me NationalLo@tiM Swqs WS) pro- SUPP- may s~di= desi~ed

ti tier-e wdashtig of the labor ukd ad metho& of && m~ection. me

Disassio. Papers stia rnc~ra-s some of the r=e=ch cofig out of the pm~m.

my of the pyrs h this stim have bem dtivwed as fti repotis mtissiond as

pd of m e~awd gmt pro~m, mdm whiti ~mts we awwded tiough a

competitiveprwess. me *es is btmded to ctiulate the titigs to hta~ted radas

tithin md outside theBueau ofLaborStatistics.

Paom tit=-ted k obtiting a copyof my DiscussionPapm, otherNLS repo~,

or gmmd Momtion aboutthe NLSpmgm md =eys should contict the Bw=u of

Labor S*tistics, O~ce of Econtic R==cQ Wastigton, DC 20212-0001, or dl

(202) 606-7405.

Mttid h MS publication is ti tie public doti md, tith appropriak crdit,

maybe re~duced titbout pefission.

Optiions md mnclusiom e~r-sed h this docmmt xe those oftie author(s)md

do not nwesstiy rqramt m offlcid position of the Bw=u of LaborShtistics or the

U.S. Dcp*wt of Labor.
The Intergenerational Effects of Fatherlessness on

Educational Attainment and Entry-levd Wages

Jeff Grogger

Nick Ronan

Department of Economics

Universityof C~ornia

SantaBabar~ CA 93106

(805) 893-4533

je~econ.ucsb.edu

Find Report to the Bureau of Labor Statistics,

September 1, 1995.

We thankworkshop participantsat the BLS for helpfil comments. The opinions

apressed in ttis report are solely those of the authors. They do not necesstily represent

tie positions of the Bureau of Labor Statistics,the Departmentof Labor, or any other

government agenq.
Executive Summa~

h 1960, otiy five percent of dl birthsoccurred out of wedlock and ody 13

percent of d childrenfived in a sirr~e-parentftiy. By 1990, increasingdivorce and outof-wedlock ctidbearirrg had raisedthese figures substantidy more th.mone-fourth of dl

biihs were to unmarriedmothers, and 27 percent of M childrenKvedwith ody one

parent. Bumpass (1984) predicted that, as a rwult of risingdivorce and non-mariti

fefity, 50 percent of W childrenborn as earlyas 1980 wodd spend part of their

childhood in a fatherlessftily.

Asuuring thatworkers enterthe labor marketat age 20, and thatthe worHorce

turnsover every 40 years,these demographic trends implythat,witi the next 20 years

or so, rou@y one-fourth of the labor forced have spentpart of its ctidhood in a

sin~e-parent home. Put differently,thismeansthatwithinthe next couple of decades,

there *be as may workers who grew up fatherlessas workers who hold co~ege

degrees. The fraction of the labor force thatwas raisedin a single-parentftily ti

undoubtedly exceed tie fractionthatis unionixed.

Thwe Wendsin fmnilystructuremay bode dl for tomorrow’s labor force, atleastif

the predictions of economic theory are correti k Becker’s(1981) model, for example,

cMdren raised in fdes with fewer resources tend to have Iower humancapitrd. Thus

econofic theory would predictthat,M else equ~ the next generationof workers wiu

enter the labor marketwith less humancapitrdthanthe last.

The objective of this study is to estimatethe effects of fatherlessnesson the

ctidren’s educatioti attainmentand entry-levelwages. We consider an important

methodologicrd issue not addressedby previous researche~ unobsewed heterogeneity

across fties. One can imaginethatfamifiesvary ~eatly in a numberof ways thatare

unobsewable to the amlyst. Moreover, manyof theseunobsemable tily characteristics

are hkely to be correlatedboth with the probabilityof divorce and with the well-being of

the cMdren. Thus a cross-sectioti regressionof children’s educatiod attainmenton a

measureof their childhood familystructurefails to identfi the effects of tivingin a

fatherlessfamily,because the effects of fatherlessnessare confounded with the effects of

the family-specificunobsewables. We wodd generallyexpect such unobserved

heterogeneityto lead to exaggerated estimatesof the true effects of fatherlessness.

We adjustfor family-specificunobservable by makingwithin-familycomparisons.

Drawing on previous research we speci~ a child’s humancapiti to depend on the

numberof yeas she spends in a single-parentfdy. Because childrenenterand Iave the

family at differenttimes,the durationof a spefl of fatherlessnessgenerallyd vary among

sibfirrgs.To efirninatethe effects of fatiy-specific unobservable, we difference the data

withinfarnifies,relatingdifferences in humancapiti to dflerences in the durationof the

fatherlessspeu.
WspeUswere measuredaccurately,then &aencing withinf~es wodd provide

vdd estimatesof the @ects of a year of fiherlessness. Our dati on tidhood Eving

arrangementsare measuredretrospectively,howevw, and there is evidence of a fair

amount of measurementerror, partictily in the &aend da~ Under strmdard

assumptio~ measurementerror causesthe estimatedregressioncoefficients to be biased

downward.

The usti solutionto thisproblem instrument variablesestimatio~ performs

poorly in this case. The approachwe adopt instmd is method-of-moments estimation.

We implementthisapproachby using sibhg comparisons to estimatethe extent of the

measurementmor in our retrospective data.

The data are takenfrom the~SY. This richlon~tudmrdsurveyhas seved

importantfeatureswithout which our anrdysiswodd be impossible. FKs&rou@y Mf of

itsmembers have sibkgs who dso took partin the swey. Ittherefore offers samples of

sibbgs thatare large enough for mdngful anrdyses. Secon& it has detded information

on the ctidhood fivingarrangementsof its respondents. F1ndIy,its participantshave, for

the most part, completed theireducation. Thuswe can dyze the eff~ of fitierlessness

on c~dren’s ultimateeducatioti attainment,ratherthanintermediatemeasureswch as

high school graduation.

For whites we findthatfatherlessnesshas a negative effect on educatioti

attainmen\regardess how we estimatethe models. Moreover, althoughthe estimates

v~ somewht, ~ we significant,at leastatthe 10 percentlevd of cofidence. Thus for

whites, the evidence is clem longer spellsin a sin@e-pment familylower ducatioti

attakunent. The ordy question concerns the precise magnitudeof thisnegative effect. We

fid some evidence thatis consistentwith theunobserved heterogeneityhypothesis but

we rdsofind evidence of measurementerror. On the basis of a numberof tests, we cannot

rule out the explanationthatthese two countervai~ig specificationerrors simplycancel

each other out. Our best estimateis thateach additiond year of fatherlessnessreduces the

chil&s education attainmentby six-tenthsof a year. Since the typid fatherlessspe~

hts about nine years, we conclude thatthe typicalwhite ctid in a sin@&p~ent family

will acquire about one-~year less educationthanshe wodd have had her parents

remainedtogether.

The picture is similarfor Mspanics: additiomdyears of fatherlessnesslead to lower

educationrdattainmen~and the estimatesare largelysitiar regardlesshow they are

computed. Because our samplesof Hsptics are smallerthanour samplesof whit% we

mustnecessarilybe somewhat more cautious about our conclusions. To a great dent,

however, the typicrdMspanic ctid who spends time in a singlep~ent familyfaces

disadvantagessimilarto those of hiswhite counterparts. On average,Mspmric children

who grow up fatherlessacquire one-half year less educationthanthey wodd have if they

had they Evedwith both psrents.

u
For blacks the resultsare most surprising. Our unadjustedestimatesindicatethe

typical pattern longer spellsof fatherlessnesslead to lower education attainment. When

we control for ftily-specific unobservable, however, the estimatechanges sign.

Furthermore,it is difficultto attributethis occurrence to chance, since the adjusted

estimatesare statisticrdlysignificant. Thus on the surface, our estimatessuggestthatblack

ctidren who five in single-parenthomes actudy acquiremore education thantheywould

if they Evedwith both parents. This resultis pu~g, and calls for firther study. Indeed,

untflitis cotied by futureresearch it best to view this fiding as tentitive.

Because fatherlessnessreduces education attainment,at leastfor whites and

Hspauics, and because education is an importantdeterrnirmutof adultwages, we expect

thatfatherlesswould contribute adverselyto the children’s adultearningsas wefl. When

we ~yze the effects of fatherlessnesson wages directly,however, the evidence is mixed.

Nthough the unadjustedestimatesare typicallynegative, estimatesthatadjustfor family

effects are eitherpositive or negativebut very srnrdl.Adding firther to the difficultyin

interpretingthese results,the adjustedestimatestypicdy are insi@ficaut.

We swpect thatthese mixed resultsstem from the natureof the wage dati

avtiable in the NSY. my necessity,the ~SY includes ordy entry-levelwages, which

for a number of reasons maybe rathernoisy compared with the wages of prime-age

workers. We conclude thatit would be best to revisitthis issue with data on older

workers.

... m
L htroduction

b 1960, ody five percent of W btihs occurred out of wedlock and ody 13

percent of dl childrenfived in a singlepsrent fdy. By 1990, inereasirrgdivorce and outof-wedlock childbearinghad raisedthese fi~res substantirdlymore thanone-fourth of dl

btihs were to unmarriedmothers, and 27 percent of d cfildren Evedwith ordy one

parent. Bumpass (1984) predictedthat, as a rault of tising divorce and non-mariti

fertifity,50 percent of all childrenborn as earlyas 1980 would spend partof their

childhood in a fatherlessfamily.

&surning thatworkers enterthe labor marketat age 20, and thattie workforce

turnsover every 40 years,these demographic trendsimplythat,withinthe next 20 years

or so, rougtiy one-fourth of the labor force will have spent part of its childhood in a

single-parenthome. Put differently,thismeansthatwithinthe next couple of decades,

thereW be as manyworkers who grew up fatherlessas workers who hold college

degrees. The fraction of the labor force thatwas raisedin a single-parentftily will

undoubtedly exceed the fraction thatis uniotied.

