The impact of including monetarily ineligible claimants for unemployment insurance in the LAUS estimating system

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ESO 60.2: I 56
IMPACT OF INCLUDING ]\10N}o;'l'l\IULY
INELIGIBLE CLAIMANTS FOR
UNEMPLOYf1ENT INSURANCE IN THE
LADS ESTIMATING SYSTEM
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THE IMPACT OF INCLUDING MONETARILY
INELIGIBLE CLAIMANTS FOR UNEMPLOYMENT
INSURANCE IN THE LAUS ESTIMATING SYSTEM
by
THE RESEARCH AND REPORTS SECTION
OF THE UNEMPLOYMENT INSURANCE ADMINISTRATION
ARIZONA DEPARTMENT OF ECONOMIC SECURITY
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PREFACE
The Bureau of Labor Statistios does not speoifioally inolude mone­tarily
ineligible olaimants for unemployment insuranoe in its LAUS (Looal
Area Unemployment Statistios) estimating system. For purposes of improv­ing
estimates of unemployment at the substate level, we obtained ohar­aoteristios
of unemployment insuranoe oZaimants from the Arizona UI data­base
and oonduoted a survey of monetariZy ineZigible olaimants with regards
to their labor foroe status. The 'l3u!'eau of Labor Statistios provided fund­ing
for the projeot. We found that the ohance of a olaimant being deter­mined
monetarily ineligible for UI benefits is affeoted by that person's
se:c, ethnio baokground, age, and othezo oharaoteristios. Unemployment rates
for monetarily ineligible otaimants after the date of their filing were oom­puted
from OUI' survey data. Methods of integrating those survey resuUs
into the LAUS estimating are e:r:ptored in this paper.
This report was written by M:!'. Robert Furgerson. Several other indi­viduals1Jithin
the Researohand Reports Seotion of the Unemployment In­surance
Administration of the Arizona lJepartment of Eoonomio Security oon­tributed
to the overall development of the report. Mr. Riohard Porterfield
initially supervised the study; his planning of projeot tasks had muoh to
do with its suooessful oompletion. The jobs of maintaining reoords of
survey responses, phoning members of the survey gzooup, and typing this
report were oarefuUy performed by Ms. Agnes Toombs, Ms. Rosemary Gutierrez,
Mr. Gilbert Mendoza, and Ms. Judith Vaughn. The ooding of the questionnaire
responses was aaaomptished by Ms. Karen Marsh. Mr. Joseph T. Sloane and
Dr. Robert St. Louis aarefuUy read a rough dZ'aft of this report and pro­vided
several. useful oomments. Dr. St. Louis also devised the sample design
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used.
Several individuals from other organizations also lended assistanoe to
this projeot. Mr. Vio Conti, Ulho works for the Labor Market Information
Seotion within the Arizona Department of Eoonomio Seourity, provided useful
teohnioal advioe and data. Valuable assistanoe was also given by Anne
Christy and'Ed Gray, who are oomputer programmers for the Offioe of Data
Administration of the APizona Department of Eoonomio Seourity. Ms. Sharon
Broum of the B.L.S. National Offioe and Ms. Mitzie Slater of the B.L.S.
San Franoisoo Regional Office made several oonstruotive suggestions regard­ing
the oontent of this report. Ms. Slater, who aoted as the Government
Authorized Representative, deserves a speoial thanks for her help in the
administration of this oontraot.
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IX. SUMMARY AND mNCLUSIONS • • • • • •. • • • • •
II. CCMPARISON BEIWEEN M)NEI'ARILY ELIGIBLE
AND M)NEl'ARILY INELIGIBLE CLAIMANI'S •
VIII. IMPACl' ON THE. ESTIMATE OF NEW· ENrnANI'S AND
REENTRANI'S TO THE LABOR FORCE • • • • • •
VII. INrEGRATION OF RESULTS INro THE LADS
ESTIMATmG SYSTEM • • • • • • • • • •
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PAGE
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PREFACE •••
I. INrRODUCTION
V. DESIGN OF THE SURVEY. •
IV. RATE OF INELIGIBILITY •
TABLE OF mNI'ENTS
VI. RESULTS OF THE SURVEY •
III. REASONS FOR M)NEI'ARY lliELIGIBILITY
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Appendix 1 - Statistical Tables • . . .
Appendix 2 - The Survey Questionnaire
Appendix 3 - COlIDties and Planning Districts
m.1srizona • • . • • . . • . .
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OO'RODUcrION
Currently, persons declared rronetarily ineligible for Unerrployment
Insurance benefits are. not specifically included in the LAUS estimating
system. Failure to take rronetarily ineligible claimants into account
will produce biased est:i.roates of unanployment at the substate level
unless either of the following conditions is met:
(1) '!he number of rronetarily ineligible claimants is an insignif­icant
proportion of the labor force, or
(2) lv10netarily ineligible claimants are distributed evenly
throughout the state, ani the labor force experience of those
claimants does not vary significantly from area to area
during the weeks following the ineligible claim.
In Arizona, the first condition is not satisfied. For calendar
year 1979, 12,210 people filed· for Unanployment Insurance benefits in
Arizona and were det.e:anined to be m::>netarily ineligible (63,320 filed
ncnetarily eligible claims.). A contract with the Bureau of Labor
Statistics enabled us to study a group of nonetarily ineligible claimants
to see if the second condition is met. Characteristics of persons
filing. for or benefits in Arizona in 1979 were obtained fran the or
data base. A semple of those persons deteonined to. be ineligible due
to rronetary reasons was sent a mail questionnaire in order to ascertain
their labor force status during the 26-week period imnedi.ately follCMing
the filing of their claim.
(V)
(VI)
(VII)
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We found that the incidence of nonetary ineligibility differs
anong Arizona counties.. The labor force experiences of the survey
respondents also vary anong substate areas. In general, persons
living in urban areas are likely to return to work or establish an
eligible UI claim sooner than are persons residing in rural areas.
Therefore, the second condition also is rY:>t met, and the IAIJS estimating
systen may be improved by the specific inclusion of nonetarily inelig­ible
claimants.
The renainder of this paper is organized into eight sections:
(II): canparison of the characteristics of nonetarily eligible
and m:>netarily ineligible claimants a
(III) Analysis of the· reasons for m:>netary ineligibility in
tenns of personal characteristics.
(IV) Examination of the rate of ineligibility anong various
Arizona cx:>unties.
Description of the design of the survey.
Results. of the survey.
Pror;x:sed methods of utilizing the survey results in the
!AUS estinlating. system.
(VIII) Impa.ct: on. the estimate of new: entrants and reentrants
to the labor force.
(IX) Stmna.z:y ar:d conclusions.
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II. <D1PARISON BElWEEN K>NETARILY ELIGIBlE AND MJNErARILY INELIGIBLE cr.AIMANI'S
An individual filing for UI benefits in Arizona ean be declared
to be IIDnetarily ineligible for benefits for any of the follcwing
reasons:
(1) Failure to earn a certain mi.n.imum arrount of IIDney while
eFJ3'aged in covered errployrnent during the "high quarter" J
which is the quarter in a person's "base periodII· with the
highest covered earnings. A "base period" is the first four
of the last five quarters a:::mpleted before a person's
application for benefits. '!he m:i..niIrn.Jm was $375 until
August, 1979, at which t:iIne it was raised to $625. In
August, 1980, the minimum was raised to $725.
(2) Having base period earnings which are less than one-and-one­half
times those of the high quarter.
(3) Trying. to establish a new benefit year within eighteen IIDnths
of the prior benefit year beginning date without having earned
since that date at least eight t:iInes the weekly benefit arrount
to which the clai:mant would be entitied.
Table I, Appendix 1. shows that 63,320 people filed for UI benefits
in 1979, and were determined. to be rronetarily eligible for benefits.
'!bose declared ineligible numbered. 12,210, or 16.2 percent of the total
number of applicants. Monetarily ineligible claimants are typically
just IIDving into the labor force (new entrants and reentrants) have
difficulty staying attached to it (marginal. workers), or work in non­covered
srployment..
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A slightly larger percentage of female claimants were rronetarily
ineligible than were male claimants: 17.6 percent of females as corn-pared
to 15.3 percent of males. This is accounted for by the relatively
higher unemployment that females have had (which indicates a less stable
work history), and their increasing rate of entry into the labor force.
Adult female participation in the labor force went fran 49.3 percent
in 1978 to 50.6 percent in 1979.*
The data shows that the very young and the elderly were rrore likely
than persons in other age groups to be rronetarily ineligible. 34.0 per-cent
of the claimants under the age of 20 and 20.5 percent of claimants
in the 20-21 age group were ineligible. People in th:>se age groups are
just rroving into the labor force and are still acquiring needed job
skills. The percentage of ineligibles in the 22-24 years category was
about the sane as the average, while in the age groups from 25-64, there
were below-average rates of rronetary ineligibility, 29.8 percent of
person$ 65 years and over failed to meet the rronetary eligibility
criterion.
Examination of. the effect of ethnic background indicated that white
claimants had a below-average incidence of rronetary ineligibility: 15.1
percent as carpared to 16.2 percent for the total group. Hispanics and
Indians had rates of 17.4 and 19.1 percent , respectively, while blacks
had the highest rate of nonetary ineligibility (21.9 percent) of any
of the ethnic groups.. The difference between the Asians I incidence of
nonetary ineligibility and the total group I S rate was not statistically
significant at the five percent level.
*Monthly Labor Review, u.s. Dept. of Labor, December, 1979, page 68.
Figures used are for woman twenty years of age and above.
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Am::>ng occupations, the "professional/technical/managerial" group
had the lowest rate of rronetary ineligibility - 13.1 percent. This
is probably due to the above average wages and the relatively stable
employment enjoyed by those workers. The fanning/fishing/forestry class­ification
had the highest incidence of rronetary ineligibility at 27.0
percent. This can be explained by the relatively low wages of these
occupational groups, and the fact that many agricultural workers are
still not covered by the UI system.
A sizab~e -percent of workers with no infonnation available on indus­trial
attachrrent were determined to be rronetarily ineligible - 36.9
percent. This result is not surprising given that often no infonnation
is available on industrial attac:hment because an employee had no base
period employer, and hence no base period wages. The industry with the
greatest percentage of rconetary ineligibles was the services industry
(with 15.8 percent). This can be ascribed to that industry's lower than
average wages, the non-coverage of many of its workers, and the fact
that a sizable part of scme service workers' wages carte in the fo:r:m of
ti ps,. which are not covered by the. UI systan.
A canparison of the claimants t high quarter and base period earnings
showed the expected. pattern of the group not rronetarily eligible for
benefits having much lower earnings than the group that met the rronetary
eligibility requirements. For ~le, 86.2 percent of the claimants
with high quarter earnings ofi less than $700 were in the ineligible
group, while onlyJ.6 percent of those with high quarter earnings of
at least $5,000 failed to meet the rronetary eligibility criteria. The
two base-period· wage distributions showed. a similar pattern. People
with annual earnings of less than $2,000 had an ineligibility rate of
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77.8 percent, while only 1.2 percent of those with annual earnings of
at least $5,000 failed to meet rronetary eligibility. All of the base
period wage categories in the range fran $0 to $2,999 showed substantially
rrore rronetary ineligibles than the overall percentage (16.2 percent) 1
an::l all of the categories above $3,000 shcMed substantially fewer. Obviously1
the group not eligible for benefits is daninated by persons with extremely
low earnings 1 consistent with the unemployrrent insurance principle of
replacing lost earnings only for those who have derronstrated a strong
labor force attaclurent.
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OVer one-fourth of these claimants had not received any wages fran
covered enployment during· the entire one-year base·· period, and an addi­tional
17.2 percent had earned less than $625 (less than $375 before August,
1979) during their high quarters.. The largest group, however, consisted
of those who had sufficient high quarter earnings but failed to earn at
least half as much as those earnings during the. renaining three quarters
of their base period. This group accotmted for 55.5 percent of those
declared ineligible.
REASONS FOR MJNEr.ARY INELIGIBILITY
This section is devoted to a fairly detailed explanation of the
reasons for rronetary ineligibility for the group that failed to meet
Arizona's rronetazy requirements for benefit eligibility. As was just
noted, this group is daninated by persons with extremely low earnings.
As previously stated, reasons for rronetary ineligibility include in­sufficient
high quarter earnings (including no wages reported for the
entire base fariod) , a base-period-to-high-quarter-earnings ratio that
is too leM, and failure to meet the requiranents for requalifying wages.
The distribution of the total group (which was obtained by using a
weighted sample); is sumnarized in_the table below:
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III.
Reason for Monetary Ineligibility
No Base Period Wages
Insufficient High Quarter Earnings
Base period/High. Quarter Ratio Too I1:::Jt.N
Insufficient Requalifying Wages
Percent
27.2%
17.0%
55.5%
0.4%
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Men differed sanewhat fran \<\Onen in teIIns of their reasons for zrone­taJ:
y ineligibility. A.larger percentage of the nen had. no base period
earnings (28.6 vs.. 24.9 percent) or ~e ineligible due to their base period
earnings being less than one-and-one-half times their high quarter wages
(56:5 J?Ell"CSI1t as c::x:npared. to 53.9 percent). 20.8 percent of the w:::men were
ineligible due to insufficient high quarter earnings, while relatively fewer
miiell were ineligible due to that· reason - 14.4 percent. The numbers of
persons declared ineligible because of failure to earn sufficient requalify­in;'
wages were approximately equal between the two sexes.
Only O. 4 percent of the imeligible claimants were dete.triri.ned inelig­ible
due to insufficient requalifying wages. It is interesting to canpare
that result to fiscal year 1976 data, ltbich showed 16.7 percent of all
ineligible claimants during that period being ruled ineligible due to
insufficient requalifying wages, That workers in fiscal year 1976 were
apparently:crore subject to periods of prolonged unemployment than workers
in calendar year 1979 is not surprising. The country was just caning out
of a recession in 1976, with the econanic expansion continuing through :crost
of 1979.
