- --
Num
ber
- --
Perc
ent
Mic
higa
n10
,267
5,42
22,
406
486
1,95
353
235
192,
439
7.2
7.2
Wis
cons
in4,
694
1,57
497
51,
488
657
3421
3214
2,14
56.
313
.5O
hio
11,3
376,
250
2,97
31,
181
933
5526
108
2,11
46.
219
.7M
issi
ssip
pi1,
875
135
01,
740
07
093
01,
740
5.1
24.8
Min
neso
ta4,
720
1,66
81,
352
1,26
343
735
2927
91,
700
5.0
29.8
New
Yor
k10
,899
9,01
619
160
81,
084
832
610
1,69
25.
034
.8N
orth
Car
olin
a2,
743
696
390
687
970
2514
2535
1,65
74.
939
.7Il
linoi
s9,
787
5,98
12,
216
143
1,44
761
231
151,
590
4.7
44.3
Wes
t Vir
gini
a1,
552
126
122
1,30
40
88
840
1,30
43.
848
.2Pe
nnsy
lvan
ia7,
703
4,84
51,
755
457
646
6323
68
1,10
33.
251
.4C
alif
orni
a10
,687
8,89
578
60
1,00
683
70
91,
006
3.0
54.4
Ten
ness
ee2,
074
415
667
491
501
2032
2424
992
2.9
57.3
Ark
ansa
s1,
119
2713
453
142
72
1247
3895
82.
860
.1M
isso
uri
1,87
676
319
324
167
941
1013
3692
02.
762
.8G
eorg
ia2,
148
621
631
566
330
2929
2615
896
2.6
65.5
Tex
as4,
915
2,19
01,
851
662
212
4538
134
874
2.6
68.0
Iow
a1,
854
01,
013
140
701
055
838
841
2.5
70.5
Vir
gini
a1,
866
376
703
642
145
2038
348
787
2.3
72.8
Lou
isia
na1,
769
704
296
506
263
4017
2915
769
2.3
75.1
Ken
tuck
y1,
143
190
232
584
137
1720
5112
721
2.1
77.2
Okl
ahom
a1,
064
344
046
925
132
044
2472
02.
179
.3W
ashi
ngto
n3,
045
1,53
587
838
724
550
2913
863
21.
981
.2O
rego
n1,
358
604
145
060
944
110
4560
91.
883
.0In
dian
a1,
505
452
487
483
8330
3232
656
61.
784
.6M
onta
na56
00
040
715
30
073
2756
01.
686
.3V
erm
ont
487
00
487
00
010
00
487
1.4
87.7
Mai
ne53
769
046
80
130
870
468
1.4
89.1
Kan
sas
770
7124
036
198
931
4713
459
1.3
90.4
Ari
zona
1,35
890
30
045
566
00
3445
51.
391
.8So
uth
Dak
ota
351
00
351
00
010
00
351
1.0
92.8
Neb
rask
a63
025
236
342
040
654
034
21.
093
.8Id
aho
461
016
90
292
037
063
292
.994
.'7C
olor
ado
1,61
21,
156
203
025
372
130
1625
3.7
95.4
Nor
th D
akot
a22
00
022
00
00
100
022
0.6
96.1
New
Mex
ico
317
990
202
1631
064
521
8.6
96.7
Mar
ylan
d3,
756
3,27
726
434
181
877
15
215
.697
.3U
tah
'Vyo
min
g69
226
465
020
14
670
2920
1.6
97.9
194
00
194
00
010
00
194
.698
.5N
ew H
amps
hire
167
180
149
011
089
014
9.4
98.9
Ala
ska
176
061
011
50
350
6511
5.3
99.3
Haw
aii
344
255
00
8974
00
2689
.399
.5Fl
orid
a3,
790
1,83
51,
870
085
4849
02
85.2
99.8
Con
nect
icut
1,26
496
322
774
076
186
074
.210
0.0
Dis
tric
t of
Col
umbi
a15
515
50
00
100
00
00
010
0.0
Nev
ada
148
014
80
00
100
00
00
100.
0So
uth
Car
olin
a1,
550
01,
550
00
010
00
00
010
0.0
Del
awar
e38
6(
386
00
010
00
00
010
0.0
Mas
sach
uset
ts2,
042
1,79
624
60
088
120
00
010
0.0
Rho
de I
slan
d41
528
513
00
069
310
00
010
0.0
New
Jer
sey
2,79
72,
797
00
010
00
00
00
100.
0A
laba
ma
1,01
953
848
10
053
470
00
010
0.0
Tot
al12
8,19
867
,324
26,8
7218
,348
15,6
5453
2114
1234
,002
Sour
ce: J
TPA
Ann
ual S
tatu
s R
epor
t dat
a, a
s co
mpi
led
by th
e U
. S.
Dep
artm
ent o
f L
abor
, Off
ice
of S
trat
egic
Pla
nnin
g an
d Po
licy
Dev
elop
men
t.