These trends in familystructuremay bode dl for tomorrow’s labor force, atleastif

the predictions ofeconornic theory are correct. InWeiss andWilfis’ (1985) mode~ for

example, an absentfatherinvestsless in his childrenbecause it is difficultfor him to

monitor how the mother allocates his financirdcontributions. Becker’s (1981) model dso

predicts that childrenraisedin farni~eswith fewer resources d tend to have lower

humancapital. Thus economic theory would predicttkt, dl else equrd,the next

generationof workers till enterthe labor marketwith less humancapitrdthanthe last.

1
Against thisbackdrop, itis surprisingthatso few economists have stutied the

intergeneratiomdeffects of familystructure. Nevertheless,previous research conducted

primarilyby sociologists, largelyhas cofied the predictionsof economic theory.

Researchershave found that childhood fatherlessnessdecreases educatioti attainment

and adultwages, and has adverse effects On a numberof other socioeconomic outcomes. *

h importantissuenot addressedby previous researchers,however, is unobserved

heterogeneityacross farnifies. one can imagine thatfarnifiesvary greatlyin a numberof

ways thatare unobservableto the analyst. Moreover, manyof theseunobservable

characteristicsare hkelyto be correlatedboth with the probabilityof divorce and with the

we~-being of the children. Thus a cross-sectional regressionof children’s education

attainmenton a measureof their childhood familystructurefds to identifythe tiects of

fivingin a fatherlessfatily, because the effects of fatherlessnessare cotiounded with tie

effects of the ftily-specific unobsewables. We would generallyexpect such unobserved

heterogeneityto lead to exaggeratedestimatesof the true effects of fatherlessness.

The god of this study is to distinguishthe effects of observable spells of

fatherlessnessfrom the effects of unobsemable ftily-specfic characteristics. We do this

by makingwithin-familycomparisons. Drawing on previous research,we specfi a cM&s

humancapitalto depend on the numberof years he spendsin a sirr~e-parentftily.

Because childrenenterand leave the fdy at differenttimw, the durationof a spe~ of

fatherlessnessgenerallywifl vary among sibfings. To ehminatethe effects of ftily-

...

1 McLanahan, 1985, 1988; Hogan and Kitigsw~ 1985, Kre@ 19S6; Keith snd Rday, 19S8;

Krein and BelIer, 19S& McL*n and Brrmpass, 19S& ~one and Mc~ 1991; Li and

Wojtietiq 1992; Wojtietiq 1992 and Havenran and WoEe, 1994,

2
spectic unobservable, we difference the datawithinfamifies,relatingdifferences in

humancapitalto differences in the durationof the fatherlessspell.

Espells were memured accurately,then differencingwithinfamifieswodd provide

consistent estimatesof the effects of a year of fatherlessness. Our dataon childhood hving

arrangementsare measuredretrospectively,however, and there is evidence of a fair

amount of measurementerror, particularlyin the difference data. Under standard

assumptions,measurementerror causes the estimatedregression coefficients to be biased

downward.

The usual solution to thisproble~ instrument variablesestimatio~ performs

poorly in this case, for reasons we discuss below. The approachwe adopt insteadis

method-of-moments estimation. We implementthisapproach by using sibfing

comparisons to estimatethe extent of the measurementerror in our retrospective data,

The resultsare somewhat mixed. For whites, we find thatthe estimatedeffe~s of

fatherlessnesson educationalattainmentare quite robustto changes in the specification.

For blacks and Msparrics,simpleOLS estimatesare negative,but the estimatesthat

account for possible model ruisspecificationare generallyquite variable.

~ Data

We use datafrom the NationalLongitudind Surveyof Youth @S~, a national

panel study of 12,686 youths who were 14 to 22 years old in 1979. Survey respondents

have been titetiewed annuallysince 1979, and asked questions about their fiving

arrangements,education, and earnings. Our study makesuse of two specialfmtures of

the NLSY its subsampleof sibhngsand its 1988 retrospective on respondents’ childhood

hving arrangements.
Our primarymeasureof childhumancapitalis the respondent’s level of education

at age 27, Measuring education attainmentatthisage hastwo benefits. Fust, most

people have finishedtheireducationby the~ so educationat age 27 essentiallymeasures

completed education. Second, dl mSY respondentshad turned27 by 1992, the lastyear

for which education datawere available. Thuswe are able to use as many obsemations as

the surveyprovides.

We dso study entry-levelwages. Here we use average wages, e~loiting the

longitidmd natureof the survey. Specifically,we average dl vtid wage databegitig

bee years after the respondentlefi school, and efiendmg untilage 27.2 Using average

wages should add to the precision of our regressionestimates,wtich is particularly

beneficial due to the noisinessof entry-levelearningsdata

h 1988 the suwey asked respondentsabout theirfivingarrangementsfrom birth

through age 19. From this retrospectivewe constructed our primarymeasureof family

stmcture the numberof yearsthatthe respondentfivedin a fatherlesshousehold.3

Actually,this definitionis sfightlytisleadmg, because our ‘years fatherless”variableis the

total amount of time duringchildhood thatthe respondent spentfivingin ~ back to

original] a mother-ody, father-ordy,mother-stepfather,or father-stepmotherhousehold.

For the most part, however, thisvariablecapturestrue fatherlessness,since time in a

father-osdyor tither-stepmotherfamilyaccounts for less than 10 percent of the toti

number of years spentin the absence of atleast one biologicrd parent. Note thatby this

2 Forthoseinditiduak who had completed fewer than 10 years of schoofin~ we average did

mge data from age 1S to age 27.

3 =oughout thepaper,weusetheterms“fatherlesshousehold” and “sin@e-pment homehold”

synonymously, even though they are not qtite the sme thing, and nekher t- i3 e~tiy accurate.

4
defmitio~ fatherlessnesscan arisedue to an out-of-wedlock birth a divorce or separatio~

or the death of a parent.

We dso constructed a second familystructuremeasurew the number of years

duringcMdhood. spent Hvingwithout eitherparent. For the most part,these spells in

other, @ically non-familyfiving arrangements,were spentin foster homes, detention

centers, children’s homes, with grandparents,or with other relatives. We separatethese

relativelyunusualfivirrgarrangementsfrom the more common ftily-type arrangements

because our primaryfocus is on the effects of single-parentfamifiesthat arisedue to either

a divorce of out-of-wedlock birth.4

To estimatethe effects of fatherlessness,we exploit the sibfingsticture of the

~SY. h the originalwave of interviews,households were the primarysampfingunit

and d youths who met the age restrictionsin each household were drawn into the survey.

As a result,about hdf of the surveyrespondentshave sibfingswho are respondentsas

wall. To the extentthat sib~rtgssharea common familyenvironment,sibhg comparisons

can be used to control for unobsewable characteristicsof theirfkrnily.

Means of the various family structire variablesare presentedinTable 1, along

with the samplemeans of several other variablesthatwe include in the regression models

below.s The firstfour columns presentdatafrom the fill sample. We see thatwhites

obtain the most education on average, followed by blacks andWspanics in that order.

4 Whife we r=o~n that some of our “othef’ hving arrangemen~ partitily tith grand~nta

or other relatives, may come about as a reauft of an out~f-wdock bkth or a divorce, we ~clude them

tim ow main mmaure of fatherlmsneas bermme tkq may come about for ~erent rmamra as well.

Bscarrae there are relatively fw sample members in MS mtegory, mu redta are largely insensitive to mu

$hoice of how to classify tkem.

Appenti I explains mu apdIc sample inclusion criteria and how we wnatrrrti the variables.

5

—
Blacks, however, spend the most time in a fatherlesshousehold, fo~owed by Hsprnrics

andwtita. This bivariateevidence thussuggests thatthatthe relationshipbetween fkrnily

structureand education may vary by race. The lastfour columns of Table 1 present &ta

from the subsampleof respondentsfrom ntulti-sibhouseholds. For the most pm this

subsample,which wfil be the basis for most of our estimates,appearscomparable to the

fill sample.

~ Estimation

A. The Model

We study the effects of fatherlessnesson education attainmentand addt wages

using the regression model

Y>=Fp+Qfip+Pf+&fi, f= 1,...,u i= 1,...,Tf, (1)

where,yfi is the outcome variable(education attainmentor adultwages) of the ith child

in thefih ftily, Xflis the numberof years spentin a fatherlesshousehold, ~ is a vector of

background characteristicssuch as familyshe, matemd education, and birthorder. The

variablepfis the ftiy-specific unobservable, &fis a zero-mea i.i.d. &sturbancete~

and y and ~ are parametersto be estimated. SpecificMy, y measuresthe effect of a year

of fatherlessnessonyx.

This specificationmerits some dismssion. It may seem reasonableto posit that

time spentin differentfivingarrangementswould have differenteffects on the htian

capital of cMdreL and thattime in a fatherlesshousehold mighthave differenteffects

depending on the age of the child. h equation(l), however, we have constrainedthe

effects of d] ftiy-type fivingarrangements@esides the tradhiond two-parent family)to

be the same, and have ruled out any interactionsbetween fatherlessnessand age.

6
The support for these restrictionscomes &omWojtkiewicz(1992), who studied

the relatiorrfip between familystructureand high school graduationusing data from the

~SY. Wojtkiewicz explicitlyallowed for differenttypes of fivingmarrgementato have

differenteffects on the MeMood of graduatio~ and for age-dependence as we~. On the

basis of a numberof specification tests, he concluded thata simple specification that

constrainedthe effects of all non-traditionrdfamily-typefivingarrangementsto be the

same, and constrainedage interactionsto be zero, provided the same informationas the

more complex specifications. We have substantirdlyreplicatedWojtkiewicz’s result$ and

concur with his conclusion.c

This restrictedspecification greatlysimplifiesour analysis. Moreover, in the

presence of age interactions,our simpledifferencingscheme would no longer solve the

unobsewed heterogeneityproblem. Indeed our approach to the measwement error

problem would fail as well.

