Opfiom md conclusionsex~essd in MSdmmmt ae hose of tie a“tior(s)

ad do not nmwsmily representm official position of the B.r~u of Lahr Statktics

or tie U.S. Depm.nt of L&or.
The Determinants of Public-Sector and

Private-Sector Training

James J. Heckman of National Bureau of Economic Research,

the University of Chicago, and Yale University

Stephen V. Cameron of University of Chicago, and

Peter Z. Schochet of the Mathematical Policy and Research Corporation

November 1992

.

~is final paper was funded by the U.S. Department of Labor, Bureau of Labor Statistics

under want number E-9-J-9-0048. Opinions stated in this paper do not necesstily represent the officiaJ position or policy of the U.S. Department of Labor.
Executive Summ~

b a series of empirical reaesrcb papers based on the Natiomd hngitudmd Smey of Youth

(NLS~, we have investigated tie determinants and consquencea of various fo- of post-sandary

education and training. fie god of Wi rea=cb is to broaden tie mdysis of post+andary education

to consider a variety of non-academic training optiom that are widely used but rarely studied. Thwe

options are especially important for the study of minority schooling and wortiorce attachment patterns.

Ml of our tiysea are done for de youth.

A variety of forms of non-tradltiond education are considered: pubfic job training, ditsry

training, business md proprietary schooling, mmmuni~ mllege tiucation, on the job training (foti

irrs~ction from employers) and apprentic=]p programs. Mer than adpirrg these hoicea in

isolation, we consider the choiw tiat individuals tie from the Ml sp~ they mnfront. @

analysis of choices considws tieae options as weII as tie options of wortig without formal mairdmg,

serving in tbe military without training, not working at dl, and more trdItioti educatioti choicm. We

dso consider p~icipation in “semnd chmce” activitia SU* as Addt Basic Mutation and General

Equitience Degree programs.

This study has both subatsntive and metiodologid components. New wnometric methods are

used to explore dynamic modds of choicm among discrete options at various stagea of the life cycle.

~eae methods enabIe us to extend traditional piecem~ intimation metioda that mnsider one choice at

a time in isolation from other choices to a filly dynamic setting. Such an extension tum out to be

easentid in prducing behaviorally interpretable models of schooling and training cboicea that reco@e

the selective nature of post-semndsry training and schoo~mg for minority youth. To consider transitions

in isolation from each other is to ignore the selective nature of schooling arrd-g. Grdy the most able

tiority students complete high school and attend college. Standard statistical metiods mnfound the

i
parameters of behaviorrd functions with tie psrmeters of distributions that describe the sdection proc~s

hat mak= a person eligible for a transition. In our study of the post-semrrdary choic= of minority youth,

we find hat th=e mnsiderations are emptildly important in wtimsting modds that are int~retsble.

me tools developed in WISproj~ have wide applicability in arrometrics and socialscience more

generally.

Many new emptilcd findings have been produced. me empY1cd results on job training show that

tie vast majority of young dea invwt hr ~ type of trainiig program and that most programs are taken

wifiln the first four years after mmpleting sandsry school or attaining a GED. me ordy exception to

WISrule cornea for persons taking company training. Blacb ue over-repraented in government and

m~ltsry progrmns and are under-reprwented in college and off-the-job programs. Blacks and wfdtes are

equally likdy not to participate in any program, or to participate in government training programs.

M=ured family background variables sod finsncid variables affect trtig choic~. We reject

traditiorrd models that make simple two-state (e.g. mllege-no mllege) distinctions b favor of mrdtistste

models that recogrrke a diversity of choic~. We find that once we disaggregate schoo~mg and training

choices, we produce empirical models that more closely account for difference in minority schoo~mg and

training behavior tisn do trdltioti models that ignore tie spectrum of choices mofrontirrg youti. k

models that acmunt for sdf-selection into achwlirrg, we find evidence that timme effects and srdlt

market limitstiom play strong rol~ in explaining schoo~mg and trairdrrg choic~.

me retuma to most forms of private @aWmgactivity are positive. me same cannot be asid of

- public Kaining activiw. ne longer one spends in most priwte activities, the greater tbe she of the

economic reward. An econometric curiosity that emergd horn our work is that ~tisnates of the anornic

returns to one training ativity are not affmd by exclusion or inclusion of other forma of training

activity in an mings ~uation. ~is fiding appears to vindicate the pimemd approach to estimstig

ewnomic returns that studiw one form of training in isolation of mther. ~i r~ult ordy holds for

ii
NLS

Discussion

Papers

.

.

.
earningsquatiom andnotfor quatiom for the choiceof m~od of trfifig. ~ eatiating the return

to various forms of trsitig, there appws to be litie problem with aelf+elecdon. Corrections for

endogeneiw or self-selection ordy raise standard errors and do not affect point estirnatw.

tir eatimatea rev~ that six months of off-the-job training or training in the mflitsry is ~ident

to between one and two years of mllege education. hdividuds who inv=t in such types of training are

prdlcted to earn roughly 35 cents more per hour (1986 dollars) than those who do not and they work

about 2.5 more weeks than non-brvwtora. A major limitation of th=e estimatea is their short-run

character. me ~SY msfy follows youth for a short portion of their life CYCI*.