The distribution of men and w:men by reasons for :cronetaJ:y ineligibil­ity
reveals sate interesting differences between the two groups, as shown
in the sumnaJ:y table below:
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Reason for Moneta;Y Ineligibility
No Base PeriOd Wages
Insufficient High Quarter Earnings
Base Period!Hi.ghQuarter Ratio Too Ii:M
Insufficient Requalifyin1 Wages
!-1a.le
Percentage
28:'6%
14.4%
56.5%
0.5%
Fema.le
Percentage
24.9%
20.8%
53.9%
0.3%
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In the remainder of this section, these reasons for rronetary
ineligibility in canparison to various other claimant characteristics
are discussed, In each case, the erphasis is on rrarked departures fran
arrj particular characteristic, relative to the distribution recorded for
the total sample.
Occupational category. As shown a!:x:>ve, a total of 44.2 percent of
those ineligible for benefits had no base period earnings or insufficient
high quarter earnings. The occupational category (see Appendix 1, Table
2) with the greatest percentage of its members ruled ineligible due to
this reason was the service group (51. 7%), followed by the fanning/fishing/
forestry category (51.0%). The high incidence of insufficient earnings
in these cases may be explained partly by employrrent in noncovered estab­lishments,
the generally low wage levels in these industries, and for the
service occupations, the fact that a large part of many workers' income
is received through tips, which are usually not covered by the UI system.
A surprising result was ~t an above average percentage of profes­sional/
technical/managerial workers were ineligible due to low or no
earnings (48.00).... Lcx:>kin::r nore closely at these workers,we fim. that only
7.1 percent (as c:x::m-pa.red to an average of 17.0 percent) had insufficient
high quarter earnings. In contrast,. 35.6. percent of them had no base period
earnings, which was nore than the average (27.2 percent) and also the highest
of all the occupational groups. This may be due to a high number of these
workers being self-employed durirJJ their base period.
For the total group, 55.5 percent failed to meet rronetary eligibility
requi.re:nents because. the base period/high quarter earnings ratio was too
low. Three occupations had a considerably larger proportion of their mem­bers
failing to qualify for this reason: processing (64.9%), benchwork
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(62.3%), and structural work (59-.0%). That pattern is due, in part,
to the seasonal nature of construction work and sane of the processing
and benchwork occupations (e.g., food and wood product processing) .
Industrial Attachment. For the total group, 27.2 percent were in­eligible
for benefits because of no base period wages. A higher per­centage
(86.7%) of those in the information not available catego:ry failed
to meet eligibility requirerrents because of no earnings (see Appendix 1,
Table 3); those with no earnings in the base period are in the nonclas­sifiabla
catego:ry because they had no covered base period employnent.
33.6 percent of the ineligibles frcm the wholesale and retail indus­tries
were ineligible due to insufficient high-quarter earnings, while
29.8 percent of those in the service industry were ineligible for the
same reason. A contributing factor is the lower than average wage level
of these industries. Another possible cause is·. the high number of young
people in these industries - 25. 7 percent of the ineligibles under 20
were. in the wholesale or retail industry, while 15.2 percent were in
the services industry. These workers are j1.J$t ~~ing the la1::x:>r force
and thus find it difficult to secure high-paying employnent.
Overall, 55.5 percent of the ineligibles were dete:r:mi.ned to be in­eligible
because of their base-period....to-high-quarter-earnings ratio.
However,. if those with no infonnation available on industrial classifi­cation
are not considered, then the industry average of being ineligible
for that reason is 75.2 percent. Taking that figure into account, the
wholesale/retail industry had a below average percentage (65.6) of work­ers
ineligible dtE to their base-period-to-high-quarter-earnings ratio;
the transportation/carrm.mi.cation/utilities catego:ry had the highest
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(87.3) of its workers ineligible because of that. Apparently,
ineligibility due to a low base-period-to-high-quarter-earnings ratio
is rrore likely in the higher paying industries.
~. The distributions of reasons for ineligibility by age for the
total sample and separately for males and females are provided in Tables
4, 5 and 6 , respectively, of Appendix 1. Al:x>ut 44.2 percent of the total
group of ineligibles had either no base period earnings or insufficient
earnings; for workers under 20 years of age, however, the canparable
percentage was much higher, as ~uld be expected. 53.2 percent of male
workers less than 20 years old and 54.6 percent of female workers in that
age group failed to meet the mi.nimum earnings require:m:mt. The over 65
age group also showed high numbers of vvorkers ineligible due to no or
low earnings: 61.3 percent of the males and 53.6 percent of the females.
Overall, 55.5 percent of the total group was denied benefits because
the requirerren.t that base period earnings be at least one-and-one-half
tines high quarter earnings was not rret. The 35-44 age group had the
highest relative number of ineligibles disqualified for this reason
(61. 3 percent). This figure is broken down by sex into 61. 2 percent
for males. and 60.2· percent for females.
Etlmic.. The distribution by reason for ineligibility are quite
similar for each of the ethnic groups with the exception of Indians
(see Appendix I, Table 7). 35.7 percent of them had no base period
earnings, while this was true for only 27.2 percent of the total group.
This can be explained by the fact that errployers on Indian reservations
are not required to pay into the unemploym:mt. insurance system.
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IV. RATE OF INELIGIBILITY BY COUNl'Y
An llnportant question with respect to LAUS estimating procedures is
whether or not rronetarily ineligible clairnants are distributed equally
throughout the state. In order to rreasure their distribution, tv.o types
of ratios were canputed: the number of m:metary ineligibles in a county
divided by that county's laror force, and the percentage of n€M initial
claims filed by a county's residents classified as rronetarily ineligible.
These ratios can be seen in the table below:
Number of Civilian Ratio of M:metarily Percentage of N€M
Monetarily Labor Ineligible CJ 3..i.ms Initial Claims
Ineligible Force To Number in Labor Detennined to be
County Claims in 1979* Force Monetarily Ineligible
Apache 343 14,203 .024 20.5%
Cochise 711 25,072 .028 26.6%
Coconino 465 30,013 .015 18.6%
Gila 369 12,835 .029 26.6%
Graham 229 6,603 .035 24.6%
Greenlee 64 3,957 .016 33.0\
Maricopa 5.,215 631,160 .008 13.4%
Mohave 325 17,357 .019 20.7%
Navajo 473 21,965 .022 21. 7%
Pima 1,879 184,159 .010 15.1%
Pinal 791 26,064 .030 25.2%
Santa Cruz 201 7,349 .027 21.7%
Yavapai 319 24,075 .013 16.3%
Yuma 713 30,680 .023 17.9%
I.N.A. 113 20.5%
Total 12,210 1,080,094 .011 16.2%
*These are June, 1979 figures taken fran Arizona Labor Market N€Msletter, Arizona
Depa.rtn'ent of Econanic Security, July, 1979, page 14.
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Maricopa had the rrost m:metarily ineligible claims of any.county;
however, if the number of persons in each county's labor force is taken
into account, it had relatively fewer ineligibles than the other counties
(see preceding table). Pima County had a similar ratio of ineligible
claims to labor force size. All of the rural counties had proportionately
more rronetarily ineligible claims than did Maricopa or Pima, with the
ratio for Graham County being more than four tiIres that of Maricopa.
If the number of rronetarily ineligible claimants in canparison
to all new initial claims is fairly constant across the substate areas,
then they could be estimated from the total number of claims. Obviously,
however, this ratio varies widely anong the counties (see preceding
table). Maricopa County had the lowest percentage (13.4) of claims
being declared rronetarily ineligible, while Pima County had the second
lowest (15.1). The percentage of ineligible claims in Greenlee County,
33.0, was nore than twice the percentage for ~ urban counties. Clearly,
ib1etarily ineligib.1e claimants are not distributed evenly throughout
the state, either as a percentage of a county's labor force or as a
percentage of its total claims.
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v. DESIGN OF THE SURVEY
A major part of the Arizona LADS contract was the survey of rrone­tary
ineligibles in regard to their labor force status after filing
for UI benefits. In order to reduce costs, yet still obtain a reliable
estimate of the rronetary ineligibles' survival rate, a random sampling
scherre was devised. Stratification was done by county since reliable
estimates are desired for the survival rate by county.
The sample percentage used for each county was detennined by can­puting
the sampling size required to estimate 6-nonth survival rates
within a .85% absolute error. An expected response rate of 78% was used.
Based on these assumptions, the rrost fXJpulous counties 7 Maricopa and
Pima, had sampling percentages of 32% and 66%, respectively. Cochise
and Pinal counties had sampling percentages of 98 percent and 99 percent,
respectively. For the rest of the counties, the entire fXJpulation was
surveyed.
The existence or nonexistence of sampling bias is critical when­ever
a survey uses sampling.. To test for sampling bias in the TAUS
survey, characteristics of the sample. in a particular oounty were can­pared
with those of the oounty's population. ~led T-tests were
used to c::x:>npute statistical significance of any differences. The results
for Maricopa and Pima oounties, which had the lowest sampling percentage,
are givan in Appendix I as Tables 8 and 9. As can be seen in the tables?
none of the differences between the sample and fXJpulation characteristics
give rise to a T-value that ~uld generally be considered significant.
It can therefore be ooncluded that sample bias is not a problan for the
study.
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Persons selected for the survey were mailed a questiormaire (see
Appendix 2) along with an accorrpanying cover .letter which explained
the purpose of the project. The front page of the questiormaire asked
when was the last day ~rked before caning in to file for Une:rployment
Insurance benefits, and if they had looked for work during the four weeks
preceding the effective date of the claim. The back page asked, for
each week in a l3-week period beginning when the rronetarily ineligible
claimant filed for benefits, questions regarding that person's labor
force status.
If a selectee for the survey did not respond within ten days after
the initial :mailout, then a reminder postcard was sent. We atte:rpted
to contact by phone those who still had not responded, and for whom we
had a phone number. Four atte:rpts at phone contact were made for each
such person - one rcoming (7:00 a.m. to 11:00 a.m.) weekday call, an
early-afternoon (11:00 a.m. - 3:30 p.m.) weekday call, a late afternoon
(3:30 p.m. - 6:00 p.m.) weekday call, and a calIon Saturday. A cer--'­tified
letter was mailed to those people for whctn contact had yet to
be made. If there was no response after all of these attertpts at contact
had been made, then a· person was classified as a non-respondent.
Survey respondents who had not established an eligible claim within
the· thirteen weeks after their initial ineligi:ble claim were mailed an
additional survey questionnaire. This second questionnaire was similar
to the· first, except that its questions pertained to the thirteen-week
period starting with the fourteenth week after the person's initial claim.
The same follow-up procedures were used.
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VI. RESULTS OF THE SURVEY
Only 21. 3 percent of the claimants selected for the survey responded
to the initial rnailout of the first thirteen-week questionnaire. This
is not st:lJ:"Prising because we would expect the survey group to be antag­onistic
towards our agency, given that they were denied UI benefits.
Clearly, other nethods of contact were necessary in order to get an ade-quate
rate of response. The rrost frequent nethod of contact was by tele­phone,
as can be seen in the table below:
Method of 1st 13-week Questionnaire 2nd 13-week Questionnaire
Contact* Number Percentage Number Percentage
Initial Mailout 1,618 21.3 1,087 27.0
Postcard 660 8.7 455 11.3
certified Letter 589 7.8 182 4.5
Phone 1,848 24.3 1,320 32.8
Never Contacted 2,877 37.9 982 24.4
'rorAL 7,592 100.0 4,026 100.0
The first question of the survey was "our records indicate that
you filed for Unemployment Insurance Benefits during the week of (effective
date of claim). Before (effective date· of claim) when was the last day
you 'worked for pay or profit?' If you cannot reme:nber exactly what day
you last worked, please give us your best guess". It was answered by 4,610
persons . our· coders put the. answers into six categories: never worked,
less than two weeks,. two and up to four weeks, four and up to thirteen
weeks, thirteen and up to twenty-six weeks, and twenty-six weeks or rrore.
The results, broken down by age groups, are shown in Appendix 1, Table 10.
*Not all persons contacted provided a full response. Data on the number
of people partially responding is presented later in the report.
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A surprising result was that very few people (6) indicated that they had
never worked. An obvious pattern am:mg the age groups was that older indi­viduals
experienced, on the average, a longer period of time between their
last job and filing for UI benefits.
The next question asked was " ..•did you' look for work' at any time
during the four weeks before (effective date of claim)?" OUt of 4,653
people answering that question, 3,474 responded "yes" while 1,179 answered
"no".
The second page of the questionnaire had two sections for each week
of the survey period starting with the week in which the rronetarily ineli­SJible
cl2rimants filed. Survey respOndents were asked to check one of the
boxes in each of the sections. section 1 asked if the person had worked
either 1-34 hours or hours in excess of that; or did not VJOrk because of
an absence due to illness or vacation, had no job, had a job to start within
30 days, or was on layoff for less than 30 days. Several people indicated
that they had been on strike, or that they had rroved out of state. We
therefore decided to put. those categories on our coding sheets. The second
section asked whether the respondent had looked for work in a particular
week, or did not look for work because he already had a job that satisfied
his needs, was terrp:>rarily ill, or for other reasons.
A tabulation of responses to this part of the questionnaire is presented
in Appendix 1 as Tables 11 and 12. It should be mentioned that it was
often the case that a survey respondent would write in answers for only
a few of the weeks, or would check off boxes in only one section. We attempted
to contact again those people who gave partial responses in order to get
their questionnaire completely filled out. The seriousness of a partial
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-18-
response varied, depending on how the person responded. If that respondent
indicated having a job in a particular week, and did not check a box in
the section asking about looking for work, then we still had enough information
to determine his or her labor force status. In fact, for sw::veys done
over the phone, a person who said that he or she had a job for the relevant
time period was not asked about looking for work, as the information was
not necessary. However, we were unable to detenni.ne the labor force status
of an individual who indicated having no job and gave no information about
looking for work.
From these raw answers a person's labor force status can be canputed.
