What Researchers Have Learned

from the National Longitudinal w

Surveys About Youth Unemployment

U.S. Depaflment of Labor

Lynn Matin, Secretary

Bureau of Labor Statiatica

August 1992.

Repofi a2a
Preface

Data from the National Longitudinal Sumeys of Labor

Market R~~rch (NLS) are “sd intensively by private

and government r~mrchers and the academic and busin=s communities: ~Is repofi iummarizm some of that

r=earch, with special reference to the mployment problems of minority and disadvantaged youth. The NLS are a

collection of five smeys. They ae Young Mm who were

14-24 yews old in 1966, Older Men who were 45-59 in

1966, Mature Women who were 30.44 in 1967, Young

Women who wme 14-24 in 196S, and Youth who were

14-21 in 1979 which include both sexes.

This report was written by David K. Howe, a summer

titem, and Harley J. Fmzis, an economist in the OffIce of

R=each and Evaluation, Bureau of Labor Skfisfim. Rita

Jain of the same office astited ti its prqaration.

Information in this rqoti will be made available to sensou impaired individuals upon requ=f. Voim phone

(202) 606-STAT; TDD”phone (202) 606-5897; ~b Mmsage Refemal phone 1-8W326-2577.

Mat~ial in this publication is in the pubfic domain and,

with appropriate credit, may be reproduced without

pemission.
Contents

Page

Tables:

1. Employmmt status by sa,. race, and Hispanic oritin,Spring 1979 . . . . . . . . . . . . . . . . . . 2

2. Employment status byage, Spring 1979 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

3. Selected characteristics of unemployed youth by race, Spring 1979 . . . . . . . . . . . . . . . . . . . . . . 3

4. Percent distribution of employment during the sumey yea by race,

weeks worked, andnumber of jobs held, 1971 and 1980 .,,,,.... . . . . . . . . . . . . . . . . . 4

5. Summa~ of research in distribution/turnover s~tion . . . . . . . . . . . . . . . . . . ... 5

v
Introduction

Unemployment rates of youth typi~lly gr=tly exceed

those of other workers. Therefore, it is interesting to examine the characteristic of unemployed youth, the length

and frequency of their spells of unemployment, and the

importance of the unemployment ciperimce on them,

both in the short mn and the long run.

This r~ofi summarizm some of the r=mrch that uses

the National Longitudinal Sumeys of hbor Market Experience @LS), with special reference to the employment

problems of minority ihd disadvantaged youth.’ The National Longitudinal Sumeys of bbor Market Experimce

are a collection of Lve surveys. They are.:Young Men who

were 14-24 in 1966, Older Men who were 45-59 in 1966,

Mature Women. who were 30-44 in 1967, Young Women

who were 14-24 in 1968, and Youth who were 14-21 h

1979, which includw both sex=.

Because of the large sampl= of youth and be=use NLS

respondents have been surveyed once evm y=r or two

over an extmded period, these data are well-suited to examining the Iong-mn consequences of youth labor market

experience=. In. panicular, the 1979 NLS Youth Cohoti

(NLSw contains tiee~y work histories detailing mch respondent’s labor force status, hours worked, and emPlOymmt at more than one job, pemitting” analyses that are

not possible with other data series. (Note The words

“sumey” md “qohort” are used interchangeably in thts

rqofi.)

All of the younger r~pondents were askd about their

work =periences, their family income and assets, their

parenk’ education, as well as various attitudinal and demographic charactefistim. The NLSY includ= week-byweek work hlstori= as well m gr=t detail on other topi=.

The surveys ovemmpled several groups of particular

interest. The original NLS sumeys during the 1960s oversampIed blacks. The NLSY ovmsampled blacks, Hispanics, and economi~lly disadvantaged wh]t=.z Few studies

using the NLS focus on”poor youth, although many examine blacks and whit= separately.

The first s-tion of this report gives an ovemiew of the

genmal characteristics of unemployed youths. The next

s~tion discusses iwue relating to the duration and incidence ofjobl=sness =ong youth. The third section surveys the literature on the consequmm of youth jobl=sn=s. Section four discusses the.longer tem consequence

of youth unemployment. In the fifth setion, job se=ch

strategi= of the young are discussed. Sction six provides a

brief conclusion.

—
Youth Unemployment: General

Characteristics -

In 1980, unemployment among 16-24 ye= olds was 13.9

perant, while those over 24 smtatied rates ofrrnly 5.1 percent. ln 1990, the comparable figures wme 11.1 percent

and 4.4 percent, r-p=tively.> The NLS allows resmrchem

to mamine the demo~aphic traits of youth experiencing

difficulties k the labor maket.

Many factom Emit youths’ abifity to work. Schooling, of

course, mkes full-time employment cliff]cult, at Ie=t outtidc of the summer month. Those who have left school

mn find the trmsition b&ttieen school and work rather

daunting. Some of the difficulties me outlind by Re=

(1986): Many youths have not developed an extensive network of job conticts, and some me unfamiliw with the

limits of acceptable behatior on the job. This faifing can

result in a youttis tirly dlsmissaLq Volun~ quits me

also higher.

“The higher rate of volunta~ quifi h= two quite

sepamte sonrt=. Fimt, youth are still trying to dscovw what they want to be when they grow up, and

in the procas tv many different job<, some of which

do not prove congenial... Second, youth living with

employed parents often work to e- money for a

specific purpose—to buy a mr or to take a tripand

oftm l=ve the hbor force for a time when this shotitem goal has been reached.”s

This weak attachment to the labor market letis economists to pay considerable attention to the qu~tion ofdlstinguishing different labor market situations. Thwe ticlude the following

The unemployed are persons who are not working but

are actively looking for work md are available for work.

Those out of the labor force are persons who are neither

working nor actively seaching for work. The nonejnployed

orjobless are those without ajob. Tti mtego~ is more inclusive and includa those out of the labor force. The latter

group includes discouraged worker$ thQsewho would like

employment but are no longer =tively seeking it6

The labor force participation rate equals the sum of the

~plOyed and the unemployed dividd by the relevant

population.

Stice attmpts by youth to find work we often s~mdic,

the distiriction between being “unemploy& and out of the

labor force is not as clwr as it is for mattire..adults.Thus,

much of the recent literature US= the more ticIusive

masure of nonemployment rather than unemployment.

Flinn and H&kman (1982), however, emphasize that

there are behaviorally mmtingful difference betwem

those out of the labor force and the unemployd, evm for

youth. Nevetih>less, th~ note that, “.. job sarch activity

,occum in both stata...tbe dflermce between the two

states is only a matter of deflw ....”7

The 1979 NMY (16-21 yar-old subs-pie) revds

much about the group’s labor market behatior. Table 1

provides data on the mploymmt status of various groups.

Blacks md H1spani= have lower labor force patiicipation

md higher unemployment than whites. Young women

dso =perience relatively low padicipation and high unemployment. Table 2 shows the trmtion into the winkingworld as youths age Not su~risingly, as young people

become older more of them find jobs and unemployment

mtes decreases

Table 1. Employment status by sex, ra=, and Hispanic origin

Spflng 1979

*

1

Female. . 67,6

Male .. . . . . ?4, 1

Black ..,.... 65.3..