In the course of our investigation of job training md fifecycle schooling choicm, we begin so

extensive investigation of a neglectti aocid phenomenon tie recent rapid growth in tie fraction of

persons who achieve high acbool certification by means of an ~uitiency examination rather than tiugh

the tradition route of high school graduation. h 1968, ordy five percent of dl new high school students

were awarded high school certificate= through exam cefiification. By 1987, the correapondmg figure was

in wceas of fourteen percent. Eleven percent of dl persona who mmpleted their edu~ion with a high

school degree obtained it with the GED. (GED ia short for GenerA Edrrcatiorrd Development). It is

widely believd that tie GED ia equitient to the traditionti Klgb school degree and the U.S. Cemus

equatea the two forms of high schml certification. Marry training programs adopt the GED as so

education end in itself, especially Adult Basic Education programs.

Gur andysea of the ~Y da~ cbdlenge the conventiorrd wisdom. fiarn+ertified high school

graduatea do no better in the labor market than high achml dropouts with the aarne number of years of

classroom msirring. mere is Iitie evidence of SOYdirect arrorrric benefit to msrn certification. However,

G~ recipients are more hkely to qualify for post-secondary training benefits than do dropouts. me

modst economic benefit that arises from msm certification ia solely a consequence of addltiond training

activity. GED recipients do less well in these training programs than ordirr~ high school graduat=. Gur

...

111
study finds Htie evidence of any social return to GED @t-tiIng. me private return to GED certification

arises from its role in satis&lrrg burearrcraficdlydetemrined r~irements for post-s-ndary training and

schooling programs.

A major conclusion of M]s atrrdy is the Emited value of exam measurements for prdlcting labor

market outcomes. While teats are wideIy used to evaluate schoofing and training, there is no evidence tiat

the team pr~lti succss in the labor maket. A mmparrion study of the GED fids Iitie widence that the

deterrninmm of GED test-taking are relatd to the quW1tyof the high school attendd or to job market

oPPOfiniti=. GED t=t-~g do= not appear ~ be a r=pome to standard irrcentiv= discussed in the

tradition schooling literature. GED teat-tilng explaim the apparent p=le of a post-1970 dwline in

high school graduatw as a proportion of 17-yw olds md a nw mnstanq in the proportion of persons

in tie age range 2024 with at least a high school certificate.

Mthough GED teat-tiing apparently is not explairrd by the same factors aplairdng high school

graduation we fmd that school mntinustion dwiaions are critically aff~cd by ftiy background and

local labor market variables. ~e better the opportunities for urrstiltilabor, the lower ~e Mgh achml

continuation rat=. S&ool qu~]ty do= not aff- dropping~ut b&avior once par~ background and

Iocrd labor market opportuniti~ are controlld for. Msaggregating post-high school choicw into the WI

array of academic and non-academic sfioo~mg pmdrrcea more sensible models of post-seeond~

schooling choices for minority youth ~ models that w be interpreted in a inherent b~avio~

framework).

h a more dmaggregated model, we find fiat bIack, white @ hispsnic achoofing choices are

semitive to tuition wsts, the gerreroai~ of labor-market opporturdtim which eonstitnte Atemativm to

stiooling, and to family background and schooling. We ~ evidence of forward-looking b~avior. Wlgh

school dropout rates rise when mllege tuition wsts rise. Mthough dmaggregated models with better

iv
income and tuition variables produce b~aviordly more interprable models for dl =e/*nit ~oups,

tiey do not account for eitier time serim or croaa-smiond different= -rrg tbwe groups.

,

v
Paper Smnrnariea

(1) Alternatives to College ~ucatiom Incidence and Returns For Young Md~

by Peter Z. Schochet

(2) The Nonequitience of High School Equitients

by Stephen V. Caeron and James J. Hechan

(3) MucatiorraJ and Training Transitions: Dettiants of Youth Schno~mg

and Training Transitions

Stephen V. Cameron and Jsmw J. Hectisn

(4) Dynamics of Education~ Awirrment For Blacb, ~ites and HMpsrsics

Stephen V. Cameron and James J. Hechsn

(~ Trends in College En~ Among ~t=, Blacb and HIspsnics: h Emnomic

and Emnometric Pmpective

Stephen V. Cameron and James J. Hechsn

I
I~ODU~ON

me five papers summsrtied in this report use the ~Y to broaden and deepen our

understanding of the determirrmts and consequences of schooling and &aining choic= of late adolescents

and young adults. ~me papers -tend previous studl= of mllege attendance and mmpletion by

considering the determinants of schoofirrg choices made at each age tier age 13. me studies reviewed

below extend the traditional approach by considering a broad array of nonacademic educatioti options

that are o*en selected by youthepecidly minorities. ~Is report dso mnsiders the mnomic return to

the variety of madltioti and nontrsditiorrd training and education activitiw sdected by youth.