Tab
le 4
-Dis
trib
utio
n of
PY
87 y
outh
term
inee
s by
Sta
te, b
y SD
A ty
pe, r
anke
d by
sum
of te
rmin
ees
in n
onm
etro
and
non
met
ro d
omin
ant S
DA
's
Stat
e
Total ter minces per SDA type
Terminee percent of State total
Sum
of
Tot
alno
nmet
ro
yout
hM
etro
Non
met
roM
etro
Non
met
ro&
non
nict
roPe
rcen
t of
Cum
ulat
ive
term
inee
sM
etro
dom
inan
tdo
min
ant
Non
met
roM
etro
dom
inan
tdo
min
ant
Non
met
rodo
min
ant
tota
lpe
rcen
t
n=26
1n=
136
n=84
n=12
9r=261
n=13
6n=
84n=
129
term
ince
c
Number
Percent
'Number-
Percent
Mississippi
10,502
1,666
08,836
016
084
08,836
8.1
8.1
North Carolina
11,992
2,084
1,551
4,266
4,091
17
13
36
34
8,357
7.6
15.7
Kentucky
9,588
1,488
1,202
5,813
1,085
16
13
61
11
6,898
6.3
22.0
Tennessee
11,272
1,434
3,134
?,500
3,204
13
28
31
28
6,704
6.1
28.1
Louisiana
14,048
4,187
3,184
4,927
1,750
30
23
35
12
6,677
6.1
34.2
Arkansas
5,721
196
623
2,995
1,907
311
52
33
4,902
4.5
38.7
Wisconsin
8,267
2,397
1,886
2,476
1,508
29
23
30
183,984
3.6
42.3
Georgia
7,884
1,556
2,517
2,512
1,299
20
32
32
16
3,811
3,5
45.8
Illinois
23,415
14,539
5,100
238
3,538
62
22
115
3,776
3.4
49.2
Michigan
15,226
8,367
3,373
569
2,917
55
22
419
3,486
3.2
52.4
Ohio
21,803
13,098
5,529
1,322
1,854
60
25
69
3,176
2.9
55.3
Oklahoma
5,022
1,894
02,367
761
38
047
15
3,128
2.9
58.2
Texas
21,824
9,880
8,828
2,048
1,068
45
40
95
3,116
2.8
61.0
Missouri
7,249
3,387
854
954
2,054
47
12
13
28
3,008
2.7
63.8
Virginia
6,78F
1,485
2,333
2,350
620
22
34
35
92,970
2.7
66.5
Indiana
7,511
2,273
2,660
2,087
491
30
35
28
72,578
2.4
68.8
California
29,704
25,411
1,719
02,574
86
60
92,574
2.3
71.2
Minnesota
5,443
1,904
988
1,803
748
35
18
33
14
2.551
2.3
73.5
West Virginia
2,799
233
109
2,457
08
488
02,457
2.2
75.8
New York
21,252
18,645
242
796
1,569
88
14
72,365
2.2
77.9
Pennsylvania
15,839
10,821
2,921
1,017
1,080
68
18
67
2,097
1.9
79.8
New Mexico
2,466
637
01,641
188
26
067
81,829
1.7
81.5
Oregon
4,853
2,689
382
01,782
55
80
37
1,782
1.6
83.1
Arizona
4,611
2,891
00
1,720
63
00
37
1,720
1.6
84.7
Iowa
3,993
02,294
205
1,494
057
537
1,699
1.6
86.2
Washington
7,099
3,564
1,889
1,047
599
50
27
15
81,646
1.5
87.7
Kansas
2,472
577
365
1,012
518
23
1541
21
1,530
1.4
89.1
South Dakota
1,403
00
1,403
00
0100
01,403
1.3
90.4
Colorado
4,446
2,583
530
01,333
58
12
030
1,333
1.2
91.6
Idaho
1,766
0504
01,262
029
071
1,262
1.2
92.8
Maine
1,248
59
01,189
05
095
01,189
1.1
93.9
Montana
1,126
00
903
223
00
80
20
1,126
1.0
94.9
Vermont
851
00
851
00
0100
0851
.895.7
Nebraska
1,075
263
46
766
024
471
0766
.7
96.4
Wyoming
684
00
684
00
0100
0684
.6
97.0
Maryland
5.799
4,506
728
190
375
78
13
36
565
.5
97.5
Alaska
894
0354
0540
040
060
540
.5
98.0
North Dakota
494
00
494
00
0100
0494
.5
98.5
Utah
1,537
106
975
0456
763
030
456
.4
98.9
New Hampshire
557
105
0452
019
081
0452
.4
99.3
Florida
14,936
7,663
6,939
0334
51
46
02
334
.3
99.6
Hawaii
1,401
1,132
00
269
81
00
19
269
.2
99.8
Connecticut
2,138
1,418
546
174
066
26
80
174
.2
100.0
Rhode Island
831
588
243
00
71
29
00
00
100.0
Massachusetts
3,015
2,607
408
00
86
14
00
00
100.0
Delaware
987
0987
00
0100
00
00
100.0
Nevada
2,091
02,091
00
0100
00
00
100.0
New Jersey
2,797
2,797
00
0100
00
00
0100.0
Sout
h C
arol
ina
5,92
60
5,926
00
0100
00
00
100.0
District of Columbia
362
362
00
0100
00
00
0100.0
Alabama
9,164
3,221
5.943
00
35
65
00
00
100.0
Total
354,171
164,713
79,903
64,344
45,211
47
23
18
13
109,555
Source: JTPA Annual Status Report data, as compiled by the U.S. Department of Labor, Office of Skrategic Planning and Policy Development.
BE
ST C
OPY
AV
AIL
AB
LE
1 9
3. Nonmetro dominant--50 to 99.99 percent of the SDA populationliving in nonmetro areas.
4. Nonmetro--100 percent of the population living in nonmetroareas.
Program activity is presented in terms of the total number of alladult terminees, the number of welfare adult terminees, and thenumber of youth terminees.8 "Terminee" is a program term used todenote a person who completed training or otherwise left the SDAprogram without completing training. Welfare adult terminees area subset of all adult terminees (that is, adult terminees who hadbeen receiving welfare upon entry into the program). Youthterminees are terminees who were less than 21 years of age whenthey entered the program. Though they may be receiving welfaresupport, they are included in the youth rather than welfare adultcategory.
In PY87, there were 261 metro SDA's and 129 nonmetro SDA's. Theremaining 220 SDA's were distributed very evenly between thesetwo extremes. Metro SDA's accounted for slightly less than halfof the all-adult and youth terminees and a little more than halfof the welfare-adult terminees. Nonmetro SDA's accounted forabout one-eighth of the terminees in each group.
Tables 2, 3, and 4 are arranged by State according to the sum oftheir terminees in nonmetro and nonmetro dominant SDA's. Thisordering was chosen to highJight States with the largest programsin predominantly nonmetro areas. Seventeen States, located almostexclusively in the Southeast and industrial Midwest, accountedfor two-thirds of the total terminees in these two SDA types. Tenof the 14 largest programs were in these 17 States.
Alabama and South Carolina are anomalies within thisclassification scheme. Each State has sizeable nonmetropopulations served by single, geographically extensive SDA's withpopulations more than 50 percent metropolitan. Consequently,these two States show no terminees in either the nonmetro ornonmetro dominant categories despite large aggregate nonmetropopulation percentages.9
Table 5 displays simple means for basic program characteristicsby SDA type across all 610 SDA's. Program cost is a measure ofFederal funds expended on training for each terminee group by theSDA during the program year. Separate cost data are collected
Data on the number of terminees and on program cost measuresare from the JTPA Annual Status Report (JASR) data provided bythe Department of Labor.
