The Effect of lntewiew Length on Atirition in

the National Longitudinal Suwey of Youth

Laura Branden

Westat Inc.

R. Mark Griti

Seattle Research Center

Michael R. Pergamit

Bureau of Labor Statistics

Mmch 1995

~s paperw fidd by tile U.S. Deptimt of hhr, Bmau of Labor SWti*cs uder d pwckse order.

me tiews e~ressd hem ~e those of the authors ad do not neces~ly r&ti the tiews of the U.S.

Dep-ent of Uhr.
THE EmCT OF ~TER~W LENGTH ON NON~SPONSE ~ THE

NATIONAL LONGITUD~AL SUR~Y OF YOUTH

LauraBranden~estat, he.), R. Mark Gritz (Seattle Research Center),

andMichael R. Pergamit(Bureau of Labor Statistics)

ABSTRACT

b this paper, we e=mine the effect of interview length on wave nonresponse in a

longitudinal survey, controlling for respondent-specific characteristics known to affect

survey response. We use the Natio”ndLongitudinalSurvey of Youth ~S~, a sample of

over 10,000 individualswho were 14-22 years old when firstintetiewed in 1979. These

individualshave been titewiewed armudly every year since then, providing 16 years of

da~ The interviews have been conducted in person in aUyws except one. Ufllke the

CPS or S~P, the NLSY does not dow proxy responses. The NLSY attempts to

intefiew -ly dl fiving respondents ach year. Over the years, the length of the

interview has varied. It *O varies substantiallyacross individuals in the sample within

years.

A transition probabtity model is estimated using bard equations. Holding constant

personal, demographic, and environmentalfactors known to itiuence survey response as

weU as several measures of respondent attitude and cooperatio~ we find that longer

interview length is associated with sample retention. HypothesElng that interview length

may prow for some uncontrolled dimension of respondent cooperation, an alternative

measure to interview lengt~ namely the number of questions aske& was constructed.

Reestimatingthe h~ards tith this variablegenerates similarfindings.

We conjecture that survey length whether measured in minutes or number of questions

asked, measures the sfiency or apphcablhty of the survey to the respondent. Those

respondents who possess the characteristicsmost importantto the content of the survey

have the longest intefiews but are tiso the most interested. The poficy prescription we

propose is to design survey instrumentswhich include sets of questions applicable to dl

respondents, focusing less on the average lengthof the interviewand more on the range of

potentialinterviewIen@hs,

mYwoRDs

Attritio~ hterview Length, NationalLongitudmd Suwey of Youth, NLSY, Nonresponse

1
Introduction

A common behef etists that nonresponse increaseswith the length of the survey. In tis

paper we use a panel data set, the National Longitudinal Survey of Youth WSM, to

wtimate the effects of survey length O: attrition. By using panel dat~ where the same

indlvidurdsare interviewed repeatedly, we are able to control better for person-specfic

factors than is possible in a cross-section survey. Repeated obsewations of the same

people whh measures of interview length which vary across people and across time

provide a richfiarneworkfor isolatingthe impact of survey length.

We mntrol for a variety of demographic, personal, and enviromnenti characteristics,

many of which have been found in the literatureto be correlated with nonresponse in

surveys. (See Goves (1989) and Oroves, Clddlni, and Couper (1992) for discussions of

the causes of nonresponse and findlrrgsfrom various surveys. Oritz, MaCurdy, and WOZ

(1994) study attritionin the NLSY. They charactetie nonrespondents and returneesand

examine the effects of attritionon the Iongitudld representativcnessof the panel.) We

dso makeuse of some intefiewer assessmentsregardingthe respondent’s cooperativeness

and understandingof the sumey and other pexson-sptic igt!cators of Cooperativeness

such as the number of contacts requiredbefore an interview was completed and whether

the individualhad to be converted. In gened we find thatlonger surveysdo not irrcr=e

attritionand, in fact, may indicatea cooperative, interestedrespondent.

me National Longitudinal Survey of Youth (NLSY)

The NLSY, sponsored by theBureau of Labor Statistics,is asample of young people who

havebeen intefiewed annuallysince 1979.* Originally12,686 youths between the ages of

14 and 22 were interviewed. The sample included oversarnples of blacks, Mspanics,

economically disadvantaged nonblack no~spanics, and youth in the dtary. The

dtary samplewas discontinuedtier 1984 and the econornic.rdlydisadvantagednonbiack

nofispanic oversimple was discontinued &er 1990. The base~mesample, adjusted for

these deletions, includes 9,763 individuds. Interviewshave been fielded as face-to-face in

dl years except 1987 when the survey was fielded by telephone. In any year, some

intetiews may have been conducted by telephone ranging between about 5 and 15

percent of completions. Proxy irrtetiews are not rdlowed in the NLSY and respondents

are offered $10 for theirtime (though some receive more than $10).

The focus of the NLSY is primarilyon labor market behatior. Irrfomtimr is collected

about dl jobs held since the lastinterviewincludingstartingand ending dates, occupation

industry, wage and hours worked. In addition to information about jobs, the survey

collects items related to labor ~ket behavior such as ducation and job training

household compositio~ marital tistory, fertfity, heaIth, income, assets, and program

participation.

‘ Foramorecompletedsscnptionofthe~SY, sactie ~S ~tik (1994).

2
k various years other federd agencies have contributedfinding to incr~se the content of

the sumey. In particular,questions have appeared regsrting the respondents’ drug use,

alcohol use, sexual atiivities, child care, and pregnancies. Beginning in 19S6 and every

other year since, questions havebeen addressedto the mothers in the sample regardingthe

physid, cognitive, and emotional. development of their children. The children were

administeredseverrdassessmentsappropriatefor theirage.

Attrition in the NLSY is low by comparison with other longitudinal surveys. Dan

collection is undert&en for BLS by NORC, which has done an incrdlble job of

mainttig high response rates. After 16 years of interviews, nearly 90 percent of the

“adjusted” basefine sample cooperated in 1994. In this paper, we used data through 1992

tid adjust the basefine for the deleted samples. In 1992, the overall response rate was

90.5 percent of the basetie sample.

One dfimence between the NLSY and other surveys is that contact is attempted with

virtudy dl hving respondents. This includes respondents who have moved overseas,

those who have entered the tihtary, those who have entered prison, etc. Many

Iongitudirrdsurveys drop an individud horn the efi@ble interviewingsample afier one or

two nomesponses. Most surveys do not interview anyone who leaves the United States,

leaves the citibm population, or entersan institution. The high response rates maintained

in the NLSY reduces the need for comphcated weighting schemes or heroic assumptions

about norsresponse.

Attrition in the NLSY is not true attritionin that respondents can returnto the sample.

Therefore it is more accurate to refer to nomesponse @y thiswe meanwave nonresponse,

as opposed to item nonre$ponsez). k rmygiven year be~een 4 and 10 percent of the

basefine samplewas not interviewed. Table 1 shows the response rate in each year of the

survey. The first column labeled “TotW shows the rate for the entire sample as a

percentage of the basehne sample. The second column labeled “Tot# shows the

“continuous” response rate, i.e. the percentage of the base~me sample who had been

interviewed in dl survey years. As can be seen, 74.5 percent have been continuously

interviewed. This is more consistentwith retentionrates in other surveys,though it is still

generally tigher for comparable numbers of years or interviews. Exchsding 1980, the

percentage of firsttime nonrespondentshas rangedbetween 1.2 in 1991 to 2.7 in 1987.

Similarto other suweys, response rates have differed by se~ and racdethnicity. Table 1

dso shows the yearly and continuous rates for males and females, On an armurdbasis,

fernfles appear to have ordy a sfightly hi@er response rate than males; the difference

generrdlybeing betwm 1 md 3 percentage points. However, the percentage of ties

who have ever been nonrespondents has been significandy higher than fe~es. The

continuous response rate for femaleswas 78.2 p¢ in 1992 wMe ordy 70.7 percent for

ties. In other words, 21.8 percent of dl fedes bd at some time not responded, while

29.3 percent of mdti had at some time not responded.

2 Wedo notaddressfrotentidrevnse dettiorationcawd bytie lengthoftheway. Fora My

wtichexandnesre~nse qtiity andsurveylengthseeHemogandBachrnan(1981).

3
Table 2 shows yearly and continuous response rates for Hsptics, blacks, and others.

Response rates by year do not differ greatly by race or etbnicity,though Hsptics are

sfightlylower in most years. On the other han~ continuous response rates for Msptics

definitely lag the other two groups. Blacks have generally kept pace with nonblack

no=spanics (other); ordy startingin 1987 does there appear to be the begisming of a

wideninggap in continuous response rates.

Interview Len@h in the NLSY

The NLSY questionnaire ii a fairly complex krstmment with significant skip patterns

which generate very differentlengths of interviews across respondents. A major section

on jobs does not apply to those who are not ernployet major parts of the fertifitymrd

child care sections do not apply to people without childrew etc.. hterview lengthhas dso

varied over time, particularlydue to the irregularinclusionof questions from other fkderd

agencies.

Table 3 shows the average interviewlength for each year of the suwey.3 As can be see%

the average length of intefi.eys bs varied horn a low of 32.5 minutes~ lg87 to a figh

of 86.3 minutesin 1979, with a wide range of times in between.

Table 3 dso shows the 10th and 90th percentiles for each year. These percentiles

demonstratethe tide variancein surveylengthacross respondents. The lengthsat each of

these extreme percentilesmove in the same mannerover the years as the averages. The

difference between the 10th and 90th percentilesis fkirly stable, but shows some variance

consistent with the movements of the average. The movements in the 10th and 90th

percentilesrelativeto the averages can be seen inFigure 1.

