me National hn~mdid Sweys ~] proq suppo~ mmy stidies d~i~d

@ hcrme ~dersmtig of the labor makti md methd of dti m~~tion. me

Dkcmsion Popers series bco~omt- some of tie ~smch cotig o.t of the p-.

Mmy of tie papem in tis series have bea defivad m fmd mpo~ whsion~ %

pti of m extiwd gat pm-, mder which -s ae awmdd ti”gh a

competitive process. ~e series is inmded to cixtiam tie findings to inkrmti rders

wihin ad o“tiide tie Bureau of Labor S~tistiG.

Persons ktereskd in obtining a WY of my Dismssion Paper, otim ~ repo~,

or genmd kformation &out tie NLS program md swws should mntiti tie Bmw d

Nor S@tistics, Ofim of Wonotic Resflch, Wmhington, K 20212~01, or cd

@02) 606-7405.

Materid in tis p“bfication is in”the public domti ad, with appmpriam m4L

may be xprduced tithout pmission.

Opitions md conclusion exp=ssed h tis dmument we those of the author(s) ad

do not n-stily repment m o~cid oosition of the Bmeau of Mr Smtistiw or tie

US. Depment”of ~tior.
Incentive Pay, Information, and Earnings:

Evidence from the National Longitudinal Survey of Youth

Stephen G. Bonars

Carol Moore

University of Texas

Mach 1995

~s paper wm fundd by tbe U.S. Dep~ent of Labor, BBU of Labor 5mtistics un&r stil purch~e

order. me tiews exprc%d here ze tiose of the authas ad do not nwesstily reflect the views of the

U,S. Deptiment of Labor.
Abstract

W report studies tie rncidence of incentive pay and seleetion of workers into

incentive pay jobs, measures and compares the wage-tenure profles of incentive pay and

time-rate workers, and tests for hbor market disctiatimr in rncentive pay jobs relatie

to tim~rate jobs using the National bn~titid Survey of Youth ~SY). Workers in

this study are classtied as incentive pay earners ifthey reeeive either piece rste~ bonuse%

cohsions or tips. Each of these methods of pay are based on individud pefiormsnce

and may supplement a workefs typical *or wage.

A prknmy hypothesis under@g this study is tkat mofioring costs are rektively

low h jobs thst use incentive pay and base a workefs compensatio~ at least ti part, on

individud perfo-ce. Monitotig and information costs have been used to rationk a

number of empirical tidings, from the employer tie wage premium to positive returns to

tenure in wsge regressions. Mo&otig mat eWlanations of empirical phenomena are

typic4y unsatwg, however, because tkese costs are unobsewable to the researcher.

me incentive pay data m the ~SY provides the best opportunity to evatiate a number of

tiese tiormstion cost modek, by comparing wage-tenure pro~es, turnover, and

employer sti wage prenria (for workers* a obsewable charactetics) across

jobs with rehtively high and low monitoring costs.

me fist section of our study descnies rncentive pay earners and their jobs. We

are able to provides more complete picture of incentive pay workers than studies based

on estabfiabment dat~ such as the hdustry Wage Smeys. We fid substantial &erences

across categories of incentive pay. Commission and bonus esrnera tend to be weU

educate~ male, have high test scorw, md hold jobs that require substantial rnveatments m

education and trairdng. Rece rate and tip workers however, receive less education, have

lower test scores, and are concentrated m jobs that require fewer investments m training.
me second section of our study tests the monitoring coat e~hation ofpositively

sloped wag~termre pro~es, by comparing tie wag~temrre profles of incentive pay and

tire-rate workers. ti h~otbesis has been advanced by hzear, who wggests that

deferred compensation is a snbsttite for incenttie pay and more direct contemporaneous

monitoring of individrrd worker pefiormance. We fid httle evidence to wpport tie

notion that incentive pay jobs rely less on deferred compensation and tfied wage pro~es.

We fid that wag~tenwe proMes are steeper in jobs bat reqtie more ~S bonus and

commission jobs tend to have the steepest wage profles. Even affer controtig for these

job characteristics, irrcenttie pay jobs do not have flatter wage proties.

me hd section of our study examines racial and gender dtierences h tbe

incidence and amount of incentive pay. ti resrdts provide mixed evidenw in favor of

modek of both e~loyer and customer discrimination. Blacks are more Mely to earn

incentive pay in operator, fabricator, and laborer jobs than are whites. ~tics and

women are less Mely to earn incentive pay in sales occupation% and bhcks are less Wely

to earn incentive pay m customer-oriented seMce jobs. k contrast, racial and gender

wage gaps do not appear to ~er “srrbsttitia~yamoas incentive pay and timerate jobs.
Section 1. Who Earns hcentive Pay?

L htroduction

Employment relationships are marked by a wide variety of irnphcit and expficit

contrac~d arrangements which re@ate effort and docate workers awoss jobs and

employers. h most job% wages are expressed in terms of time spent on the job. k

wntrast, incentive pay mntra~s--piew rates, bonuses, mtiIons, and tips--base an

employee’s pay eWticitly on fis or her produ~ivi~. For this r~~ inuntive pay has

atiraded the attention of many emnomists interested in stidying the relationship between

wages and produtivi~. Empirid work b@ on estabhshrnent-level data sets We the

BLS kdust~ Wage Smeys ~S), has providd a pi@re of the marmfatiring

prodution workers who earn incentive pay. We exarnkre inwntive pay workers and their

jobs using data horn the Natiod Longitudmd Survey of Youth ~S~.

The NLSY is a panel data set mnsisting of 12,686 individtis aged 14-21 in 1979.

=orities and persons &om low inmme backgrounds are over sampled. The 1988, 1989,

and 1990 NLSY surveys askd respondents whether their pay was b- fiHy or k pm

on their ‘lob performance” in their mrrent or most rwent job. h -ch of these years

about 20-25% of the vtid responses were positive, a ratio mnsi~ent with that found in

establishment data (e.g., Sefler, 1984). Respondents dso identfied whi~h of the foUowing

types of pay they rmeived: piece rates, wmrnissio~ bonus tips, stock options, or

some “other” form of pay.

This report is divided into three ~tions. This ~io~ “Who ~ kcentive

Pay”, deseribes incentive pay aers and their jobs and compares them to time rate

workers and their jobs. Our god is to form a more complete pitire of incentive pay

workers than has tended to be possible using tie NS and other estabhshrnerrt-levd data

1
sets, fist, by using NSY data on workers’ human capiti, demogrsptic, and job

characteristics and secon~ by ex smining incentive pay workers in W industries and h

service, ties, and other non-production oapations. The WSY includes data on

workers under dsfinct pay systems: piece rates, commissions, bonuses and tips. We

examine each of these, and fid substantial dtierences in workers across the ~erent

types of kwntive”pay.1

Section 2 of tis report, “Do Motitorirrg Costs Explain Positive returns to

Tenure?’, @mpares tie wage-tenure pro~es of incentive pay and time rate earners in

order to test a monitoring costs explmtion for positive returns to tenure. hcentive pay is

ofien viewed as a substitute for defemed forms of compensation such m positive wage

tenure profles @ear, 197X Luear, 1981; tildq 19S6). ktintive pay systems

require fmns to accurately maure the quantity, and ofien the qu~ty, of kdividud

workers’ output. Tne rate wage or d~ systems require employers to mmure the time

workers have spent on the job. M else eqti, incentive pay systems such as piece rates,

bonuses, and commissions are urdikely to efist where the employe~s monitoring rests ue

hi@ (Sti~@ 1975; L==, 19S6). Tips are a possible exception: wtie they N pay

explicitly to performance, tie monitorirrg rests are borne by the customer rather than by

the employer.2

k Section 3 of this repo~ ‘hcentive Pay and Labor Market DlscrimirratioL” we

document race and gender ~erences in the incidence of incentive pay and k incentive

‘For d~d purpo%, resrarch has crrrphasired s-tics kfwccn irrwdve py system wtie

rm@~g tie Merences For example,~rar ~ &aemea tit ‘me fiportarrt fafure which

diti~sh= a piecersfefroma Wary k tha~witha piece rate, the workefs payment h a @m period is

rehcd to output irr * Pridn and tites, “Mrsmen who are paid on a strict m-on tis are

piece ratewmkem. _ mgers in majorw~rstions..nrsy ofrenreceiveatin-, thetie of which is

geared dirrcffy to~ h period’s output me hnu mmpnenf is ~chroti to outpu~ is flem%le,

and is essenti~s pi- rstqn w, 19W, p: “MT.

*titipstiOn in piece rati’”or coti on systems kp~ that the empIoyer can m- esch tit of srr

ti&tid@s outp~ Under bnm sysfex empl- may sinrpIy motitor performance w to a -Id

lev~ motitotig output tither&low or abe that point 1* clo~y.

2
pay wages, and consider our resuks in fight of customer, employer, and statistid

disctition. mere monitoring costs are reIstiveIy Iow, employers can base

compensation on objective meamres of a workefs output, rather than a supervisors

subjective assessment of worker petiorrnmce and a workeds time input. Therefore, we

expect employer and statistid discrimination to be less prevalent in incentive pay jobs

reIative to M@ monitotig mst time rate jobs. This impties that minorities shodd be more

MeIy to sort into incentive pay jobs and that rscid and gender wage gaps shotid be lower

among incentive pay earners than among time rate earners. Customer dlscriminatio~

however, irnpfies that race and gender ~erences in pay should dso vary witi tie amount

of customer mntact typical of the job.

Monitoring costs are a consistent theme of tis resesrc~ but their effects on wages

ad wage growth is easfly confounded with those of human ~iti. h~ monitoring wsts

may be associated whh more clmly defied ~ks and performance standards. kcentive

pay jobs, particuhIy piece rate jobs, may requke fewer SHS, permit Iess ~pe for

employee discretio~ and entd fewer inve~ments in general or ti-specfic human apiti

than do stiar time rate jobs. ~erencw in wage:tenure proties across incentive pay

and time rate workers could skply reflect variation in productivity growth human mpi~

and on-thejob trfig. SMsrly, dtierenms in training and s~ are centi to

~erenccs in wages between minorities and whites or men and women. The empirid

relationship between SW and training on one hand and incentive pay on the otier is

ambiguo~ however, because both the costs and benefits of worker monitoring are Mdy

to be high in jobs requiring more sWS.3 Us-mg matched WS and me Dictio~ of

OcmPtioM1 fifles data on produdion workers, Brown (1990) found that the probability

..

3BM~ (1990, p. 171-S) notm W “Mgh-tiu jobs am jobs h wM& WO* OQut k =titive to

~eren~ h worker qtity. ~W M@.H jobs shodd. bve greater benefit &om precise motitofi~

aad grater w of piece rates...” @ tie otier ti~ ‘when a-cy snd @& of work are @rtsntcbsrsctedcs tit are oflen but not n~y ~ted witi M Iw* (motitotig *) are ~dy to

be M@ and the usc of piece rater less comom ❑

3

.
of r-itig” incentive pay is inversely related to the degrm to wtich job tasks involve

diverstied duties artd a need to “gene&e, evaluate, and decid~” and positively relatd

to precision of standards. fis tidence supports the view that incentive pay jobs are

relatively less stied.

h our reswch we use ~SY data on the se~-reported trtig and experience

r~uirements for respondents’ jobs. The 1989 md 1990 waves include respondent’s

assessments of the duration and type of trsining-edudo~ previous qerien~, and

wment on-th~job training--rr4ed to fiUy master and q- for their jobs. bter in this

don we show that these -g experience requirements dtier substanti~y by method

of pay commission rmd bonus jobs are Wely to be more stied than piece rate or tip jobs.

h Sections 2 and 3 of this report, we condition our -gs equations on training

requirements.

~ Characteristics of heentive Pay Workers and Jobs

nom incentive Pq?

h tis sectio~ we describe the personal characteristics, schoofing, training,

-gs, ~d jobs of incentive pay earners. The sample fike d of those usd in this

repo~ excludes respondents who were seK-employed or working in the agricultird sedor

in their rarrrentimost reeent (CPS) job. The sample dso omits workers reporting notid

hourly wages exceeding $100 per hour or less thmr $1 per hour in their ptiary job;

workers reporting wage changes larger than $50 per hour in absolute value over adjacent

y-s; and workers who reported earning “other” forms of kwntive pay W

mmrnissions, piece rates, bonuses, and tips. Bemuse our focus is on workers paid by

individu~ as opposed to group incentive pay plans, workers who reported -g stock

options were clsssfied as time rate workers.

4
Table 1.1 presents sample means and standard deviations for the 1988 sample, for

wkich there were 5567 vtid observations. Respondents were claasficd according to heir

method of pay status in 1988 (dfleren= in the 1988 cross sections and those of 1989 or

1990 were ne@gible). Workers who reported -g piece rates, commissions, bonuses,

tips, or multiple forma of incentive pay may have been co~ccting part of thek wage k tie

form of time rates, wortig under a system in which part of their wage was based on time

kput and mother part baaed on the vrdrre of their output. The NSLY data do not

distinguish between tie and incentive pay earnings. 4 The ~ column of Table 1.1

shows descriptive data for workers under multiple incentive pay systems. Mtitiple

incentive pay earners C1OSCIYresemble bonus earners bwause moat workers in this group

reported e-g bonuses along with other forms of incentive pay.

Previous research h= uncovered some common characteristics of incentive pay

mers and their employers. Brown (1990) and Glti (198~ found that women are

more Wely to pdicipate in incentive pay systems or - piece rates than are men.

~ldii argues that if women have shorter eq~ed job tenures thm m% employers

shouId assign women to morritorable jobs and offer kcentive pay in fieu of deferred

compensation. Table 1.1 indicates that women acmunt for 420/0 of incentive pay earners

and 48% of time rate earners. However, women dominate the piwe rate and tip

G m— of eandngs k an ~SY-ti *Ie, ‘homly rate of pay. ” That no &tiction k made

beween time rate and P ssrrdngs led us to _ tit ~ mrn~ might aystenratidy rmderataterheir

*8s~@)W-8Stiy fluctuate moretbao bssetierstaeandngS arrdnotbs~

remembers and (E) some forms of P, mch as hn-, maybe ~sb~ at irre~ar titetis and not

considered by the ~ndent to k a basic @ of conrpe~tirm snd (i) tip m= are h cash md may

stiply k rmde=prtd To chd for this Poasfiflity, we computd an dtemstive m- of average

hourly *SS from an MSY qtion h wMch respnndenta were ~ked to ~rt totsf annti wge and

dsry bcome including *SS hm conrndWo~ tipq andpresumably, other forms of F. This figme

m divided by the ntir of hours worked in the reIevsnt mfendsr y-. The resrdt wAGE~C) m

comparedto the~SY hourly rate of pay ~) for each r~ndent fn 1989, the mean of WAGWC -

W was31.7 centsfor sff W -era and 47.3 omtafor time rate -era, su~esdng tit P -era do

not have a systematic tendencyto md~ts theti *SS relative@ time rateearners. k fix for tip

and pi= rateworkers,~ mtiaten~ m- WAGEWC on average.~s patternemergeswhether

or notthemple k -ctd to thw holtig mdyonej& in therel-t dendar y=.

5
categories. Plwe rate earners have the longest tenures on avers= 3.28 years, mmpared

to 2.99 years for tie mers and 1.97 years for tip -ers.

