Continuation of NLS Discussion Paper 93-16
Part 3 of 3
This version of the paper was split for web delivery.
Appentix
This appendix
andyzd
in this study.
selection
criteria
the construction
A.1
desctibes
tie procedures
The tit
A
used in the conswction
section briefly describes
appfied in choosing
of tie variables
the analysis
contained
of tie data set
the data set and details the
sample.
The second section describes
in the arrdysis
data set.
The Saple
The data used in tils study are from the first ten rounds of the National
Longitudind
chosen,
SuWey - You% Cohort (NLS~.
nationtiy
representative
The NLSY
covers both a_randomly
sample of 6,111 young pople,
and a supplemented
mmple of 5,295 Black, Hispanic, or economically disadvm~ged
youth. The investigation
respondents
from boti components
of age as of January
beginning
concentrates
1, 1979.
on the labor market
of this survey.
experiences
of male
These young men were 14 to 21 years
The youths themselves
in 1979 and information
non-Hispanic, non-Black
w~re interviewed
about the labor market
men is drawn from the fust ten rounds of the ~Y
experiences
covering
annually
of these young
the years 1978 to 1988.
—
This paper analyzes a data set of 2,699 young men drawn from the nationally
representative
sample of the NLSY and the supplement
The economically
Hispanic
men.
excluded
from the analysis data set because there are a number
way his supplemental
disadvantaged
~mples
sample was originally
non-Black,
constructed.
A-1
of young Black and
non-Hispanic
sub-mmple
of shortcomings
This exclusion
ti the
restriction
is
rduces
~Y
the avtiable
@ 4,837.
other screens.
sample size from the 5,579 men in the non-dtary
kclusion
The fist
in the analysis
screen required
first ten rounds of tie NLSY.
.
.
3,744 young men.
sampIe dso rquired
Table A. 1 details the number
a man’s experiences
an individud
of men drop~
1988 interview
date to be included
left school sometime
mpIe
from 4,837 to
from the analysis
F~y,
from the first time he permanently
must have permanently
in every year of the
reduces tie analysis
sample by the year in which tiey first missed an interview.
captutig
a young man to pass @o
the person to be interviewed
This restriction
samples of the
to ensure we are
enters the labor market
..
bew=n
January
1978 and the
in the analysis data Wt. This last screen ehminates
1,W5 men from the data set.
To determine
if these selection
young men, Table A.2 presents
our analysis
A.2
a breakdown
data set by sample component
rable suggests
repr=ented
rules result in an “unrepresentative”
tiat our analysis
of tie male respondents
and racial origin.
sample is representative
sample of
in tie NLSY and
A casual survey of this
of tie male population
in the entire NLSY.
The Variables
The variables hat enter into the data set analyzed in this study an
five categories:
participation
(1) labor market experiences;
in other educational
and (5) demographic
variables.
programs;
be grouped
(2) regular school attendance;
(4) sources and amount
Each subsection
A-2
(3)
of no~abor
below details the construction
into
income;
of tie
specific variables witkin these categories.
and mnnirrg through
the week of the 1988 interview
weeMy series are combined
anrdyses reporti
combine
A wee~y series beginning with January
in various
in the main bdy
the wee~y
ways to construct
of the paper.
series are outirred
is cmti
for every variable.
1978
These
the dara sets for the empirid
The specific
metiods
we use to
in the relevant section of the paper.
.
A.2.1 Labor-Market
The WY
Experience
provides an exhaustive
experiences
of youths.
information
co~ected
wage rate.
This detailed information
youti
The specific data tit
jobs.
Specifically,
is obtained
respondents
the usual wee~y
hours and the usual
for every significmt
job held by the
are not asked these detailed questions
less
is missing for tkis job unless it is the main
date, or it is not part of a government
these detailed questions
for
for a job held for less than nine weeks or involving
tian twenty hours per week, wage information
job at the interview
about the labor market
are relevant to this analysis include the
on tie dates of employment,
from 1978 on; however,
extraneous
amount of information
are not asked if the respondent
training program.
is less tian
In ad=dition,
16 years of age at tie
time of tie interview.
Even tkough tie earnings
account
for a negligible
two approaches
and hours
of work
from
fi?!e
fraction” of totil !abor income and,hours
to impute any missing
information.
ex~aneous
shotlld
of work, we explored
The first method imputes a missing
wage rate and/or hours of work for a specific job by using available
A-3
jobs
information
regarding his job from other survey ywrs.
Specifidy,
if the respondent worked at tie
same job in any ofier year of tie survey and he reported a value corresponding to tie
missing
wage rate/hours
variable.
of work information,
&is value is used in phce
h tie mse of a missing wage rate the imputed
gened
changes
in wages.
The adjustment
of the missing
value is adjusted to account for
factor we used to deflate or inflate the value
.
is baa
on tie observed
analysis
~ple.
reported
annti
y-
to year percentage
The second approach
earnings
and hours of work information
reported
in Meron,
alternative
measures
of annual quantities
this approach
hours of work.
Therefore,
Missing
information
allow us to m~e
employment
kdividud
reported
Gri@ and MaCurdy
to compare
resulted h numerous
irrformation
from the
uses the self-
in the survey.
In pardcular,
tie
(1989) are used to construct
to the reported
negative
values.
value: for wage rates and
we only use the first method to impute any missing values.
concerning
the distinction
the hourly
wage rate at a specific job does not
between low-wage
that is a critical feature of our analysis.
employment
Thus,
and high-wage
we are forced to drop m
from the analysis sample the first time after he holds a job that does not have a
or imputed
wage rate.
tidividual
permanently
low-wage
and high-wage
the labor market.
missing
in hourly earnings
to impute missing
procedures
Unfortunately,
changes
Missing wage_ information
leaves school are ignored because
employment
For example,
experiences
for jobs held before the
the analysis
of men after they permanency
consider a young man who acquires
wage four years after. leaving school.
A-4
only examines tie
enter
a-new job with a
This map’s labor market experiences
for
tie fist fotrr years are includd
in tie sample amdyzed ti tie paper; however, arty
experiences after the date he frost heId this job are excluded from the ansdyses.
We crmte eight wee~y
employment
experiences
employment
(i.e.,
dutiag
of respondents
the repoti
a job as either low-wage
wage rate is below the low-wage
Conversely,
analogous
of low-wage
in the paper.
threshold
employment.
For every job held
W tie reported
a job is considerti
low-wage
the job is cksified
There are four series to summarize
(1) the number
and high-wage
or imputed wage rate to fie relevant
or high-wage
series to capture high-wage
series are
presented
if the wage is above the threshold
employment.
the low-wage
for each of tie two conmpts
the LQ and M thresholds)
a week we compare
chssi~
series to characterize
experiences.
low-wage
in all low-wage jobs that have a valid measure
(2) the total number
or imputed
of hours;
number
of low-wage
jobs that have a missing value for hours of work.
provide
information
on the extent of multiple job holding,
between
low-wage
low-wage
and four
the four low-wage
of low-wage jobs held during the week;
weeMy earnings
the division
on a wee~y
basis.
A-5
value; (3)
and, (4) the
These eight series
of hours of work
and high-wage jobs, and &e fraction .of total earnings
employment
or imputed
as high-wage
In particular,
in low-wage jobs that have either a repo~ed
to
employment.
experiences,
of hours worked
tireshold
derived
from
A.2.2 Re@lar
Reguh
School Attendance
schooling refers to education
activities designed to culminate in tie
award of a high school diploma or a college degree.
generaUy be available in primary/secondary
These diploma/degree
schools, communityfiunior
programs till
colleges, 4-year
.
colleges and universities.
.
information
whetier
With regard to reguti
relating to participation
tie respondent
k regula
is currentiy
ht
interview,
the highest grade completed
school diploma
received
in school, if the individud
the highest grade attended
and the last date of attendance
attended school since tie last interview.
In addition,
information
was emolld
if enrolled
in
since the
enroIIed but he
is collected
and whether he has obtained
sine= the last interview,
obtains
including
if the person is not currentiy
by the respondent
or a GED certificate
the NNY
schooIing at each interview
enrolIed
school at any time since the last interview,
school attendance
regarding
either a high-
as well as the month he
the djploma/cerdficate.”
Two weetiy
respondents.
The first series summarizes
prior to each week.
the respondent
otherwise.
series are created to summarize
We cannot determine
we use a simple assignment
tie reported
of an indicator
vatiable
activities
of participation
scheme based upon schooling
Specifically,
that equals one if
week and zero
in regular schooling
stahls at the interview
if tie individual
of
by the respondent
reguIar school during a particular
the exact week
last date of attendance.
at an interview
the highest grade completed
The second series consists
is classified as attending
the regular schooling
was enrolled
date and
in school
date, the series is set equal to one for each. week since the last interview
A-6
so
w=k Qanuary 1978 for tie fust interview) including tie current interview
Further,
if the respondent
the kt
interview,
Accordingly,
is not enro~ed at tie titerview
we cart only determine
but he has attended
the last month he was enrolld
as long as the reported last rJate of atindance
the hst full week in the monrh of last attendance.
above conditions
are met, the series is equal to =ro
school since
in school.
is after tie last interview
date, tie series is set equal to one for each week since the hst interview
kcluding
week.
)
Finafly,
week up to and
if neither of tie
for each week since the kt
interview.
A.2.3 Participation
in Other Educational
NLSY respondents
otier
are dso asked about their participation
than regular schooling.
several government
of privately
provided
vocational
schools.
Programs
These other educational
training programs
training including
(e.g.,
CETA,
programs
JTPA,
formal company
To be included in this category
in educational
primarily
programs
consist of
Job Corps) and a wide varie~
training programs
of educational
activities
as well as
the training
program must last at least four weeks but it _does_not have to result in any formal degree
or certificate.
The training data obtained at each annual
particip~tion
in training programs
interview
before 1978, tie beginning
spells that occur after January
1978, the respondent’s
program,
the occupation
the type of program,
consists of information
A-7
and ending dates of training
success in completing
being trained
on
the training
for of applicable),
and the
usti
number of hours per week s~nt in the program.
role training plays in determining individuds’
single weeUy series to summarize
Specifically,
we create a weetiy
one if tie person is participating
Although we m
interesti
employment ex~nences,
the training activities
series consisting
of the young
of an indicator
in either a government
we create a
men in our mpIe.
variabIe
or private
in the
fiat is. equal to
mining
program
during a given week.
A.2.4 Sources and Amount of Nonlabor
To constict
amount
during
tie tables in Section 3 of”the paper we require
of nonlabor
about numerous
concerning
unemployment
or fati
annual
income,
alimony
payments
or sources.
information
is obtained
from each source
and other members
covering
educational
Alternatively,
and child support
from government
Further,
labor market earnings,
compensation,
or sources.
annurd fiformatiori
on the
of the
These “measures include income from unemployment
persons
a spouse’s
At each interview
year for both the respondent
the cash value of transfer
of the interview,
persons
calendar
business
income from otier
.
by source.
infofiafion
sources and tie amount of income derivd
household.
compensation,
benefits,
income
income
the previous
respondent’s
Income
business
benefits,
if the respondent
A-8
welfare
if the respondent
the previous
payments,
programs,
was married
calendar
y=r
or farm income,
and
at the time
is aIso obtained
income from
and income received
was cohabitating
educatiomd
from other
with an opposite
sex adult as a p-er
hcome receivti
at tie time of tie intewiew, information is co~ected about the toti
by Ms person ti We previous
We create tiree
wee~y
first series ctictetis
including
series to capture otier
tie nonlabor,
sources.
durational
sex adult p~er.
government
Food Stamp Program
assistance”
~SP)
(OPA) programs).
quantities
(i.e.,
and Supplemental
The measures
other income series,
annual measures.
kcome
Aid to Families
and we use a simple averaging
respondent’s
the toti
The procedure
wee~y
from three
with Dependent
Children
Security
hcome
and/or any
that enter into the fist
scheme to assign wee~y
If the respondent
in the past year.
at tie last interview,
two. series are annual
amounts.
For tie
is married during the previous
If the respondent
to~l income for the
is not married
at the time of the interview
but hving with
and he was hving witi a
the second series is equal to 1/52 of the partner’s
income in each week of the previous
conditions
“other pubhc
used for the second series depends upon the household
year, the second series is equal to 1/52 of the spouse’s
partner
(AFDC),
income is equal to 1/52 of the sum of the
calendar
sex adult as a partner
or
spouse or
transfer ticome
duting the relevant week.
an opposite
The
alimony
persons
of a respondent’s
structure
weeks he was married
income.
busirress or farm income,
benefits and income from otier
The third series mptures
welfare programs
sources of household
income of the male respondents
compensation,
The second series summarizes
opposite
-’
nontransfer
income from unemployment
md child support payments,
crdendar year.
calendm
year.
Finally,
if neither of the above
are met, the second series is set equal to zero for the entire 52-week
A-9
total
period
covetig
the relevmt
calenti
basis and we can determine
amount
Data for the Mid
year.
the exact months
for toti welfare benefits.
of remipt
Thus, for each w=k
series are recorded
on a monthly
as we~ as an average
monWy
tiat begins during a particuti
~
month the third series is equal to the sum of the toti benefits received during tiis monti
.
divided
by 4.3 to obtain an average
A.2.5 &rn-ographlc
The ~Y
demographic
age and his
wee~y
amount
of transfer
income.
Variables
provides so extensive amount of demographic infomtion.
variables
of interest
racial origin.
for our analysis
The WY
are tie marital status of tie man, his
collects data at each interview
and year of any change in marital status since the last interview.
information
not only on marriages
and the death of a spouse.
seIf-reported
respondent
and divorces
but dso
on
regarding
the month
These changes include
separations,
reconciliations
With respect to age and racial origin, tie respondents
their date of birth and we base heir
to a specific sample component
components
The
are: non-Hispanic,
non-Black
racial origin upon the assignment
in the ~SY.
(referred
Specifically,
of the
the three ~mple
to as White in tie paper);
Black; and
Hispanic.
We create three weekly series of demographic
an indicator
variables.
The fust series consists of
variable tiat equals one in a given week if tie respondent
being
married
with their spouse present and zero otherwise.
variable
is set to one in the first week of the month an i.ndivid!i.al reports a marriage
A-10
For-ins~nce,
reported
this indicator
or
reconctition
scp~tion
and remains qual to one until We next tie
or dati
years and montis
of a spouse.
he reports a divorce,
The second series measures
in each week horn January
1978 to tie last interview
tie tiird series is simply the raciaI origin of tie respondent
pried.
tie age of tie respondent
~~
.—
A-11
week.
and is consbnt
in
Finally,
over tie entire
Table A.1
Y-c
.
of btemi&
Numhr of Ob=matiom
for Mising
Deletd
htew”iew”
Num&r
of Ob=mtiions
Remining
1979
--.
4837
1980
210
4627
1981
92
4535
1982
89
~.
4446
i984
106
42S5
1985
125
4160
1986
139
4021
1987
15s
3863
1988
119
3744
.
1983
4391
Table A.2
Sample Component
Origin
Rmdom
md Racial
R~dom
1394
(51.6)
Sample, Black
346
(7.2)
192
(7. 1)
Sample, Hispmic
218
(4.5)
109
(4.1)
Sample, Black
1105
(22. 8)
636
(23.6)
Sample, Hispanic
729
(15. 1)
368”
(13.7)
Supplemental
Supplemenhl
Num&r of Ob=wations
halysis
Sampleb
2439
(50.4)
Sample, non-Hispanic,
non-Bl=k
Rmdom
Number of Obsewations i“ Enti~
NBY Sampie=
a The number in parentheses
from each sub-sample.
is dre proportion
in
of the original sample of the NLSY men
b The number iri parentheses is the proportion from each sub-mmple of tie original
sample of tie NLSY men interviewed in each of the 10 years and who permanently
entered the labor market after Jamlary 1978.
A-12
Appendix B
This appendk describes the empirid
tie comprehensive
picture of the Iabor market experiences
main body of the paper.
describes
the empirid
charactetie
market
empirid
~is
appendix
specifications
contains
empIoyed
the amount of time an individual
statuses
outied
continuously
in Section 2 of the paper.
enmrs each of the alternative
& Econometric
Framework
number
for Estimating
of weeks in a particular
status.