Female . . . . 60.1

Male, ,. ... 71.0

Hispanic

o rigid . . . . . . 61.8

Female. 53,4

Male, ..,.. 70,7

White . . . . . . . 72,4

Female. 70.0

Male . . . . . . 74,9

Per=nt

unemployed

19,1

20.7

17.6

36,5

41.2

36.0

23.2

24,7

22.0

15.~

17.5

14.4

Employ menl[

population

ratio

57.3

53,6

61.1

40,2

35,4

45,4

47,5

40.2

55.1

60,9

57.7

64,1

Universe: ~viNans, age 16-21 on intemiew date. (N=24,580.000).

Source SantOs (i981 a).

Table 3, from Sates (1982), d~crib= the share of

16-to-21 -y=r-olds repofihg unemployment in 1979.’

tiost Wf of the unmployed are high school students;

80 percent live with their parents. Minoriti@ suffm &spro-

~tionately from unemployment-a black yOuth is mO=

than twice as Wely to be unmployti aS a w.~t+but,

stice the majority of the population is whit% l= tb hdf

of the ~employed are membem of a racial minority. Of

those whine family income is bown, 22 ~rmt of the unemployed are pwr, compared to 15 prcmt of the youth

population.

2
Table 2. Employment SW-by age, Spring 1979

fi” oermnt)

Age I I‘nemp’eyed I‘“’::F Employed

Total I l’412g 57

16-17 . . . . . . . . . . 44 I

17 I39

18-19 . . . . . . . . . . 61 13 26

20-22 . . . . . . . . . . 68 10 23

Source Calculated from Santos(1987aJ;tables2,1 and 2.2.

Mnomkts such 88 Freeman Md Wise (1982),

Feldstein and Ellwoti ( 1982), and Rees ( 198@ have found

that unemployment is ody a serious problem for the small

propotiion of youth who stay out of work for extended

periods of time. Hdf of %de teemge unemplo~ent, for

emmple, ocms among those who are out of work for over

6 months ~Is group consists of Iws thm 10print of the

youth labor force. NonempIoymenrspells tend to be longm

and va~ by mce Holzm (1986a) repofis the avemge

duration to be over 10 months for whites ad over 13

month for blacks.

In an effoti to shed light on the truly disadvantage,

Bores (1984) sepamtd out a subsmple of “hard-core unemployed,,. whom he defined as thow who (1) were out of’

school, (2) fived on their own or fivd with parents whose

income was below the povefiy level and (3) had bem unemployed for at lwt 10 weeks. By that definition (w.h]ch

Bores ackowledgm as necasarily arbitra~) approximately 1 in 11 of the unemployed youth were ;hard-core,,

in the spring of 1981. They tendd to be “...older, more

likely to kve patiicipati in trainin~ to be marnd, to

have children, to five in the central city of an SMSA, and to

live in an =ea of high unemploymmt than was tme of all

unemployed youth.,’ 10

Unemployment spells Too often or too long?

Differences h“ jobl~sness or nnemploymmt ratw ca”

be analyzd by distinguishing betwem two factors Duration—how long spells ofjobl~sn~s Iast—md incidenceti

how oftm thq occur. Researihen disagree on which

aspect is more impofiant. Their etiination of different

periods md use of diffeient masure (unemployment ~

OppOsed tO nOnemployment) makes comparison of thtir

results problematic.

Leighton and Mincer (1982) mphasim incidence.

Using the data from the 1966-71 NLS s-eys, they repofi

that hlgb job tumovm explains why unemployment mt~

among male youths me higher than those among mm 42 to

62 Y=KSold. Duration actually rduces the age dltTerential: Older ma tend to have longer unemployment spells.

This explanation applies to the &fference in uncmp]oy.

ment rate betwem adults and both studenti and nonstudents, whether white or black. Black youths were found

to have higher unemploymat rat= than white youths,

mostIy due to higher turnover, although longer duration

also plays a role.

Among whites, low= tenure at a giva job,smms to explain why younger whites have higher probabilities of unemployment than olda white accordkg to Leighton and

Mincer. When tenure is taken into xcount, age plays a less

kpofimt role. Young white mal~ who have been

~plOyed by.a firm for up to 5 yas have similar chances

of unemployment as older white males with the sme

tenure. Young blacks, however, retaio a high incidence of

unaployment (compared with older blacks) even after

tmure is t~en into account, espaially among those who

have spent less thm a y=r with their employer.

Table 3&e[etied Characterlstiw of unemployed youth by HIs

panic origin and race, Spring 1979

on percent)

Characteristic

Sex

Female

Male

Age

16-17

18.19

20.21

Enrollment status

High school

dropout

Mgh school

student

College !

student

Nonenrolled

tigh school

graduate

Household status

At home, with

parents

Away at college,

in dormito~

Has own

dwelkng

Povetiy Stal”s

Poor

Nonpoor

Not available

Total

53

4?

44

34

23

24

45

10

21

80

3

17

17

61

22

ilsDanic

47

53

46

29

25

36

44

10

11

81

1

18

34

50

17

Vtite

54

46

45

34

22

23. .

45

10

22

78

4

18

10

67

23

31ack

51

49

40

35

26

22

46

9

22.

86

2

12

33

46

21

Universe G“ilians aged 16-21 who were unemployed o“ i“ter”iew

dale (N = 3,300,000),

Source Santos (1962).

3
Table 4. Percent distrlb”tio” of employment during the suwey

year by mce, week%worked, and number of jobs held, 1971ati

.-..

,...

Total number

of weeksljobs

Total employed

(thousands)

Total (percent)

Weeks

1-38

39+

Jobs

1

2+

Weeks/jobs

1-38 1

2+

39+ 1

2+

1971

287

00.0

3i.2

68.8

47.4

52.6

3.8

27.4

43,6

~

Wtite

1,503.

100,0

f8.1

81.9

61.4

38,6

5.8

12.2

55.6

~

1980

White

296

00.0

40.8

59.2

60.5

>9.5

20.9

20.0

39,6

~

Black

1,955

100.0

22,6

77.4

52.,8

47,2

8,9

13,7

43.9.

33.5

Universe;. Males. ages 18-21 as of the beginning Of the surveY Year,

who were not enrolled in school, not in the mititaw, and who were

employed al least i week during the suwey year.

Source Pollard (1984).

Comparing the older NLS cohorts with the Young Men

and Young Women,s coho~, Frmk md Freeman (1978)

reprt that the higher unemployment of the younger

cohort3 redts from gr=ter job turnover. Within the

younger cohorts, however, the authors emphasize the importance of duration in explaining unemployment.

tirfier NLS sumeys were compared with the 1979

NLSY by Pollard (1984). Both white and black youths experienced rising unemployment and joblesm=s between.

the two surveys. For whit=, Pollard concludes that increass in joblwsness r-ulted from=rising turnover. Black

joblessnas, on the other hand, resulted from longer nonemployment spell% if anything, turnover among young

blacks decfined over the d~ade. (See table 4).