9In PY88, South Carolina disaggregated its single SDA intoseveral smaller SDA's. For the program year under study, however,there was a single SDA for the entire State.
r10 (,
Tab
le 5
-Pro
gram
cos
t and
par
ticip
atio
n
Item
Uni
t
PY86
unw
eigh
ted
U.S
. mea
nn=
610
PY86
unw
e;,,h
ted
mea
nby
SD
A'p
ePY
87PY
87 u
nwei
ghte
d m
ean
by S
DA
type
Met
ron=
262
Met
rodo
min
ant
n=13
5
Non
met
rodo
min
ant
n=84
Non
met
ron=
129
unw
eigh
ted
U.S
. mea
nn=
610
Met
ron=
261
Met
rodo
min
ant
n=13
6
Non
met
rodo
min
ant
n=84
Non
met
ron=
129
Adu
lt:M
ean
tota
l pro
gram
cos
tD
olla
rs1,
441,
253
(1)
1,68
2,30
5 (1
)1,
468,
316
1,58
8,78
682
9,15
61,
411,
575
1,60
5,68
11,
425,
618
1,68
2,73
482
7,47
9
SDA
type
mea
n/U
.S. m
ean
Rat
io1.
001.
171.
021.
10.5
71.
001.
141.
011.
19.5
9
Part
icip
ants
Num
ber
965
1,03
01,
043
1,17
861
195
21,
005
980
1,26
461
3
Ter
min
ees
Num
ber
722
809
763
808
443
724
801
740
901
439
SDA
type
mea
n/U
.S. m
ean
Rat
io1.
001.
121.
061.
12.6
11.
001.
1!1.
021.
24.6
1
Wel
fare
:M
ean
tota
l pro
gram
cos
t--
----
----
----
----
Part
icip
ants
Num
ber
291
347
294
294
171
292
342
279
325
179
Ter
min
ees
Num
ber
205
255
203
188
117
210
258
198
218
121
SDA
type
mea
n/U
.S. m
ean
Rat
io1.
001.
24.9
9.9
2.5
71.
001.
230.
941.
04.5
8
You
th:
Mea
n to
tal p
rogr
am c
ost
Dol
lars
1,02
8,31
41,
182,
717
1,09
3,97
61,
191,
589
539,
685
1,05
2,45
31,
187,
563
1,10
0,69
81,
300,
833
566,
493
SDA
type
mea
n/U
.S. m
ean
Rat
io1.
001.
151.
161.
16.5
21.
001.
131.
051.
24.5
4
Part
icip
ants
Num
ber
763
837
802
952
448
762
805
798
1,02
946
2
Ter
min
ees
Num
ber
575
659
584
669
332
587
645
588
766
350
SDA
type
mea
n/U
.S. m
ean
Rat
io1.
001.
151.
021.
16.5
81.
001.
101.
001.
30.6
0
= N
ot A
vaila
ble.
(1)
One
SD
A (
whi
ch w
as a
met
ro S
DA
) w
as d
ropp
ed f
rom
the
PY86
adu
lt co
st c
alcu
latio
ns b
ecau
se it
s re
port
ed v
alue
was
far
bel
ow a
ll ot
hers
.
Sour
ce: J
TPA
Ann
ual S
tatu
s R
epor
t dat
a, a
s co
mpi
led
by th
e U
.S. D
epar
tmen
t of
Lab
or, O
ffic
e of
Str
ateg
ic P
lann
ing
and
Polic
y D
evel
opm
ent.
(
BE
ST C
ITY
AV
P,E
,411
.E
only for all adults and for youth. Costs for welfare adults arenot segregated from the all-adult total. The number ofparticipants is the total number of people who were in theprogram during the program year, whether or not they finishedtraining. The difference between participants and terminees in agiven program year is the number of people who were in theprogram at the end of the program year but who had not yetcompleted training. For example, if a person began training onJune 1, 1986, but did not complete the program until August 1,1986, he or she would be counted as a participant in both PY85and PY86 and as a terminee in PY86.
The data in table 5 indicate that metro dominant and nonmetrodominant mean program cost and size were comparable with metrolevels in both the all-adult and youth programs. Metro programsdid, however, have a considerably higher average number ofwelfare adult terminees. The average nonmetro program wasconsiderably smaller on all measures than those in each of theother three SDA-type categories.
Five socioeconomic measures, displayed in table 6, are containedin the SDA-level data provided by the Department of Labor. Theseestimates are made by DoL for modeling purposes and are notreported directly by the SDA's.
The socioeconomic data indicate a steady decline in populationdensity from metro SDA's across the intermediate SDA types to thenonmetro SDA's. This is the expected finding. There is alsoconsistent variation from metro through nonmetro on the fourother variables. The more nonmetro the SDA type, the lower theprevailing wage rates and the higher the rates of unemploymentand families in poverty.
Relationship of Program Act:Lvity Levels to Size ofLabor Force, Unemployment, and Economic Disadvantage
Table 7 provides some summary measures of PY87 program activityas it related to the size of the civilian labor force, the numberof unemployed individuals, and the number of economicallydisadvantaged within each SDA. Data for program activity aretaken from the JTPA Annual Status Report (JASR) data. Civilianlabor force, unemployment, and economically disadvantaged datawere also provided by DoL.
Data on the number of economically disadvantaged are from aspecial tabulation of 1980 Census of Population data provided toDoL by the Bureau of the Census. These counts are consistent withthe definition of economically disadvantaged used in the Title1I-A allocation formula. DoL has used these specific totals forseveral program years to allocate Title II funds to the States.The States, in turn, have used them to allocate funds amongSDA's. The reason for their repeated use is that ro more recentsource exists of county-level data on the number of economicallydisadvantaged.