A formulation
for the duration
@l)
fi(c)=
of’ young men prFsen—ti in the
The first subsection
the spell distributions
occupies ach
that summarize
hration
the Wehhood
that
of the five labor
The second subsection
probabilities
to cons~ct
specifies
the
tie lkehhood
statuses give”n he has left a particular
A duration distribution characterizes
specific
that are estimated
two subsections.
to estimate
model used to estimate the entrance
an individud
B.1
specifications
statis.
D:stributiom
an individual
experiences
a
labor market status given initial entry into the
distribution
is given by
S,(T - 1)[1 -Pi(c,al,
with
,-1
@.2)
where Pi(t, Z) represents
on the: variables
~j(~) specifies
—
Si(r -1)=~ Pi(fa,
*=1
the probability
of continuing
t and Z , and i designates
tie probability
that duration
in a partictdar
an arbitrary
in stiws
B-1
i
statis
labor market status.
that conditions
The function
will last exactly ~ weeks for
tidividuds
function,
characterized by attributes Z. The quantity Si(7- 1), referred
represents
the probabfity
that tidividuals
with attributes
to as tie survivor
Z WN experience
at
least ~-1 weeks in statusi.
Speci@ing
pardcular
,
the likelihood
labor market status,
at Ore end of the observation
framework
observing
for estimating
that amanexperiences
recognizing
period fi.e.,
the duration
asequence
the possibility
ofweeks
tbathemay
sti~bein
tie spe~ is right censored),
distribution
a spefl of length T for an individual
ina
provides
that status
a
in status i. The Likelihood of
with attributes
Z is
T-1
@.3)
(T,z)
L,
= ~ Pi(i,z)
*=1
where c = 1 if tie spell is right censored
estimates
of the transition
must implement
weighted
nonrepresentative
samples
likehhood
of observing
a Iog-hkelihood
finction
probabilities
maximum
included
a particular
[1 -Pi(T,z)]’-”
,
and = O otherwise.
To obbin
Pi(t,Z) that determim
likelihod
methods
in the NLSY.
duration
unbiased
tie duration
to account
Introducing
we
for the
weights
for an individual
distributions
(u) into the
with attributes
Z results in
of
T-1
@.4)
h Li(T,z)=
{
M=imizing
~ 0, qPi(tz)]
f=I
the sum of the individual
parameter
+ W,(c-I)
contributions
individuals
yields consistent
distribution
witi a known variance-covariance
h[l
-P,(TZ)]
.
}
estimates
represented
rhat possess
by @.4) over spells and
an asymptotic
matrix (see Amemiya
B-2
normal
(1 985) pp. 3 19-338).
h tie specification of the probabilities
Pi(t,Z), tie variables Z are set at the time
of entry into the status, sod tie variable t represents the level of duration in s~tus i
The Hterature terms the influence oft on Pas
accurmdated up to the point of evaluation.
duration
dependence
function oft,
fmture
data atiysis
rutirrg out simple parametic
this prelimtiary
irrdividud
and exploratory
data tiysis
attributes
suggests
Z and the pattern
formulations
here
one of the most popular
The following
that P is a higtiy
of duration
are sophisticated
of duration
of the dah rules out “propordonal
represents
reveak
hamrds”
dependence.
interactions
dependence.
nordinear
betwwn
Accounting
as a specification
Fufier,
.
for this latter
for P, which
choices in the literature.
logit specification
for tie probabilities
Pi(t,Z) incorporates
tie
desired features:
Pj(t,z) =
where 21 and ~ are vectors of variables
appropriately
dimensioned
parameter
1
~ + ~zlb,+8AfA.uf) ‘
made up of the atibutes
vectors,
and the finction
Z, 8; and ai are
gi(t,~.,~i)
is
:iven
by
KI
g[(~Z23ai)= ~
j=
The quantities
[@,j(t)-_~ij_,(t)]
@ij(t) denote the cumulative
variable possessing
smooti
i
mean K,j and variance
spline function that determines
spent in labor market status
[
distribtltion
atioz2 + ray,] .
function
(cd~ of a norrnd
a ‘ii and their inclusion
the duration
i.
B-3
properties
in gi(*) results
associated
random
in
a
with the time
-..
To understand the nature of tiese spkes,
consider the properties of g(*) which
Wow for increasing, decreasing or non-monotonic
presence of the cdfs
in @.@ incorpotites
mijo~- + t au, represents
,
~
“~lows. *e pa~ms
gi(=l
forms of duration dependence.
spfie
fmtures
gi(*) over only a prespccified
of dumtion
de~ndence
The
in ~(*T”so that the polynomial
rmge
oft and the inclusion
of Zz
to vaw ac~o~ding to ~1 tie a~bu@s
.,
.
included
in tils vector of variables.
tie moment
particular,
To describe
hat ~ consists .ordy of an intercept
suppose
and set gi~)
the basic properties
~.e.,
~ijo ~
of gi(*), suppose for
+ t aij, = aijo + t aij,).
one wishes to set gi(*) = ai,o + t ~il, for values oft be~een
= &no + t aul for values oft
create a specification
between
for the three srandsrd
the cdfs
deviations
imply that the quantity
assign <
= 2 in @.6); fi
aio , Ci, , and ua.
These choices for tie p’s and the a’s
@i,(t) - @iO(t)= 1 over the range’ (O, t.) and = O elsewhere,
@a(t) - @i,(t) = 1 over the range (t”, P) and = O elsewhere.
giP)
fie
desired
Propefly
and
it
is
differentiable
tie ~j’s and the &ij’s set in. advance of estimation,
parameters
ai and bown
polynomial
begins and ends by adjusting
control
how quic~y
higher
values providing
the
as HiO = O, Pi, = t=, pa = t“; and pick sma~ values
the quantity
possess
O and t“
t. and an upper bound of t“. To
of gi(*) that satisfies this property
three” means determining
In
finctions
oft and Z?.
in
t.
Fu~er,
the
values
of
One mn control where mch spline or
each spline cuts in and out by adjusting
for .a more gradual and smoother
B-4
The finction
gi@) is stricfly hnear in the
the values of the pii’s.
to tie next.
with
and
Similarly,
one can also
the values of the g ‘ij’s, with
transition” from one polynomial
Pre_
analyses of tie &plarr-Meier
hazard finctiotis suggest & = 5 for
each of tie five labor market stamses: low-wage employment (t); high-wage employment
(h); simultaneous employment in both a low- and high-wage job (b); training activities
(e); and nonemployment
(n). Table B. 1 presen~ the prespecifid
and &u ‘s. Separate “empirid
tiyses
are conducted
vaIues of tie five
for tie four education
~j’s
categories
.
s
denoted
in the paper and the Pij’s and u Zij’s are me -e
Further,
extensive
testig
indicates
the nu~ hypothesis
rejected at conventiorrd
significance
imposed
on” the parameters.
this restriction
for d
ducation
cak~ories.
-.
of ~ijl = O for au i and j cannot be
leveIs and all of tie estimated
duration distributions
Table B.1
Means and Standard
hbor
Deviations
of Smooth Spline Functions
in Duration
Distributions
p. , co
P1 , al
k- > U2
P3 , a3
P4 , U4
Ps , ~s
e
o, 0.1
8, 1.0
20, 2.0
50, 4.0
100, 8.0
lWO, 1.0
h
o, 0.1
15, 1.0
50, 2.0
100, 4.0
200, 8.0
1000, 1.0
b
o, 0.1
4, 0.5
8, 0.5
20, 2.0
40, 2.0
1000, 1.0
e
o, 0.1
8, 1.0
20, 2.0
50, 4.0
100, 8.0
Im,
1.0
n
o, 0.1
4, 0.5
12,
30, 2.0
80, 4.0
1000,
1.0
Market
Status
The effeck
of tie covariates
Bi’s equal to zero for au i.
1.0
Z are incorporated
In addition
to an intercept
B-5
entirely
through
~
@rnr, the empirical
by setting the
results in
reported in the pa~r
include WO distinct sets of variables in the covariates Z-:
demographic characteristics represented by X; and variables H that summarize an
individurd’s particular work history prior to tie start of the current spell. The only
attributes
included
in X are two indicator
.
~SPANC).
The work histo~
x
labor market experience
variables
variables
measured
as toti
for racial origin @LACK
and
H consist of the foIIowing measures:
potential
number of weeks since tie individud
left
,
school @XP);
two indicator
variables
for previous
low-wage
employment
weeks and in the past 104 weeks since leaving school &WJ 1 and LWJ2);
variables
for schooling
occupied
by tie individual
the total number
six indicator
and the five labor market statuses to capture the economic
prior to entering
of weeks employed
@MP52);
status
tie current status @s, P t, Ph, Pb, Pe, Pn);
since leaving school @MP);
52 weeks (or the time since leaving school if individual
spent in employment
in tie past 52
the fraction
of the last
left school less than a year ago)
and the total number of weeks spent in trainin”g programs
since leaving school ~R~.
Tables B.2 present tie final specifications
The fust column in each table lists the definition
esti-mated for tie-four
of tile variables
edumtion
groups.
included in Z_ for all of
the five labor market statuses and the rest of the table presents details of the parameter
restrictions
imposed
are necessary
in the final specification.
to secure identification,
other than the constant
significantly
different
we
term, in two ways:
In addition to parameter
restrict tie coefficients
restrictions
on the variables
first, if none of the” individual
from zero at conventional
B-6
hat
in Z-,
coefficients
significance =levels and. a joint
hypothesis
are
test suggests that M of the parameters are eqd
ad
to zero we impose tils =ro restriction;
second, we restrict tie coefficients to be equal across spline points whenever a joint
hypothesis
test indimtes
table specifies
consider
tidicating
the spfine segments
tie intercept
segment
category
11-, in the column corresponding
whereas tie covariate
that this variable is included
restrictions.
For instance,
status b in Table B.2 for education
category
the p~sence
of any across spline
the column corresponding
to labor market
12, the lower entry for the variable
that the @dividual entered his status from a low-wage job &t)
indicating
that the parameter
and foufi
that this variabIo
BLACK has an entry “ 1, 2, 3, 4“
indimting
tiird
to low-wage
in the first four splines but is not included in tie
The lower entry in a cell indicates
parameter
For example,
@rm has an entry of “ 1, 2, 3, 4, 5” indimting
five spline segments,
last segment.
The upper entry in each CCUof the
that contain the re~evant vafiable.
Table B.2 for education
employment
enters d
&is is a vafid restriction.
for his variable is constrained
spline segments.
B-7
is “2-3-4”
to be equal across tie second,
.
Table B.2
for Duration Distributions
Swcifications
High-School
Dropou~
hhr
P
Variable
Intercept
BLACK
HIsP~IC
Pb
Pe
b
1, 2, 3.4,
5
1,2,
e
3,4,5
1,2,
3,4,5
1, 2, 3,4
1,2.
3.4
1, 2
1-2
1; 2, 3
1,2,
1,2.
3,4
1, 2
1-2
1,2,3
1,2,
3, 4
1, 2
I .2
1,2,3
3,4
Pt
Ph
Market S~tus
h
1, 2, 3, 4.5
(11-)
1,2,
3,4
n
1,2,
3.4,5
1,2,3,4
1,2,
3,4
1,2,
3,4
1,2,
3,4
1,2,3
I, 2, 3.4
1,2.
3,.4
1,2,
3,4
1,2,
3,4
1,2,
3,4
1,2,
3,4
1,2,
3,4
1,2,
3,4
1,2,
3,4
1,2,
1,2,
P?l
Ps
h(EXP)
ln(EXP) *
(EMP/EXP)
(EMP/EXP)
EMP52
LWJ1
LWJ2
T~
1, 2, 3
1,2
1-2
1,2,3
1, 2, 3, 4
1, 2.
1-2
i, 2, 3
3,4
1,2,
3,4
1, 2
1-2
1,2,3
3,4
1, 2, 3,4
1, 2
1-2
1, 2, 3, 4
1,2,
3,4
1, 2
1-2.
1,2,3
1,2,
3,4
1,2,
3,4
1, 2
I-2
1,2,3.
1, 2, 3,4
1,2.
3”,4
1, 2
1-2
1,2,3
““
1, 2, 3
1. ?, 3,4
1,2,
3,4
1. 2,3,4
1,2,
3,4
1, 2, 3,4
1,2,
3,4
1,2,
3,4
1,2,
3,4
Table B.2 (cont.)
,.-,o)
Hish-School
Gradua&s ()
.
bkr
Variable
[ntermpt
BLACK
HISP~IC
!
h
Pb
Pe
b
e
1,2,3,4,5
1,2,3,4,5
1,2,3,4
1,2,3,4
1,2,3,4
2-34
1,2,3
1,2,3,4
1,2,3,4
1, 2, 3, 4
2-34
1, 2, 3
1,2,3,4
1,2,3,4
2-34
1,2.3
Pe
Ph
Market Sam
1,2,3,4,
5
1, 2, 3,4
1,2,
3, 4,5
n
[,2,3,4,5
1, 2, 3, 4
1,2,3,4
1,2,3.4
1,2,3
1,2,3,4
1, 2,3,
4
1,2,3,4
1,2,3,4.
1,2,3,4
1, 2, 3,”4
1,2,3,4
P/l
Ps
ln(EXP)
ln(EXP) *
(EMP~XP)
(EMP/EXP)
EMP52
LWJ 1
LWJ2
TN
1, 2,3,
4
1,2,3,4.
[,23
1,2. 3,4
2,3-4
1,2,3
1,2,
3.4
1,2.
3,4
1,2, 3,4
2-34
1,2,3
1,2,
3,4
1,2,
3,4
1, 2, 3, 4
2-34
1,2,3
1,2,
3,4
1,2,
3,4
1,2, 3,4
2-3-4.
1, 2, 3
1, 2, 3, 4
1, 2, 3, 4
1, 2, 3.4
2-34
1, 2, 3
1,2,
3,4
1,2,
1, 2, 3, 4
2-34
1,2,3
1,2,
3,4
1, 2, 3, 4
1,2, 3,4
2-34
1,2,3
3,4
1,2,
3,4
1.2,
3.4
1,2,
3,4
1,2,
3.4
1, 2, 3, 4
1,23,4
1, 2, 3, 4
Table B.2 (cont.)
Some College (13-15)
b~r
Variable
Intexept
BLACK
HISPANIC
P
1,2,3,4,5
Pb
Pe
4, 5
1,2,
3,4,
e
5
1,2,3,4,5
n
1, 2,.3,4,
1,2,3
1,2,
3,4
1,2, 3.....
2-3
1,2, 3,4
2-34
1, 2, 3
1, 2, 3
1,2,
3,4
1,2,3
2-3
1,2, 3,4
2-34
1,2,3
1,2,
3,4
1,2,3
2-3
1,2, 3,4
2.3-4
1,2,3
PP
Ph
b
h
1, 2,3,
I
Market Stitus
1,2,3
1, 2, 3, 4
2-3-4
1,2,3
1,,2, 3,4
1,2,3.
!. 2,3,4
1,2,3
1,2,
3,4
1,2,3
1,2,
3,4
1, 2, 3
1,2,
1,2,3.
1,2,3
Pn
Ps
ln(EXP)
k(EXP) *
(EMP/EXP)
(EMP/EXP)
EMP52
LWJ 1
LWJ2
T~
1,2, 3,4
2-3-4
1,2,3
1, 2, 3
2-3
1,2, 3,4
2-34.
1,2,3
3,4
1,2,3
2:3. .-
1,2, 3, 4
2-34
1,2,3
1,2,
3,4
1, 2, 3
2-3
1, 2, 3, 4
2-3-4
1,2,3
1, 2, 3
1,2,
3,4
1, 2, 3
2-3
1, 2, 3, 4
2-34
1,2,3
1, 2, 3
1, 2, 3, 4
1,2,3
2-3
1,2, 3,4
2-3-4
1,2,3
1,2,3
1,2,
1, 2, 3
2-3
1,2, 3,4
2,34
1,2,3
1, 2, 3
1. 2,3,4
1,2,3
2-3
1,2, 3,4
2-34
3,4
B-10
1,2,3
5
Table B.2 (cont.)