Recent studia using NLSY data have tended to focm

on duration. A group of NBER studies in 1986 compared

the NLSY data with a specially commissioned suryey of

black inner-city youth—what we will mll the NBER sample.J1In one of the studla, Ballen and Freeman (1986) selected a subset that was not k school; they found intensive

evidence of lengthy nonemployment spells. Twenty percent of their subsmple had been without work for a yew

or longe~ those never employed accanted for over half of

the sample’s weks of total nonemployment, Duration is

thus the dominant factor, both in comparisons between

NBER blacks and NLSY whh= and between NLSY

blacks and whites. h imphmtion of these r=tits i8 that a

va~ing propensity to lose jobs do= not drive.the blackwhite aployment differatial so much...as the difflc~ty

young blacks have in findktg an actiptible job in the fi=t

place. 12

Table 5 summtiz= the literature suweyd in this s&-

tion. It is mpting to conclude that Vhde incidence

seemed to produce most of the resdts for the origtial Whofis of young men and young women, duration becae

the key fact,or by the time the 1979 NLSY was conductd.

Such a conclusion is not completely wammtd, however,

stice =rtier studi- usd unemployment dza from the

NLS as a measure while more recent studia tmd to use

nonemploymmt dat6 from the NEY %a masure.

Consequences of youth unemployment

~arching and ssarring

For youth in general, there are a variety of ways in

which emly jobl=sn~.s ~n Med their future prosp-ts in

the labor ~arke~,13 Three ~conomic th~~fi~, ~ch bor.

rowed from the broader unemployment fitemture, identify

these eff=ts. Thehuman capital mode[sugg=ts that the

knowledg% skills, and discipline msociatd with working

should enhance prospects for both hlgber wage and lower

unemployment. Ushg the Young Men’s Cohort, k-

(1976) =timated that approximately one-third of a young

worker’s total compensation was delivered in the fom of

human capital. This reason alone might make =rly jo~

l&n6s up=ially unfortunate, as =rly work experima is

thought to entail intensive on-the-job training. If oppotiunities to acquire mly human mpitil are fleeting, theeff=ti of youth unemployment would be =p&ially

persistent.

Dual labor market theorists beheve that unemployment

“scars” its victims, leading fimt to dlscouragemegt and ultimately to decfining work habits and a sucmsion of job

with little payorupwwd mobility. Thus, mlyentv into

the primav swtor (the one with d=tiable jobs) is critical if

one is to stay out of the cycle of d=d-end joh =sociated

with theseconda~ swtor. Adherents ofthis theory note

that potential employem make extensive use of job historiw when hiring applicants. Those who have experience

substantial unemployment emly in their careem risk being

tagged as poor workem.

h contiast, search theov emphasiz= the beneficial mpects of youth unemploymmt. In this tiew, youth unmplowent allows those new to the labor market to %ther

valuable itiormation shut thtijob prospects. Seen irithk

way, job search -n be as much as m “inv-tmenl” as ontbe-job training, by allowing wo!ke~ to switch into more

lucrative positions at other firms.

Stevenson (1978a, b, c), Raefin (19S0, 1981), Becker and

Hills (19S0, 1983), Ellwood(19S2), Grcoran (1982), HLlis

(1989, Lynch (1986) and Ballen md Frman (1980 all

address the smrnng hypoth~is. With the exception of

Hills (19 S5), none of the empirical work in three stud<=

attempts to explicitly dlstiriguish between the human mpital and dual labor market/s*g hypoth==. Inst=d,

they simply a~ whethw youth unemployment d~r=s=

wage or future employment prmpats and, if not, whether

youth unemploymat in fact advmca labor market op4

I
pofluniti=. ~efin (1980) uses a subsarnple focusing mreclusivelyon dimdvantagd youtk Bdlen md Freemn

study black inner-city youth; the other authors distinguish

merely between black and white subgroups. All of thae

studies focus on indlviduds who are out of school.

These studl= imply that those individuals with =rly labor market dtT1culti= tend to have gr=ter unemployment

later in their working fiv~. This finding does not nec=szily imply a musal relationship, however. It is @ssible

(even fikely) that some third factor or set of factors (e.g.,

education or aptitude) muses both the early ahd later

problems. In panicular, workem who are less productive

may have trouble in the labor market all.throughout thti[

lives, but that would not necwady imply a scarring effeck Both arly and later aployem may simply recognize

less productive workers whm hiring and firing. If this is

the -se, mrly unemployment would be correhted with

later unemployment, but it would not follow that the former ~used the latter.14

Both cross=sectional and longitudinal data sets =n address ttis issue by controlling for such characteristics as

yam of education and pychologiml indicators that are

thought to be comelated with worker quahty. But longitudinal data sets in addition have the pote”tiaI to control for

unobse~ed cbacteristics, since tiey track tie sme tidividuds over tie.

Studies using rhe NLS Young Men k and Young Women k

cohorts. Stevenson ( 1978b) repotis that out-of-school

whites who were employed during the sumey week in 1966

@md approximately $2W more per yer a d-de later

than out-of-school whites ,who were unaployed at the

time. For out-of-school black maks, the improvement

amountd to $7W a “YW. For out-of-school females, the

differences about $9W per y~r.15 Greter differentials

●

Table 5. SUrnmaV of research In duration ftirnover secfio”

Author

,

Leighton

and Mincer

(1982)

.

Frank and

Freeman

(1978)

Pollard

(1984)

Bane” and

Freeman

(1986)

Measure :

(nonemploymentl

unemployment

Unemployment

Unemployment

Pdncipally

nonemployment

Nonemployment

Database

NLS

NLS

NLS

NLSY

exist for males who were originally defind as “out of the

labor force, “ i.e., out of school, without a job, and not

actively sexctig for aployment.

Usfig a different method, Wefin (1981) foun{no relationship between youth untiployment aid either future

wage rat= or occupational smtus, although unemployment did lead to dwlines in job sa~fwtion, 16Using a subsample of disadvantage youth, Raelin (1980) reported

that a variable summarizing data on..occupati0nal StatUS,

wag- and hours of the respondent’s fimtjob si~ificantly

affected future wag= and occupational status.’7 Unfortunately, the latter study made. no attempt to control fol

other factors.

In contrast to the above r=ults, Becker and Hills (1980,

1983) found support for the semch hypothesis. Thoseexperiencing nabnemploymeqt but who changd jobs more

frequently =m@ higher wag& y“ars liter. Longer spells

of unemployment, howevm, did appez to depress wag=.

Thee resdts are broadly consistent with Raefin’s finding

that part-time status (which allows both sarch and the acquisition oFjob sk14s) is assqcisted with higher future pay

rates and occupational stitus.