Correlates of Nonresponse

To estimate the effects of intetiew length on nonresponse, we estimated transition

probabilitymodels (~~. Because respondents can returnto the sample, we focused on

firsttime nonresponse. The transitionprobabtity model is the same one usd in Oriti and

MaCurdy (1992). A fl descriptionof the model can be found in thatpaper.

The TPM derives a h-d fiurction. The hamrd function measures the probabtity of

leaving the ssmple in a given year, conditionedon having been interviewed each previous

year. (This is the inverse of the survivor finction which measures the probabtity of

remainingin the sample corrditioti upon having been interviewed in mch previous y=.)

The h=ard is a spe~-based model. The dependent variable takes a value of zero for W

years in which the indlvidud responded untila yeN of notiesponse OCCUK,then it takes a

3~s mmsuredoesnotincludeanititi homsholdenumerationanda sectionattie endoftie intervisw

usd to coHa lmting infotion WMCL on average,tie tiut fivendnutes=fi.

4
value of one in the first year of nonresponse. Mer that year, the individual does not

contributeto tie model since we look at firsttime nonresponse ody.

We held constant a large set of variables including a variety of demographic and other

personal charactetitics of the respondents, environmental variables, and interview

characteristics. These covariateswere allowed to change over time to reflectthe statusof

the respondent in each interview year. Holding these variables constant, the effeet of

interview length was isolated. The hazards were estimated using samphng weights to

reflectthe fact thatminoritiesare sampledat higherrates.

The complete set of parameterestimateswith vtiable definitionsappears kr the Appendix

tables. Because tie parameter vsdues do not have an easy irrterpretatiouwe cofine

ourselves here to a discussion of the direction of the effects (and statisticrdsignificance).

Eventuallyone would want to determinethe size of the effect, but at this point we ordy

discuss the correlat=. The relationshipof each set of variables to attritionis described

below.

Derno~aphic. Personal. andEnvironmentalCharacteristics

&ce/ethnzcr~

The sampling scheme for the ~SY categorizes individuals into three groups: blacks,

Mspanics, and others. Ufllke Census definitions, blacks and HisFtics are mutudy

exclusive. The hazards reveal no difference between the nonresponse probablfities of

blacks and others for men or women. However, Mspanics have a greater Hkehhood of

nomesponse. This bears out the uncontrolled patternsshown earher. Relative to others,

both blacks and Mspanic nonresponse is more hkely to be due to locatabihty as opposed

to refusal.

Age

kdividuds in the sample were born between the YWS 1957 and 1964. The empirid

results show that, in general, nonresponse increaseswith age. It is not clear whether this

is because the younger a person begins as a respondent the more likely tiat person

becomes “hooked or if the younger respondents merely havent gotten to the ages where

they are more hkely to become rmnrespondents.

Mmiage &FertiIi~

Being marriedincreases the hkefihood of nomesponse for both sexes, and particularlyfor

women. The e~lanation may reside in the dtemative uses of time for marriedpeople, or

because spouses exert an uncooperative itiuen~. These fidings, however, are not

5
consistent with fmdkrgsin the hterature. Oroves and Couper (1993) study seven surveys

and find that the surveys they wamine mostly indicate single people as less Wely to

participate. It is not obvious why our resultswould differ.

Related to thismaybe a measureof whether the respondent’sparentsare in the household.

Parentswere generrdlyin the household for the younger respondents in the early years of

the smey. Some youth may remainin tieir parents’household or returnto it. This may

be particularlytrue for women. For me% therewas no impact of the parentsbeing in the

househol~ for women, it increasedthe tikehhood of nomesponse. On the other hand,the

presence of others duringthe actualinterviewhad no effect on futureattrition.

The impact of hating ctidren entered into the equation h two separate variables. One

was a dummyvariableindicatingthe presence of one’s own childrenin the household. The

other variablewas a mntinuous measure of the actualnumberof one’s ovm ctidren in the

household. The effects are dfferent for men andwomen.

For men, there is no difference in average response for those who bad ctidren versus

those who do not, However, for those who had childre~ the more ctildren they had, the

less Wely they were to leave the sarnple.4For women, the very presence of childrenhad a

ti@ficMSt effect in retainingthe woman in the survey. In ad@tioA the more ctildren she

had,the more fikelyshe stayedwith the survey. Goves and Couper (1993) fid a positive

effect of childrenon surveyparticipationin the surveysthey studied.

Two measureswere includedwhich mptured schooting. One variablemasured the effect

of being enrolled. For both men and wome~ being enrolled increased the fikefiood of

stayingin the survey.

The other measures were a set of educatiorud a-ent variables. These include

variables for high school dropouts, high school graduates,those with some college, and

college graduates. Here therewas no patternfor women. For mew however, retentionin

the sampleincreased consistentlywith the level of educatioti attainment.

EmpIo~errt and Wor~orce Attachment

The primary focus of the ~SY is labor force behavior. A mnsiderable amount of

information is collected about each job, each trainingprogram, and each nonwork spell.

The sdlency of the survey maybe relatedto anindlvidud’s employment status. Of course,

the burden encountered by the respondent is rdso related to their employment status.

Measures of workforce attachment may dso account for the generrd stilfity of the

dme varishlewasdefinedm hatig one’som childreninthehousehold. In MS mtiei, a divoti

fatherwhose ctidren are fiving titi heir motherwoufd k the sameas a mantiti no c~dren.

6
isrdividud. Three variableswere used in this contefi: employment stitus at the time of the

interview, averageweeks worked per year, and averagenumberof jobs per year.

Employment at the time of the survey had no effect on women. For me% it increased the

Wefihood of staying with tie survey. Average weeks worked per year measured the

degree of long-term attachmentto the labor market. For both men and women, more

weeks worked imphed lower likelihood of nonresponse. Average number of jobs per year

is a measure of general job stabikty. For me% the more jobs per year, the greater the

probabihtyof nonresponse. There was no effect for women,

tiings

Other studies have shown that nonrespondents tend to come from certain portions of the

earningsdlstributio~ typicaflyboth the lower and upper ttis.5 Here we found thathaving

no e-gs preditis future nonresponse. Moving up in the earningsdistributiondoes not

yield a clear patternfor eithermen or women. Most other studieshave found nonresponse

correlated with other measures of socioeconomic status ~arti~larly at the low end).

Consistentwith these studies,we find an impact of e-gs atthe very low end. The lack

of a clear pattern may be attributable to our many measures which aheady reflect

socioeconomic statusand that earningshas no clear independ~nteff-.

Re@”onad Urbmiciy

Nonresponse does not dtier for women across regions. However, there were

considerable differences for men. Men in the northeast had the lowest propensity to

respond, those in the north centraf region had the highest. The west and south were

similarto each other, lying between the other two.

Urbanicity was measured with a set of variables representing rural arm, urban areas

which are not part of a SMS~ areas that are part of a SMSA but not a central ci~, areas

that are pti of an SMS~ but ody partly in a central ci~,6 and areas that are the central

city of a SMSA. The ordy distinction which mattered in the estimation was hving in a

centralcity. For both men and women, ~ving in a centralcity impliedgreater likehhood of

attrition. This is consistentwith other studiesof nonresponse. Oroves and Couper (1993)

~ to account for this tiding by including variables which vq by urbanicity. After

includingthese variables,they stillfind a direct effect on participationof fiving in a central

city.

5 W=, Wtidy, andWz (1994) fid tis for the WSY.

‘ ~ese are tip codeswtich spanacrossmnti city and noncennti city

7
Memres of Reqondent Attitude

A vtiety of measures efist to inform us about the respondent’s attitude toward tie

survey. The most obvious is an interviewerassessmentmade at the end of the interview.

The interviewer chose horn among four categories: friendly and interested; cooperative

but not partictiarly interested;impatientand restless; and hostie. Most individualsfdl in

the fist two categori~, about tbre-quarters are in the fiendly and interested category,

one-fifih in the cooperative category. Ody approximately 34 percent in each year are

coded as impatientand restless,and generrdlyless than one-hrdfof one percent are coded

as hostile. (See Table 4 for the percentages in each category in ~ch year.) Despite the

low numbers of those in the two more hostile categories, tiese variablesare very strong

predictors of nonresponse. In the estimtio~ the probablfity of attrition incr~ed

successivelymoving from the most cooperative to the most hostfle categories.

Another direct measure of cooperation is whether the respondent had to be converted.

The designation of whether a case was converted rested with the interviewer and is not

always consistent. It can tie a variety of forms from a simple refisd that requires a

second attemptto cases when a special interviewerwith mnversion expertise and great

persuasivepowers is brought in &er the initiallyassigned interviewerhas failed to secure

a response. Not surprisinglythe percent of the sample who had to be converted has

grow over time. Table 5 shows the percent converted each year. In the earhestyears

(1979-1983), this was under 3 percent. Conversions grew somewhat after 1983, then

took a big jump &er 1988.7 The big jump may be attributableto changes in procedures

for coding conversions. Oiven the number of years, the percentage requiring conversion

remainslow.

The h=d estimationshows that as was the case for the interviewees assessmentof the

respondent’s attitude, if a respondent was converted, it is a strong indicator of fiture

nonrespome.

A less direct measure of cooperation is the number of contacts which were attempted

before an interview was secured. Interviewers are rquired to record any time they

attempted to contact the respondent. This includes busy si@s and no answer on the

phone or atthe door, which introduces noise into this as a measureof cooperation. If it is

purely noise, there should be no prdictive power for attrition. We hypotheske that it

does correlate with cooperativeness of the respondent. Table 5 dso shows the mean

numberof contacts attemptedfor those wbo were interviewedby year. The average grew

for the fist severalyears, but has leveled off since the mid-1980s.g

We allowed the impact of the number of contacts to vary in a noncontinuous manner.