Individuals indicating that they worked 1-34 hours, worked 35 hours or
rrore, were absent from work due to illness or vacation, or were on strike
during a particular week, were classified as anployed for that week. Those
who checked the "Accepted a job to start within 30 days" or "On layoff
for less than 30 days t' boxes were put into the '-'unemployed'.l category ~ A
person indicating that he or she did not have a job, but looked for work
during that particular week was classified as unanployed. A person who
bad no job and was not currently looking for work, but had looked for work
during the previous four weeks, would be classified as unemployed according
to the C.P.S. definition,. and out-of-the-labor force according to the Dr
definition*. An individual with no job who was not currently looking for
work and had not looked for work at any time during the previous four weeks
would be classified as out of the labor force by both the C. P.S. and UI
definitions.
we calculated ~ labor force status for each sw::vey respondent for
whan we had sufficient infonnation with both C.P.S. and fII definitions.
*Ui does not explicitly classify individuals this way. Claimants are
classified as either ineligible, eligible unemployed, or eligible anployed.
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-19-
The results for each survey week, broken down by sex, are presented in
Appendix 1 as Tables 13-18. The greatest difference between the sexes
was that females were rrore likely to drop out of the labor force. With
the C.P.S. definitions of labor force categories, 14.3 percent of the
fanales were out of the labor force at the end of the survey, compared
to only 8.9 percent of the males. The figures for fanales and males using
the UI definitions are 15. 7 percent and 9.5 percent , respectively. This
result is not surprising since relatively fewer waren than men participate
in the U. S. labor force.
Survival. An :i.rrp:>rtant concept used in the LADS estimating system
is that of survival. FOI: our study, a person who is unemployed (C.P.S.
definition) and rronetarily ineligible for UI benefits is considered to
be a "survivor". Becani.ng employed, dropping out of the labor force, or
establishing rronetary eligibility for UI benefits would all cause a person
to be reroved fran the survival group. we define the"survival raten as
the number of persons fran a group surviving in a tinE period divided by
the number of group rranbers wOO were survivors in a preceding time period.
Tables 19 through 22 in Appendix 1 show the proportion of survey respon­dents
surviving in each survey week,. broken down by sex, ethnic group planning
district (groups of supposedly similiar counties used for planning purposes) ,
and. county, respectively. The proportions shown in Tables 19 through 21
are weighted by county to reflect the stratified randan sampling scheme
that we used.
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-20-
Weekly survival rates can be ccmputed fran these tables by taking
the proPJrtion of survivors in the desired week, and dividing that number
by the proPJrtion of survivors in the preceding week. The number of people
for wmn we were able to deteJ::mi.ne survival status varied from week to
week; values for the first and final weeks are presented at the bottan
of those tables (19-22). People who reSt:Onded to the first survey but
were not mailed a second survey due to the establishment of a rronetarily
eligible claim are included in those figures even for weeks 14-26. They
were classified as ~'non-survivors'·' beginning with the week in which they
were rronetarily eligible for benefits.
Surprisingly, the survival rate of males as a group was similar to
that for females. LTl the final survey week, the percentage of males still
surviving was the Satre as that for females - 22.8 percent.
OUr data showed that members of minority groups had higher survival
rates than did whites. 28.6 percent of the blacks, 26.6 percent of the
Hispanics, and 28.9 percent of the Indians were survivors at the end of
the survey period; only 20.5 percent of the whites were still surviving
at that time•. These figures were used in b.o-tailed T-tests in. order to
see if the differences in proPJrtions. of survivors between whites and minority
groups· were statistically significant. The differences in proPJrtions
for Hispanics, blacks, and Indians were each found to be different fran
whites at the 1% level of significance. Differences anong blacks, Hispanics,
and Indians were not statistically significant. Survival figures for survey
resPJndents classified as Asians or of unknown ethnic background are also
presented in Table 20, but there was no statistically significant difference
between these and other ethnic groups. However, this may be due to there
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-21-
being so few people in those two classifications.
Survival status by planning district can be seen in Appendix 1,
Table 21. Appendix 3 is a map depicting the counties and planning dis­tricts
of Arizona. The urban area planning districts 1 and 2 had lower
survival rates than the other planning districts. However, two-tailed
T-tests showed. that only District 5 and District 6 were different from
each urban district at the 1 percent level of significance.
Table 22 of Appendix 1 shows survival rates by county. One of the
smaller counties in the statel Graham, had the lowest proportion of survivors
(15.9 percent) at the conclusion of the survey. The urban counties, Mari­copa
and Plina, had the second and third lowest survival rates, respectively.
Greenlee County, the county with the highest average annual wage in the
state, had the highest proportion of survivors (37.0 percent) in the final
survey week.
The reliability of these estlinates is of great interest. In order
to evaluate this, an estlinated standard error of proportion (O"p) was
calculated for each county's percentage of survivors at· the survey end.
A confidence coefficient of 95% was selected, so the estimated standard
errors were multiplied by 1.'96 in order to compute confidence intervals.
The last column in the table on the following page shows 95% confidence
limits for each of the counties.
At the time the survey was originally designed, required sample sizes
were calculated so as to achieve a .85% absolute or 17% relative error
(the absolute error divided by the point estimate). The desired standard
for the absolute error was not achieved for any of the counties (see column
2 of the following table). Sample sizes were insufficient (due to a lower
-22-
had a much different survival rate than the other counties (Cochise,
Greenlee, and Santa Cruz) within its planning district (number 6). The
criterion for relative error, even though none did in tenns of absolute
6.4 21.1 24.0 36.8
3.4 10.2 29.8 36.6
5.3 22.9 17.8 28.4
5.5 22.0 19.5 30.5
6.0 37.7 9.9 21.9
13.8 37.3 23.2 50.8
2.7 13.4 17.5 22.9
4.9 22.5 16.9 26.7
4.7 18.9 20.2 29.6
2.8 13.4 18.1 23.7
3.6 12.5 25.1 32.3
5.3 22.6 18.1 28.7
4.9 22.5 16.9 26.7
3.7 15.0 21.0 28.4
Upper Bound Upper Bound .
on Absolute on Relative IDwer 95% Upper 95%
Error (95% Error (95% Confidence Confidence
Confidence) Confidence) Limit Limit
30.4
33.2
23.1
25.0
15.9
37.0
20.2
21.8
24.9
20.9'
28.7
23.4
21.8
24.7
Percent of
Resp:::>ndents
Surviving in
Final Survey Week
An interesting result fran these calculations is that Graham County
rronetary ineligibles, Planning District 6 is a poor grouping of counties.
Apache
Cochise
Coconino
Gila
Graham
Greenlee
Maricopa
Mohave
Navajo
Pima
Pinal
SantaCruz
Yavapai
Yuna
confidence interval was 29.8-36.6%; it is highly unlikely that these two
County
error.
samples came fram the same p:::>pulation. At least for purp:::>ses of surviving
confidence interval for Graham County was 9.9-21.9%, while Cochise County I s
percentage actually survived, so that results in some counties met our
would still be surviving at the end of the 26-week period; a much larger
during the survey design period assumed that only 5% of the survey resp:::>ndents
Pinal County had only a 17.1 percent relative error. calculations made
of the counties did have a lower than 17 percent relative error, while
survey resp:::>ndents were survivcrs at the end of the survey period. Three
than necessary resp:mse rate) and a higher than expected prop:::>rtion of
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-23-
would be the average number of weeks the person was a survivor. Those
rrea,ns, and their standard errors, can be seen in the following table.
Another measure of survival for rronetary ineligibles within a county
56
445
308
349
343
308
648
728
455
665
209
181
7,592
1,190
1,707
Number*
Sampled
311
80
338
23
265
514
688
110
141
125
105
133
131
166
3,130
Number
of Full
Respondents
0.591
0.356
0.747
0.413
0.571
0.404
0.656
0.547
0.727
0.713
0.314
0.581
0.538
0.119
0.293
Standard Error
(With Finite
COrrection
Factor)
9.514
9.826
12.962
12.736
10.872
10.868
11.531
11.152
10.135
12.102
12.652
11.887
10.191
10.843
10.162
Mean
Number
of Weeks
Surviving
Pima
Gila
COchise
Apache
County
*Ineligib1es for wban infonnation on. county of residence was not initially
available and who were selected for the sample, were later classified by
county as rrore infonnation becane avai1aP1e.Therefore, it is p::>ssib1e
that nore people were sampled in a county than the number of ineligibles
in a county listed on Page 12, since the· latter figures are based on
initial canputer runs.
Yavapai
Yuma
Santa Cruz
COconino
Pinal
Greenlee
Graham
Navajo
Statewide
Mariocpa
~have
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These figures include the total number of weeks that a resp:::mdent
was a survivor; they are not necessarily continuous spells. It was
often the case that a rronetary ineligible dropped out of the survival
group and then went back into it. Approximately 1,300 of our survey
respondents changed their survival status rrore than once; therefore,
means for continuous spells of survival w::>uld be much lower than these
figures. Only individuals for whcrn we couJ,d detennine survival status
in each of the twenty-six survey weeks (3,130) were included. The rank­ings
arrong counties are roughly similar to those obtained from the pro­portions
of survivors in the final survey week. Exact relative rankings
axe not important , given the size of the standard errors.
Response Bias. An important aspect of any survey is response bias.
For purposes of testing for response bias, we divided the persons selected
for the survey into three response types - full, partial, or none. These
categories, crosstabulated by sex, look like this:
Respqnse Type SEX
Male Female Total
Full: Number 1673 1458 3130
Percent 36.7% 48.1% 41.2%
Partial: Number 1024 677 1701
Percent 22.4% 22.4% 22.4%
None: Number 1867 894 2761
Percnet 40.9% 29.5% 36.4%
7592
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Men were nro.ch more likely than wcrnen to not answer the survey at
all; they were significantly less likely to give full response. How-ever,
it should be recalled that the ~ in our survey had roughly
the same survival rate as the men did. Therefore, weighting ~uld not
be useful for purposes of correcting this response· bias.
It should be recalled that members of minority groups, in general,
had higher survival rates than whites did. Different response rates
arrong ethnic groups could therefore cause problems. Unfortunately, this
was the case, as shown in the following table:
EI'HNIC GroUP
White Black Hispanic India Asian Other TOtal
Full: Number 1919 140 809 240 11 11 3130
Percent 42.7% 34.2% 45.6% 28.4% 44.0% 28.9% 41.2
Partial: Number 975 92 392 220 8 14 1701
Percent 21.7% 22.5% 22.1% 26.0% 32.0% 32.8% 22.4
None: Number 1605 177 574 386 6 13 2761
Percent 35.7% 43.3% 32.3% 45.6% 24.0% 34.2% 36.4
7592
Hispanics were !£Ore .likely to fully respond to the questionnaires
than were whites; Indians and blacks were less likely to fully respond
than were whites. For purposes of calculating a statewide survival rate,
weighting by ethnic. group ~uld probably be worthwhile.
Since estimates of county survival rates are desired for our study,
response bias should be checked at the county level. crosstabulations
of ethnic group and response type were done for each county; chi-square
tests were used to test the hypothesis of independence between the two
types of classifications. Using a 1% level of significance, independence
had to be rejected for Cochise and Maricopa counties.
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For weighting of Maricopa and Cochise survival rates to be useful it
lM)uld have to be shown that their etlmic groups hcrl significantly differ-ent
survival rates. To test for this, survey respondents were classified
as either "survivors" or "non-survivors" according to their survival status.
Following are the results for Maricopa County:
Survival Status ETHNIC CATEGORY
in
Final Survey Week White Black Hispanic Indian Asian Other Total
Survived:
Number 109 13 25 2 1 0 150
Percent 18.5% 29.5% 25.5% 22.2% 50.0% 0.0% 20.2%
Did Not Survive:
Number 479 31 73 7 1 2 593
Percent 81.5% 70.5% 74.5% 77.8% 50.0% 100% 79.8%
743
The chi-square for this table has a value of 6.74032, with 5 degrees
of freedom. The significance level for this chi-square is 0.2407, so we
v.uuld not re.ject the hypothesis· that survival status and ethnic background
are independent for nonetary ineligibles in Maricopa County. A similar
result was obtained for Cochise County. We therefore oonclude that al­though
there does appear to· be significant response. bias arrong etlmic
groups in these counties, weighting v.uuld not be useful for our estimations
of county survival rates.
There were similar problems of response bias arrong age I earnings,
industry, and occupational groups for purposes of estimating state-wide
survival rates. For example older people were nore likely to respond than
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were young people. There were no characteristics, however, for which
both response rates and survival rates were significantly different
at the county level.
INTEGRATION OF RESULTS INI'O THE LADS ESTIMATlliG SYSTEM
included.
-28-
In order to best estimate true survival rates for an area, we fitted
Weekly Survival Rate
.942
.943
.948
.900
.978
.979
.959
.985
.979
.974
.986
.968
.991
Week No.
14
15
16
17
18
19
20
21
22
23
24
25
26
Weekly Survival Rate
.842
.927
.910
.904
.910
.921
.931
.949
.959
.938
.962
.941
.952
Week No.
1
2
3
4
5
6
7
8
9
10
11
12
13
equations to the data using linear regression techniques. It should
be noted that the later a week. was in the survey period, the higher the
weekly survival rate. Here are the weekly survival rates (weighted by
county) for all survey respondents:
The ultimate purpose of this project is to improve the LADS esti­mating
system. we have established that there are a significant number
of rronetary ineligibles in the state, that they are not evenly distributed
throughout the state, and that the survival rate varies arrong the sub­state
areas. Therefore, rronetary ineligibles should 'be specifically
VII.
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In canputing the first weekly survival rate, it is assumed that
all the survey respondents were initially survivors. The first week's
rate is much lower than the others, which we might expect for a variety
of reasons. One possible cause is that a person might still have a full­time
job during the week that he files a claim. Suppose sorreone loses
his job on wednesday, and files for benefits on Friday. The effective
date of his claim will be on the Sunday of that week, and thus he would
actually be employed (a non-survivor) during that initial week of inel­igibility.