College Gmdua&s (16+)
hkr
Variable
Intercept
BLACK
HISPANIC
P
1,2,
3,4,5
Market S&W
h
1,2,
b
3,4,
5
1.2,
3,4,5
e
1, 2, 3, 4, 5
n
1,2.
3,4,5
1,2,3
2-3
1,2, 3,4
1, 2
1-2
1, 2, 3
1-2-3
1,2,3
1, 2, 3
2-3
1,2,
1, 2
I -2
1,2,3
I-2-3
1,2,3
1, 2
1-2
1,2,3
1-2-3
1,2.3
3,4
1,2,3,4”
PP
Ph
1, 2, 3
2-3
1,2,3
1-2-3
Pb
1. 2,3
2-3
1,2. 3,4
Pe
1,2,3”
2-3
1,2.
3,”4
Ps
1,2,3
2-3 .:
1,2.
3.4
ln(EXP)
1, 2, 3
2-3
1,2,
3,4
h(EXP) *
(EMP/EXP)
1,2,3
2-3
(EMP/EXP)
1,2.3
Pt2
EMP52
LWJ 1
1, 2,”3
I -2-3
1,2,3
1.2
I-2
1, 2, 3
1-2-3
1,2,3
1,2, 3,4
1,2
1-2
1, 2, 3.
1-2-3
1, 2, 3
1, 2, 3
2-3
1,2, 3,4
1,, 2
1-2
1,2,3
1-2-3
1,2,3
1,2,3.
2-3
1,23,4
d,2
1-2
1,2.3
1-2-3
1, 2, 3
I, 2, 3
2-3
1, 2, 3, 4
1, 2
1-2
1, 2, 3
1-2-3
1, 2, 3
1,2,
3,4
1.2
1-2
1.2, 3
1-2-3
1,~,3
1,2,
3,4
1, 2
1-2
1,2,3
1-2-3
1,2,3
LWJ2
TN
1,2,3
2-3.
B-11
B.2
Empirical
Specifimtions
Multinomid
of Initial Status and Entrance
logitspecifi=tions
are used to estimate both types of entrance
probabiuties outikned in the main body of the paper.
estimate the initial Iabor market s~tus probabilities
individual
probabilities
are implemented
drat determine
the general statistical
specifications
to estimate
the likelihood
addresses
an individual
framework
probabilities
This sub-section
u~n
terminating
enters status
i
economic
and finally, the
probabilities.
sta~s
the
when it”is kow,n
he has
be termed an “enVance” probability.
an individual
enters each of the
an episode in status k, define the probability
that an
.
as
I T,
a spell of T weeks in status k.
tie probability
first ouflines
upon ending a period of time spent in a given status.
Pr(k-2)=Pr(k-i
after experiencing
labor market
of the particulu
for the entrance
reflect the likelihood
statuses immediately
More
needed to examine the process that determines
occupies a particular
@.7)
represents
estimated
statuses involves what can generally
These entrance
tidividual
s~tus.
an
of the entrance
enters a particular
it hen turns to a presentation
tie specifications
an individual
just switched
Specifimlly,
framework;
the parameters
used for the initial labor market status probabihties;
The statistical
alternative
are used to
that capture the probability
status given he has just ended a SPI1 in a different
probability
Simple specifications
enters one of the five labor market statuses upon leaving school.
complex specifications
discussion
Probabilities
an individud
~,
k#i,
Formally,
moves from residency
B-12
the quantity
in @.7)
in status k to occupancy
of
labor market status i conditional on ending a
covtiates
weeks in stares k and on tie
of T
Z.
The inclusion of the supplemenwl
implement
weighted maximum
probabilities.
status
SPU
btroducing
log-Welihood
likelihood
weighs
k for an fidiiidual
procedures
to es~a~
~ into the likelihood
who has occupied
requires us to
~e~
entmnce
of observing a transition
status k for T weeks ~fi
afibufis
out of
Z yields a
function of
@.8)
hLi(T,
Z)
= Ok
where here are M possible destination
if the obsewed
the individual
k produces
samples from the NNY
~m(z)
{ i=l
known variance-covariance
represented
We parametrize
matrix
variable fiat = 1
Mwim~ing
the sum of
by (B.8) over all observed transitions
normally
(see Amemiya
the entrance
>
}
status change is to status i and-. = O otierwisecontributions
Z)
statuses and m(i) is an- indicator
consistent and asymptotically
with a geneti
kPr(k-il_T,
probabilities
distributed
parameter
out of status
estimates
with a
(1 985) pp. 3 19-338).
using a multinominal logit s~cification
form given by
~ztP**+8k,{r.%. aft) . ai(~j % Y*,)
@.9)
Pr(k-i\T,
Z)=..-.
.,k
=
~zlBl,
+ gk~T, %> .1,)
#i,
+ ut~A. ZJ> Y~j)
j.k
where A is a particular
attributes,
attribute
of an individual,
z! , ~- and Z3 am vectors of..individu~
ati, Bw, and yti are suitably dimensioned
ati(”) are smoofi spfine finctions
parameter
vectors. ad
that permit very flexible relationships
B-13
g~(=) and
between tie
entice
probabfity and the variables T, ~- , A and Z,. The finc~ons
iderrtid
to functions gi(0) specified h
completed
spell length of T.
characteristics
determine
of duration
has just terminated
dependence,
presented
the smooti
in B-6 determine
the quantity
tie
spline functions in these specifications
of various entrances
change with tie length of the spell that
in status k. The functions %(*) are defied
except tie spline properties
Specifically,
B. 6 with the norrnaf cdfs now evaluated at the
Whereas the funchons
how tie WeMo&
gti(*) are
now relate to different
very similarly
values of the individual
to tie gti(*)
attribute
A.
ati(*) is given by
K;
aki(A>
‘3yyki)
=
X
j=l
[@kij(A)
- ‘kij-t(A)]
[ ‘kijz3]
where the @~i(A)denotes a normal df with a presycified
the value of attribute A. These smooti
Zq to have a different
individual’s
influence
value of attribute
>
mean and variance evaluated at
spline functiorrs permit the variables
on the entrance
probability
depending
included in
upon an
A.
The initial labor market status probabilities
reflect tie likelihoti
an individual
leaves school (status s) and enters each of the five labor market statuses ~, h, b, e, and n.
We specify these probabilities
given in equation
categories
@.9).
Differen;
with tie amibutes
school.
The attributes
of tiese
probabilities
as a simplification
mdels
of the pultisromial
are estiated
Z measured at the tie
Z only include demographic
rules out the possibility
B-14
for each of the four eduation
the individual
characteristics
that hey
logit specification
permanently
leaves
X because the namre
depend upon any labor market
history variables.
HISPAMC),
Specifically, 2, includes tie two racial origin variables @LACK and
the a’s are all set to zero resulting in the g,,(*)’s dropping out of the
probability, Zj only includes an intercept, and the attribute A, which determines
nature of the a,,(*) functions,
The particular
is equal to the age of tie individual
pammeterization
tie normal cdfs
measured
the
in months.
of the a,,(-) has W,i = 2 with the mean and variance of
.
being equal for the five potential labor market statuses but differing
across tie four edumtional
groupings
as shown in Table B.3.
Table B.3
Means and Standard Deviations for Smooth Splines in Initial Labor Market Probabilities
Uucation
11-
12
13-15
16+
Mean (weeks)
216.0
228.0
27C0
288.0
S~~ndard Deviation
1.m
1.00
1.m
1.00
The entrance
Category
probabilities
status given an individual
estimated
~(o)
the likelihood
has just ended a spell in a particular
using a general specification
smoo~
preceding
that characterize
spfine finctions.
but are equal for the four educational
the gti(*) functions,
categories.
for the entrance
probabilities.
by fie du~tion
The adopted specification
g~,(.) and
of the
sets &
means and standard
To account for non-Enear
B-15
boti the
differ across the origin status k
for all statuses k and i. Table B.4 presents the prespecified
deviations
labor market srams are
of equation @.9) including
The spline points dete~ined
speu, which characterize
of entering an alternative
effects of labor
= 2
market exprience
on drese entrance
attribum A equal to the to~
measured
EXP).
at the beginning
We specify
are identicd
.
the ~i(*) spline finctions
number of weeks of potential
set tie
labor market exWrience
of the spell in status k that is just ending (i. e., tie covanate
K’ti = 2 for all possible stamses and tie Iomtions of the spline points
across tie statuses k but differ only slightly for tie four educational
categories.
functions
probabilities
Table B.5 Iisw tie means and smndard deviations
for tie four edumtional
usd
in tie
~j(.)
spline
categories.
Table B.4
Means and Standard
Deviations
bbor
Exiting From
Market Satus
for g~,(*) Splines in Entrance Probabilities
e
h
b,
e
Mean (duration in weeks)
20.0
50.0
4.0
20,0
12.O
Standard Deviation
2.0
2.0
0.5
2.0
I .0
n
Table B.5
Means and S@ndard Deviations
~ucation
Category
11-
12
13-15
16+
Mean (weeks of EXP)
2m.o
200.0
2m.o”
104.0
Standard Deviation
50.W
50.W
50.00
50.00
The tifluence
accounted
for aLi(*j”Splines in Entrance Probabilities
for tirough
of individual
attributes
all three covariate
(Z) on the entrance probabilities
are
vectors, Z, , L. arsd 23. In addition to the
B-16
demographic
and labor market history variables
two additiond
covariate
variable
covariates
included in the entrance
above in Section B. 1, there are
probabilities.
The first additiond
is the length of the spell in status k that is just ending fl)
tfrat determines
covariate
@ining
discussed
the spline points in”the g~i(*) finctions.
is art indicator
program
to account
and is the same
The second added
variable that is equal to I if tie individual enrolled
prior to tie start of the just terminated
spefl (ANYTR~
for any possible qualitative effec-k of participating
in any
and is included
in”a training~rogfirn
.
after
leaving school.
Table B. 6 summarizes
distinguishing
the covariates
included
in the final empirical
among the variables included in the vectors
Z, , ~ and 2s.
in Table B.6 co”tiespond to the labor market stares the individual
entry in each cell details whether the variable is included
each particular
example,
destination
esdrnated
stituses
destination
of low-wage employment,
for
high-wage
“For
probabilities
of entering dre possible
employment
and training.
If an
shtus does not appear in an entire column, this implies that the
,.
.
probability
of ente~ng
leaving the relevant status.
high-wage
The upper
in the entrance probability
from the origin status n, an entry of (f, h, e) implies the entrance
destination
The columns
s~”ms the person can enter from tie relevant origin status.
include this variable in the estimation of the probability
possible
is leaving,
specification
employment
this excluded
status is identically
For instance, the probability
from nonemployment
aPpear in tie column corresponding
zero for everyone
of entering both low-wage
and
is set equal to mro and the stah:s b does not
to status n. The lower entry in each cell indicates
B-17
‘
I
I
whether the variable
mtegories.
is included in the final mdel
Specifimlly,
for each of tie four edumtiond
an entry of (1 l-, 12, 13-15, 16+)
“includ& in tie model for all educational
indicates
tile variable is
categories while an entry of (11-, 12, 13-15)
imphes tie variable is excluded from the mdel
college graduates.
I
I
I
B-18
describing
tie entrance
probabilities
for
Table B.6
Model S~cificahons for Entrance Probabilities
Origin Lahr
Variable
e
h
e
n
f,h. n
!1.. 12. I+IS. !6+
f,h, e
i,.. 12. 1~1$. 16-
b
Variabl~
includti
f, b. e, n
,,., ,2 1+,S, 16.
Pf
Market Stitus
in Z,
e, 1,
11.. 12. !>15. 16+
Ph
Pb
h, b, e, n
,,., ,?, !31S, 16.
!,b,
e. n
1[., 12. 1>1S. 16.
Pe
h, b, e, n
1,.. ,?. ,>!5, ,6.
f, b,e, n
L!.. !?. !3.15, !6.
P.
h, b, e, n
11.,12.1>15, 16.
Ps
h, b, e, n
,1-. ,2.1.*15.16+
t,h,
e
t!.. 1:. 1>:5, L6.
t,h, n
11.. l:. 1>15. 16+
t, h
11.. 12, 1+1$. !6.
!, b.e, n
11., 12. 1>1S, 16.
!, h. n
11., [2. 1>15. [6-
t.lt. e
1[-,,:. 1*,~. 16.
Ps*BLACK
t. h.e
!:-. 1?.1>1S. 16.
Ps*HISP~IC
l“&xP) *
@MP/EXP)
t,h, e
11.. 1?, 1>15. 16+
h, b, e, n
t, b,e.
?, h
n
f,tl,
n
t,h,
e
II.. [~. 1+15. 16L
[I- ‘~ ‘~15 ‘6-
11 ‘2 ‘St’
@MP/EXP)
h,b, ?, n
,,., ,2, 1>1$,16.
f, b, e, n
1!.. 12, !>1s, 16.
e, h
11.. l?. 1>15. 16+
(,h, n
11.. 1?. lJLS. f~+
f>h, e
II.. I:. L~I$. 16+.
EMP52
h, b, e, n
11.. 1?. tsrs. 16+
!, b, e, n
11., 1?, 1>15, 16.
t,h
11., 12. CS15. 16+
f, h, n
11.. 1% ,%,~. :6+
t,h,
e
IL.. I?. 13.15.16+
LWJ 1
h, b, e, n
il., 12,B>,5, 16.
t, b, e, n
il., 12. s>)%. 16.
!, h
)1.. t2. 1>13. 16+
!,h, n
Il.. i:. 1F13. 16+
f, h, e
L,-. I=. ISI~. 16+
LWS2
h, b,e, n
,1., ,2. 1>15,16+
f, b, e, n
II.. l?, 1>13. 16+
e, h
11.. 12. 1>15. 16+
(, h. n
Il.. I?. 1~15. 16*
f, h, e
11.. 1?. 1>1S, X6+
Tm
h, b,e, n
,,.. ,2 1>c5. 16+
t, b,e, n
11.. 12. 1%1S.lb+
t,h
il.. 12. 1>1: 16+
t,}t, b,e, n
1~.. L=.~~1~. 16+
t,h, e
II.. 11. 1L13. ~6+
-TN
e
11.,:2 IS15.16+
11., 12, 1%15.
1*+
e
B-19
16”
“.1’
‘>”
‘6”
11- !’ ‘5”
‘6”
e
II.,12lsl~.16+
Table B.6 (cont.)
Model S~ifi=tions
for Enttice
Probabilities
Origin ~bor M=ket Smms
Variable
!
Vaiables
Intercept
BLACK’
HISP~IC’
T
In@m)’
e
n
t,h, n
,1.. 12. ,>!s. 16.
t. h, e
1!., ,!, I*,,, ,6+
included in ~
h, b, e, n
11..12. 1*,5. !6+
f, b, c, “
,1., 12. 1>, s, ,6-
h, b, e, n
11.,12, !%13
!, b, e, n
11-. 12, )>15
t, h
1!., 12. 1>,,
t,h, n
,1., 12, !>1s
f,h, c
11.. 12, ,>,5
h, b, e, n
1!., l?, ,>15
f, b, e, n
1,.. ,?, ).>!5
t, h
11., l?, 1>15
!, h, n
$1.. 12, 1>1s
/, h, c
,,.. 12, C*,5
h, b, e. “
,1., 1,- ,S, j. L6-
(, b, e, n
,1.. ,2. ,.>1$,16.
f,h
,,.. ,!. ,>,5. ,6-
e, h, n
,1., 12. !3.15, 16.
t, h, e
[!., 12, 1>1S, [6.
t, h, n
,,., ,2, ,*, S, ,6,
(, h, e
,,.. !2. 13.!5. ,6.