Estabkhment stie has been central to numerous labor mrrtract models based on

motitotig mst$ large employers face relatively hia costs of monitoring the output of

individrsrds (Cdvo and WeUx 1978; Oi, 1983; Osre% 1985; Bulow and Summ~

1986, Sti@er, 1962).. “The data in Table 1.1 show that incentive pay. is concentrated in

smd to medium shed estsbfishments-those employing fewe-r than 50 peopIe. h mntrss4

x...!..: .

time fates are skewed tow~d relatively large estabfishents. Piece rate earners, 4% of

,..,. . .

whom work irs estabfishents emplofig “’200’ or more people, are an exception” to. tbia

.,. ..

pattern: ~t pi=’ rates should be more mmmon among large employers, who

presumably have a cornpara~ve disadvantage in monito~g the output of individgds, is

irriti~y surprising. How&e~ Bro& has proposed that estabhent sti should be

positively mrrelated tith the use of incentive pay because large pl&ts have-lower average

costs of adrninistetig eqcnsive payment systems. This effd, Brown argues, outwei@s

the greater .dMtity of monitoring indi+dud perforrmmce ti” Isrge estabhshm:nts. h @s

tests using the NS data for selected msntiacturirrg industries, Brown found a positive

,,.. .... .... . .

mrrelation be~&p Zn@’rnpltiyment). ~d”the Lcidence of incentive P~Y ~ both don ~d

. ....7 “.

rionunion plants.

. .

. . .

BIacks atiunt for fou@y ,~ud percentages of incentive pay ruralt~e rate

-ers, but notile .&cid ‘@erenws etist by type of ticentive pay ody 16”A of

..

,., ,

co~s~on workers,: ~9-~rioftip “&er+ and 2Y/o’ ofpiece rate workers are black. These

unconditiomd means are consistent tith the view that bIack workers can seek out

incentive pay to cucumvent .emplgyer oc Statistid ~sc*tio% but nevefiel~s ~

customer discrimin ation in ti~ssion or tip -g jobs.

We e~ect workers whose wages are governti by muective bargaining

. .. .,, .:.:,..,. ;, -,. .4;,’:,,. . . -:,.....

........ ..,,~,,.. .<, :,

agreements tobe !esi ~ely to’ ~. iricentfi: Pay - we.?onutioriiirk~rs:, x.u+ovs E?ve 1.

.

6

.,,

. . ..

,.
traditiondy opposed the use of piece rates ~tche~ Lewirr and Lawler, 1990). kcentive

pay systems based on individud petiorrnance a undtie sofidsrity and negotiated

work rules may create undesired variation in workers’ inmmes. Brown fids that union

coverage or membership is aswciated with a grmter tendency to use seniori~-based pay

systems. However, unio~tion bore an insi~cant relationship to P in d of Brown’s

tests. Table 1.1 shows the highest uniofition rates in piece rate jobs, but Iower union

mverage in W other in=ntive pay jobs relative to time rate jobs.

R~dcnw in an SMSA is e~cted to raise the probability of -g tips or

commissions because these systems depend on the potential to mntact a large number of

spending customers. For the same r~~ higher lod unemployment rates should rduce

the attractiveness of tip or commission jobs. Low Iocd unemployment rates may dso

raise the probabii~ of -g bonuses if bonuses represent a form of profit sharing

during good times. Nterrmtively, tis may offer bonuses, instead of or rdong wit~ fied

wage incr-es in order attract employees.5 h Table 1.1, 85-860/0 of tip or mrnrnission

workers reside h SMSA’S compared to 78°/0 of time rate workers and ody 68°/0 of piece

rate workers.

Abtity and education are Wely to be important to workers’ choi~ of pay system.

LZW (1986) showed that high-abfity workers til ~avitate toward “piece rate” systems,

wtie those of low or average abfi~ prefer time rates. Workers who are ~ceptiotiy

productive withkr their occupations can raise their tigs working under pay systems

which base compensation on current-period productivity rather than on time hput or on

the average productivity of a class of workers (e.g., with identid dumtion or other

observable traits). That hccntive pay workers maybe of higher abiity ia supported by the

positive estimatd inmntive pay wage prernia found in wage regressions which include
mntroIs for ompatiow irrdus@, regiow estabhsbment ske, md sex of workers (Seder,

1984; Pencavel 197Z Mtchefl, Lewin and Lawler, 1990; Peterso~ 1991). Table 1.2

gives mean raw WQT scores, percentdes, and age-adjusted reaiduds6 for the sample

classtied by method of pay in the currentimost recent job in 1988. A strmdard m=re of

abfity, the ~QT is a general cducationrd aptitude test for screening potential dtsry

entrants @erk and S- 1988). The test was administered to the ~SY -pie in 1980.

D@erenms in measured sbfity shown in Table 1.2 are pronounced. Workers in

comrnissiom bonus, and fitiple incentive pay jobs have notably higher MQT smr= than

do time rate workers but piece rate and tip workers tend to have lower scores.

Cormnissiow bonus and multiple incentive pay earners mre in the 46th to 48th percentiles

on average, wtie tip and piece rate earners =re in the 40th percentile or lower. The

average time rate mer scores in the 41st percentie. These unconditio~ mm ~QT

scores mggest that high sbfity workers sort into arnmission and bonus systems, but shy

away from piece rate and tip jobs. The observation that piwe rate and tip workers appa

less able than time rate workers contradicts some of the predictions of monitoring wst

incentive pay models. lt is Mely, however, that dtierences in ompationd SW

requirements are responsible ‘for the large dfierenws in ~QT scores across method of

pay.

Taken as a group, incentive pay -ers are mar~dy bctterducatcd than time

workers, but m- cducatiod attainment dflers mwkedly by pay mtego~ cotission

and bonus earners have over a yds more educatiom on average, than piece rate workers.

We the education attainment of tip”-ers does not dfler from other workers’, 11%

were enrofled h coHege in 1988. h contrast, ody 5.10/0 of M hcentive pay workers and

7.9A of time workers were emo~ed in co~ege. The relatively large incidenw of muege

a
mokent among tip -ers may e~lairs why they work ordy 35 hours per week on

average, approtitely 5 hours less per week than the oved sample.

We estimated a multinotird lo@t -) model to su~ e the relationship

between the kcidence of irrwntive pay and worker and job charaderistics. Resuits shown

in Table 1.3 condition method of pay status on o-patio% human capi~ age-adjusted

AFQT residuds, and estabtistient characteristics. Tne rate earners formed the omitted

group. Respondents who reportd earning multiple forms of hcentive pay were achrdd.

The model reported in Table 1.3 does not include mntrols for industry. Adding 2-digit

industry dummies to the model has a ne@gibIe effect on the results.

Are higher tiity workers more Wely to sort into incentive pay jobs? We focus

on ~QT residuds and ducation as mmres of worker abiity. Urdike the unconditioti

m-s, the - results indicate a sificant pwlive mrrelation between tip *gs =d

MQT. The ~QT scores of pi- rate and mtission workers are not si~candy

d~erent from those of otherwise identid time rate workers. The AFQT residud aerts

no independent tiuence on the incidenw of commission work. However, edumtiod

attainment among commission earners is relatively high (13.4 y-s, vs. 12.9 years for time

rate earners). Education is’ a si~tit dete- t of wdssion *gs, but is

insificant in the other method of pay qrsations.7 Bonus workers are no more educatd

thm are other workers on average, and have less e~eriesr~ but have si~=tiy higher

~QT scores. Taken together, the estiates suggest that high abii~ workers tend to

work under bonus, cotissio~ or tip ~sterns within their occupations. There is no

7G1vm that studerns are UeIy to have short= ante ~ti job tenures snd to desire flmile mg-hom

mnrra~, we_ rmrohent *tus to be a si@- prsdicror of tiundve pay. M turned orn b

k the case for tip rarners. For other ~ups, combimtiom of enrolhnent dtirs for M@ school

@us@ M@ =hml -timt mUeW ~d~te, md @Ue& enroti wre not si~- ptidoss

of ticmtive pay.

9
evidence that pi- rate workers are of greater abfity thsrr tie rate -ers irr the same

broad occupation.a

Residence in an SMSA si~cantly raises the probabtity of tig commissions

or tips, but has no si~cant effect on piece rates or bonuses. This is not surprising given

that the number of potential customers is MeIy to be Iarger in an SMSA than outside of

one. The Iod unemployment rate is si~csnt ordy in the bonus equation. hcd

unemployment rates of less than 3°/0 are associated tith greater incidence of bonuses.

&nder and race are consistently si~cant detemrinants of method of pay.

Women dotiate pi= rates and tipq meq mmmissions and bonuses. That women are

more Mely than men with the -e human capi@ working in the -e broad occupatio%

to earn pi- rates is consistent with @ldm’s model. However, this prediction shordd

apply to any job in wtich morritofig costs are relatively high and anscquently the use of

deferred mmpensation is relatively low. Blacks are significantly more Wely than nonblacks to earn bonus=, but less Wely to earn tips or mnrmissions.

The mapping be~een - estimates and predicted probabfities _ot be

discemd by relying solely on the inefficient estimat=. Table 1.4 gives the prdlctd

probabilities of bg piece rates, bonuses, commissions, tips or time rates by race and

gender, etiusted at the m- values of d other explanatory variables, using the -

estimates in Table 1.3. Time rates are predicted for 79-82Y. of workers. Men are more

Wely than women to earn incentive pay of any me, espw~y bonuses and commissions.

White women are pr~ctd to have the gr=test probabtity of earning piece rate&+.YA,

over twice the predicted rate for white men. Black fermdes have the lowest chance @r=

.01~, md white males the largest &r= .045) of earning conmrissions. Tips are relatively

rare, ordy about 1-5°/0 of the -pie is prdlctd to earn tips. Tlp-hg is
overwhebnirr@y fede. .Womm of any race Me more than tim as Mely as thek mde

counterparts to - tips.

The ~ estimates indicate that plant she and tiotition are inversely reIated

to the probabii~ of-g mmmissiom. The incidence of tips is dso reducd as plant

ske rises. The WeMood of earning pi- rates and bonuses is M1@mtly related to

plant stie and uniotition. It is possible that as estabfisbment stie increases, the rising

costs of monitotig piew rate and bonus workers are offset by lower average fied CO*

of adtistering the pay systems. Commission systems, however, are si@cantiy more

mmmon in sm~er estabtishrnents.

TabIe 1.5 shows tie prdltied probabfities of -g tie rates, pi=e rates,

mmmissions, bonuses, and tips by estabhshment sb mtegory and utiotiIoL holding

M other chara~eristics mnstant. RegardI~s of siie or union status, workers are far more

Wely @r =. 78 to Pr = .85) to earn tie rates thsn any other form of compensation. The

probability of earning mrnmissions, tips or bonuses P* in nonunion e~tisbrnmts

employing fewer tb 10 employees @r = .045, Pr = .028, andp~.116, respaively). ~

contms~ tbe probabfity that an employee in a tiniotid plant employing 200 or more

workers earns mmmissions is less than .01. The predltied probsbtity of earning piece

rates ranges horn .024 to .029 and rises with establishment ti and uniotition.

Training &Incentive Pq

Wages and on-tbejob wage growth are functions of workers’ pr,tious and current

human capiti investments, which sin= ofien info- are ofien @colt to m-e.

kmntive pay jobs may dtier horn time rate jobs with resp@ to sti level and type rmd

duration of training needed. h partiwlar, the low monitoring wsts of incentive pay jobs

m~est that tasks may be eirmmtibed by the employer, permitting less smpe for

ernpIoyee di=etion and desision-msking. Many of the vtiab[es which play a sifi-t

11
role k dct-g methd .of pay may by correlated with job SW training and

experience requirements. This is sknost certainfy true of abiity, and is tikely to be true of

gender as we~. For example, ~onau (1988) documents women’s’ lower rates of

participation in a variety of job training progmms.g

SeK-repofied trtig and experience requirements for workers’ currentimoat

recent jobs are avaikdrle in the 1989 NSY.lo TabIe 1.6 surnrnties sti-reported

estimates of months of experience required to become “my trained and qudied” for the

currentimo~ recent job. There is no overd tendency for inwntive pay jobs to rquire less

exptience than time rates jobs. Commission and bonus workers rquire more experienw,

and piece rate and tip earners Ieas experience than do time rate earnem.

We extie the relationship between the SM requiremenfi of ajob, ticentive pay,

and worker charatienstics by estimating OLS and censord regression m.odeI of these

experience requirements. The results, reported in Table 1.7, rtiorce many of the

patterns emer@g from Table 1,6. Contiotig for occupatio~ seL job tenure, messurd

abifity, establishment stie, and other factors which are ~iely to affect the Ml intensity of

jobs, bonus workers require more months of e~erienm, and tip workers si@ficsntly I&s,

than time rate workers.

TabIe 1.8 gives the. percentage of workers indicatkg that particular types of

trtig were rquird for their jobs by method of pay. ~ormaf on-the-job trtig and

company training programs tith the present employer may represent either gened or

ti-spectic trtig. The average piece rate or tip -er requkes less training of any

type than does the average time rate worker. h mntrss~ commission and bonus workers

.

.

