me Nationalbngitudtial Smep (NM) progrm supponsmay studiesd-igned

@ tire-e mdastmdtig of tie latir makw md metiods d datacollection. ~e Dir.

cmsion Paperss=ies rn-ratti someof tie rauch comtig out of tie progm.

Mmy of h pawn in his saies havebmn delivm.d m fmd rwofls mmissiond s

PWI of m exummd Fat pmgrm, under which grin= Z. awmded tiough a

com~titive VC=S. me smiesis intmdedto circulatetie findingsto hlerestedretie=

wititi ad o.~ide tie Bweauof Lahr Statistics.

Pmsomtit==ted inobtarntiga copy of my DiscwsionPaper,Olh.rNLSreprs, m

gmmti tifomation abouttie NM propm md suweys &odd conlzt tie Bu=m of

ktir St~istics.Office of Emnomic Roscach. Wahtigtom DC 20212-OW1(202-606-

7405).

Ma~rM k his publicationk h M pubficdomtin md, witi appropriatemtiit, may

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Dptiom md .onclusiorisexpressti in fih documentX. hose of tie anti.r(s)

md do not nwss%2y represenlm official positionof lhe Bur=u of Labr Sv.tistics

m tie U.S.Deptiment of Labor.
NLS

Discussion

. Papers

.
Work Experience, Job Tenure,

Job Separation, and Wage Growth

Lee A. bllard

The RAND Corporation

August 1991

~s projem was tided by the U.S. Department of Labor, Bureau of Lahr Statistics under grant number E-9-J8-00089, and by a ~ant from the U.S. Depament of Education, through the National Center on Education and

Employment T=hers CoUege ColumMa Utivemity. me author wishes to acbowledge the exceptional work

of Constrmtijn Pards who wrote the computer sofware and of MaT Layne who prepared the event Mstories.

Opifions stated in tiIs paper do not necessarily represent the o~ci~ position or pohcy of the U.S. Department

of LaWr.
Do not quote

or distribute

withut permission

Work Experience, Job Tenure,

Job Separation and Wage Growth 1

by

Lee A. LIUard

The R.&ND Corporation

Revised August 1991

Abstract

This ?aper us=. the precise dating of job changes and the panel data on ~vag- \vithin jobs in

the NLSY to ~~lore their implications for a number of leadng theori= of job change and \\,age

groxvth, =pecitiy the relationships bet~veen general.. ~vork experience, j.qb tenure, job ch~ge and

\vages. ~~rages and job change are modeled jointly to incorporate the potential endogeneity of job

tenure. The estimates indicate & signifi=nt effect of job tenure on wages and the hazard of job

separation, as w-e~ u evidence of returns to job sear~, job turnov~ due to mat& qufl]ty, and

job specific human capital inv=tments.

‘This research ~v= supported by Giant No. E9-J- 8-00089 Gom the U.S. Department of Labor, Burean of Labor

Statisti~, md by a grant from the U.S. Department of Education, through the National”Center on Education and

Employment, Teachers College Columbia University. I \visl!10 ackno,vledge the exceptional \vorkof Constantijn 

Pmis .vho %.roti the computer soft\vareand of Llary Layne ,vho prepared tbe event histories.

1
Abstract

~i paper uses the precise dating of job changes and the panel data on wages within jobs in the ~Y

to explore their implications for a number of leading theories of job change and wage growth,

especially the re~tionshlps between gened work experience, job tenure, job change, and wages.

Wages ad job change are molded joinfly to inco~orate tie pOtenti~ endogeneity OfjOb ten~e. me

estimates tidicate a significant effect of job tenure on wages and the hazard of job separation, as weU

as evidence of returns to job search, job turnover due to. match quality, and job specific human caPit~

investments.

.
1 Introduction “.. .. . ‘ .... ~ ‘

Study of the determinants of ~vag= has been a m~ns:ay o; econotics in general .ad labor econoti~ in pirticdar. kIore recently there h= dso been a strong interest in the relationship

between w-ages and tenure ~vith & given employer and in the motiv= for worker turnover among

ernployms.

.+ key issue is whether Ivages rise Ivith tenure with a. given employer relative to alternative

employ em, ud then if they do what is the mefiafism generating the employer spetific premium.

The primary theori~ include (1) returns to divestment in employer specfic hum~ capital which

me shined with the employee (to induce the worker to not leave), (2) impficit contractual arrangements \v,M& use tvage growth (or. ‘backloa&ng’ of wages) = incentives for effort (agtinst shirking)

or to reduce turnover, and (3) rev~atitin of information on the qufity of !vorker-employer matfi,

different= in work= abiUty, and””returns to search.

This study provides a numb”er of new insights into the empirical plausibihty and relative

importance of these theoretid perspectives by providing = empirical framework to study the

rdationstilp between job turnover and !vag= with a spetid emphmis on the roles of general work

experience and job tenure. It m~es use of tique data from the A’ationd Longitudind Survey of

Youth (NLSY) on the precise titin: of begin and ad dates of aployment (tvith ea& emPloyer),

one or more wage observations on each job (importantly including jobs beginning md endln:

bet,veen surveys), and the precise dating of employer provided trtiting on. th=e jobs, and outside

vocational traiting, M ~ve~ u n~erous .demo=~aphic and job characteristics over a period of up

to seven years (1979-86). This data provides a unique opportunity to address issues important to

the discrimination am”nng the” important theories of \vage determination =d job turnover.

Use of this dettiled information on the \vag=, jobs, ad \vork experience of yonng \vorkers

reqtires the development of a richer, more fle.tible empirical model. This”study develops and implemmts a empirical model of the joint determination of \vages, including individud differences

in the level ad gro>vth of 1~.ages, and the haard of job separation which utitizes the richn~s of

the N’LSY data.