Variables
Intercept
b
h
t,h
,,., ,2. ,s,5.
included
,6+
in Z.
h, b, e, n
11-,12,1>15,16-
t,b, r, n
!1., 12. !>15, 16-
t, h
,!.. ,,. ,>,5. ,6.
h, b. c, n
[!., 12.l.~lf
f, b, e, n
II-, 12,,>15
f,h
11-,l?. ,Y,5
f, h, “
1,., 12,,>15
f, h, e
11., 12. 1%1s
‘ For education group 16+, the coefficients corresponding to the BLACK and HISPAMC
variables in the second term of the g(. ) spline are set to zero.
2 For education group 16+, the coefficients “corresponding
swrmd term of the a(*) spline are set to. zero.
B-20
to the variable ln(EXP) in the
-
. .
Variable
5%
25%
50%
73%
95%
0.3
0,07
0,36
0.63
0.86
1
0,27
0,24
0.02
01
0.2
0,39
0.8
0.24
0,22
0,03
0,08
0.17
0.34
0.7
0.53
0,36
0 ,m
0.19
0,41
1
1
0.49
0.36
O.m
0.15
0..4 .. .
0..87
1
“03
02
042 0“69 0“9
Mean
I Sti. k“
17.41
9.99
0,36
0.26
0.84
0.59
.
0.72
0.64
0.65
0,71
0.4
0.46
0’8
0,3
I
I ‘a
0’9 0“43 0“73 095
0.16
o,i7
0.08
~ W2
o.m3
0.01
0.05
0,19
0.1
0.W2
0.W3
.0.02
0.07
0.21
1.53
0,K2
1
1
2
3
0.19
0,19
0.02
O,w
0.15
0.26
.. 0.68
0.45
0,42
0
0
.0..31
0.95
1
0.33
0.03
0.16
0.43
0.75
1
0.04
0.05
0,32
i
0.94
0.47
TABLE, 2.1 (Cont.)
V,ri,ble
Men.
12 Yea-of
Age kfi
Y-m
18.72
=hml
of ~ucacio”
B!ack
0,33
P.cent
H,spati.
0.!6
Fmction
wi*
~Y
Employment
0.9!
Periti
0.75
of Obxws(io”
%p.fli.”
witi hy
Eql.Ymcnc-M
hpohon
wih
Emp!.yment.LQ
&y
U..aliOm(l 2): Number of Individuals = 911
1.5s
17
18
18
19
21
0.2s
0.15
0.63
0.83
0.9s
1
12
Pen..,
~PO~On
Std k.
Employed
~w-Wage
0,69
hw:Wage
0.61
Ftiction of Ob=ma! i..
bw-Wage
Jobs-M
Perid
Employed i“
03
0.26
0.02
0.1
0.21
0,43
0.89
Fmcti.” of Obsewado”
bw-Wage
Job+ LQ
Perid
Empl.yed
0.28
0.26
0,02
0.07
0.2
039
0.86
kponion
of Time Employed Spent in kw.
Wage Job,.M
O,&
0.3S
O.m
0,14
0.37
0.8
1
%Poflio.
of T!me Employed Speni i. bwWage J.bs-LQ
0,43
0.35
0.03
O..lx
0.32
0.74
1
Pmp.ni.”
witi ky
Employment.M
Wlcb.WSge
0.77
tiponi.”
witi
Employment.LQ
High-W8ge
0.81
&y
in
.-.
Fmcti..
of Ob=wation
H,gh-Wage lobs-M
Perid
Employed i“
0.6
0.28
0,0$
0,3$
.0.63
0.84
0.99
Fmcti.n of Obsemado”
Htgh-WnZe Jobs.LQ
Periti
Employed in
0,62
0.29
0.08
0.4
0,67
0.86
I
%Poflion
Witi &y Sim.lti”e.u$
Mgh-Wage Eqloymcnt-M
bw-
a“d
0.2
kPO_iOn
H,&.w8gc
hw.
&
0.2
wih hy Simulm.e...
~loymc”l.LQ
Fmction of Ob=ff.ti.”
Perid Em!.yed
m
X,@-& tiw-WaZe 3&PM
in
0.07
0.11
O.m
o.m3
0.01.
0. I
0,29
Fmction of Ob=mstion
Petid =ployed
~
Mgh- & kw-WIEe
lhs-w
in
0,07
0.11
0,M2
0.W3
0.03
0.11
0..3.
1.4s
0.76
1
1
I
2
3
0.16
0.[7
0.01
0 .0s
0.11
0.2
0..47
0.73
0.38
0
O,*
0.98
1
1
0.33
0.01
O,w
0.17
0,4s
I
Pmption
witi tiy Tmiti”g
Number
of w!des
Fmction
Tmiti.g
of Ob%mation
of Tmiting
Perid
Fmclion Of Time in Tmitiw
Pmp.fiion
witi by
0.3
spent in
Mm Employed
Nonemploymc”l
Fmction of Ob=mation
Noneqloymcnt
Periti Spent in
0.86
0.31
TABLE 2.1 (Cont.)
Vari.b (e
M-n
Mom ~an
Age Lfi
Yam
.
12 .“d ~SS ~.n
Schml
of UUc,,io”
bpotiion
wih &y
EmPIoymcnt.M
27
!3.83
0.77
13
13
14
14
Is
0.21
038
0.77
0.92
1
1
0.16
0.4
I
0.4
1
0,94
0,84
Eql.yd
hw-Wage
~potiion
witi &y
Employment-LQ
of UUc,rio
24
0.2
Pctid
95%
12
H!,p. tic
of Gwwat,.m
75%
20
P.Eent
Fmcti.n
50%
19
0.33
Empl.yme”t
23%
2.61
Black
wih hy
16 Y-m
s%
22.3
Pe=cnt
hpomion
S1d W“
0.4
tiw.Waze
0.37
!
Fm.6on of 06%w*ti.”
hw-WaSe
J&>M
Petid
Employed i“
0,28
0.28
0,01
0,07
Fmcfion of Ob=wation
hw-Wage
J.bs.LQ
Periti
Eql.yed
0.29
0.29
0.02
0.08
in
0,,6
. ..
Eqloycd
Spent i“ hw.
0.39
0.35
0.02
0.1
0.26
0,67
I
tiPOfliO* Of Time Eql.yed
Wage Jobs-LQ
SPent :. hw.
0.4
0,35
on
0.12
0,26.
0.7
I
0.16
0.62
0.17
0.61
0.85
0.99
1
0.01
O.w
0.16
031
0.032
0.01
O.M
0.16
0.87
Pmp.nion of ~me
Wage Jobs.M
Pmpotiio” witi by
EmnIoYment-M
0.88
High-WaEe
O.wz
.
hpodi.”
Nuh.r
wih hy
of md.s
Pqofii~n
<h
Fm.tion of ~=mation
Noncmpl.ymnt
.1
0,27
of Tmiti”g
1.4
0.78
1
i
1
2
3
0.1s
0,18
0.01
0.03
0,07
0,18
0.4$
0.82
0,34
0
0,85
I
1
1
Perid
in Tmiting
hy
0.99
Tmiti.g
Fmction of Ob=matioti
Tmiti”~
Fmccion of~w
.
O.M
Spent i.
tiw
Eqloyed
No”eq!oymc”t
P.rid
Spent in
I
0.64
0.26
0.3
—
TABLE 2.1 (Cont.)
Variable
l.ca{ion( 16+): Number of bd!vidial,
= 591
~
0.2
0.34
0.81
0.94
1
1
.
II
I
0.25
I 001
0.27
O,w
0.12
0,27
“.9[
II
I ‘o’ ‘w
‘]’
’27 ‘
n
I 00’
’05
“4
0“34
1
II
0.3
0.3 !
0,01
O,M
0.15
0.39
t
0.22
0.28
0.74
0.91
1
1
0,22
0,28
0.74
0.91
1
I
0,2
o.m3
0.01
0.07
0.17
0.73
0.21
0.W3
0.01
0.07
0.16
0.74
0.84
1
1
1
2
3
0,24
0,02
0.04
0,08
0.2
0.23
0.18
0.98
I
1
1
0.24
0,01
0.03
0.1
0.27
1
I
I
. ..1
TABLE 2.2-@
S~fiti= for S@k by Ed.ution
Smmw
wldcs
Age .1 kgiti.g
of ~w.Wage
of Spell
Weeb Sm. hR Schml
iegifi.g
Of Spell)
(_mmd
.1
Eqloy-nl
18.0
142,47
129.36
0,0
28.0
28.28
1,0
7.0
O.x
Fmctiom WghL Cenwmd
0.07
L“@
23,91
%iti.!
Age at Wgiti”g
of His6-Wag.
of Spell
Wee& Sk”.. uti Schml
%gitiw
Of Spell)
(meawmd
at
wloyment
410,3
52,52
2,0
9,0
22.0
48,0
.15s.0
Spell
W+eb S,,.. LR Schml
beg;tinc
of Spell)
2.90
17.0
18,8
21.0
22 .s
2&o
190.n
136.86
2.7
69,0
169.5
290,8
435.3
12.70
I .0
1.0
2.0
!4,0
39.6
(measumd at
of Tmidw
20.0
22.0
25.0
1s5.01
125,81
0.0
s2.0
122.0
245.0
394.5
33.07
4.0
13.0
26.0
5L0
I W.o
20.0
22:0
M..o
105.0
229.8
395.0
Wq.tie
0.24
O.M
%8ht Ce_md
36.W
SPCUS
Qidcs
of Spell
Weeti S“ce bfi Schwl(mammd
bcgiti”g
.f Spell)
Pc=ent
Fmcti.n
of Spells = 329
{8.0
Pe=em
Fmcti.n
11-: N“tier
17,0
0.42
Age II -gifi.g
Gm”p
2.58
Bbck
of Completed
f., =ucatio”
.-.
20.21
Fmclios
U.*
Group 11.: Number of spells = 166
20.9S
9.49
SPe]lS
wtdcs
Fmcti.”
EnlplOyment for w.ca[i.n
0,03
Nghi Ct”tired
Age at &gitingof
= 696
265.0.
0.19
of Completed
Group 11.: Number of spells
144.0
P,*..<
b“8ti
76,6
47.0
0.31
Fmcti.n
29.0
0.0
Fmcti.m Black
H,sp. tic
.14.0
133.92
Wgh- mnd hw.Wage
It
398,9
166.82
4!.14
Week, Since bfi Schml(mess”md
begiti”g
.f Spell)
227.0
25.0
b“a
of sP~ll
111.0
22,0
0.18
Age *: ~zi~ng
S,a
20.0
Fmc!iOnWght Cens.xd
of &ti
22,0
18.0
0.12
%:wdes
.20.0
17,0
Pcme”t Wqatic
[cd spells
9s %
2.67
0.10
of Coql.
75%
20.59
Black
Fmcli.ri
for U“cation
50%
11-: Number of SPell, = 1081
16.0
Fmcti.n
SPells
G-p
2.68
0,41
of Coq[e[cd
f.. Nuc,ti.”
2s%
20,05
Fmction Black
HisPaNc
I 5%
Sti. k“
Man
V,ti.hl.
Gm.p
Black
HLsp*tic
%ght Cenmmd
at
Of Noncw!oy-nt
for Uticati.n
Gm.p
I l-: Number .f VCIIS = 2096
19.96
2,71
16.0
138.46
131.49
0.0
0.38
0.26
0.17
.18.0
17.0
TABLE 2.2-W (cont.)
Mean
‘urisblc
~ld.1
Lg. at %gimi.g
of bw-Wag=
of Spell
Veeks Stic bt SchaI
eginting Of Well)
(meas”md
al
Eql.ymc”t
75%
95%
f., ~UCS!iOm Group 12: Number of Spells = 1180
18.0
19,0
20.0
22.0
25.0
117.4
t 18,94
0,0
I 3..0
82.0
195.0
353.9
33.59
2.0
9,0
19.0
39,0
91,8
‘mction Mspatic
0.14
‘m.! i.. &ght Cenmmd
0.10
zngti
29.43
~isdes
50%
2,53
0.40
SPe[l,
23%
20.76
‘mclion Black
of C.qlewd
5%
Sti. m..
of H,gh.Wasc
Empl.yme.!
for W.cad.m
–.
Group 12: N.mbec of spell,
.
= 1233
21.20
2.64
18.0
19.0
21.0
23,0
26.0
veeb SIN. kfi School (measumd S1
kgitiig
.f spell)
142.35
127.70
0,0
32.C
I 14,0
234,0
3893
‘mcd.n Black
0,39
‘mccio” HL**tic
O.M
‘mc:ion tight
0.21
64,93
2.0.
11.0
27.0
64,8
192.5
\gc al &giti.s
A“gti
of Spell
Ccnmmd
51.87
of Completed SP.I!S
@isOdcs Of Boti High. snd bw-wage
\se at %gimi.g
of Spell
Weeks SW. bfl Schml(mctisumd
>egiting of **+11)
,!
12: Number of spells
2.67
18.0
19.0
154.35
121.83
5.0
46.0
24,91
!.0
1.0
0,24
Fmctio” K,spanic
0.16
Fmclion Eght Ccns.md
0,03
tinfl
15.79
Spells
Gwp
21,50
Fmc[i.” Bln<k
.f C. WIeted
Employme”: for ~.caci.n
= 267
U.o
26.0
138.0
230.0
401.0
4.0
19.0
71.0
~—” 21.0
E6ucado” GmuP 12 Number of Spells = 405
2.88
140.16
18.0
[9.0
21.0
24.0
27,0
0.0
3s,0
117.0
266.5
U5.5
I
I
20,51
wtdcs
Age et ~~ti”g
of SPell
Weeks S“.. tifi Schwl(measurd
bcgitiw
of well)
at
of No”cqloymem
9.0
Group 12: Number .f spells
21.0
34.0
69.0
= 235o
2.55
18.0
19.0
21.0
22.0
26.0
126.98
119.92
0.0
22.0
95.0
.207.0
3655
26 M
1.0
. ..3.0..
7.0
20.0
58..6
0.37
Fmcti.”
0.15
Fmction =Eht Cc”s.md
0.15
Lnfl
16.17
of Completed SPC1!S
4,0
20.97
Fmctio” Black
WIq*Nc
for ~.cation
I
TABLE 2.2-@
,.&.A,.
. . ..\Ec at %giting
Sti. -“.
M-
of hw-Wage %1.ym.nl
2pide1
Of Spell
Vecks Since kR Schwl
,egitiflg of well)
(mas.md
2,29
70.69
87.35
0,0
3,0
38,0
100.0
262.4
30.54
1.4
10.0
21.0
42.0
88.4
.. 26.0
29.0
at
‘mcti.n W,sp*nic
0,87
‘mcdm R,&t Cenm=d
0,12
xn&
29.68
spells
w~es
!gc al *giti.g
wecb S,”,. tifl Schml
kgiting
Of*ell)
‘mcti.n
of Wsh-Wage
Of Spell
(mcasumd at
Eql.yme”t
2.77
20,0
92,10
112,38
0.0
65.83
2.3
0.07
?mcti.n fight Ce.s.md
0,35
>.@
55.22
of CoWlettd
Spells
w!sde$
Of Bofi Kch-
of spell
weeks Since kfl Schmlime.s,md
,esihns
of spell)
at
a“d hw.WaEe
24,0
27.0
21.0
0:0
of Spel!s = 559
23.0
51.0
146,0
342,0
31.0
69.5
199.5
20.0
21.0
23.0
IW.82
9959
0,0
26.5
90.Q
34.32
1.0
1.0
7,s
Fmcti.n
0.15
Fmction %sht Cemomd
0 .M
b“~ti
18.73
of C.mpleled
Spell.
Wi,tiel
of Spell
Week. Since hfl Schml
begiti”s
of q.11)
(measud
al
Gm”p 13.!5: Number of Spcll$ = lM
2,6%
0.27
HIspaNc
EmploYme”I for ~“catio”
12.5
u .23
?mctio” Black
Fmc!i.”
22B
Gm”p 13-15: Nub,
23.71
‘mctio” Wspatic
A~e at ~~iting
for W.cation
21.0
0.!3
Black
kg. .[ %gi”ing
of spe!Is = 305
22.S6
0.37
.
f.r UUcati.” Gm.p 13-15: N“&r
19.0
‘mc[io” Black
of Cowl.ld
(cont.)
of Tmitinz
3.0
,..