‘A Grensu show, whetier worna’s shofim j& tenures ad punctuated labr bet -W are a caw or

~~~n~ Of 10W &g investment k fi from tious. We & not titend to addr~ tis “chi&en

and egg” PM1-

1me WY W tiIudea a yearly fle on -g program @cipstion ktween irrteMm. We choas

not m use tieae &ts ~ hey ernptii fonnsf training pro- while ne#ecdng infod On-thej& -g =d ptiom e~ence. ~ shortcoming of be 1989 data we use is tit it provi~ no way

of m- g tie dursdon of tie tig pm= w~e tie snnti pmgranr data do.

12
required more trtig of any type (other than apprenticeships) in tieir jobs. These

unadjusted means suggest that training r~uirements &tier markedly by type of incentive

pay, with piwe rate and tip jobs rquiring relatively EttIe training, time rate jobs r~uiring

moderate amounts of training, md commission and bonus jobs requiring Substmtid

training and experience. Ag& it is Wely that these dtierences reflect the concentration

of tie various forma of incentive pay in occupations of varying sm.

Table 1.9 di-egates the training data by l-digit occupation and by incentive

pay -s. k d occupations but service% incentive pay workers are relatively more Wely

to indicate hat formal company trtig was a job perquisite. ficentive pay earners in

ties and production CA and repair occupations were more Rely than their tim-tig

counterparts to report the need for on-jobttig with the current employer. kcentive

pay earners were rdso consistently more MeIy to indicate that ~erience with a previous

employer or trade, technical, business, or vocational school was neces~ to obtti ticir

jobs. With few exceptions, incentive pay workers in any occupation are either more Wely

or just as Mely as time rate mers to report that a given type of &ng was required.

There is no tendency evident in Table 1.9 for hcentive pay earners to be less extensively

trained.

Problt estimates for selected scE-reported training rquirementa are given in Table

1.10. k Cohmm 1, we estimate the probabii~ that special of ~erience of any ~

~ichrdmg apprenticeships, armed forces trti~ trade school, formal company training

on the job training with a current employer, on the job trtig with a previous employer)

k requird on the job. Commission and bonus earners are si~catiy more Wdy than

time rate earners to report that some form of special experience was rquird fir their job.

Pime rate and tip workers did not d&er &om time rate earners. However, time groups

were si~-tly less Wely, and commission and bonus workers were relatively more

Wely to report that participation in a company training program is nmes~ for their job

13
(Column 2). Piece rates ad tips had no si~cant btig on tie probabfity that current

or previous on-the-job training was requird (columns 3 and 4). Note that much of tie

dflerence between the condition and unconditioned relationships between incentive pay

and on-the-job training can be attributed to gender dfierences in both method of pay and

training. Females are si#canfIy more &ely to - piece rates and tips, and are much

Iers Wely to hold ajob which requires on-the-job trting.

~ Conclusion

The economics Eterafure on morritofig costs and wage contracts has tended to

emphaske a sin~e underIfig characteristic of incentive pay: incentive pay systems base

compensation on the vahre of output produced, rather than on time input. Our resuIts

indicate that substantial d~erences etist across types of incentive pay as we~ as between

incentive pay and time rates.

Relative to time mers, eomsnission and bonus earners have higher test smres and

are predofiately rode, wefl-educafed, and Mely to hold jobs that require substantial

investments in education and training. These workers spend more time becoming trained

for their jobs and are dso more Mely to report that frtig gained with either the current

employer or elsewhere were required for their jobs. M eIsc equal mnunission jobs tend

to rquire fo~ company training, wtie bonus workers report the need for current and

previous on-the-job ttig as we~.

Several key &eren@s etist between bonus and @nrmission workm, however.

Behg black rduces the Welihood of -g commissions. Commission workers are

more Wely than time earners to work ins~ nonunion plant$ and to reside in SMS&,

these patterns are abserrtamong bonus -ers.

The data ptit a @erent picture of piece rate and tip workers. Piece rate workers

tend to have somewhat lower test scores th~ the rate workers to be less weti-educated,

14
to hold jobs that involve relativdy s~ srnoonts of trti~ and to be prdotiateIy

female. TIp earners display stiar job cktieristics-+thetiae identid time rate

workers tend to invest more time in training than do pi= rate and tip earners. However,

tip ~ers are Mely to be of bigber-tti-average abfity titi their ompations md to be

esrro~d issschool.

15
Section 2

Do Monitoring Costs Explain Positive Returns to Tenure?

I. Introduction

That wages hcrease with job tenure in both cross-section and panel data sets is a

weU-established empirical fact @ orjas, 1981; Mncer and Jovanovic, 1981) subject to

numerous competing interpretations. h impotit explanation for rising wage-tenure

profiles centers on the costs of regulating and measuring employee performance

employers may use deferred compensation and promotion ladders to deter employee

malfeasance given high monitoring costs and incomplete information. men monitoring

costs are low, employers are hkely to implement incentive pay (~) systems -- piece rates,

bonuses, commissions, and tips -- and base a worker’s pay explicitly on hdividud

performance and not merely on his or her time input. Because jobs that offer incentive

pay (~) are expected to have relatively low costs of monitoring worker pefiormance, they

provide a means of testing’ ttis incomplete information model of rising wage-tenure

profiles. If monitoring costs account for some of the returns to setiori~, earnings of

incentive pay workers should grow more slowly on the job than time rate wages or

salarim. This paper assesses the role of monitoring costs in isrtemd labor markets by using

data on method of pay available h the 1988-1990 National Longitudinal Survey of Youth.

Laxear (1979, 1981) showed that employers may comtine positive wage-tenure

profiles with the threat of dsmissal in order to prevent employees horn sfirtig on the job

when monitoring costs are &gh ....Gven imperfect information about worker pe~ormance,

wage grotih may exceed pro~uctivity growth on the job. Employees post petiormance

bonds at the be~nnisrg of a job, which can take the form of wage payments that are

16
irritiy below the workefs value of msr~ product.11 h later y~s, wages are ptid in

excess of the vahre of marginal product. ~us, a Substitid fraction of a workers’ return

to effort may be defeti~ to fiture periods. Workers who shirk are distissed and,

consequently, forgo the expected present value of the excess of heir wage over their

~@ produ~. pefio~ce bonds ~d “tit~” wage pro~ea ~ be designed such that

ody workers who place a considerable vrdue on current-petiod leisure @ shirk.

Workers agree to this contract because deferred payments deter shirti~ raise the

overd output of the enterprise, and in turn incr-e the value of pa~ents that can be

distributed among employees. .Hgher returns to effort are purchased at a rest, howevec

the deferred payment contract entds the risk of h d~ce. Site workers are

eventiy paid wages in excess of their msr~ products, the employer has an incentive

to violate the contract by laying off older workers or by perrnhting their wortig

conditions to deteriorate. k kds mod~ the optti wag~tenure profle bdsrrm the

risks borne by both paroles, given expected retirement dates, exogenous preferences for

leisure, exogenous bushess risks, and worker and firm rates of time preference.12

There sre a number of dtemative explanations for the observed positive

relationship between wages and tenure. First, employees and employers may share

irwestments in ti-sp~c human capitak wages rise with tenure because investment

costs are shared dufig the trfig period and investment returns are shared subsequently.

h mntrsst to”the incomplete tiormation modd, wages are expected to grow more slowly

tian net productivity given shared sp~c tivestmenw, initial wages are MeIy to be higher

than the “spot” value of rnargind product so as to discourage quits @ecker, 1962).

Wages may dso rise with tenure because information about the qu~ty of a job match is

11ne hentive tim ofhmg xhemes were & expIored @ -a snd Sti4er (1974).

12 M&S & ox of A models k wMch positive returns to tenw a &se from timplek or

~e~c tiO_tiOn. = order tmrmsmen@ ti wtich emplq~ r- kdtidtis h terms of

@eu perfrmrrsnm relsdve to thti peers’, tise when emplqers carumt measure the output of individd,

but are able to rank thti perfo-~ (see, e.g., Wwnrm& 19W, pp. 499-500).

17
revded slowly over time. Wages adjust to new information about nmtch qu~ty over

time, and good matches persist wMe unproductive matches are terminated by either the

empIoyer or the worker (Jovanovic, 1979)13.

we Several competing theories cars e~lairs the stybd fact tht wages grow

with tenure, they are dficult to distinguish empiri~y @utcherrs, 198% Qem 1988). It

has been dficult to assess the reIative irnportanw of human capita rnatctig and

asymmetric Morrnation in the generation of positive wage-seniority proties because

worker productivity, match qutity, and ti-specfic training-- which are central to these

models -- are typidy dficult to obsme. Models of wage growth based on asymmetric

tiorrnation are capecidy eIusive because data pertaining to the amount and effectiveness

of supetiso~ inputs are not rmtiy avdable in standard data sets. For most jobs,

researchers know fitie about the quantity and qti~ of empIoyera’ information about

worker pdorrnance.

The empirical tests in Ws paper are based on the hypothesis that problems of

impefiect information about worker performance are less severe where incentive pay is

offered. Wage-tenure proties are more Uely to track productivi~-tenure growth in

incentive pay jobs, and deferred compensation @ be used more frquentiy with time rate

wages and daries. Therefore, a comparison of wage growth on the job across incentive

pay and time rate workers measures the tient to which employers “tfit” the wage profde

in the rate jobs.

The paper proceeds as foflows. Section ~ briefly outies the empirical prdctions

of monitotig mst models of wages and wage groti in @ md time rate jobs. Section ~

describes the data. k section W, we describe some empirid issues associated with
m*g incentive wage growth. Predictions of the monitoring cost interpretation of

wage growth me tested in section V. Using 1984-1990 wage and tenure dat% we track

the earnings history of each workefs primary (currentimost recent) job in 1989. The ~rd

section provides some brief mrrclusions and suggestions for fiture research.

~ Monitoring Costs and Wage Growth

FoUowing Lucar, we hypotfreske tht deferred compensation ~.e. a steep wagetenure protie) is a substitute for &cct @ut costly) monitoring of workers.14 hcentive

pay is urdikely to ocwr when the rests of me-g employee output are high (Sti@Z

1975). h mch of the ~ systems @peal in this paper, tith the possible uception of

b~nuses and tips, workers are rew~ded for individti rather than team output. The job

performance of tip and commission workers is ‘monitored” by customers, and tip earners

are actually rewarded by customers and not tie fim

Luear (1979, 1981, 1986) defies piece rates as any payment scheme--tips,

commissions, etc., h addition to forrnd pi= rate schemes - in which a worker is my

paid at the end of the period for work done tbt period.ls Such a payment scheme, he

argues, is a substimte for a back-loaded deferred payment mntract and generates a distinct

wage pro~e:

19
empirical predictions: ~) the wages of ~ earners ~ow more slowly and more variably

.

16

.

However, Bishop ‘~1987) repo~ etidence hat wpetiso~ wrduatiom are both tigMy mbjective and

imccute.

20

“When piece rates are used, the resulting age-etings profile is flat because piece

rates are a substitute for upward-sloping age-earnings profiles. Thus, salesmen should

have less steeply rising profiles than should m~agement employees.” Qazear, 1981, pp.

618-619).

Deferred compensation and steep wage-tenure profiles are unattractive to tis

(and to their employees) that face low costs of monhotig kditidud worker pefiormrmce

duectly. These tis are Wely to tie employee compensation more closely to their (more

reliable) information about worker performance. 16

Fms that face relatively high

monitoring costs obtain less (and less rehable) ifiormation about worker performance, and

are more fikely to use deferred compensation to ensure worker performance.”

We inte~ret the presence of incentive pay as indications that the employer has

accurate tio”tiation about worker petiormance and uses W to encourage the optimal

employee effort and to efficiently penatize stirking. b a pure ~ system shirkers are not

dismissed, but instead simply earn less. Thus, ~ can produce a harmony of interests with

respect to effort supply. Deferred payments arise when employers don’t directly obseme

individual output, or, equivalently, the discrepancy between actual and optimal output:

Piecertite workers are, in a relevant sense, seK-empIoyed. If it were cheaper to

observe that shir~g is positive than it was to determine the precise amount of shirking,

the contract which dismissed all workers would dominate @iece rates). The widespread

etistence of ml- which require the dismissal of s~rkers is testimony to me=”urement COSt

dtierences. (A worker caught sleeping on the job is usually distissed rather than docked

for the hours slept. Embezzlers find themselves without jobs when caught rather than with

a smaller paycheck for the month.). @=ear, 1981, pp. 614-615.),

The deferred compensation model generates some refitable predictions for wages

and wage growth. Moreover, incentive pay earners constitute an exce~ent control group

with wtich to test these predictions. h this paper, we extie two of “L-tin@’s. (1981)
thasrdo those of time rate earners, and (i) estabhshrnent skewage effects are tower for

~ earners than for time rate earners.

We fist compare the wage gro~h patterns of incentive pay earners, for whom we

expect monitoring costs to be low, to the wage growth patterns of wage-salary earners,

for whom monitoring cosw are expected to be relatively high. The main prediction of

L=eds model would have empirical support if wage-tenure pro~es are flatter for P

earners than for otherwise identical time rate earners.

In the first chapter of this repo~ trting and experience requirements were

shown to depend on method of pay commission and bonus jobs are likely to be more

ski~ed than time rate jobs, while piece rate or tip jobs (Tables 1.6-1. 10) are less sMed.

Because wage growth can reflect an employee’s returns to a pretious humarr capital

investment, we condition on training and education requirements before comparing wagetenure profiles across workers and jobs.

Comparisons of wage-tenure profiles across W and dme rate earners are subjecf to

the caveat that differences in these pay systems can induce sorting of workers. across jobs

based on their preferences and opportunities.. For example, Q contracts are ~iely to

subject employees to greater income risk than are time rate wages and salaries (Sder,