12
Tab
le 6
--So
cioe
cono
mic
cha
ract
eris
tics
of s
ervi
ce d
eliv
ery
area
s by
SD
A ty
pe, P
Y86
and
PY
87
PY86
PY86
unw
eigh
ted
mea
nsPY
87PY
87 u
nwei
ghte
d m
eans
unw
eigh
ted
by S
DA
type
unw
eigh
ted
by S
DA
type
Mea
sure
U.S
.m
ean
n=61
0
Met
ro
n=26
2
Met
rodo
min
ant
n=13
5
Non
met
rodo
min
ant
n=84
Non
met
ron=
129
U.S
.m
ean
n=61
0M
etro
n=26
1
Met
rodo
min
ant
n=13
6
Non
met
rodo
min
ant
n=84
Non
met
ro
n=12
9
Ave
rage
yea
rly
earn
ings
per
job,
Dol
lars
all s
ecto
rs17
,540
19,3
1017
,150
15,8
1015
,470
18,1
6720
,120
17,6
7016
,300
15,9
50
Ave
rage
yea
rly
earn
ings
per
job,
reta
il/w
hole
sale
12,1
1613
,700
11,6
0010
,600
10,4
0012
,489
14,3
0011
,900
10,8
0010
,600
Perc
ent
Une
mpl
oym
ent r
ate
7.81
6.48
7.97
8.36
9.96
7.40
6.10
7.61
8.15
9.30
Perc
enta
ge o
f fa
mili
es b
elow
the
pove
rty
leve
l, 19
809.
598.
009.
5011
.40
11.8
09.
598.
009.
5011
.40
11.8
0
1,00
0 pe
r sq
uare
mile
Popu
latio
n de
nsity
.74
1.61
.15
.06
.04
.74
1.61
.15
.06
.04
Not
e: V
alue
s fo
r th
e pe
rcen
tage
of
fam
ilies
bel
ow th
e po
vert
y le
vel a
nd f
or p
opul
atio
n de
nsity
wer
e on
e-tim
e es
timat
es a
nd a
re th
e sa
me
for
both
pro
gram
year
s.
Sour
ce: J
TPA
Ann
ual S
tatu
s R
epor
t dat
a, a
s co
mpi
led
by th
e U
.S. D
epar
tmen
t of
Lab
or, O
ffic
e of
Str
ateg
ic P
lann
ing
and
Polic
y D
evel
opm
ent.
r4
BE
ST C
OPY
Ani
tIL
LE
Table 7Measures
of a
ssoc
iatio
n am
ong
prog
ram
act
ivity
, lev
els
of e
cono
mic
dis
adva
ntag
e,em
ploy
men
tan
d un
empl
oym
ent b
y SJ
A ty
pe,PY87
Item
Num
ber
of c
ases
Wei
ghtin
gU
.S.
mea
n
PY87
mea
n by
SD
A ty
pe
Met
ron=
256
Met
rodo
min
ant
n=13
6
Non
met
rodo
min
ant
n=83
Non
met
ron=
124
Dol
lars
Adu
lt pr
ogra
m e
xpen
ditu
re p
er m
embe
rn=
598
Unw
eigh
ted
96
810
13of
the
civi
lian
labo
r fo
rce
Wei
ghte
d10
89
1213
Tot
al p
rogr
am e
xpen
ditu
re p
er m
embe
rn=
598
Unw
eigh
ted
1511
1518
21of
the
civi
lian
labo
r fo
rce
Wei
ghte
d17
1416
2222
.Z
1, lt
pro
gram
exp
endi
ture
per
n=59
7U
nwei
ghte
d12
010
611
413
214
4un
empl
oyed
per
son
Wei
ghte
d12
812
312
014
214
3
Adu
lt pr
ogra
m e
xpen
ditu
re p
er e
cono
mic
ally
n=59
9U
nwei
ghte
d24
2224
2427
disa
dvan
tage
per
son
Wei
ghte
d24
2225
2628
Tot
al p
rogr
am e
xpen
ditu
re p
er e
cono
mic
ally
n=59
9U
nwei
ghte
d41
3743
4245
disa
dvan
tage
d pe
rson
Wei
ghte
d42
3943
4546
Adu
lt pr
ogra
m e
xpen
ditu
re p
er e
cono
mic
ally
n=59
9U
nwei
ghte
d42
3944
4348
disa
dvan
tage
d ad
ult
Wei
ghte
d43
4044
4548
You
th p
rogr
am e
xpen
ditu
re p
er e
cono
mic
ally
n=59
9U
nwei
ghte
d14
012
514
915
015
2di
sadv
anta
ged
yout
hW
eigh
ted
150
134
161
167
166
Not
es: S
ee f
ootn
otes
at e
nd o
f ta
ble
Con
tinue
d--
Tab
le 7
-Mea
sure
s of
ass
ocia
tion
amon
g pr
ogra
m a
ctiv
ity, l
evel
s of
eco
nom
ic d
isad
vant
age,
em
ploy
men
t,an
d un
empl
oym
ent b
y SD
A ty
pe, P
Y87
-Con
tinue
d
Mea
n by
SD
A ty
pe
Item
Num
ber
of c
ases
Wei
ghtin
gU
.S.
mea
nM
etro
n=25
6
Met
rodo
min
ant
n =
136
Non
met
rodo
min
ant
n=83
Non
met
ron
= 1
24
Perc
ent
Adu
lt te
rmin
ees
as a
per
cent
age
of th
en=
598
Unw
eigh
ted
.44
.31
.44
.54
.63
civi
lian
labo
r fo
rce
Wei
ghte
d.5
3.4
5.5
0.6
7.7
0
All
term
inee
s as
a p
erce
ntag
e of
the
n=59
8U
nwei
ghte
d.8
0.5
7.7
9.9
91.
14
civi
lian
labo
r fo
rce
Wei
ghte
d.9
7.8
0.8
81.
281.
28
Adu
lt te
rmin
ees
as a
per
cent
age
of a
lln=
597
Unw
eigh
ted
6.16
5.24
6.08
7.23
1.42
unem
ploy
edW
eigh
ted
7.24
6.91
6.70
8.23
8.08
Adu
lt te
rmin
ees
as a
per
cent
age
of a
lln=
599
Unw
eigh
ted
1.22
1.06
1.29
1.35
1.37
econ
omic
ally
dis
adva
ntag
edW
eigh
ted
1.34
1.22
1.37
1.48
1.53
All
term
inee
s as
a p
erce
ntag
e of
all
n=59
9U
nwei
ghte
d2.
171.
922.
292.
382.
44
econ
omic
ally
dis
adva
ntag
edW
eigh
ted
2.37
2.16
2.39
2.65
2.72
Adu
lt te
rmin
ees
as a
per
cent
age
of e
cono
mic
ally
n=59
9U
nwei
ghte
d2.
181.
912.
322.