.28,7
148.8
2U.4
24.3
73.8
for Wuc?tio” Group 13-15: Number of SPI1, = 203
24.54
2,82
20.0
22.0
X,o
27.0
29,0
143.51
i30,w
0.0
35..0
111.0
216.0
~2.6
17.54
4.0
5.0
9.0
22.0.
.. 56.0
0.22
Black
Fmction ~lm.tiC
0.18
Fmclion W&l Ce.mmd
0.13
kn@
16.99
of Comlckd
SP.US
Qidcs
of Noneql.ymc.t
for ~“cati.n
Gm”p 13-15: Number .f spells = 726
n.15
2.58
20,0
21,0
22.0
M.o
28.0
Weeks Since bR Sch-l(mamti.1
Lgitins
of qelD
87.48
94.47
0,0
7.0
56.0
135.5
291.0
Fmction Black
0.40
Fmction HIspaNc
0.17
Fmclion Wghl Censored
0.15
Age at &gi&ns
Of Spell
TABLE 2,2-M
5%
Sld, k“.
Vatible
&i&es
Age .1 &giti”g
of ~w-Wage
.( Spell
Wccb s“..
bR Schml (m.as.md
begitiw
of qcl!)
at
EWloyment
16 +: Number of spells = 159
24,0
36.0
29.0
64.36
87,76
0,0
0,0
31,0
91.0
264.0
29.38
1.0
6,0
14,0
362
60,5
0.0?
Fmcdon
Wght Ce”mmd
0.16
23.28
of ~tgh-w,ge
95%
22.0
Hgspadc
~ISdCS
75%
2[.0
Fmcti.n
Spells
&up
50%
2.3 I
0.15
of Completed
for Wuctti..
25%
24.37
Fmc tion Blnck
~ti
(cont.)
EWloyment
for WucatiO” Gm.p
.
16 +: N“mbec of spells = 743
24.72
2,29
22.0
23.0
24,0
26.0
Weeks S;nce bfl Schml (mcemred at
b~iting
of ,p.11)
63.29
85.71
0.0
1.0
25.0
.. . %.0
Fmcti.n
B!ack
O.w
Fmctio”
Hispanic
0.01
66.s6
2,0
10.0
28.0
Age ,1 *giti”g
of Spell
Fmc:ion RLgh( Ce”wrcd
0.44
tinfi
52.24
of C.mplewd
Spells
WISd~S.Qf
Age .1 &gimi.g
b*
High. and bw.Wsge
of Spell
Wrecks Since bfi Schml(mca6.~d
begiti.g
of spell)
at
Ew!.ymc”:
23.0
25.0
71.28
87.03
0.0
12.0
50.0:
119,0
293.6
1.0
1.0
6.0
16.0
61.0
27.0
30.0
159.8
321.0
Fmction
Mspatic
0.07
Fmclion Wght Ce.mmd
O,w
U“@
13,03
18.15
of Tmi~.z
for m.czlion
GWP
2.33
22,0
24. O_.
25.0
Wek
S(... kR Sehml (meammd .,
bezi~ng
of spell)
107,42
101.54
0.0
ZO
76.0
Fmcti.n
Black
0.16
F“etion
H,w.dC
0.06
Fmction
~ght
0,10
b“~
Ce~&
Of CoWIctcd
12.86
SPOIIS
W$des
Age at ~giti”g
or Spell
WCks S,”ce bfi Schml(meawmd
begifi”g
of qell)
at
of Noneql.ymsnt
.
4.0
15.26
for ~“cati.n
Gmp
4.0
5.0
17.0
48.0
16+: Number of SP.!IS = 604
22.0
22,0
24.0
26.0
29.0
56.15
83.=
0.0
0.0
16.0
81.0
Xo.s
!7.97
1.0
2.0
6.0
15.0
48.0
0.18
Fmction
%Tatic
0 ,W
Fmcti..
Wghl Cens.wd
0.12
Spell.
-
2.32
Black
of Completed
29.0
24.19
Fmction
ti”fi
..= ?7,0
16+: Number of Spells = 260
25,39
of Spell
= 87
22,0
0.18
Age *1 kgiti”z
,.208.0
2,34
Black
~i~=$
Group 16+: Number of spells
236.0
24,91
Fmcd.n
of Completed SP<IIS
for W“caiio”
65.0.
29.0
12,19
TABLE 2.2-M
S-a~
Shfitic3
for SWlk by Edumtion
Group
1,<.ble
wt&es.fhw-W#ge
4ge ●t Bgiting
Of Spell
Meek, 3ime hfi Schml
,egitiq
.f Spell)
:mcti..
(-m&
.t
Eql.y*"tfor
19,0
21.0
24.0
120,22--
119.04
0.0
180
8.5,0
192.0
367.0
32.24
1,7
8.0
16.0
34.5
87,3
0,38
B],ck
x ngti of Coqieled
26,79
SPclfS
~idcs
4ge al a~ting
of spell
ueeh
Schwl
3in<c kfi
of High-Wsge
(_mmd
at
~1.ymnt
2,60
17.0
19.0
21,0
23.0
25.0
190.81
133.54
4,0
77.0
-- 174.0
291,3
424,0
55.29
2.0
10.0
50.0
167.8
of w.!!)
0.30
?mcli.n
0,26
HispaNc
‘mclion Egh[ Cc”mmd
0.2!
bngb
42.83
of Coql<ted
SPCIIS
Cl&eSOf&ti
kg. at kgiti”s
W!gh. and bw-Wage
Of Spell
WeeksSnce LRScbml
,e~itiu8
Of m~ii)
(meosu=dat
i~ .0
190.77
131.82
16.9
77.5.
12,53
1,0
i .0
Hrspanic
0,20
Fmcti.n
Wght Cenwti
0,03
835
~dea
Age at k~”g
Of SP.11
Sme hfl Schml
of Tell)
(msumd
●l
of aqleti
23.0
26.0
170.5
2863
435.1
1.0
12.8
39.0
21.0
= 319
20.21
2.58
!7.0
18.0
20.0
22.0
z .0
155,01
125.s1
0.0
520
122.0
245.0
3.9.4.s
33,07
4.0
26,0
S2.O
100.0
36.W
spell,
Age ●t Wgiti.g
Of well
Weeb
Sehwl(_suA
tifi
at
of Noneqloymcti
for Wucsti.”
Gm”p 11: N.ticc
13.0
of spells = 2W6
19.%
2.71
16.0
18,0
20.0
22.0
z .0
138.46
131.49
0.0
17.0
105.0
229.8
395.0
[,0
.*.U
..13.U
“..”.
J>*
.
7>..
of VCII)
Fmclion Black
0.38
Fmction WtSPatic
0.26
Fmetion Wghc Ce_md
0.17
bnti
11-: Number of spells
148
O.w
Ce-md
Wldes
~si~.~
Gmp
.fspel!s=
O.x
Fmctioo Wqatic
S=,
for 2ducati.n
24.0
0,42
Black
Wht
of Tmiti”g
.—..
ll.:N"mber
17,0
Fmcd.n
SPell$
~"catio"Gm"p
2.74
0.29
of tiq!etcd
Eql.ymenlfor
21.02
Fmctioa Black
b~
f.. Sd.catio n Group 11-: Number of SpcllS = 1226
21.11
!mcti.m Black
Fmctiw
12o4
18.0
0.M
Fmcti-
Spells=
!6.0
‘mctio” Wght Ccnm=d
Wecti
begiti
Nutier.f
2.49
0.26
Lnfi
G_pll-:
19.61
~mctiw mvatic
~gifins
=uc.li.n
of CoWleted
Spells
I 26.20
.—
I 36.17
I
TABLE 2.2-M (cent,)
V.dable
%Id.1
As. *1 &giti”g
of bw-W1gc
of spell
Weeks %nce bfl Schwl
b.gitins
of spell)
(m-mmd
.!
Eqloymnt
18.0
18.0
20.0
21.0
2$,0
91.48
104.47
0.0
3.0
54.0
.140.8
3[4,4
36.66
2.0
.9.0
20.f3
Fm.tion
0.14
Fmctio” Wght Cenmed
0.07
Lngh
3 I .93
~I~CS
Age .1 hgiti~
Week, since bfi Schml (masumd
kgiting
of **.11)
Fmcci.”
of High.W*ze
Of Spell
,!
Black
Eqloymcnt
21.0
33.0
26.0
1S6.78
126. S6
0.0
42.8
138.0
245.0
397,0
64.56
3,0
12.0
29.0
0.29
&sht Ceom=d
of Completed SPells
Qisod.s
~gi~nz
52,20
of ~~
~sh-
of spell
Weeks s>... tifl Schml(mcasumd
bcgiting
of well)
.,
and ~w-waz=
19.0
21.0
23..0
26.0
136.86
lM.26
3.0
47,s
.127.5
205 .s
.336.0
23,54
1.0
! .0
4,0
18.0
71,0
0,18
Fmclioa Wght Cc”s.%d
0,03
Ls@
14.82
Spells
~i~c~
Age al kgid”gaf
Spell
Weeb Stme b~ Schml (m~sumd
begiti”g
of wdl)
at
OfT~i~.s
18.0
19,0-
21.0
24,.0
27.0
158.42
140.16
0,0,
35.0
117,0
266.5
..445.5
20.51
4.0
9.0
21.0
34.0
69.0
Fmction WtWa<.
0.17
Fmcti.n
0.10
24.80
SPells
~I~c.
at&gitingof Spell
Wc=b since tie Schml(m~,”d
bcsiti”g
of wet!)
at
of NO.emelOym..1
2.S5
18,0
19,0
21.0
z .0
26,0
126.98
119,92
0.0
220
9s.0
207.0
365.5
26,W
I .0
3.0
7.0
20.0
58.6
0.37
Fmctio” ~ISp,ti.
0,15
Fmctio” ~rshL Cc.mmd
0.1s
tin@
16.17
SPellS
for Education GmUP 12 Number of Spells = 2350
20.91
Fmclion Black
of CoVleted
GtiuP 12: Number of spells = 405
2.88
0.3 I
of C.mplckd
fbr Sd.cation
21.66
Fmction Black
Ce”wed
of Spells = 262
Group 12: K.mb.r
!8.0
Fmcd..
of C.mple!ed
19S.0
2.40
0.22
Hispatic
Employment for ~ucalio.
...64.0
21,27
Fmctio” Black
Age
::
‘
20.0...
0.24
bn@
Group 12: Number of Spells = 207S
18.0
Fm.tie”
E&t
99.0
2.S9
0,16
Age.,
for W.catio.
,=43.0
21.67
Fmclio” Xtspatic
hngti
12: Number of Spell. = 1352
2.21
0,38
of Completed SPCIIS
Gm.p
20.19
Fmc:ion Black
Hispatic
for =Ucnli.n
>
TABLE 2.2-M (cont.)
V.ti.hle
wl~c$
Age ●t &ziti”g
of bw-W*Sc
Ew!.ym”t
of Spell
Weeks Since Lfl Schml (me*mmd
begiting of 9.10
at
0,0
0.0
26,s
37,12
1.8
8.0
22.0
3! .97
of Spell
Weeks since bfi
~h~l
~gi~ng
(meammd
Of Wgh.W,gc
at
Ew!oymnt
2.63
20,0
22.0
92.07
105.63
0.0
0.0
63,92
2,5
13,0
hclio”
0,18
Hl$patic
24.0
26.7.
85.0
23s,1
.
45,0
99,0
.
Z.O
.5.5
.....25.0
.28.0
147.0
314,0
74.0
189.5
0.38
Fmc!ion Ksht ~w~d
of C.qleted
Age at ~gi~ng
55.01
Spells
%!sdes
of W*
figh.
and hw.Wage
Of sP,lL
Weeks Since bfi Sbl(mtau:ei
bcgiting
of spell)
al
spells
%idea
of Spell
Week. st...
kfi Schwl
begting
of Spe10
Z.o
s .0.
29.0
96.74
96.93
0.0
23.0
75.0
145,0
3jl.0
20.79
35.59
1,0
! .0
8:0
29.0
74,6
of Tmiting
f.r =Ucati.n
(mca=md
at
29.0
0.0
35;.0
111.0
216.0
402.6
4.0
5.0
9.0.
no
56.o
130.05
17,54
-.
0.13
Cemxd
16.99
SPellS
~ldem
Of Spell
Weeks since LR %hwl(meammd
begiti.g
of qell)
at
Of Nowwloymcn%
Group 13-15: Number of Spell% = 726
U.ls
2.5s
20.0
21.0
23.0
X.o
2s.0
87.48
94,47
0.0
7,0
.56.0
135.5
291,0
Fmclio”
Black
0,40
Fmcti.n
KwaNc
0,!7
Fmctio” Wgh! Cc”-d
27.0
143.51
0,18
Age at *giting
2s,0
20,0
F“clio”
= 2W
22.0
2.82
0.22
HSTaNC
Gm”p 13.15: Number of spell,
24.54
Fmction Black
of Coqietid
= 99
O.w
Fmction Wght Cc-red
Fmction Wet
13.15: Number of spells
21,0
0.14
Age at Wgiting
Gm.p
20,0
Fmclio”
ofcompletd
f., Mucado.
2,76
0,29
Hivatic
Empl.ymen[
32.0
23.12
Fm<tian Black
bnfi
.22,0
OCSPCIO
0,31
k“gh
95%
Gm”p 13.15: Number of Spells = 980
23.65.
Fmction Black
b“o
for ~U.atiOn
75%
13-15: Number of Spells = 326
81.1!
0,10
W,d.S
50%
59.M
Fmcti.”
Age at &giti”z
for WUcation GWP
M%
20.0
0.17
spells
5%
19,0
Fmct;on KsPaNc
of Coqicti
I
m”,
2.29
0,35
fight Ce_md
sti.
22,15
Fmction Black
b“@
I
Met.
i
0.1s
.
TABLE 2.2-hi (cont.)
Variable
Wide,
Age al kgiti”g
of ti-Wage
of Spell
WeckF Since Gfl Schwl
bcgiting
of qell)
(meammd
.!
for Sd.cs!ion
Gm.p
22.97
2.26
21.0
54.75
83.61
0.0
32.54
I .0
16 +: Number .f spells = 156
22.0
23.0
25.0
29.0
.0,0
18.0
b7.8
262,2
5.5
13.0
34,5
87.0
I 0.17
Fmction Black
Fmc600
Eql.yw.t
O.w
H,qa”ic
,
Fmction Right Ce.mmd
0.12.
knti
24.41
of Complc{ed Spells
of High-wage Employment for Muc.6Q.
WWC$
Age al &giti”g
of Spell
We,k, Sncc tit Schml (“e,s”md
&giting
of ,pel[)
at
2.19
22.0
23.0
24.0
26.0
29,0
63.19
86,27
0,0
0.0
24.0
98.5
256.0
64,33
2.0
11.0.
29.0
66.0.
191.3
Black
0.17
Fmcci..
Wtspanic
0.08
Fm<ti.”
Ktshl Ce”so=d
0.45
.f Coqleted
5 I .95
Spells
%LS4eS of &h
Age at ~~i~fig
High .nd bw.Wage
of sP.11
Weeks 3.,.
GR Sch@l(mcasurcd
bcgimti.g .f spell)
at
Fmclion Black
24,0
69.@
78.93
0.0
9.3
49.5
108.8
2S0.3
1.0
I .0
5.0
16.5
60.9
0,09
bn@
12.96
Weeb 5,”,. kti Schm[ (meawmd
begitiq
of well)
at
Of Tmiting
17.96
for =Ucalion
Group 16+: Number of SpeIIS = 260
24.0
S.O
Z7.Q
30.0
107,42
10I.54
0.0
220
76.0
159.8
321,0
1S.26
4,0
4.0
5.0
17.0
48.0
Fmetio”
K,qatic
O.M
0.10
Fmction Wght Ce”Sti
12.86
Spells
%Idc$
of Spell
W-b
3“,.
kfi Schwl(meas”md
begitins
of spell)
al
of No.eqloyme.t
22.0
22.0
24.0
26.0
56.1S
83.25
0,0
0.0
16.0
81.0
250.8
17.97
1.0
2.0
6.0
15.0
48.0
Fmction Htqatic
0.%
Fmclio.