&ges of the distributionwere constrainedto have the same impact, but different ranges

codd have different impacts. This method was chosen over the more conventionrd

method of a hnearrelationshipwhich requires the margiti effed of the vtiable to be the

‘ Thespke in 1987a be attributd to fielding the sruvq ss a cen~ telephoneoprstion.

8me Spke in 1987- again bc atibuted to fielding the wq Mti a ~n@&A telephonedesign.

8
same at dl points, Akhough the relationshipis not everywhere consistent, the hamrds

indicatethatthere is predictive power. The greaternumberof contacts required,the more

fikelythatthe person will be a fiture nonrespondent.

Aother less duect measure of cooperation is whether the interview was conducted in

person as designed or on the telephone. Each year since the be~rrrring,some people

would ody consent to a telephone interview. To achieve desired response rates,

intefiewers offer a telephone interview in lieu of a personal interview. There are

significant restrictionson this practice to maintainthe integrity of the design. Over the

years there has been growth in the percentage of interviews completed over the telephone

(see Table 5).

We hypothestie that completing an interview by telephone is a measure of

noncooperation, perhaps a step along the way to nonresponse. In fact, the &arda bear

this out. For both men and women, those who completed their interview on the

telephone were more hkely not to participatein firtureinterviews.

One issue”wtich tietis cooperation is the presence of sensitivequestions. The MSY has

had a variety of sensitive questions in various years including questions on alcohol, drugs,

semd activity, crirnirtrdactivities, and (not least of dl) income. k general, item refusal

rates for any of these variables has been low. Even as the sample has aged, the item

norrresponse rates have not grown appreciably. However, we attempted to capture

whether these questionsmay be problems for certainpeople.

We chose two variablesto exarnine.gThe fist was whether the person refused to answer

a question about fifetime marijuanausage. This question, in sfightly dtierent form,

appeared in 1980, 1984, and 1988 as the lead-into a set of questions about drug usage.10

A dummyvariable indicatedwhether the person refised to answer the question. For both

sexes, refising to answer indicatedincreasedhkehhood of nonresponse, though it was not

si~cant for men.11

The second variable was etigs. Many people argue that income variables are more

sensitive than questions about sex and drugs. We counted a refusal if the respondent

refused to answer any of three earnings questions: wage and saary earnings, rnifit~

eting$ or earnings horn one’s own business or fm. E=h question referred to the

previous crdend= year. The estimationindicated thatfor both men and womeq refising

to answer earningsquestionswas indicativeof fiture nonresponse.

9 ti choiesswae rfstemrindbyWOconsiderations.Therebadtobea signifiearrt rrmnberof refusafs

(questionsabut Amhol omge, for emple, bad afmos no re=s) and the questionshadto apply to the

-.

women their preserrmwas associatedktig more lkely to shy titi the wey! This may k spurious,

acmrrrrdngfor some otherysar-spatic sspeetof the sruvey,

9
We dso tried a varianton the earningsvariable, Some people answered “don’t know” to

earningsquestions. While this may be a trut~ response, we hypothesbed that it may

dso reflect an unwillingnessto answer the question wMe not wanting to say so directly.

Counting refisals A “don’t knows” together, we tested if they had separate prdlctive

power in the attritionksrd. For wome~ they did not, indicatingthat women are not

choosing the don’t know response in lieu of refising. Men, on the other hand, showed an

additiond effect from “don’t knows.” Such an answer is a firther predictor of

nonresponse beyond the effect of refising irrdlcstingthat men are less wilfing thanwomen

to provide direct answers.

SurvevIenmh

The impact of survey lengthon attritionis modeled in a ftirly unstructuredway in order to

let the effect vary over the distributionof times. We rdso dow differentialefdects from

the most recentintetiew andthe average of dl previous interviews. &ch of these effects

are rdlowed to differ in the early, middle and lateryears. This unstructuredapproach does

not requireus to have prior expectations on the relationshipsas would, say, a simpleti~

or quadraticspecification.

The resultsare quite surprising. While it is dficult to make generrdiitions because of the

number of parameterswkch are allowed to vary, the length (in minutes) of the most

recent interview has either no impact on attrition, or, reduces the WeMood of attrition.

To be more specific, for both men md women, the longer the most recentintefiew in the

early years (modeled as yetis 1-S), the more bkely the person stays in the sample. The

length of the most recent interview has no effect in the middle and later years. Though

our resdt is surprising,it is consistentwith the find]ngsof Zabel (1994). He examinedthe

Panel Study of kcome Dynamics @S~) and two waves of the Survey of Program

Participation(SPP). Ustig a bd modd, but with different specifications than ours,

Zabel found that response increased with survey length in both surveys. The subject

matter of the ~SY is stisr to these two surveys, though there are some important

design differences.

The lengthof the most recentintetiew may not be the best indicatorof how survey length

impacts on respondents’ cooperation. H~ard estimationallows us to condition response

on historicrdinformation from previous waves of the survey. To capture the impact of

irrtefiew length beyond the most recent interview, we dso measure the impact of the

average length of dl previous interviews. With each successive titerview, the average of

all previous interviewschanges.

To see best the impact of longer interviews,we calculatedthe predicted h-d rates for a

base case of a 60 fiute interview in dl years. Then we made the same dculations

assumingthe length of the interview to be 90 minutes in dl years. Figure 2 shows the

predicted h-d rates for men assuminga 90-rninuteinterview compared with the base

10
case-60 minute interviews. In this case, increasing the length of the interviews does

increasethe tiard ratesin the earlyyears. By the stih year the effect goes away.

We performed the sametype of experimentbut decreased the lengthof dl interviewsto 30

minutes. The predicted hmd rates for this length intefiews dso appmrs in Figure 2,

The surprisingfinding is that decreasing the interview length dso increases the h-d

rates, in fact by more than increasing the length of the interview. The effect also goes

away @er about six yws.

The predicted h=ard rates for women for the same two experimentsare seen in Figure 3.

The results are more striking. Increasing the length of d] interviews from 60 to 90

minuteshas no impact in the first four years. Mer that,the h~ard rates are lower in dl

years. Shorteningthe interviewfrom 60 to 30 minuteshas no impactin the firstfour years

either. Mer that,tile hmrd rate increasesby a smallamount for seversdyears, returning

to hating no impactin the lateryears.

To recapitulate,we see thatlengthetig the interview may increase nonresponse for men

in the early years, However, shorteningthe interviewdso increasesnonresponie, and by

more. Lengtheningthe interviewfor women reduces nonresponse; shorteningit increases

nonresponse.

One hypothesis is that interview length is another measure of cooperation. Those who

enjoy the interviewor tik: it seriously spend more time talkingwith the interviewer,more

time mnsidering their answers, and generally create a more relaed and slower-paced

intefiew. However the effect has to be independent of the other measures we kve

includedto mpture cooperation as they have been held constant,

&an alternativeto interviewlengthwe attemptedto create a variablewhich measuresthe

number of questions asked of a respondent. Some quwtions collect informationwhich is

not released and could not be munted by using the pubfic data set. Other questions were

dlffictit to count dhectly such as when prerecorded items are verified. However, we

befieve the amount of noise in this measure is considerably less than in the memure of

interview length, Figure 4 shows the average number of questions and the 10th and 90th

percentilesby year. The patternis very similarto the patternfor interviewlength by year.

Figure 5 shows the averages for the two variablesoverlaid with an arbitraryadjustmentin

the scales. It can be seen thatthe two measuresmove very closely together over time,

We reestimated the kards, replacing interview length with the number of questions

asked. We entered the number of questions as a series of variables symmetricalwith our

treatmentof interview length. The resultsare equally provocative. To see the impact of

the number of questions we performed experiments similarto those for interview length,

We estabhshedpredicted hmd rates for a base case of 250 questions asked. Then we

predicted huard ratesfor interviewswith 325 questions asked ad for interviewswith 175

questions asked. Figure 6 show the resultsfor mew Figure 7 for women.

11
More questions unambi~ously decreased the tid rate for men in dl years. For

wome~ the huard rate is lower through the tenthyear, tier which the effect disappears.

Fewer questions lowered the h~ard rates of both men and women in the early years. For

wome~ the effect goes away begirmingaround the sitih year. For me% reducing the

numberof questions increasestisrd rates in the sixth and subsequentyears with a shq

increasein the middle years.

In generrd,the effect of the number of questions asked is similarto the effect of interview

length. Longer intetiews, as measuredeitherin minutesor in questions asked can lead to

an increasein pred]cted response rates.

Mer controlling for a variety of demographic, personal, and enviromnenti

characteristics,we investigatedthe impact of surveylengthon nonresponse in the Natiod

Longitrsditi Survey of Youth a panel data set, using the first 14 of the 16 y- of data

on the same individuds. The effect of surveylength on fist nonresponse was found to be

generallythe opposite of what was expecte~ in ody one case dld the anticipateddirection

occur. Otherwise, interviewlengthseems to eitherhave no pattm of effect, or it leads to

greaterWe~iood of retention. h dtemative measureof burde~ the numberof questions

asked bd similar,but stronger, effects.

To the extentthatinterviewlength showed no effect, this restit is important and perhaps

otiy mildly surprising. It is possible thatinterviewlengthmay not have much of an effect

in a face-to-face survey hke the NLSY, but may have more impact with a telephone

interview. To the extent that interview length actually indicated that longer interviews

lead to less attritio~”this result is quite surprising. Of course, nothing here impfies

cautihy, ordy correlation, and it does not seem credible to suggest that we shodd

lengthenour interviews@_order to retainrespondents.