1984 Stight& 1975), Thus, more risk averse workers are less hkely to choose an P job,

and workers with greater financial wedt~ who are more wilkg to accept fisk in their

labor earnings, would be more Kkely to accept an W job. 17 Moreover, Ndebuff and

Zeckhauser (1981) show that long-term imphcit crrntracts which shield workers from

income risk also generate wage-tenure profiles that are steeper than productivity-tenure

1 ‘hds model generates no CIW prdction about tie di~b”tion of risk preferences across wge

stmc~es. On one ti~ WS mtiel prticts tit P is ~ely to be wed when production involvm a

large “luck” componen~ suggesdng hat risk lovers choose P jobs. On the otier han~ deferrsd

compensation entils tie risk of firm defauft in later years, suggesting that risk lovers shoufd prefer those

jobs M=d. For e~ple, Lzear and Moore ( 19S4) develop a model h which a seK-empIoyd agent is

more risk averse than a sdtied employ=.

21
proties. Thus, workers with relatively flat wage-tenure pro~es may simply be less risk

averse tharrother workers.

The second empirical prediction of the model we test concerns the relstionsbip

between estitishment she and wage-tenure proties in ~ and time rate jobs. Hutchens

(1989) md others have wgued that large empIoyers are more Wely to offer deferred

payment contracts. There are two major reasons for this prediction. Fust, deferred

payment enttis the risk of h “defadt” in Mer ymrs of workers’ tenures. Large ti

are better able to diversify against risk and are in a better position to honor long term

wntracts and insure empIoyees than are smder, more vubremble employers. Second, the

tiormation impda”mrs which give rise to deferred payments maybe more pronound

in large estihshrnents (StigIer, 1962; Oi 1983; Bulow and Summers, 198@.ls Tkis

suggests that returns to estabfisbment S* should be lower for P workers than for time

rate workers, condition on tenure, and that the wage growth of E workers shodd be

insensitive to etifishment sbe compsrd to tie rate workers.

The tests of hds model proposal here are among Several which test models of

asymmetric information in the labor market by identi@g jobs in which monitotig costs

are Wely to be smd. L=ear and Moore (1984) argue that because agency problems do

not beset sef-employment, the relationship between -gs and eWenence should be

fitter among the sek-employed than among employees. They tid that tig=

aperien~ pro~es of the se~-employed are flatter than those of wage and srdary workers.

Sitiy, Hutchens (1987) fids that workers in repetitive jobs have Iower returns to

seniority and are less Mely to have pensions than are those holding more compleA bardto-morritor jobs. @ldm (1986) ~ed reductions in monitotig co~s to the payment of

piece rates and the growing feb tion of certain occupations around 1900. Brown and

Howwer, mrnp=
Medoff (1989) have used establishment data on individud perfo~ce-basd pay to test

the morritorktg costs e~lanation for the establishment wage premium, contrary to the

prdlctiom of the monitotig costs argument, P esmkrgs were found to be even more

sensitive to estsbhshment ske th= were tie rate wages. FMy, some supprt for the

,.

deferred compensation modeI has been provided by Medoff and Abraham (1981) who

found that ~erences h the performance ratings of workers at a hge h e~ltid

d~ dtierences less rehably than did seniority.

~ Data

We measure wage ~owth using 1984-1990 wage and tenure data for each

workeds ptiary (currerrtimost recent) job in 1989. The sample was cofid to

respondents who ~) were not se~-employed in their currentimost rmnt job, ~i) were

employed k the non-agricultural sector, (i) reported average hourly wages between $1

md $100 in their currentimost recent job, fiv) reported hourly wage changes of less than

$50 in absolute vahre in consecutive YWS, and (v) reported vtid 1989 vducs for the

vtiables fisted in Table 1.1.

Bemuse it conttis large samples of incentive pay workers in conjunction with

detded data on their persod characteristics and work histories, the NSY is we~-suited

to tests of the deferred compensation model of wage growth. However, the id~ data set

for testing the model would consist of employees of W ages and a wide distribution of job

tenures. Most empirical research on deferred compensation has rehd on ssmpl= of older

workers with relatively long tenures at their fis @utchcns, 198& Hutchens, 198~

Medoff and Abhrah~ 1981). It may be argud that the tigh turnover ~idy found

among young workers is inconsistent with the long term employment relations wfich

Lu@s model predicts. However, there is no r-n to beheve that the underlying

mectims by which these relationships are estabfishcd are irrelevmt to the early p~s

23
of a workefs career or tenure. The main dtierence between this sample and samples of

older workers is that the former are posting bonds with their employers whUe the latter are

coUecting returns to bonds posted wfier. L~ds modeI predicts that older workers are

paid above the vrdue of their mar@d product wMe younger workers are paid below it.

Wage vfiation among workers of both age goups - potentially be explaind in terms of

tis model. When young workers leave jobs, it need not imply that they did not participate

in the type of wage-ladder whemes which distinguish the defemd W.mpensstion model.

Mther, turnover can reflect a young workds rejection of one employefs wage-tenure

contract in favor of rmothets.

N. Wage Growth Patterns

Measuring the wage grotih of incentive pay mers is comphcated by the

observation (e.g., SeHer, 1984; Sti@@ 1975; &w, 1981) that the *SS of

incentive pay workers are subject to more variation over time than are {irne rate earnings.

Because ~ ~ers’ output is subject to changes in luck demand and productiti~ shocks,

and other factors beyond workers’ control, their -rigs and earnings growth may display

marked fluctuation over time.~g h contrast, the time rate workers’ pay may be insured

against many of these fluctuations. Thus, mwwement of relative wage growth over any

short period of time may be unrepresentative of a workefs typid wage-tenure pro~e,

depending on the yas over which wage growth is m~rd.

1%e high wage ace prrdicted for W workers can be j-ti in two ~. F- the conqt of tie

_gs W%- that “tie WOrkem’inwm= ~ insensitive to tie vsgari= of the p[tiution pm ad

sbofi-mn fluxtiom in ds-V (Seifer, 1984, pg. 364). -n~y,k=(lg81, pg. 61~ UgUSS @t

pi- rate schcmrs W be offered when output depends si~mntfy on a mdonr variable, “luck”, which

is indisdn@shsbIe from effom ~ rmmn is tit %th dtierred compensstio% a worker who ewrienm

a M dmw is ~ although it tid & efficient to * ti _ states, ‘1..pi- rates ti & foond

not mdy b -tiom where ouq~ is messnred more ch=ply, bnt dso h mpsdom wtich have a

Imge luck compnent ~ed tirh a given indvidti’s variation h ou@t over tie.”

24
Table 2. I shows real wage growth on the 1989 curresrtimost recent job over the

years 1984-1990 by method of pay for selected crdendar years. Respondents are classfied

according to their method of pay status in 1989.. The number of workers represented k

each cefl differs because job start dates vary. It is evident that no l-year growth period

represents wage growth patterns fu~y. Measured over l-year periods 1987-1990, the

wage growth of piece rate workers vties by 11.9 percentage points and tht of tip earners

varies by 13 points. Piece rate and tip wage growth is occasionrdly negative. In contras~

time earners’ wage growth varies by 4.5 po”isrts,ranging &om 1.90/0to 5.5°/0. Counter to

intuitio~ however, commission and bonus wage growth is less sensitive to calendar y=

than is time rate growth. ~timately, the question of wkch wages sow faster depend on

the choice of calendar years over which to measure growth.

More representative measures of wage gromh can be obtained by using longer

periods of time over which to average wage grotih. Unfortunately, this invites a tradeoff between how representative the years of wage data are, ad the sample selection of

workers based on length ofjob tenure. Few workers in the sample have tenure in excess

of six years, and hence computing average wage growth over sk” year intervals may dso

be problematic

A alternative picture of wage growh patterns emerges by trac~g the wag- of

each respondent over the years they held their @rimary) 1989 job. Table 2.2 presents

wage growth fions 1984 to 1.990 by method of pay and by years of tenure. Ag@

respondents are clsssfied according to their method of pay for the 1989 jobzo. For these

tables, “Year j“ corresponds to the j-th year in which the respondent held his job, which

may be a different calendar year for different workers. Tme rate wage ~owth fo~ows the

20 We dso clsasfied workers into dhTerent F mtegories depentig on theti r~naes toP cstegorim in

1988 and 1990, & weU. Fo{example, we conside~d a ch$~cation in wtich a 19S9job w considered

a piece rate job, tithe worker give the pi= rate response to tie W qtion in at [east 2 of the 3 y- ti

which tie E quesdon w asked. We obtined stisr resrdte to those presentti here wtig this more

tingent P clsssficstion.

z
positive (until year 7 on the job) Wd smoottiy decreasing pattern typically found k crosssectionrd and Ionghudlnal data sets. In comparison, incentive pay wage growth fluctuates

considerably. For example, commission wages grow by 1.90/0from year 1 to 2, 120/0from

years 2 to 3, and 3.5% between years 3 and 4. For piece rate earners, wage growth f~s

by 4.5 points between Years 2-3 and 3-4, but rises by 109 points over Years 3-4 and 4-5”

Changes in the direction of wage growth appear ~ the other@ categories as we~.

The empirical results outfined in Table 2.2 provide fittle evidence that wage-tenure

profiles are systematically steeper in time rate jobs. Of course, ttis empirical result is

subject to the caveat that there may be unobsewed heterogeneity across workers in wage

levels, and that jobs differ k their skill and experience requirements, h the next section

we use a regression model to account for some of these dtierences.

V. Regrwsion Results

Wage-Temre Pro@[es

h this section we present empirid tests of the hypothesis that time rate workers

are more Ekely to receive deferred compensation and tilted wage profiles ..th~ incentive

pay workers. We use a subsample of 5264 workers in their 1989 primary (CPS) jobs.

For each worker, we track hourly eatings for their 19S9 job from 1984 to 1990. (Our

base sampIe of 1989 jobs includes 5656 workers, but we excluded 392 workers for whom

we observed mrnings for ordy a single wave of the NS~, We observe each worker for

at most six years, md at least two years over this time period. Our panel data set includes

20,974 worker-years.

We hypothesize that a worker’s wage profle depends on a person-spetic

intercept, and wage gowth p~eters which are finctiona of method of pay,

estabfisbment stie, trtig and job experience requirements,

therefore model worker i’s hourly etigs in year t as:

26

and union status. We
(1) log~lt) = ~ + ~tb + dt + qt

where & is a person-specfic tied effect, dt is a calendar year specific effe~ w~ch

we estimate with year dummy variables, and qt is an error term. We propose sever~

dtemative specifications for the vector Xlt. The first includes age, age square~ tenure

and tenure squared, and interactions between the job tenure variables and: method of pay,

establishment stie, training and job experience requirements, and ufion status. ~

additio~ we estimate (I) including interactions be~een both method. of pay ~d

estabhsbment stie and tenure and tenure squared.

The regression results of equation (1) &e presented in columns one and two of

Table 2.3. We first consider the spectication in column one. Jobs which have greater

traiting and experience requkements have steeper wage-tenure profiles. Evaluated at

sample means, for each one year increase in the amount of time required to become filly

trained for the job (the variable in Table 1.5), wage growth is tigher by .0095 per hundred

weeks on the job. On average, jobs which require special experience (the variable in row

one of Table 1.6) have wage growth that is about 4. I percent kgher per 100 weeks of job

tenure. Somewhat surprisin~y, we find that establishment she is unrelated to the wagetenure profile. Union workers have significantly flatter wage-tenure profiles, all else equal

@ased on an F-test of the union interactions with tenure and tenure squared).

Except for the interactions between piece rates and tenure and tenure squared,

each of the interactions between method of incentive pay and tenure and tenure squared

are jotitly significant at the 5°/0 level. Despite the fact that many of the differences in

wage-tenure profiles by. method-of-pay are statistidy sitican~ there i?. no etidmce

that jobs using time rate pay rely more on deferred compensation than piece rate, bonus,

or cornmissionjobs. k contrast, the etidence suggests that these W jobs have higher rates

of wage growth on the job than time rate jobs. Ordy tip earners appear to have a flatter

27
wage-tenure profle than time rate wage and salary earners. There appears to be fittle, if

~Y, SUPPOflfor Laem’s hypothesis that ~ jobs have flatter wage-tenure profiles.

We now investigate the possibility that the shape of the wage-tenure protie in P

jobs differs systematically with establishment ske. In column WO of Table 2.3 we interact

P status with both establishment ske and tenure and tenure squared. h this specification,

we fid stitisticdy significant dfierences in wage-tenure profiles across time rate jobs and

piece rate jobs, cormnission jobs, and tip jobs. Moreover, we fid evidence that the

relationship between the slope of wage-tenure profles and estabbshment ske d~ers

across time rate jobs and these ~ j ohs. Bonus workers have wage-tenure profles that are

statistically significantly different from time rate workers at ordy the .10 level. We find

that, &er control~mg for establishment ske, union status, and job experience

requirements, an additional 100 weeks of tenure yields the average -wo-rker wage ~owh

of 8.340/0in time rate jobs, 11.3 1°/0in piece rate jobs, 1.27°% in tip jobs, 12.73°/0 in bonus

jobs, and 12,67”A in commission jobs. The mean remms to (log) establishment size per

100. weeks of tenure are: -.24°A for time rate jobs, 7.057. for tip-jobs, -4,49Yo for piece

rate jobs, 160/0for bonus jobs, and 1.54°A for cotission jobs. .

Agai~ despite the fact that many of the differences in wage-tenure profiles by

method-of-pay are statistically significant, the overall evidence suggests that P jobs, other

than tips, have steeper-wage tenure profiles than time rate jobs. We do fmd strong

evidence that establishment stie effects on wage-tenure profiles are sigticantly lower ~

piece rate jobs, but higher in commission jobs relative to time rate jobs. This provides

some mixed evidence in support of the monitoring costs explanation of wage-tenure

profiles. h general, however, we reject this explanation of positive returns to tenure in

our sample, because we ftil to find empirical evidence that ~ jobs have flatter wagetenure profiles.

28
We intimated specifications of equation (1) which dewed for dfierent controls

for training and job experience requirements, with tiftle effect on our overd r~dfs aod

conclusions. We also included interaction terms between union status, method of pay, and