It is also possible that a person filed for benefits due
to losing a full-time job, but still maintained a part-time job; or that
sorreone was actually out of the labor force at the time of filing for
benefits. Persons for whom these conditions were true would not be class­ified
as survivors during t..l-.,e i..'1itial part of the survey period.
In general., weekly survival rates were higher during the latter part
of the survey period. This was anticipated at the beginning of this pro­ject.
M:>netary ineligibles with good job skills, for whcm unemployrrent is
a temporary aberration in their job history, should have quickly found em­ployment.
During the final weeks of the survey period, the group of sur­vivors
YJOuld be mainly made up of the hard-core unemployed; their chance
of finding employrrent would l:::e' lOW'.
With survival rates rising over time, the IlDSt appropriate equations
might be geanetric or logarithmic, rather than linear. We found that the
single equation which best fit the data was of the formula Yx = __1_
a+bx
where x is the week number, Yx is the· estimated number of survivors in
week x, a.isc.a~oonstant:.te:on, and b is a linear coefficient.
In order to canpensate for the varying number of respondents within
each survey week and to maximize the use of our info:nnation, the proportion
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of respondents surviving in each survey week was multiplied by the number
of respondents in the first week to obtain the "true" nunber of survivors
in each week.. The equation derived for Maricopa COunty is shown below
(equations estimated for all counties are shown in Appendix 1, Table 23).
S . 1 urv~vo~ x = -.0=-:0=-=1""::'0"='"07="6=--+-.0=-:0:-':0~1~57="9:---,(-week--:---n-umber-:----:-)
For example, the estimated number of survivors in week 5 would be
1 = 557
:0010076 + .0001579(5)
Using the estimated Number of survivors in each week, the following weekly
survival rates were derived:
Week No. Survival Rate Week No. Survival Rate
1 .865 14 .951
2 .881 15 .953
3 .894 16 .955
4 .909 17 .957
5 .912 18 .959
6 .919 19 .961
7 .925 20 .962
8 .931 21 .964
9 .935 22 .965
10 .939 23 .966
11 .943 24 .967
12 .946 25 .968
13 .948 26 .969
-31-
copa COunty surrently "surviving" would be the surrrnation of the rronetarily
Sm::vival rates for later weeks could also be derived fran the equation.
The number of sUJ:Vivors in any particular calendar week could be estimated
by applying the proper weekly sm::vival rate to the rronetarily ineligible
claims of the current week and each of an appropriate number of previous
weeks. Thus, the total number of rronetarily ineligible claimants in Mari-ineligible
claims in the present week multiplied by .865, the claims from
the previous week multiplied by .762 (the product of .865 x .881), the num­ber
of claims from two weeks ago multiplied by .681 (the product of .865
x .881 x .984), etc.
One problem with using the equation is selecting the number of weeks
needed to build up to a total estimate of unerrployed rronetary ineligibles.
The equation implies that sC:.m= rronetary ineligible claimants would still be
unemployed even years after the date of filing. For ~le, al:out four
percent of rronetary ineligibles would still be unemployed three years after
• filing. *
-ve. found. a s~ler meth:Jd of calculating the nunber of survivors by
estimating the equation Sm::vivors
t
= f (Survivors
t
_l ) where sm::vivorst is the
TIl..lIllber of survivors in week t, and Survivors
t
_l is the number of sm::vivors
in the week previous to> t. For all counties, the first weekf S sm::vival rate
was I'C1UCh 1O\\er than the other weeks f survival rates; therefore dropping
Survivorst=l = f (Survivorst=o) increased greatly the equation's goodness of
fit. The y-intercept tenn was not included in the canputation of the linear
regression line; so instead of our equation being of the usual fo:rm y = a + bx,
it is y = me. The weekly survival rate is then simply the regression
*1 ~ (.0010076 + .0001579(200)) = .039
1 -to .0010076
coefficient "b".
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The -least squares estimate of the weekly survival rate for Maricopa
County was .926 (for all of the counties and plaruring districts, see
Appendix 1, Table 24). The percentage of rronetary ineligibles in Mari-copa
County who were survivors in the initial week of the survey period
was 82.9%. In order to estimate the nunber of rronetarily ineligible
claims in that week multiplied by .829 would be added to the nunber of
survivors fran previous weeks multiplied by .926. A representative work-sheet
for this rrethod is presented on the next page.
In order to begin this procedure, a total estimate of unemployed
rronetary ineligibles would have to be built up over a period of several
weeks. For Maricopa County, a period of seventy-two weeks would probably
be sU£ficient. In other words, the proportion of persons still unemployed
seventy-two weeks after filing a rronetarily ineligible claim in Maricopa
County would be SU£ficiently close to zero so as to be ignored. * A
shorter "build-up" period would be necessary for the smaller counties,
since they have fewer rronetarily ineligible claimants.
For purposes of testing the irrg;>act of including these claimants
in unemploynent estimates., the nunber of surviving rronetary ineligibles
for the week including July 12, 1979, was calculated for each county
using the method just given. These values were then added to the Ha.nd1::x:Jok
estimate of unemployment for each county, in order to get a revised
Ha.nd1::x:Jok estimate. Using the revised figures,. the percentage of state-
*The average nunber of rronetary ineligibles per week in Maricooa County
for calendar year 1979 was 100. Multiplying 100 by [.829 ( . 92671) ] gives
.35, which is less than a 'whole I person.
- - - - - -- - - - - - - - - - - - - -
WORKSHEET FOR ESTIMATING MONETARY INELIGIBlES*
Number of Total Number of
Survivors from Surviving Monetary
Number of Estimated Number of Previous Weeks Ineligibles
Monetarily Number Surviving: Surviving Monetary Still Surviving: for Current Week
Ineligible Col. I x Survival Ineligibles From Col. III x Survival (Column II +
Week Beginning Claims Rate of .829 Previous Weeks Rate of .926 Column IV)
1981 Iw
1/4 150 124 1210 1120 1244 wI
1/11 140 116 1244 1152 1268
1/18 120 99 1268 1174 1273
1/25 100 83 1273 1179 1262
2/1 100 83 1262 1169 1252
* Figures for Column I and the first entry in Column III are made up for purposes of the worksheet.
Survival rates used are those estimated for Maricopa County using the survey data.
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-34-
wide unen:ployment that could be attributed to each county was canputed.
These percentages were then multiplied by the c. P. S. estimate of unem­ployment
for the state (55,092), so as to derive a neN estimate of un­en:
ployment for each county.. These county figures were then divided by
the respective c. P. S. labor force estimate for each county, in order
to obtain revised county unemployment rates.
The results of these computations are shown in Table 25 of Appen-dix
1.. The inclusion of rronetarily ineligible claimants ~uld lower
Maricopa County's published unemployment rate fran 4.6 percent to 4.5
percent. Cochise County's rate ~uld increase fran 7.4 percent to 8.2
percent. Five other counties (Gila, Grahaml Greenlee, Pinal, and Yuma)
sl1cMed an increase of at least three-tenths of a percent in their respec­tive
unemployment rates. The estimated rate for Santa Cruz increased
from 12.8 percent to 13.0 percentI while the estimate for M::>have County
changed by only one-tenth of a percent. The change in the estimated
•
unemployrrent rates for each of the other counties was less than one-tenth
of a percent.
The inclusion of rronetarily ineligible claimants produced similar
changes in the estimated county unemployment rates for other periods.
The estimated unemployment rate for Maricopa County during November,
1979, would decrease by one-tenth of a percent. COChise County's
unemployment rate ~uld increase fran 7.2 percent to 7.9 percent, while
the rate for Graham County would be 7.2 percent instead of 6.6 percent.
The revised unemployment. rates for each of the remaining counties were
either higher or not significantly different from the previous estimates.
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VIII. IMPACl' ON THE ESTIMATE OF NEW ENTRANrS AND REElNTHANI'S 'ID THE LABOR FORCE
In general, rronetary ineligibles are disqualified from UI benefits
due to insufficient participation in the lab:>r force. Therefore, we
would expect sare of them to be unemployed entrants into the lab:>r force,
which are already part of the LAUS estimating system. Unemployed entrants
are divided by BLS into two categories: new entrants, who are persons
entering the lab:>r force for the first time and have not found a job,
and reentrants, who have previously worked full-time for at least two
weeks and were out of the lab:>r force before beginning their work search.
Putting rronetary ineligibles into the system and keeping the present
rrethod of estimating the number of unerrployed new entrants and reentrants
might lead to duplication in the counts of the unemployed.
It appears to be doubtful that many new entrants to the lab:>r force
file for UI benefits. only six of our survey respondents indicated
that they had never worked, while a Itlast day worked'" was recorded on
the initial claim for all persons initially selected for the survey.
This is very close agreement given that alrrost five thousand persons re­sponded
to that question on their survey fonn.
The estimate of unanployed. reeentrants to the lab:>r force would
be affected by the inclusion of rronetary ineligibles, havever • Given
the questions asked on our questionnaire, survey respondents could be
classified. as just beccming unenployed. reentrants at the beginning of
the survey period if they indicated that they had not looked. for work
during the previous four weeks, had no job for at least the previous
two weeks, and were unemployed at the beginning of the survey period.
Out of the 4,610 people for whom we had sufficient infonnation, 159
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-36-
could be classified as unemployed reentrants at the time they filed a
rronetarily ineligible claim. However, it is possible that none of
these people were unernployed reentrants in the first sw:vey week, since
we asked for the last day worked, rather than the last day that one
had a full-time job for at least two weeks. The total number of poten­tial
unernployed reentrants at the beginning of the sw:vey period
would be all respondents unemployed during the first survey week who
had no job during the previous two-week period. This was true for 1952
survey respondents. Therefore.l given the information available fran
our survey, the percentage of sw:vey respondents who were reentrants
at the time of filing might be zero, or as high as 42 percent. In all
likelihood, however, at least· some rronetarily ineligible claimants are
also unemployed reentrants to the labor force at the time they filed
a claim. Therefore, formulas used to estimate neM entrants and reen­trants
to the labor force should be revised so as to exclude persons
recentiyfiling a ncnetarilyineligible VI claim•.
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-37-
IX. SUMMARY AND CON:LUSIONS
Statistics indicate that there is a significant number of rronetarily
ineligible claimants for unemployment insurance benefits. We used two
ways to rreasure the dispersion of such persons amJng the sub-state areas.
With each criterion, we found that Arizona's rural counties have propor­tionately
rrore rronetarily ineligible claimants than do its two urban
counties.
Female claimants are rrore likely to be declared rronetarily inelig­ible
for benefits than are male cla.i.mants. There is a greater incidence
of rronetary ineligibility anong black, Hispanic, and IndHm _claimants
than there is for white claimants. However, the distribution of reasons
for rronetary ineligibility do not vary much anong ethnic groups, with
the exception of Indians.
We surveyed rronetarily ineligible cla.i.mants with regards to their
labor force status during a twenty-six week period, beginning with the
week in which they filed their claim. Respondents were classified as
"survivors" during a particular survey week if they were both unemployed
(C .P.S~ definition) and still rronetarily ineligible for benefits. The
proportion of survivors at the end of the survey period was about the
sane for men respondents as it. was for WClIreIl respondents. The percent~
age of minority group respondents surviving in the final survey week
was higher than the percentage for whites.
In general, survival rates for rural counties were higher than those
of urban counties. Response bias was not statistically significant at
the county level, but it was. for state-wide figures due to different re­sponse
and survival rates anong ethnic groups. Therefore, canputations
of results at the state-wide level would have to be weighted both due
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-38-
to response bias and the fact that a stratified randan sample was used.
Since data from the Arizona UI database indicates that rronetarily ineli­gible
cla..i.mants are not distributed evenly throughout the state, and our
survey results showed that their survival rates differ anong the counties,
we recamend that they be specifically included in the LAOS estimating
system. Estimates of unemployed rronetary ineligibles should be made at the
county level. The rrost practical way to survive rronetary ineligibles would
be to apply a survival rate to the current week's rronetary ineligibles, and
apply another rate to survivors carried over from previous weeks (recom­me.
rrled rates are shown in Appendix 1, Table 22). This mathod was used to
e::at"pUte revised county unenployment rates for sane t..ima periods in 1979.
Maricopa County's estimated unemployment rate decreased by one-tenth of a
percent, while the rates for other counties either increased or else showed
no significant change. our survey results give scma indication that inclu­sion
of rronetarily ineligible claimants will require slight revisions to the
equations used to estimate unenployed. n€M entrants and unenployed reentrants
to the labor force so that double-a:>unting is avoided.
C.P.s. J:::JE::!finitions •• ........................ •..' e. _.•• .57
c··.p·•.s·.·. :De.finitions: - ., - .. .56
C.P.s •. 'Definitions e . ., -',' "",,, tl>"" e "..sa
Pa-ge 'IWo, Sec'tion II 55
Title Page
Apperrlix 1 - Statistical Tables
-39-
Responses to Survey Questionnaire:
Labor Force· Status of Male Survey ReSFCndents,
(Sl.JrV'eY ReSJ;?C>IldeI1.ts)'., .- •••'.... •' - ' -53
Cross Tabulation of Age by Reason For M:>netary
Ineligibility: Males, CY 1979 - 46
Cross Tabulation of Age by Reason For Monetary
:rneligibility: Total sample, CY 1979....•••.•.•............• .45
Cross Tabulation of Industry by Reason For Monetary
Ineligibility: cy 1979 44
Cross Tabulation of OCcupation By Reason For Monetary
Ineligibility: cy. 1979 43
Claimant Characteristics: A Comparison of Monetarily
Eligible and Ineligible Claimants Who Filed During
cy 1979 (Arizona Intrastate UI Claimants Only) •............... 41-42
Cross Tabulation of Age by Reason For Monetary
Ineligibility: Females, C':l 1979 "' 47
Labor Force Status of All Survey Resp:mdents,
Labor Force Status of Female Survey Respondents.~
Cross Tabulation of Tine. Period •Between LaSt Day
Worked and. Filing For UI Benefits by Age GrOup
Responses i:o::Sur:.rey, Ql.;restiomlaire:.. ,
Page" ~,- sect.wn I .•.•.. e- .' • • ' '._ -•• • '.'.' ~ ' ~ .. .54
Cross Tabulation of Ethnic Group by Reason For
Monetary Ineligibility: CY 1979 48
eatparison Between· the Population and the Sample Used
in the Arizona LAUS COntract - Maricopa COutny 49-50
~ison Between the Population arJ the Sample
Used in the Arizona LAOS COntract - Pima COunty 51-52
2
1
3
4
No.