We fid that the traditioti approach to the ecunomics of tiucstioti choices k, in sever~

respects, quite mislesdmg. Fust, in papera Q), @) ad (4), we note that youth confront a variety of

schooling and training options. & ~temative to h]gh schml graduation is GED ctiificstion. We

document that such certification h= grown in importance over time. One in eve~ seven new high schooI

cefified persons is a GED recipient. GED recipients earn no more than high school dropouts with the

same number of YWS of formrd schooling. Neifier tibary nor civflisn employers tiue an exsrucertified high acfrool degree on par with a maditiond high school degr=. me determinants of GED

cwification are different from the determinants of ord~ high school achievement. me educstioti

consequence of the two types of degr= are dso different many fewer GED recipients go onto college

and those who do finish buti two ym and four ym mlleges at a lower rate than &aditiorrsf graduates.

r me main economic incentive for obtaining a GED is that it entiti~ recipients to feder~ tici~ support

programs for post-s~ndary ducation. However GED recipients complete such programs at a much

lower rate than trsdition~ graduat~.

Second,the tiadltiond approach to the ewnomics of ducation does not mnsider the dynamics of

educstionrd choice. Either mmpleted years of schooling are studied or one grade transition in isolation

1
from other transitions h =sndned. Both approa~ea are quite rnislmdmg and ae challenged in papers

(3), (4) and (3. For rninoritiea, it is =pecidly irnpomt to mrrmol for self-selection in mmpleting Mgh

school for determining who go= on to college. Failure to acmunt for education seldvi~ r=ults in

tie now standard finding that mnomic incentives do not explti mllege attendance. Just the opposite

is found when mntrols for selection are made. h a general dynamic modd of schooling &oices, lod

labor market opportunity=, fsmfly income, college subsidlea and my background dl acwmrt for the

life cycle dynamics of schooling choices.However, here factors do not acmunt for muti of tie

difference in tie levels and timing of dlfferencea in school attendmce by race and ethrrici~. See espwidly

paper (4).

~ird, most of the previous literature that eatirnstm gross returns to schooling, vomtiond -g

and other forms of training looks at one activity in isolation from other maining and educatiomd activities.

Using the ~SY, in paper (1) we eatirnate tie returns from dl ativities in a common framework. We

find strong returns to most forms of training and education. Somewhat su~risirrgIy sod r-surirrgly we

find hat tradition approaches tiat ignore otier programs in estimating gross returns for a particular

program appm to produce valid eatimstw of hose returns.
(1) Alternatives to College =ucatiom fncidence and

Returns for Young MAes

by Peter Z. Schochet

~is study explora the incidence and short-run retoma to dtemative types of forrnd human

capiti investment programs for young men. me motivation for WISstudy rests on tie observation that

less than hdf of young adul~ attend college progr-, and tie figure is substiti~ly 1=s for black and

hisprmics. It is &us of great interest to determine the training activities of yorrtbs who do not attend

\

college. In most empirical hurnsn capiti studies it is assumed that individuals who do not attend wllege

otiy invest h on-thejob sKI1l acWisitirm. me main reason for WIS assumption is the absence of

information shout such tra-ming programs. ~Is study, hsaed on data from the random sample of the

1979-1986 National hngitudind Survey of Youth WV, shows that 52 percent of mdea between the

ages of21 and 28 reported attendance in foti training programs apart from the training receiving in

two- and four-ye= colleg+. Almost one-hflf of the 60 percent who did not attend mllege participate

in dtemative human capiti inv=~ent programs. Msngum, Msngum, ad Hansen (1990) assess tie

remrna to tiese progrm and state, “Considering tie massive volume of training ongoing in the U.S.

economy and the constant advocacy for more, it may be surprising how Etie is atidly known about the

results. ”t

Using an economic model and emnometric metiods, we study govemrnent, vocatioti and

comrnerci~, miIiq, apprenticeship, company training. and two- and four-year college education in a

unified choice ~ework. me term “unifiti” is higWlghted since the bulk of the literature that addreasm

address human capiti training programs treats participation in each program in isoIstion, whtie other

studies aggregate dl program participation witim a single “training” variable. Lltie empirical

1. Mangum, S., Marrgum, G., Hansen, G., 1990, Does it pay? Assessing the returns to &aining.

1990 IU Volume, page 1.

3
tiomation is how concerning the interactions among m may of tiaining programs-private sector and

public sector, includbg the mili~ tiaining-when smdid in the same contexmd simation ova time.

One benefit of adopting a unified choice approach is fiat we can syatematicdly ascertain whethw or not

tiere we obsemsble differences song individuals who chose the different maining progmrrrs. bother

benefit is that we a assess the comparative economic remm of mch progmm by ticludmg relevant

tiaining vaiablm that have typidly been excluded from previous smdiea. Oors ia the fist smdy that

achievea tiIs unification. 

We adopt m economic model w~ch assumes that irrdividrrds choose the program(s) that

m~imke their net present vdrse of lifetime income swesms. Family background, deud mndltion and

ability wiablw ae rrsd as explanato~ wiabl~ to proxy for the ‘costs’ of the ptiwlsr pro~ams.