F]rst, a +scussion” of the models of \vage determination and of the hazard’ of job separation

are presented in section 2, don: \vith a brief discussion of the estimation procedures. The data on

~~~agesand job duration are dwcribed in section 3 don: \vith the unique features relevant to this

.

study and the model parameter estimates. Section 4 discussed the resdts and their impficatimls

for theories of job turnover and !vage determination.

~ The Model

The essential features of the model are related to the dyn~ics of \vage variation o~.er time as a

function of general \vork experience and job tenure and its relationship to the dynamim of job

change.

The fo~o~ving discussion presents first the \vage equation and then the hazard of job separation.

This is follo~ved by a brief presentation of the hkehhood function and estimation method.

2

.
2.1 The TVage Equation

The b~ic wage equation is designed to. f~c~; on in~vidu~: patterns of ~~age gr~:vth ~vith labor

market experience md ~vith job tenure. The b~ic lvage equation relates the (log) \vage (lVij(t))

at time t of individud i on job j to his total months of labor m=ket experience, ~z~(t), tid to

his tenure on his current (j – th) job, Ten:j(t).

PVij(t) = A;+ B/EZP~(t) + Cfj + DijTe~Tj(t) + V{j(Z)

Eati worker has m individud intercept, A;, upon entering the labor m=ket at the be~nning 

Of his cmeer and m individu~ rate Of grO~vth Of ~vages with gener~ wOrk experience, ~{~zP;t).

The intercept Ai may be a function of the (non-time mrying) &aracteristics of the \vorker, .Y~.

Ai = ~ + -/~X~+ Jai

This equation relates initial labor market entry wages to covariat.es Xi, \vith ~ being mean ({og)

ent Iy wages. 2

The model is specified

Hnem spfine equation

with ~ = 13 so that the mean experience profile given by the piece~tise

n==P

Ezp;(t) = ~ 8~V~(experiencei (t))

k= I

\vhere nezp is the number of nodes and the function V is the usual linear spfine operator~. The

coefficient on Ezp:(t), B;, may be a function of the (non-time varying) &aractaistics of the

T\,orker, X;.

B; = B + 7j4Yi + 6*~

The comiates Xi then proportionfly shift the mean profle according to the regression function.

The int=cept and the experimce slope each have random elements, $={ and 66i respectively, \vhl&

may be corrdated.

Upon beginning each ne~lr job, say the j – t~, the \vorker receiv= = initial \vage, Cij, and

rate of gro~vth of Ms \vage ~vith job tenure on that job, DijTe~~j (f). Dra\vs of Cij and Dij are

=smed independent (iirf) from job to job, except that they are functions of the chmacteristic3

of the job. That is,

The first equation relatw initial \\rageson a job to the characteristics of that specific job Z{j,

or the ch=acteristim of the \vorker on that jobs On average Cij must be zer6,6 so that ~ = O.

‘The .o..ari&tcs X; are me-nred w deviation from the mean over individuds.

3The COVariateSX; are me~uzed u deviation from the mea o.,er inditid”ds. Eq”ivdently, on. might allo~v

~ free .vK1e normalizing e,, the spli”e coefficient in the first interval, to one so that subsequent e~s represent

- mperienceequi..dent” uni,tsof \vozkexperience.

‘V*(Z) = maz IO,min (t —~k-,,pk —PA-, )1 ~Vherep,(~ = 1, n - 1) a.. the nodes. lmP1icitl?, POand b-==.

Ttis fltible ftinctiond form includes the linear experience vzriable u a spetid cue (e~ = I, for dl k) a“d can

e=ily approximate the form of the more US”A quadratic terv.s (\vithout requiring . peak).

‘The job covariates are me=ured M deviations from the mean over jobs.

‘If a tvorker receives a higher initial \vageon average, then the imp~~edC, becomes part of that ,vorkersA;.

3
The second equation relates the :rO~v!h_in $vag~ with tenure On that jOb t.o the characteristic=

of the job. The model is specified with D = 17 so that t> mea” tmure profle given by the

piece.rise Erie= spfine equation Ten:j (t), i. Z“.

nrc.

Ten;j(t) = ~ (I Vk(tenU.e;j(t))

k=l

where n~.. is the number of nodes and the function V is the usual Enea sp~lne operator. A:tin,

this fle.tible functional includes the linear experience and tenure miabl- M a spedd ase (<~ = 1

for W k) and cm eufiy approfirnate the more wud quadratic tenure terms. The re~ession equation for the coefficient Dij repr=ents shifts in the profle M a function of the characteristi~ of

the job or of the individud On that” job, md a random residud term 6d;. The job-person specific