Racial br=kdowns of data presentd by Becker and

Hills (1983) are striking. Blacks who experienced no unemployment as twnagas and who changd jobs 1-s than

two time hti even lower wages than blacks who experienced unemployment spells of 26 weeks or longer. Blacks

who remained employed but changed jobs two tire= or

more fared worse than” those who had unemployment

spells of 5 weeks or fewer, indl~ting that job sarch associated with unemployment may be more beneficial than

s=rch that occurs while employed. Whhes also appeared

to benefit from job search, although not as dramatically as

blacks. It is also notable that whites who were unemployed

for over 25 weeks were ptid more than blacks with any

Phenomenon to be explained

Wtite age differential

Black age differential

Racial differential

Age differential

Variation among youth

D<fferentia!: NBER inner cily

Blacks vs. NLSY whites

NLSY racial differential:

Explanation

(incidence

or duration).

incidence

incidence

incidence

incidence

dura~on

incidence

duration

duration

5
levd ofjob mobtity. Btiat= were based on recessions

which mntroUd for du=tion, experience and various

dmogmphic vtiable. 18

Two ~icl= by BIau md Ktin (198 la, 198lb) point towads a poxible rmondation of the semching and scar-

*g MewPints. One afiicle a“ddr~s~ the consequences of

quits while the othm studl= layoffs. This resemch sugg=ts

that voluntw quits Iead to improvements h wmings for

all race ad sex groups. hyoffs lad to lower wage among

reds, but not for femties.

EUWOM(1982) noted that an unobsemed facmr or set of

factom, such m three relating to the worker’s mw ~ility,

could act tidependently on both the =rlier md bter job

~tienc~ fiere maybe qualities of the worker that are

ob%mable to the potential mployer but not reflected in a

household swey. Mtemately, =rly unemployment could

tidlwte w~ attachment to the labor force, which in turn

might mmehte with lower worker productivity. 19

Mw@ exploited the fact that the NLS, like all longitudinal dab sets, tmcks the same individuals over time.

Cros-=tional studies, in contrast, select new responden~ eve~ sumey. In Longitudinal dah sets, by examining

how btir force outcomes change for each individual after

a SWU of unaploymmt, one can emmine the effect of

events such s spells of employment without the confonndmg itiuence of mob=mtile traits such as w=k attachment to the labor forw. Consequently, Ellwood could

use the NLS to control for respondents’ othemiie unob-

*mable trtits to the extent that the traits stayed constant

over time.’0

hatbpting to control for such unobsemable chzacteristics, Ellwood concludd that early unaployment

huti future job prospects only mildly, ad only for a shoti

time. “Even a 6“month spell out of work tinds to generate

ody an addhional 3 to 4 week out of work 1 YW Iater.”z1

In contrmt, ‘~ly work ex~fience hm a tiable impact

on wages. ~ntrblling for individud effects, experience in

the wnd, third, or foutih y-r out of school tends to be

=stiatti with wage increm~ of kt ween 10 and 20 pr-

=nt a yar.,,z2 (Itti= added.)

Usrng a similar method, Corcorm ( 1982) analyzed the

con~uence of unemployment mong young females. She

found a stronger relationship between present and future

~PIOyment than EIIwood did for men, even after control.

hng for unobsewable individual chamcteristics, while the

wage &Sts of ~rly nonemployment for women are IW

tha they are for men but still appretiablc Unfotiunately,

her analysis doa not take into acmunt marriage or childbifih, =h of which muld plausibly r=ult in a volunta~

etit from the bbor force (and which obviously changes

ova time). Futih~or% the shofin~s of the panel prohibitd ~rco~ from ~timating how long these “scars,, last.

Studies Wing the NUY The N2SY obbi”d more dettil

on its rapndents, work experimc~ than earher sumeys.

In addition, due to the economic downturn during the exly 198Vs, the NLSY dIows us to evaluate the eff=ts of unemployment in a w=ker labor market.

h gened, recent malys= uskg the NLSY have tended

to assmiate long spells of arly nonaployment tith subsequent l~or market problems. HNs ( 1985) prducd results that app= at odds ~th his prior work with Becker.

While @rlier afiicl= had linked Io@er peritis of ititifl

unemploy mat with lower eventual wage among white

maim, the later papm revded the opposite (at lat for unemployment spells of 23 week or 1-s). Su~risingly, in

contrast to the implications of search theoq, job chang=

did not I&d to signifitintly higher .mings among the un-

~ployed. The effect of longer perioti of initial unaPloYment for black male and all females wme negative but insignificant.

The difference may be due ti the specification of the

model in H]lls’ 1985 paper (though waker labor markets

during the erly 198Vs may have erodd the advantag= of

sarch). In addition to a m=me of reemployment dufing

197.9, Hills also incIuded a variable indicating the we~

worked since the respondent turned 18. Thus the unem.

ployment m=sure used by HilI pr~umabiy refl%ts “sarring” rather than lmt human capital. This latt= m=sure

w= h]ghly significmt. One plausible ht~retation of

Hills,s re”lts is that although early jobl=m=s do= have

long-lasting effects, a given spell of unemployment, if it is

r=sonably shofi, do= not prove epecia~y crippling.

Thus, the 1985 paper is consistent with human mpital

models, which strss the tiportance of =lY work m~rience, although the impact of Iost experience is 16s severe

than some might imagine. The criti~ factor app-s to k

lost working expefimce ooblmm~s or nonemployment]

s opposed to the fmstration of s=rchlng for new work

(unmploymmt).23 On the other hand, Hills, evidence k

also consistent with the interpretation that long peritis of

nonemployment can “tag~ one as a low quality worker. .

In their study of nonemployment duration” and labor

market turnover, Ballen and Fr=man (1986) compared

the NBER wple of inner-city black with data from the

NLSY74 Nter controlling for unobsemed chmacttistiw,

they found that longer spefls of nonaployment lower&

marginally the inner city bI=ks’ probability of mploymmt, but did not app=r to affect either blacks or whit= in

.

the NMY. Inter~tingly, long periods of mployment signifimtly reduced NLSY blac~ md whit@, probability

of nonemployment, but did not ‘improve the NBER

.

group’s chances. Wd evidence suppo~ing incidence dependenc+lage numbem of spe~s of nonmployment

l=ding to subsequent nonemployment—w~ preented

for the NBER sample. Data from the NLSY, how,ever, did

not support the existince of incidence dependenm.

Llmititions Ofthe NBER data set led BalIen md Freeman to pumue more eridence. They intemiewed employers in a primarily black dktrict of one city to win fufihm

6
insight into the caus~ of labor mket problas of tiercity youth. While 7.8percat of those em-ployemwho inked

about theti hires,”work record considerd it “a strike

against the youth if he h= a Msual work histoW~ only 28

per-t considmed it bad “for youths to have been “out.of

work for a long pefiod of time before applying for ajob.,,zs

The authors inte~reted this as evidence of “incidence dependence,’ among innm-city blacks.

In order to detemine why employment duration did not

appea to help inner-city blacks asmuch asit did others, the

authors exmined jobs held by this group. They found that

fewer than 20 percent of these jobs requird a high school

degree or higher, while just over 15 percmt were whh&collar. The authors sumised that they were “d=d-end jobs,”

i.e, of the type that protided fittle humm capital.