Models that allow for discrete choice (multinomid probit sod multioorsdd Iogit choice models) ~e

estimated. fie estimates we used to comect for and test for potential sample seIection rid/or endogenei~

biasea when howly wage, snorrd sd~, and annrsd weeks workd re~easioos me estimated.

Orrr main fintings we summacbed io the order that they app~ in the text as follows:

1. mere is diversity in tbe pro~sm chmacteristica, dtbough there is ofien some overlap io

the t~e of tmining received acrosa the vmious pro~m. However, there ae enough differences to

suggest a possible sofiing of the d= into the progmrns based on their socio-anomie back~ound md

ability vsriablea.

2. me vast majority of md~ p~icipated in, at most, one fom of human capiti tivesnent progmm,

and, in most cases, the foti tmining begarr by tie age of 22 with an reception for fiose who received

company Eaining.

3. me sample mesm show that blacks we ovw-represented irr

we under-reprwented ti the college md off-the-job progmrns.

4

gmesnnrent and tiI~ progmnsa, md

Howwer, blacks mrd whites are qudly
likely to participate in none ofthetrainingprogrsma. High schooldropouts are Hkely to either take no

training, or to participate in government training progr-.

4. Measured family background vsriablea have explanatory power in determining the training choices of

the individuals in the sample. Both the variable means and the polychotomous choice model eatirnates

both imply a sorting of the individuals into the training program categories b~ed on tieir observable

variables. Individuds from more advantaged backgrounds are more ~ieIy to choose investment patha

fiat involve greater reaourcea than are individuals from less advsrttsg~ backgrounds.

5. me socioeconomic background variabl= seem to be prdlctors of the Wllity m=ure used in the

smdysis of the Armed Forces Quotient Test (AFQn scores. The result casts doubt as to what the

variable tily represen~. It is not certain whether the AFQT smres are a cause or mnsquence of

schoohng. Results are tius presented witi and without the AFQT measure as a control variable. me

results pertaining to the models that exclude tie smres are ‘purer’ ad more reliabIe.

6. The parameter estimates in tie multinomi~ choice modds that include the AFQT m-ure as an

~planatory variable are significmfly different tisrr those obtained when the AFQT mwure is excluded

from tie independent set. In particular, the family background parmeter estimates and t-tiues are

larger when the AFQT variable is excludd from tie sndysis.

7. In the polychotomous choice models, blacka are significsndy more likely tbrm whites to have enrolled

in college programs than any other programs when the AFQT scores are entered into the explanatory set.

However, blacks are most likely to have participated in government end mfiitary programs when the

AFQT variable isexcluded from tie endysis.

8. We statistically reject the tradition~ collegdno college choice framework in favor of a more diversified

choice structure. In fact, we reject any aggregation of the six to eight training states that are employed

5
in tie smdysis. The result suggests tiat there are ststistidly significmt differences in the d@errninsnts

of various Witig choic=.

9. The multinofid probit and the multinomid logit estimatea are qusfitstivefy simifar, and the goodnwsof-fit measurw suggest that the two models perform ~dly well.

10. The multinomid probb results suggest tie presence of some si~-t mrrdations among the

norrnd ked unobservsbles in the training choice equations, and the dwtiion of the eff- genersfly fit

prior expectations. me eatirnated vsrisnceavarisnce mstric= are very atisr whether or not the =QT

vsriable is included as a control variable.

11. If funding for the gov-ent programs had been curtailed, we ~ that the government train=

would have more likely received no formal training thm to hsve inv=ted in ay of the other trsisdng

progrm. The situation wouId cmrse a private anomie loss to these traineea since we estimate small

but positive returns to the govermnent progra. We find that if the mfitary mntinus to be leas

accessible to individuda due to its increasingly stringent entrance requirements, tien the demnd for

vocational programs wodd likely incrae. Tbwe rmults are obtsind by estimating multinondd logit

models for the subssmple of des who d:d not participate in the atutiled &aWmg category, and by using

tbe resulting estimat= to prdlct the ~ieIy choica of the members of tie respective omitted group.

12. There is Iittfe evidence of structural change by age in the training choice quations reflecting the

increasing returns to educstion in the period when our ssmple members were at risk. We do not reject

any aggregation by race. me rmult is probably due to the atil number of blacks and hispanics in tbe

13. It is the Ien@ of time that an individrrd spent in a training program that yields positive returns ss

oPPos~ @ Pro- participation per se. There is dso evidence that vocatioti and mmpany training

6
programs yield positive retu~ ordy if the programs were completed, and that tiere are no sdditiond

premiums attached @ government progrsms that Isst for more thsn nine months. A week spent training

in any of the studiti programs generdIy yields return that are as lwt as Isrge m a week spent in the

labor force.

14. The inclusion of h-e MQT variable aiwificandy chmges the =tirnatw of tie returns to education

Qrades completed), but it does not significantly change the coefficient estimates for the training dummy

or weeks spent in trainiig variables. ~rrs, the AFQT variable seems to be rorrdated witi academic

progrm, but ia uncorrelatd with the programs that have techrsicd and vocational emphases.