0.12
of Comple[=d Spell,
16 +: Number of spells = 604
Z,z
0.18
Kght Cenmmd
for Sducntion OWp
24.19
Fmction Black
hnti
I
I
22,0
0.16
AE. al &giting
29,0
2.33
Black
of tiwleled
.._.27.0
2539
Fmctim
bngti
or Spells = 80
23.0
Fraction R!ght Cemored
Of Spell
Gm”p lb +: Nuder
22.0
0.08
Age al &giti”g
foc ~“cati.n
2.36
Fmction WW*tic
~1~.s
Employment
24,81
I 0.20
of Completed Spells
spells z 1029
24,73
Fmcdon
k“gti
Group 16+: Number .f
12.19
‘-
29.0
TABLE 2.3-W
S-W
Stifiti=
for Enti&
&Simti..
Drigi” Sul”s
bw-wag.
E~loyment
hw.WaZe
E~Ioym<nt
High.W.gc
Eqloyment
Group
Stim.
m
Hngh. &
bw. wag.
Employment
High.Wigc
Eqloymnt
~.cation
.
by Edu=tion
Noxqloyment
Tmiting
Group !l -
0,16
0,17
0.53
0.16
0.31
0.0
0.25
0,41
0.01
O.m
High- & bw-Wage
Employmnl
0.05
0,08
rmi.i”g
0,05
0.%
0.01
N..eql.ym,”t
0,62
0.63
0,03
0.51
Schml
0.12
007
0J3
0.07
0.20
0,48
0.15
0.25
0,44
0.53
0.54
0.01
0,.w
Wucali.”
bw.Wage
Employment
High-Wsge
Employment
0,08
Gmmp 11
0,13
0,20
bti
High. a“d bw-Wage
Employment
0.M
0,08
Tmi”ing
Oa
010
0.03
N.”empl.yment
053
0,57
0.01
0,24
Schml
0,17
0,12
0.03
0.%
0,17
0.38
0,08
0,17
0.45
0,66
0,60
0.02
O.m
M“cati.”
hw.Wage
Gm.p
13-15
O,w
Employment
0,34
High. Wage Empl.ymenl
0,20
bti
Ki8h- & ~w-Wage
Eqloymc”(
0,07
0.07
Tmiting
0.04
0,[3
0.05..
Noncql.yme”t
O.*
0.44
0,02
0.15
Schml
0,22
0.27
0.10
0.10
0.20
0.32
0.05
O.w
0.49
0.76
0.51
0.02
0 ,m
Wucatio”
bw-Wag.
Evl.yment
tigh-W*ze
Eqloyme”t
&ti bWfiploymnt
&
tigh-Wage
O.w
0.25
0,13
‘
G-P
0,03
16+
0.05
O.m
Tmiting
0.03
0,20
0,05
Noneqloyment
0.33
0,+
0,01
0,08
Schml
0.21
0.27
0.13
0.0P
0.38
TABLE 2.3-M
by
Stifiti= for Entic6
S--
&mim<i.n
2rigi” Smm’
bw.~,.g.
Wucation
High-Wage Eqioym.1
sum,
No”cmployme”t
Tmhdng
Group 11-
0,19
EmPIoy&”L
Group
&ti High. &
bw. wage
Eqloyment
HighWage
EqIoymcnl
Eqloymenl
bw-Wage
Eduation
0.10
0.53
0.19
0.37
0.42
0.22
0.35
0,01
O.w
bti Xtgh- & bw-w.ge
E~loymcm
O.w
0.08
Tm;ti”g
0,05
0.01
0.01
N.”eq!oymc”:
0.67
0.63
0,02
0.51
Schml
0.15
0 .M
0.01
0.07
W“cati.n
hw.
High-Wage
Eqlo:ment
O.m
Group 12
0.17
Was= EmPIo>mc”I
0,08
0.12
0.54
0,19
0.30
0,39
0.49
0.49
0.01
O.m
&& K~gh. and tiw.Wage
Eqloyme”!
0,05
0.0s
Tmiti.~
0.05
0.10
0,03
N.ncmploymc”:
0.56
0.56
0.01
0.24
Schml
0.12
O,w
O.w
Ow
0,17
O.*
0.0s
0.21
0,37
0,66
0.56
0.02
O.m
-
~ucali.n
hw-Wage
Group 13-15
O.w
Eql.yment
0.04
High-Wage EqIoyment
0,14
bti Wgh- & bw-Waze
Employment
0,07
0.07
Tmitin~
O.M
0,14
0.05
No.eqloyment
0.47
0,44
O.m
0.1s
Schml
0.28
0.26
O.w
0.10
0.20
0,33
0.05
O.w
0.49
0.76
0.50
0.01
O.m
Wucnti.n
bw-WaEe
Eqlomm
High-Wage
hpl.ymem
0,04
0.16
Gm.p
0.03
16+
0.12
0.0s
TmiGng
0.32
0.21
0.05
N.ncwl.ymc”t
0,37
O.a
0.01
0.08
Schml
0.33
0,26
0,13
Om
h~
bwEql.yment
& Wgh.Wage
0,02
0.38
.
!
I
S-W
I
TABLE 2.4M
S&fitiG for Exiti by EdumtionGroup
I
bslim[i.n
Ong;n sums
I
W-w*g.
hloym.n[
Kxgh. Wage
~loym.nl
!
=ucati.n
I
bw-Wage
!
I
,
I
I
Tmirnng
N.”ew
Ioyment
GmuP Il.
O,w
0.%
~~~
0.05
0,64
0.01
0,72
0,01
0.02
Kxgh. Wage Eql.ymenl
0.15
High- & bw-Wage
Employment
0.31
0,66
T*iting
0.16
0.29
0,01
Nomemploy men:
0,39
0.51
O,w
0.10
Schwl
0,19
0,15
001
0.03
0,6!
0.12
O.m
0.53
0.07
0.12
0,69
0,02
0.02
~ucali.,
hw.WaEe
,
bti High. &
hw.wnge
Employment
0,22
Eql.ymcnl
SUN*
Group 12
0,29
EmPIoyme”l
High- Wag< Emp!oyme”t
0.13
~ti
Htgh- and hw-Wage
EmP!oyme”c
0.29
0.66
0,12
0,61
0.S4
!
I
TmiN”g
I
Noncmp!,>?mcnl
0,3[
0,64
Schml
O.D
0,3!
0.25
0.02
Ow..
0.05
0.01
0:03
0.42
0 1s
0.M
0.45
0,07
0.20.
0,64
O.w
0,01
W“ca( ia” Group 13.15
t
bw.w.ze
Employm.nl
H,gh.Wage
Eqloymemt
0,34
O.w
Boti High- & tiw-Wage
Employment
0.22
0,73
Tmiting
0.07
0.79
0,03
Noneqloyment
O.m
O.n
O.w
0.05
Schml
0.13
0.53
0.02
0 ,W
0.28
0.21
O.w
0.39
0.07
0,34
0.52
0.05
0,01
=.cati.n
.
0.31
meti
0.11
Group 16+
bw-WaZc
Eqloy
Mgh-Wage
Employment
0,07
=*
bwE~loyme”t
& High-Wag.
0.25
0,68
Tmi <“g
O.m
0:91
0,02
No”cwloyment
0.10
0.86
O,w
0,04
Schml
0.07
0.47
0.02
O.M
0.05
0.39
bw-Wsag.
Eql.yme”r
Wtgh.*,,ge
Eqloyment
0,20
0.12
0.07
0.05
0,67
0.05
0,07
0,74
0.01
0,01
bh
H,~h-&bW-W.gc
+Iomnt
0.30
0.67
Tmi~
0,19
0.26
0.01
0.6
0.44
O.m.
0.10
0.27
0.08
O.m
0.03
0.61
0.11
O.M
055
O,M
0.12
0,71
0.03
0.02
No”cqloy
me”:
Schml
Educ.tio”
bw-Wage
EmP!oymenl
HtEh-Wage
Employment
0,54
Group 12
0,28
0.10
0,28
0,68
Tmitiq
0.17
0.57
0.02
N.n<q[.ymemt
0.38
0,57
O.m
0,05
S.hml
0,33
0,20
0,01
0.03
0.42
0.16
0.05
0.51
0.M
0.2[
0,65
O,w
0.01
&h H18ti-a”d
EqIoy_nt
Lw.W,GC
W“cati.n
bw.
Gm.p
13-35
0,28
W*ge Employment
0.25
Hzgh-Wa~e Employment
0.07
~
&gh- & kw-W*ge
E~Ioymc”L
0.2s
0,72
Tmi&nS
0,08
0.78
0,03
Nowq!.yment
0.2s
0,70
O.w
0.05
Schmi
0,18
0.49
0.02
0.04
0.28
0.19
O.w
0.41
0.07
0.35
0.54
0.04
0.01
=“cali.n
bw-WaZe
Eql.ymtnt
Wtsh-Wage
Eqloyme”I
0.31
0.04
0,11
,.
Group 16+
0,25
0.70
Tmitiq
0,01
0.92
O,m
N.wqloymcnt
0,11
0,85
O.m
O.w
Schml
0.09
O.ti
0,02
O.m
be
bwEqloyme”t
& Wgh-Wage
0.05
0,39
.
Table 3.1-W
PadicipaLion
Percen&g&
=.cntion
Perid
ht.
I
11-
27
28
34.
39
45
6m
3m
6m
59
25
13
27
41
18
31
38
42
56
57
58
31
23
10
2?
12
31
31
19
40
16
25
56
25
38
48
49
15
50
67
28
47
15
39
17
37
18
?0
39
21
2+
28
4125
9
6!56
1$
7
19
26
12
32
38
3m
45
16+
17
1s
2,
20
25
6m
---
27
28
74
24
7
13
48
16
66
18
7919
20
8
56
72
34
40
S2...
65
51
33
tiW
56
46
60
.32
18
24
B
59
39
20
.28
5I
26
68
35
36
21
7
11
30
22
36
SO
17
12
21
32
67
19
14
14
47
.x
17
29
38
22
@
?1
10
___
19
___
31
34
34
15
28
43
51
22
34
25
37
ti tis able
for a nation.Uy
am .sttiatd
r~=se”~tiv.
to the ~riod
1984-3987.
20s comswnds
m age 27.
19
8
13
9
17
12
17
12
10
21
18
20
17
20
[=s[ squares. The .p~r cnt~ ti =ch ceU
uskg weightd
sample, and the ti=
lower cnluam for the racednic
groups Wit.,
Black, and Hisp”ic,
tispivcly.
2 hte 70s, firly
80s refers to the Wriod 1978-1983; and Mid 80s refers
3 b:.
T-s
com=~nds
LO age 19; &r!y 20s mfem to age 23; and hte
t4
Zj
,E
1 The ~mnQges
~fid
mm.s~”ds
to figur=
1[
:6
37
53
28
2k12
22
32
23
14
171716107
22
16
12
13131277
_
14
25
17
__.
28
19
13
21
22
15
ti
66
18
13
32
56
39
45
4326262513
55
31
38
26
9
42
47
!6
31
35
21
-__
10
35
26
s
37
10
10
24
27
9
28
28
21
8
11
19
18
60
3
46
64
56
.4
36
20s J
21
24
49
*
[56
30
36
37
36
b!.
28
66
37
34
26
49
12
IS
35
38
38
38
22
20
33
32
8
28
2Y
22
4145
5
43
20s >
22
32
n
6
19
35
54
6
20
-.
54
15
17
$Y
12
9
13
13
41
7
(5
brly
41
8
5
8
38
30
37
>
34
32
25
24
46
h!e Tee”,
18
18
52
~Y
15
15
48
IY
25
27
30
Edumtion’
14
17
38
38
22
13
31
f,m
II
IO
36
3P
18
36
39
2Y
9187
23
35
20s *
Is
17
30
30
IY
13-15
28
25
24
12
22
59
59
Markets
md
11
12
10
4!
2Y
hhr
by Age
Mid 80.1
ht.
20s J
22
30
IY
Men
arly
24
22
in bw-wage
for Young
70s, &rly 80x :
h!< Tc<”s 1
]m
Rates
31
Table 3.1-M
PaflicipationRat= h bw-wage ~~r MarkeK
Per=bga
T
for Youg
Men by Age ad
Edumtiou’
3m
38
11-
6m
I
36
45
22
31
z
19
30
I
z
34
15
24
36
34
20
43
I
30
23
17
28
22
1,
11
74
47
38
37
39
- 45
70
3m
80
41
13.15
43
6c”
36
24
49
27
57
35
67
IY
+
6S
74
24
I
40
55
52
w
:24
14:12
w
-
-
~Y
64
74
36
47
36
20
31
[4
28
18
13Z9
41
31
18
43
32
13
72
.
81
70
L
53
&
W
19
20
-I
13
=.24
u
1 ~e
~rcenmges
rcpti
h KS mble am .sttiatd
co-~.d$
to 6gutis for a nalio”aUy qms..~tiv.
groups ~ite,
B1.ck, and Hispanic,
-Ftiv.Iy.
‘ bte
70s,
‘ Late Twns
13
22
12
I
12
13
24
___
14
16
to mge 19; =rly
20s refen
I=st squar.s.
us hg weigbti
sample, md the tirm lower
to age 23: a“d ~te
13
6613
17
~e
c“tti
firly 80s mfem to tie wriod 1978-1983; and Mid 80s mfem to tie pried
cotispnds
17
7
20s am~”ds
uppr mt~
h tich c.U
are for tie mceA”ic
lg8*1987.
to agc 27.
9
27
Table 3.>@
Percentage of =tigs
Avemge
Rweivd
Per-tige
from bw-Wage
Eqloyment
by Age md ~uution’
Mid 8h>
b[< Tc<ns >
..
U
come
9[
85
79
86
85
76
66
76
‘1
77
65
53
5?
41
80
69
68
;1
67
56
86
80
19
70
70
56
58
;3
70
12
58
59
43
62
84
46
32
76
65
49
71
76
67
66
52
39
56
56
77
58
28
43.
78
64
43
69
55
34
61
41
17
69
54
49
73
39
63
47
30
55
36
3
43
70
80
73
57
77
62
w7246
.
52
48
66
59
37
39
39
a
53
I
37
51
72
29
43
26
35
74
80
69
59
46
63
19
69
88
62
85
88
84
80
74
6!
70
63
48
38
82
73
80
73
91
80
85
66
69
62
71
58
47
59
19
62
81
52
52
76
82
87
76
65
16
64
68
80
16
59
68
7s
83
79
65
14
13
32
73
71
44
50
61
56
m
53
51
35
53
54
61
80
59
84
61
54
’26
23
I
40
48
4?
4<
3:
38
88
82!70
80
75
I
65
w
88
5<
34
77
74
“’
74
84
78
7?
84
65
78
80
81
65
77
10
52
72
54
71
60
47
II
31
67
56
88
74
63
48
71
58
73
70
61
47
56
48
37
46
37
37
32
66
I
69
47
56
67
~
58
34
34
39
39
6S
41
50
79
70
5Z
61
47
16
77
89
60
23
65
75159
87
72
48
36
73
81
BE
60
74
81
26
59
I
85
60
31
31
33
58
43
a
45
53
69
66
50
69
30
72
49
72
40
84
I
89
88
76
71
48
68
61
81
61
82
70
83
36
89
61
85
89
20, ,
4s
31
63
76
53
72
83
69
93
83
66
33
<5
76
57
46
56
87
ti
65... 55
w
41
a
57
56
:1
41
69
67
>4
54
39
17
!5
60
51
46
88
87
60
62
70
>6
65
74
79
‘6
7.1
&
54
2Y
85
70
59
65
IY
80
M
70
77
‘3
83
83
86
;3
ht.