9
5
6
8
7
15
10
11
14
12
13
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U. I. r:>efinitions.............................................. 60
U.. I. r:>efinitions.............................................. 61
-40-
Labor Force Status of Male Survey Respondents,
Title Page
Appendix 1 - Statistical Tables
(COntinued)
Change in Coun"ty' Unemployrrent Rates Due To The
Inclusion of Ineligibles (for the Week. Including
JUly 12,1979) .••.• _ _. _••.••'••••.•. ' :.'." 68
Labor Force status of Female Survey Respondents,
Labor Force Status of All Survey Respondents,
U. I . r:>efinitions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... 59
Equations Estimated For Each COunty of the Fonn
Y = a,.+1b (x) ' ' .. 66
'Weekly Survival Rates For Counties and Planning
Districts. . . . .. . . . . . . . . . . . . . . . . . . ... . . . . . . . . . . . . . . . . . . . . . . .. 67
Percentage of Respondents Surviving in Each Survey
'Week, By' Etlm.i.c Grotlp '•••".' ••••••••'••••_.'. • • • • .. • • • • •• 63
Percentage of Respondents Surviving in Each Survey
'Week" By' SeJc a_ a_••••••••••••• 62
Percentage of Respondents Surviving in Each Survey
'Week, By' District.. . . . • • • . • .. .. .. .. .. .. .. •. .. .. .. .. • .. .. .... .. .. .. .. .. .. .. .. • .... 64
Percentage of Respondents Surviving in Each Survey
'Week" By' COlJIl"ty' ' ' _•.' '. .. .. .. .. .. .. 65
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I 23
I 24
I 25
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-41­TABLE
1
CIAIMAN1' CHARACI'ERISTICS: A <n1PARISCN OF .mNEI'ARILY ELIGIBLE
AND :rnELIGIBLE CLAIMANI'S WHO FILED DURING cr 1979
(ARIZONA INTRASTATE or CLAIMANI'S ONLY)
Number Number Total Percent
Characteristic Eligible Ineligible Ineligible
Sex:
Male 40,560 7,351 47,911 15.3
Female 22,760 4,859 27,619 17.6
Total 63,320 12,210 75,530 16.2
Age:
!ess than 20 2,404 1,238 3,642 34.0
20-21 5,130 1,325 6,455 20.5
22-24 9,366 1,761 11,127 15.8
25-34 21,777 3,818 25,595 14.9
35-44 11,293 1,747 13,040 13.4
45-54 7,868 1,269 9,137 13.9
55-64 4,828 775 5,603 13.8
65 or nore 654 277 931 29.8
Total 63,320 12,210 75,530 16.2
Ethnicity:
White 43,580 7,769 51,349 15.1
Black 2,804 787 3,591 21.9
Hispanic 12,281 2,594 14,875 17.4
Indian 4,132 974 5,106 19.1
Asian 188 38 226 16.8
IoN.A. 335 48 383 12.5
Total 63,320 12,210 75:530 16.2
Occupation, Last Base Period
~loyer:
Prof./Tech. /Mgrl. 7,662 1,153 8,815 13.1
Clerical/Sales 12,471 2,340 14,811 15.8
Service 5,803 1,521 7,324 20.8
FaDm/Fish/FOrestry 1,606 594 2,200 27.0
Processing 799 194 993 19.5
Machine 2,941 471 3,412 13.8
" aen.<mWOrk 2,977 621 3,598 17.3
Structural 12,623 2,356 14,979 15.7
Miscellaneous 6,169 1,249 7,418 16.8
I .•N.A. 10,269 1,711 11,980 14.3
Total 63,320 12,210 75,530 16.2
Continued
I -42-
I TABLE 1 (Continued)
-I Number Number Total Percent
I Characteristic Eligible Ineligible- Ineligible
Industry, Last Base Period
I Employer:
Ag./Forest/Fish 4,011 701 4,712 14.9
Mining 2,520 288 2,808 10.3
Construction 6,329 1,015 7,344 13.8
I Manufacturing 11,037 1,410 12,447 11.3
Trans. /Ccmnun. /Util. 3,467 369 3,836 9.6
Wholesale/Retail 10,915 1,949 12,864 15.2
I F.IoR.E. 4,435 501 4,936 10.1
services 9,263 1,740 11,003 15.8
Pub. Admin. 2,578 377 2,955 12.8
Nonclassified 2,401 138 2,539 5.4 I IoN.A. 6,364 3,722 10,086 36.9
TOI'AL 63,320 12,210 75,530 16.2
I UI High Quarter Earnings:
I $ 0-374 30 4,716 4,746 99.4
$ 375-499 219 494 713 69.3
$ 500-699 709 758 1,467 51. 7
I $ 700-899 1,346 634 1,980 32.0
$ 900-1099 1,899 707 2,606 27.1
$ 1100-1499 6,654 1,364 8,018 17.0-
$ 1500-1999 11,242 1,283 12,525 10,.2
I $ 2000-2999 18,965 1,200 20,165 6.0
$·3000-3999 9,040 520 9,560 5.4
$ 4000-4999 5,527 248 5,775 4.3
I $ 5000 or· over 7,689 286 7,975 3.6
TOI'AL 63,320 12,210 75,530 16.2
I UI Base Period. Wages:
$ 0-562 35 5,015 5,050 99.3
I $ 563-999 245 1,370 1,615 82.3
$ 1000-1999 2,322 2,720 5,042 53.9
$ 2000-2999 4,669 1,492 6,161 24.2
I $ 3000-3999 5,750 697 6,447 10.8
$ 4000-4999 6,081 357 6,438 5.5
$ 5000-7499 14,672 380 15,052 2.5
I $ 7500-9999 10,447 101 10,548 1.0
$ 10,000-14,999 11,235 47 11,282 0.4
$ 15,000 or over 7,864 31 7,895 0.4
TOI'AL 63,320 12,210 75,530 16.2 I
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TABLE 2
cross TABULATION OF OCCUPATION BY REASON FOR IDNm'ARY INELIGIBILITY*
CY 1979
CX:cupational Catego:ry
Prof.
Tech. Clerical
~ason for Ineligibility ~. & Sales
fanning
fishery
Service Forestty Processing
Machine Bench- .None or Non-
Trade Work Structrual Misc.Classifiable 'Ibtal
A. PerQe1lt DistrwutiCIl of Reason for :rneligibility by CX:cupation
~ Base Period Wages 12.8% 18.7% 13.4% 5.1% 1.1% 4.0% 3.6% 17.7% 9.2% 14.4% 100.0%
[nsufficient High Quarter
Earnings 7.1% 23.1% 17.3% 5.2% 1.0% 3.9% 5.4% 16.8% 10.4% 9.6% 100.0% ~
~se period/High Quarter wI
Earnings Rat.:i.o Too laol 9.1% 18.7% 11.0% 3.9% 1. 7% 3.9% 5.8% 19.9% 11.7% 14.3% 100.0%
Cnsufficient Requalifying
Wages 13.3% 14.2% 12.2% 0.0% 7.1% 6.3% 12.5% 4.0% 18.4% 12.1% 100.0%
Ul Reasons 9.8% 19.4% 12.7% 4.4% 1.5% 3.9% 5.2% 18.7% 10.8% 13.5% 100.0%
B. Percent Distribut.:i.on of CX:cupatiol'l by Reason for Ineligibility All CX:cu.
lo Base Period Wages 35.6% 26.1% 28.6% 31.1% 21.0% 27.7' 18.8% 25.6% 23.1% 29.0% 27.2%
:nsufficient High Quarter
Earnings 12.4% 20.2% 23.1% 19.9% 12.0% 16.9% 17.8% 15.3% 16.3% 12.0% 17.0%
lase Period/High Quarter
Earnings Ratio Too Ii:M 51.5% 53.4% 47.9% 49.1% 64.9% 54.7% 62.3% 59.0% 59.8% 58.6% 55.5%
:nsufficient Requalifying
Wages 0.6% 0.3% 0.4% 0.0% 2.0% 0.7% 1.0% 0.1% 0.7% 0.4% 0.4%
'Ibtal 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.00% 100.0% 100.0%
Based on all who filed for benefits at any tirle during calendar year 1979 and were denied benefits because of a failure to
Ireet the nonetary eligibility criteria. (It should be noted that a particular claimant can file for a nonetary detenn­ination
each calendar quarter; these data inchrle persons in the characteristics count each time they had a nonetary
detennination. )
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TABLE 3
CROSS TABULATION OF INIXJSTRY BY REASON FOR M)NEI'ARY INELIGIBILITY*
CY 1979
In::1ustry
Agr~
~ason for Ine1i.gibi1ity Forestry Wholesale None or Non-
.Fishing Mini.Q9 COnst. Mig. TCPU Retail F. 1.R. E. Services GoVerI1lleI1t Classifiable Total
A. PeroeJ1.t Di$tribu,ti.0Il pf ReaS9n for Ineligibility by Industry
'b Base Period Wages 0.3%
[nsufficient lIigh Quarter
Earnings 7.6%
3ase Period/lligh Quarter
Earnings Ratio ToO ION 7. 7%
[nsufficient Requalifyi.Ilg
Wages 27.3%
tU1 Reasons 5.8%
0.2% 0.1% 0.4%
2.9% 8.8% 10.5%
3.1% 12.0% 17.3%
0.0% 4.0% 14.4%
2.3% 8.2% 11.5%
0.0%
2.2%
4.7%
0.0%
3.0%
0.3%
31.6%
18.8%
12.3%
15.9%
0.1%
3.1%
5.9%
14.6%
3.9%
0.1%
25.5%
18.2%
4.0%
14.5%
0.0%
3.9%
4.1%
4.0%
3.0%
98.6%
3.2%
6.3%
11.3%
30.9%
100.0%
100.0%
100.0%
100.0%
100.0%
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B. Percent Distribution of Industry by Reason for Ineligibility All Indus.
0.0% 0.2% 0.5% 0.0% 0.3% 1.6%
100.0% 100.00% 100.0% 100 % 100.0% 100.0%
21.8% 18.3% 15.4% 12.4% 33.6% 13.5%
76.3% 81.3% 83.0% 87.3% 65.6% 84.5%
~o Base Period Wages 1.2%
[nsufficient High Quarter
Earnings 22.4%
3ase Period/High Quarter
Earnings Ratio ToO ION 74.5%
rnsufficient Requa1ifying
Wages 2.0%
Total 100.00%
1.9% 0.2% 1.0% 0.3% 0.4% 0.4% 0.2%
29.8%
69.9%
0.1%
100.0%
0.3%
22.4%
76.8%
0.6%
100.0%
86.7%
1.8%
11.33%
0.2%
100.0%
27.2%
17.0%
55.5%
0.4%
100.0%
3ased on all who filed for benefits at any tine during calendar year 1979 am were denied benefits because of a failure to
ooet the rronetary eligibility criteria. (It should be noted that a particular claimant can file for a rronetary dete:rmination
=ach calendar quarter; these data include persons in the characteristics count each tiIre they had a rronetary detennination.)
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TABLE 4
CROSS TABULATION OF AGE BY REAS(X:\l FOR IDNEI'ARY INELIGIBILITY; 'IDl'AL SAMPLE*
CY 1979
Reason for Ineligibility less than 20 20-21 -22.-2-4
Age
-25--34 35-44 45-54 55-64 65 or over Total
A. )?erqmt Distribution of Reason for Ineligibility by Age
~ Base Period Wages 8.3% 11.1% l3.4' 29.7% 13.7% 11.5% 7.9% 4.3% 100.0%
Insufficient High Qu(1rter
Earnings 18.4% l3.4% 15.3% 30.9% 10.1% 6.9% 4.0% 0.9% 100.0%
Base Period/High Quarter
;Earnings Ratio Too LQrl 8.3% 11.3% l4.4% 32.3% 15.7% 10.7% 6.0% 1.4% 100.0%
Insufficient Requalifying ,
Wages 0.0% 8.0% 6.1% 21.4% l4.4% 12.1% 6.0% 32.0% 100.0% ,j:::o
U1
!Ul Reasons 10.0% 11.6~. 14.2% 31.3% 14.2% 10.3% 6.2% 2.2% 100.0% ,-
B. Percent Distribution of Age by Reason for Ineligibility All Ages
~ Base Period Wq.ges 22.6% 25.9% 25.6% 25.8% 26.2% 30.5% 34.4% 52.4% 27.2%
Insufficient High Quarter
Earnings 31.2% 19.1% 18.2% 16.7% 12.1% 11.3% ll.l% 7.1% 17.0%
Base Period/High Quarter
Earnings Ratio Too IJ::M 46.2% 54.1% 56.0% 57.2% 61.3% 57.7% 53.5% 34.5% 55.5%
Insufficient Requalifying
Wages 0.0% 0.3% 0.2% 0.3% 0.4% 0.5% 0.4% 6.0% 0.4%
Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%
3ased on all who filed for benefits at any ti.rre during calendar year 1979 and were denied benefits because of a failure
:0 meet the rronetary eligibility criteria. It soould be noted that a particular claimant can file for a rronetary
ietennination each calendar quarter; these data include persons in the characteristics count each ti.rre they had a
ronetary determination.) -
-------------------
TABLE 5
cross TABULl-\TIOO OF AGE BY REASON FOR MJNE!'ARY INELIGIBILITY: MALES*
CY 1979
Age
~ason for :rnel..j.gi.l:>.i1j..ty less than 20 -20--2-1 -22--2-4 25-34 35-44 45-54 55-64 65 or over Total
A. l?ercent D.i.stribution of Reason for Ineligibility by Age
\lo Base PerioCi Wages 8.6% 11.7% 12.3% 29.9% 12.2% 11.2% 8.8% 5.4% 100.0%
[nsufficient High Quarter
Earnings 19.3% 13.4% 16.8% 29.8% 10.4% 5.6% 3.4% 1.3% 100.0%
3ase Period/High Quarter
Earnings Ratio '1'oQ lJ::Jw 8.2% 11.5% 13.4% 33.1% 14.7% 10.6% 6.7% 1. 7% 100.0%
[nsufficient Requa1ifying
I wages 0.0% 11.8% 2.9% 19.3% 16.6% 17.8% 5.9% 25.8% 100.0% Il::o
\11 Reasons 9.~ 11.8% 13.5% 31.7% 13.4% 10.1% 6.8% 2.8% 100.0% 0'1
I
B, Percent Distribution of Age by Reason for Ineligibility lUIAges
110 Base Pericxl wages 25.0% 28.2% 25.9% 27.0% 26.1% 31. 7% 36.8% 54.8% 28.6%
[nsufficient High Quarter
Earnings 28.2% 16.3% 17.9% 13.6% 11.2% 8.0% 7.1% 6.5% 14.4%
3ase Pericxl/High Quarter
Earnings Ratio Too Low 46.7% 55.0% 56.1% 59.1% 62.1% 59.4% 55~6% 34.3% 56.5%
[nsufficient Requa1ifying
wages 0.0% 0.5% 0.1% 0.3% 0.6% 0.8% 0.4% 4.3% 0.5%
Total 100.0% 100.0% 100.0% 100.0% 100.0% 100~0% 100.0% 100.0% 100.0%
~sed on all males who filed for benefits at any t.i.rre during calendar year 1979 and were denied benefits because of a
:ai1ure to Ireet the nonetary eligibility criteria. (It smuld be noted that a particular claimant can file for a nonetary
letennination each calendar quarter; these data include persons in the characteristics count each t.i.ne they had a
:onetary determination.)