The firstproblem for estimationis thatxx and~f are fikelyto be correlated. In this

case, OLS estimatesof equation(1) are inconsistent. To efirninatethe family-specific

unobservable, we difference equation (1) withinfamihes,obtaining

Ayfi = hfiy + AQ3~ + A&3 (2)

6 Wojtiewicz’s classification of spell ~w ~ers from ous slighfly in fit he included spells

titi grandparents and other relatives in his main mwe of non-traditioti fiving arrangements (tin to

our yezra fatherless measure), whereas we include such spells in ou secondary ~other”) category.

Conqtily, our classification scheme betfir suits our prinraryf-, as &wsed above. As a prsctid

maner, however, tie WOclass~lcation schemes yield naly identicaf resrdts. Details are prtided in

Appendix D, along titi ou replication of Wojtieticz’s resrdts.

1
where Ayfi = yfi – y~ for some j#i, and so on. Provided that &fi is uncorrelatedwith

XX, w~ch mounts to assumingthat child-specificunobservabledeterminantsof

edueation do not itiuence the durationof the chil&s spe~ of fatherlessness,OLS appfied

to the sibkg-differenced datayields consistentestimates. Note thatequation (2) can ody

be fitted to the subsamplewith multiplesibhngsin the household.

h the case where the lengthof the fatherlessspell is measuredwith error,the

situationis more complicated. Suppose that, ratherthanobserving X8 diredy, we

observe Zfi = x$ + Vfl, where Vfiis an i.i.d. zero-mean measurementerror thatis

uncorrelatedwith Xj, Q3, and &$. In levels,the model is now

Yfi =YZ~. +Q>P +PJ +vfl..> (3)

where 7J = &fi- y VJ, and in differences, we have

Ay$ = &$y + AQ$~+ Aq> . (4)

Because ZJ is a fincfion of V$, and Vj appearsin the composite error term qfi, OLS

aPPfiedto the model ~ levels, equation (3), would yield inconsistentestimateseven if

years of fatherlessnessandthe family-specificunobservablewere uncorrelated. Stiarly,

OLS appfied to the dlfferenced model in equation(4) will resultin inconsistentestimates

due to correlationbetween Az$ and AVfi.

B. InstmmentalVariablesEstimation

The usual solution to the measurementerror problem is instrumenfdvariables

estimation. In fief in the case of paneldafq Wches and Hausman(198~ have shown

that,under plausibleassumptions,no efiemal instrumentsare needed. h levels, we could

8
.

simplyuse one si~s report of Zfi as an ins~ment for her sibfing’s report. Provided the

meamrement errorswere uncorrelatedacross sibfings,thiswould yield consistent

,..

esdrnatesso long as the fafily effect aid ‘the fatherlessspellwere uncorrelated.

E Xfiand ware correlated, however, thenwe must differencethe datato etinate

& In this case, the IV approach is easiestto illustratein the case of a fily with exactly

three c~dren in the sample. Mer differencing, the first observation will include data on

zf3 – ZfZ, the second ~11 include z~2 – zfl, ~d the ~d will include zf3 – ZYI>say. The

variableZfl is a vdld instrumentfor Zfi – Zfz, zp is a vflld instrumentfor Z7Z– z~,, ~d zz

is a vtid instrumentfor zJ~—Z$,.7 In pficiple, the panel stmcture of the data itself

provides allthe necessaryinstruments.

k practice, however, these instrumentsperform poorly in ttis particdar

application. The reason for this is simple the len~h of the thirdchifd’s fatherlessspell is

ody wetiy correlatedwith the differencebetween the spell lengthsreported by the first

and second children. In Mfiches andHausrnan’smodel, the panel d:mension of the dati

was time, so autocorrelationin the z’s generallywould imply thatthe regressor ~n

differences) and the instrumenton levels) woufd be reasonablyhig~y correlated. men

the panel dimension of the data stems from the presence of sibfings, in contrast, the

corre~tion between differences and levels can be quite low. In this case, N estimation

produces unsatisfactory results.

B. Method-of-Moments Estimation

7 Mternatively, mrder the homogeneity assumption tfmt the varianw of the measurement error is

b same for all sibfingq one codd use Z* as an instrument for Zmzp, Zflas an inatrmnent for Zmzfl, and

Zflas an i~em for Zwzfl.

9
For this reasonwe chose an rdtemativeapproach, method-of-moments-stirnatio~

which is based on a simplefact. AssumingthatZflis the ordy@s-measured regressor in

the model md M is uncorrelatedwithxx, the probabtity Emitof the OLS estimateof y in

equation (3) is given by

(5)

where V(vfi) is the varianceof Vfi,V(zfi) is the varianceof zfi,md Rj~ is the~ from an

aufiary regression of z on Q. Of cours~ dlfferencingallows us to rel~ the assumptions

thatthe unobserved familyeffect is uncorrelatedwith the fatherlessspell. The probtiltity

fimitof the OLS estimateof y tiom equation(4), the model in d~erences, is Qven by

[

2v(vfi)

plim(~d) = y 1-

1

V(kfi)(l - R;.a) ‘

where V(AZ8) is the varianceof Azfi and R:,. is the@ from an autifi~ re~ession of As

on AQ. The term V(&fi ) and the autifiary~‘s can be estimatedreaMy from the data.

K V(vj) can be estimatedconsistentlyaswell, thenone can constructthe method-ofmoments @O@ estimators

and

[ 1

2f(vfi) “

yd=~d 1– .

V(kfi)(l - R;,.)

(7)

(8)
hplementing the MOM estimatorclearlyhinges on obtaininga consistent estimateof

V(vfi), the varianceof the measurementerror.

The usual approach to thisproblem is based on replicatedmeasuresof the variable

of interest. Suppose thatZfland Zflwere both noisy measuresof the same latentvariable

~fiso zfi‘xfivfl adz> = xf + VP,where vx and VX, the measurementerror%are

independentof each other andXfi In this case,

cov(zf,,zf2)=V(Xr)/~~ =V(xf)/V(zf,), where thelasteq”fityholds

under the homogeneity assmption that V(V7,) = V(vf ~). Since the measurementerrors

are independentof xfiwe have V(vf ~) = V(Vf~) = [1- COV(ZJI,z,Z )]V(zf,),wtichcanbe

estimatedfrom the data.

A complication arisesin the familystructureproblem however, because ZflandZz

do not measurethe same thing. This is because sib~igs whose parentsdivorce, or whose

parentswere unrntied to begin with, generallywill spend differentamounts of time in the

resultingsingle-parenthousehold. To see this consider the three-cMd family depicted in

Figure 1. For purposes of illustration,we assumethatthe childrenwere born in 1957,

1959, and 1962, thatthe parentsdivorced in 1965, andthatM three childrenremainedin

their family of origin untilage 18.

Fisrrre1: A ThreeZhild Howehold

Sib 1

Sib 2

Nb 3

I I I I I I

11
Year 1957 1959 1962 196S 197s 1977 1980

Because the ctidren are dfferent ages atthe time of the &vorce, the durationsof

their spe~s of fatherlessnessdiffer. For the first child,the truelengthof the fatherlessspefi

is xl = 1975-1965=10 (the f subscriptis dropped for clarity),for the second child, X2= 12,

and for the thirdctid, X3= 1S. The children’s actualreports of theirfatherlessspells,the

z, terms, may dtier from the actualspells, however. h general,we would not e~ect the

report of the first child to equalthe report of the second child even on average, because in

the case of divorce, earher-bornchildrengenerallyexperience shorter spells of

fatherlessness.gThus the simpleapproach for estimatingthe varianceof the measurement

error outfinedabove will not work in this case.

The problem can be solved once we recode thatthe middle ctid spends his

entirechildhood in the presence of at least one of his sibtings. Thus for any subperiod of

sib 2’s childhood, both sib 2 and one of his sibfingsti provide repofis of the amount of

time thatthey spent in a single-parenthousehold duringthat subperiod. With ajudicious

choice of the particularsubpenod, we can ensurethatthe acturdtime in a singe-parent

fmnilywas the same for both children. Thuswe have replicatedmeasureswhic~ under

some assumptions,allow us to estimatethe varianceof the measurementerror over the

children’s entirechildhood.

To see this, note thatsibs 1 and 2 are presenttogether in the household between

1959 and 1975, and sibs 2 and 3 are presenttogether in the household between 1962 and

8

In the case of out+f-wedock childbearing, slier-bem ctidren genersfly till experience longer

*W.

12
rmdfor sib 3 we have X3= x; +x; + x:: SuperscriptOrefers to the time when sib 1 is the

ordy child present, and superscript4 denotes the period when sib 3 is the ordy child Iefi at

home.

Measured spells of fatherlessnessare given by z, = z; + z; + z~-snd accortin~y

for the other children,where z~ = <“ + vj. Within any subperio~ the true fatherlessspefl

is the same for all childre~ so xi = x: for all i#l. The independence and homogeneity

13

1977. Durirrgthe subperiod from 1959 to 1970, say, sibs 1 and2 experiencedthe same

spe~ of fatherlessness,lastingfor 5 years startingin 1965 and ending in 1970. During the

subpenod born 1971 to 1977, sibs 2 and 3 experiencedthe same spe~ of fatherlessness,

lastingthe entire6 years. &suming homogenei~, and provided thatthe measurement

errors in the children’s reports of subperiod-specific spells of fatherlessnessare

brdependentacross subpenods, the sum of subperiod measurementerror variances is equal

to the variance of the measurementerror over sib Ts entirectildhood. By homogeneity,

the variance of the measurementerror is the same for dl sibfings.