15. The training vsriablm are essentially otiogoti to one another. The exclusion of my of &e trsfning

variables does not aigrsificatiy change tie estimatw of tie included onm. The result suggests that

=timates from previous human capiti atudles that exclude any of the mainbrg program vsriabl= are not

seriously biased.

16. There is very Iitie evidence of tie endogeneity of the training variablea. The r=tit holds true for

Al the control and ins~menti variable methods thst sre uati, and the result rdso holds tme whether tie

AFQT variable is included or excluded from the Sssdyais. The main effect of using the ssmpleaelmion

techniqu= ia that tbe training dummy vsriabl= dl become insignificant.

17. Six months of off-th~job, goverrunent, or military trtilng is equitient to betw- one and two

years of college education. hdividuds who invwted in progrm for tiat length of time are pr~lcted

in 1986 to have ~ed about 35 cents more per hour, about 1,5W dollars wre per y~, srtd to have

worked 2.5 more weks per y= *SO dld those who chose to invwt h none of tie training programs.

These ~timstm, however, reprsent short-run return (about seven-yin returns) and say notfdmg

concerning the long-run effects of the training progrm.

7
18. Blacks who participated in SOYof tie mining programs -d comparable hourly wages and sdsri=,

and worked similar number of weeks as did whites who ~ld not enroll in any of the training programs.

Both groups are pr~lcted to have med about 7.25 doIl=s per hour, 12,400 dollara per y=, and to

have worked about 43.3 weeks in 1986. However, the same pattern do= not emerge wheo high school

dropouts are compared with high school graduates while holding race constant. h 1986, dropouts who

investti in any of the programs are predicted to have earned about 10 cents less per hour, about 800

dollars 1=s per y-, and to have worked about 2 fewer weeks per y- Man dld nondropouts who

invested in none of the training progr~.

From a po!icy persptiive, an important finding is that those who participated h ~ of the

training programs generally received higher hourly Wsg= and annual sdsries, and worked a grwter

number of weeks than did hose who participated in none of the training progrm. Howwer, tie

positive rewards from the programs ordy accrual to those who participated in the programs for a

substantial amount of time snd/or to those who completed their programs. We find that ties from

poorer households were more likely to hwe specidked in programs that rqrrired leas resourc= to attend

than were those from more advantaged backgrounds, suggesting that bcirrg wnatrsintx played a major

role in determining the mining program choices of tie individuals. mere is dao no evidence of

comparative advantage based on unobsembles among the trainees. ~rrs, non~llegiate timg

progr~ can be productive alternatives to more expemive college programs for tboae with access to

limited resourc~ (at Imt in the short-run). me particular program chosen is not so important. Wther,

it is the fact that psrticipmts chose to invest at dl in a program for a sigrrificmt amount of time. A

major drawback with Wi study, is that it contains very litie information mrrceming the msrmer in which

individuals financed their invwtrnent choices. fius, our estimates of the effm of my background

variabl~ on the humsrr capiti investment choic~ of tie males in our sample may be biased upwards if

the amount of firrsncid aid received by so ind:vidti is inversdy rdatd to his ftiy income.

8
Consequendy, it is difficult to perform simulations in order to measure the effects of chsngea in

govement policier on individuds’ training program participation decisions and to perform rest-benefit

sndyss. We csmmt determine the change in tie demand for tie various programs due to cbang~ in

government pohcies that alter tie supply of funds available to the individuals.

me finding that tie training program vsriablw are close to orthogoti in the earnings regression

has practid aignificace from a policy perspective. me result suggests that it ia possible to accurately

ascertain tie impact of a given training program *ile ignoring the effm of other mainirrg progr~.

me procedure yields estinrstea tfrat do not suffer from omittd variable bias due to the exclusion of other

human capital investment variabler. Grrsequendy, the use of nnnexperimenti methods in determining

progrm premiums can focus on one training program at a time.

9
(2) me Nonequitience of High School Equivdenrs

Stephen V. Cameron and Jams J. Heckm~

University of Chicago

December, 199& Revised, Wch, 1991 and June, 1991

Revisal May 1992

Tbii paper_ = the causea and consequence= of a neglaed social phenomenon - the recent

rapid groti in the fraction of persons who atileve h]gb school certification by mm of a quivdency

exam rather than through the tradition route of Vlgh school graduation. b 1968, ody five percent of

dl new Klgh school certificate were awarded through Wivdmcy exsms. By 1987, the corr=pondimg

figure was in excess of fourteen percent. In 1968, ody two percent of dl persons who complti tieir

education with high schooI degr= were exam+ertified. h 1987, the mrr=pontimg figure was Amost

deven percent. It is widdy behevd that exsm+ertified high school ~ivderrts are the -S of

trtiltiond high schooI graduates in dl relevant behavioral dmemions.