It maybe thatinterviewlengthis picking up some other respondent attribute. It is ~cult

to identifi what this would be that is not already captured in the control variables,

especiallygiven our varietyof measuresof cooperation. However, cooperation may be a

multidlmensiomdattribute, osdy partially captured by our control variables.*2 &other

possible explanation is stiency, or appticabifity. The more the suwey appfies to the

individud, the more questions which will be asked and the longer the intefiew,

accounting for the strong resemblance in their movements over time.13 If the survey is

applicable, fie rapondent may in fact be interested. The more apphcable, the more

interestedthe respondentis,

12 In ~aa -Ftion ~wt ~ mtititimetioti for mofOmvsriomm-es to indewnd~tfybe

:grdfiue, x hey do. Merrviss mtiticollin~ty wotid lead to insi~mce.

On tie otier h~ a simple regressionof Survq len@ on tie nrmrkr of questionsaskti ~elds an Rsqwd of ofly abut .2, implfing onfy weak corrdation at tie rnimolevel. We intendb explore ti

~er.

12
The main focus of the sumey is labor force behavior. We observed that those who were

employed andthose tith greater labor marketattachmentand stillity were more hkely to

stay with the survey. The second biggest focus of the survey, particularlyfor wome~ is

fetiihty, with a substantialnumber of questions on each child and, for women, each

pregnancy. We dso observed thatthe number of childrenwas positively associated tith

staying in the sample, This implies that we have rdready controlled for this sort of

srdiency. However, the number of possible controls is substmtidly larger than what we

have used here, It is plausible that interview length is a prow for saliency in some way

not measuredby our control variables, & noted, nearlydl respondentsare considered by

interviewersto be cooperative the vast majority friendly and interested. (Of course, we

have controlled for this,too.) If respondentsare wilhng to participatein a surveythatlets

themtdk about theirfives, they maybe relativelyinsensitiveto the length of the suwey (at

leastwithinthe bounds of the interviewlengthsin our data). But if the survey is generally

inapphcable to them, they have little interest and become nonrespondents, This is

reflected in the findings that decreasing the length of the intefiew or the number of

questionsasked dso increasesnonsresponse.

13

This implies that our surveys should contain series of questions which can apply to dl

types of people in order to maintainresponse rates, men we construct our surveys, we

generallyfocus on the average length of the interview, Our findingsimply thatin addition

to averages, we should rdso concentrate on variances.
Centerfor HumanResource Research,NLS Handbook, 1994, Columbus, Ohio.

Grkz, R. Mark, MaCurdy, Thomas, and Mro% Thomas, “A Evaluation of the NLSY,”

prelinrinq drfi paper preparedfor the Bureau of Labor Statistics,February 1994.

Gritz, R. Mark and MaCurdy, Thomas, “Participation in Low-Wage Labor Markets by Young

Men; National Longitudinal Suweys Discussion Paper, Report: NLS93-16, Bureau of

Labor Statistics,Washington,DC, September 1992.

Groves, Robert M? Cialdini, Robert B., and Couper, Wck P., Understandingthe Decision to

Participatem a Survey,Public Opinion Quarter&, Vol. 56:475-495, 1992.

Groves, Robert M. and Couper, Mick P., “Unit Nonresponse in Demographic Sumeys; paper

presentedattheBureau of the Census 1993 AnnualResearch Cotierence, March 1993.

Groves,l f;~ M., Sumey Errors and Suney Costs, New York: John Wiley and Sons, kc.,

Herzog, A. Re@la and Bacbman, Jerald G., “Effects of Questionnaire Len~h on Response

QuAty~ Public Opinion Quarter&, Vol. 45:549-559, 1981.

Zabel, Jefiey E. and -S D]tision, Bureau of the Census, “A Comparison of Attritionin the

Panel Study of Income Dynamics and the Survey of Income and Program Participation,”

unpubhshedpaper, April 1994.
Table 1

~SY Wsponse Mtes by Yew, by Sex

Sumey IPercentofBasefine / Percent Continuous I

Yem

Total Male FemAe Toml Male Female

1979 100.0 100,0 100.0 100.0 100.0 100.0

1980 96.0 ~ 95.7 96.2 96.0 95.7 96.2

1981 96.6 96.4 96.7 94.3 93.8 94.8

1982 95.8 95.5 96.1 92.7 91.9 93.5

1983 96.4 96.0 96.8 91.7 90.8 92.5

1984 95.3 94.7 95.9 89.9 88.6 91.1

1985 94.0 93.2 94.8 87.7 86.0 89.3

1986 91.9 90.8 93,0 85.2 83.1 87.2

1987 90.4 88.8 91.9 82.5 79.9 85,1

1988 90.2 89.3 91.0 80.1 77.4 82.8

1989 91.3 90.0 92,7 78.8 75.7 81.8

1990 89.8 88.5 91.2 77.0 73.7 80.2

1991 90.5 89.0 92.0 75.8 72.1 79.4

1992 90.5 89.2 91.8 74.5 70.7 78.2
Table 2

MSY Response Rates by Year, by RaceEtticity

Suwey Percent of Baseline Percent Continuous

Year

Total Mspanic Black Other Total Wspanic Black Other

1979 100.0 100.0 100,0 100.0 100.0 100.0 100.0 100.0

1980 96.0 94.7 96.3 96.3 96.0 94.7 96.3 96.3

1981 96.6 95.6 97.2 96.5 94.3 92.4 95.1 94.5

1982 95.8 94.1 96.2 96.3 92.7 89.7 93..6 934

1983 96.4 95.2 96.7 96.6 91.7 88.5 92.2 92.6

1984 95.3 94.9 96.2 95.0 89.9 86.7 90.8 90.5

1985 94.0 92.8 94.7 94.Q 87.7 83.5 88,8 88.6

1986 91,9 89.9 93.0 92.0 85.2 80,5 86.6 86.2

1987 90.4 87. I 91,7 90.9 82.5 76.9 83.8 84,0

1988 90.2 86.6 91.5 90.7 80.1 73.,8 81.3 81.9

1989 91.3 90.0 92.3 91.3 78.8 72.9 79,6 80.6

1990 89.8 88.2 90.5 90.1 77.0 71.0 77.5 79.0

1991 90.5 89,8 90.0 91.1 75.8 69.9 75.7 78.1

1992 90.5 90.3 89.9 90.9 74.5 68,9 74,2 76.9
Table 3

~SY Intefiew Lengths by Year

SurveyYe= Average 10thPercentile 90th Percentile

1979 86.3 55 125

1980 67.2 40 95

1981 63.6 40 90

1982 69.3 45 95

1983 59.0 35 85

1984 71.3 45 105

1985 58.3 35 85

1986 55.3 30 85

1987 32.5 19 50

1988 74.0 45 110

1989 47.2 30 70

1990 55.0 31 80

lQQ1 ?7 7 77 <5
Table 4

~SY R=pondent AttitudesRepofied by Interviewers,by Yea

Suwey Year Interested Cooperative Impatient Hostile

1979 74.7 21.4 3.6 0.3

1980 76,3- 20.6 2.9 0.3

1981 76.8 20.1 2.9 0.3

1982 76.7 19.6 3.4 0.3

1983 78.4 18.6 2.7 0,3

1984 77.4 18.9 3.2. 0.5

1985 78.2 18,0 3.4 0.4

1986 75.8 20.5 3,3 0,4

1987 82.6 14.4 2.7 0,3

1988 73:4 22.1 4.1 0.4

1989 75.0 20.4 4.2 0.5

1990 74.4 21.7 3.6 0.3

1991 75.1 21.2 3.2 0.5
Table 5

~SY Mean Conta~s, Percentage of Telephone Intetiews and Convened

lntefiews, by Year

Sumey Year Mean Number of Phone Intefiews Converted

Contacts Intetiews

1979 3.14 4.3 1.2

1980 4.52 4.5 1.0

1981 5.26 5.2 1.4

1982 5.68 8.1 2.0

1983 5.74 2.3 2.4

1984 6.20 5.1 4.1

1985 6.50 8,4 5.4

1986 6.51 8.6 5.1

1987 8.70 89.0 13.6

19g8 6.80 8.9 7.8

1989 6.43 14.1 16.6

1990 6.34 12.2 13.0

1991 6.60 13.7 17.7
figure 1 NLSY Interview Length by Year

140 T

l— Mean time ~ 10 percent “- 90 percent \
0.2

Ha* 0.15 ard 01 Ra O@ te o

4

O123456789 10 II 12 13 14 15

Y=
500

450

400

350

300

250

200

150

100

50

0

Hgure 4 Number of NLSY Questions Asked by Year

\

m 0. N m m a h m m o

F m m m m $ m m m w m m z

m m m m m m m m m m m m m

— Average # of questions — 1070 —+— go oh
.

6861

0661

I

986

Lti61

8861

L

S86 L

ti86 L

6L61

0861

L86L

2861

C861

O.m

-

Ha O.W

-

.

za~ O,m

-. d

O.Q.-

Ra

tam.

.

e

O123456769 10 II 12 13 14 15

YH
Variable Definitions

v-ABLE DEF~ION

BLACK Black

msPANc Hispanic

Omitted category = Nonbl?gk nONsPtic

BYC1958 Year of btih 1958.. .

BYC1959 Yesr of birth 1959

BYC1960 “Y% of birth 1960

BYC1961 Year of btih 1961

BYC1962 Year of birth 1962

BYC1963 Year of birth 1963

BYCI 964 Yesr of btih 1964

Omitted category = Year of birth 1957

NO RELIGION No reh~on

CA~OLIC Cathofic

0~ ~LIGION Other refigion

Omitted category = Protestantrefigion

PARENTS HH parents fivingin household.