Finally, BaOen and Frmman used the NLSY data set to

study the effects of nonemployment on wa8es. Among

blacka, the number of spells mattered more than spell duration. Resdts for whites revealed a positive relationship

between the number of spells and wages, after controlling

for unobsaved characttistics.

Aside from the long-t- qu~tion of “warringfl there

is the short-tern quetion of ‘Zdumtion dependence’,—whethw the Ionger a pmon is unemployed, the

more fikely he or she is to remtin unemployed. Lynch

(198@ used the NLSY to focus on nonemployment, which

she defined as being neither employd, in school, or in the

military. After controlling for various demographic facton, she found that longer spells of nonmployment substantially reduced the chancw of findlrig work during the

next period. Lynch writ= Where-employment probability for either a ,typical’ male or female who has not been

work]ng for 1 week is slightly gr=ter thm 30 percmt. If

they have not been working for 8 week this drops to 8 percent and if they have not bm employed for 52 weeks thek

re-employment probability is only 2 peycent.’,26Results for

a subsample of high school dropouts were much the sme

While tbe papem discussed here differ in many details,

the overall picture is r=sofibly cleu. h the shofi tern,

nonmployment may l-d to futher nonemploymmt,

wheras in the long run, emly unemployment has little dfect on future employment for male although posibly

more of an effect f~r.females. Long periods of =rly unemployment have a negative effect on w~ges,’”howevm. This

effwt appars to be stronger for bIacks ad feti= than

for white mala. Counteract~rig the negative effmt or unemploymmt on wages is the positive effect ofjob s-rch—

the job mobility sometimes associated with periods of unemployment.

Search strategies

The qu=tion of the methods and strategy that youth use

in job search is interesting both theoretically—as a way of

explaining unemployment dumtion—.and from a policy

perspective tince it may be possible to ttich youth to

semch mme ticiently. me Natioml Longitudlnd Suiveys mntain numerous quetions on various faceh of job

SWCL The 1981 NLSY investigated the methods youths

med whm they Iookd for aplwment.

Wie1g6sz and Ca~ter ( 1987) r~ofied that individuals utig multiple job s=rch methods spen! less time lo.Oking for ajob. Infomal methds, spmifidly asking friends

or relatives md d]rect appfimtion b the employ-, were

jMged more effective thm fomal methods such = apply

ing through a State employment agmcy .27Among unaployed workers who wme not new entrmts to the labor

market, checking tith the local union w= pafiicularly effective. Those who were alrady employd, however, may

have found checking tith a union counter-prductive due

to seniority roles. No single method affected subsquent

job satisfaction stistmtiaUy?a

Holzer (1987a) disaggre~td the monthly probability

of becoming employed into probabihties that ~e conditional on v~ious =ch metho~. For both whit= and

blacks, infomal methods of job search wme found to be

the most frequently used and most productive in terns of

generating job offers md acceptanc=.’q

Holzer also disaggregate the difference between” the

probability of a black md white baming mployed into

different= betwem. the use of different s=ch methods.

All methods of swch gave whites a geater chmce of receiving a job offer, but difimenca k dkect application to

the employer explained a patiicularly Imge share of the racial emplopent differential. In fact, the two infomd

semch methods together =plaind 87-90 percent of the total black-white dlffermtial. “Fufihemore, vifiually au of

this reflwts Wereqm h the abihty of th=e methods to

produce job offe=, as oppos~ to differmc- in methods

used or job acceptance rates.”

One elaent of a worker’s job smrch strategy that economists have ptid sp=ial attention to is the reservation

wage A reservation wage is the Iow=t wage that a worker

will accqt at a given point in time. The NLSY m=sures

this conc~t with two cate~ri~ of vatiabla. The fimt

notes whether a r=pondmt would acqt a s~cifid job

(for e=mple, washing dishes) at a patiicular wage level

($2.50, $3.50, and $5.00). The second meas~= reemation wages by asking what minimum wage the youth

would accept in a new job. We refer to this secqnd m=sue

as asking wag~.qo

Bores, et al. (1981) and Bores (1982) analyzd the determinants of both me%ures of resmation wages. As one

might expeti, reservation wag- rise with age and are higher among employed workem. Females have lower asking

wages than mal~ those out of school have higher a&lng

-ges than students, probably beause many of the latter

mticipate working in a tempora~ summer job.3L

Youths from For famifies were more fikely to accept

jobs at S2.50 in 1979 than youths from wwlthler fmiliw.

Each job categmy w= sufficiently attractive at $2.5&a

7
rate of pay that was 86 percent of the minimum wage it the

time of the intemiew—to elicit at least a 20 percent accep.

tance rate from the smple of all youths. >1

Wcial differences in asking waga were small. Howev.

er, black youth were more likely to exprms a willingnms to

work at the amay of hypothetical jobs than whitw, even

after cent rolling for various demographic variabl~. 33

But, while black resemtion wages ~e comparable or

lower than white resewation wages, the market wag= for

blacks are quite a bit worse. Thus, while unemployed

whites will ultimately receive wag= ~eater than thti r~-

evation wags, blacksapper to have to scale down their

wage exp=tations. Two empirical results follow: Blacks

have long nonemployment and unemployment spells and

the ~tra serch time nairows the black-white wage differential to a de~ee. Holzer summarizes th’e situation as

follows

Young blacks seek wagm comparable to those sought by

young whites but which are lessavailable to them. B-use

ofthls, their durations of unemployment rise substantially.

As th=e lengthy durations progress, many young blach

either lower their reswation wags or accept other positions which they consider to be tempora~. Othem gain no

employment at all. Thus, the unemployment durations of

young blacks will reflect their high resemation wages

while their received wig= will do so to a leser extent.

Although tlot all elements of this scentio have been cl=rIy documented, they are consistent with the evidence that

is thus far available.jg

Intermtingly, results by Borus, et al. (19S 1) suggest that

black employment probabilities are 1=s sensitive to drops

in resemation wages than are white ernplo~ent probabilities. A drop in a white male studegts’ remation wage

from $0.60 above hIs fimputed) market wage to hls market

wage can adjust downwards hls probability of unemployment from 96 percmt to 10 percent. Comparable black

mde students experience a 17-pementage point drop in

their unemployment probabihty from 98 “percent to 81

percmt. Among non-students, the phenomeno~ is I=s

dramatic.

To summarize, NLS rmearch h= mown that blacks and

whit- appur to sarch for jobs in stillar ways, both with

regard to the search methods used and with re~rds to r~.

emation wag= for accepting a job offer. However, whit=

have more succes in generating offers.