=Cly 20s ~
31
22
55
I
58
u
46
62
41
Table 3.2-W
84
89
89]75
78
84169
65
64
77
85
18
57
93
87 I 79
a2
81
I
68
3m
6m
lY
w
47
45
43
36
42
2Y
44
38
27
26
62
58
52
62
55
52
45
55
31
43
47
43
35
22
38
38
27
.
.
25
68
57
I
61
60
S6
29
.28
56-57
35
38
48
28
37
78
39
20
27
1“
56
56
68
48
47
33
28
3a
32
E
32
.
.
M
40
49
41
33
30
30
30
24
M
20
2Y
53
47
49
3a
41
33
42
6m
[Y
2Y
‘ me prc.nmg=
41
43
43
@
45
69
69
54
6a
62
49
M
21
28
6a
5a
67
61
M
so
36
49
60
63
50
39
52
34
26
38
24
37
28
54
68
51
66
37
u
50
57
59
4a
60
62
65
36
43
57
29
59
41
41
61
49
36
34
28
56
51
27
24
m
155
6
18
15
32
13
45
46
36
51
56
3S
36
22
39
24
54
1
38
37
33
27
36
27
22
14
32
60.62140
32
25
20202014627
52
3m
;1
30
42
51
33
42
6m
55
51
61
2Y
47
57
$1
i8
lY
S3
66
*
16
34
43
52
68
48
43
3m
60
49
83
22
60
-
62
a
45
I
71
7?
38
62
70
iz
30
37._ 4L
26
34
48
26
I
42
24
35
4r
43
50
u
45
46
57
S4
61
il
54
55
6m
28
78
6a
ia
17
62
3m
39
!2
69
61
a
64
2Y
82 I 73
21
M
16
16
16
I
10
23
41
D
32
27
la
*
repti
a-pnd:
to figur=
for
UPS W:te,
Black, and
‘ ~.70s,
=rly
80$ refers
1 hte Twns amespnds
to
h W: mble am =tkatd
a nat?o?aUy r~xsentilive
Hispan,c,
r.sWdvelY.
m tie Wriod 1978-1983;
age 19; Early 20s refes
usbg ~ighti
last
sample, and tie ti=
and Mid 80s ref.=
m age 23; and W
s uar=.
1 ower
~e
.ntti
to tie Fried
20s w=~nds
upwr entw h =ch
am for the m-~nic
19861987.
to age 27.
CCU
Table 3.2-M
Permnhge
of =tigs
R=ivd
from kw-wage
Employment
Avemge Pemntige
by Age ad ~u~tion!
“cation
11.
>Ul
divid.al
lb.,
come
bm
t
IY
,4
87
77
68
76
67
61
76
76
68
81
80
62
70
70
161
70
79
;3
90
84
77
85
79
63
80
74
81
88
86
15
83
81
61
78
76
I
]
3m
78
>ml Family
.n[m”sfer
come
hm
,6
86
70
79
66
lY
,5
79
70
58
58
;S
.70
P
hm
>uI Family
come
51
70
62
M
S8
73
78
65
76
55
60
41
48
83
3m
69.
62
69
t
77
59
68
37
76
S8
83
62
61
74
72
54
53
65
65
73
51
65
62
42
81
53
62
43
82
73
8!
72
59
75
63
79
89
86
.d
84
76
62
72
62
41
67
52
74
84
82
63
53
42
61
48
59
14
72
81
67
66
80
46
82
84
83
71
‘i’
S2]49
74
&‘i:
341171
76
74!55
71
69
63
64
42
52
35
74
89
71
51
&
56.
51
75
59
58
!1
IY
66
65
e
52
84
70
53
51
63
81
76
57
75
67
72
68
47
67
S8
49
61
57
38
5g
52
67
17
71
66
76
50
65
58\49
68
W
12
&
ii:
7[
82
6S!55
I
2,
55
I
74
45
58
80 I 64
83
61
81
79
86
hm
2Y
3m
—
6m
otil Fstily
,Come
2Y
55
26
63
55
68150
7S
70
65
43
81
41
38
68
60
4S
67
37
79 I 62
80
71
I
57
69
54
59685
51 55
~~
72
67148
73
*
74
77
59
54
43
65
51
81
35
72
83 164
74
75 I 56
62
37
31
4S
21
49
49
53
51
63
47
63
43
50
76
7[\50
69
59
I
49
68
45
e
616265
31
71
30
S94936S733
73
a~62@335a23
37
II 80
47
&
48
72
71
62
62636748
85
7a
79
74
50695946654134632
78
84166
51
55
70
57
=
54
41
mm
75
4%l\81
49
60
60
IY
—
@
45
64
72152
F
IY
37
68
72
.til F,ti!y
‘O”lmnsf.r
WOm.
43
47
66
‘i;
48
61
41
39
ti
5647355230
35
45
31.
29
39
21
Table 3.2-M
COnt.
—- ... .
ducatim
h,ome
M,.*ux
P.nd
3m
13.15
hk
93
91
82
6m
87
91
85
73
80
83
79
60
84
80
60
47
70
66
61
61
65
6m
TOUI Fatily
N.”tmnsfcr
h-ome
65
61
S9
53
60
54
62
46
52
M
70
65
34
33
fim
65
60.
67
60
59
S1
60
52
61
46
55
67
S9
51
39
65.
S8
51
43
4a
51
32
3a
3m
.
.
76
72
70” 54
6m
.
.
.
69
64
S9
41
..-
55
46
so
a
.
.
.
38
30
.
.
69
51
57
M
49
37
6m
.
.
.
s,
4s
37
29
.
.
.
38
32
al
62
-=
3m
.-
-
26
-
57
31
74
S6
49
41
Toml Fatily
w...
.
.
.
S1
45
.
.
.
39
33
55
.
.
.
27
31
35.
74
70
68
63
6S
52
38
5s
53
67
61
56
42
62
52
70
67
52
W
63
62
34
27
55
52
67
60
Ss
42
39
36
18
13
62
50
39
34
51
39
31
20
34
26
17
10
55
43
38
48
39
53
---
12
47
.-.
63
39
---
49
20
S4
---
31
18
10
66
61
45
61
51
35
67
60
48
34
79
70
54
50
--
--
5S
61
--
-..
47
S1
50
36
---
34
38
38
24
---
24
22
---
S5
16
---
47
37
69
S1
S9
42
49
33
---
34
39
37
Z
---
23
31
56
S7
47
41
32
31
27
S6
87
Sa
46
59
so
80
50
42
53
3s
S1
35
26
41
22
22
22
17
4?
41
67
42
45
35
36
64
3s
m
31
26
*
27
26
24
15
26
15
16
6a
41
4s
63
35
20
42
3s
36
39
31
26
W
26
26
24
16
24
27
64
24
34
14
27
36
47
S1
34
#
56
61
S0 .32
S3
25
26
49
z
34
Is
58
39
48
16
50
48
55
19
32
63
69
57
32
30
31
54
48
3a
34
70
64
42
33
31m40
?2
17
32
69
54
43
27
30
35
49
62
33
41
38
49
49
51
51
27
60
61
S5
32
64
S1
51
18
63
45
61
43
70
56
73
53
S2
27
75
69
62
63
5s
32
73
39
63
47
W3823
27
2Y
47
54
43
38
IY
5s
75
34
49
6M
62
79
73
82
57
41
56
54
38
69
55..
27
2Y
so
83
60
38
IY
58
30
50
TOUI Fahly
Nontmmfer
kome
57
91
83
70
70
3a
36
54
7S
64
80
74
6
*4634
57
14
53
57
3m
54
31
43
lY
58=
80
87
7s
41
54
lY
83
50
69
Toml
hi,$. idual
Lb.,
hcom.
71
57
76
16+
62
93
84
~ti48
33
34
89
41
43
S7
2Y
55
S3
S7
lY
64
61
65
TOUI Fati[y
k ome
d8
90
85
56
34
70
3m
65
45
S8
2Y
75
55
57
lY
75
69
66
63
70
3m
75
47
al
2Y
86
62
80
IY
83
74
88
T.ul
titvidual
bbor
. ome
75
82
92
91
Mid SW
70s, &dY 8W
26
14
16
21
Table 6.1-Q
SUmV
T
hw.wage
Kgh. Wage
&*
Tmiting
3E
77
11-
67
74
12
75
96
76
37
EXWrienM
3s
30
37
32
w
w
a
55
M
28
41
32
28
27
25
II
13
12
[2
14
11
II
13-15
39
m
16+
23
=.
10
14
11-
278
I 43
228
112
57
93
165
a6
137
12
339
263
326
I*
105
la..
193
157
186
13-15
4!0
374
420
194
172
198
215
201
223
16+
405
w
I 95
2W
201
210
126
207
11-
84
3
4
2
2
5
2
!
12
9
6
7
6
4
4
3
3
4
13-15
10
16
4
4
7
2
6
9
3
!6+
6
1
6
3
4
3
2
3-3
11-
30
59
31
!7
29
17
13
30
14
12
27
25
23
1s
14
12
12
II
10
.426
.25.
13-15
33
23
!9
II
8
7
21
15
II
16+
39
18
42
18
8
19
21
9
24
11-
[37
241
180
92
142
!13
45
98
68
z
48
‘6
~K60
‘-
47
130
:
:ml.lo
;*
11-
0.8
0.78
0.78
12
0.74
0.82
0.75
FL
H,gh-Waze
for Cumuldiye
Black,
HiXc)
~
‘Uction-
N.”emp!.yment
bw-wag.
Shtistics
wte,
0,65
0.57
0.63
0.55
0.61
0.56
0,64
0,71
0.65
0.42
0.58
O.@
0.39
0.34
13.15
0.5
0.51
O.M
0,42
0.22
0.26
0,21
16+
o.#
0.44
0.38
0.31
0.33
0.23
0.24
0.22
0.24
11-
0.98
0.87
0.97
0.93
0.68
0.88
0,96
0,75
0.9
12
0,99
0.96
0.98
0.9S
0.86 _.
Q.92
0,96
0.89
0.95
1
1
0,99
0.97
0.99
0,97
0.97-
0.98
13-15
1
16+
I
1112
.
1
0,98
0.98
0.97
0.98
0.99
0.98
0.37
1
~
0.23
O.m
0,2
0.11
0.1
0,24
0.14
0.14
0.34
0.32
0.3
O.M
O.n
0.19
0.17
0.15
0.17
0.19
0.09
0.18
0,21
0,08
13-15
0,32
0.33
0.16
0,2
16+
0.33
0.31
0.33
0.17
0.17
0.12
0.2
0.19
0,17
11-
0.53
0,69
0.53
0.35
0.5. .
0.35 –
0.31
0.5
032
12
0.5
0.49
0.4
0.34
0.32
0.3
0.3
03 I
0.26
13-15
0.62
0.54
0.46
0.34
0,27
0.24
0.46
0.38
031
16+
0,64
0,62
0.59
0.42
0.4
0.39
0.52.
0.47
0.51
11-
0.99
1
0.99
0.98
0.99
0.98
0,86
0.89
0.87
12
0.91
0.95
0.91
0.84
0.9
0.85
0.68
0,74
0.62
13-15
0.85
0.92
0.86
0.74
0.84
0,72
0.5
0.68
0.6
16+
0.8
0,82
0.72
0.7
0.72
0,57
0.5
0.46
.
Table 6.1-M
Su~V
SMtis\ics
for Cumulative
Black,
H1~mIc)
~te,
=
‘-’ion
Aw. wage
iigh- wag.
bh
T.tiw
~
:=~o
~~
11-
n
76
%3
47
42
50
25
35
32
12
86
95
66
64
63
49
22
3Z
17
13-15
48
45
37
36.
33
2a
12
13
9
16+
31
21
24
15
11
12
16
9
12
11.
271
148
217
Im
52
78
17[
96
139
205
12
330
177
342
131
Iw
138
199
111
13-15
a2
378
182
167
190
220
212
227
16+
05
427
417
~z.
I 95
202
207
2W
.225
216
l!-
7
3
4
3
1
1
4
2
2
s
4
6
3
2
4
12
8
6
10
13- Is
10
15
7
5
1
4
5
8
4
16+
1
8
7
4
4
3
3
4
3
11-
33
48
33
19
21
17
14
27
16
!2
25
20
24
14
11
14
12
9
10
13-15
32
17
[8
14
7
8
18
10
9
16+
29
14
32
!3
7
13
i6
7
19
11.
137
245
183
91
la
113
U
101
70
71
122
79
41
76
54
24
4s
25
?%
64
41
D
*
5
11
II
49
49
35
33.
16
14
II
NonevIoymc”t
13.
15
16+
A
Wgh.Wag.
Wti
Tmitiw
No”evIoymcnt
.30
..35
24
Panic ;pa:ion Rate
Uu$.t!on
bw.was.
Ex~rienc=
Y,,.
Ym. !-10
~
11-
0.83
0.78
0,8
0.75
12
0.79
0.82
0 ,7s
0.74
..0,63
0.75
13-15
0.61
0.6
053..
.
0,55
.0.5.
16+
0.52
052
.0.41
-..
0.35
029
11-
0.98
0.85
0.96
0,9
12
0.99
0.97
0.99
0.92
13-15
0.99
1
1
16+
1
1
1
Ym. 6-10
1.5
0.72
0.49
0.55
0.5
0..69
0.37
0.46
03
0.22
0.24
0,17
027
0,31
0.26
0.22
0,6
0,81
0.97
0.77
0,9
0.87
.0,92
0.97
0.93
0.98
0.98
0.98
0.99
0.97
0.98
0.98
0.99
0.99
0.99
0.98
0,99
0.99
0.12
_.L4
11-
0,33
0.22
u
0.2
0. I
0.1
0,18
0.13
12
0.3
0.28
0,34
0.23
0.21
0.27
0.12
0.1
0.14
13-15
0.34
0.35
0.15
0.24
0.24
0.1
0.17
0.19
0.08
16+
0.35
034
0.29
0.17
0.18
0.13
0,22
0.2
0.19
11-
0.54
0.65
0.53
0,36
0.43
0.35
0.32
0.48
0.32
12
0.5
0.47
0,47
0.34
0.3
031
0.32
03
0.29
13-15
0.58
0,49
0,43
0.35
0,27
0..26
0.4
0.31
0.26
16+
0.57
0.55
0.ss.
0.33
032
032
0.45
0.43.
0.s
11-
0,99
0.99
1
0,97
0,97
0.96
0.88
0.88
0.88
0.85
0.88
0.85
0.66
0.7
0.58
12
0.93
0.94
0.9
13-15
0.83
0,9
0.85
0.74
0.84
0.76.
0.41
0,61
0.52
16+
0.82
0.81
0.68
0.71
0.71
0.57
0.52
0.49
0.39
TabIe 6.2-@
.
1-5
Table 6.2-Q
tint: .. ..
hbm
Market
SUN,
m
.25
10
~
l!-
Fmiti”g
Ptm.”,ite
W.catioa
000
000
0
1
000
000
0
00
000
000
0
00
lb+
000
000
0
0
12
13.
[5
11-
17
<o”em.
12
,1.ymc”t
13-15
39
21
0
18
50
22
17
13
13
8
2
0
16
9
59
89
61
53
48
&
.=, 41
29
24
16
S6
25
59
57
80
lM
103
129
201
164
!91
252
221
000
6
21
9
31
63
39
67
124
88
114
203
15s
000
070
9
33
14
32
67
44
58
110
79
16+
000
000
12
16
4
42
41
37
88
91
73
181
154
181
232
2W
231
260
25 I
258
229
36
71
47
2
19
0
qo”. m.
13-15
000
,1.yment
jp
16+
L000
11-
000
00
hw-
!2
000
u.~e
13-15
+
0
w
83
11-
was.
15
~
12
kw-
50
72
122
96
I 19
29
66
26
77
135
142
211
170
216
4
19
3
32
56
32-
75
105
79
128
183
I 47
_ 24
32
15
64
___
68
56
111
117
99
_ !30
6
16
II
48
60
55
95
135
127
000
0
16
0
40
63
45
90
115
110
000
000
0
00
0
8
0
27
39
41
16+
000
000
0
0
0
0
0
43
3s
53
11-
4400
108
0
57
182
54
143
236
!59
221
255
~6
2S3
~gh-
1?