Omitted category = Parentsnot fiting in household

~D Msrried

PREV ~D Previously married

Omittedcategory’. Never.@~

CHANGE ~S Change in maritalstatus

Omitted category = No change in mtitd status

NO~SNHH No childrenin household

Omitted category = Children..nhousehold.

#OF~SHH Number of ow childrenkshousehold

SCHOOL ~SS Currentenrokent missing

~ SCHOOL . Currentiyenro~ed in school

Ofitted category= Currady not enrofledin school

HOC ~SS~G Highest grade completed missing

HS DROP-0~ ~gh school dropout

SOW COLLEGE Some co~ege

COLLEGE GRAD College graduate

Omitted mtegory = High school graduate

E~LOYED Employed

Omitted catego~ = Not employed

EARN M3SS~G Earningstissing

Em RE~SED E-gs refused

Omitted category = Earningsnot refised
EARN RP~K Earningsrefi.sed aod don’t know responses combined

Omitted categoV = Earningsnot refised and known

EARN ~RO Earningszero

EARN LOW 10% Esrningsin lowest 10thpercentie

Em 10~0-25~o Earningsin 10th.to 25th percentile

EARN 50Y.75Y0 Earningsin 50th to 75th percentie

EARN UPR 75~o Earnings in 75th+ percentile

Omitted category = Earnings in 25th to 5~ percentile

# JOB MSSNG Number ofjobs missing

Aw#JOB~~ Average numberofjobs per year

WW MSS~G Number of weeks worked missing

Wwmm Number of weeks worked per year

REGION MSS Region of residence rnisstig

NORTH-CENTRL North-centrrdregion of residence

Som South region of residence

-ST West region of residence

Omittedcategory = Northeast region of residence

~AN ~SSNG Urbanresidencemissing

NOT SMSA Residence not in an SMSA

SMSA NO CITY Residence in SMSA not centralcity

SMSA DK C~Y Residence in SMS~ centralcity not &own

SMSA CT CITY Residence in SMS& centi city

Omitted category = Residence@

CO~RT ~SS Interviewconverted ndssing

CO~RTED Interviewconverted

Omittedcategory = kterview not converted .

#CONT MSSNG Number of attemptedcontacts

WONT LW 10% Number of attemptedcontacts lowest 10th.percentile

#coNT 10-50% Number of attemptedcontacts 75ti to 90h percentie

#tom 75-90% Number of attemptedcon~cts 75X. to 90h.percentie

#coNT UP 90V0 Number of attemptedmntacts 90th + percentde

Ornittd category= Number of attemptedcontacts 5tih to 75th perce

~TYPE MSS Intdew mode missing

TELEPHONE Intefiew mode telephone

MERSON OTH hterview mode in person ~th others present

~ERSON DK hterview mode in perso~ other presentunknown

Omitted catego~: ktetiew mode in perso~ no others present

DRUG QUESTNS Drug questionsasked in suwey year

OmittedcategoV = Drug questions not asked in smey year

DRUG REWSED Drug questions refised

Omitted catego~ = Drug questionsanswered

ATT ~SS~G Mltode toward interviewmissing

NO ~REST Not interestedattidudedurkrginteriew

MAT~NT hpatient attitide duringinterview

HOSTWE Hostie attitudeduringintefiew

ntie
Omitied category= ~terested .~d cooperative attitudeduringinterview

WER ~SSNG Understandingof intefiew missing

FM ~ERST Understi&ng of interviewftir

POOR ~ERST Understan&.ngof interviewpoor

Omitted catego~ = Understandingof interviewgood

#QSO-10% O-5 Number of questions, Oto 10thpercentile,years Oto 5

#QSIO-25%0-5 Numbm of questions, 10thto 25th percentie, years Oto 5

#QS50-75%0-5 Number of questions, 50th to 75th percentile,years Oto 5

#QS75-90%0-5 Number of questions, 75th to 90th percentile,years Oto 5

#QS90%+ O-5 ..Numberof questions, 90th+ percentfie,years Oto 5

Otitted catego~ = Number of questions, 25th to 5Mh percentde, years Oto 5

WQO-25% O-5 Average numberof questions, Oto 25th percentile,years Oto 5

WQ50-75%0-5 Average numberof questions, 50th to 75th percentie, years Oto 5

MQ75%+ O-5 Average number of questions, 75th+ percentie, years Oto 5

Omitted category = Average numberof questions, 2th to 5Mh percentile,years Oto 5

#QSO-10YO5-9 Number of questions, Oto 10thperccntfie,years 5 to 9

#QS 10-25%5-9 Number of questions, 10thto 25th percentile,years 5 to 9

#QS50-75Y05-9 Number of questions, 50th to 75th percentile,yms 5 to 9

#QS75-90%5-9 Number of questions, 75th to 90th percentile years 5 to 9

#QS90%+ 5-9 Number of questions, 90th+ percentile, years 5 to 9

Omitted category = Number of questions, 50th to 75th percentile,years 5 to 9

WQO-25% 5-9 Average numberof questions, Oto 25th percentile,years 5 to 9

MQ50-75%5-9 Average number of questions,50thto 75th percentile,years 5 to 9

tiQ75%+ 5-9 Average numberof questions, 75th+ percentie, years 5 to 9

Omitted category = Average numberof questions, 25ti to 50th percentie, years 5 to 9

#QSO-10YO9+ Number of questions, Oto 10thpercentile,.years9+

#QSIO-25% 9+ Number of questiom, 10thto 25th percentfie,years 9+

#QS50-75% 9+ Number of questions, 50th to 75th percentfie,years 9+

#QS75-90% 9+ Number of questions, 75th to 90th perccntfle,years 9+

#QS90%+ 9+ Number of questions, 90th+ percentile,years 9+

Omitted category = Number of questions,25th to 50th percentile, years 9+

A#QO-25°A 9+ Average numberof questions, Oto 25th percentile, years 9+

A#Q50-75”A 9+ Average n~ber of questions, 50th to 75th percentile,years 9+

A#Q75%+ 9+ Average numberof questions, 75th+ percentile,years 9+

Omittedcategory = Average numberof questions,25th to 50th percentie, years 9+

m <300-5 htefiew lengthless than30 minutes,years o-5

m3045 o-5 hterview length30 to 45 minutes,years o-5

~60-75 O-5 kterview length60 to 75 minutes,years O-5

m75-90 o-5 Interviewlength75 to 90 minutes,years O-5

m 90+ o-5 hterview length9tinutes, years O-5

Omitted category = Interviewlength45 to 60 minutes,years o-5

Am< 450-5 Average intefiew lengthless than45 minutes,years O-5

A~60-75 O-5 Average interviewlength60 to 75 minutes,years O-5

An75-90 O-5 Average intetiew length75 to 90 minutes,years O-5

Am 9W O-5 Average intetiew length90+ mirstitcs,years o-5
Ondtted category= Average irrtetiew length45 to 60 fiutes, yem O-5