~ls paper challenges tie conventional wisdom. Exsm+erdfied high S*OO1quivdents are not

identicd to tradltioti high school graduatw in terms of their ab~lty as measured by a standard

psychometric test (the -d Forces wi~mg T=t), in terms of their wages ad hours of work or in

terms of their post+ertification education and training dec~lom. Exsm+eflified high school ~ivdents

are psychometrically inferior to tradltioti high school graduates. Elsewhere we =tah~i that the

determinants of high school certification by exam ae very different from the deterrninmts of traditioti

high school graduation. We demonstrate here that the anomie consquenc= of the two avenues of high .

school certification are quite different. Exam<ertifid persons are tid~tinguishable in many rdevsnt

Iabor market dimensions from high school dropouts who are uncertified. Different= ti wags among

high school graduates, exam+ertified quivdents and dropouts are acwuntd for by y- of schoo~mg

attained. mere is Utie evidence of value added horn eaarrr certification beyond the effect of y- of

10
schwfing completed on wagea. However, exsm-cetifiti graduates are more ~idy to tie vomtiod

and technicfl Eaining whlIe &aditiond high school grsduat= are more likely to attend a~errric forar-y~

collegw and mmplete academic programs when they begin them. Exam<ertified high-school graduates

are more likely to participate in some form of post-sandsry tiairrirrg ti~ are non-srn+rtified bighschool dropouts. Em<ertified persons who take peat-secrmdsry schooling and training- lower wagea

tim high schooI graduatw undetilrrg the asme activity. me return to high school eq”ivdenq

certification, such as it is, comes from the return to peat-aandsry training. Acwrdingly, it is not

apprOpri~e ~ ~mider tie GED ss ~ ~u=tiond end ti i~df - tie emph=is in mmy contemporary amte

and federd programs.

In fight of our evidence, the growing use of GED certification suggata the possibfity of

widmpresd misperception on the part of t=t takers. We estabfish in tfds paper that the groti in the Ievd

and proportion of exsm+ertifid high schml credentials is a dwect mnsequmce of feded and atste

human rwource pohcim that make GED trot-taking privately rational wen if it is socially unproductive.

Since the mid-19~, both ftierd and sate gov-ents have inambrgly subsidti sduft basic

edu=timr programs which have placed a growing emphasis on sdtit equivalency as a cl=ly identified

and desirable objective. h addition, a high school degree or an exam+ertified~uivdent is reqrrird for

participation in a host of post-secondary vocatiod and academic fisncid support programs hcraingly

subsidued by f~erd and state governments over tils period. me demand for participation in these

subsidwed programs induced a derived demand for high school certification on tie part of high shool

.

dropouts.

Gne major mnclusion of this paper is that the GED ia a vtilcle for participation in post+~n~

tiucation due to its value in satisfying buraucraticdlydeterrrrind qutilfications for adrnisaion and

fi~cid support. Subsidtiation of thae programs by governrnen~ reamcfl~ the apparent wfiict

between low economic returns to obtaining the GED and the large and growing demand for GEDs.

11
A semnd major concision mncem tie fimited value of psychom~ic mauremerrts for

prdlding labor mark~ outmm=. Gur evidence about tie labor market insdwacy of =sm*fi@

graduatw calls tito quwtion the value of psytiom%c evidence on the effl=cy of private schuols. (See

Colemm, Hoffer and mgore 1982 and Chubb and Moe, 1990 who rely on such evidenm). T=ts like

tie GED m=ure SMIS that are ody WAY related ~ the SMIS valued by employers.

12
@) Education and Training Transitions:

Determinants of Youth Schoolhg and Training Transitions

Stephen V. Cameron and James J. Hecti

University of ~lcago

Dwember, 1990, Revised March, 1990

For a sample of young men, ages 13-20 in 1978, taken from the National hngitudlti Survey

of Youti ~Sv, we demonstrate that the determinants, economic mnaequenc=, and subs~ent

education corssequenc= of exsm<ertified high achml certification are findamentily different from

those of ordinary high school graduates. Spwifidly, we demonsmte thr= points.

(1) The determinants of Klgh school certification by exam are fondsrnerrtily different from tie

determinants of ordinary high acfrool graduation. Q) The anomie cmrseqrrenceaof the two avenu= of

high school certification are very different. b terms of wag= at ages 25 and 28, e-+ertified persons

are indlstingrrishable from high school @rouou@who are not certified. (3) In tem of transitions to

furdrer education, exa<ertified high school graduatea are fundsrnentily different from ord~ high

school graduatea. The former are more fikely to take vocational and twbnicd training; the latter are

more likely to attend academic four-year mlleges md complete academic programs when tiey begin

them. Exssn+ertified graduates are much more ~kely to take some form of tr=lng than are rron<ertified

dropouts.

@r paper chdleng= a steady stream of repo~ issued by the tierican Council of Mutation -

.

the producer of the leading high schooI certification exam - the GED (for ~enerd ~ucationd

Development). That orgsnkation claims that GED grsdust= and graduating high school seniors are

equivalent in terms of their marker skills and in terms of their abiity to mmplete post+-ndary

education and tratilrrg progr~. ~dtio and Wlmey, 1982). Uairrg tied Forces QtiI~ig Tat

data administered to dl ~Y participants, we document that even on psychometric criteria, GEDcertified high school graduat~ are greafly inferior to traditional high school graduatw - even for those
graduat= who take no futier education. More irnportsntiy, we document that G~+ertified sbiii~ is

not tie ability desired by the market nor is it the ab~lty that pr~lcts completion of post-secondary

schooling and trsining programs.