Conclusion

The National Longitudinal Surveys have provm to be

an invaluable r=wch tool for the study of the labor market experiences of youth. The sumeys explore many

aspwts of labor market behavior, includlng -ings, and

provide unusually detailed information on unemployment

and nonemployment, search strategies, and raemation

~ag-. The detil of the surveys md the large sample siz=

would by themselve insure the value of the NLS in understmding the labor market. In addition, the Longitudinal

nature of the survey-tracking the sme sample membcn

over several yam—allows rs=rchus to answer qumtions about the long-tern effects of labor market experienc-, and additionally allows resachers to control for

traits not directly obsemable that might bias the r=ults of

cross-section studies. This review has attmpted to show

the contribution that r=earch using the NLS has made in

~derstanding the problem of youth unemploymmt.

Endnotes

1 [n fomaci.n o. NLSre$earch ispr.vided in Bzelby, elal. (1977 and

1979), bigh (1982), a“d Day”on[ a.d A”drka.i (1983). TWO CO1[K.

[i,>nsof NUabstrace are The’\,atio”ol Lo,r8irudinal Sumeysof Labor

,WurkerE.Yper?c,rcr:A!z A””orortd Bibliogwphy and A7LSBib/iogmphy

Updotc, 1990.Bo<”s(1982a) surveys other 10ngittiinal da[a sets.

RCeS( i986) presents a“ excellent surve>,0“ youth jobl=sn=s.

‘ Using da!, .“ family income, family size Ixation and a rnrd/”rba.

variable, ya”ths &ho K,,cdi“ fami~i~ that were below the poverty level i“

Ja””aq 1978we,e $eI%ted aspar[of the..econamhtiy dkadva" taged

r,<,,,-Hispanic, “o”.blac~ove-pie, R~nl[$ for.versamplcd rmonde”ts.= \.eigh[ed when a rcpresentarive sample.f the Iargerpopulation

is “ceded. See Fra”kel, McWilfiams a“d Spencer (1983) s“d Fcankel

(1981).

3 ,V”,zlhly Labor Rcvie*,, Ja..aq, 1983and March, 1991. Dara from

Current Pc>pubation S“rvq (cPS).NLS figures aftm van from CPS MtimaIw. Fceeman and MedoN(19S2b~ noIel hat different-bctweintie

two surveys may arise from the facf that wh!le [he CPS interview h-ti

of ha”scholds, #he NU inten,ie%s its youth rspo”de”ls directly.

“Rw(1986) pp. 617-618.

5Rws ( 1986) pp. 617. It k ako noted [hat the mi”im”m wage may &s.

<riminateagai”st youth by dryi”g”p thes”pply oflow wage, lowskiU

jobs. Rws, hox.tver, dow”plays tKtsar8”ment.

‘Some of[heamb(g.iti- implicit inthenotion ofinvol””taq ““em-

“Iovment and. bv exlension, di$coumsd workers are diwused i“ Sum.

me;s (1986).

7Flin. .nd Iieckma. (1982), pp. 19

‘k conumt, the CPS had xpofied that only about 15Fcmtof141S

y.ar-.ld$ $veFemPl0Yed. S?.!0s(19S 1). MOsl,t.d,es .ftiela~rfor.c

ovmlmk 14.and 15 year..olds. Michael md T.ma (1984) arg.. that.

..,.students age 14a.d 15.acq”i* substantial aploymmt a“d that exvricnce is vastly tiffemnt for black a“d wh,teyo”ths.,,

9The NLSYpr”d”ced a””nemplaymmt rate of 19.1 Frcmt among

16-21 y=r-ol&. For comparison, ~S tits indicate a 16.1.F=enl unemploymentrate among 16-19 year old, in 1979. Handhk of tibrStnt&

de., BLSB”lletin 2217, June 1985.

‘0 BorU(1984) pp. 30,

II ~o,zer(19s6a) notes thal <<TheNBERsufleY w~cOnd. cl&&-

Iwem November 1979 md May 1980 among 2,~ yo””gbl.ck men.

.g& 16 through X, who wem 1ivin8in che i..er-cit i= of Boston, Chica.

go,. a“d PfiIadelphia. The intemims were limited to i“habtta”[s of city

block with..atl~t 70 percent black reide”ls and 30 percc”t familie hav.

i“g incomes below the pov~y K“.. The q“~tions i“ the S“RCY fm..d

on che r=po”dmts, daily ac[iviliw...; thtir f-ily backgro””d% IhGrjob

sach behavior md experience, including r=emation wags..; their =trespective work tistoti sforthcpreedi.g 12mo”t~... The”ti”lnS

of the NBER sumey masuppleme”t [o the NLS, which pmvid- lhc bulk

of the black-white cmparimn% fiainits focus o”nofihemi..mtils

blacks...; a”d thedir%t co.mparability ofmmyof theq.mtionsi” the

NBER S“FVWto those k the NM (after wtich some of the fomm were

,!-

‘:*~a:/;ri mdFr~man.(1986) pp. 85.

13 See Daymo”t ad titisani (I 983) ad Lei& (1982).

8
Small mmple size phgued many of th=e st”di-. For .-PIc EUwod ( 1982) andB=kerand Hills, (1980, 1983).$mple $US ragd fmm

91 to 217. See B_ow (1982), pp. 289. Mili@V ind”ctiomdutis the fietmm W= wone”ed attrition ram of the 1966 cobofi,

2’ Ellwti> PP. 383.

22Ibid.

23 To {f~ti”g~ betwm b“tie~ qcle a“d model s~ificatio. tif-ti, m exmt r~Eation of Bwker a“d Hills, (1983) paper, usin~ NLSY

&b, mi8ht prove interesting.

24 Note ~hat ..ptcntjally ,~ti.”s” m-remmt problms ~d $mall

=mple sizes phped this pan of Bane” and Fr-”>s study. Ball.. and

FEmm, pp. 89.

2s Ballm and F,-.”, PP. 95-96.

% Lynch (1986), pp. 16-17.

17Ot~erfomal methods incl.de“Si”gprivateemploymenta8m.i=,

sch.ol p[acme”toff,ws,hborunionhin”ghallsa“d neqapm advwtiseme”ts,Holzer(1986.)producedsimila %tits. 28,o~ ,atj%faccionis primmlyaff~tedby vocasion,e~i~g$. ad

g?qob ~cepta”ce, .,. ~~,”red .$ thepeme”tofjob offersaccepted.

= Freman(1978)discussesthe“seof s“~-tive vtiabl~ i“ economic

2..1”.;.

:“TfB:m$ (1981.).

3’ Bo,”$1482b).

33Bom$ ( 19s I~ Ig82b) Exqtions to this ge”emlization w-e that

bhck$ te”dd to h. more reluctant to “Clea” “p ntighborhoti and

“Work away from home al a national forat or par~ than whites.

3’ Holzer (1986b), pp. 173.

References

Ah, Ad V. ad Ma”g”m, Gtih L. 1978, The Li”zen.”~ Cfiis of

Yo.rh Unemplqmen(, Wamzm, MI: W.E, Upjohn I.stit”te

for Employmmt %e~h,

hdtiti, Paul J. 1978. “The Estabhshmt of Stable and Sncc-sful

bploymmt -m me Role of Work Attit”dm a“d Labor

:y~ Knowltize.- ~ U.S. Depaflme”t of bbor ( 1982,), pp.