372.
43
disa
dvan
tage
d, a
ges
22 a
nd o
ver
Wei
ghte
d2.
402.
222.
462.
632.
68
All
yout
h te
rmin
ees
as a
per
cent
age
of e
cono
mic
ally
n=59
9U
nwei
ghte
d7.
806.
748.
078.
669.
11
disa
dvan
tage
d, a
ges
16 to
21
Wei
ghte
d9.
007.
968.
9610
.40
10.9
0
Not
e: O
ne S
DA
was
dro
pped
fro
m th
e ca
lcul
atio
n of
the
two
civi
lian
labo
r fo
rce
mea
sure
s du
e to
an
extr
eme
valu
e. T
wo
SDA
's w
ere
excl
uded
for
the
sam
e re
ason
s fr
om th
e ad
ult/u
nem
ploy
ed c
alcu
latio
n.
Sour
ce: U
.S. D
epar
tmen
t of
Lab
or. O
ffic
e of
Str
ateg
ic P
lann
ing
and
Polic
y D
evel
opm
ent.
C 9
('
4", t
";
The civilian labor force and unemployment rate data were providedto the D0L program office by the Bureau of Labor Statistics(BLS). These data are for PY87 (July 1987-June 1988) .10
Seven expenditure-based ratios are presented in table 7. Theseratios were calculated by dividing the relevant program costvariable by the relevant labor force or disadvantaged count. Theterminee-based measures in the continuation of table 7 use thesame denominator as these seven cost measures but employ termineecounts in the numerator instead of expenditure levels.
In addition, I weighted the results to measure the effect ofprogram size on the expenditure ratios. For the expenditure-based ratios, the weighted values use total SDA program costs forthe relevant terminee population (all adult or youth) as theweighting variables. For the terminee-based ratios, termineecounts are used.
The patterns displayed by these ratios are strong and consistent.With few exceptions, both weighted and unweighted values show anincrease in level across SDA types from metro to nonmetro. In nocase was the metro SDA value higher than the value for either thenonmetro dominant or nonmetro SDA categories. The nonmetro SDAmean value was always at least 16 percent higher than the metroSDA mean. It was, indeed, approximately double on thoseunweighted measures that used labor force or unemployment countsin the denominator.
A comparison of the weighted and unweighted values shows that thelarger programs within each category had higher than averagevalues on almost all measures. This influence was strongest inthe metro and nonmetro dominant categories. The metro SDAincrease was sharpest relative to the nonmetro SDA increase onthose ratios using labor force or unemployment counts in thedenominator. Size had much less influence on relativemetro/nonmetro values for those ratios related to thedisadvantaged.
"The number of SDA's in this labor force/disadvantageddatabase is 599, 11 SDA's fewer than the number submitting JASRreports in FY87. This discrepancy arises because the number ofSDA's dropped from 610 in PY87 to 599 in PY88, and DoL used thePY88 structure in compiling the labor force/disadvantaged data.These two data structures were reconciled without greatdifficulty, however. On variables utilizing the labor force data,there were one or two SDA's with very extreme values. Thesecases were dropped in calculating national and SDA type meansbecause they substantially affected the mean values. The numberof SDA's on a particular measure in table 7 may thus be slightlyless than 599..-
16J
The above results prompt the question: why are these variationsso systematic? The data permit examination of some hypothesesregarding this issue.
As table 7 indicates, the largest metro to nonmetro differentialsare found in the total expenditures per member of the civilianlabor force. The correlations among the data elements show thatvariatiel in the unemployment rate was a strong predictor ofvariation in expenditures per member of the civilian labor force.This relationship is shown in table 8. The quartiles are definedin terms of expenditures per member of the civilian labor force.Among the four quartiles, the top quartile contains the 25percent of SDA's (about 150) with the highest expenditures percivilian labor force member. The table shows how the unemploymentrate drops sharply across the quartiles. This suggests that thehigher the SDA's unemployment rate, the more JTPA funding itreceived per member of its labor force. This finding isconsistent with the heavy reliance on interstate differences inunemployment rates to allocate Title II-A funds among the States.
I also performed a simple linear regression to measure thisassociation more systematically. The results suggest that thevariation in the unemployment rate explained about 71 percent ofthe variation in total program expenditures per labor forcemember."
A second finding, also depicted in table 8, was that expendituresper disadvantaged person living in the SDA rose sharply withexpenditure per labor force member. SDA's in the highest quartileof expenditures per labor force member had mean expenditures perdisadvantaged person over twice the mean of the lowest quartile.If unit program costs were comparable from one SDA to another, aneconomically disadvantaged person living in a top-quartile SDA(with high expenditures per labor force member) had about twice
VAs noted in footnote 3, unemployment rate thresholds of 6.5percent and 4.5 percent are used to determine State eligibilityfor two-thirds of available funds. A finer level of analysiscentered around these thresholds was not pursued because theexplanatory power of the simple unemployment rate was very high,and use of this single rate facilitated presentation of thefindings. However, the threshold data clearly reinforce theinterpretation presented in the main text. For each threshold,the more nonmetro the SDA category, the higher the percentage ofSDA's with unemployment rates above that threshold. Thepercentage of SDA's with unemployment rates above 6.5 percentincreases steadily from 31 percent for metro SDA's to 53 percentfor metro dominant, 60 percent for nonmetro dominant, and 72percent for nonmetro SDA's. For the 4.5-percent threshold, thecorresponding percentages are 64 percent, 89 percent, 90 percent,and 93 percent. Since expenditure ratios do not appear related tothe third formula criterion (that is, the number of economicallydisadvantaged), incorporation of this threshold information wouldprobably explain a substantial part of the remaining variation inthe spending ratios, as shown in table 8.
17
the chance of receiving training as one living in a bottom-quartile SDA (with low expenditures per labor force member).
Table 9 shows that, overall, total expenditures per disadvantagedperson varied across SDA's by a factor of 14. Mean expenditures
per disadvantaged person in the highest expenditure quartile wasalmost three times the mean expenditures in the lowest quartile.
When differences in unemployment rates are controlled for, there
is a significant negative association between expenditures perdisadvantaged person and the number of disadvantaged personsliving in the SDA (table 9) .12 Since the number of disadvantagedis the third specific criterion used in the Title II-A allocationformula, it seems anomalous that its allocative effect appears to
be more than offset by the influence of unemployment rates, which
had a slight negative correlation with the absolute number of
disadvantaged.