residud intercept, (6.;, and tenure slope, Jdi, may be corzdated Tvith each other, but must be

orthogonal to 6.i=d ~b~.

k addition to these experience and tenure components of ~$,ages, there is a time series of

deviations from th=e profiles, Uij(t), ~vhere

Uij(t) ‘ 7~l<j(t) + ~ij(t).

The Yij (t)are me=med time varying covariat= influencing \vages, such u business cycle and local

labor market conditions, and uij (t) is a purely and r=idud reflecting random lrariation in \vages

=d measurement error.

The \vage equation may be ~v.ritten in terns of co:=iat- ad residuds by substituting for A,

B, C, D and U.

lVij(t) = ~ + 7LX~ + EzPT(t) + vi X;) E~P~(t)

+ 7: Z{j + Tenij(~) + T:zij Te~7j(~) + ~?~yij(~)

+ 6={ + Jb, Ezp”(t) + 6c;j + Jdii Te~”(~) + ~ij(t) ,,

The cotariates Xi ““are interacted ~yith the fill set ..of experiace spline variables represented in

Ezp”, and the job-levd covmiates 2; are interacted with the full set of tenure spline variables represented in Ten-, but in a \vay .vhich mtintains the b=ic proportionahty of the spline coefficients.

The residuds terms indicate individud ad job level random coefficients on experience md

. tenure rwpectively. They induce both heterogeneity and correlation among residuds o..er the

xb.ork cxeer. ,

2.2 Tile Hazard of Job Separation

hdi~-iduds may hold a number .of jobs during their ~~-ork care~s. Once a job begins, say the

j – f~, the ~~Or~eris immediately at risk tO leave the job. The job is assmed to titimately end at

some point, \vith tvork experience Ei and job tenue ~j. The basic equation of job e.ti t behavior

is the (log). h~ard of leaving the. job, say the j – th,

In gij(t) = ~Q+ E~~”(t) + Ten;(t) + a~.Yj + O~Zij + ~~Yij(t)+ <i.

.~

‘Since ~votkexperience k the sum of tenure on dl jobs, a ,vorker \vho&xrays, or on average, h= greater tvage

g.O~~rh~vithtenure h= .Z steeper experience prOfile, $0 that any ~< becomes part of Bi.

4
The log hazard of job sep-tion incorporates two forms of duration dependence – general

w-ork a~perience and cummt job tenure. Each changes limarly in time within a job, but their

effects may be iep=ated because of wiation initial \vork experience at the beginning of the job.

The terns Ezp”-(t) and Ten;,:(t) =e eah piece~vise linear sphn= in work experience and job

tenure.

m.=,

~zp~(t) = ~ O;-Vk(experience i(t))

k=l

-rem

Ten;;(t) = ~ [:-Vi (tenure ij(t))

k=l

xvhere mc.P and ret.. are the number of nodes in experience =d tenme respectivdy, ad the

fmction V is the usual hnem spfine operator.

The h=ard equation is =sumed to hold for M jobs and individuds, but is a function of individud Aaracteristics .Y;, the Aaracteristics of the job (or the workers &aacteristics on that

job ) Z;j and time varying covujates Yij(t). In addition, the h==d of job separation includw a

residud term, <i, reflecting indlvidu~ differences (heterogeneity) in the rate of job changes. 8

The huard of job sepmation, condition on worker heterogeneity e, is given by

gij(t, ~) = e

ee+E=P~”(t) + TcK~~(t)~=~~;+-~Zij+e~Y{j (t)+.i

The combination of the effects of Ezp’” ud Ten”” may be termed = “overlapping splinea formulation of the huard. Let the “ b=etine” hazard be composed of the intercept and the combined

duration effects. Then the ‘:b=&lne” survivor function is

CoI=iat= ~use proportion~ shifts in the hazard. The comriates .Yi and Z~j are constant for

the duration of a job. The col-ariates Yij (t) may v=y ova time }vithln a job, but are ~sued

constnt within sublntervals of time. Denote the number of such suKlntervds by Zij and the end

points of the sybinter~rds by tijg. Therdore, the condltion~ (on c) survivor function for job j i

gix-en by g

.G’j’~(’)’)=EIG:::/~::;)l

~o: xi*=; Z;*.; Y;,(t)+.i

tshere ,y(t) denotes the full history. of time varying co>ariates Yij up to t. The condition~ density

fnnction of completed job duration Tj is given by

Th=e haz=d and survivor functiom are conditional on individud heterogeneity in tl~e rate o

job change, c;. Individnd heterogeneity in the rate of job leaving is identified by the observation

aIi the ate of job turnover is correlated “tith the level and rate Oi gro%vthoi ,vag-, then f~lur= to control fo

the endogeneity of job change \villbi- estimates oi the effect of experience md te””re on .vages. The nature 

this correlation speaks directly b certtin hypothes= to be discti~ed later.

,

5
of the duration of dl job held by \vorkers oyer a fixed length of time.

2.3 Estimation