To forma~ie this idea, we divide sib 2’s childhood not into two periods but rather

into three, corresponding to the datesat which various childrenenteror leave the ftiy,

writing the length of time thathe spends in a fatherlesshousehold as Xz =x: +x$ +x:

(againwe drop the f subscriptsfor clarity). The 1 superscriptdenotes the period between

the birthsof sib 2 and sib 3, when sibs 1 and2 are the ody childrenpresentfi.e., 1959 to

1962 in figure 1). The 2 superscriptdenotes the period between tie birthof sib 3 in 1962

and the time when sib 1 leaves home, in 1975. The 3 superscriptdenotes the period

between 1975 and 1977, when sib 2 leaves the nest. For sib 1, we have xl = x: +x; + x:,
assumptionsinvoked in estimatingY(vJ ), where vf2 = v~z + v~z+ v~z and so fo@ are

given by

E[vj,v;]=O, for dl E i,j, s, andt, and (9a)

Y(v;) = V(v’) for~~~andt. (9b)

Together, (9a) and (9b) imply

V(vfi)= r(v’)+v(v’+’)+v(v’+’) . (9C)

Asumption (9a) impfiesthat: O) subpenod measwement errorsare unmmelated

across subperiods, both withinandbetween sibhng> and cl) ssm~subperiod m~urement

errors areuncorrelated across siblings. Asurnption (9b)says fiatthevariancesof

subperiod-specific measurementerrors arethessme for Wsibs. These irnply(9c), which

says thatthe varianceof the toti measurementerror is equalto tie sum of the variances

of the subperiod-specific measurementerrors.

To estimatethe subperiod-specific variances,difference the reported sub-periodspecific spells across siblings,forenmple, b}z =Z}2 -z},, k:, = Zj2 –Zjl , and

~~, = z;, – z~. Because the truthis the samewithinsub periods, V(&~,) = 2V(V’),

V(~~~) = 2Y(v2), and ~(~~j) = 2V(V3). Al of these quantitiescm be estiated from

the subsampleof ftifies whh threerespondent ctildren.g Thus our estimatorof V(VJ) is

ti(v,) = :[t(&})+i(&;)+i(&;)] .

9 We are not firrritd to using ody three-person households to ddate the vtian~ of tie

measurement error. In each family tith more than 2 respondents, there etist n~- 2 titerior sibkgs whose

reports can be oaed to estimate this variance. M each of these Wlies, we can compare the respooaes of

14
W. Results

~

Table 2 presentsOLS estimatesby race from the regressionof educational

attainmenton years of fatherlessnessand a set of background variableswhich includedthe

numberof years in a non-ftihd fivirrgarrangement,the ctid’s btih order, the mother’s

education, the size of the family,and a sex dummy. Chow tests failed to reject poofing by

se~ althoughthey strongly rejected poofing by race. The firstthree columns in Table 2

present resultsfrom the fill sample,whereas the lastthreepresentestimatesfrom the

subsample of multi-sibhouseholds.

Years of fatherlessnessare negativelyrelatedto education attainment,and for M

races, the relationshipis significant. The coefficient for whites is largerthanthe

coefficient for blacks, which is similarto the resdts of Kein rmdBeller(198@. The

coefficient for Mspatics is also smder thanwhites. To our knowledge, we are the fist to

report separateestimatesfor ~spanics.

Time in non-famifialfivingarrangementsrdsohas a negative coefficient, as does

birthorder, at leastfor whites and blacks. The findingthatlater-born sibs acquire less

education on average has been reported elsewhere@anushek 1992). Family ske is

stronglynegativelyrelatedto educatio~ consistentwith Becker’s (1981) model of the

trade-off between child qutity md quantity. The education of the mother is strongly

relatedthe education of her childreq althoughthe effect is stronger”for whites thanfor

blacks or fispanics. b general,the resultshorn the multi-sibsubsampleare similarto

those from the fill data set.

tkeinteriorsiblin~titk tie responsesoftkeWOadjacentsiblingsovertke3periodsasdefied above.

15
Let us now focus on the effect of ftiherlessness. Table 3 presentsvarious

estimatesof the effect of fatherlessnesson educationrdattainmentbased on the wbsample

of multi-sibhouseholds. In each case the regressionmodels includethe full set of

background variablesin addkion to years of fatherlessn~s. The fist row reports OLS

estimates,and so simplyreplicatesthe estimatesinthe lastthree columns of the top row of

Table 2. For whites, each addhiond year of fatherlessnessreduces education attainment

by 0.064 ”years,on average. For blacks, the figure is substantiallysmaller,edthoughstill

statisticdy significant. The estimatefor Msparricsfiesbetween the estimata for whites

and blacks, and is rdso significantlydifferentfrom zero.

The n% row of the table provides estimatesof the refiabifityof the years fatherless

regressor. The retitilfity is inverselyrelatedto the varianceof the measurementerror, rend

is given by

V(vp )

r,=l–~. (10)

The estimatedrefiabifitiesare fairlyhigh, For example,the refiabifityfor whites indicates

that ordy 13 percent of the varianceof zflis attributableto measurementerror, a

proportion thatvaries ontyhttleby race.

k then% row of the tablewe presentmethod-of-moment estimatesthatuse these

rehabifitiesto correct for measurementerror. These estimateswould be consistentif

measurementerror were the ody source of nrisspecificatio~thatis, if therewere no

correlationbetween family-specificunobservable andyears of fatherlessness. Mthough

we do not consider thisa particularlyplausiblehypothesis,we presentthese estimatesfor

Weusethe%comptisons to estimate the vsrimrce of the mewement error.

16
sake of completeness. We see thatthe MOM estimatesare ordy sfighdylarger thantheir

OLS counterparts,wfich is to be expected given the modest amount of measurement

error.

The estimatezin the next row are from OLS appfiedto the model in equation (4),

in which the datahave been difference across sibhgs. The estimatesfor whites are quite

a bh smrdlerthanthe OLS estimatesbased on equation (3), providing evidence of

substantialcorrelationbetween family-specificunobservable and years of fatherlessness.

& additioti year of fatherlessnessis now estimatedto reduce education attainmentby

ordy 0.035 years among whites. Nthough this estimateisjust more thanhrdfthe ske of

the =timate in the first row, it is stillsignificantlydifferentfrom zero, atleast atthe ten

percent level. For whites, there seems to be tittledoubt thatfatherlessnesshas a negative

effect of education attainment.The otiy question concerns the magnitudeof the effect.

For blacks, however, controlling for family-specificunobsemables has a much

more surprisingeffect. The OLS estimatebased on sibfingdifferences is positive rather

thannegative, a counterintuitiveresult. Moreover, it is difficultto attributethis resultto

chance, because the estimateis significantat conventionallevels.

For ~panics, controlhng for unobserved heterogeneityacross ffies has fittle

effect on the estimates. It does lower the precision of the estimates,however. Taken at

tice value, both OLS based on the sibfingdifferences and OLS based on levels suggests

thatfor Msparrics,each additionalyear of fatherlessnessreduces education by about 0.04

years.

17 
Row 5 presentsestimatesof the re~abiities of within-familydflerences in years of

titherlessness. This measuretoo is a finction of the varianceof the measurementerror,

and is given by

2V(VJ)

‘d =l–v(Azfi). (11)

The rehfilfities of the difference familystructurevtiable are substantirdlylower thanthe

refiabfities of the levels. From equation (1I), we can see why. Firs\the numeratorof the

second term on the right-handsideof(11) is twice its counterpartin equation(1O).

Second, provided thatfatherlessspells arepositively correlatedwithinfdes, which

indeed they mustbe, the varianceof the within-familydifference is less thantwice tie

variance of tbe levels. Intuitively,the differenceshave more measurementerror thanthe

levels because dflerencing removes more si~ thannoise.

The greatermeasurementerror in the difference datasuggests another reason

why OLS appfiedto sibtingdifference dati yields stiler estimatesthanOLS appfiedto

levels. Rather thanaccounting for correlationbetween family.structureand tily-specific

unobservable, dfierencing the datawithinfamifiesmay simplybe exacerbatingthe

problem of measurementerror, accentuatingtheusualattenuationbias.

The estimatesin the stih row of Table 3 reitiorce thisnotion. These are the

method-of-moment estimatesfrom the difference dat~ which account both for farnilyspecific unobsewed heterogeneityand measurementerror. A expected, accounting for

measurementerror yields largercoefficients. Indeed for whites and~spanics, the

coefficients on years of fatherlessnessare now more negativethanthe originalOLS

Is
esfimafes based on levels. For blacks, accounting for measurementerror in the dflererrced

datayields a largerpositive coefficient.

The differenf approaches to esfimafionthusyield subsfsntidy differentestimates

of the effect of fatherlessnesson education afftinrnent. For whites, the largest

coefficient is greater tbn .fhe stilest by more thana tictor of three. For Hispanics,the

IargesfWd sm~lesf esfirnatesdiffer by more thana factor of four, althoughofly the OLS

estimafebased on levels is si@canf. For blacks, the esfirnatesvary as to sign.

It is clearlyimportantto choose horn among these various estimates,to determine

which provides fhe besf representationof fhe dat~ A simpleapproach is to use a set of

fiusman tests. Under the nullhypothesisof no modeI nrisspeficafio~ OLS based on

levels provides consisfenf and asymptoticrdlyefficienf esfimstes. The other estimatorsdso

should be consisfenf, but ingeneraltill be less efficienf. Under the alternative,however,

OLS appfiedfo Ievelswi~ be inconsistent. k the presence of bofh measurementerror and

ftily-specific unobservable, ody the mefhod-of-moments esfimstor appfiedto sib~mg

differenceswill yield consistent resu!ts.

The first row of Hausmanstatisticsprovides tests of the nullof no rnisspecification

againstthe dfernafive thaf measurementerror is presentin Ievek, butthere is no

unobserved ftiy effect correlatedwith years of fatherlessness..The nefi row provides

tests againstthe dtemative fhatthere are fdy-specific unobservable, but no

measurementerror. The thirdrow provides tesfs againstthe composite dternafive that

dews for both unobserved heterogeneityand measurementerror.