Enroute to eatsblishmg tieae points, we present new evidence on tie determinants ad

consequences of the -ly schooling decisions of America wfrbe, hIspsrric, and black dea mrnirrg of

age in the late 197& and mid-198&. We sndpe school dropping~ut ad mntimsation decisions. We

demonstrate how the growth in msm+ertified high school graduat= explains the apparent pwle of a

post-1970 _ in high school graduat% as a proportion of 17-yesr*lds and a near mnstsrr~y in the

proportion of perso-m ages 2G24 with at least a high school certifica@ over the same period.

~Is paper &so ex~~ the role of family background, Iod labor market opportufiti~, and

school quality on decisions to continue schooling ad on wagea and hours of work. Urdiie more

traditioti studies that focus on “college” choice, we tisaggregste post~lgh-school edu=tioti and

training choices to account for the full array of academic and non-academic schoo~ig and maining choices

available to potential students. ~Is disaggregation turns out to be helpful in producing sensible modek

of post-secondary schooling choices for minority youti.

We find strong effects of Wily background on school continuation dec~lorrs. We sfso find that

local labor market opportrmiti= play so important role in eWIaining secondary schoo~mg decMlons and

high school dropping+ut behaviour. me better are opportunities for unskiiled Isbor, tie lower are high

school continuation rates. We fid fitie evidence tfrst persons @p out of Iowqudity high schools at

a higher rate, once puenti background and Iocd labor-m~ket oppotititiea are acmunted for.

14
(4) me Dynsmica of ~ucationd Attainment For Blacks,

Wltes and Hupmica

Stephen V. ~eron and Jsmea J. Heckrrrmr

University of Ctilcago

September, 1991, Revised, Aprfi, 1992

~is paper exarnin= the role of famtiy background, faily income, labor market opportunities

and college tuition in accounting for differences in educational attainment by age among black, white and

hispanic ~~. ~i study extends from tie previous literature in two important ways.

(1) Previous inffuenti~ work by Hauser (1991), me (1990) and others is baaed on Current

Population Survey (CPS) data. ~eae dam suffer from major firnitationa of special irnpo-ce to @ysm

of the role of tiny background on edumtiond choices. me CPS data report parenti fsmiiy

characteristics of persona ordy if hey are living in tie parerrti home, for tfroae attending mllege, or, for

those living in group quarters. Parenti background and inmme information is not avtiable for nonstudenw not living with parents or for students not living in group quarters.

VlrtudIy dl of the evidence on the inr~rtance of ftiy background and filly income on

schooltig choic= is derived from sarnplea of “dependents”, i.e., persona living in the parenti home or

studen~ in college living in group quarters. Using the ~Y ~atiorrd bngitodti Survey of Youth)

data we demonstrate that, as a consequence of WIS data generation process, previous studl~ tend to

underestimate the wntribution of ftiy income and financird reaourc~ to adooling decisions.

(2) me ~SY data contain richer background information than do the CPS data. We demonstrate

the value of access to such information in acmunting for achoofing deciaiorra. Exploitig the longitudinal

structure of the ~SY data, we model educatiorrd choices as decisions made squentiafly at wcb age.

Urdike previous cross-sectionrd amdim that focus attention on explaining years of schooltig completed,

we consider the daerminanta of educatiorrd choic~ at ~ch age.

Urdike other strrdiea that andpe one schooling transition in iaolationfiom dl others, we mnsider

15
dl schoolingchoicesfrom ages 14 to 28. Such acmunting tum out to be emptilcrdly important irr

explaining minority/majority differences in w!Iege attendnce. K]gh school dropout rat= me so lmge for

mioority youth that those who graduate high school and are efigible to attend wllege ae smcely

repr~entative of dl minorities. By mndltioning on hi@ school ~aduatiorr ststus, previous analysts mute

tie role of economic ticeotives in explaining college attendmce becauae tie same incentivw operate h

much the same way on high school graduation.

Schooling attainment is the outmme of a sesi= of choicw made at mch age. By =timating age

specific schooltig choice functions, we detemioe at which ages and for what choic= aMmic md

socioeconomic factors play an impo-t role. Find levels of schooliog attained are tie outcomes of our

dkaggregated ag~specific achoo!ing choice quatiom.

Using MS framework, we reach the following thr= major conclusion.

(1) Black, white and hispanic schooling chaic~ are sensitiw to tuition costs._the generos~ of

labor market oppo~nities which constitute afternotiws to schooling, and to f&y background &

incom.

p) %re is evidence offorward-looting behavior. High school dropout rates tie when college

tuitwn costs n.se. ~is &ence suggests that mare qlicit structural dy~.c models are ltify to be

empincally~i@.