m <305-9 kterview lengthless than30 tinutes, years 5-9

m3045 5-9 kterview Iagth 30 to 45 minutes,years 5-9

~60-75 5-9 hterview length60 to 75 minutes,years 5-9

m75-90 5-9 hterview length75 to 90 minutes,years 5-9

m 90+ 5-9 htefiew length90+ ndnutes,years 5-9

Ofitted category= Intefiew length45 to 60 rrdnutes,years 5-9

AW<455-9. Average inte~ew !ength less than45 minutes,years 5-9

A~60-75 5-9 Average interview length60 to 75 tiutes, years 5-9

AW75-90 5-9 Average intetiew length75 to 90 nrinutes,years 5-9

Am 90+ 5-9 -. Average intefiew length90+ minutes,years 5-9

Onrittedcategory= Average intetiew length45 to 60 tiutes, y- 5-9

m<30 9+ kttiew Ierrgthless than30 minutes,years%

m3045 9+ kterview len@ 30 to 45 minutes,years 9+

~60-75 9+ titerview length60 to 75 nrinutes,years 9+

m75-90 % ktetiew length75 to 90 minutes,years 9+

m 90+ 9+ kterview length90+ tiutes, years 9+

Otitted category= btefiew length45 to 60 tiutes, years W

Aw <45 9+ Average interviewlen@h less than45 rnirurtes,years 9+

A~60-75 9+Average intetiew length60 to 75 tiutes, years 9+

A~75-90 9+ Average ktetiew length75 to 90 fiut~ years9+

Am 90+ 9+ Average titefiew length9W minutes,years 9+

Otitted category= Average intefiew length45 to 60 minutes,years 9+

CONST ~ O-5 Constantte~ years Oto 5

LM~ Y O-5 Linearte~ years Oto 5

QUm ~ O-5 Quadraticte~ years Oto 5

CONST ~ 5-9 Cons~t te~ years 5 to 9

LN~ Y 5-9 Linear te~ years 5 to 9

CONST m 9+ Constantte~ years 9+

LN~ Y 9+ Linear te~ yms 9+
NONRESPONSE HAZARD ESTI~TION FOR MEN

INCLUDING INTERVIEW “LENGTH

*** UNNORMALIZED LIKELIHOOD VAL~ = “-1.312 ***

VARIABLE

B—-

HIS

BYC

BYC

BYC

\T,ACK —

PANC =

1958 =

1959 =

1960 =

BYC1961 —-

BYC1962 =

BYC1963 =

BYC1964 –—

NO RELIGION =

CATHOLIC -—

OTH RELIGION=

PARENTS HH =

=IED =

PREV MARRIED=

CHANGE MARRS=

NO KIDS N HH=

# OF KIDS HH=

SCHOOL MISS =

IN SCHOOL =

HGC MISSING =

HS DROP-OUT =

SOME COLLEGE=

COLLEGE GRAD=

EMPLOYED =

~ MISSING=

EARN REFUSED=

EARN RF&DK =

EARN ZERO =

EARN LOW 10%=

EARN 10%-25%=

EARN 50%-75%=

EARN UPR 75%=

# J.OB MISSNG=

AVE#JOB/YEAR=

WW MISSING =

ww/YEAR =

REGION MISS =

NORTH-CENTRL=

SO~H —

WEST —

URBAN MISSNG=

NOT SMSA –—

SMSA NO CITY=

SMSA DK CITY=

SMSA CT CITY=

CONVERT MISS=

CO~RTED =

#CONT MISSNG=

#CONT LW 10%=

#CONT 10-50%=

#cONT 75-90%=

#CONT UP 90%=

ESTIMATE

-0.077496

0.191082

0.246143

0.043419

0.171718

0.037779

-0.073967

.-0.038166

-0.189999

-0.091198

.-0.014806

0.191661

“-0.063741

0.196135

0.103339

-0.324116

-0.014664

-0.327756

-2.877777

-0.327058

0.897769

0.231531

-0.071104

-0.127576

-0.184217

0.386762

0.415831

0.403836

0.104812

-0.180620

0.016161

-0.017083

0.129845

.0.608920

0.198017

-0..766510

-0.009625

0.776162

-0.327961

-0.178714

-0.140783

0.382252

0.193749

-0.080297

-0.025253

0.266432

-0.723306

0.969343

0.444304

-0.432207

-0.379621

0.145174

0.403410

STD ERROR

0.089567

0.103696

0.153910

0.157634

.0.150127

0.160253

0.161871

0.168789

0.184316

0.163264

0.096963

0.114102

0.092209

0.130709

0.173308

0.163624

0.219321

0.120486

1.568567

0.115842

1.007761

0.096126

0.110084

0.141362

0.104272

0.288358

0.360121

0.236642

0.166042

0.189043

0.143900

0.115074

0.117420

0.393711

0.128441

0.385035

0.005138

0.241581

0.110717

0.103301

0.116411

0.1601”54

0.165419

0.123879

0.123101

0.131417

0.664028

0.106613

0.406873

0.151773

0.132710

0.128133

0.110660

T - STAT

-0.8652:.

1.8427

1.5993

0.2754

1.1438

0.2357

-0.45.70

-0.2261

-1.0308

-0.5586

-0.15.27

1.6797

-0.6913

1.5006

0.5963

-1.9809

-0.0669

-2..7203

-1.8347

-2.8233

0.8909

2.4086

-0.6459

-0.9025

-1.7667

1.3413

1.1547

1.7065

0..6312

-0.9554

0.1123

-0.1485

1.1058

1.5466

1.5417

-1.9908

-1.8732

.3.2128

-2.9622

-1.7300

-1.2094

2.3868

1.1713

-0.6482

-0.2051

2.0274

-1.0893

9.0922

1.0920

-2.8477

-2.8605

1.1330

.. 3.6455
INTTYPE MISS=

TELEPHom=

INPERSON OTH=

INPERSON DK=

DRUG QUESTNS=

DRUG REFUSED=

ATT MISSING=

NO INTEREST=

IMPATIENT=

HOSTILE=

UNDER MISSNG=

FAIR UNDERST=

POOR UNDERST=

INT< 30 O-5=

INT30-45 0-5=

INT60-75 O-5=

INT75-90 O-5=

INT 90+ o-5=

A=< 45 o-5=

A~60-75 O-5=

A~75-90 O-5=

An 90+ o-5=

INT< 30 5-9=

INT30-45 5-9=

INT60-75 5-9=

INT75-90 5-9=

INT 90+ 5-9=

Am< 45 5-9=

A~60-75 5-9=

A~75-90 5-9=

Am 90+ 5-9=

INT< 30 9+=

INT30-45 g+=

INT60-75 g+=

INT75-90 9+=

INT 90+ 9+=

Am< 45 9+=

A~60-75 g+=

A~75-90 9+=

Am 90+ g+=

CONST YR O-5=

LINEARY O-5=

QUAD YR o-5=

CONST YR 5-9=

LINEARY 5-9=

CONST~ 9+=

LIY 9+=

1.268994

0.278995

0.092562

-0.718348

-0.103873

0.905098

-0.055364

0.545785:

0.965485

1.824514

0.443240

-0.170451

-0.291399

1..688132

0.507797

-0.089850

-0.709271

-0.35675”7

-0.155025

0.620449

1.001331

1.038160

0.157708

-0.112335

-0.273293

-0.183546

-0.393419

0.101097

-0.185764

0..141965

-0.033769

-0.370725

-0.318406

-0.156451

-0.826109

0.571769

0.035767

-0.273159

-0.913866

-1.451234

-1.920920

-1.638588

0.224050

-2.673922

-0.077794

-2.613683

-0.090489

0.406268

0.103148

0.093635

0.506662

0.141143

0.652773

0.651820

0.083542

0.138618

0.2~0918

0.571290

0.111040

0.225147

0.492000

0.312222

0.252242

0.305532

0-319210

0.500246

0.274702

0.301629

0.339550

0.244534

0.206348

0.250203

0.300635

0.305649

0.405905

0.180177

0.224358

0.370039

0.248213

0.224297

0.306124

0.439112

0.367173

0.364675

0.193017

0.370216

1.257117

0.542084

0.347182

0.066911

0.901933

0.112361

0.976040

0.079051

3.1235

2.7048

0.9885

-1.4178

-0.7359

1.3865

-0.0849

6.5330

6.9651

6.7346

0.7759

-1.5350

-1.2943

3.4312

1.6264

-0.3562

-2.3214

-1.1176

-0.3099

2.2586

3.3197

.3.0575

0.6449

-0.5444

-1.0923

“-O.61O5

-1.2872

0.2491

-1.0310

0.6328

-0.0913

-1.4936

-1.A196

--0.5111

-1.8813

1.5572

0.0981

-1.4152

-2.4685

-1.1544

-3.5436

-4.7197

3.3485

-2.9647

-0.6924

-2.6778

-1.1447
NO~ESPONSE mZARD ESTI~TION FOR WO~N

INCLUDING INTERVIEW ”LENGTH

*** UNNO-IZED LIKELIHOOD VALUE = -1.009 ***

VARIABLE

BLACK

HISPANC :.

BYC1958 =

BYC1959 =

BYC1960 =

BYC1961 ‘=

BYC1962 =

BY ___ --

NO RELIGION =

CATHOLIC =

OTH RELIGION=

PARENTS R =

-IED =

PREV MARRIED=

CWGE MARRS=

NO KIDS N ~=

# OF KIDS HH=

SCHOOL MISS =

IN SCHOOL =

HGC MISSING =

HS DROP-OUT =

SOME COLLEGE=

COLLEGE GRAD=

EMPLOYED =

EARN MISSING=

EARN REFUSED=

EARN RF&DK =

_ ZERO =

EARN LOW” 1O%=

EARN 10%-25%=

EARN 50%-75%=

- UPR 75%=

# JOB MISSNG=

AVE#JOB/YEAR=

WW MISSING =

WW/YEAR =

REGION MISS =

NORTH-CENTRL =

SOUTH ——

WEST

URBAN MISSNG:

NOT SMSA =

SMSA NO CITY=

SMSA DK CITY=

SMSA CT CITY=

CONVERT MISS=

CONVERTED =

#CONT MISSNG=

#CONT LW 10%=

#coNT 10-50%=

ESTINATE

-0.081170

0.167190

-0.176414

-0.041192

-0.101024

-0.376686

-0.167863

,-0.301083

-0.589481

0.043056

0.254831

0.390007

0.137278

0.346822

0.163782

0.042950

0.321117

-0.135504

-0.842462

-0.412559

0.134548

0.000341

0.179194

-0.035317

-0.158633

0.042824

0.853964

-0.004761

-0.065514

-0.224559

-0.262226

0.041624

-0:108969

0.082021

0.051555

-0.022765

-0.014060

0.370791

-0.014223

0.020889

0.025061

0.439388

-0.171017

0.083636

0.122856

0.3.89214

0.252905

1.151551

1-361259

0.013335

-0.423341

STD =RROR

0.108138

0.114949

0.160923

0..=6373

0.156695

0.169045

0.171562

0.180866

0.203570

0.260950

0.106003

0.121992

0.108188

0.U8.679

0.163798

0.147992

0.166710

0.086316

0.981141

0.E2681

0.732186

0.H6187

0.108774

0.152867

0.1~651

0.327477

0.403126

0.309137

0.160554

0.187697

0.163595

0.128922

0.15145s

0.441154

0.173773

0.429658

0-006357

“0.324226

0.124852

0.1.20475

0.134294

0.202129

0.198461

0.128608

0.132595

0.~.0162

0.541768

0.116898

0.489803

0.149135

0.140592

.T-STAT

._-O.7506

1.4545

-1-0963

-0.2634

.-0.6447

-2.-2283

-0.9784

-1.6647

-2.89”57

0.1650 :