~=meters of the mod~ are =timated by m~~mumfi~e~hood b=ed on assumptionofjoint

normfllty of the three independent sets Of st~~astic elements (~, J., fb), (~.j, ~~j), and uij(t). The

first set of three represent heterogeneity in, respectively, the hazud of job separation, the level of

titid w-agss, and !!:.. ~O~vth Of :~ag- >vith..:ener~ IabOr market exPerienceThe second set represent job specific heterogeneity in the ifiti~ level of \vages ad \vage gro~vth

with tenure on the job, both specific to a job md independent from job to job.

(t)-’v(Q!~:~JdP$c,. %P’’’dl)

for eve~ jOb j.

The third set of rssidud terms are the individual period ~~age residu~s, M’ = (u1, ~2, . -., UT),

representing both independent variation in” ~vages. nd observational error.

It \..fil be convenimt .to relvrite the Ivage equation in a simp~fied matrix notation. Let IY be

the vector of”observed ~vage vdu,m for Ivorker i organized in order of job: and then time ~vitbin

job.

~=.~+~

avhere the mean is given by the >e:r=sion equation

=d the co%ariate \,ectors are gi~en by

6
The Ekefihood for eafi individua worker, given his observed history of lv~es and job &mges,

is given *y

3 The Data

Estimation of the parmeters of the lvage equation md the h=ard of job separation is e~tremely

demanding in terms of the data requirements. The NLSY h= a fe~v,key featur= \vhi& m~e it

espeddly useful for this study.

This study us- data on job 10 , ad trtining, histories constructed from the A’ationd Longituan~ Sumey Youth (xLSY) cohort, y~rs 19.79-1986, and the companion Employer Supplement.

Ea& survey yem, respondents ~vere =ked detailed demo~aphic qu=tions, u lvell M qu=tions

about trtining received, employment status, income md ~sets ti”d acadetic status. The compafion Employer Supplement gathers dettiled information on up to five jobs in each smvey year.

hduded in the qu=tions are stint/stop dates for each of the five jobs, industry, occupation,

usual hours per ~i-eek ~uorked and lvage rate. Table 1 reports the list of variablw (.Y, Z, and Y)

entering the \vage and job separation equations, their means ad stadmd deviations, and a brief 

dfficription.

.ti importa;t feature of the survey is that it covers the full e=ly \vork cmeer of a representative set of young men 11 so that there is no problem of unobser~,ed earfier behavior. Our analysis

of the ~1.ages and job turnover behavior begins \*-hen the young men fitislled formal schooling and

entered the labor force, some time during the 1979-1986 period. 12

Critically important is the reporting of the begin and end dat= of dl jobs, =d the reporting

of ~vages -.,,at suvey dates. and for dl jobs held since’ the l=t survey. The Employer Supplement

,oThroucho”c the term job is meant to imply employer rather thm t-k or job d=cription.

.

i>$Yomen are not included in ‘this study.

‘21n&vidua]s xvereexcluded if >vecould not determine the respondent’s education or ii industry 5VUmissing fOr

dl jobs.

7
is used to construct begin and and dat= fOr..~l jObs. held d~ring the sur~.ey periOd, 1979-1986. 13

This indudei jobs beginting and. .en~n: between surveys, yhifi ~vOuld be missed in the ~nu~

14 FiCme 1. iUu~tratH the. b~ic patterns of data in the cOnte~t Of a

reports of wages and jobs... ~

job e}-at Klstory. ,,

The resulting sample includes j,26~ yOvng men who held a tOt~ Of 18,427 jObs and repOrted

a total 28,586 \vag& ~dues o~er..t>e seven y=r period. The .dstribution of number of jobs held

is reported. in Table 2. The fractiOn Of th=e jObs ~vhich ~vere cemOred, i.’e. $tfl in PrO:ress as

of the find sumey date, mean duration of the completed jobs, and mean full time experimce at

the beginting of the job are reported in Table 3. The overall distribution of number of \vage

tii= avtiable for each job is repOrted in Table 4. 15 Table 5 reports me= v~ues of the fraction

reporting some period of non-work just befOre the job began, the duration of the period of nonIvork (for positive dti=), and the cumulative time in non-~vork (including the current aount)

prior to the job.

4 Results

The model includes a lmge number of equations =d even more relationships to be considered,

ti>-olving more thm a hundred jointly estirnared pm-eters. Nltimul likelihood estimates of the

parameters are presinted in Table 6, for the b~ic modd. Appendix table 2 presents atimatw of

the p~ameters of the model ~vithout mvariates, representing the basic relationships in the raw