Bdle”, Joh md Fmma”, &chard B. 1986. “Tra”titio”s betw~” EmPlOymml a“d No”emplomat? 1“ F,&ma” and Holzer (1986.),

pp. 75- I 12.

Bmow~8&3fiWS 1982. “Comrnentfl 1“ ~-” a“d Wise (198ti), pp.

&ker, Brian E. a“d Hills, Stephen M. 1980. “Tee”age Unemployment:

%me Evidence of the Lo”g-m. Effects on WaZm.X,Jour”ol ofH.-

mon Rmo”mes 15(3} 35+372

kker,, Brian E. and Hills, Stephen M. 1983..-The Lo”g-m” Effects of.

Job Chmg~ a“d Unmployme”tamensMaleTemgers.,,Jour.

“cl of H“mo” Re,ourccs 18(2) 197-212.

Bielby, Wilfiam T.; Hawley, C.B.; and Btlls, David, 1979 ,’Re%uch USof the Na!io”al bngitudiml SUmWs.,, R & D Monograph 62

uS. Depanmcnr of Lb,.

B!an, Fra”cine D. a“d K&n, bwrme M. 198la. ‘.CSUS ad Cons..

que.c= of ~Yoffs” Economic Inquiw. 19(2):270-296.

Bla”, Fra”ci”c D. ad Kahn, bwre”ce M. 1981b. ..Race a“d Sex Differ.

a= in Qtits by Young Worker,.,, Indusz,iar ond Labor Rela.

[i.”, Review.3~4)563 .577.

BOVS Michael E 1980& ‘,K”owltige of the World of Work? In Bows,

et d (1980), pp 340-343. .

Bores, Michael E, 1981.. “Introd”ctia”.,, In Bores (1981 b), pp 1-17,

BOW. Michaei E,, ed. 198lb. Pathwaysto the Future:A repor! on the Notionar Lon8ir.dinar SUm,y of Youth Lob., Mo,kel Experience in

1979,Columbus, OW @nter for Human Resource R~mrch, The

Ohio State University.

Bor”s, Michael E 1982a. ‘<A. I“ve.toq of tingitudinal Data Sets of Interest to Economists? Review of fibric Dora uxe.

10(1-2):113 .126.

Bows, Michael E. 1982b. ‘.Wilti”fl~ to Work AmongYouth.,,Joura./

of Human Resotirces, 17(4}58 1-593.

Bor”s, Michael E., ed. 1983. Tomormw’s Workers. Laingt on, MA Lexin~ton Book.

&r”$, Mrchael E. 1984.. ‘<ADe$ctiptio” of Employed a“d Unemployed

Youth in 1981> 1“ Bor”$ (1984 b), pp 13.55.

Bor”s, Michael E,, ed. 1984b, Yo.zh and {heLobor~arket:Anaryss fmm

the Natio”ul Lon~itudi”ar S“mey, Kalamazoo, Ml: W.E. Upiohn

lnsti”le for Employment Research.

Bor.s, Michael E,; Crowley, Joan E; R“mberEer, Russell W.; S..10s, Richard; and Shapiro, Datid, 1980. “RSmrch on Youth Employment and Employabi fity D.evelopmmt: Fi”drn@ of the Natio”al

Longit”di”al S“WV of Young Americans, 1979? Youth K“nwl.

&ge De.elOPmmt R~oti 2.7. Washington U.S. G..om,nt

Printing Off,ce. PB80-203217.

Bor”s, MichaelE.; Kim, Choong$~o, and Sates, Richard. 19S1. “Job

Se=ch Activides of Youth.,> 1. Bor”s (198 Ib), pp 223-276.

Corcomn, Maw. 1982. ‘<The Employment a“d Wage Co”seq”mces of

Tec”aEe Womenss Nonernployme”t.,, 1“ Freernin and Wise

(1982a), pp 391-419.

9
Damont, Thom~ N. a“d &drismi, Paul J. 1983. “The R=mrch ff=

of the National Longitudiml S.WW: .“ U@ate.,, Re.iew of &b.

Ii. Data fJ$e.11(3):203-310.

Ellwoad, Darid T. 1982. ‘.Ttemse Unaplo~mk P-mat Scam or

Tmporav Blemitie?” k Frwma” and Wise (1982.), pp

349-305, . .

FeI&t&”, Main and E1lwo&, Darid T. 1982. ‘,Te”#ge U“employ -

~,~:, What is tie Probla? In Freeman md Wise (1982a), pp

Fli”n, Christopher J. ud Heck.”, lam= J, 1982 ‘~tie Unemplaymmt

a“d O“t of the Labor For= &&vi.&y Di$ti”ct kbar Force

StatmV Jou,”al of Labor Economics 1(1}28 .42,

Fmnk, Robefl H. and Fr=man Kchud T. 1978.‘~e D,strib”tion of the

Unemploymmt Burden Do tie ht Hired Luve Fint?” Review

of Ecmomiwand S,ottiti& W3)380.39 1.

Frankel, Martin. 1981. “Sampli”s, Wdghti, a“d Sapling Emors: b

BOmS (1981b), PP. 19-58.

Fra”kel, Martin, McW%ams, Harold A. and Spencer, Bruce D. 1983.

“Natio”al Longit”&”al S“mey of Labor Force Behavior, Youth

S.wey (NM), T%hnical Sampling Rtpofl.,, Chicago, IL: Nation.

al Opinion R=czch Cmtm, Uni.ctity of ~cago.

Freeman, Richard B. 1978, ‘.Job Satisfwtio” z a“ Economic Vsriable7

A,nerican Economic Review. 68(2} 135.140

Fr_a”, Richzd B. md Holztr, Ham J., eds. 1986a. The Black Youth

E,nplaymenI Crisis. Chicago Univwsity of Chicago Prms, 1986.

Fr=man, Ricbmd B. and Holzer, Harm J., ~, 1986b. ‘The Bbck Youth

Employment Critis, Summary of Fbdin~? In F,-.” a“d HolZ.F ( 1986.), PP 3-20.

Fremm, Richard B. ad Medofl, Jme L. 1982. “Why Do,, the Rate of

Youth bboc Form Activity Differ Acrms S“me~W In.Fre=afi

and Wke (1982a), pp 75-114.

Freeman, Richard B. md Wis% David A., eds 1982. The Youth tibor

Market Problem: In Nature, Came. and Comeqze”em. ChicaEo

U“iversiry of Chicago Pres.

Frema”. Rich=d B. and Wke, David A., ~. 1982b. ‘.The Youth Labor

Markti Problem lti Nature, Ca”s~, md ConSq”e”ces.,, 1.

Freemn a“d Wise (19828), pp 1-16,

Hills, S.tephe” M. 1985. .$The~ects of High Uriemployrne”t i“ the Late

197LYsa“ [he WaEm of Young Me” and Women; Wortig PaPer.