-------------------
TABLE 6
CROSS TABULATION OF AGE BY REASON FOR K:Nm'ARY INELlGIBILITY: FEMALES*
CY 1979
~son for Ineligibility less than 20 -20--2-1
~-~~ -
22-24 . 25-34 35-44 45-54 55-64 65 or over 'lbtal
lo Base Period Wage~ 19.1% 22.3% . 25.3% 23.8% 26.4% 28.8% 31.0%
:nsufficient High Quarter
Earnings 35.5% 25.0% 18.7% 21.7% 13.2% 16.1% 19.2%
lase Period/H:i,.gh Qua:J::ter
Earnings Ratio Too LcM 45.4% 52.7% 55.8% 54.2% 60.2% 55.1% 49.3%
:nsufficient Requalifying
Wages 0.0% 0.0% 0.3% 0.3% 0.2% ·0.0% 0.4%
'lbtal 100.0% 100.0% 100.0% 100.0% 100.0% ~.Ioo.i6% 100.0%
~o Base Period Wages 7.8%
[nsufficient High Qua:J::ter
Earnings
~se period/High Quarter
Earnings Ratio Too I.!:M
:nsufficieiJ.t'-'Requaiifying
Wages
ul Reasons
A. PerCMt Pi~tribution of Reason for lneligibility by Age
10.0% 15.5% 29.3% 16.3% 12.2%
17.5% 13.5% 13.8% 32.0% 9.8% 8.2%
8.6% 11.0% 15.9% 30.9% 17.2% 10.8%
0.0% 0.0% 12.7% 26.1% 9.5% 0.0%
10.3% 11.2% 15.3% 30.7% 15.4% 10.6%
B. PerCMt Pi~tribution ot Age by Reason for Ineligibility
6.4%
4.8%
4.7%
6.4%
5.1%
2.4% 100.0%
0.6% 100.0%
0.9% 100.0%
45.2% 100.0%
1.3% 100.0%
I~
All Ages ~I
44.8% 24.9%
8.8% 20.8%
35.1% 53.9%
11.4% 0.3%
100.0% 100.0%
lased on all females who filed for benefits at any tiIre during calendar year 1979 and were denied benefits because of
l failure to meet the nonetary eligibility criteria. (It should be noted that a particular claimant can file for a
pnetary determination each calendar quarter; these data include persons in the characteristics count each tiIre they
lad a nonetary detennination.)
-------------------
TABLE 7
CROSS TABULATION OF El'HNIC GROUP BY REASON FOR M:m:rARY INELIGIBILITY*
CY 1979
Reason for Ineligibility
A.
No Base Pericx:l Wa.ges
Insufficient High Quarter
Earnings
Base Pericx:l/High Quarter
Earnings Ratio Too I.Dw
Insufficient Re:Iual:j..fy:j..ng
Wages
All reasons
B.
No Base Pericx:l Wages
Insufficient High Quarter
Earnings
Base Period/High Quarter
Earnings Ratio Too LcM
Insufficient Requalifying
Wages
Total
Ethnic Group
White
White Spanish Black Indian Asian Other Total
Percent Pisu-ilJut:j..cm of Reason for Ineligibility by Ethnic Group
63.2% 18.5% 6.8% 10.4% 0.3% 0.7% 100.0%
66.5% 20.5% 6.3% 6.3% 0.2% 0.2% 100.0%
64.5% 20.9% 6.7% 7.2% 0.3% 0.4% 100.0% I .e::.
65.5% 27.4% 3.0% 4.1% 0.0% 0.0% 100.0% co
I
64.5% 20.2% 6.6% 7.9% 0.3% 0.5% 100.0%
All
Percent DistrilJution of Ethnic Groups by Reason for Ineligibility Ethnic
Groups
26.6% 24.8% 28.0% 35.7% 30.0% 43.3% 27.2%
17.5% 17.2% 16.2% 13.6% 11.3% 7.5% 17.0%
55.5% 57.4% 55.7% 50.4% 58.7% 49.2% 55.5%
0.4% 0.6% 0.2% 0.2% 0.0% 0.0% 0.4%
100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%
rcaased on all who filed for benefits at any time during calendar year 1979 and were denied benefits because of a failure
to meet the rronetary eligibility criteria. (It should be noted that a particular claimant can file for a rronetary
detennination each calendar quarteri these data include persons in the characteristics count each time they had a
IOOnetary detennination.)
TABLE 8
-49-
"CCMPARISON BE'IWEEN THE POPULATION AND THE SAMPLE
USED rn THE ARIZONA rAUS CONTRAcr-MARIQ)PA COUNTY"
Probability of
Difference This
Percentage Percentage Large OCcuring
of Sample of Population Due To Chance
68.4% 65.7% .4180
31.6 34.3 .4180
14.5 14.2 .9044
11.8 11.1 .7490
14.7 15.6 .7264
32.3 31.1 .7114
13.4 13.2 .9362
8.5 8.8 .8808
3.8 4.9 .4654
1.1 1.1 1.0000
72.4 75.2 .3524
~.~ 8.4 .5352
15.6 14.2 .5686
2.2 1.7 .5824
0.4 .6528
0.2 0.1 .3682
.7264
.2892
.8966
.8494
.7184
.4010
.8572
..389R
.6384·
.5352
Continued
2.7
0.9
4.9
5.5
28.8
10.4
6.4
11.3
18.9
10.1
3.1
1.6
4.7
5.8
27.6
12.2
6.7
9.4
17.6
11.4
Age:
Less than 20
20-21
22-24
25-34
35-44
45-54
55-64
65 or m::>re
Characteristic
OCCUpation, Last
BasePericxi
En!p1oyer:
Prof./Tech. /Mgr1.
Clerical/sales
service
Far.m/Fish/Forest/
Related
Processing
Machine Trades
Bench Work
Structural WOrk
MiScellaneous.
Not Given/Classified
Sex:
Male
Female
Ethnicity:
White
Black
Hispanic
Indian
Asian
unknown
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5.8% 4.4% .3720
1.1 1.2 .8466
10.0 11.1 .6170
11.4 10.0 .5028
2.4 2.8 .7264
17.4 18.5 .6892
3.8 3.9 .9442
15.6 14.5 .6528
2.0 2.4 .7114
0.4 0.4 1.0000
30.1 30.6 .8808
-50-
TABLE 8 (continuad)
UI High Quarter Earnings:
$0
1 - 499
500 - 699
700 - 899
900 - 1099
1000 - 1499
1500 - 1999
2000 - 2999
3000 - 3999
4000 - 4999
5000 or over
.9204
.9204
.9680
1.0000
.9522
.9204
.8728
.7872
.4592
.3628
.9204
.9680
.8026
.8494
1.0000
.8728
.9602
.9602
.4840
.8414
.3788
Probability of
Difference This
Large Occuring
Due to Chance
27.5
26.4
20.4
11.6
6.3
2.3
3.5
1.1
0.6
0.4
27.5
16.6
8.6
5.6
4.7
8.1
9.2
10.1
4.3
2.0
3.3
Percentage
of Population
27.8
26.7
20.5
11.6
6.2
2.2
3.3
1.3
0.2
27.8
16.5
9.1
5.3
4.7
7.8
9.1
10..2
5.3
1.&
2.2
Percentage
of Sa;nple
Industry, Last
Base Period
Employer:
Ag./Forest./Fish.
Mining
COnstruction
Manufacuring
Trans. /Comn. /Util.
Wholesale/Retail
Trade
Finance/Insurance/
Real Estate
Services
Government
Not Given/Classified
Infonnation Not
Available
$0
1 999
1000 - 1999
2000 - 2999
3000 - 3999
4000 - 4999
5000 - 7499
7500 - 9999
10000 - 14999
15000 or over
Characteristic
ur Base Period Wages:.
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-51-
TABLE 9
"ffiMPARISON BE'IWEEN THE POPUIATION AND THE SAMPLE
USED IN THE ARIZONA IAUS ffiNTRAcr-PIMA COUNTY"
Probability of
Error This
Percentage Percentage Large OCcuring
Characteristic of Sample of Population Due to Chance
Sex:
Male 65.8% 63.9% .8104
Female 34.2 36.1 .8104
Age:
Less than 20 11.2 10.2 .8414
20-21 9.5 9.7 .9680
22-24 14.9 14.6 .9602
25-34 35.6 35.2 .9602
35-44 13.6 15.3 .7794
45-54 10.2 9.7 .9204
55-64 4.7 4.9 .9522
65 or rrore 0.3 0.4 .9282
Ethnicity:
White 74.9 72.6 .7566
Black 6.1 5.5 .8728
Hispanic 15.9 18.8 .66
Indlan 2.4 2.7 .9124
Asian 0.7 0.4 .7794
Unknown
OCcupation, Last
Base Period
Employer:
Prof./Tech./Mgrl. 12.2 13.5 .8180
Clerical/Sales 18.6 17.7 .8886
Service 14.2 15.5 .8336
Farm./Fish./Forest./
Related 2.4 1.8 .7872
Processing 0.2 .7872
Machine Trades 6.4 5.8 .8808
Bench Work 2.7 3.3 .8414
Structural Work 20.3 20.6 .9680
Miscellaneous 6.1 7.1 .8180
Not Given/Classified 16.9 14.6 .6966
continued
TABLE 9 (COntinued)
-52-
1.0000
1.0000
.9680
.9680
.9760
.9760
.9442
.8650
.7872
.7184
1.0000
.9204
.8728
.9522
.6744
.9204
.9204
.8966
.9442
.8026
.8180
Probability of
Error This
Large OCcurring
Due to Chance
26.8
25.4
22.1
11. 7
6.0
3.3
2.9
1.1
0.2
0.4
26.8
16.2
7.1
4.9
6.4
9.7
9.3
11.9
3.5
1.5
2.6
Percentage
of Population
2.4 2.7 .9124
1.7 2.0 .8966
9.5 9.7 .9680
7.5 8.4 .8494
1.7 2.0 .8966
19.7 18.6 .8650
3.4 3.8 .8966
18.0 16.6 .8258
2.0 2.7 .7948
2.0 2.7 .7948
32.2 31.0 .8728
26.8
25.4
22.4
11.5
6.1
3.4
.3.1
1.4
26.8
16.6
T.8
5.1
4.7
10.2
9.8
11.2
3.7
2.0
2.0
Percentage
of Sample
"CCMPARISON BEIWEEN THE POPULATION AND THE SAMPLE
USED rn THE ARIZONA IAUS CCN!'RACI'-PIMA COUNTY"
$0
1 999
1000:;\ - 1999
2000 - 2999
3000 - 3999
4000 - 4999
5000 - 7499
7500 - 9999
10000 - 14999
15000 or over
$0
1 - 499
500 - 699
700 - 899
900 - 1099
1100 - 1499
1500 - 1999
2000 - 2999
3000 - 3999
4000 - 4999
5000· or over
Industry, Last
Base Period Einp1oyer:
Ag./Forest./Fish.
Mining
COnstruction
Manufacturing
Trans. /eann. fUtile
Who1esale/ Retail
Trade
Finance/Insurance/
Real Estate
Services
Q)ve.rrnnent
Not Given/C1assifed
Infonnation Not
Available
Characteristic
VI Base Period. Wages:
VI High Quarter Earnings:
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TABLE 10
cross TABUIATION OF AGE GIDUP BY TIME PERIOD BRIWEEN LAST DAY IDRKED AND FILING
FOR UI BENEFITS
AGE GIDUPS
I.essThan
20 20-21 22-24 25-34 35-44 45-54 55-64 65 or Over Total
ri.ne petlod # % # % # % # % # % # % # % # % # %
'lever ~rked 0 0.0 1 0.2 1 0.2 1 0.1 0 0.0 3 0.5 0 0.0 0 0.06 6 0.1
~ss Than
2 Weeks 242 53.2 232 50.9 29(i 59. 8 671 51.6 408 55.2 293 50.3 172 46.1 50 41.3 2364 51.3
2-4 Weeks 101 22.2 90 19~7 98 16.8 227 17 .5 108 14.6 79 13.6 52 13.9 16 13.9 771 16.7
4-13 Weeks 88 19. 96 21.1 124 21.3 263 20.2 158 21.4 125 21.4 81 21.7 26 21.5 961 20.8
13-26 Weeks 12 2.€ 20 4.4 39 6.7 74 5.7 34 4.6 42 7.2 35 9.4 14 11.6 270 5.9
3reater Thar
26 Weeks 12 2.6 17 3•.., 25 4.3 64 4.9 31 4.2 41 7.0 33 8.8 15 12.4 238 5.2
rarAL 455 9. q 456 9. ( 583 ·12. (i 1300 28.2 739 16.0 583 12.6 373. 8.1 121 2.6 4610 100.0
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TABLE 11; RESPONSES 'ID SURVEY QUESTIONNAIRE, PAGE 'IW), SECrION I (UNWEIGHTED)
~#
12
3
456
78
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
SECl'ION I.