~) De~ite ti impo~ance of economic and socioeconomic variables in accom-ngforschaoling

choices, they qlain Iittle of the cross-section or dme-senes differences in schooling attainment rmes

among white, hispanic and black mafes.

16
(~ Trends in College Entry Among W,tes, BIacks

and H]spani~ k Economic and Economemic Perspective

Stephen V. Cameron and James J. Heckman

University of Chicago

December 26, 1991, Revisal Aprti 11, 1992, Second Revision, June 7, 1992

In this paper, we qrr=tion the smen~ of the evidence supporting the main conclusions set fofi

by those who use Current Population Survey (CPS) samples. There are marry limitations of the October

CPS. We examine aever~ of these shoficomings by looking at mllege enrollment data basal on the

National hngituditi Survey of Youti WW. Although these data contain substantially fewer persona

than the CPS and cannot be used to estimate aggregate armud enrollment rates rehably, they are

longitudinal in namre, mntairr much more information on family background &aracteristics, and enable

analysts to construct measures of fdy rwources for rdl persons - not just those who are “dependents”

as classified by tie CPS. Using these richer data, it is possible to estimate more interpretable models of

schoofing attendance that do not support many conclusions derived from CPS data.

We dso raise S. impo~t interpretive problem that plagues WISpaper and many others in this

hteramre. Following a long trdltion, Hauser and others estimate the parameter of one transition equation

in a multistate tiucationd process: the transition from high school to mllege. Klgh school graduation is

a selmive process. Many more whites graduate from high stiool than do black or hlapanics. h the

presence of unmeasured ability and motivatiomd variables, CFS ~timates of behaviod +ations for tie

transition from high school to college mrrfound the effects of miables in placing a person in the catego~

of being a high school graduate and being efigible for college with the effects of those variables in

“causing” persons to go to mllege. We present evidenm irsdlcating tie importance of measuring or

controlling for such motivatiomd modda in mplsining the determinants of ducation transitions and d

into question the validity of bebaviord models of educatioti transitions estimated on repwted~oaasection data sets like the CPS.

17
~s evidene, and other evidence, render suspm CPS tiysea of rscid+tiIc differences in

college entry. It is not appropriate to mnsmsin farrdly backgrmmd effe to *WIW in aaunting for

racM/etinic trends. Such a procedure amounts to irrrplicidy picking one value of back=orrnd

charaderistim to mmpsre outmme difference between nonparallel wIlege atrendmce ~uatiorrs. me

bentimark value chosen is ordy implicitly defind, has no compelling justification, and in fact has a

peculiar and unintuitive property. A better method of comparison wordd be to eme the difference in

estimatti non-ptilel equations at a _ of expficidy ststd and plausible vdu=. me widely-heId

intuition that slope - wrrstrained ~ations pass through the OV-1 sample mean is Mse.

“Is
.

01 Michael R. Pergmit

02 Noman M, Bmdbum

Wtin R. Frankel

RegtiAd P. B&er

Michael R. Pergmit

“03

04

05.

06

07

08

09

10

11

,12

13

.

14

15

8aU1 Schwm

Roti Hutchem

George Jakubson

A. Colh ~meron

R. Mk Grim

Tbomm MaCmdy

Hen~ S. Faber

Frmk L. Mott

Pauk B&er

Au&y Light

Wnuefim Ureta

Lim M. Lynch

Evmgelos M. Faltis

H. EItibeti Petws

hne HII1

June E. ONeill

Aleen Uibowin

Jacob Afex Klemm

Ltida Waite

Lee A. L1lIwd

Joseph G, Altonji

Thomas A. Dunn

George J. Bo~~

Stephen G. Bronas

Stephen J. Trejo

James J. Hcchan

Stephen V. Cameron

Peter Z. Schochet

m

How the FdeM Government Uses Dam fmm

the National Longitudinti Suweys

A Comptision of Computer-Assisted Pe~ond

Intiews (CAP~ with Paper-and Pencil Interviews @w~ in the Natioti Longitudinal Sumey

of Youth

Dynmic Models of tie Joint Dekmination of

btir Supply md Fmily S~ctuw

me effmta of Unemployment Compensation

on the Unemplo~ent of Youth

Evduting Competing Tbeoris of Worker

Mobifiv

Evdwtion of the 1989 Child-cae S upplement

in the National Longitudinal Suwey of Youti

Gender Differenms in the Quit Behavior of

Young Workem

~e Impact of Private Secmr Trtining OriRace

and Gender Wage D]ffemntiaIs and the Caeer

Patterns of Young Workers

R~nses of Femafe hbor Supply md Fertility

to the Demo~aphic Cycle

A Study of Intercohort Change in Women’s

Work Patterns and filngs

Women’s Employment Dwing Pregnancy

md Following Birth

Work Experience, Job Tenure, Job Sepmtion,

md Wage Growti

Family Background and Labor Market Outcomes

Self-Selwtion and Internal Mi~ation in the

United Sates

The De@minats and Consequences of Pubfic

Swtor md Private Swtor Training’