Columbus, OH: Ce”rer for H.ma” Rsoume Resmrti, The Ohio

Stale U“ivetily.

Holzer, Harv J. 1986& ‘,Thc Blink Y.”& No”employmenk Duration

a“d Job Sarch.>, 1“ Fr-a” a“d Hal=. (1986a), pp 23.70.

Holzw, Harry J.. 1986b. “RS_atim Wa8m and theirLabor Market Effects for Black and Wbi[e Male Youth.” Journal of Human ReSOU,C,S,21(2)157-177,

Holzer, Harw J., 1986.. ..Sarch Method Use by. Unemployed Youth?

National B“r~n of Eco”omic R-ch Working Papr Setiw,

No. 1859, Cambridge, MA: NBEK

Holzer, Harry 1. 19S7a. ..hformd Job Sarch a“d Black Yo”ti fJnmployment? Americm Economic Review.77(3)44642.

Ho1m, Haw J. 1987b. “Job s~mh by Emp]oyti md UnemPloyti

Yo”th~, t“d~triulazd tibor Belatio”s Rmiew. ~4}@1 -611.

tie,,, Edwzd. 1976. ‘.A8e> Experience md Wage Gmwth,”Ame,fcon

Em”omic Review.66(4> 548.558.

high. D“... E. 1982. ‘~e Natio”d Lo”8buti”al Sumw A Stl-tive

SUWV of Recmc Evidence? Review of @bfic ~ra Use

1W3}185 .201.

Leighton, Linda and Mincer, Jacob. 1982. “bbor T.movm a“d Youth

Unmployme”t.,, In Fr~ma” a“d Wi= (1982s), pp 235-270.

Lynch. Lisa M. 19s6. “Tb. Youth h~r M=ket in the 8& Detcmim“ts afRe.mployment ~ob.b~fhim for Yo”.g Me” a“d Worn.

en.,, National B“r~u of Economic R_ch Worti.g Pap S..

rie, No, 2021. Gmbridgc, MA NBER,

Michael, Rohn T. a“d T-. Nanq B. 1984. ..You& tiplommc

Does Life Bean at 16Y Jou,”al of tibor Economim

2(4>464.476.

NLS motatd Bibliography 1968-1989. 19S9. Glumbus Cmter for

Humm Resource R--ch, The Otio State Univenity.

NLS Etbliography Update 1990. Colwbis Cater for H- Rsmrce

Res=rch, The Ohio State U“ivetiry.

NE Handbook 1990, Col”mb~ Gnler for H”.ma” Rwnr~ R_ch,

The Ohio Staa U“ivetity.

Olsm, Randall J., 1989. The Future of tke NLS:A Reptifrom che,VSF

Co”fe,ence on tke Fur”m of rhe NBand the NQ Tmknicoi R+

,,i,w Commirfee. ti”mb”s, Ohim Cmler for H“mm R~”rce

R-h, Ohio State U“i.ersity.

Par”=, Herbm S.a“d K.hen, Andrew I. 1975. ‘.Occ”p.tio”d Ifiomation a“d Labor Market Stat”% The *C of Young Mm..- Journal

of Hum=” Re,oumes. 10(1~W55,

Pa%more, Darid L.; Ay, UDd; Rmkel, Shevl; Wade. Barb-; md WE,

Jam=. 1983. ‘,H-hh a“d Youth Emplowmt.-App/ied fianomiCS 15(6):715-729.

P.Uard, Tom K. 1984. “Cha”S= ovc the 197VSin TheEmployment Pattms of Black s“d ~ite Ymns Men:- In Bo~s ( 19S4b), PP

57-79.

Raefi”, Joseph A. 1980.Btii/di”Sa Coreez Be EffcczofInil!alJob fiperiexcesa“d Related Work A tt;~ud= m tire, EmploJme”L Kda.

mazoo, MI: W.E. Upjohn I“stit”te for Employment Rw&.

-.E”, Joseph A, 1981..“A. Comparative Study of htm Work Exti-

. . . . among Full-Tim% Pafl-Xme, and U“empIoy4 Mde

Youth? Journal of Vmrio”ol Behavior. 19(3)315.327.

Rms, tib~. 1986.“h Essay on Youth Jobl=sn=s: JOumaf of Ec*

nomic Lile,ature. 2q2)613 -628.

R“mberger, Rus.11 W. 1983. ,The Influence of Family BackSound on

Education, &i”@, md W~kh,,> SocfaI Forcex 61(3)755-773.

Sa”tos, Nchrd. 198la. ..Dc Employrnmt S1aCUof Youth.,- In Bows

(1981b), pP 59-116.

Sante% Rchati. 1981b. ,~eH=hh Stat”$of Yo”w” 1“ Ba(1981 b),

pp 465480.

Smtas, fich=d. 1982, “klhatinE Youth Emplopmt a“d ff”cmploy -

menfi me National SuW~s of Youth Utir Markti &fiMc..”

Roiew &PubOc Dar. Use, 10(1-2) 127-135.

10
S.WM1, Iabl V. 1988. ‘Povetiy i“ the U.S.: Why k it so Paiste”tY

Journal .f Economic fit,m,urc. 26.(3Z 1073.1119.

Stwmwn, WaWe. 1978.. ‘,The Relatia”ship Between Youth Employment a“d F“t”re Employ abifi$y.‘. 1“ Adam a“d Ma”g”m ( 1978),

pp 93-124.

Stevmso”, Wayne. 1978b. “The Relatio”stip Betwe” Youth Employmat ad F“l”re bployability a“d timings.” 1“ U.S. Depatiment of tibor ( 1978b). pp 191-205.

Stevmm”, Wayne. 1978b. 1978., .<ThcTra”sition from School to Work?

In Adsms md Ma.g”m (1978) pp 65-91.

Summa, Lwx”ce H. 1985, ‘Why is the U“employme”t Rate So VeW

HiSh Near F“ll Employment?- Hamard Institute of &o”omic

R-w~h Disc”ssim Papr Seri6, No. 1284. &mbridge, MA:

Hamard U“ivemity.

U.S. Dqaflmmt of Lbor, 1978a, Conference ReWH o“ Youth U“employme”?:Ir.Measurement ondMeo”i”x, Wti”gton, DC: U.S.

Government Printing OE*.

U.S. Dqatime”t of tibor. 1978b. Suppleme”tam Papersfrom the Conference 0. youth Unemploymmr It. Me.swreme.t and Meaning.

Eti14 by Naomi Bergm Davidso”. Wmhi”gto”, D. C.: U.S. Govemmmt Pri”ti”g O~ce.

Wielg.sz,JohnB.a“d CVnter, Susan.1987..$TheEffective”es of Altemativ. Methtis of *arching for Jobs and FI”dt”s Them: An

Exploratoq Analysis of the Data B-ri”EUpO” Copin8 tith Job.

lessnes? American Jour..! of Economics ond SocioloD.

46(2)151-164.

Wink, Robcfi J. 1982. ‘Comment,,, 1“ Freeman a“d Wtse (1982a), pp

386.3.89,

11