~t-age and job duration data. Appendix Table 3 presents estimates of the b~ic model enhmced to

include memur= of the accumulation of, and time lapsed since , vocational training and formal

on-th-job trtining events.

O\,erW, the results indicate evidence for a number of theories of \vage :ro\tith and job turnover.

-Ml components of ~vage :ro~~th and Of the h~=d of job tnrno$er are si:nificantI? related tO

expl= atory factors in ~vays that are intuitively appe~ln:. There is also significant and important

variation in the components of heterogeneity - in ititid c=eer \vages and cae= \vage development,

in initial job specific ~vage and the effects of job tenure on \vages, in transitory ~vage vaiation,

and finally in the the hazmd of job turno~er. Let us take the variOus cOmp Orients Of the mOdel in

turn, then relate them to the. yarious theori+-

4.1 I1litial Tvage Levels and tile }Vage Gro>vtll l~ltll General Experience

Initial I>-ages are sigtilficnatly enhanced at. higher levels of of me-red IQ. And having a college

● education very significiritlj “in”cie~es ititial earnings by appro.timately 23 ‘percent.

The a~eragapattern of <vage groivth ~vith general experience is represented in the top portion of

Figure 2. .Ifter the. first year ~vag= rise .ftirly sharply until year three the taper of a bi t thereafter

(shol$n to eight years). Only edu,catio.n incre=es the rate of gro~vth of ~v:g% ~~ith .gener~ ~vOrk

experience (i.e. shifts the slope Of the O~eraU curve). Remember that any ~vage gains occuring on

every job are attributed to general ~vork experience, but may be due to greater learning On each

job. College graduates both have high= ititial tvagw and greater \vage gro~vth. The effects of

education are illustrated in Flgur.e 4. kter=tingly measured IQ do= not incre=e ~vage gro~vth,

only the initial level, condition on education level which is another meuure of lemning ability..

This resdt for IQ is count= to a learning interpretation of general \vage :ro\vth.

lZODIV~ho5ejobs thzt ,vere in progras ,vhen left iormti schooling or thereafter.

l+lt i; _“m=d th..t reported ,va$esaIe s of the end of the job.

IsThe &,~trib”’ion by job number is,reported in the Appendix.

8
Table 1.

Variable Descriptions, Nleas, Standard Deviations, ad

Spetificitions of the lVage ad Job Sepaation Equation

Legend: 1 = }Vage Function

2 = Hazmd of Job SeD=ation - l-st iob

Tmure on currmt job - months

Race indicating black

L=s thm high s&ool education

Some college

CoUege graduate

IQ me=me in bottom 25 pmcent

IQ me~ure in 2-rid quatile

IQ me=ure in top 25 percent

Vmiable 12 ti1em,70 Desmiption

FT Exp xx”” ~ time exper - month, begining of job”

Job Tenure x x.

IVORHER CH.kR.lCTE~STICS (X)

Black xx .231

Ed <12 x x .295

Ed 13-15 x x .192

Ed 16+ x x .120

IQBOT25 x s .250

IQ2550 xx .250

IQTOP25 x .x .250

JOB CH.+R.4CTE.RISTICS (Z)

UNJ .s .x 18.7 .39

GJ .Y .x 3.0 .17

SERV xx ; 22A . ..42

CO~ST .x x 18.8 .39

OTHER .x x 36.2 .48

S.%NIEI xx 32.2 .4?

Jl~’P xx S.1 .27

BJN-\\;I{ x X 67.0 .47

BJUh-l10 x x 6.1 11.45

cullTYI{N\Y x x 19.9 22.95

FTEXPO 16.5 .20.27

LKIV.4GE ‘ .j.2 .52

TIIIE V.4RY1XG V.A~.4BLES (Y)

U~T x .164 .02

GDP x 13.01 .06

US % LF \vith positi~-e \veeks unemployed

US Gross domestic product (SBil)

Job covered under union a~eemmt

State or federd government supported job

Industry - Services ad Retail Trade

hdustry - Construction

bdustry - All others (Omitted = YImufacture)

Same industry”= previous job

First job in progress before leaving school

Indicator of some non-xvork before current job

~Veeks of non-~vork before current job

Cumulative <veeks of non-~vork before current j

NIos. experience at start of job

Log \VeeHy \Vage

9
Table 2. “’

Distribution of Number of Jobs Held

Jobs Number %.

1 1277 24.3

2 1082 20.6

3 852 16.2

4 623 11.s

5 432 S.2

6 343 6.5

7 215 4.1

8 156 3.0

9 93 1.s

10 64 1.2 ””,”

11 46 0.9

12 S2 1.6

Total 5265 100.0

Table 3.

Censored and Completed Durations

and Mtid Experience by Job Order

glean bIean

Percent Find Initial

Job N’umber Censored Tenure FTEXP

1 3265 1s.3 17.2 0.0

2. 3988.. 21.0 13.5 11.5

3 2906.. 22.4 12.0 19.1

4 2054 23.3 11.0 24.9

,j 1432 22.6 9.9

6

30.0

999 26.3 8.3 ~ .35..4

7. 656 24.7 7. .j 37.6

8 441 26.3 i.3” “40.4

9 2s5 22.1 6.9 42.2.

10 192 24.0 6.6 a4.9

11 12s 2s.1 “,”6.6 45.9

12 S2 .”” “1s.3 5.7 47.s

Total lS42i 21.5 12.9 16.”5

10
Table 4.

Number of \Vage