There was also a weak negative association between theexpenditures per disadvantaged person and the percent of SDAfamilies with incomes below the poverty line. Unlike the number
of disadvantaged, however, the poverty rate had a relativelystrong positive association with both the expenditures per laborforce member and the unemployment rate.13 Since the poverty rate
is not a part of Title II-A's allocation formula, it is likely
that higher poverty rate SDA's tended to have higher expendituresper labor force member due solely to their higher unemploymentrates.
To test this interpretation more formally, I regressedexpenditures per labor force member against the unemployment rateand the poverty rate. The results strongly suggest that thepoverty rate provided no additional explanatory power beyond that
provided by the unemployment rate.14 In other words, the povertyrate, by itself, did not appear to directly influence patterns of
program expenditure. Higher expenditures per labor force member
12When expenditures per disadvantaged person were regressedagainst both the unemployment rate and the number of economicallydisadvantaged persons living within the SDA, the variable for the
number of economically disadvantaged had a negative t-ratio,which was significant at the 0.001 level. In contrast, the t-ratio for the unemployment rate variable was positive and alsosignificant at the 0.001 level.
13The Pearson correlation coefficients between the unemploymentrate and the poverty rate and between the unemployment rate andthe expenditures per member of the civilian labor force bothexceeded 0.5.
%When the expenditures per labor force member were regressedagainst the unemployment rate alone, the R-square value was 0.71.
It remained virtually the same when the poverty rate was included
as a second independent variable.
18
Tab
le 8
Unw
eigh
ted
mea
n un
empl
oym
ent r
ates
and
exp
endi
ture
per
dis
adva
ntag
ed p
erso
n by
quar
tiles
of
expe
nditu
re p
er m
embe
r of
the
civi
lian
labo
r fo
rce,
PY
87
Item
Uni
tT
op q
uart
ileSe
cond
qua
rtile
Thi
rd q
uart
ileB
otto
m q
uart
ile
Exp
endi
ture
per
mem
ber
of th
eci
vilia
n la
bor
forc
eD
olla
rs28
1611
6
Une
mpl
oym
ent r
ate
Perc
ent
10.5
7.3
5.7
4.3
Exp
endi
ture
per
dis
adva
ntag
ed p
erso
nD
olla
rs55
4536
27
Sour
ce: U
.S. D
epar
tmen
t of
Lab
or, O
ffic
e of
Str
ateg
ic P
lann
ing
and
Polic
y D
evel
opm
ent,
Div
isio
n of
Per
form
ance
Man
agem
ent a
nd E
valu
atio
n.
Tab
le 9
Unw
eigh
ted
mea
n ex
pend
iture
per
dis
adva
ntag
ed p
erso
n an
d un
wei
ghte
d m
ean
num
ber
ofdi
sadv
anta
ged
pers
ons
by q
uart
iles
of e
xpen
ditu
re p
er d
isad
vant
aged
per
son,
PY
87
Item
Uni
tT
op q
uart
ileSe
cond
qua
rtile
Thi
rd q
uart
ileB
otto
m q
uart
ile
Exp
endi
ture
per
dis
adva
ntag
ed p
erso
n
Num
ber
of d
isad
vant
aged
per
sons
Dol
lars
Num
ber
63
45,3
84
44
57,2
67
33
78,9
07
23
89,4
51
Sour
ce: U
.S. D
epar
tmen
t of
Lab
or, O
ffic
e of
Str
ateg
ic P
lann
ing
and
Polic
y D
evel
opm
ent.
r4
in areas with higher poverty rates probably occurred becausepoverty rates were positively associated with unemployment rates.
The positive interaction between poverty and unemployment rateswas not strong enough, however, to produce above-averageexpenditures per disadvantaged person in areas of higher povertyrates. In fact, as noted, there was a weak negative correlationbetween the poverty rate and the expenditures per disadvantagedperson. This outcome is likely attributable to the higher ratioof economically disadvantaged persons in areas with higherpoverty rates relative to the number in the labor force. Thishigher ratio more than offset the advantage created for higherpoverty areas by use of the unemployment rate in the allocationformula.
As for poverty in nonmetro areas (table 10), expenditure levelsin SDA's containing "persistent poverty counties" can be comparedwith those which have some nonmetro population but are notpersistent poverty areas. Persistent poverty counties constituteone category of the ERS Ross-Green typology of nonmetro countiesand are defined as those with average per capita incomes in thebottom quintile of all U.S. counties in 1950, 1959, 1969, and1979. These counties are located in 73 of the 343 metro dominant,nonmetro dominant, and nonmetro SDA's. These 73 SDA's had, in
turn, mean poverty rates 6 percentage points higher (15.6compared with 9.5) than the 270 metro dominant, nonmetrodominant, and nonmetro SDA's containing no persistent povertycounties. As shown in table 10, the persistent poverty SDA'sconform to the general patterns found above for the poorercounties in all SDA's: mean unemployment rates were 1.1percentage points higher, and expenditures per labor force memberwere 24 percent higher, but expenditures per economicallydisadvantaged person were 16 r "rcent lower.
Table 10Unemployment rates, average expenditure per disadvantaged person and per memberof the civilian labor force, in and out of "persistent poverty county" SDA's, PY87
SDA's containing one or more Metro dominant, nonmetroItem "persistent poverty counties" dominant, and nonmetro SDA's
containing no "persistent poverty county"
Unemployment rate
Percentage of families below thepoverty line
Expenditures per disadvantagedperson
Expenditure per member of thecivilian labor force
Percent
8.7
15.6
Dollars
38
7.6
9.5
45
21 17
Source: JTPA Annual Status Report Data, as compiled by the U.S. Department of Labor, Office of Strategic Planning and Policy Development.
20
t.)
1
A companion piece to this reports shows that metro SDA's tendto have higher unit costs per terminee. Unit cost per terminee ina given program year is defined as total Federal expendituresunder the Title II-A program divided by the number of programterminees. Higher unit costs might come from differences inparticipant characteristics (for example, a more or a less job-ready clientele), differences in cost levels (for instance, theneed to pay higher trainer salaries and rents), differences inoperating efficiency, or differences in the types of servicesprovided. Whatever the reasons, not only is a smaller absoluteamount spent per disadvantaged person in the typical metro SDA,but a dollar of expenditure does not go as far toward trainingthe average terminee.