~rked Did not work because;
1-34 35 hrs. Absent due Did not Accepted a . On layoff On Left Arizona Total
hrs; or rore; to. i;l.:w,ess have a jOl:> to start for less than Strike or joined of
lor vacat.ion: .. iOO:. __ within 30 days: 30 days: ,the military Responses
# % # % # % # ~ # % # % # % # %
272 5.9 234 5.1 17 0.4 - 3867 84.1 14 0.3 191 4.2 3 0.1 0 0.0 4598
300 6.5 412 8.9 19 0.4 3701 80.3 24 0.5 149 3.2 3 0.1 1 0.0 4609
358 7.8 629 13.6 19 0.4 3479 75.5 18 0.4 101 2.2 3 0.1 2 0.0 4609
393 8.5 814 17.7 21 0.5 3287 11.3 24 0.5 66 1.4 2 0.0 3 0.1 4610
429 9.3 983 21.3 23 0.5 3122 67.7 22 0.5 24 0.5 2 0.0 4 0.1 4609
458 9.9 1107 24.0 29 0.6 2959 64.3 22 0.5 22 0.5 2 0.0 6 0.1 4605
476 10.3 1187 25.8 29 0.6 2865 62.3 15 0.3 18 0.4 2 0.0 8 0.2 4600
492 10.7 1254 27.3 31 0.7 2767 60.3 20 0.4 17 0.4 2 0.0 9 0.2 4592
490 10.7 1315 28.6 34 0.7 2704 58.9 27 0.6 12 0.3 0 0.0 11 0.2 4593
517 11.3 1374 29.9 31 0.7 2613 56.9 29 0.5 19 0.4 0 0.0 11 0.2 4594
511 11.1 1450 ' 1.6 25 0.5 2547 55.4 30 0.7 20 0.4 0 0.0 12 0.3 4595
518 11.3 1524 33.2 26 0.6 2475 53.4 20 0.4 16 0.3 0 0.0 13 0.3 4592
510 11.2 1565 34.2 33 0.7 2404 52.6 31 0.7 16 0.4 1 0.0 11 0.2 4571
377 12.6 1060 35.3 22 0.7 1517 50.6 10 0.3 7 0.2 2 0.1 4 0.1 2999
377 12.6 1113 37.2 22 0.7 1464 48.9 10 0.3 4 0.1 1 0.0 4 0.1 2995
382 12.8 1142 38.1 19 0.6 1432 47.8 11 0.4 4 0.1 1 0.0 4 0.1 2995
384 12.8 1154 38.5 13 0.4 1423 47.5 11 0.4 5 0.2 0 0.0 4 0.1 2994
386 12.9 1170 39.1 17 0.6 1402 46.8 11 0.4 4 0.1 0 0.0 4 0.1 2994
378 12.6 1176 39.3 22 O.:z 1395 46.6 11 0.4 5 0.2 0 0.0 6 0.2 2993
388 13.0 1199 40.2 21 0.7 1357 45.4 11 0.4 5 0.2 0 0.0 5 0.2 2986
361 12.1 1223 40.9 26 0.9 1'357 45.4 8 0.3 7 0.2 0 0.0 7 0.2 2989
367 12.3 1244 41.5 26 o 7 1337 44.6 6 0.2 8 0.3 0 0.0 7 0.2 2995
373 12.5 1254 41.9 29 1.0 1318 44.0 7 0.2 7 0.2 0 0.0 6 0.2 2994
374 12.5 1264 42.3 22 0.7 1298 43.5 6 0.2 16 0.5 1 0.0 6 0.2 2987
379 12.7 1283 43.0 28 0.9 1263 42.3 5 0.2 19 0.6 1 0.0 5 0.2 2983
377 1,2.6 1288 43.1 30 1.0 1261 42.2 10 0.3 15 0.5 1 0,0 5 fI ? .- ?qR7
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TABLE 12: RESPONSES TO SURVEY QUESTIONNAIRE, PAGE TWO, SECTION II (UNWEIGHTED)
WEEK#
1-
2.
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
SECTION II
LooKed
Did not look for work because.
For Had a Temporary
Work: jot> that Illness or Other;
satisfied need Disabilitv~
% of % of % of % of Total Number
# ResPOnse~ # Responses i Responses # Responses of Responses
3810 86.3 25 5.7 ~1 0.9 313 7.1 4415
3630 82.8 39( 8.9 ~2 1.0 324 7.4 4386
3399 78.4 55 12.7 ~O 0.9 344 7.9 4334
~:p~ 74.4 69( 16.1 3.5··· 0.8 371 8.7 4275
2961 69.8 84 19.9 42 1.0 398 9.4 4244
2811 66.7 94 22.3 49 1.2 412 9.8 4213
. 27Q6 64.3 102~ 24.4 54 1.3 424 10.1 4209
2608 62.3 l09( 26.0 ~7 1.4 434 10.4 4189
2524 60.4 115 27.7 50 1.2 445 10.7 4176
2447 5tL9 120~ 29.Q 45 1.1 460 11.1 4156
2368 57.2 126c 30.6 49 1.2 457 11.0 4143
2306 55.7 132 32.1 53 1.3 453 10.9 4139
2265 54.9 135E 32.9 48 1.2 458 11.1 4129
1297 50.8 90E 35.5 60 2.3 291 11.4 2554
1230 48.4 94c 37.3 63 2.5 299 11.8 2541
1196 46.9 98E 38.8 61 2.4 304 11.9 2549
1183 46.4 99E 39.1 56 2.2 313 12.3 2550
1159 45.5 101 39.8 52 2.5 312 12.3 2546
1151 45.0 102 40.0 53 2.5 320 12.5 2555
1110 43.4 1054 41.2 74 2.9 322 12.6 2560
1090 42.6 106E 41.7 78 3.0 325 12.7 2561
1068 41.7 IOU 42.0 BO 3.1 335 13.1 2559
1055 41.4 1094 43.0 73 2.9 324 12.7 2546
1061 41.6 109 43.0 73 2.9 318 12.5 2549
1032 40.6 112 44.1 74 2.9 317 12.5 2544
1037 40.8 112 44.1 74 2.9 309 12.2 2542
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-56-
TABLE NUMBER 13:
Labor Force Status of All Survev Resuondents - C.P.S. Definitions (Unweighted)
blaved tJnemp layed Out-of-Labor Force Total
Week No. Number Percentage Number Percentage Number Percentage Number
1 512 11.1 3909 84.7 194 4.2 4615
2 718 15.6 3996 80.2 194 4.2 4608
3 994 21.5 3426 74.3 194 4.2 4614
4 1212 26.4- 3139 68.4 241 5.2 4592
5 1419 30.9 2904 63.3 267 5.8 4590
0-' 1571 34.3 2720 59.3 292 6.4 4583
7 1674 36.5 2594 56.5 323 7.0 4591
8 1759 38.4 2469 53.9 349 7.6 4577
9 1821 39.8 2397 52.4 358 7.8 4576
10 1906 41.6 2304 50.3 368 8.0 4578
11 1976 43.1 2233 48.7 377 8.2 4586
12 2055 44.9 2142 46.8 383 8 ..I.. 4580
13 2093 45.8 2077 45.5 395 8.7 4565
14 1448 48.5 1310 43.8 230 7.7 2988
15 1500 50.2 1252 41.9 236 /7.9 2988
16 1533 51.3 1213 40.6 241 8.1 2987
17 1544- 51.9 1101 37.0 332 11.2 2977
18 1563 52.5 1079 36.3 333 11.2 2975
19 1565 52.6 1070 36.0 338 11.4 2973
20 1601 53.9 1031 34.7 341 11.5 2973
21 1598 53.7 1029 34.6 349 11.7 2976
22 1622 54.4 1004 33.7 354 11.9 2980
23 1640 55.0 988 33.2 352 11.8 2980
24 1652 55.5 979 32.9 345 E.6 2976
25 1680 65.5 949 31.9 344 11.6 2973
26 1683 56.6 953 32.0 339 11.4 2975
I -57-
I TABLE NUMBER 14:
I Labor Force Status of Male Survev Res'Oondents - C.P.S. Definition (Unweighted)
I Employed Unemcloved Out-of-Labor Force Total
I Week No. Number Percentage Number Percentage Number Percentage Number
1 300 11.8 2173 85.5 70 2.8 2543
2 443 17 .5 2026 79.8 69 2.7 2538
I 3 590 23.2 1881 74.0 70 2.8 2541
4 780 28.0 1721 68.0 101 4.0 2530
I 5 837 33.1 1590 62.8 104 4.1 2531
6 924 36.7 1486 59.0 110 4.4 2520
I 7 982 38.8 1418 56.0 130 5.1 2530
8 1034 41.0 1348 53.5 139 5.5 2521
I 9 1071 42.5 1305 51·.7 146 5.8 2522
10 1136 45.1 1235 49.0 149 5.9 2520
11 1171 46.4 1205 47.7 149 5.9 2525 I 12 1208 47.9 1152 45.7 160 6.3 2520
13 1220 48.5 1136 45.2 159 6.3 2515
I 14- 797 50.0 694 43.5 103 6.5 1597
15 841 52.7 651 40.8 104 6.5 1596
I 16 847 53.1 639 40.1 108 6.8 1594
17 84.8 53.4 602 37.9 139 8.7 1589
I 18 866 54.6 581 36.6 139 8.8 1586
19 868 54.8 575 36.3 142 9.0 1585
20 891 56.3 554 35.0 138 8.7 1583 I 21 888 56.1 355 35.1 140 8.8 1583
22 895 56.4 546 34.4- 146 9.2 1587
I 23 908 57.2 S3T 33.8 143 9.0 1588
24 920 38.0 526 33.1 141 8.8 1587
I 25 928 58.6 513 32.4 142 9.0 1583
26 927 58.4 519 32.7 142 8.9 1588
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TABLE NU~BER 15:
Labor Force Status of Female Survev Resoondents - C.P.S. Definitions (Unweighted)
Emo1oyed Unemp10ved Out-of-Labor Force Total
Week No. Number Percentage· Number Percentage Number Percentage Number
1 212 10.2 1736 83.8 124 6.0 2072
2 275 13.3 1670 80.7 125 6.0 2070
3 404 19.5 1545 74.5 124 6.0 2073
4 504 24.4 1418 68.8 140 6.8 2062
5 582 28.3 1314 63.8 163 7.9 2059
6 647 31.4 1234 59.8 182 8.8 2063
7 692 33.6 1176 57.1 193 9.4 2061
8 725 35.3 1121 54.5 210 10.2 2056
9 750 36.5 1092 53.2 212 10.3 2054
10 770 37.4 1069 51.9 219 10.6 2058
11 80S 39.1 1028 49.9 228 11.1 2061
12 847 41.1 990 48.1 223 10.8 2060
13 873 42.6 941 45.9 236 11.5 2050
14 651 46.7 616 4.4.2 127 9.1 1394
IS 659 47.3 601 43.2 132 9.5 1392
16 686 49.2 574 41.2 133 9.5 1393
17 696 50.1 499 36.0 193 13.9 1388
18 697 50.2 498 35 •.9 194 14.0 1389
19 691 50.2 495 35.7 196 14.1 1388
20 710 51.1 477 34.3 203 14.6 1390
21 110 51.0 474 34.0 209 15.0 1393
22 721 52.2 458 32.9 208 14.9 1393
23 732 52.6 451 32.4 209 15.0 1392
24 731 52.6 453 32.6 205 14.8 1389
25 751 54.0 436 31.4 203 14.6 1390
26 755 54.4 434 31.3 198 14.3 1387
I -59-
TABLE NUMBER '6:
I Labor Force Status of All Survey ReS'Oondents - U.I. Definitions (Unwei¢lted)
I Emo1oyed: Unemp1oved: Out-of-Labor Force: Total:
Week No. Number Percentage Number Percentage Number Percentage Number I 1 512 11.2 3772 82.3 298 6.5 4582
2 718 15.7 3534 77 .2 323 7.1 4575
I 3 994 21. 7 3252 70.9 342 7.5 4588
4 1212 26.5 3005 65.6 363 7.9 4580
I 5 1419 31.0 2750 60.1 403 8.8 4572
6 1571 34.4 2577 56.4 423 9.3 4571
I 7 1674 36.6 2462 53.8 440 9.6 4576
8 1759 38.5 2359 51.6 451 9.9 4569
9 1821 39.8 2296 50.2 454 9.9 4571 I 10 1906 41.7 2202 48 .2 463 10.1 4571
11 1976 43.2 2136 46.7 464 10.1 4576
I 12 2055 45.0 2046 44.8 463 10.1 4564
13 2093 46.0 1995 43.9 458 10.1 4546
I 14 1448 48.7 118.5 39.8 341 11.5 2974
15 1500 50.4 1126 37.9 348 11.7 2974
I 16 1533 51.5 1092 36.7 353 11.9 2978
17 1544 51.9 1072 36.0 358 12.0 2974
I 18 1563 52.6 1046 35.2 363 12.2 2972 •
19 1565 52.7 1036 34.9 371 12.5 2972
20 1601 53.9 986 33.2 384 12.9 2971
I 21 1598 53.8 984 33.1 391 13.2 2973
22 1622 54.5 955 32.1 401 13.5 2978
I 23 1640 55.1 952 32.0 384 12.9 2976
24 1651 55.5 941 31.8 377 12.7 2975
I 25 1679 56.5 917 30.8 377 12.7 2973
26 1682 56.6 921 31.0 369 12.4 2972
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TABLE NUMBER 17:
Labor Force Status of Mal e Survey Rescondents - u. r. Defini tions (Unweighted)
Employed: Unemcloved: Out-of-Labor Force: I01:al:
Week No. Number Percentage Number Percentage Number Percentage Number
1 300 11.9 2101 83.3 122 4.8 2523
2 443 17.6 1941 77 .2 131 5.2 2515
3 590 23.4 1788 70.9 145 5.7 2523
4 708 28.1 1668 66.2 145 5.8 2521
5 837 33.2 1531 60.8 151 6.0 2519
6 924 36.8 1428 56.8 161 6.4 2513
7 982 38.9 1360 53.9 181 7.2 2523
8 1034 41.1 1304 51.8 178 7.1 2516
9 1071 42.5 1271 50.5 177 7.0 2519
10 1136 45.1 1203 47.8 178 7.1 2517
11 1171 46.5 1167 46.3 181 1.2 2519
12 1208 48.1 1112 44.3 190 7.6 2510
13 1220 48.8 1100 44.0 182 7.3 2502
14 797 50.3 643 40.6 145 9.1 1585
15 841 52.9 603 37.9 145 9.1 1589
16 847 53.3 591 37.2 150 9.4 1588
17 848 53.4 588 37.1 151 9.5 1587
18 866 54.6 568 35.8 151 9.5 1585
19 868 54.8 564 35.6 152 9.6 1584
20 891 56.3 536 33.9 155 9.8 1582
21 888 56.2 534 33.8 157 9.9 1579
22 895 56.5 S2Q 32.8 169 10.7 1584