Observations per Job

No. Freq %

o 2649 14.3

1 9150 49.6

2 3762 20.4

3 1346 7.3

4 604 3.2

5 432 2.3

6 230 1.2

7 132 0.7

8 122 0.6

Total 18427 100.0

Table 5.

Job Characteristics by Job Numbm

% lVeeks lVeeks

Job BJNIV BJUNM O CUN1}VKNIV SANIEI

1.60 16.5 16.5 0

2 ~1

3 71

4 68

5 69

6 66

7 66

8 6S

9 71

10 64

11 66

7.6

6.9

6.2

6.2

5.4

4.7”

4.2

4.0

3.4

3.2

15.7 44

20.7 43

24.7 45

2s.9 47

31.9 46

34.6 47

36.4 47

39.3 49

40.6 51

45.1 53

12 74 4.2 4s.9 62

Tot& 67 9“.1 20.0 32

11
Bla&s earn si~~ific~tly less ii initi~ ~vages, but the difference is Onl~ ~bOut ~.~ percent and

wage gro~vth \vith general e-xp:rie.nce is nOt signifi~ntly less.

4.2 Job Specific Initial JVages and \Vage Growth

.L number of metiured factors simficantly affect the initial level of wages cm the job. These

include industry of employment, being cOrered, by a union contract, government employment,

coming from a last job in the same industry, and time spent not lvorHng (out of the labor force

or unemployed) bet~}-een jobs or between school and first job.

The average pattern of wage growth ~vith job tenure is uniquely illustrated by the spline

function, as shown in the second panel Of Figure 2. lVag& increase ~vith job tenure only over the -

forst y-r on the job, then ae a constant differential from initial wages. Therefore, Ivhlle \vages

do not continue to rise with tenure for q long period, there is a sie-ificant loss of \vages, about 7

percent, from leaving a job after one Y=. The effect. of multiple jobs is illustrated in Rgure 3.

Only time not ~vorklng significantly affects ~vage grolvtb on the job.

4.3 Dynamics of Job Separation and Job Duration

The h=ard of leaving a job is significantly rdated to both incfividud characteristics and the

chmacteristics of the job. Th=e include education, me~ured IQ, industry, union =d government

jobs, and 10A labor market conditions. The hazard of leaving the job decfines botb \vith general

\vork experience and \vith job tenure, u illustrated in Table 3, and for some covariates “in the

following tablw.

,4.4 Residual. Variation in TVage Growth and the Rate of Job ~rnover

Th=e is sietifimnt correlation betlveen the haz=d of job leaving and \vage :ro\vth \vith \vork

axperiace, but not ~vich initual ~vage. Thus models of \vage gro~vtb not accounting for theis

correlation \vill systematically attribute too much ~vage gro~vth to long jobs.

*
Table 6“.

Structural Paraeter Estimates

IVages

hdividud Job Specific

Xtid GrO\vth l~th Ifitid GrOn-th \Vith

Level E~erience Levd Tenure

~Tp* (Jionths): Ten’ (kionths):

SFELT12

SFE1224

SFE2436

SFE36P

COvariates (X):

Intercept

BLACIi

EDLT12

ED1315

ED16P

IQB 0T2

IQ2550

IQTOP2

5.0744 ***

( 0.0105)

-0.0445 ***

( 0.0156)

0.0016.

( 0.0155)

0.0000.

( 0.0164)

0.2344 ***

( 0.0205)

-0.1467 ***

( 0.0181)

-0.0619 ***

( 0.0166)

0.079s. ***

( 0.0160)

0.0036 ***

0.0010)

0.0052 ***

0.0006)

0.0074 ***

0.0006)

0.0035 ***

0.0002)

1.0000

STNLT12 0.0051 ***

( 0.0007) 

STN1224 0.0007 ***

( 0.0002)

STN24P -0.0002 **

( 0.0001)

COmriates:

_oNE .“ 0.0000 1.0000

UNJ 0.1575 *** 0.12S6

( 0.012s) ( 0;2661)

-0.0922

( 0.0s12)

-0.2399”***

( 0.0748)

0.3779 ***

( 0.0s25)

.0.6554 ***

( 0.1163)

-0:1360

( 0.0S61)

-0.0031

( 0.0s30)

0.0241

( O.OSli)

GJ -0.210s *** -0.1252

SERV

CONS

OTHR

SAIIEI

JIINP

BJNIV

BJUNkIO

cuhlwI<N\v

( 0.0244)

-o.lsi2 ***

( 0.0177)

0.1197 ***

(-0.0170)

-0.osli ***

( 0.0157)

0.0613 ***

( 0.011s)

-0.1303 ***

( 0.023i)

-0.0650 ***

( 0.0130)

-0.0016 ***

( 0.0006)

-0.000s ***

( 0.6234)

0.0s55

( 0.3672)

-0.32S5

( 0.3716)

-0.3432

( 0.3235)

-0.3955

( 0.2579)

1.2136 **

( 0.4797)

0.1s66

( 0.2s01)

0.0326 **

( 0.0129)

-0.0146 **

( 0.0003) ( 0.0064)

N’OTE: (a) Proportional Shifts h ‘;B~efinem

GrO~vth Due to Co~-ariates in

De*iatiom from Nleans.

13
*

Table 6a. <

Structural Paramet3r Estimates

Hazmd of Job Separation

EXP-* (NIonths) Ten** (Lfonths)

EX-O-12

EX-12-36

EX-36P

Covariat= (X):

BL.4CK

EDLT12

ED1315

ED16P

IQBOT25

IQ2550

IQTOP25

-0.0217 ***

( 0.0033)

-0.0091 ***

( 0.0014)

.o.oo~~ ***

( 0.0010)

0.0680 **

( 0.0310)

0.2933 ***

( 0.0303)

0.0425

( 0.0336)

-0.52s2 ***

( 0.0541)

0.0585 *

( 0.0352)

0.0523

( 0.0322)

-0.0773 **

( 0.0346)

G-Int

Go-3

G3-6

G6-12

G12-24

G24-36

G36P .

C0vmiate5 “(Z):

JIINP

BJN}V

SERV

-2.3075 ***

(“0.0380)

0.1225 ***

( 0.0148)