Consider firsf fhe resultsfor whites. Neifher the test againstmeasurementerror

nor the test againstunobsewed ftily effects yields sificanf evidence againstthe nufl

19

—
hypothesis, althoughthe test againstfamilyeffects comes close. The test againstthe

composite rdternativeMS to reject as well, which is not surprisinggiven the large

standarderror of the MOM estimateapptiedto sibbg dflerences.

We therefore conclude that,for white$ the dataprovide no significantevidence

againstthe nullof no rnisspecificatio~in which cme OLS appfiedto Ievds provides the

best estimateof the effects of fatherlessnesson education attrdnment.Dmregardkrg

si~cance levels for the moment,the various estimatestefl a plausiblestory of how this

could happen. The estimatedrefiabthies suggestthatsome measurementerror indeed is

present, even in levels. Under standardassumptions,measurementerror causes OLS

estimatesto be too smallin absolute vrdue. The OLS estimatesbased on Sibkg

differences,fikewise, suggestthatfamily-spectic unobsewables maybe present,because

we would generrdlyexpect OLS appfiedto levels to be biased upward fin absolute value)

in the presence of suchunobserved heterogeneity. Thus both ~es of rnisspecfication

may be presentto some ement, althougheach offsets the other,

For blacks the stoV is different. Mthough measurementerror has Ettleeffect on

the estimatesin levels, there is strong evidence of fdly-spectic heterogeneitythatis

correlated with spells of fatherlessness.The surprisingfinding, of course, is that

accounting for familyeffects actuallyyields positive and significantcoefficients.

There is some etidence inthe literaturethatthe adverse consequences ofgrotig

up f~herless tie sder for bkcks thanfor whites, and indeed our resultsare consistent

with thisgenerrdfinding ~ein andBe~er 1986). To our knowledge?however, tkese are

the fist significantestimatesto suggestthatfatherlessnessmightactmdlyhave beneficial

effects for blacks. Clearlythispuzfing resultcalls for firther study.

20
For Mspanics the resultsof the Hausmantests are qutitatively similarto whites.

Individually,there is fittleevidence of eithermeasurementerror or familyeffects.

Mthough the MOM coe~cierit based on sibfingdifferencesis much larger thanthe other

estimate>because its standarderror is large, we failto reject againstthe composite

alternativeas well. The Hausmantests thusfailto rejectthe nul~in which case the OLS

appfiedto levels provides thebwt estimateof the effects of fatherlessness.

k summary,the specificationtests lead us to conclude thatthe OLS estimates,

which are tin to the estimatesfound in the previous Hterature,provide the best

representationof the effect of fatherlesson educationrdattainment,at leastfor whites and

Hspanics. For whites there is some insignificantevidence of both familyeffects and

measurementerror, but these two types of misspecificationseem largelyto offset ~ch

other. For Mspanics, the evidence of rnisspecificationis sfight.

“For“whites,our best estimateis thateach year of fatherlessnessleads to a decrease

of 0.06 years of educatio~ for ~spanics the decrease is 0.04 years. The average spefl of

fatherlessnesslasts 9.4 years for wfites who experiencefatherlessness;for ~sprnrics, the

conditional mean is 11.3 years. Thus for both whites andHispanics,the average child

growing up in a fatherlessfamilywould acquire about one-hrdfyear less education thanhis

counterpartfrom a two-parent home. Presumably,such a reduction in education would

affect his adult etings as well.

B. Entrv-levelWages

Unfortunately,the ordydata at our dispod with which to test thisproposition are

data on entry-levelwages. Entry-levelwages are potentiallyproblematic, because relative

wages early in the fife-cycle maybe ordywetiy relatedto relativewages duringthe prime

21 
earningsyears. Ehigh-skill workers takejobs with lower startingpay but with higher

prospects for earningsgrowth, for example,thenthe effect of fatherlessnesson entry-level

wages might appear differentthanits effect on wages over the fill fife-cycle.

Nevertheless,to get a sense for the effeti of fatherlessnesson earnings,we present

in Table 4 resultsbaaed on the same assortmentof estimatorsused to studythe effect of

10 Before ex~~ng these ~timates, however, it ~ wages on educationrdattainment.

instructiveto determinethe ma@~_des thatthese coefficients shouldhave if the sole

effect of fatherlessnesson wages were due to its effect on education. Ka year of

schoofing increaseswages by 10 percent on average, and each year of fatherlessness

reduces education by 0.06 years,then each year of fatherlessnessshould reduce wages by

0.06 percent. This is a smaUeffect, and given the sample sizes at our dispod, it may be

difficultto estimatean effect of thismagnitudevery precisely.

The dependentvtiable is the averagewage described in section D. For whites,

the OLS coefficient baaed on levels is statisticauysignificant,and is rougtiy doub!e the

~titude we would expect if the ordy effect of fatherlessnesson wages was due to its

effects on education. We cannot rejectthe hypothesisthatthe tme coefficient is qurd to

0.006, however. For blacks andWspanics the OLS coefficients based on levek are dso

negative,though neitheris significant. The coefficient for Wspanics differs horn zero ofly

atthe ~h decimd place.

Correcting for measurementerror done has ody a negligibleeffect on the

estimates. k contrast, correcting for familyeffects by themselveschanges the sign of the

. .,

10 In adtition to the set of regrwsora included ti tie education models, the mge modefs included

age and agesqusrd as well as titicators for re>on of tidence, rrrtitity, ad the regkrti

unemployment rate.

22
coefficients for both blacks and Mspanics. & one would expect, correcting for both

measurementerror and familyeffects produces estimatesthat are largerthanthe estimates

based on OLS appfied to sibfingdifferences, but with the same sign.

Athough the patternof the point estimatesacross differentestimatorsis different

in the case of wages thanit was in the case of educatio~ the conclusions based on the

foti specification tests are largelythe same. For the most part,the nu~hypothesis of no

rnisspecificationcannot be rejected. The exception concerns blacks, for whom the

estimatesbased on sibhngdfierences are positive and significant.

Thus our conclusions based on the formal hypothesistests are the same for the

wage models as for the education models. Whh the exception of blacks, OLS based on

levels provides the best estimateof the effects of fatherlessnesson entry-levelwages.. The

estimatesfor whites indicatethat the wages of the average fatherlessworker are about 12

percent lower thanthe wage of the averageworker who grew up in a two-parent fbmily.

For Mspanics, there is no evidence thatfatherlessnesslowers entry-levelwages.

We note that,for a numberof reasons, we view the conclusions regardingthese

wage models as more tentativethanthe conclusions we drew from the education models.

h the firstplace, for whites, the test againstfamilyeffects ody narrowlyfails to reject.

More generrdly,the estimatesfrom the wage model are less precise thanthe estimates

horn the education model, & a results,researcherswith differentpoints of view could

justifiablydraw the conclusion thatfatherlessnesshas no effect on entry-levelwages. K

one’s prior befief were thatfamilyeffects and measurementerrorwere present, so thatthe

ody basis for inferencewere the MOM estimatesbased on sibhrrgdifferenc~. .fien one

23
would failto reject the nullof no effect. Moreover, the specificationtests could not reject

tie maintainednullofgenerd misspectication.

Therefore, akhough the dab are consistentwith the notion thatfatherlessnesshas

negative effects on entry-levelwages, atleastfor whites, we view this finding as less

conclusive thanour resultsregardingthe effects of fatherlessnesson education

attainment. Much of the inconclusivenessundoubtedly stems from the noisinessof the

entry-levelwage data, and the relativelysd samplesizes at our disposd. It wodd be

desirableto revisitthis questionwith dataon a larger sample of prim-age workers.

V. Conclusions

Past research conducted primady by non-economists, has suggestedthat ctildren

who grow up fatherlmsacquire less humancapitalthanchildrenintradhionrdtwo-parent

homes. Our analysisindicatesthat,for whites, thisgeneral conclusion is quite robust.

Our best estimatessuggestthaton average,white ctidren in single-parentftihes obtti

one-hrdfyear less schookg thantheir counterpartsin two-parentfkrnifies. Our results

rdsoindicatethatfatherlessnessis fikelyto lead to lower educatiosrdattainmentamong

mspanics.

For blacks, however, accounting for unobsemed familyeffects yields estimatesthat

are positive and statisticallysigtificarrt. Taken at face value,this indicatesthatbhck

ctidren horn singe-parent homes actua~yfare better thanblacks who five witi both

parents. It is hardto take such a surprisingresultatface vrdue,howeve~ this &ding

clearly calls for firrtherresearch. It also serves as a ruethodologicd warning against

poofing dataacross the races to study the effects of familystructure.

24
Since fatherlessnessreduces edumtioq atleastfor whites and Mspanics, one

fi@t ~~ tit workem who grew Up~ sindeparent ffies would - less on the

labor market. Mthough our wage sndyses yield resdts thatare consistentwith this

notio~ atleastfor whites, the evidence is rathertied. It maybe ths~ for a number of

reaso~ entry-levd wages maskthe true effect. It would be desirableto revisitthis issue

witi dataon older workers.

25
References

Astone, Nan Marie and Sara S. McLanahan. “Family Structure, Parenti Practice$ mrd

~gh School Completion: American Sociological Reviw. 56, (1991): 309-20.

Becker, Gary S. A Treatise on the Family. Cambridge, ~ss.: HarvardUniversityPress

(1981).

Bumpass, LarryL. 1984 “ChildrenandMaritalDismption: A Reification andUpdate.

“Demogrqhy. 21: 71-82.

Grifiche$ Zvi and JerryHausman. 1986. ‘%rrors in VariablesinPanelData?’ Journal of

Ecmrometiics. 31:93-118.

Hanushe~ Eric A. 1992. “The Trade-off between Child Quantityand Qudhy.m Jamal

of Political Economy. 100: 84-117.