tenure and tenure squared. These interaction effe~s were fypicrdly insi~cmt from zero

and did not affect our most importtit empirical results.

Person-Spec]~c Fixed Effects.

Using the regression model in column 2 of Table 2.3, we can rwover point

estimates of the person-specfic fixed effect ~. These tied effects capture the impact of

au non tim+varying worker and job characteristics, such as race, sex, education, MQT

score, occupatio~ industry, rmion status, and ~ status. Mthough kear’s models

generate prediaions about wage-tenure profiles, and not dtierences irrwage levels by E

statis, it is st~l useful to examine the relationship between the level of wages and ~

status, conditional on worker and job characteristics. We therefore estimafed a second

stage regression of ~ on the typical worker demographic characteristics used in cross

section regressions and R du~y variables. Cohunrrs.one and two of Table 2.4 reports

the P coefflcierrfs from these cross-section regressions.

The first column of Table 2.4 indicates that Aer controhg for worker

demograp~c characteristics, traiting requirements, WQT scores, and dummy variables

for region, industry, occupation, the average pay of piece rate workers was not

significantly different from time rate workers, wtie bonus and commission workers

earned significantly more on average, and tip workers earned si~carrtly less, o-naverage.

The second cohrmrr of Table 2.4 interacts these ~ dummy variables wifh boti

estabtishrnent size and union status. The union stifus interactions are insignificantly

different from zero, but the estabfishrnent ske premia differ si~canfly across ~

categories. Tip earners receive the highest wage estabtisbment size premiu~ whiIe piece

29
rate workers receive a negative wage pretium for establishment size. The fact that the

estabfishrnent size wage premium is negative for piece rate workers provides some suPpOfi

for models of wages and mo~totig costs.

W Conclusions

The empirical results in this Section of the Repofi provide ~ttle, if any, empirical

support for the hypothesis that incentive pay jobs rely less heavily on deferred

compensation and tfited wag: profiles than do time rate wage and sala~ jobs. h

comparing wage-tenure profiles across jobs with different methods of pay, we found that

it is important to control for differences in the amount of trfing and skill requirements

across j ohs. Wage-tenure profiles are steeper in jobs that require more stills and traiting,

and skill requirements dtier substasrtiafly across jobs by their method of pay. Mer

conditiotig on these trai@ng variables, we tid that wage-tenure profiles are actufly

steeper in bonus, piece rate, and commission jobs than they are k time rate jobs. Wagetenure pro~es on tip jobs are quite fla~ with httle evidence of a positive return to tenure.

We found evidence that piece rate jobs have negative estabtisti.ent, size wage

premia and that the wage-tenure profile for these jobs .is the flattest in large

estab~shments. These results may be interpreted as evidence in support of monitoring

cost models of wage-tenure profiles. We do not, however, observe the same size effetis

for other categories of incentive pay.

What, if anything, do our resul~ imply about agency models of wage-tenure

profiles? The ~SY data set is utique in that it offers ticentive pay variables together

with detailed tiormation about worker attributes and wage histories. h important

advantage of our empirical work is that we utifized lon@tidlnal dat~ and thus were able

to compare re~]zed wage-tenure profiles across jobs, rather tha imputing wage growth

horn a cross-section of workers or establishments. Our results maybe tited, however,

30
by the relatively young age of our sample members. The mean worker in our sample has

about 180 weeks of tenure on the job. We find no evidence that time rate jobs have wagetenure profiles that are tiked relative to P workers over the first 5 to IO years on the job.

Employers may instead defer compensation much firther hto the fiture for time rate jobs

to ensure workers’ optimal effort. This empirical hypothesis may ody be testable using

either a much longer panel, or a data set which includes workers of quite different ages

and job tenures. k contrast to the incentive pay dummies, the training variables are strong

predictors of wage gro~h, suggesting that human capital investment dominates contract

effec~ in explaining the wage growth of young workers.

Aother explanation for the poor empirical performance of the deferred

compensation model may arise fiorrr the concept of employee morrhoring emphasized in

this essay. It is assumed that the relevant monitoring task is the evaluation of employee

output. Recently, Osterman (1994) has distinguished between two ~pe~ of the

monitotig problem the degree to which the employee is supervised and the extent of

control he has over work methods. Incentive pay workers may be closely supervised in

the sense that their output is monitored but permitted varying degrew of discretion over

how they do their jobs. Wle incentive pay is a good indicator of supervision over output

monitoring, the extent to which it indicates employer control over work and thus the

actual scope for worker ma~easance, is questionable.

31
I

Section 3 hcentive Pay and Labor Market Discrimination

I. ktroduction

Pervasive gender and racial wage differentials have been of interest to labor

economists for several decades. Labor market discrimination models protide one set of

explanations for persistent wage gaps and occupatimrd segregation. The employer

discrimination model holds that employers’ attitudes toward white and black (or male and

female) workers differ. Gven his relative distaste for one group, the employer makes

wage offers which are less than those for the other group. Statistical destination

models hypothestie that minority workers receive lower pay because employers perceive

greater noise in a tiority worker’s initial produditity signal (fi~er and Cain, 1977).

Customer discrimination attniutes wage gaps to tastes for discrimination among

customers, whose resewation prices are higher when buying from blacks (or women) thm

from whites (or men).zl

The prim~ purpose of this essay is to document racial and gender differences in

the wages and jobs of incentive pay earners using data from the 1988”and 1989 waves of

the National Lorrgitudind Survey of Youth ~S~. We discuss our results in fight of the

customer, employer, and statistical discrimination models. Because incentive pay rewards

workers exphcitly for their productivity rather than on the basis of time input, we expect

the scope for employer and statistical discrimination to be sma~er for incentive pay than

for time-rated wage Wd salary employees.zz That incentive. pay workers may enjoy a

21 See ~ (1986) for a wsy of the di~ritination titeratie.

22 Etidcnce tiat in~ntive pay more” accurately refleck workers’ ~i msr@”nd pmduc= tian time rates is,

for the most pm medoti md tititive rather than empirid. However, Seifer (1984) fin& that tie

cmss-sectionaf wage variance of incentive pay workers exceeds that of time rate workers, wtich is

comistent tith his hypothesis tit incentive pay is more sensitive b time rate pay to ~emncw in

effofi preduti demen~ and the productivity of mpiti. In the NLSY &@ the wge groti of inmntive

pay ~ers is more vsriable over time thaa that of time rate careen ~able 2. 1).

32
wage bargaining advantage relative to time rate workers is frequently recognized. Chen

and Eden (1991) observe that “.. under piece rate compensatio~ workers are paid for each

ufit of output produmd. Subjective, possibly prejudiced evaluations by supetisors are

less important in determining earnings for those workers relative to time wage workers.”~

Chen and Eden cite Shchter(194 1), who explains that under piece rate systems,

“The unusuauy fast and competent worker who knows that he is

producing more than other employees and who knows that he is entitled

to higher pay than he receives is not dependent upon the fairness or whim

of the foreman for his reward. ” (S fichter, 1941, p. 288).

In a competitive labor market, workers can rdso mitigate the impact of statistical

disctiation by selecting jobs in which the employer can assess worker productivity and

job performance with relative ease. Blacks should derive especially large benefits from

incentive pay, and racial and gender wage gaps should be lower among incentive pay

workers than time rate workers. h additio~ racial and gender differences in returns to

skill or abihty should be smauer under incentive pay systems than time rate systems.Z4

Ufllke employer or statistical discriminatio~ customer discrimination impfies that

incentive pay will exacerbate differences in earnings among tip, commissio~ or bonus

workers in occupations in which customer conhct occurs regular[y. We frame our

empirical work in fight of the customer discrimination model presented by Bo~as and

Bronars (1989). In this setich model, there are two types of buyers tid seUers: b[ack and

23 Chen and Eden dso iden@” saved fictors which @we mde-fede Wge gaps tO ~ ISrge ~der

pia rate systems tb tirrre rate ayate~ ~) gender ~eren~ in morivstio~ effoz and sense of

entitlement to moneq rmard, @L) ““dscrirnination in job assigrunent~ so that for examp[q tie des

workers seU tie expensive ‘%ig ticket” items, while fenrrde sates workers are cotiti to tics of

inexpensive products. ~s may k a form of employer, rstier than customer discrifinatirnr. However,

customer discrimination may rdso compel employers to favor white men in jobs where customer

interaction is pardcrdsdy irnportsn~ regtidms of employers’ om tastes for diactinstion. “

24 MIy ~~ti~ti~ &SCrifinatiOn models, like that of fi~er and tiz dld nOt Prrrdt emPlOYem tO

improve their information shut worker productivities over time. b contrast, @ttinger (1993) presents a

atatistid tiscritinstion rntiel in wfich the qdity of job nratchti formed by black workers is revdd

gradually over time. In mn~ the q~ity of matches forrnd betwwn employers and white workers is

knom inune~ately.

33
white. Momtion regardng product price arr~or the race of the seUer is assumed costly.

k equifibriuq the incidence of self-employment will be lower among blacks than whites

and the eatigs of self-employed blacks will be lower than the earnings of self-employed

whites.zs In additio~ the most productive black sellers are harmed the most by customer

discntiation. Consequently, the most able blacks are Wely to select out of seKemployment in the fist place: the efistence of customer disctiation raises the

OPPOfiUfiWcost to ~g~y able blacks of being self-employed. Mgtiy able blacks sort into

the wage-srdary sector in order to evade customer disctiation.

The authors test the predictions of their model by comparing the incidence of seKemployment across minority and white mde workers, and by ex- g the relative

earnings of self-employed men across racial and ettic groups. & important fimitation of

their emptied work is that racial differences in se~-employrnent maybe due todfierencei”

in initirdasset endowments and access to capital markets. Tests based on self-employed

workers may reflect dlscrirnination in credit markets rather than (or in addition to)

customer labor market discrimination..

The Bo~as and Bronars customer discrimination model is well-suited to examining

race and gender dtierences k method of pay arid eafings. Here, the decision to earn

incentive pay over time ratw ii analogous to the decision to enter SeE-employment over

wage and s~ary work. Thus, Borjas and Bron~s’ customer discrifiation. model predicts,

first, that minority workers are less likely to choose occupations with substantial customer

contact and more hkely to sort into goods-producing jobs.ZG Secondly, &ority workers

,..

25 In COnm~ the stidsrd cmromer tisc- tiori model tith perfect infmmation pre~cts one outcome

of dscrirnimtion-mccupatiorad segregation by ace or sex-very we~, but protides a pour expkmatimr for

mce and gender wage ~erenti~s, With perfect infomtio~ workers sort into apatiom rmti wage

~erentids are efitited. For this reaso~ labor ~onondti have tended to tiew tie ~omer

disctination model tith skepticism (~ 19S6)..

26 c“somer &crifi&tion is uely to tiect the cccrrpatioti choicss of women “~d fioriti~

~erentiy. Wle b]acks may avoid contact with white customers altogether, wornen may. select public

occupation in wtich” they are placd in stereo@id IOIW” (e.g., Vti-ti of c~d-rsistig fd

34
are less fikely to earn incentive pay within customer-oriented occupations. Third, the least

able minority workers are the most hkely to select occupations which hvolve customer

contact. Finally, incentive pay wage premia should be sma~er for minority workers than

for white workers in customer-~riented occupations.

The fist prediction is straightforward. h both the standard model of customer

discrimination and Borjas and Bronars’ emension, discfination leads to complete

segregation of blacks into.. jobs in which they do not meet_the. pubfic. However, it is

commonplace for minority workers to hold jobs which involve. extensive contact ~th

white consumers, and for women to hold “men’s” jobs. Customer discrimination might

instmd appear as a tendency for women and minorities to choose time rates in occupations

which require frequent dealings with the public. Ntematively, employers may assign

minority or female workers to jobs in which revenues are relatively insensitive to their

detikrgs with customers. Incentive pay is most fikely to appear when the share of worker

effort in tot~ output is large (Stigfiti, 1975). Mrrorities or women maybe placed k jobs

in which brand names or advertising sell the product or in which. the. price elastici~ of

demand is low.

The predictions regarding abflity-based sg~ing depend on assumptions specific to

the Borjas-Bronars model. The model predicts, for example, that the least able minority

workers will select sales jobs. However, it is possible that expected customer resistance to

female, black or Hisptic sales workers will lead o~y the exceptionally able into these

jobs. The d~ection of abihty-based sorting depends on patterns of comparative and

absolute advantage found in the labor force. Mnority workers who have a comparative

advantage in, say, sales as ppposed to goQds production may select sales jobs despite the

existence of discrimination. On the other hand, minofity workers who are ti~y able in d

prepmtion, and hou~keeping). For e~ple, customers may favor women & ti~tig jobs but be

skeptid of women who seII ~.

35
occupations are more tikely to select goods-producing. jobs in wfich they. we more

productive, Utiortunately, our measure of abdity, the ~QT score, is a urri-dmensiond

measure of abifity and does not capture relative abfities or specific skills.

Tfis paper proceeds as fouows. Section H documents the role of race and gender

in the choice of occupation and method of pay. We emphasize specfic occupations in

which incentive pay is common: sales, customer-oriented setice, and operator,

fabricator, and laborer occupations, We chose to focus on ths set of occupations because

two involve extensive customer contact, wtie one involves minimal customer contact. h

section W we present wage equation estimates of racial and gender dfierences in

incentive pay wage “prerniarmd differences in returns to SW by race and method of pay

status.