-0.1966 ***

( 0.0129)

-0-.0~6

( 0.0072)

-0.0216 ***

( 0.0047)

-0.0108 *

( 0.0058)

-0.0059 **

( 0.0029)

-O:268Y ***

( 0.0409)

0.1901 .ET.*..

( 0.023S)

-0.0046 ***

( 0.0010)

0.0012 *

( 0.0007)

0.0.S62 ***”

( 0:0”298)

CONS.T 0.3474 ***

( 0.0324)

OTHER 0.1102 ***

( 0.0276)

S.LIIEI -0.014s

( 0.0214)

~~J .-O.6G29 ***

( 0.026i)

GJ o.~67~ ***

( 0.0522)

Covariatis (Y):

U3T -1.4337 ***

GSP

14

0.4220)

0.023s ***

0.0092)
Table 6b.

lVage and Job Turnover Residu4 Vuiance Components

St=dard Deviations and Correlations

\Vage Components

Transit Gener4 Job Specific

Initial GrO\vth Ititid GrOXvth

lJ7age Components

Transitory .2634

(.0007)

General

fitial Levd

Growth $\,/Exper.

Job Specific”

Wltid Level

-.

GrO\vth \v/Tenure

Job Change

Level \v/E~er Level \v/Tenure

(Spetric)

.2645

(.0061)

-.4961 .8677

(.033s) (.0409)

.3062

(.0033)

;.~6;) ;:;~;;)

-.0059 -.1490

Job Change

.4ss1

(.03S1) (.0567) (.0174) 

“Kote: Blmkentries arezero, except fors~mmetcy of correlations.

15
.,

Fiwx. L: T-g of Wage Obsemations, Job

Separations and Training Events

.,

‘1

.’
--

Fi~re 2: Uages, Eazard of Job Separation, and

~lopenc Sumival Function at m~an co~axiaces:

No jobs begiuing (1) at career encq and

(2) after 5 years. on the first job.

J1 = Job 1

32 = Job 2
I .,

*

.,

.05 .

0

6 lj 22 5s 46 60 7> 9’4 $=

experience (mo”tnsl

.2

.15

.05

c

rl

h J2

‘%

,

,

Fi~re 3: Wages, Hazard of Job Separation, and

@lo&enr SumiVd Function at mean covariaces:

5 jobs begiming

(1) .J1 at career ent~

(2) J2 at 6 months qezience

(3) J3 at 10. months e~erience

(4) J4 at 34 months eqerlence

(5) J5 at 46 months e~erlence
.-

.~&,. :

/

Log Vage

:.a 1

L:

5.5 .,

,

3

5.4

~..

5.2 

.2

i

.15 -

. Hazard of Job Separation

.1 -

.05-

1

FLgure 4: Wages, Hazard of Job Separation and

klo~enc Sun~val Function, by education,

at mean other covariates

I- college

2 -=. s-e college

3 = high SCbOOl

4- high school drop out
;

?

~’”;”

5-+

6

-

Sk 1’9 6’0 7’2 E4 $6

excerie5ce cnootns]

.2

.15 j

.1 J

IL, ~......: 

1

.05 1

3,4 ~ “’

3,4 2

Figure 5: Wages, Hazard of Job Separation and

~lovenc Sumival Function, by industmy,

2 jobs each in the s-e induscg

(1) constmction

(2) -nufac’turing

(3) semices, retail

(4) other”

-.

Abraham, I<athmine G.., and Henry S. Farber. “Job Duration, Seniority, and E=tings.”.4 merican

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16
Jovanovic, Boyan. ‘:Firm-specific Captid and Turnov=~’ Journal of Political Economy 8i (December 1979): 1246-60.. (b)

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Is
ADnendix Table 1. . .

XTumb= of Ilrage Observations by Job Number

First Second Ttird Fourth ‘ Fifth Sixth ,

# ~ Freq o Ereq o Freq % Freq % Freq

o 629 11.9 5s7 14.7 44s 15.4 309 15.0 229 16.0 161 16.;

1

2

3

4

5

6

7

s

2531

1023

4?2

223

16S

10s

74

S7

4s.1

19.4

S.o

4.2

3.2

2.1

1.4

1.7

1750

909

333

161

117

65

3s

2s

43.9

22.s

S.4

4.0

2.9 .1:6.

1.0

0.7

1417

..605

213

100

69

“34

14

6

4s.s

20.s

7.3

3.4

2.4

1.2

0.5

0.2

1006

459

157

62

39

19

2

1

49.0 i53 52.6 ail ‘-- 57.S

22.3 2S4 19.S 190 19.0

i.6 101 7.1 56 5.6

3.0 33 2.3 5 0.5

1,9 26 1.s i O.i

0.9 3 0.2 1 0.1

0.1 2 0.1 2 0.2

0.0

Seventh fighth Nineth Tenth Eleventh T\velfth

# Freq % Freq % Freq Y, Freq % Freq % Freq Y

o 101 15.4 i2 16.3 43 15.1 2S 14.6 23 1S.0 19 23.;

1 405 61.7 265 “ 60.1 Isi 65.6 132 6S.7 .7S 60.9 49 59.s

2 112 17.1 iS Iii 40 14.0 2i 14.1 24 1S.S 11 13.4

3 2i 4.1 1s ..4.1 10. 3.5 4 2.1 3 2.3 2 2.4

4 9 1.4 6 1.4 3 1.1 0.5 1

5

1.2

2 0.3 2 0.5 2 O.i’ 1

19
.ippendix Table 2.

\Yage and Job Change Duration

Dependence. %J’ithout Regressors

Ifem

Initial JVage

Duration Splines:

\Vage Groxvth \vith Experience

SFELT12

SFE1224

SFE2436

SFE36P

T?’age Grox!.th tvith Tenure:

STNLT12

STN1224

STX24P

Haz=d of Job Separation

Full Time \Vork Experience

(llonths)

EX-O-12

EX-12-36

ES-36P

Job Tenure (Jlonths)

G-Irit

Go-3

G3-6

G6-12

G12:24

G~4.36

G36P

5.031i ***

( 0.0103) ~~

0.0082 ***

( 0.0009)

0.0055 ***

( o.0007j

0.0071 ***

( 0.0006)

0.0032 ***

( 0.0002)

0.0043 **’

( 0.000i)

0.0007 ***

( 0.0002)

0.0000

( 0.0001)

-0.0149 ***

( 0.0031)

-0.00i1 ***

( 0.0013)

-0.002s ***

( o.oolo)-

-2.3iil *?*

( 0.0346)

o.loi2 ***

( 0.0144)

-0.20”47 ***

( 0.0127)

-0.0146 **

( 0.0072)

-0.0262 ***

( 0.0047) =

-0.0126 **

( 0.005s)

-0.00ss ***””‘“-”