Havem~ Robert, and BarbaraWolfe. 1994. Succeeding Generations On the Effec& of

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Hog~ DennisP. andEvelyn M. Kitigawa. “The Impact of Social Status, Family

Structure, and Neighborhood on the Fertifity of Black Adolescents? Americarr

Journal of Sociolo~. 90, (1985): 825-55.

Keit~ Vema M. and Barbara Fday. “The Impact of Parentrd Divorce on Children’s

Educatioti Atttinrnent, Marital Timing, and L1kehhood of Divorce: Jmmal of

Marriage and the Fami&. 50, (1988): 797-809.

Kre@ SheilaFitzgerald. 1986. “Growing Up in a Single-ParentFtiy The Effect on

Education and Earningsof Young Men.” Fami@ Relations. 35: 161-68.

=e@ SheilaFhzgerrddand hdrea H. Beller. 1988. “Education Attient of

CMdren From Single-ParentFarnifies:DWerences by Exposure, Gender, andRace.”

Demography. 25: 221-34.

Ll, JiangHong and Roger Wojtkiewicz. “A New Look atthe Effects of FamilyStmcture

on StatusAttainment.” Social Science Quarterly. 73, (1992): 581-95.

McLanahan, Sara. 1985. “Family Structure and the Reproduction of Poverty.” American

Journal of SocioIo~. 90: 873-901.

McLansbw SaraS. “Family StructureandDependency EarlyTransitionsto Fetie

Household Headship.” Demography. 25, (1988): 1-16.

McLanah~ SaraS. andLarryBumpass. “IntergenerationalConsequences of family

Disruption: American Journal of Sociolo~. 94, (1988): 130-52.

Weiss and WI1fis. ~ Jeff.

26
Woj&etic~ Roger L 1992 “Simplicityand Complexity in the Effects of Parental

Stmtire on Hgh School Graduation.” Demo~qhy. 30: 701-17.

27
Full sam~l~ Multi-sib households

Vatiable name Total Wte Black Hspanic Toti Wte Black Hsptic

Education 12.74 13.08 12.49 12.00 12.80 13.21 12,44 12.19

(2.39) (2.46) (1.99) (2.52)

Red wage 8.29 8.79 7.22 8.24

(5.44) (5.70) (4.73) (5.27)

Years fatherless 3.40 2.33 5.75 3.32

(5.99) (4.89) (7.40) (5.92)

Years other 0.43 0.26 0.79 0.44

(2.20) (1.57) (3.10) (2.23)

Mtih order 2.98 2.73 3.40 3.18

(2.25) (1.93) (2.61) (2.50)

Female 0.51 0.51 0.50 0.50

(0.50) (0.50) (0.50) (0.50)

Ody child 0.03 0.03 0.03 0:02

(0.17) (0.17) (0.17) (0.14)

One tibtig 0.13 0.16 0.08 0.09

(0.33) (0.37) (0.26) (0.29)

Mother’s education 10.39 11.37 10.15 7.39

(3.76) (3.17) (3.51) (4.35)

Sample stie 9660 5516 2559 1585

Number of intitidurds

tith vdld wage data 9179 5297 2375 1507 4345 2267 1229 714

No@ Unweighed sample means. Standard dtiatiom fi parentheses.

(2.31) (2.4~ (1.92) (2.23)

8.28 9.04 6.93 8.24

(5.21) (5.61) (4.21) (5.02)

3.00 1.72 5.32 2.85

(5.7~ (4.22) (7.30) (5.54)

0.19 0.12 0.32 0.20

(1.33 (0.88) (1.90) (1.3~

3.13 2.80 3.60 3.30

(2.30) (1.87) (2.6~ (2.64)

0.48 0.49 0.48 0.46

(0.50) (0.50) (0.50) (0.50)

N.A. N.A N.A N.A

0.08 0.12 0.04 0.05

(0.28) (0.33) (0.19) (0.21)

10.64 11.75 10.44 7.48

(3.7~ (2.72) (2.87) (3.95)

4579 2428 1384 767

28
Table 2: OLS Coefficients from theRegression of Edumtioti Attainmentat Age 27

on Years Fatherlessand Other Control Variables,by race

Dependent variable Completed schoofing at age 27

F~ ~

VariabIename Wte Black Mspanic ~te Black Hspanic

Years fatherless -0.060 -0.027 -0.022 -0.064 -0.023 -0.044

(0,006) (0.005) (0.010) (0.010) (0.007) (0.014)

Years other -0.087 -0.026 -0.013

(0.018) (0.011) (0.028)

-0.113

(0.048)

-0.022..

(0.026]”

0.002

(0.056)

Birth order -0.066 -0.038 0.023

(0.01~ (0.016) (0.027)

-0.027

(0.025)

-0.022

(O:m”o]

0.052

(0.032)

0.097 0.438 0.188

(0.057) (0.073) (0.1 19)

0.250

(0.084)

0.560

(0”:097)

0.361

(0. 154)

Ordy child 0.449 0.720 0.335

(0.17~ (0.216) (0.41~

N.A, N.A “N.A.

One sibhg 0.452 0.409 1.106

(0.082) (0.142) (0.215)

0.651

(0.134)

0.019

(0.265)

1.179

(0.370)

Mother’s education 0.411 0.241 0.187

(0.012) (0.015) (0.016)

0.420

(0.018)

0.229

(0.022)

0.148

(0.021)

8.561 10.033 10.433

(0.167 (0.198)” (0.199)

8.383

(0.248)

10.002

(0:281)

10.836

(0.245)

Sample size 1384 767

Notes Standarderrorsare in parentheses. ~gs we~ crated to aecomo&k nrissing varues intbe

vtiablw r~rted intie table.Separateflagswereaereqti toonefortie observationtiti a tisaing

vahreintie blfi orderorrnotier’seducationvariablea,andtieywereseteqti tozeroofitie. me

nrisskgvdw intie tible wasfien settozero. Mm, separatefigs weresetq~ tooneKwe

obsewed tie respondent’s edumrion at age28 or age 26, hey were set to zero otietise. me re~sions

for h white -pies includ~ an indi~tor of mefietip h tie poor w~te subsanrple.

5516 2559 1585 242X

29
Table 3: AlternativeEstimatesof the Effeet of Years in a FatherlessHousehold

on Education Attainmentat Age 27, by race

Dependent variable: Completed schoo~ig at age 27

%te Black His~anic

(1) -0.023

(0.007)

Ordinaryleast squares -0.064

(0.010)

(2)

(3)

(4)

(5)

(6)

Estimatedrefiabifity(r,) 0.87

Method of moments (levels) -0.074

(0.012)

Sib~ig differences -0.035

(0.019)

Estimatedrefiabifity(r.) 0.32

Method of moments -0.118

(sibfing differences) (0.062)

0.83

-0.027

(0.008)

.-0.044

(0.014)

0.90

-0.049

(0.015)

0.021

(0.011)

0.33

0.066

(0.035)

-0.041

(0.029)

0.24

-0.182

(0.129)

Hausmanteat statistics:

(7) (1) vs. (3) 2.27 1.07 0.86

(8) (1) vs. (4) 3.22 26.88 0.01

(9) (1) vs. (q 0.78 6.74 1.16

Sample skes

Levels 2428 1384 767

Sibhg differences 1673 1013 548

Notes: Standard errors = in umntheses. Each re~ssion includes tie mntrol tila reDort~ h he

body of Table 2 as well as the fl~~ fiited in the note~to Table 2. me ~mman stadstim are ‘d~ti

wing the differenm in tie variable of interest to increase the power of the test. The Critid due for the

95 pr-t level of the chi-sqmred test is 3.84. The sample sties differ bemeen tie OLS and sibtig-

@erence spwfimtions kose we lose one obsemation from dl Wo-rewndent Wes.

30
Table 4: MterrrativeEstimatesof the Effect of Years in a FatherlessHousehold

on the Logarithm of the Average Red Wage, by race for ties ody

(om educationrdattainmentnot includedas a re~essor)

Dependent variable: The logarithmof the averagered wage rate of mrdes

White Black Hispanic

(1) Ordinaryleast squares -0.011 -0.004 -0.005

(0.004) (0.003) (0.005)

(2) Estknatedrehabihty(r,) 0.87 0.83 0.90

(3)

(4)

(5)

“Method of moments (levels) -0.012

(0.005)

Sibkg differences 0.011

(0.009)

Estimatedrefiabifity(r.) 0.32

Method of moments 0.048

(sibbg difference) (0.039

-0,005

(0.004)

0.011

(0.009

0.33

0.042

(0.023)

-0.005

(0.006)

-0.00s

(0.014)

0,24

-0.067

(0.121)

Hausmarrtest statistics

(7) (1) vs. (3) 0.11 0.14 0.00

(8) (1) VS. (4) 7.45 8.33 0.05

(g) (1) VS. (6) 2.72 4.07 0.26

Sample sizes

Levels 727 428 267

Sibfingdifferences 436 279 la

Not% Standard errors are in D=ntheSeS. The rcmessionareuortcdin this table do not include the

respondent’s educatioti attai~ent as a ~gressor. -Each regr~sion contains the control variables

r~m~ ~ the bdy of Table 2, the flags fisted in the notes to Table 2, and indimtors for region of

residmce, tianicity, and fie regioti unemployment rate. The Ww- statistics are ddtcd using

the ~erencc in tie variable of interest to increase the power of fie teat. The Critid vafue for the 95

pement level of the chi-sqwed tmt is 3.84. The sample sizes dfler between the OLS and aibling-

~erence ~cfilcstions because we lose one observation from dl familiea having ody NO rnafe

respondents.