U. The Choice of Occupation and Method “of Pay

Gender and race are consistently significant detetimrts of method of pay wittirr

au occupations. k Part I of ttis report, we found that, condhiotig on occupation and

other worker and job attributes, women are si@canfly more hkely than men to ~

piece rates or tips, and are significantly less fikely to earn bonuses or commissions. We

also found that blacks are significantly more likely than non-blacks to earn bonuses, but

less likely to earn tips or cotissiona (Tables 1.3.and 1.4).

The possiblhty of discrimination is expected to affect the choice of method of pay

differently for dtierent occupations. Customer discrimination” may appe”ti as a tendency

for women and minorities to choose time rates in occupations which-require frequent

dea~igs with the pubhc. In occupations in which interactions with employers, rather than

customers, predotiate, employer mrd statistical disctiation are relevant. Members of

minority groups might prefer incentive pay to time rates in these occupations.

We exafine race and gender differences in incentive” pay in sales, services, and

operator, fabricator, and laborer occupations. Sales and servicm occupations involve a

36
high degree of mtomer contact and may expose workers to customer discrimination. k

contrast, operators, fabricators, aid laborers are almost exclusively in jobs for w~ch

customer contact may be assumed to be minimal. Workers in au three occupational

groups have a high fiequenq of incentive pay (Table 1.3). k addition to these basic

categories, we defie customer-oriented services to include the sub-group personal

services (1980 Census Codes 456-469), wtich includ~ for example, barbers, ushers,

guides, and baggage handlers; and food service workers except for cooks and other

Mtchen stafi Customer-oriented services dso ticludes two occupations from the motor

vehicle operator sub-group of operators, fabricators, and laborers: taxi cab drivers and

driver-sales workers. These occupations are in turn omitted from the operator, fabricator

and laborer group. Other service occupations, which may require varying degrees of

customer contact, include protective, hedtk domestic, food preparation and

cleanin~uilding services. Rnally, we isolate sales clerks and csstiers (1980 Census

Codes 275-27~ from the rest of the sales group. We the degree of pubfic exposure in

these jobs is high, they do not typically require persuasive salesmanship compared to other

sales jobs. Thus, both time rate and incentive pay earnings should be less sensitive to

deafings with customers in clerk and tastier than in other salesjobs.

Table 3.1 illustrates the etient of racial and gender segregation across

occupations.27 Whhin each racia~etfic group, women are more fikely than men to be

employed assales clerks or cashiers or in customer-oriented services, whle men dominate

operator, fabricator, and laborer jobs. ~te men make up 6.7 0/0 of sales clerks and

castiers, far less than their overall representation in the sample, but account for 39.90/o of

other sales workers. Black and Mspatic men account for ody 6.6°A and 9.4%,

respectively, of sales workers.
Thwe patterns are reirrforced in the multinotid Iogit model for choice of

occupation shown in Table 3.2. Manageri4, professionti and technical workers formed

the omitted occupational group.Z8 Predicted probabfities of choosirrg selected

occupations, based on the M coefficient estimates, are presented in Table 3.3. Women

are more likely than men to be employed as sales clerks, cashiers, or customer-oriented

services workers. Blacks are more fikely than whites to work in services and operator,

fabricator, md laborer occupations.zg No si@cant differential effects exist for black or

Hispanic females. However, ability-based sorting into occupations is pronounced for

these and other groups. “The N results indicate negative ablity-bssed selection of black

men tito clerticashier, cutomer-oriented services, and other services. Black men wortig

as operators;” fabricators, or laborers tend to be no less able than wtites in those jobs.

Thus, customer discrimination may deter higtiy able black men horn entering pubfic jobs

but not “betid the scenes” jobs, The resulfi indicate positive abihty-based sorting of

black women into these occupations and of black and Msparric womefi into op~ratoi,

fabricator, and Isborerjobs.

Wce and gender. dflerences in occupation are marked and consistent with a

customer discrimination model in which segregation occurs. For example, women are

more fikely than men to be employed in customer-oriented services, and as clerks and

csshier~ than are men. Discrimination may lead women and tirrorhies imo “passive” sales

jobs as opposed to those in which initiating contact with potential customers andor

persuading customers to buy are important. As the standard customer discrimination

model predicts, black workers are less likely than whites to be employed in customeroriented services, but more likely to be employed as operators, fabricators, and laborers.

28ne w nr~del~so includw ~mtiom for clendtifistitivi d-d production C* Snd Ie@

workers, but for the sake of brtity restix are not sham.

29 Wen the sample is iofined to respondents who hold setices jobs, blacks are siti”ti”tiy lus weIY

than are whhes to be employed in actirnner+riented setice.

38
However, some of the results are anomalous to the customer discrimination model: blacks

and Hispanics are no less Mely to be employed as srdes workers than are whites, and

Mspanics do not differ &om whites in any of the ~ equations.

Table 3.4 shows the percentage of workers e-g incentive pay by occupatio~

race and sex. k most occupations, one or two types of incentive pay predominate. For

this reaso~ we do not disaggregate method of pay. No si@cant difference .efist in the

tendency of demographic groups to earn incentive pay across rdl occupations (F=l. 10).

Wthirr occupations, race md gender differences h the incidence of incentive pay are

significant for all occupations but Other Sefices. GeneraHy speaking, whites are more

fikely than blacks or Msptics to earn incentive pay in occupations that require de~gs

with customers, however, the reverse is true in the operator, fabricator, and laborer jobs,

where customer disctination is”urdiiely to be relevant. Akhough men are less Wely

than are women to be employed as sales clerks or ~biers, they are more &ely to earn

incentive pay in those occupations and in other sales jobs. In contrast, wtie relatively few

women are employed as operators, fabricators, or laborers, they are more hkely than men

to earn incentive pay in those jobs then are men, Wte women are more fikely than any

other grouP, includlng w~te me% to. earn incentive pay in customer-o”riented sefices

occupations (~. 270). hong blacks and Wspanics, however, men are at least as hkely as

women to earn incentive pay in these jobs.

Table 3.5 presents the results of probit estimation for incentive pay among sales

workers. Column 1 shows the basic model; in column 2, we present a model wtich

includes interaction terms between race and sex on one hand and AFQT, Log

Establishment Ske, and SMSA on the other hand. k bofh. spectications, the dependent

variable takes on the vakre of 1 if the respondent earned some fow of incentive pay (sales

workers in the sample repotied earning tips and piece rates as we~ as the more common

bonuses and cofissiorrs). Dummy variables for the type of sales job held are inchrde~

39
the omitted occu”pationd group was Other Sales, a categoy co-misting of auctioneers,

demonstrators, newspaper vendors, and other miscellaneous sales jobs.30 AZ expected,

clerks and cashiers are no more Mely than workers in tie omitted group to earn incentive

pax incentive pay is relatively common in sales of business goods and setices and

personal producw. In both specifications, female sales workers are si@cantly less Mely

than men to am kcenti~e pay. “Note that this is the case &er adjusting” for the tendency

of female sales workers to hold jobs as clerks or cashiers. Blacks and Hisptic sales

workers are no more or less Mely than wtites to earn incentive pay.

Results of the full model are presented in column 2 of Table 3.5. Here, blacks are

signifitidy more fikely than whites to earn incentive pay. However, this probability is

d-shed for blacks who reside in SMSAS. This result is striting because with the

exception of clerk and cashier positions, sales jobs tend to be concentrated in SMS&, in

additio~ the returns to incentive pay in srdesjobs are likely to be augmented in SMSAS.

To the extent that location in an SMSA cotiers a superior base of potential contacts,

black ssdes workers maybe at a disadvantage. Similarly, the incidence of incentive pay

decreases with establishment &ze for blacks. Again, this may. Ktit the number of

customer contacts “for black sales workers in large establishments which typically have

large customer bases. Establishment size and SMSA effects are significant for women as

well as for blacks. In contrast to blacks, however, the probability that a female sales

worker earns incentive pay rises ”with both the log of estabhshment size and residence in..

arrSMSA. The probabi~ty that a male sales worker earns incentive pay is higher among

workers who report that some specird experience is required for their jobs, su-ggesting that

incentive pay jobs may be more tig~y stied than time rate sales jobs. For womew

however, this effect is diminished if not offset completely. Finally, the(e appears to be

30 We -t~ an identid model i“ “whici”sdcs mpatiom were dsa~egated to the ficst POSSible

cxtenL Dales were created for each of the wcupations tithin pcraoti product da, boainess sdw,

etc. hclusion of these dunsndes tid not alter the retits repond here.

a
positive abfity-based selection into .mcentive pay. However, Hispanics or women who

sort into ticentive “payare relatively less able than white male sales workers.

Table 3.6 presents probit estimates for incentive pay for workers in service and in

operator, fabricator, and laborer occupations. Both equations include occupationrd

dummies. hong operators, fabricators, and laborers, textfie workers and drivers are

significantly more fikely to earn incentive pay than are laborers (the reference occupation

group). Mlde horn these occupational dummies, the ody si@ficant determinant of

incentive pay probabtities is race. Blacks in the operator, fabricator, or Iaborer

occupations are significantly more Mely to earn incentive pay than are white workers in

these occupations.

Column 1 of Table 3.6 presents r=ults for service workers.. Occupational

variables include a dummy for a customer-oriented service job and its interactions with

Female, Black and Hispanic. Compared to employees in the omitted occupation group,

Private Household Setices, customer-oriented .sefice workers are signific.mtly more

fikely to earn incentive pay, particularly tips.. However, black customer-oriented sefice

workers are significantly less Wely than whites in that occupation to earn incentive pay.

The results in Table 3.6 are consistent with the view that while customer discrimination

might deter blacks from earning incentive pay in pubfic occupations: i.e. blacks select

incentive pay jobs wbicb involve minimal customer contact. Interactions between NQT,

race, and sex were not si@cant deternriniants.of ~centive pay for either service workers

or operators, fabnmtors, and laborers.

Our results indicate substantial differences in both the choice of occupation and the

choice of method of pay by race and sex. Women are more fikely to work in sales

occupations than are me% but female sales workers are less Rely to earn incentive pay

than are mde sales workers. This is parti~y, but not entireIy, attributable to women’s

relative dofinance in clerk and cashier jobs, in which incentive pay is relatively rare.

41
Fetie and Mspanic sdcs workers that do earn incentive pay tend to be less measurably

able than white men who do, which suggests customer dlscrmination. Blacks are less

tikely than wtites to work in customer-one.nted service jobs, and those that do are less

Mely to e~ incentive pay. The opposite is true for operators, fabricators, and laborers:

blacks are more ~iely to work in these occupations, and also more Wely to earn hcentive

pay within the~ than are whites.

There do not appear, however, to be many significant differences between

occupation and incentive pay choicw of whites and Wspanics: Ttis fact is rmomdous to

customer discrimination explanations of the patterns found in this section. Aso

problematic is the tiding that blacks sales workers are no less ~iely to earn incentive pay

than are white sales workers; controtig for the tendency of black sales workers to be

reside outside of SMS A’s, blacks are significantly more likely than whites to earn incentive

pay. FinaUy, with two exceptions we find no evidence of abfity-based sorting into either

occupations or pay systems.

~.--Incentive Pay and Wages

k this section, we document race and gender differences in the wages of incentive

pay workers. Of special interest is the extent to which (a) racial and gender wage gaps

typical of time rate workers are smaller under incentive pay, and@) these wage gaps vary

with the customer-onentedness presumed to charactetie workers’ occupations. Where

employer or statistical discrimination occur, we would expect race and gender wage gaps

to be smaUer under incentive pay, regardless of occupation. Customer disctition

imphes that these gaps should vary with occupation.

Table 3.7 presents mean log wages by race, sex and method of pay in selected

occupations: sales workers, service workers, and operators, fabricators, and Iaborers.

These unconditional means suggest that minority wage dtierentids are somewhat larger

42
among sales workers who receive incentive pay. The unconditioned white male-black mrde

wage gap is is 28°/0 for time-rate sales workers and 380/0 for incentive pay+rrg sales

workers. The corresponding figures for the ~sparric-white wage gap are 120/0 and 3 So/O

respectively. SirniIarly, mal+female wage gaps are somewhat larger under incentive pay

than time rates for black and Wspanic srdes workers. In operator, fabricator, and laborer

occupations, the reverse is true: the black-wage wage gap is narrower under incentive pay

than time rates. Mspasric men in these occupations who receive incentive pay earn 22%

more per hour than do their white counterparts.

Table 3.7 makes no attempt to control for other factors which might itiuence

wages. Table 3.8 presents OLS log wage estimates of incentive pay wage prenria by race

and se~ contro~ng for NQT score, human capital and other standard variables. Dummy

variables for each of the 388 occupations represented in the sample were included, as were

dummies for job training requirements (formal company tratig, on-the job training with a

previous employer, on-the-job traiting with a current employer, apprenticeship, trade or

technical school, and armed forces training), which prow for job skill. Taken together,

the results do not cordorm to the predictions of employer/statistical discrimination models.

Wce and gender wage gaps are no different among b~nus earners than among time rate

eamers.31 Female piece rate workers earn less than men. One result does suggest

employer/statistical discrimination Msparric piece rate workers earn significantly more