In summary, then, the unemployment rate appears at present to bethe key factor in defining patterns of the expenditures permember of the civilian labor force and the expenditures perdisadvantaged person in the Title li-A program. This patternappears to particularly benefit the more rural SDA's because theytend to have higher than average unemployment rates and lowerthan average unit costs. Secondly, expenditures per disadvantagedperson vary widely across SDA's and are negatively associatedwith the number of disadvantaged. The wide variance inexpenditures per disadvantaged person means that disadvantagedpersons living in different SDA's face very different odds ofreceiving training. Finally, expenditures per disadvantagedperson are somewhat lower in higher poverty areas. This suggeststhat jurisdictions least able to afford training on their ownreceive a lower level of support per disadvantaged person.
Alternative Allocation Scenarios
The apparent negative correspondence between the expenditures pereconomically disadvantaged person and both the local poverty rateand the number of economically disadvantaged raises the questionof how funding allocation would be changed if funds weredistributed in a manner that more directly reflected thesemeasures of economic distress. And further, in what ways wouldsuch a reallocation affect the metro/nonmetro distribution ofprogram activity? To address these issues, two scenarios can bepropounded:
Scenario 1: Program funds are allocated to SDA's based on thenumber of economically disadvantaged in each SDA.
Scenario 2: Program funds are allocated to SDA's based on thenumber of economically disadvantaged weighted by the poverty ratein each SDA.
15See John M. Redman, Metro/Nonmetro Program Performance UnderTitle II-A, Job Training Partnership Act, AGES 9072, Econ. Res.Serv., U.S. Dept. Agr., Dec. 1990.
21
The criterion used in scenario 1 is the same as that currently
used by the Title II-A program in the third part of the existing
allocation formula, that is, the number of economicallydisadvantaged in the locality. The criterion used in scenario 2
will distinguish between SDA's that had, in 1980, similar numbers
of economically disadvantaged but different poverty rates. If two
SDA's have the same absolute number of disadvantaged, the SDA
with the higher poverty rate will be favored.
Because aggregate State poverty rates had not been calculated by
DoL, the computations of the results of these two scenarios were
performed in a manner very different from the existing Title II-A
allocation procedure. As discussed in the earlier overviewsection, the current funding plan employs a two-tier approach.
First, each State government receives an allocation from theFederal Government; the State then allocates funds to theindividual SDA's. For our two scenarios, we simply bypass the
State and allocate funds directly to the SDA, based on the SDA's
values for the applicable criteria. If a two-tier approach wasapplied to this exercise, the results might be very different.
There is no a priori way to estimate the magnitude of this
potential difference.
The procedure used here is conceptually similar, however, to the
"bottom up" approach to funding contained in both theadministration's and in Senator Simon's proposed amendments to
the JTPA legislation. Under that approach, funding allocations
are made to each SDA instead of to each State. The individual
SDA's share of the total funding is determined by comparing its
values on the allocation criteria (for instance, number ofeconomically disadvantaged) against those for all other SDA's. A
State's total funding becomes simply the sum of Title II-A funds
allocated to its individual SDA's.
Table 11 shows funding by region under each scenario expressed as
a percentage of PY87 Title II-A expenditure, as reported on the
JASR submissions. Under the first scenario (using the absolute
number of disadvantaged), New England and Ncei York/New Jersey
experience substantial increases in their allocations, while theindustrial Midwest (the East North Central region) experiences asharp decline. This result suggests that the Northeast has lowunemployment levels relative to the number of economicallydisadvantaged, while the Midwest tends to have high unemploymentrelative to the number of disadvantaged.
The results using the second scenario (weighting the number ofdisadvantaged by the poverty rate) are substantially different.
Here, the Southeast and West South Central regions join the NewYork/New Jersey area as major beneficiaries of the funding
change. This outcome suggests three things. First, the New
York/New Jersey area appears (based on 1980 data) to have bothrelatively large numbers of disadvantaged and relatively highpoverty rates, since its funding levels increase substantiallyunder either scenario. Second, the Southeast and West SouthCentral regions have very high poverty rates relative to their
share of economically disadvantaged. Including the poverty rate
22
Tab
le 1
1Fun
ding
allo
catio
n le
vels
und
er a
ltern
ativ
e al
loca
tion
scen
ario
s, P
Y87
Reg
ion/
SDA
type
Exi
stin
gal
loca
tion
Scen
ario
1Sc
enar
io 2
(cri
teri
on: n
umbe
r of
(cri
teri
on: n
umbe
r of
dis
adva
ntag
eddi
sadv
anta
ged
indi
vidu
als
wei
ghte
din
divi
dual
s)by
the
pove
rty
rate
)
Reg
ion:
----
Perc
ent-
---
Perc
ent o
f ex
istin
g al
loca
tion
New
Eng
land
100
142
107
New
Yor
k/N
ew J
erse
y10
012
814
2M
id-A
tlant
ic10
096
88So
uthe
ast
100
107
13::.
'
Eas
t Nor
th C
entr
al10
077
60W
est S
outh
Cen
tral
100
9412
1M
idw
est C
entr
al10
011
397
Mou
ntai
n/W
est N
orth
Cen
tral
100
105
87So
uthw
est
100
107
91N
orth
wes
t10
091
66
SDA
type
:M
etro
100
109
99M
etro
dom
inan
t10
095
97N
onm
etro
dom
inan
t10
089
108
Non
met
ro10
087
99
Sour
ce: J
TPA
Ann
ual S
tatu
s R
epor
t Dat
a, a
s co
mpi
led
by th
e U
.S. D
epar
tmen
t of
Lab
or, O
ffic
e of
Str
ateg
ic P
lann
ing
and
Polic
y D
evel
opm
ent.
S
BE
ST C
OPY
AV
AIL
AB
LE
.r.
in the formula makes a very big difference for each of theseregions. Third, New England benefits considerably from relianceon absolute numbers of disadvantaged but loses most of thisadvantage when the poverty rate is included.
At the other extreme, the Northwest joins the industrial Midwestas a big loser under the second scenario. This indicates thatthe industrial Midwest has not only relatively low numbers ofeconomically disadvantaged but relatively low poverty rates as
well. The Northwest shows this same pattern, though to asomewhat lesser extent than the Midwest.