31
Table 5: Nternative Estimatesof theEffeet of Years in a FatherlessHousehold

on theLogarithmof the Average Red Wage, by race for mrdesordy

(own education attainmentincludedas a regressor)

Dependent variable The logarithmof the average rerdwage rateof males

White Black msparric

(1) Ordinaryleast squares -0.009 -0.003 -0.005

(2)

(3)

(4)

(5)

(6)

(0.004)

Estimatedrefiabifity(r,) 0.87

Method ofmoments (levels) -0.010

(0.005)

Sibhngdifferences 0.013

(0.008)

Estimted refiabtity (r.) 0.32

Method of moments 0.054

(sibfirtgdifferences)” (0.035)

(0.003)

0.83

-0.003

(0.004)

0.010

(0.006)

0.33

0.040

(0.022)

(0.005)

0.90

+.005

(0.006)

-0.005

(0.014)

0.24

@.046

(0.132)

Hausmantest statistics:

(7) (1) vs. (3) 0.11 0.00 0.00

(8) (1) vs. (4) 10.08 6.26 0,00

(9) (1) vs. (Q 3.28 3.89 0.10’

Sample s~es:

Levels 727 428 267

Sibhngd~erences 436 279 164

Not= Standard errors are in parentieaes. Udke Table 4, tie regressions re~rted in this table

contained the respondent’s edncatioti attainment ass regressor. Each regression dso inclti the

control vtiablw repetied in tie body of Table 2, tie flags fisted in tie notes to Table 2, age,ageqnerd

and in~cators for region of residen~, urbticity, and tie regioti unemployment rate. % ~

titistics are cddated naing tie tierence in tie variable of interest to increase tie power of fie =

me titid value for tie 95 percent level of fie cti-~wed test is 3.S4. me sample sizes differ beWeen

the OLS and sibfing~erence”apecfications beearrse we lose one obemtion fim M -es tig

nfly WO tie rqonderna.

32
Table 6: Mtemative Estimatesof the Effect of Years in a FatherlessHousehold

on the Logarithm of the AverageRed Wage, by race for fe~es ordy

(OW educatioti attainmentnot includedas a regressor)

Dependent variable The logarithmof the average red wage rate of females

White Black Hispanic

(1) OrdinW least squares -0.013 -0.005 0.008

(2)

(3)

(4)

(5)

(0

(0.005)

Estimatedrefiabifity(r,) 0.87

Method of moments ~evels) -0.015

(0,006)

Sibfingdifferences -0.012

(0.013)

Estimatedrefiabihty(r.) 0.32

Method of moments

(sibfingdifferences)

-0.043

(0.047)

(0.004)

0.83

-0.00.6

(0.005)

0.011

(0.009)

0.33..

0.043

(o.03q

(0.006)

0.90

.0.008

(0.007)

0.027

(0.017)

0.24

0.176

(0:102)

Hausmantest statistics:

(7) (1) vs. (3) 0.36 0.11 0.00

(8) (1) VS.(4) 0.01 3.94 I .43

(g) (1) VS.(6) 0.41 1.80 2.72

Sample sizes:

Levels 675 354 195

Sibfingdifferences 417 215 117

Notes Standarderrorsareinparentheses. Theregressions~pofiedb thistabledidnotmntainthe

respondent’sedumtiondattainmentas a regressor. However, Each regression contains the control

variablea repotied in the body of Table 2, the fla~ listed in the notes m Table 2, agq age squsr~ and

tirficatom for re~on of residence, mbardcity, and the regioti unemployment rate. The Hauanran

atstiadcs are cflmlated using the ~erence in tie variable of interest to incr~ the power of tfre teat.

The titid vrdue for the 95 percent level of the chi-sqmd testis 3.S4. The sample sizes ~er &Ween

the OLS and aibling~erence spec~l~tiom bemuse we lose one obsemation from dl farnifies having

rady ~o fetie respondents.

33
Table 7: Mtemative Estimatesof the Effect of Years in a FatherlessHousehold

on the Logarithmof the Average Red Wage, by race for females ordy

(OM education attainmentincludedas a regressor)

Dependent variable The logarithmof the average red wage rateof feties

Wte Black fisparric

(1) Ord~ least squares -0.010 -0.004 0.010

(2)

(3)

(4)

(5)

(0

(0.005)

Estimatedrefiabifity(r,) 0,87

Method of moments (levels) -0.011

(0.005)

Sibfingdifferences -0.009

(0.013)

Estimatedrehabfity (r.) 0.32

Method of moments -0.031

(sibfingdifferences) (0.046)

(0.004)

0.83

.-0,005

(0.004)

0.006

(0.009)

0.33

0.027

(0.038)

(0.006)

0.90

...0.011

(0.ooq

.0.017

(o.ol@

0.24

0.132

(0.120)

Hausmantest statistics:

(7) (1) vs. (3) 0.26’ 0.181 0.OO1

(8) (1) vs. (4) 0.01 1.54 0.22

(9) (1) vs. (q 0.21 0.67 1.04

Sample skes

Levels 675 354 195

Sibfingdifferences 417 215 117

Notes Standarderrorsareinparentheses. Theregressionsreportedinthistableincludedthe

mwndem’s educatiod attainmentasaregressor,thecontrolvtiablesrsportdinthebodyofTable2,

tie ~gs fistedinthenotestoTable2,age,agesqw~ andindimtonforregionof residence,tianitity,

andtheregio~ rmenrployarent rae.TheHammanatatiticsaredcrdatedusingthe~erence inthe

variableofinteresttoinc~e tbepowerofthetes~Thecntid vduefor the95perwntleveloftbectisq- testis3.84. Thesamplesiza differbetweentheOLSandsibtig~ermm @ations

bwe weloseoneobservationfromdl fitilies batingody NOfetie reapondcnta.

(1) Wmr&ng of the Wdard errors in the tables @es it app~ Orwe statistics a not be estimatd

34
Appendix I

~Data

It was necessaryto exclude some of the original 12,686 hdividrs~ Born the

analysis. Because we look atthe effects of tily structureon educatioti attient at

age 27, we could not include individualswith missingdata on eitherof these measures.

We dso excluded 9 biological sibfingswho report being of differentraces. The resulting

data set had 9,660 individualswith complete childhood fivingarrangementand educationrd

attainmentdat~ 9,179 of whom hadvafidwage dataas we~.

k the initialintetiew in 1979, the~SY identifiedthe relationshipof each

respondentto rdlco-resident respondents and collected information on the numberof

sibfingsand the numberof older siblingsof each respondent. We used this informationto

identi~ bIolo@cd sibhngswithinhouseholds and to construct measuresof family size and

birthorder.

We identifiedtwo respondentsas biological sibfingsit in 1979, both claimedthe

other as a biological brother or sister. Half-brothersand hti-sisters did not qurdii. There

were 4,579 individualswho bd a blologicd-sibfing respondentwith vflld educationrd

attainmentinformation of which 2,428 arewhite, 1,384 areblack md 767 areHispanic.

Of these, 4,210 individualshad a sibfingrespondentwith vtid wage data as wefl: 2,267

white, 1,229 black, and 714 ~spanic.

To construct our measuresof familysize, it was firstnecessaryto correct for

inconsistencieswithinfamifies. To do this,we constructed an average familyske from the

responses to the numberof sibfingsquestion. We thenconstricted two dummyvariables

to measurefamily size. Fust, we set a dummyvariableequalto one if the average family

35
size equated one, and it was setto zero otherwise. Second, we constructed a dummy

variableequalto one if the average familysize was two, and it was setto zero otherwise.

To calculate the respondent’s biih order, it was againnecessaryto correct for

inconsistencieswithinfarnifies.We first constructed a btih-order variableby adding one

to the indlvidu#s reported numberof older sibkgs. We thenchecked for consistency

between the sibting’s birthdatesand our estimateof theirbmh order. h famifieshaving

inconsistenciesbetween btih dates and bkth order, we corrected discrepancieswhere

proper order could be determined,otherwise birthorder for dl irrdividudsin these famifies

was set to missing.

We created flags for missingand chmged values to includein the regressions. M

missingvalues of control variableswere set to zero and an indicator of this was

constructed. We dso constructed a flag equal to one ifbkth order was edited, and it was

set to zero otherwise.

k 1988, the NSY asked about the education attainment of each respondent’s

mother. To correct for measurement error in this variable, we used the within family mean

of these reports.

h each year, the~SY determinesthe respondent’s region of residence,whether

the respondent Evesin anurbanor ruralarea,andthe regionalunemploymentrate. We

used the reports of these variablesin the year the respondentturned27 to control for lod

labor market characteristicsthatmighttiect wages. Ktbis informationwas missingin the

year the respondentturned27, we used the educationd-attaimnentdgoritbm reported in

the teti to constructthese measures. AgtiU missingvrduesof thwe variableswere set to

zero and an indicator of thiswas includedin each regression.

36
Appendix ~

Woittieticz Reification

Wojttiewicz (1992) used the family-structureretrospective in the ~SY to

determinehow experiences of parentalstructuretiect high school graduation. We

presentthe resultsof tis Model 2.1, our reification of hismodel, and estimatesof this

model using our analysis samplesin Table Al. The first column restatesthe rmults

repotied in WojtKewicz (1992). The second column shows our reification of these

results. The thirdand fourth columns report the resultsof estimatinghismodel 2.1 using

our samples.

A comparison of the fist two cohumrsof the table show thatwe were able to

repficatehis results. In dl cases, the estimatedfamily-structureparametersare not

significmtly different,and in some cases, they are identicd. Six of the seven birthcohort

dummieshave the same sign, and they are not si~cantly different. There is no statistical

difference between the se~ race, and parentaleducationvariablesin the two regressionsas

well.

A comparison of the resultsin columns three and four show the expected result

thatthe parameterestimatesdo not vary between individualsin our fi~ sampleand those

in the multi-sibhouseholds. Moreover, a comparison of the parameterestimatesin

columns three andfour with those in columns one and two show fittledifference between

the restits obtained using our samples,Wojttiewicz’s results, or our repfimtion of his

results.