than do their wtite counterparts. Table 3.8 offers tied evidence of customer

disctination:” female tip workers earn si~cantly more, and female cotission

workers less @-value=. 103), than men. In additio~ black and ~spanii commission

workers earn less than whites @ut the former coefficient is not significant). Flndy, black

tip workers earn significantly less than white tip workers.

3lms rat Shodd be regwded titi cautio~ stice it is not CleU fiOm the dsm tie e~ent tOw~~ ~n~

aers are part of group or in~vidti systems.

43
h Table 3.9, we estimate separate log wage equations for blacks, blacks or

Mspsnics, and whites. h tfis table we focus on differences k returns to abti~ by method

of pay and race. Education and ~QT score are used as proxies ‘for worker abifity.

Taken together, the results protide no consistent support for either of the three types of

discrimination: Counter to the ktuidon of the statistical or employer d“isctiation

models, blacks or Msptics who earn bonuses enjoy lower returns to ~QT score than

time rate earners of the same racdettic group. Tips and piece rates do not augment

returns to abfity, as measured by the ~QT score, for black Mspanic, or white workers.

Table 3.10 also indicates that white commission workers derive particularly high returns to

educatioL as do black and Mspanic bonus workers. We these last two results are

consistent with customer disctinatio~ we also fid, unexpectedly, that black

commission workers get greater “returns” to MQT score than do” blacks who earn time

rates,

Table 3.10 presents results fiam regressions sitilar to 3.9, where we instead

estimate separate equations for men and women. Mthough gender wage dflerentials are

found to vary by method of pay, there is fittle evidence that returns to skill for women

differ by method of pay. There is some weak etidence-that female commission workers

have higher re@ms to edumtio~ and lower returns to test scores, au else equal.

Finally, Table 3.11 pr=ents OLS earnings estimates of ratial and gender wage

gaps by method of pay and by occupation. The equation ticluded kteractions between

race, se< a dummy indicating whether the respondent earned any type of incentive pay,

and the fouowing occupations: operator, fabricator, laboreq sales, not including sales

clerks and cashiers; sales clerks and cashiery customer-oriented seticey and other

services. ~cial and gender d~erences by method of pay in clerk tastier, and other

services occupations were genedy insigticarrt, and the results are not shown to save

space.
A expected, incentive pay workers earn significantly more than time workers on

aversge--7.2°/a. This incentive pay wage premium does not vary with race, but is reduced

to 1.6Y0, on average, for women. It increases by 12 percentage points in des

occupations, andisactiauy negative in operator, fabricator, rmd laborer occupations.

Tbreeresults areconsistent with customer discrimination. Fwst, black customeroriented service workers who earn incentive pay earn about 250/0 less per hour tha do

blacks inthesame occupation whodonot earn incentive pay. Note that black customeroriented services workers who earn time rates do no worse, relative to whites, thm blacks

in the reference occupation. Secondly, Hispanic srdes workers who receive incentive pay

earn about 290/0 less than their counterparts who earn time ratea.32 Fmdy, female

incentive pay workers who are in customer oriented services earn si~cantly more than

time rate earners, and the ~ wage premium is larger for women than for men in this

occupation. Other results, however, are difficult to interpret in fight of the customer

disc-ation model. For enmple, women and blacks are disadvsmtaged neither by being

sales workers, nor by choosing incentive pay in sales occupations. It is possible that

customer discrimination against women is reflected in occupationrd segregation and

preferences fourtime “rates ~“ bppo”sed to incentive pay

Hypotheses based on employer and statistical discrimination do not fme as we~. h

Table 3..11, women and blacks in operator, fabricator, and laborer occupations -

sigdcantly less than do white mew but incentive pay does not appear to overcome the

gender wage gap in this occupation. Wkh one exception (women in customer oriented

sewices), incentive pay does not narrow gender and racifl wage gaps within omupations.

If anything, these gaps are smaller under time rates.

32 ~ ~~ ~efi~io% 387 &-cuPatio~ dties were inClude~ ~r~endng tbe-”~t~ extent Of

occupatioti di=ggregation possible tith tie da~ men broad ~patioti dunrnri- are ti ti=&

Wspardc des wofirs earn si@mnfly mom M whit= and Msptics h tie referenm occupation. A

a rcsrd~ tie time rat~incentive pay mge gap is everilarger rban in Table 3.11.

45
W. Conclusion

Our empirical work uncovers numerous racial and gender differences in both the

incidence of incentive pay and incentive pay wages. Differences in the method of pay are

shown to depend significantly on race and sex tier controlhg for 3-digit occupatio~

training requirements, ~QT score, and standard earnings quation variables. Reid and

gender .wage gaps differ by method of pay as we~. Some of these patterns are explainable

in terms of employer, statistical, or customer discriminatio~ but results are tied. We

find, for example, that blacks are more fikely to earn incentive pay in operator, fabricator,

and laborer jobs than are whites. At the same dine, the black-white wage gap under

incentive pay is no smaller than it is under time rates. However, blacks who earn bonuses

seem to get tigher returns to education than blacks who don’t. The same is not found to

be the case for wtites. GeneraUy speaking, the results for occupational choice and method

of pay are more readily interperable in terms of the three discrimination models than are

the wage results. Of the three discrimination models, employer and statistical

discrimination are the least able to explain the results. That incentive pay does not appear

to reduce these gaps suggests that they are attributable to unobsewable productivity

differences rather than employer tastes or imperfect tiormation. Customer discrimination

models fare sfightly better. We find consistent evidence of customer dlscimination against

Hispanics and women in sales occupations, and against blacks in customer-oriented

services.

46
Table 1.1 Sample means and standard deviations

Tme wka Plti Co& Bmu mps Mdtiple flw

fik tian F

Howly 8.28 7.73 10. U 9.23 7.36 9.49 9.01

3.9.6

2.01

.4 I

40.34

8.78

12.89

2.26

.92

.27

.15

.36

,08

.27

8.16

3.06

.53

.49

.48

,49

.26

.442

.16

.367

27.06

2.23

3.50

1.95

.41

42.15

7.53

11.86

1.68

.98

.14.

.04

.,20”

.02...

.14

9.55

L60

.55

,49

.46

.50

.29

.45

.09

.28

27.41

116

6.60

2.15

,56

43.30

11.46

13.44

2.35.

.95

2

.27

.@

.05

.22

7.75

3.03.

.51

.50

.31

.46

.16

37

.16

.37

27,19

2.41

4.40

2.12

.45

.43,19

.8.24

13.27

2.23

,95

.21

.23

.43

.34

.-.19

7.59

2.>7

.53

.49

,40

,49

.26

.43

.15

.36

26.86

228

4.53

1.81

.61

35.39

11.25

1224

2.00

.87

.33

.06

,24

.11

.32

8.74

3.05

.47

.50

.68

.46

.19

.39

.17

.38

26.9%

2.23

5..17

2.12

.50

44.19

9.64

13.19.

211

.95

.22

20

:39

.05

.22

7,68

2.92

.48

:s0

.36

.48

.21

.409

.15

.36

26.88

225

4.89

207

.50

42.36

9.62

13.m

221

.95

.33

.19

.39

.05

.22

7.98

3.01

.51

.49

.42

.49

.23 .. .

.42

.15

.35

26.98

2.28

N 4405 144 172 581 143 212 1252

(contiud 0..& p~e)

47
Table 1.1 Sample means and standard deviations

(contiuti)

The Rte Pi- Coti% Bonw Tips Mdti91e Ml fP

Rate sim P“

Yms of 2.95 2.s0

T~we

Plmt Sue

Small

(1-10

wrkem)

Mediw

(1149)

Mge

(50-199)

Vey

IWg<zoo

+)

UtiOn

COve@e

SMSA

2.99

2.81

533

2134.26

.19

.39

.27

.44

.21

.41

.31 ,46.-.

.14

.35

,20

.40

.78

3.28

3.11

307.76

576.

.18

.39

:17

..38

.19

.39

,4

.49

.02

.16

.24

.43

.68

221

2.30

299.25

3047

.32

.46

.32

.46

.19

.39

.10

.30

.01

.07

.04

21

.86

3.01

2.73

533.70

2039

.21

.40

..29

.45

.23

.41

.28

,.a

.07

.26

.16

.36

..81

1.97

2.10

87.68

159

.20

,40

.50

.50

.21

.40

.08

-;27

.01

.08

.09

.28

.8S

2.82

=2.89

918.88

.30.

.46.

. ..29..

,=. 4s

.21

,40

.18

.39

0

0..

.10

‘.30.

.86

2.70

373.62

1846.97

.24

“.43

.30.

..45

21

.41

.23

.42-

.04

.19

.13

,34

.81

.41 .46 .34 .39 .36 .34 .38

N 4405 .. 144 172 581 143 212. 1252

Dam me tim the 1988 ~Y. “R&pondenb u cl~s~led accordhg to methti of py fi tieu cwmVtiost

rant job h the 1988 sm’q, The ~ple exclud& tho~ who wme eitier seE~ployed o: fmployed h the

@c”lwal sector h theu cwenVmost rment job, who had tissfig val- for mos. of the’vxabl= *OW .

ahve, for region of r~idenw, or for mmplo~mt rote, whose noti howly w~e w 1=s ha S1 or

g-ta ti~ $100, ho repofled wwe chmgm of more tbm $50 h akoluk wlue 1988-198% md tio

repofled - a fofi of hcefitive py ‘othm” thm bonw~, cotissiom, tips, or piece mtes.

a hcludes works tio - stock optiom

b &perimce is defined m Age-EdumtiOn~.

48
Table 1.2 Mea bed Forc~ QuaUficati.n Test ScO~ by Mtihod of Pay, 1988

(stitid ktiatim h ~ti=)

Ttie Wte Pi* M* Ctiwion Bouw Ti - MtitipIe P

~

mw Sam 66.01 59.45 70.24 69.29 64.84 71.28

21.38 19.07 19.76 20.70 20.21 19.44

Pamtie 41.61 31.5 47.59 46.67 39.16 48.60

28.41 23.74 27.69 29.15 26.46 27.M

*QT -.475 -7.59 3.57 3.17 -1.57 5.04

R=idml 21.07 18.65 19.05 20.24 20.18 18.64

49
Table 1.3 MuItinodal bgit Est5mates of Method of Pay Cat%otia

G*titim &low ~5cimt dtiak)

tig L = -3203, Raq4 = .14, N = 5259

Piew Rak CO&ssiOn %n~ Xps

Edumtion .0251 .195 -.01s7 -.0597

0.356 3.230 4.469 4.819

Tame

Finale

Black

fi~tic

Log Plmt Sii

UtiOn

SMSA

UnmplO~mt

Rate~”A

AFQT Residwl

Mm%erid,

PrOfessimal.

Tectid

Sales

Sticm

Pmducti~ Cm&

ad Repak

@eratom,

Fabrimtors,

.012

0.397

1.121

5.444

-.220

4.888

-.629

-1.810

.026

0.516

.033

0.149

..010

0,051

-.231

4.379

.W1

0.253

-.702

-1.132

.194

0.634

.717

1.443

2.76

6,488

2.68

6.6s6

-.087

.-2.360..

-.832

4.219

-.648

-2.399

-.170

4.671

-.170

-3.403

-.995

-2.465

.674

2.727

.578

1.599

-.0048

4.792

1.04

226S

3.23

7.429

.n 1

1.426

1.26

2.5S6

1.o8

2.198

.01s

0.905

-.400.–

-3.898

.264

2.04s

.094

0.658

-.029

-1.263

-.120

4.907

.03s

0.295

.4S6

2.197

.0062

1.940

.20g

1.514

.308

1.699

-.373

-2.010

-.153

0.838

-.217

-1294

-.098

-2.19

...662

3.120

-.485

-1.728

.180

0.640

-.112

-2.036

-.358

-1.102

.712

2.7S3

-1.68

-1.634

.0205

3.136

““1.S8

1,%2

293

2.734

S.40

5.349

1.57.

1.271

3.33

3.184

swq. no= fig multiple fo~ of ticative pay wme otittd-bm tie -pie.” E&ates for mtiti

~~, e~rimm, gove-ent mplo~mk md region of resida= not sho50
Table 1.4 Preditid method of pay probabilities by mce and sex (“A).

Blwk Wle Blink Wk Wle Wk m@c fi@c

Fde F&e We F&e

Tme mk 80.5 82.2 79.6 80.2 79,8 81.3

Pi- Ek 1.8 .80. 2.3 4.9 1.2.. . 27

COdG<On 3.0 ‘-1.5 “: .“:4.5 22 42 2.1

Bon~ 13.7 10 11.6 8.4 12.3 9.1

51
Table 1.5 Pmd[cted Method of Pay ProbabiUties by Establishment Sk and Union Coveqe ~A)

TticWe R=e Mte COtissiOn Bonm ~p

Union

Smll 81.6 2.5 u 11.1 2.4

Medim 82.7 26 1.8 10.5 2.3

Mge 83.5 . . .. 2.7 1.4 10.0 2i

ti-lwge 84,6 2.9 .9 9.4 2.0

Nonunion

Small 78.5 2.4 4.5 11.6 2.8

Me&u 80.0 2.5 3.5 11.2 27

tie 81.1 2.6 2.8 10.7 2.6

Em-lmge 82.6 2s 20 ..10.1 ....2.4

Predictd probabititia “meb~d on mdtiotial l.git &ation of ‘metid of pay eqhti-, 1988 “&m

Sue mtego~ effm~ wxe..@culakd by setttig tie log e~blitient tie vtiibles eqd @ tie m- 10g

sti titi tie mlaat sti mkgo~ sdl=l .42, medIu=3 .03., Iw&<,43, e~-lage% .55..

52
Table 1.6 Months of Experience Requirti For Job by Method of Pay

P-&s by pay wtigow)

MOnti The Wk Pi& W& Codssion Bonw~ Ti

<1 22.9

Multi le F

26.2 125 13.0 62.6 13.7

1-3 22.3 40.6 26.0 23.2 21.8 -14.2

4-6 13.9 10.1 20.0 13.8 5.6” 12.2

7-12 15.2 5.9 15.5 16.1 6.3 20.9

13 + 24.6 15.9 25.5 .33.5 3.5. 37.6

Totil Y. 100 100 100 100 100 100

53
Table 1.7 Months Reqtired to Become FUHYTmined

(t-sbtitim blow *ata)

OLS a -oral No@ o

Piece W .257 1.%

0.151 0.888

Bonm 2.219

2.748

3.423

3.539

Co-ion” -.266 1.72

4.213 1.151

Tips -2.258 4.96

-1.420 -2.ati.

Edwtion 1,228 1.59a

6.415 6.a61

E@mm ‘‘ “:560 .74a

4.576 5.00a-

,537

..xoK

5.756 7.”135

WQT Rtiidd ..04a .079

3.639 4.a27

Log @ltit Sue) .oas .0344

0.601 0.193

Faale 4.422 -8.406

-10.399 -11.042

B1mk -3.592 ..-5.18

4.9a2 -5.79a

fis@c -1.716 -1.674

-2.084 -1.676

54
Table 1.8 Avemge Experienc~mining Requirement by Method of Pay

(O/.of wrk=, *H dtitiion klow m-)

Ttie Wte Pi- W* COtissiOn Bmu Tips M~le P

Some s7.2 44.9 68.0 66.6 42.9 663

S~ial .49 .50 .46 .47 .49 .47

Extienwa

Tde or 14.1 6.7 18.5 , =.... 16.3 .028 19.8

Tectid .34 .25 ..38 .369 .16 .40

tihool

ApPmti=- 4.6 2.5 .6 . ...4...3 35 4.5

Stip 21 .15 .=. . 20 .184 .20

Foti

Cmpmy 8.5- 3.3 Lzo 14.3 4.2 18.8

Ttig .27 .18 .32 .35 m .39

on--at 30.2 22.8 3X .37.2 25 37.7

Employer .45 .42 .46 .48 .41 .48

om- -- 29.5 16.1 35.5 38.8 32 37.7

PreviOU .45 .36 .47 .48 .42 .48

Employ=

tid

ForcB md 4.3 .8 7.0 5.7 o 5.1.

mm .m .092 z .23 0 22

Tmtig

N 4441 118 200 .“ 558 .142 196

55

..
Table 1.9 Avemge Within-Occupation Expedence Requimmenfi

~ Method of Pay-1989

tiqem, Cleriml md tiduction, Qerators,

hf=sions, Ati. C@ ad

Tecticim w

Fabrimtm,

- ~u.w -

Ttie P Ttie fP The F Ttie P Ttii” P Ttie E

Trtie m

Tectid 12.9 14.2 8.o 6.1 17.6 23.8 30.1 12.8 20.1

School

9.0 6.0

21.6

ApprentimSbip 5.4 6.2 2.8 1.7 1.0 .6 13.6 13.5 3.0 4.7 3.7 1.7

Fomal

Compmy 9:8” 13.2 11.0 20.4. 7.8 15.2 .7.8 13.5 10.4 3.7 5.6 8.1

T-g

03TCment 35.0 37.3 28.9 43.4 31.9 35.4 42.8 24.3 25.9 24,0 22.8

Employm 28.6

03T–

Preview 36.7 46.5 30.3 38.6

Employer

35.1.. 32.0 33.1 20.7 25.9 19.6 18.1

40.1

hed

Forces md 8.4 8.0 2.3 4.8 2,3 4.4 3.6 5.2 4,6 2.1 2.2 2,5

Oth=

Tmtig

N 1086”” 273 336 230 . ..894 559 133 623 “183 944 232

..1.57 _____

Dam =e from tie 1989. ~S.Y questions, “Po). you have to have some work experience or ~tial katig

toget(tie)job?" md''...what tidofexperimce tii~cial &atigfistiat)...T R~ndenkaecI=sifid

accordtig totiekrnetiod ofpaysm~s md~mptionti 1989.

56
Table 1.10 TmitinE and Experience Requimmenti

4.979 -1.879 -1.422 -1.528

.264

3.146

.225

2.223

.>020

Ozo

.077

0.934

bnm .168 .278

3.129 4.227

.130

2.449

.217

4.032

Tip -.083.

4.817

. ..-.329.

-1.925

-.030

4275

-.09.0

4.808

-.M2

4.99.9

Fade -.075. -.106

-1.869 -1.898

-.095

-2.296

Edu=tion .053 _.oi.5

4.2@ 0.854

.010

0.775

.059

4.530

.046

5.806

.003

0,332

.015

1.829

.W8

5.720

Tmwe -.027 .009

4.566 “1.171

.037

5.994

-.0ss

-12.436

h @lat Ske) -.004 .06s

4.S06 5.165

.032

3.313

-.00s

4.s35

=m R=idml ..002 .001

2.943 1.2s3

402

2X5

.003

3.454

.—

37
Table 2.1. Mean Real Avemge bnual Wage Growth by Method of Pay,

WIetid Calendar Yearn

ma, s, w

Time Span Ttie bte Piwe Rate CO&siOu Bonw Tips ~ fP

1 Year

1987-1988 .055 .036 .020 .067 .o~o .060

,27 .25 .38 .24 .44 .30

2063 65 74 298 -43 580

1988-1989 .019 .080 .042 .032 -.050 .023

.25 .24 .44 24 .49 .34

3179 86 118 430 83 855

1989-1990 .010 -.039 .009 .029 -.023 .OD

.24 .25 .40 24 .55 34

3962 104 181 527 105 1097

tige .045 ,119 .033 ..039 .13 ,047

2-Year

1986-1988 .055 .055 ..066 “. ,063” .:0”67 .066

.14 .14 .24 .11 .22 .16

1512 1512 55 216 27 417

1987-1989 .034 ..M7 .m9 .055 ..032 .043

.14 .14 .12 .14 .25 .15

20@ 65 74 298 43 580

1988-1990 .016 -.004 .058 .033. ..-.043 .022