74
0
34
L59
?2
142
217
I 80
214
254
231
257
260
260
260
wag.
13.
[21
96
147
203
174
214
246
227
248
259
254
260
260
260
260
16+
120
169
[17
187
114
I 79
235
2M
US
257
260
260
260
000
000
0
0
32
0
258
11-
0
0
0
11
3
2
12
000
000
0
00
0
0
0
425
13-15
000
000
0
00
0
0
0
10
30
0
16+
000
000
0
00
0
0
0
37$
11-
000
000
0
1
10
48
15
51
91
50
12
000
000
0
00
4
5
3
35
35
35
13-15
000
000
0
00
11
10
4
67
39
25
16+
000
000
2
0
1.
20
9
24
56=77
11-
000.
4209
23
84
42
60
167
lM
113
222
184
Nomm-
12
000
000
7
21
6
29
61
31
64
151
78
?Ioymnt
13-15
000
000
0
82
7
29
IS
19
57
30
16+
00
bw-
11-
2
12
No”emp!oyme.t
bh
rmiting
W.g.
+
1S
0..
.88.
Q.,
0
0.
000
0
00
18
16
16
47
32
35
3
13
65
2.4
55
1S6
.95
121
217
177
196
259
241
000
1
10
0
22
65
_20
76
la
92
153
241
203
13-15
000
000
2
16
5
16
43
24
48
91
71
16+
000
000
3
35
38
21
32
84
63
79
14
.
-
-
-
-
Table 6.2-M
11-
11
000
awwag.
%gh-
.
wa~.
titi
rraiting
Xonem.
,Ioyme”[
117
119
D189
14
67
56
129
138
107
640
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Numbr
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89
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12
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28
24
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282
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22
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58
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21
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50
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35
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13
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30
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168
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89
84
105
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177
148
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196
220
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2
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783
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337
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16
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15
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21
32
32
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52
59 ~
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58
39
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16+
39
43
58
13
13
Tab~o$t4W
Pcc.ntiIe
aH
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7
13
19
18
26
12
869
13
12
15
24
22
13- 15
233
6
75
14
14
16+
2!2
4
24
96
11
10
62
56
81
85
82
45
44
42
73
66
62
12
31
29
27
6i
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11
26
64
20
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132
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3
5
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13
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10
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27
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28
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54
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102
91
112
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75
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188
11
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14
17
17
41
57
50
70
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14
14
19
30
25
&
57
54
78
84
91
138
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555
12
12
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35
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97
96
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224
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19
22
68
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156
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12
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88
71
105
243
172
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14
83
85
193
198
185
---
15
18
11
26
30
16
31
29
27
16
2
21
492
35
12
111
212
43s.
30
16
58
33
54
i3 -15
121
2
52
8267
41
62
42
88
113
75
16+
111
1
22
267
a
17
21
30
33
36
11-
4s5
10
16
13
55
60
52.
80
96
79
12
224
s
5
11
13-15
3
44
8128
41
~
75
121
16+
212
4
24
95
11-
122
2
64
7
Nonem-
12
121
2
43
ployme”l
13-15
121
2
32
lb+
112
2
24
Tmiting
24
31
29
i4
14
23
.26
68
77
6a
68
S4
18
b7
33
43
145
72
29
la
37
71
50
22
16
19
38
24
16
21
52
26
W
39
31
37
26
10
20
10
28
11
20
57
6117
16
410S
11
9812
22
22
-
-
-
kgti
Table 6.4M
of SFIIS Dutig 10 Y%= Followtig
Wte,
SChWi
Black, HISP=C)
PeCe”tile
aH
.!O
50
18
79
434
ow-
12
464
11
12
10
24
{*Z.
13. 15
56S
11
13
17
30
16+
87
13
II
17
23
11.
544
11
11
11
30
.
11
19
74
25
20
52
52
43
81
91
70
30
34
56
58
56
84
90
90
17
33
57
29
63
98
59
93
34
30
73
81
76
180
2*
215
105
164
34s
330
421
14
24
25
32
63
65
86
186
149
233
-
428
-
68
12
18
22
37
57
65
102
165
2~
229
m
439
494
11
1
2
21
833
16
13
13
30
25
29
25
17
24
1!12
11
1
2
12
435
57
48
55
13.15
11
I
I
22
3
15
15
19
43
.54
61
95
118
16+
111
1
22
3
13
14
19
27
28
42
52
SI
12
16
15
26
32
32
55
57
57
82
81
84
15
11-
587
12
4
13.15
222
!6+
21
Il.
2
..7
2
132
10
7
19
17
25
38~m
67
61
65
4
54
10
11
11
26
22
25
62
52
54
4
24
959
19
II
21
44
19
55
3
zonem-
12
12
1
!Ioymcnt
13.15
12
16+
11
I 12
84
9
27
343
8
14
1
243
5
13
2
3
35
434
9
8
10
18
19
464
11
13
10
24
24
14
20
11
10
16
11
12
10
6s5
14
14
13
8814
22
22
.30
465
16+
7s
11-
5s4
%gh-
12
wa~e
13-15
11
18
6S
40
57
170
76
8
20
35.
20
42
67
47
8
14
25
19
26
&
37
22
22
27
48
49
55
19
36
.43
39
56
80
74
19
50
52
41
S7
94
72
53
54
52
82
88
90
15
8912
12
13-15
:B
58
45
16+
bh
37
41
99
.
90
a
44
13-15
1-5
~
35
14
{age
Nan.
75
17
15
66.6
aw-
18
15
12
miing
8
128
figh-
ah
<
25
11-
31
34
19
15
28
42
24
s4
52
4s
83
27
34
27
59
82
63
156
228
164
39
36
40
lW
88
135
----
56
5.9
8.5
187
154
239
---
n
120
212
-
-
---
16+
77
12
19
22
11-
11
1
2
21
432.
1s
10
10
26
19
17
12
11
1
2
22
433
19
15
21
S2
4s
so
13-15
II
1
1
2
3915
17
36
62
58
78
124
II
I
I
35
25
28
36
45
52
57
16+
~.
41
30
2.
60
8
14
17
.
. .
Table
6.&M
Cent.
11Tmiti.g
8
10
9
13
16
1.s
29
31
32
5s
55
55
84
77
81
17
23
19
26
41
44
41
66
66
68
12
8411
13
11
13-15
212
6
75
12
12
12
28
21
23
66
49
52
16+
2.12
5
34
II
6
II
22
12
26
52
26
63
4
11
II
35
20
34
79
48
67
190
98
53
8
16
9
22
40
D.
48
76
S4
6
14
10
16
29
22
29
S1
@
.8
10
13
~24
26
35
_55
57
63
18
17
17
35
40
39
61
97
111
11-
242
12
121
3
13-15
121
2
5
~ 16+
m112
:3
35
11-
333
8
69
h.,
12
5s4
12
12
!0
29
21
22
56
59
47
I 03
110
81
wag.
13-15
797
II
12
12
23
26
34
63
65
65
103
93
88
16+
10
16
13
18
31
22
3s
75
38
76
122
88
114
249
25 t
Nowmployment
j
9
11
6
.3
11-
555
13
12
12
35
39
37
98
111
lM
217
HiEh.
12
878
22
20
..’24
64
59
83
190
187
-
---
wag,
13-15
16
12
16
35
32
42
102
88
120
-
216
-
---
16+
8
10
14
~
27
38
74
8S
102
202
222
m
---
11-
11
1
2
22
17
15
16
3S
29
40
12
11!
13
3
14
39
21
32
57
49
68
13-15
!1
1
5
27
25
33
61
51
7?
114
121
16+
11
1
1
2
!7
23
24
w
49
45
11-
465
9
16
52
60.59.
86
94
IW
,2
223
5
5
36
34
40
76
61
63
13-15
121
343
30
96
60
64
bti
Tmiting
!057
2..12
13.
2
..2
14
..11
2
10
{1
23
33
.31
161223
7
11
8
32
Z
16+
212
4
24
859
19
9
21
45
16
S4
11-
121
2
74
7
22
12
19
61
3S
47
166
7s
Nowm-
12
121
2
43
6
13
1
19
32
18
37
70
42
ploymcnt
13-15
121
2
3
4!0s
11
21
17
18
36
28
16+
I
2
24
7711
20
18
20
41
35
41
.1
2
..2
●
,
-,
.
.
Table 6.5-M
Hotimn
DumlionsTo hd Fmmbw-WageEmployment
During1O-YWI
mite,
Black, Hiwmic)
Pementiles Excludin~ GWp at -m
Until
11-
fim J& given
12
Rm
13.15
timtion
WIoymnt
is bw-Wage
3B
8
&
aE
B
‘ii
.*
Uti[
given
imo Mgh.Wage
98
11-
99
12
13-15
87
91
.18
Im
Im
MNM
~4452
11-
80
78
Tmini”g give” C“IW
12
14
82
78
.
1S
i.!. h-Wsge
13-15
50
51
44
16+
mm.,
17
I@
g~
9
17
30
16
15
32
54
32
w
51
91
62
I
9s
352
~::
::!
Z3
17
17
13
S]
61
S4
181
173
~f
53
~
I66
194
3W
---
183
-
237
-
60
78
lb6
212
29S
---
mwn~
53
41
53
144
9s
146
*4
269
5W
Mmm
34
35
44
13s
144
160
4s7
511
-
mmn*
57
26
28
133
I 19
118
316
393
405
---
225
489
44
44
38
Hmm.,
20
17
28
55
no
64
I 13
53
69
53
m~m
19
25
24
6S
78
64
232
188
167
---
: 50
49
44
16
22
29
82
67
69
377
173
201
-
62
54
46
mmm
~o
26
83
259
162
313
---
64
62
S9
M.m
93
342
3W
303
---
~,na
m
..
v,
-_i~
-
.
.
-
-
-.
216
E
4!2
---
66
1 Mm.
;:;
~a:
16S
284
:::1
:;:
i:i
/::
;“:i
MM..
Iw
UNil
~
98
Im
3B
14
iii
96
16+
h“tion
,0
16+
:::
bw-Wage
15
83
a=
ti”!im
10
m
‘Rti%’%g’
YB
.
.
.
----1
---
.
.
Table 6. S-M
DumtiomTo hd From bw-Wage EmploymentDutig 10-YwrHorimn
Wite,
5B
F
H
:~:
23
32
48
34
58
92
62
!03
202
135
238
365
148
~ 41
23
41
9
II
10
13
20
15
25
42
28
41
71
59
74
133
90
67
55
37
53
6106
12
!8
14
24
34
U
49
55
43
91
88
85
74
85
E 47
49
58
12
II
15
19
29
36
58
56
63
91
90
97
83
18
80
mnam
8812
20
20
11
42
77
63
87
221
141
161
~3
285
12
79
82
75
m..
II
14
9
28
31
19
59
61
49
1is
126
98
213
260
182
13.15
61
60
53
M.M
8
10
14
17
18
30
41
45
52
75
89
84
134
156
145
E 16+
52
52
41
! mmna
17
14
22
31
25
40
656473
116
81
107
I 1-
98
85
%
mm.
2!
54
62
34
205
196
229
-
12
99
97
99
232
-
m
12
fim J* givm
12
46
43
41
13-15
w
67
16+
~ 19
,11-
Mgh-Wage or ~
given c~
~mlio”
UMil
&.
&w-wa~Q
I
~mtio”
h-W*ge
Omv i~
~mti.m
Umil
sivcn
Ht&-Wage
Until
Tmitiog given C.IV
13-1s
12
19
67
62
73
403
39
66
112
149
343
---
---
M
65
83
117
266
285
347
---
--
“n
64
49
49
!63
102
la
499
36
62
40
129
2M
143
457
-
210
242
38<
4*7
292
2S9
237
---
2W
---
---
---
---
---
---
---
---
Im
!W
Mm.
I [-
83
78
80
“,
12
79
82
75
M..
52
w
J3
“a
52
41
mm.
m
M
,W
546553mwm
150
41
47
.*
m
m
584943mmm
!::
575555
BE
-.
---
20
Mna
16+
-
32
Im
3E
510
mmna
Im
‘bt
9913
18
Iw
13.15
~668
21
B 16+
inl” bw.W.#e
‘F’”’
~ ~
iii
24
37
m M
‘:i”
18
43
3}fi$-wag.
‘Z;
10
I 1-
in
:i;
5
timtion Ufitil
fim w[oymti
Black, HisTmic)
MM’
Ml
320
71
12
64
16>
29
19
21
936673
20
24
19
62
62
61
241
203
19
21
28
47
67
66
325
311
35
23
15
223
130
269
-
488
86
82
IU6
252
284
3~
---
473
---
---
.
-
---
.
.
.
.
.,
,-
,
Table 6.61
Cmdative Winks During~r=
Y~rs Followin
Paflicular Two:Y+ Work Ex~rience
&hIte, Black, HIWWC)
for High-Schml DroPuLs (1 l-)
Table 6.62
Mulative Wmb Dting ~rw Yam Followin PanicularTwo-YmrWork Exprience
&it.,
for Mgh-Schml
Black, Hi~ic)
—
—
—
T“i”i”g
—
—
.
.
-,
Gmdmt=
(12)
Table 6.64
Cuulative
.*
W=ks During k
Ymn Followin Pafiicular Two-Ywr Work Ex~rienm
(#hlte, Black, HIspmIc)
for College Gdmtm
.*
(16+)
National
Longitudinal
Surveys (NLS)
Discussion Paper Series
w
m
hfichacl R. Pergmit
How tic Fticti
Government
Uses Dam from
NationA hngi[udinal
Surveys
tic
02
Noman
M. Bradbum
hhtin
R. FrmkeI
Reginald P. B*er
Michael R. Pcrgmit
A Comptision
of Compu~er-Assis[ed Personal
Intwviews (CMD witi Pa~r-and PcnciI In[cr@ngi[udinti
Sum.ey
vicws @mI) i“ the Nadond
of Youth
03
Saul SchwRohn Hulchens
Gwrge J&ubson
Dynamic Mdels of tie Joint Determination of
h~r
Supply and Fmily Smuc[ure
A. Colin Cameron
R. Mzk Griw
~omas
MaCurdy
~e effec~ of Unemployment COti~nmtiOn
on tie Unemployment of Youth
05
Rcnw S. Fti~r
Evaluating
hfobility
06
frank L. Molt
Paula B&er
Evaluation of tie 1989 Child-cam Supp!eit:;:
in tie Na:ional Longitudinti Survey of You[h
07
Au&ey Light
Wnueliti
Ureti
Gender Differences
Young Workers
08
Liw M. Lynch
~e Impact of Private Smtor Training on Race
and Gender Wage Differentials and tie Career
Patlems of Young Workers
09
Evmgelm
H. Elhkti
R=~nses
of Female hbor
m tie Demosqhic
Cycle
10
Anne Wll
June E. ONeill
A Study of Inle~ohon Change in Women’s
Work Pattern and W,ngs
11
&lwn tiikwiti
Jamb Alex Rfeman
Linda Waik
Women’s Employment
and Following Biti
12
13
..M
M. Faltis
Pelws
A. Lill~d
Jowph G, Almnji
Thomas A. Dunn
Com~titig
Work Experience,
md Wage Grow*
Family Back@ound
~wrics
of Worker
in tie Quii Behavior of
Supply md Fertility
During Pregnancy
Job Tenure, Job Separation,
and Labor Mtike[ Oulcomes
14
Gmrge J. Boqs
S[ephcn G. Bronws
Stephen J. Trejo “
Self-Selwtion and [ntcmal Migra[ioi
Unimd Sm[m
15
James J. HecMan
S{cphen V. Cameron
Pcmr Z. Schmhct
~c k~minm=
and Conscqucnccs
Swlor md Privalc Sw[or Training
[6
R. Mxk Grim
Thomas MaCudy
Pticipation
in bw-Wage
Young Mcn
in the
of Public
Lobor Mwkcls by
.
>