37
Table Al: Comparison of the Effect of Years k ParentalStructwe Type

on ~gh School Graduation, by sample

(1) (2) (3) (4)

Analvsis smole

WoitKewim’s Our FuU Multi-sib

Variable results reification sample households

Mother ody -0.037 -0.033 “-0.032 -0.037

(0.007)

Mother stepfather -0.036

(0.011)

Fatherody -0.102

(0.025)

Fatherstepmother -0.034

(0.029)

Orarrdparents -0.051

(0.olq

Other relatives -0.034

(0.035)

Other -0.082

(0.024)

Birthcohort-1957 -0.063

(0.128)

Birth mhort-1958 -0.107

(0.126)

Birth cohort-1959 -0.097

(0.125)

Bifih cohort-1960 -0.141

(0.118)

Birth cohort-1961 -0.124

(0.1 18)

Birth cohort-1962 0.005

(0.118)

(0.007)

-0.036

(0.01 1)

-0.121

(0.026)

-0.035

(0.029)

-0.036

(0.OIQ

-0.0.44

(0.035)

-0.101

(0.017)

0.031

(o.12q

-0.015

(0.124)

-0.133

(0.121)

-0.139

(0.llq

-0.103

(0.1 15)

0.002

(0.115)

(0.005) (0.oon

-0.030

(0.008)

-0.105

(0.019)

-0.024

(0.023)

-0.029

(0.013)

-0.055

(0.027)

-0.088

(0.020)

0.280

(o.11~

0.188

(0.116)

-0.060

(0.111)

-0,066

(0,108)

-0.064

(0.108)

-0.010

(0.108)

-0.041

(0.013)

-0.102

(0.030)

0.051

(0.048)

-0.021

(0.028)

-0.031

(0.058)

-0.140

(0.046)

0.297

(0.198)

0.413

(0.179)

0.204

(0.163)

‘0.151

(0.148)

0.124

(0.144)

0.066

(0.142)

38
Table A2: Comparison of the Effect of Years InParenM StructureT~e (continued)

—(1) (2) (3) 7

~

Woitkiewicz’s Our Fufl Multi-sib

variable results rephcation sample households

Birth cohofi-1963 -0.126 -0.068 -0.089 0.067

Black

Hspanic

One sibfing

More than3 sibfings

Parentfailed to

graduate from high school

Parent some college

Parent college graduate

Mssing parentti education

Poor-white subsample

(o.11~

0.426

(0.059)

0.067

(0.078)

-0.491

(0.081)

0.271

(0.106)

-0.399

(0.068)

-0.974

(0.070)

0.571

(0.129)

1.435

(0.163)

-1.461

(0.134)

N.A.

(0.1 14)

0.437

(0.058)

-0.027

(0.074)

-0.524

(0.079

0.177

(0.118)

-0.376

(0.084)

-0.988

(0.068)

0.619

(0.127)

1.378

(0.153)

-1.466

(0.133)

N.A.

(O.108)

0.404

(0.053)

0.03.7

(0.072)

-0.441

(0.076)

0.199

(0.loq

-0.423

(0.075)

-0.959

(0.061)

0.605

(0.112)

1.312

(0.133)

-1.474

(0.124)

-0.697

(o. 144)

0.610

(0.078)

-0.134

(0.104)

-0.469

(0.1 14)

0.345

(0.213)

-0.349

(0.110

-0.762

(0.091)

0.517

(0.159)

1.299

(0.195)

-1.127

(0.188)

-0.999

(0.081) (0.137)

Sample Sizes 8381 8382 9660 4579

Nets S@dard emors are in parentiew. Woitieticz’s re~ are from Table 2, Model 2.1, ml- 1

ad 2 h Wojti~m (1992). “Mso,for a discu~sion of tiable definition sse Wojti*cz (1992). me

tin Werence bemeen our -PI= and Wojtiexticz’s is fiat we include re~ndenti from tie ~rwtite Sub=ple.

39
02

03

04

05

06

07

08

National Longitudinal Suneys ~LS)

Discussion Paper Series

Mickel R Pergtit

Nomm M. Bradbti

Hn R Frtiel

Reginald P. B*m

Michael R Pergtit

Sad Schw@

Rokfi Hutchem

Gorge J&ubson

A. Colin heron

R Mak Griti

Thorns Matidy

Heq S. Faber

Fra& L. Mott

Patia B&er

Au&ey Light

Manuehm Ur&

Lisa M, LWch

09 Ewgelos M. Fdtis

H. EMeth Peters

10 he ~11

Jue E. ONeill

11. kleen LGbotiQ

Jamb Mex NeLin& Wtite

12 Lee A. LMmd

13 Jos~h G. Mtonji

Thorn% A. DU

m

How tie Fedeti Govetient Uses Data Gom

the Natioti LongimdinaJ SUeys

A dmp~ion of Computer-&sistd Pe~nd

Intefiews (WI) titi Pa~-md Pentil ktertiews @AP~ @ the Natioti bngitiditi SWsy

of Youth

D-c Models of the Joint Detefimtion of

Lakr Supply W F~ly Stitie

The acts of Unemplo~ent Comp~tion

on the Unempl~ent of Youth

Edmting Competig Theorim of Worker

Mobfi~

E@mtion of the 1989 CMd~ Supplement

in the NationalLongitu~ Swey of Youth

Gender DMerenms h the @t BeMtior of

Yomg Workers

The Impad of Private Seaor Tting on he

snd Gsuder Wage DHerentiaJs md the ~er

Patterns of Yomg Workem

Rmpnses of Fede Labor Supply md F~ty

to the Demo@ptic Cycle

A Smdy of ktercohon Chage in Women’s

Work Pattern ad Edngs

Women’s Emplo~ent ~ng Pre~y

md FoUoting Bti

Work E@ence, Job Tenue, Job Sqmtion,

ad Wage Gmti

Ftily Ba&~omd md L*r Mwket @tcomw
National Longitudinal Sumeys ~LS)

Discussion Paper Series

-

92-01

92-02

92-03

9244

9245

92-06

92-07

92-08

9249

92-1o

92-11

92-12

92-13

No-n M. Bradbum

Mtin R. Frtiel

Reginald P. B&er

~ckel R. Pergamit

Saul Schwti

Robefi Hutchens

krge Jtibson

-A. Colin Cmeron

R, ~k Gtiti

Thorns Ma~rdy

Hew S. Farber

F* L. Mott

Patia B&er

Audrey Light

Muelita Urea

Lisa M. Lynch

Evagelos M. Faltis

H. Elinbeth Peters

be ml

June E. ONeill

&leen Ltibotiti

Jacob Mex ~emm

Lin& Waite

Lee A. LWd

Joseph G. Mtonji

Tboms A. Dm

~

How the Federd Govement Uses Data from

the Natiod Lon@tidind SWeys

A Co~tision of Gmputer-Assisted Persoti

Intetiews (CAP~ titb Paper-ad Pencil Interviews @API) in the Natioml Lon@mdml Smq

of Youth

Dytic Models of the Joint Detefination of

LAor Supply and Ftily Stictu

The effects of Unempl~ent Compemation

on tie Unemplo~ent of Youth

Evacuating Compettig Theories of Worker

Mobili@

Evaluation of the 1989 Child-cme Supplement

in the Nation& Longitudind Swey of Youtb

Gender Dfiemnus in the Qtit Behatior of

Yomg Workers

The Impad of Private Se~or Traifig on ~ce

and Geuder Wage DBerentids and the tieer

Patterns of Young Workers

Responses of Femle L%or Supply md Fetility

to the Demoflapbic Cycle

A Smdy of Intercohoti Cbge in Women’s

Work Patterns ad E-inSs

Women’s Emplo~ent During Pre~nq

md Follotig Bti

Work E~erience, Job Tenure, Job Sepwation,

md Wage Gro\ti

Fandly B&kgound md bbor ~ket Outcomes
92-14

92-15

93-16

94-17

94-18

94-19

95-20

95-21

95-22

95-23

95-24

95-25

95-26

95-27

95-28

96-29

George J. Bo~as

Stephen G. Bromrs

Stephen J. T~jo

Sek-Sel~on ad Inteml Mi~ati6n h the

Utited Stites

Jmes J.Hecti

Stqhen V. Cmeron

Peter Z, Schochct

The DetetimE ad Comequences of Wblic

Sector ad Private Sector Trtig

AJa L. Gu~m

Thorns L. Stetieier

Ctistopher J. Ruh

Wk Lowenstein

James Spletier

Jacob Alex fGerw

&leen Leiboti@

Stephen G. Broms

tiol Moore

Donald O. Pmns

Donald O. P-ns

Audrey Light

Lawa Branden

R tik Griti

Mickel R. Per~t

.Thoms Dum

Douglas Holti-Nn

Pficipation h Low-Wage Labor MwkeE by

Youg Men

Retirement h a Ftily @ntm A Stitiral Model

for Husbmds and Wivm

Transition from School to Work A SWey of

~se~ch Ustig the Nationfl Longitidlnd Sumcys

~gb School Employment Comption 01

kvaent

Itiormal Ttiting A Retiew of Efitig Data ad

Some Nm Etidence

Ctiacterizing Leave for Matetity: Mdtig the

NLSY Dam

Emplo~ent Contitity bong NW Mothem

hcentive Pay, Itiomatio~ md E-w: Etidence

from the National Longimtid SWey of Youth

The Evolting Stmcmres of Femsfe Work Activities

Etidence from the National Longimdind S“meys of

Msmre Women Smq, 1967-1989

Pove~ WCs tio~ Wtie Women: Etidenm

from the National Longimdiml Sumeys, 1967-19S9

Techologicd Chge ad the Skill Acquisition of

Youg Worke~

High School Employment

The Effect of Intetiew Length on Attition in the

NatiOti hngituditi Sumq of Youth

Opitaf M~ket Constits, Paenti Wdth ~d the

Trmsition to sti-Emplo~ent mong Men and

Women
96-30 Jeff Grower

Nick Wu

me Intergenerational Effas of Fatherlessness on

Edumtioti Atttiment md En@-level Wag=