.13 .13

26 ....

.13 .25 :17

2912 76 109 412 62. “... ”:.-786

tige ..039 ..059. .037 .030.. ..11 .344

3-Year

1985-1988 .051 .021 .M5 .066 .065 .“..“”” .061

.09 .09 .18 .11 .11 .12

1106 41 39 161 19 308

1986-1989 . ...04 .<044 .058. 455. _ -.009. .0s

.09 .09 .10 .0.8 .18 .10

1513 48 55 216 27 417

1987-1990 .026 ““”:002 .323 .046 .-.027 .032

,09 .10 .10 .09 .21 .11

1941 60 71 289 36 549

Rmge .025 ..042 .029. .02 . . ...092 .029

6-Year

1984-1990 .033 ....017 .342 .M9 .025 .044

.051 .05 .067 .05 .053 .059

824 32 26 111 10 216

W@e ~ti * wwe obbtied by tiactig w%es of tie 1989 cwenVmOst re~t job over the 1984-1990

smqs. Workws wme classfied zcordtig to metid of pay k 1989. Colm 2-5 otit multiple tic=tive

pay -em. Multiple E -=s U% however, ticluded h tie I@ =teoa, ‘N ~.”

58
TabIe 2.Z Ave%e Real Wage Gmtih @er Adlacent Yearn On the Job

1984-1990, “

~-, S, ad ,~

Tme me Pi- Rate Codssion knw Tips ME

.046 .077” .019 .065

Yw 1-2

.Mol

.25 276

.050

.41 7.7 ,46 .35

YW 2-3

Ym 34

3486 93 162

.345 .021

.26 .19

2299 60

.033 .-..026

.29 .27

1375 43

.026 .083

.27 25

879 28

.004 .029

,.22 27

501 20

.120

.45

84

.035

22

49

.063

.25.

35

.034

20

20

-.007 -.032

:20 .15

-.096

.45

.-

M2”. 115

.051 .m2

23 .41

317 58

.071 -.120

.19 .63

203. .33

.052 -.036

274 .56

128 -. 18

.010 -.037

.28 .43

73 11

.M2 .064

.13 .09

978

.053

.32

628

..038

.32

..403

.062

.32

255

,Oow

m.

152

-.0009

.23

S9
Table 2.3 Wage-Tenure Pm files titb Pemon-Specific Fixed Effec~

(absoluk value of t-s@ti@im kIow -at=)

(1) (2)

Age .0374 .0386

2.77 2.85

Age Sqmed -,0010 -.0011

4.53 4.62

Tenu

(h hm&b of w~b)

.0912 .0944..

8.04 ?.94

-,0059

3.21

-.0064

3.29

Tips*Tmwe -.1281 -,2698

5.41 4.55

Tips*Tenw Sqwd .0137 .0144

3.29 1.43

Bonw*T~we .0518 .3401

4.82 1.60

Bonus*Tam Sqwed -.0048 -.0032

2.5.8 .706.

Cotission*Tmwe .0324 -.0250

1.81 0.66

COtissiOn* -.0020

T-tie Sqmd

.0143

0.59 1.95

Piece Rates*”Tam .0211

0.98

.1724

250..

Pime Rat~* -.0060 -.0231

Tetitie Sqmd 1.62 1.59

Pretiow Tmtig*

Tenue -‘

.0263

3.40

.0240

3.11

ReviotiTfi-- -.0021 ..0017

Tenue Sqw& 1.57 1.28

Monti ~tiae .00W3

Requtied*Tmwe

.omo3..

1.00 0.90

Sqwed

N 20,974 20,974

(contiued on neti p~e)

60
Table 2S W~+Tenum Pmfiles with Pemon+petific rued Effec@

(mnttid)

~ 2

Log Embtishmt -.0010 -.0015

sti*Tau 0.52 0.73

hg Wbtistient Sti=TmW -.00002 .oom9

Sqd 0.06 0.24

Ution8Tmue -.0031 -.0029

0.34 0.31

Ution*Tmme Squ& -.0019 -.omo

1.21 1.28

Tlp*Log Sti*Tmwe .M13

2.78

Tip*bg S&~mwe -.0005

Sqwd 0.21

Bonw’hg Sti*Tmti .0031

0.61

Bonus*hg Ske*Twti -.W05

Squd 0.55

COtissian*LOg Sk* .0199

Tenme 1.85

COtissiOn*bg Sue* -.0055

Tmwe Sq~ed 2.52

Pi-e Rate*Log Sti*

Tenwe

-.0295

2.40

Piwe Rate*Log Sue* .0033

Tmue Sqmed 1.34

R3qti .211 .213

N m.974 20,974

~e &h *t comi~ of 5624 workm obs-ti fm up to 7 y- 19S4-1990 on tbti 1989 job. RWndmti

m clmstied =ordhg h metiti of pay - h 1989. Y- dti= ticludd but not ~OW.

61
Table Z4 %cond St~e Pemon+pwific F&ed Effed W~e Regressions

{absolute value of bstatisdu below wtimates)

(1) (2)

Tips -.1173 -,2488

15.81 14.48

Bon- .0692 .0611

18.90 6.77

Codsm .0217 .0013

3.80 0.12

Pie- R* .0063 .1285

.82 6.77

Tips*Utim .0202

0.94

Bonm Wtion -.0136

1.34

COhssiOn WtiOn -.0073

0.35

Pie= Me* UtiOn .0239

1.40

UtiOn .0029

0.79

Tips*Log Su .0384

8.07

Bonus*hg Sti .0024

1.43

COtission*LOg S&e .0083

2.49

Pl%e Rak*Log Sue -.0274

7.20

Log Es@blishmt Ske .0034 ..0027

5.10 3.73

N 5264 5264

.0025

.75

62

Table 3.2. Multinominal hgit Estimatw for Ocmpation

@*tistim below mefficimk)

N=5481; LLF=W39.62 :-

Sal=. exe. C&m=- @cmtom.

Cl* or Clerk or %mkd Fa~ri=to~,

Ctia Cstia Smiws ma *1= tid tih=m

Finale 1.74 -.418 ,725 -.465 -1.194

3.@7 -2.103 3.190 -2.516 -7.281

Blwk

Msptic

Black*Fde

Mspti-c$

Female

AFQT

*QT*Fde

AFQT*B!a.&

AFQT*

ws~c

AFQT*

ws@c*

Female

AFQTTBlwk*

Finale

Edumtion

Experience

SMSA

.963

1.235

.806

1.206.

-.306

4.370

..806

-1.050

.0006

0.028

-.W.

-1.775

-.056

-1.723

-.027

4.85

.014”

0.387..

..098

2.728

-.750

-9.729

-.166

-3.562

-.710

-,200

4.743

-.238

4,906

-.003

4.009

.188

0.494

,-.001

-0.212

-.004

4.417

-.009

&.662

.020”

1.498

-.043

-1.993

.020

1,058

-.352

-8.71S

-.024

5.915

.03 I

.138

0.344

-.376

4.968

-.351

4.729

.M4

0.731

-,o16

-1.691

-.010

4,838

-.035

-2.057

:.006

4.339

.010

0.402

.052

2.402

..618

.11.414

-:032

5.986

.162

.no

2.955

-.206

4.797

-.18.5

5.558

.2977

0.8M

.-.031

4.654

-.019

-1.986

.-.020

-1.789

.ml

0.083

.030

1.417

.033

2.063

-.629

-14.478

-.090

-3.425

-.W

.675

.3.263

-.210

4.980

-.350

-1.144

-.626

-1.491

.-.031

-S.388

-.009

-1.098

:-.011

-1.094

-.003

4.3H

..037

2.404

.a37

2.404

-.774

-20.077

:.040

--1.760

-.919

-3.070 0.191 0.801 -3.719 -7.228

Dab we Gom tie 1989 NLSY. me model alw ticludes vtiables fir re~on, mtibl ~tis, ad nuk of

cM&en h tie howehold. b tidition to the mupatiom show akve, tie multiotial Iotit mtiel

hcluded cltid (CLE~CM) , mmagtid, professional md tectid ~, ad prduction, mti ad

r~ak workem @R). Mmwtid, professional ad kctid workem ~ m-rnprised tie oti~

ocmpation.
Table 3.3. P~dIctid Pmbabitity of Emplo~at in %Iected Oaupations by Ram and &nder

pa mt)

~te ~Ie %k Black Wle Blwk m-c

Finale

m~tic

Finale we Fmde

Sales Clak

md .42 3.8 .75 5.4 1.2 3.7

Cmtim

Otier Sds 9:0 7.7 5.5 4.8 .8.4 6.6

CtiOmerMenti 2.9 9.0 2.3 5.4 2.5

Stim

8.1

Othm 8.9 ..9.0 n2 I 12 9.1

s&w

9.3

6S
Table 3.4. Percentage of Wortim Eaml~ bcentive Pay Within

&lecti Occupations, by Wce and finder

kupatiou mte Wte Blwk Black E@c

Mde

Mwtic Fc

Femle We FmAe Mde Finale

Sda Clerk

md 11.1 4.0 37.5 14.2 37.5 18.7 3.54

hfim

Otier Sal= 61.8 35.3 51.7 40.0 48.7 4.0,0 5.32

Cubmatiati 51,1 62,2 40.0 27.9 46.6

Seti&

44.8 4.17

Other 9.4 92 11.1 15.7 8.1 3..5 .95 sem&

~rato=,

Fabrimtom 14.3 26.0 22.4 28.5

hborms b

14.8 20 4.19

Al 23.0 21.1 21.6 19.8 20.7 18.6 ‘1.10

&cupatiom

Dah=e tithe 1989 ~SY. 1980 Cems OcmptioncodesuemeL CeHstive the~-@eof

. .

works h a ~vm rxdgmder sow ad omupation do - hcentive pay,

ahclu&s re~ontiBaployed hpmoti smices (1980 Cmm Cod~456469)mdm wtit p~m

b~etiem, restimmt suptisom, mdho~(433435, 438, 443 U). kaddition, tis=tego~ticlti

opemtm, fabrimtommd Iaborwskpubhc occupatio~ tiab tivasmd tiv~da work= ~~

s~ce occupations, not ticluded kcwtmm orimtd swices, weprotetive, hdm private howhol~

md otha fod tiCM.

b The foUotig motor vehicle op-tom were raovd tiom this mtego~ ad placed ~ tiomw+rimti

xwic=: M mb tivem ad tiv~-~les workms.

c T- the hypotimis that no titiwcupation d~erm=i “mtie ticidence of timtive @y ~

66
Table 3.5. Pmbit Estimatu for hcentive Pay+al= Workem

(Z shtlSf~& .&low ~fficimt etiates)

Q

Female

(2)

-.5.n -1.10

4.318 -2.659

Black .177 1.89

0.935 2987

MQT

.131

0.716

.217

0370

.006

1.491

-.026

-0.665

.021

2.997

-.013

-1.820

.-.0.07 . .

4.662

--.017

-1.661

-,101

-1.506

.151

1.816

Log Esbblishat Ske*Black -.266

-2.251

(conttiud on nem page)

67
Table 3.5 Probit Estbates for bcentive Pay4ales wofiem

(cmti@)

(1) (2)

Special E~rimm a .175 .504.

1.325 2.364

Special Ex~enw*Wsptic

SWA

SMSA*Fmle

SMSA*Bl=k

-.022

.039

SMSA*MWtic

.073

1.608

tig, Mmufactig> &

Molesde Sties

.216

0.328

.1.489

2.148

1.125

1.749

.906

1.331

-.671

-2.464

.344

1.010

-.08S

4,245

.-.144

4530

-.679

1.927

-1,066

-2.268

-.236

4.486

,og5.

1.787

.208

0.311

1.746

2.475

1.301

1.997

1.U6

1.630

Sales Supemisor or Sales .639 .777

Engtiem 1.000 1.199

u -296.83

N

-282.57

539 539

region of residmce, ~tim-, job time, mtitil sh~, md nmbm of ti&m k the ho~hol~ tich

we not show.

a ~wff to the question. “(Do) you hve to have mme WO* exptiaw 01 ~ecid

&fig m get (tie) job?”

6S
TabIe 3.& Probit Estimst- for hcentive Pay+tice Worhm and Opeutom,

Fabricator, and fibomm

(Z-WtistiG beIow cm5cimt ~ak)

Sti= Workm -tom, Fabrimtom, md

bb

Female .Zz -.140

1.052 4.994

Black .319 .304

1.483 1.992

Mwtic -.002 .078

4.008 0.399

AFQT .0147 -.001

2.381 4.370

SpecM Exptimce Rwuti .337 -.041

2.681 4.426

Cwtomm-Oriated Sai~ 2.54

3.971

69
Table 3.6 Pmtit Estimates for hmntive Pay-Sefim Workem and Opemtom,

Fabricator, and Laborem

(L-tistiii blow coeffi.imt estiaks)

(wnttiued)

Smiw Wotia -tom, Fabriwtom, ad

bborm

Fmle*Cwtimer~rientd

Semiw

-.035 .,.. -.

4.125

Black* C@omm-tienkd -.958

Swiws -3.359

Wsptic*ktomer@rimEd -.26g

Smic- 4.700

Jtibri~ufldtig Sefiws 1.257

2.058

Hdti Smicu 1.565

2.526

PrOtmtive Setices 1.476

223

cook .971

1.585

Tmck, Bw md Otier ~va ‘“.801

3.OM

Tetile, Appwel, md 1.491

Ftistigs ~~tom 6.911

70
Tab[e 3.7. Mean hg Wages by WC% %X and Method of Pay, Seleded Occupations

(N, Mm, S)

a @emtos. Fabritiors. md Stice Works Sales Workem

hmtive hmtive hwtive

Pay Ttit Rate Pay The Wte Pay Ttie Mk

Wte Wie 62 3.69 36 . ... 147 108 74

2.03 2.08 2.01 1.95 2.43 2.12

.39 .38 .49 .47 .51 .48

~te 45 128 81 141 48 132

Female L79 1.81 1.78 1.67 2.10 1.77

.35 .35 .45 .46 .57 .43

Black Mle M 221 23 119 18 19

1.98 1.95 1.86 1.86 2.05 1.84

.4 .43 .57 .37 .47 .48

Black 26 6S 31 133 20 S7

Finale 1.8S 1.81 1.66 1.65 1.80 1.61

.3s .37 ,35- .435 .31 .33

Ms@c 21 120 11 S3 23 26

Male 2.25 2,05 2.05 .200 208 2.00

.36 .44 .58 .46 .6”i .47

Msptic 7 28 14 43 “13 28

Finale 1.86 1.72 1.9s . 1.83 1.82 1.86

.24 .38 .s4 .% ..3.3 .. .s6...

Dam m fom tie 1989 moss wction of tie WY. 1980 G- &cupatioml md= ae A. Rapndmk ze

clsfid acmrtig m &e& 1989 metiods of pay md ompatiom.

71
Table 3.8. hcentive Pay Wage Premia by Race and Sex

O= Coefficient Estimat--Dependent Variable hg Wage

(t-statistics blow -fflcient mttib)

Pie= Wte .081 Bonw*Fmtie .003

1.698 0.124

Bonw .053 Bonu*BJack .012

2.542 0.383

.010

0.262

Tips -.076 Tips*Femde .101

-1.509 .. . ...1.885

-.109 Tips*Black

-8,456

-.126

:2.073

Black -,026 Tips*~Wtic

-1.909 ..2°:4:

WSptic :.042 Co6ssion*Female -.072

2.686 -1,628

Piwe Rate*Femde -.104 Cotission*Black -.070

-1.748 -1.353

Piece Rak*Blmk .031 COtisSOn*Msptic -.171

0.517 -2.830

Pie- Rate*fi~tic .219 AFQT

2.135.

..003

.9.967

Edumtion .044

shtus, .Werienw, ex~rience sqtied,” du-tion, ta~e, tenwe- sqw~, tion cove&e, log

estiblishat stie, dti= tidimttig @Mg reqti~eik, ntik of ctitien ti the househoId, region,

SMSA, govemat mplo~mt, regim of risidence, tie AFQT rmidti md Iod memplo~ent mti.

72
Table 3.9. hcentive Pay Wages by WE O= Esttiati

Dependent Variable: ~ W~e

(t-sbtitiw below coefficiat tie)

Black or Mwtic Black my Non-Bw Non- -

E*tic

Rece W .292 .303. .072

0.720 0.671 0.224

Cotision .097

0.323

Bon= -.357

-2.205

mp .184

0.572

~QT .005

10.162

EduwtiOn ,036.

6.237

WQT*Pime Rate -.002

4.862

MQT*.Cotission -.00006

4.034

NQT*Bonw -.002

-2,052

~QT*Tip .Owl

O.O6O

Eduution*Piece Rate -.018

4.587

~utiiOn*COdssiOu -.002

4;095 .:

Eduation*Bonw .032

2.694

Mu~lion*Tips -.024

4.943

F 42,00 29.07..

N

56.17. --

2248 1418 3225

Dak me tiom tie 1989 -Y. V~abI~ for mupation, hdmW, maplo~mt rote, S~A, job titig

Xqutiaenk, tenwe, hue ~me~ X% mtibl s~, ~erimm, e~ace qmea nuti of

cM&m ti tie howehol~ region, tion cover~e, estibEsbmt sti, ad gove-mt we ticludd but not

tiow. The vtiable ~QT is tie msidml of a regession of &w MQT tire on ~e h 1980.

.728

1.932

-350

---1.719

.189

“-~“0.470

.004

6.727

.043

5.529

-.002

4.743

‘-. :005

1.848

.-.003

-2X6

.0007

0.287

-.023

4.660

-.041

-1:533

.029

2.018

-,026

4.796

,012

1.295

-.0143

4.769

-.&1

-3.565

-.135

-1.056

.156

O.m

.004

8.113

.M2

8.742

.003

1.190

-.003

-1.756

...0008

Oml :

4.01

0522

-.005

4204

:059

4.315

73
TabIe 3.10. hcentive Pay Wages by Sex-OU Estima&s

Dependent VatiabIe hg Wage

(t-mtistics &iow cmffic~tit--tiates)

Meu Womm

Pi@e ~k .511 -.327

Bonu

1.310 -1.133

: ‘“ -.485

-2.577

-.29s

-1.170

-.362 .022

-2.877 0.149

T1p -.076 .306

4.234 1.331

mQT - :003 .W3.

8.305 7.034

Edu=tion .038 :044

7.612 8.276

.0?9?.

0.255-

-302

4.996

NQT*COdssiOns -.0004 -.003.

4.325 -1.548

NQT*Bonw -.0018 .Ow.> .. .

-1.748 0.666

.002 .001”

1.224 0.710

Edu=tion*Ple= Mte -.032 .025

.1.018 1.073

Edu=tion*Coti”ssion .045

3.195

.029

1.571

Eduation*Bonm .033 .002

3.486 0.253

Edumtion*Tips .0013 -.017

0.053 -4.967

F 47.52 39.88

N 2900 ‘ .“ .’ “ 2573

Dab %Ctiom the 1989 WSY. Vtiables for occupation; tid~, m.mplopmt rote, S~A, job Wg’

requtiam~, tmwe, tenwe ~we~ black, Wsptic, mtiti sti~, exptimm, ex~mce WWeL

nm~ of cMtim k the howehold, region, tion cove~e, eshbfish=t stie, md govmmt a

ticluded but not show. The vtiable ~QT is the r~idml of a re~mion of ~QT score, @ ~c~tfl:

tits, on age k 1980.

74
TabIe 3.11 Wage Gaps by Method of Pay and OccupatiOnOM Estiams. DeDendent Vadablg k Wage

Finale -.080

4,559

Black -.037

-1.980

msw-c” .019 -

0.988

Femle*P -.o56

-1.775

B1wk*P .030

0.772

mptic*F .052

1.163

OFL*P -.113

-2.387

Female*O~ -.068”.

-2.W5.

Female*P*OFL .237

0.569

Black*OFL .001

.033

Black* ~*OFL ,028

0,423

Msptic*om .019

0.506

mptic*P*oFL .078

0.875 -2.S23

F

,..

14.48.

Female* fP*Ctiomm.

mmtd Stica

Black*P”CwtmerWentd Stim

Fetile*Sale

FemaleT*Sales

“Black*Sdm

Black* P*Sales

msptic*P*sdes

-.095

-1.330

.189

1.930

.064

0.913

-.252

-2.255

.201

2.292

-.136

-1.066

.126

2237

-.05s

-1.176

-.008

0.111

-.04s

4.762

-.052

4.525

.006

0.104

-.2S7

75
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02

03

05

06

07

08

09

10

11

12

13

National Lon@tutinal Surveys (NLS)_

D=cwion Paper Seriw

m

Michael R. Pagtit

Nomm. M. Bradbun

M~n R. Frakel

Regitid P. B&er

Michael R. Pergtit

“.SaulSchw~

Robeti Hutihens

Gmrge J&bson

Frti L. Mott

Paula B*er

Au&ey Llgbt

Mmuefih Urem

~Sa M. Lynch

E~mgelos M. Falmk

H. Efiubeth Peters

Anne Hill

June E. ONeilI

Lee A. L~lad

Joseph G. Atonfi

Thomm A. Dunn

m

How the Ftieti Govement Us= Dam from

the National hn~mdinal Smeys

A Comptision of Computer-Assistd Pmsond

Intemiews (CAPI) with Papm-md Pencfi Interviews @API) in the National hngitutid Smey

of Youth

Dyntic Models of the Joint Dekfination of

bbor Supply ad Ftily Stictu~

The eff=b of Unemployment COm~nsatiOn

on b Unemployment of Youth

Evaluating Competing ~eories of Worker

Mobifi~

Evaluation of the 1989 Ctid-c=e Supplement

h the National hngitudlnal Suwey of Youth

Gnkr Differemes h the Quit Behavior of

Young Works

The bpzt of Privwe Sector Ttifing on Rwe

md Gender Wage Differentials md the Cweer

Patterns of Young Workers

R=pons= of Fade Labor Supply ad Fetii~

to the Demo~apbic Cycle

A Study of Intercohofl Chmge in Women’s

Work Patterns md Etings

Women’s Emplo~ent Dufing Re~aW

md Following Bfi

Work Expedience, Job Tenure, Job Sepwation,

md Wage Gowth

Ftily Bmkgmund ad Labor M~ket Outcomw
14

15

16

17

18

19

20

21

22 ““ “’:-”‘-

Gmrge J.B@m

Stephen G. Bmnms

Stephen J. Trejo

Jaw J. H=tim

Stephen V. -eron

Peter Z Schochet

R. Mwk ~Iw

Thomm MaCmdy

Am L. Gus~an

Thow L. Stetieier

Au~ey Light

Ctistopher J. Ruh

Mmk bwenstein

Jues Splewr

.SeF,Selection ad Intemd Mi~ation in the

Utitd sum

P~cipation in hw-Wage hbr Mikes by

Young Men

Re&ement in a Ftily C&n@xc A S~ctmd Mdel

for Husbm& md Wives

Trmsitions from Schwl to Work A Smey of

Resewch Using the National bngim~d Smeys

Mgh Schml hployment Consumption or

lnves~ent

Infoti Trtiting A Review of Existing Data ad

Som New Etidence

Chx=kriting Leave for Matity: Mtietig tie

NLSY Dati

Emplo~ent Continui~ bong New Motie~

-.