Also measured was the differential metro/nonmetro effects ofthese two scenarios. The results are also presented in table 11.Under the first scenario (using the number of economicallydisadvantaged alone), metro SDA's experience a moderate increasein the total amount of program funds made available to them.This increase comes at the expense of the remaining three SDAcategories. The size of the decrease in these three othercategories increases as the category becomes more nonmetro.This outcome gives a broad indication of the benefit nonmetroareas receive from emphasis on the unemployment rate in theactual program formula. As these findings indicate, the effect ofthe unemployment rate more than offsets the effect of includingthe absolute number of disadvantaged as the third leg of theTitle II-A funding formula.
Under the second scenario (the number of disadvantaged weightedby the poverty rate), little change from the existing allocationoccurs, except that nonmetro dominant SDA's receive an increasedshare of funding. Here, the poverty rate appears largely tosubstitute for the unemployment rate in directing funding tononmetro areas well in excess of what is received using only theabsolute number of disadvantaged.
Nonmetro areas might be better served over the long term by aformula emphasizing the poverty rate rather than the unemploymentrate. In recent years, the metro/nonmetro difference inunemployment rates has been steadily declining and for the year1989 stood at just 0.5 percentage point. This reduction has notproduced a similar narrowing of poverty rates, however. In fact,the metro/nonmetro poverty rate differential, defined in terms of
the percentage of individuals living below the poverty line,increased from 3.5 percentage points to 4.4 percentage pointsbetween 1980 and 1987. Use of the poverty rate, then, may offernonmetro areas comparable but more stable funding advantagesrelative to those offered in recent years by the unemploymentrate.
Conclusions
The JTPA program is the main Federal effort to enhance theemployability of the economically disadvantaged. It is of centralimportance to the many areas with no other ongoing source of
24
employment and training funding and whose local revenue bases aretoo small to support sustained independent efforts.
For those who work in the field of rural development, theforegoing review suggests that, because of its reliance onunemployment rates, the current Title II-A allocation formulahas, up to this point, produced higher expenditures perdisadvantaged person in the more rural SDA's. This has been adirect result of the unusually high unemployment ratesexperienced by nonmetro areas in recent years.
This finding is not necessarily inconsistent with past studies16which argued that use of standard unemployment rates firallocating Federal funding discriminates against nonmetro areas.Such discrimination arises, it is contended, because standardunemployment rates fail to capture various dimensions of truelabor distress more prevalent in nonmetro areas (such asinvoluntary part-time employment, higher levels of discouragedworkers, or low and irregular income among farm proprietors).17Echoing this theme, a recent Joint Economic Committee report onemployment and training programs stated:
Allocation of Federal program funds reveals an urban bias.Despite the fact that nonmetro unemployment andunderemployment rates exceed metro measures by a third to ahalf, nonmetro areas receive only about 13 percent ofemployment and training funds. Federal procurement programsalso show a pronounced urban leaning. Another illustrationof implicit Federal discrimination is the funding formulafor the Job Training Partnership Act of 1982. Two-thirds ofthe funding was allocated according to unemployment figuresof little relevance to the rural employment picture.Because of under-reporting of unemployment and the way theformula was designed, rural areas were denied over $100
16For a discussion of this issue, see Sigurd R. Nilsen,Assessment of Employment and Unemployment Statistics forNonmetropolitan Areas, RDRR-18, Econ. Res. Serv., U.S. Dept.Agr., Dec. 1979. For a recent discussion of the use of andalternatives to standard unemployment rates see Richard J.Reeder, "Targeted State Aid to Distressed Rural Communities,"Publius, 19 (2), spring 1989, pp. 143-160.
VThe standard unemployment rate calculated and published by
the Bureau of Labor Statistics (BLS) is total unemployed as apercentage of the labor force, including the resident ArmedForces (U-5a). Alternative rates are also made available by BLSbut are not available at the county level. These alternativesinclude components which reflect additional dimensions of labordistress (such as the number of discouraged workers or thoseemployed part-time for economic reasons). The standardunemployment rate is thus only one of several measures which BLSitself has developed and one of the many others (for example, percapita income or the percentage change in unemployment) whichmight also be used in formula allocations.
254
'-ft 4
million in funding from 1983 through 1985, according to apreliminary analysis by the GenerDl Accounting Office."
From this perspective, the higher Title II-A expenditure levels
in nonmetro areas are still well below levels justified ifcongressional intent was to use the unemployment rate as a proxy
for overall labor distress. Within the context of the Title II-Aprogram, however, use of the simple unemployment rate held some
advantage for nonmetro areas compared with alternative criteriawhich might have been applied, such as the number of economicallydisadvantaged or the number of unemployed.
Practitioners should be aware, however, that the Title II-Aallocation formula is one focus of an ongoing congressionalreview of the JTPA legislation. This review has importantramifications for the future of rural employment and training
activity. Although it is still unclear if or how the formulamight be specifically modified, two major proposals have alreadybeen presented, one from the Bush administration and one from
Senator Simon of Illinois.
These proposals reflect considerable "second guessing" regardingthe use of unemployment rates as the dominant allocation
criterion.19 A major concern has been the lack ofcorrespondence between the incidence of unemployment and ofeconomic disadvantage--a lack of correspondence evident in thedata presented above. As a consequence, both proposals woule.greatly reduce the role of unemployment in setting allocations.Instead, both would emphasize the number and concentration ofeconomically disadvantaged within the SDA.
As discussed above, increased emphasis in the allocation formula
on the number of economically disadvantaged would tend to work in
favor of metro areas whereas emphasis on a poverty rate-basedmeasure could work to both the short- and longer-term advantageof the more nonmetro areas. The net effect of the formula change
on metro/nonmetro allocation will thus likely depend on thebalance struck between the number and the concentration of
economically disadvantaged.
"Dale Jahr, "The Rural Political Economy: Change andChallenge," U.S. Congress, Joint Economic Committee, Sept. 1988.
19See, for example, Abt Associates Inc., "An Assessment ofFunding Allocation Under the Job Training Partnership Act,"Contract No. J-9-M-5-0051, U.S. Dept. of Labor, Aug. 1986.
26A
U.S. Government Printing Office 1990 2g2-9,,g/2154:74/