( 0.0029)

20
.Appelldix Table 2a. :

J\~age and Job Turnover Reidud Variance Components .,

Standard DeviatiOm and Correlations

!Vage Components Job Change

Tramit Gener4 Job Specific

Iltitid Gio{tith Initial ‘-Growth

Level \vjExp er Levd xv/Tenure

\Vage Components

Trasitory” .2644

(.0007)

Gaerd

Ifitid Level .3351

(.018s)

Grolvth \v/Exper. -.4454 .90s2

(.02ss) (.0420)

Job Specific

Wtid Level

GrO\vfih w/Tenure

Job Turnox.er

.3154

(.0034)

-.474s 4.2469

(.0305) (.6956)

-.1s39 -.1625

(.0323) (.046S)

..6295

“(.0173)

21
i

1

~ Appendx Table 3. :

Strtictural Puameter Estimates

\Vages - ~ i

General \Vork Experierice

Initial Growth }Vith

Level Experience

EXD* (Jlonths):

SFELT12

sFE1224 ~

SFE2436

SFE36P

0.0041 ***

( 0.0010)

0.0051 ***

( 0.0006)

0.0074 ***

( 0.0006)

0.0034 ***

( 0.0002)

Covariat=:

Intercept 5.0723 *** 1.0000

( O.OIOi)

BL.4CI< -0.0461 *** -0.0915

( 0.0159) (“0.0820)

EDLT12 0.0014 -0.2457 ***

( 0.015s) ( 0.075s)

ED1315 -0.0007 0.3654 ***

( 0.0166) ( 0.0S32)

ED16P 0.2279 *** 0.6591 ***

( 0.0209) ( 0.1177)”’

IQBOT2 -0.1465 *** -0.1140

( o.ols4j ( 0.0s73)

IQ2550 ~~-0.0651 **.* .0.0320 ‘

( 0.0169) ( 0.0s40)

IQTOP2 0.0819 *** 0:0099

( 0.0163) ( 0.0s28)

NOTE:. (a) Proportional Shifts In “Bweline”

Gro\\.thDue to Covariales” in

Deviations from hleans.

22”
Appendix Tzble 3ti :

Structural Par-eter Estimates

\Vages

Job Specific lVagw

Initial Gro,vth \Vith

Level Tenure

Ten+ (hlonths):

STNLT12

STN1224

STN24P

0.0050 ***

( 0.000s)

0.0006 ***

( 0.0002)

-0.0002 *

( 0.0001)

COvariates

_OHE

uNJ

GJ

SERV

CONS

OTHR

s.4%1E1

311NP

BJN%V

BJVXhIO

0.0000 1.0000

0.1612 *** 0.0810

( 0.0130) ( 0.2s01)

-0.2089 *** -0.1737

( 0.0248) ( 0.6571)

-0.1804 *** -0.0760

( 0.0179) ( 0.3866)

0.1292 *** -0.5499

( 0:Oli3) ( 0.3955)

-0.0724 *** -0.5857 *

(0.0159) ( 0.3451)

0.0607 *** -0.3SG9

( 0.0119) ( 0.2i13)

.0.1304 *** 1.2968 **

( 0.0242) ( 0.515i) .

-0.06iS *** 0.2323

( 0.0132) ( 0.296i)

-0.0015 ** 0.0323 **

( 0.000G) ( 0.0135)

CUbl\171<N>V -0.0008 *** -0.0145 **

( 0.0003) ( 0.006i)

NOTE: (a) Proportional Shifts In “Baseline”

Gro\t,ih Due to Co>.ariates =

De\.iztiol~s from hIeam.

23
.

.4ppendix Table 3b. :

Structrud Par-eter Estimates

IVages ~~~

Trtining E“ffects

COvariatM:

Company Trtining:

Colvv

DSICO

DS2C0

DS3C0

SIPJCO

S2PJC0

S3PJC0

TOTVO

PJDSIVO

0.0881 ***

(0.0192)

-0.000.0

0.0000

0.0000

0.0000

0.0000

0.0000

0.0100

( 0.010s)

0.0000

PJDS2V0 0.0000

PJDS3V0 0.0000

.
.4ppendix Table 3c,

Structu;;l Parameter Estimates

Hward of Job Separation

Exp** (Jlontk) Ten** (Nfonths)

EX-O-12 -0.0210 *** G.Int

EX-12-36

EX-36P

COmiat- (X)

BLACK

EDLT12

ED1315.

EDi6P

1QBOT25

IQ=50

( 0.0.033)

-0.0100. ***

( 0.0014)

-0.0059 ***

( 0.0010)

0.0639 “*

( 0.0313)

0.2907 ***

( 0.0307)

0.0390

( 0.0340)

-0,5252 ***

( 0.0544)

0.0515

( 0.0355)

0.0549 *

GO-3

G3-6

G6-12

G12-24

G24-36

G36P

Covariate (Z):

311hrp

BJN\V

( 0.0325)

IQTOP25 -0.0740 ** BJUNIIO

( 0.0349)

CUAI\VI<K\V

SERV

CONST

OTRER

S.khIEI

UNJ

GJ

-2.31S2 ***

( 0.0365)

0.125& ***

( 0.014s)

-0.1962 ***

( 0.0129)

-0.0079

( 0.0073)

-0.0230 ***

( 0.0047)

-0.0103 *

( 0.0058)

-0.0065 **

( 0.0029)

-0.2746 ***

( 0.0411)

.0.1965 ***

( 0.023S)

-0.004s ***

( 0.0010)

0.0012 *

( 0.0007)

‘ 0.0927’***

0.0300)

0.3540 ***

0.032S)

0.1145 ***

0.0277)

-0.0133

0.0214)

-0.6628 ***

0.0269)

0.2$09 ***

0.052”1)

Covaiata (Y):

UXT

GSP

FTCCO

Dslco

DS2C0

DS3C0

PJcCO

SIPJCO

S2PJC0

S3PJC0

TOTVO

PJDSIVO

PJDS2V0

-1.375s ***

( 0.423S)

-0.0222 **

0.0093) 

-1.123~ ***

0.1316)

0.1445 ***

0.01s0) 

-0.0523 **

0.0222)

0.0200 *

( O.oloq

-0.8772 ***

( 0.3045)

0.0506 **

( 0.0201)

0.000s

( 0.0059)

0.00ii

( 0.0107)

-0.4746 ***

( 0.0712)

0.0393 ***

( 0.0062)

-0.012i **

( 0.005i)
Appendix Table 3d. :

\Vage and Job Turnoy<g Residu~ Variance Components “ ,

Standard De”iiations md Correlations

\Vage Components Job Change

Trnsit General Job Specific

Initial Gro\vth Initial Gro\vth

YVage Components

Level

Trnsitory” .2632

(.0007)

General

Initial Level .2662

(.0062)

Growth \v/Exper. -.4994

(.033s)

Job Specific

Ititial Level

GrO\vth w/Tenure

Job Turnover -.0066..

xv/Exper Level \vjTenure

(Symetric)

.8763

(.0423)

.3070

(.0034)

-.54ss 4.190s

(.0165) (.6223)

-.1476 ...4922

h~ote: Blink entries are zero, except for symmetry “of correlations.

.

*

26