2.4040

3-1970

1.2689

2.9224

0.9999

0-2902

1.9262

-1.5699

-0.8587

-3-3629

0.1838

0.0027

1.6474

-0.2310

-1.3958

0.1308

‘. 2.llg4

.-0.0154

-0.4080

-1.1964

-1.6029

.0.3229

-0.7195

‘0..1859

O .2967

-0.0s30

-2.2118

.1..1436

-0.1139

0.1734

0.1866

2.1738

-.0.8617

0.6034

0.9265

2.5920

0.4668

9.8509

2.7792

0.0894

-3.0111
#coNT 75-90%=

#CONT UP 90%=

INTTYPE MISS=

TELEPHONE=

INPERSON OTH=

INPERSON DK=

DRUG QUESTNS=

DRUG REFUSED=

ATT MISSING=

NO INTEREST=

IMPATIENT=

HOSTILE

——

UNDER MISSNG=

FAIR UNDERST=

POOR UNDERST=

INT< 30 O-5=

INT30-45 o-5=

INT60-75 O-5=

INT75-90 O-5=

INT 90+ o-5=

Am< 45 O-5=

AW60-75 O-5=

AW75-90 O-5=

Am 90+ o-5=

INT< 30 5-9=

INT30-45 5-9=

INT60-75 5-9=

INT75-90 5-9=

INT 90+ 5-9=

Am< 45 5-9=

A~60-75 5-9=

A~75-90 5-9=

Am 90+ 5-9=

INT< 30 9+=

INT30-45 9+=

INT60-75 9+=

INT75-90 9+=

INT 90+ 9+=

Am< 45 9+=

A~60-75 9+=

A=75-90 9+=

Am 90+ 9+=

CONST YR O-5=

LI~ARY O-5=

QUAD~ O-5=

CONST YR 5-9=

LI~Y 5-9=

CONST YR 9+=

LINEARY 9+=

0.432472

0.588902

-0.436877

0.457614

-0.004424

-0.194455

-0.387524

1.774349

1.385296

0.806960

1-471330

2.159783

-0.623546

-0.071922

-0.337417

1.016673

0.340658

-0.106269

-0.175528

-0.180841

-0.557055

-0.186825

-0.049741

0-087145

0.012381

-0.370906

-0.310783

-0.088382

0.110826

0.197092

-0.296175

-0.612493

-0.”616510

0.075131

0.307141

0.469927

-0.052782

0.241401

-0.140402

-0.415211

-0.322459

-1-940734

-2.197406

-1.277366

0.145752

-2.829703

-0.124715

-4.572331

-0.013125

0.139656

0.132956

0.594457

0.113890

0.112706

0.627752

0.166242

0.759752

0.602948

0.097715

0.159871

0.326793

0.622963

0.138775

0.302317

0.723884

0.3~5148

0.279996

0.315866

0.363667

0.492237

0-268358

0.306143

0.360801

0.329432

0.234246

0.260700

0.314750

0.299126

0.544549

0.201071

0.264868

0.388870

0.304810

0.277372

0.356514

0.457638

0.469038

0.512768

0.220349

0.357666

1.0~2285

0.538230

0.385818

0.075653

1.029557

0.130559

1.111149

0.089026

3.0967

4.4293

-0.7349

4.0180

-0.0393

-0.3098

-2.3311

2.3354

2.2975

8.2583

9.2033

6.6090

-1.0009

-0.5183

-1.1161

1.4045

1.0809

-0.3795

-0.5557

-0.4973

-1.1317

-0.6962

-0.1625

0.2415

0.0376

-1.5834

-1.1921

-0.2808

0.3705

0.3619

-1.4730

-2.3124

-1.5854

0.2465

1.1073

1.3181

-0.1153

0.5147

-0.2738

-1.8843

-0.9016

“-1-8800

-4.0827

-3.3108

1.9266

-2.7485

-0.9552

-4.1150

-0.1474
NONRESPONSE WARD ESTI~TION FOR MEN

INCLUDING NUMBER OF QUESTIONS ASKED

*** ~OwIZED LIKELIHOOD VAL~ =

VARIABLE

BLACK

HISPANC =

BYC1958 =

BYC1959 =

BYC1960 =

BYC1961 -—

BYC1962 =

BYC1963 =

BYC1964 =

NO ~LIGION =

CATHOLIC =

OTH RELIGION=

PARENTS HH =

WIED =

PREV MARRIED=

CHANGE MARRS=

NO KIDS N HH=

# OF KIDS ~=

SCHOOL MISS =

IN SCHOOL =

HGC MISSING =

HS DROP-OUT =

SOME COLLEGE=

COLLEGE GRAD=

EMPLOYED –—

W MISSING=

EARN REFUSED=

EARN RF&DK =

EARN ZERO =

EARN LOW 10%=

~ 10%-25%=

EARN 50%-75%=

EARN UPR 75%=

# JOB MISSNG=

AW#JOB/YEAR=

WW MISSING =

ww/Ym =

~GION MISS =

NORTH-CENTRL=

SOUTH

WEST

URBAN MISSNG=

NOT SMSA .=

SMSA NO CITY=

SMSA DK CITY=

SMSA CT CITY=

CONVERT MISS=

CONVSRTED =

#CONT MISSNG=

#CONT Lw 10%=

#CONT 10-50%=

#coNT 75-90%=

ESTIMATE

.-0..058698

.0.212819

0.242999

0.026191

0.158673

0.011609

-0..129105

-0.140159

-0.320811

-0.102833

: 0.001471

0.183365

-0.054481

0.214661

0.140348

-0.348410

-0.0.05680

,-0.293343

-2.868990

-0.363239

0.888029

0.206023

-0.018528

-0.054738

-0.194951

0.332224

0.442298

0.370560

0.0825.86

-0.249247

-0.003578

-0.008838

0.123079

0.687057

:.0.450438

-0.826649

-0.008084

0.746641

-0.326736

-0.195457

-0.132679

0.391774

0.172430

.-0.067619

-0.014800

0.265053

-0.719704

0.981346

0.413444

-0.421339

-0.390358

0.144119

.STD ERROR

0.088581

0:1Q3687

0.153114

0-156914

0.149607

0.159458

0.160299

0.169670

0.193267

0.164188

0.096543

0.112784

0.094049

0.131198

0.176937

0.164149

0.220073

0.122211

1.542927

0.116083

0.959172

0.097272

0.110525

0.140939

0.104839

0.292294

0-353775

0.235996

0.167493

0.196056

0.144400

0.116593

0.118108

0.396285

0.152804

0.392065

0.005325

0.244049

0.110015

0.103237

0.116679

0.160416

0.164713

0.123877

0.123271

0.130773

0.655055

0.106987

0.409074

0.151292

0.132082

0.127129

-1.312  

T - STAT

-0.6627

2.0525

1.587”0

0.1669

1,06Q6

0.0728

-0-8054

-0.8261

-1.6599

-0.6263

0.0152

1.6258

-0.5793

1.6362

0.7932

-2.1225

-0..0258

-2.4003

.-1.8594

-3.1291

Q-9258

2.1180

–0.1676

-0.3884

-1.8595

1.1366

1.2502

1.5702

0.4931

-1.2713

-0.0248

-0.0758

1.0421

1.7337

2.9478

-2.1085

“-1.5181

3.0594

-2.9699

-1.8933

-1.1371

2.4422

1.0468

-0.5459

-0.1201

2.0268

-1.0987

9.1725

1.0107

-2.7849

-2.9554

1.1336
#coNT UP 90%=

INTTYPE MISS=

TELEPHONE=

INPERSON OTH=

INPERSON DK=

DRUG Q~STNS=

DRUG REFUSED=

ATT MISSING=

NO INTEREST=

TMPATIENT=

it__-–– 3STILE

UNDER MISSNG=

FAIR UNDERST=

POOR UNDERST=

#oso-lo% ..-— 0-5=

#OSIO-25%0-5= ..-.

#QS50-75%0-5=

#QS75-90%0-5=

#QS90%+ O-5=

A#QO-25% O-5=

A#Q50-75%o-5=

A#Q75%+ o-5=

#QSO-10% 5-9=

#QSIO-25%5-9=

#QS50-75%5-9=

#QS75-90%5-9=

#QS90%+ 5-9=

A#Qo-25% 5-9=

A#Q50-75%5-9=

A#Q75%+ 5-9=

#QSO-10% 9+=

#QSIO-25% 9+=

#QS50-75% 9+=

#QS75-90% 9+=

#QS90%+ 9+=

A#QO-25% g+=

A#Q50-75% 9+=

A#Q75%+ 9+=

CONST YR O-5=

LINEARY O-5=

QUAD YR O-5=

CONST YR 5-9=

LINEARY 5-9=

CONST YR 9+=

LINEARY 9+=

0..397473

1.248761

0.301240

0.086022

-0.691776

-0.124969

0.815245

-0.024293

0.556994

0.951501

1.883210

0.390991

-0.181048

-0.283598

0.509778

-0.514796

-0.494119

-0.444986

-0.554747

0.000000

-0.551279

-0.514200

-0.274475

0.313751

0.014268

-0.024370

-0.694203

0.722525

-0.375836

-0.367821

0.122116

-0.064095

0.238010

0.116448

0.773202

-0.079522

-0.282501

-2.588438

-0.330232

-1.776788

0.237950

-2.483179

-0.116380

-3.036336 ‘.