23 908 57.3 S2Z 32.• 9 155 9.8 1585
24 920 58.0 514 32.4 151 9.5 1585
25 928 58.7 501 31. 7 152 9.6 1581
26 927 58.5 506 31.9 151 9.5 1584
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TABLE NUMBER 18:
Labor Force Status of Female Survev Respondents - V.I. Definitions (Urtweighted)
Emp1oved: Unemployed: Out-of-Labor Force: Total:
Week No. Number Percentage Number Percentage Number Percentage Number
1 212 10.3 1671 81.2 176 8.5 2059
2 275 13.3 1593 77 .3 192 9.3 2060
3 404 19.6 1464 70.9 197 9.5 2065
4 504 24.5 1337 64.9 218 10.6 . 2059
5 582 28.3 1219 59.4- 252 12.3 2053
6 647 31.4 1149 55.8 262 12.7 2058
7 692 33.7 1102 ·53.7 259 12.6 2053
8 725 35.3 1055 51.4 273 13.3 2053
9 750 36.5 1025 50.0 277 13.5 2052
10 770 37.5 999 48 .6 285 13.9 2054
11 80S 39.1 969 47.1 283 13.8 2057
12 847 41.2 934 45.5 273 13.3 2054
13 873 42..7 895 43.8 276 13.5 2044
14 651 46.9 542 39.0 196 14.1 1389
15 659 47.6 523 37.8 203 14.7 1385
16 686 49.4- 501 36.0 203 14.6 1390
17 696 50.2 484 34.9 207 14.9 1387
18 697 50.3 478 34.5 212 15.3 1387
19 697 50.2 472. 34.0 219 15.8 1388
20 710 51.1 450 32.4 229 16.5 1389
21 710 50.9 450 32.3 234 16.8 1394
22 727 52•. 2 435 31.2 232 16.6 1394
23 732 52.6 430' 30.9 229 16.5 1391
24 731 52.6 433 31.2 226 16.3 1390
25 751 54.0 416 29.9 225 16.2 1392
26 755 54.4 415 29.9 218 15.7 1388
I -62-
I TABLE NUMBER 19:
PERCENTAGE OF RESPONDENTS SURVIVING IN
I EACH SURVEY WEEK BY SEX (WEIGHTED)
Week
I No. Male Female Total
1 84.8 83.4 84.2
I 2 77.0 79.4 78.1
3 70.1 72.2 71.0
4 63.6 64.9 64.2 I 5 58.3 58.6 58. t,
6 54.2 53.3 53.8
I 7 50.5 49.6 50.1
8 48.0 47.0 47.5
I 9 45.9 45.1 45.5
10 42.3 43.2 42.7
I 11 41.0 41.3 41.1
12 38.6 38.7 38.7
I 13 37.3 36.3 36.8
14 34.0 35.5 34.7
15 31.5 34.2 32.7
I 16 30.1 32.2 31.0
17 28.2 27.6 27.9
I 18 21.2 27.5 27.3
19 26.5 27.1 26.7
I 20 25.6 25.7 25.6
21 25.1 25.5 25.3
I 22 24.7 24.8 24.7
23 24.0 24.1 24.1
24 23.5 24.1 23.7 I 25 22.7 23.4 23.0
26 22.8 22.8 22.8
I No. Resp.
Week 1
(before weighting)= 2543 2072 4615
I No. Resp.
Week 26
(before weighting) = 1882 1568 3450
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1 -63-
TABLE NUMBER 20: 1 PERCENTAGE OF RESPONDENTS SURVIVING IN
EACH SURVEY WEEK BY ETHNIC GROUP (WEIGHTED)
1 Week
No. White 'Black Hispanic Indian Asian Unknown
1 84.0 B5.6 83.9 85.6 75.8 88.8 1 2 77.6 78.4 77 .8 84.1 68.1 88.8
3 69.3 75.3 72.1 80.5 73.9 88.4 I, 4 62.2 69.4 66.4 72.6 71.9 70.9
5 56.0 61.2 62.0 68.9 56.1 67.9
1 6 51.6 55.9 56.1 65.9 56.1 65.7
7 47.6 54.8 53.0 61.0 43.8 63.0
1 8 44.8 55.4 50.9 57.3 43.8 64.8
9 43.2 54.3 48.0 54.4 38.3 49.0
I 10 40.1 49.7 46.8 50.4 38.3 44.5
11 38.2 46.6 46.2 49.6 38.3 46.4
12 35.9 43.2 43.9 45.6 38.3 46.6 1 13 33.9 39.3 42.7 45.0 38.3 46.0
14 32.2 35.1 41.1 38.1 36.0 42.7
1 15 30.6 34.4 38.0 35.9 30.9 36.6
16 28.5 36.8 36.7 34.5 25.9 30.4
I 17 25.2 32.4 34.1 32.9 21.9 30.4
18 24.4 32.2 33.8 31.5 43.8 30.4
1 19 23.7 32.6 33.6 30.6 38.5 30.4
20 22.7 30.1 32.5 30.7 16.6 36.6
I 21 22.4 29.1 31.9 30.6 16.6 36.6
22 22.3 28.0 30.5 27 .. 4 21.9 36.9
23 21.5 29.9 29.4 28.8 16.6 36.9
I 24 20.9 30.0 29.8 27.6 16.6 36.9
25 20.6 29.3 27.8 26.3 16.6 36.9
I 26 20.5 28.6 26.6 2.8.9 16•.6 31. 3
No. Resp.
I Week 1
(Before
Weighting)= 2774 222 1153 422 19 25
1 NO~Resp.
Week 26
(Before
Weighting) = 2093 153 '3889 290 13 12 1
1
TABLE NUMBER 23:
EQUATIONS ESTIMATED FOR EACH
COt.JNTY OF THE FORJ.\f
.0058038 .0004342
.002355 .0001693
.0030661 .0006090
.0045808 .0006643
.0031526 .0018483
.0353265 .0017074
.0010076 .0001579
.0046916 .0008743
.0031599 .0005634
.0014870 .0002157
.0025836 .0002082
.0066023 .0008759
.0025240 .0003920
.002525 .0002727
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I COtJNTY
I APACHE
COCHISE I COCONINO
I GILA
GRAHAM
I GREENLEE
~.ARICOPA
I MOHAVE
I NAVAJO
PIMA
I PINAL
SANTA CRUZ
I YAVAPAI
I YUMA
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Y = 1
a + bex)
. Y-INTERCEPT TERM REGRESSION COEFFICIENT
PLANNING
DISTRICTS-
1 .8Z9 .926
Z .850 .920
3 .870 .941
4 .829 .944
5 .856 .940
6 .847 .950
APACHE .340 .952
COCHISE .853 .955
COCONINO .892 .940
GILA .861 .937
GRAHAM .789 .937
GREENLEE .806 .958
MARICOPA .829 .926
MOHAVE .827 .933
NAVAJO .874 .939
PIMA .850 .920
PINAL .854 .941
SANTA CRUZ .886 .936
YAVAPAI .869 .930
YUMA .830 .948
-67-
TABLE NUMBER 24:
WEEKLY SURVIVAL RATES FOR
COUNTIES AND PLANNING DISTRICTS
SURVIVAL RATE TO BE APPLIED
TO SURVIVORS FROM PAST WEEKS
SURVIVAL RATE FOR
COUNTY INITI.At WEEKS
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TABLE NUMBER 25:
CHANGE IN OOUNl'Y UNEMPWYMENr RATES
DUE TO THE INCLUSION OF INELIGIBLES
(FOR THE WEEK INCLUDING JULy 12, 1979)
Handbook ----Estimate +neligibles+- C.P.B.-c.P..S. Revised ChaIlge
Estimate of Handbook Labor Unemployment Unemployment In
of Surviving Estimate of Force Ratc~ Rate (With Unemployment
County Unemploynent* Inel~gi.p1~§ __ Unemplo~t Estimate* u Ineligibles) Rate
Apache 1,600 110 1,710 13,984 15.87%' 15.84% +.03%
Cochise 1,270 250 1,520 23,777 7.41% 8.20% +.79%
Coconino 1,418 106 :1.,524 28,333 6.94% 6.96% +.02%
Gila 797 88 885 13,765 8.03% 8.30% +.27%
Graham 382 56 438 6,578 8.06% 8.57% +.51% I
Greenlee 122 22 144 3,922 4.31% 4.73% +.42% 0\
ex>
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Maricopa 20,811 1,063 21,874 632,364 4.56% 4.48% -.08%
Mohave 735 64 799 17,988 5.77% 5.75% +.09%
Navajo 1,559 106 1,665 21,370 10.12% 10.09% -.03%
Pima 5,909 371 6,280 184,471 4.44% 4.41% -.03%
Pinal 1,342 225 1,567 26,794 6.95% 7.52% +.57%
Santa Cruz 687 62 749 7,469 12.76% 12.95% +.19%
Yavapai 768 54 822 25,658 4.15% 4.15% .00%
Yuma 2,325 253 2,578 31,159 10.35% 10.67% +.32%
*The Labor Market Infonna.tian SeGtion of the Arizona Depa.rtrrenb of Econanic Security provided;~ data for
these columns.
CONTINUED ON OTHER SIDE
Phone Number _
A person is considered as "looking for work" if any of the following activities are undertaken.
1. According to the definition above, did you "look for work" at any time during
the four weeks prior to
DYes DNo
SURVEY QUESTIONNAIRE
ARIZONA DEPARTMENT OF ECONOMIC SECURITY
Check (./ ) only one box.
Registering at a pUblic or private employment office;
Meeting with appropriate employers;
Checking with friends or relatives;
Placing or answering advertisements;
Writing letters of application;
Being on a union or professional register; or
Investigating possibilities for starting a business or
professional· practice.
Work one or more hours for salary, wages, tips,
or for meals, living quarters or supplies
received in place of cash wages;
-or
Work 15 or more hours without pay in a family
operated business or farm.
-69-
APPEND IX nlO
RS-111 (7-7')
A person is defined as "working for payor profit" if they:
Use these definitions in answering the following questions.
If any of the following information is incorrect or missing,. please make the necessary changes or
additions.
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APPENDIX TWO (continued)
There are two sections to the table below. During each week listed, you either worked or did not work
and at the same time you either looked for work or did not look for work. For each week listed, please
check (II one box in Section I to indicate whether you worked or did not work during that week. Then
make another check in Section II to indicate if during that week you were "looking for work" or not.
Please remember to use the definitions which are given on the front page to determine if you should be
considered as "working" and/or "looking for work." NOTE: each week begins at 12:01 a.m. Sunday
and ends at 12:00 p.m. Saturday.
Following is an example of how the table is to be filled in.
Example: During the week beginning on January 7,1979, John did not work and he was looking
for work. (See line A)
On January 16, 1979, John started working 20 hours per week and during that time he
was still looking for full-time work. (See line B)
On January 19, 1979, John was laid-off permanently from his part-time job but he did
not look for work for a week because he was sick. (See line C)
John started a full-time permanent job on January 31, 1979 and did not look for work
because he was satisfied with his full-time job. (See line D)
Week SECTION I. SECTION II.
Beginning
Worked Did not work because, Did not loOk for work because,
On, 1-34 35 hrs. Absent Did Accepted On LOOked Had a Tempo- Other
hrs. or due to not a Job to layoff for job that rary
more Illness have start for less work satisfied Illness
or a within than need or
vacation job 30 days 30 days Disability
LineA, Jan. 7, 1979 I I
Line B: Jan. 14, 1979 I I
Line C, Jan.21,1979 I I
Line 0: Jan.28,1979 I I
For each of the following weeks, please check Only ONE box in Section I and Only ONE box in Section II as indicated in
the example above. If you cannot remember exactly what you did each week please give us your best guess.
Have you checked only one box for each week listed in Section I and only one box for each week listed in Section II?
Date Questionnaire Completed'
APPENDIX THREE
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,
COUNTIES &~ PLANNING DISTRICTS
L'f ARIZONA
Plannin
Distrtc
III
APACHE
CaCHISE.
Planning
Dis"tric-c
VI
Planning
Distric"t
VI
GRAHAM
NAVAJO
Planning
District
III
CQCQNINO
Planning District
III
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