-0.094541

0.110484

0.408478

0.102083

0.094211

0.507725

0.146422

0.658093

0.648699

0.083176

0.138014

0.265742

0.571213

0.111662

0.225890

0.543627

0.3”15402

0.224505

0.271262

0.315168

0.000000

0.280362

0.348377

0.263849

0.208192

0.205140

0.290439

0.471936

0.669435

0.188676

0.332880

0.247805

0.268554

0.237355

0.,320692

0.369324

0.566033

0.194066

0.852636

0.680815

0.390291

0.070959

0.973865

0.125409

1.001558

0.080268

3.5.976

3.0571

2.9509

0.9131

-1.3625

-0.8535

1.2388

-0.0374

6.6966

6.8942

7.0866

0.6845

-1.6214

-1.2555

0.9377

-1..6322

-2.2009

-1.6404

-1.7602

0.0000

-1.9663

‘“””-1.4760

-1.0403

1.5070

0.0696

-0.0839

-1.4710

1:0793

-1.9920

-1.1050

0.4928

-0.2387

1“: 0028

0.3631

2.0936

-0.1405

-1.4557

-3.0358

-0.4851

-4.5525

3.3533

-2.5%98

-0.9280

-3.0316

-1.1778
NONRESPONSE HAZ~ ESTImTION FOR WOMEN

INCLUDING NUMBER OF QUESTIONS ASKED

** * ~0-IZED LI~LIHOOD v~~ =

V~IASLE

BLACK

HISPANC =

BYC1958 =

BYC1959 =

BYC1960 =

BYC1961 =

BYC1962 =

BYC1963 =

BYC1964 =

NO ~LIGION =

CATHOLIC =

OTH RELIGION=

PARENTS HH =

MARRIED =

PREV ~IED=

-GE ~s=

NO KIDS N ~=

# OF KIDS HH=

SCHOOL MISS =

IN SCHOOL =

HGC MISSING =

HS DROP-OUT =

SOME COLLEGE=

COLLEGE G-=

EMPLOYED =

_ MISSING=

_ ~FUSED=

EARN RF&DK =

~ ZERO =

E- LOW 10%=

EARN 10%-25%=

- 50%-75%=

EARN UPR 75%=

# JOB MISSNG=

AW#JOB/Ym=

WW MISSING =

ww/YEAR =

=GION MISS =

NORTH-CENT~=

SOUTH =

~ST =

URBAN MISSNG=

NOT SMSA –

SMSA NO CITYI

SMSA DK CITY=

SMSA CT CITY=

CONVSRT MISS=

CO~RTED =

#CONT MISSNG=

#CONT LW 10%=

#coNT 10-50%=

#coNT 75-90%=

#coNT UP 90%=

ESTIMATE

-0.076744

.0.143018

-0.169945

-0.035848

-0.079156

‘-0.362308

-0.161322

+0”.316653

-0.624970

0.043460

0.263816

0.378084

0.184049

0.327920

0.161811

0.065984

0.282176

-0.091020

-0..911896

-0.423059

0-205615

-0.061537

0.218813

0.014518

-0.133664

0.005528

0.819077

-0.032131

-0.137240

-0.256745

-0.274453

.0.029250

-0.129842

0.205589

0.224636

-0.293839

-0.013626

0.318369

0.016331

0.011022

0.048843

0.442190

-0.133503

0.097747

0.133473

0.395317

0.271625

1.124093

1.366500

-0.004749

-0.436804

0.432871

0.592219

STD ERROR

0.108484

0.113730

0.16.0879

0.155687

0.155833

0.168080

0.172789

0.182633

0.207810

0’.260397

0.106928

0.121961

0.109342

0.118327

0.162980

0.147180

0.168671..

0.091107

0.972822

0.123408

0.733386

0.126449

0.108827

0.153701

0.115117

0.3j6904

0.399920

0.307376

0.160626

0.190447

0.167186

0.131933

0.153011

0.441133

0.192763

0.436146

0.00646”7

0.323230

0.123285

0.119449

0.133635

0.2.01684

0..199171

0.138868

0.132369

0.150759

0.545018

0.116976

0.475723

0.149198

0.141295

0.139126

0.133587

-1.0102 ****

T - STAT

-0.7074

1-2575

-1.0563

-0.2303

-0.5080

-2.1556

-0-9336

-1.7338

-3.0074

0.1669

2..4672

3.1000

1-6832

2.7713

0..9928

0-4483

1.6729

-0.9991

-0.9374

-3.4281

0-2804

-0.4867

2.0106

0.0945

-1.1611

0. 0“169

2.0481

-0.1045

-0.8544

-1.3481

-1.6416

0.2217

‘-0.8486

0.4660

1.1653

-.0.6737

-2.1070

0.9850

0.1325

0.0923

0.3655

2.1925

-0.6703

0.7039

1..0083

2.6222

0.4984

9.6096

2.8725

-0-0318

-3.0914

3.1114

4.4332
INTTYPE MISS=

TELEPHO~=

INPERSON OTH=

INPERSON DK=

DRUG QUESTNS=

DRUG RE~SED=

ATT MISSING=

NO INTEREST=

IMPATIENT=

HOSTILE=

UNDER MISSNG=

FAIR UNDERST=

POOR UNDERST=

#QSO-10% O-5=

#QSIO-25%0-5=

#QS50-75%0-5=

#QS75-90%0-5=

#QS90%+ o-5=

A#QO-25% O-5=

A#Q50-75%o-5=

A#Q75%+ 0-5=

#QSO-10% 5-9=

#QSIO-25%5-9=

#QS50-75%5-9=

#QS75-90%5-9=

#QS90%+ 5-9=

A#QO-25% 5-9=

A#Q50-75%5-9=

A#Q75%+ 5-9=

#QSO-10% 9+=

#QSIO-25% 9+=

#QS50-75% 9+=

#QS75-90% 9+=

#QS90%+ g+=

A#QO-25% 9+=

A#Q50-75% 9+=

A#Q75%+ g+=

CONST YR O-5=

LI=Y O-5=

QU~ YR O-5=

CONST YR 5-9=

LINEARY 5-9=

CONST YR 9+=

LIY 9+=

-0.422395

0.439248

-0.005229

-0.189397

-0.458403

.1.792682

1.426478

0.829081

1;”482991

2.186373

-0.681028

-0.085982

-0.345483

0.862489

0.538829

-0.022179

-0.067719

-0.418155

-1.000280

-0.325024

-0.377334

-0.209005

0.136803

-0.053401

0.062677

-0.000678

.0.647498

-0.427955

-0.730976

0.200709

0.227605

-0.094329

-0.420314

0.136805

-0.714090

-0.254067

-0.354803

-1.420228

-1.626739

0.183662

-2.454935

-0.203823

-3.995844

-0.064573

0.590698

0.112239

0.113489

0.635455

0.177884

0.757000

0.588147

0.096227

0.159666

0.325140

0.616237

0.138314

0.301904

0.637638

0.322323

0.251900

0.318660

0-352077

0.867057

0.302025

0.392358

0.353705

0.256878

0.233271

0.282725

0.379291

1.269340

0.226662

0.32”1501

0.295460

0.285361

0-314032

0-382756

0.361365

1.096532

0.228801

0.406367

0.716872

0.426060

0.079703

1.066977

0.138001

1.0?9902

0.090783

-0.7151

3.9135

-0.0461

-0.2980

-2.5770

2.3681

2.4254

8.6159

9-2881

6.7244

-1.1051

-0.6216

-1.1443

1.3526

1-6717

-0.0880

-O ;2125

-1.1877

-1.1536

-1.0762

-0.9617

.-0.5909

0.5326

-0.2289

0.2217

-0.0018

0.5101

-1.8881

-2.2736

0.6793

0.7976

-0.3004

-1.0981

0.3786

-0-6512

-1-1104

-0.8731

-1.9811

-3.8181

2.3043

-2.3008

-1.4770

-3.6329

-0.7113
-

01

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13

National Longi@dinal Sumeys @LS)

Discussion Paper Series

-..

MichaelR Pergdt

No- M. Bmdbm

=n R Fr~el

Regitid P. Baker

Mcbsel R. Per-t

Sad SchWkfi Hutchens

George JAbwn

A. Colti Caeron

R Mk Griti

Thomas Mstidy

Hemy S. Fmber

Fr& L. Mott

PatiaBsk~

Au&q Light

Wuefita Ureta

Lim M. Lwch

me ~

Jme E. ONeill

Lee A. L&d

Jos~hG.Aftonji

ThomssA. Dmm

~

HOWtheFedd bemmt UsesDamfrom

theNatioti Longitu&ti Swqs

A Comptisonof Computer-AssistedPe~oti

Intetim (CAP~titb Pa~r-mdPentilhtertiew @API)h theNatioti bngimditi Swey

of Youth

-c Mtiels oftheJofitDtietimtion of

Labr Supplyad FtiIy StmcWe

Theeffem of Unemployment COm_tiOn

ontheUnemployment of Youth

Evdtig Com~g TheoriesofWorker

Moblfity

Etimtion of the 1989Child~me Supplement

in the Natioti Lon@titi SWey of Youth

Gender Differences ti the @t Behatim of

YOmg Woken

The tipd of Private S@Or Tting on Ww

ad Gcn&r Wage Differentis ad the Cam

Pattern of Ymmg Workers

Reapomes of Femsfe L~r Supply ad Fhlity

to the Daogmpfdc Cycle

A S@@ of htercohoti C@e in Women’s

Work Patternsad E@nga

Women’s Employment Dting Pm~q

md Follotig B!fi

Work EWeriene, JobTenwe, JobSe~atiOn,

md Wage Grow

Ftily Ba&gmmd md L~r tiket titmmes
* u S GOVERWEN1 PRINTING OFFl~ 1Vq5-6 i 2-628

14

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&rge J.Bo~m

StephenG. Broms

St-hen J.T=jo

Jaes J.Hmti

S@phenV. --on

Peter Z. Schmhti

PtidpatiOn in bw-Wage tir Mkta by

Yowg Men

Mm L. G~

Thorns L. Steimeier

Autiw Light

CtistopherJ.Rti

Dodd O. P-m

Emplo~ent Gntitity hong NW Moths