NBER WORKING PAPER SERIES
HUMAN CAPITAL POLICY
Pedro Carneiro
James Heckman
Working Paper 9495
http://www.nber.org/papers/w9495
NATIONAL BUREAU OF ECONOMIC RESEARCH
1050 Massachusetts Avenue
Cambridge, MA 02138
February 2003
James Heckman is Henry Schultz Distinguished Service Professor at the University of Chicago and Senior
Fellow of the American Bar Foundation. Pedro Carneiro is a graduate student at the University of Chicago.
The research reported here was supported by the National Science Foundation grants SES-93-21-048, 97-30-
657, and 00-99-195; NICHD grant R01-34598-03; NIH grant R01-HD32058-03, and the American Bar
Foundation. Carneiro was funded by Fundacao Ciencia e Tecnologia and Fundacao Calouste Gulbenkian. We
have benefited from comments received from David Bravo, Mark Duggan, Lars Hansen, Robert LaLonde,
Steve Levitt, Dayanand Manoli, Dimitriy Masterov, Casey Mulligan, Derek Neal, Flavio Rezende-Cunha and
Je. Smith on various aspects of this paper. We have benefited from comments on the first draft received from
George Borjas, Eric Hanushek, Larry Katz, Lance Lochner, Lisa Lynch and Larry Summers. Dayanand
Manoli and Dimitriy Masterov provided valuable research assistance for which we are grateful. This work
draws on and substantially extends Heckman (2000) and Heckman and Lochner (2000). Correspondence to:
James J. Heckman, Department of Economics, University of Chicago, 1126 E. 59th Street, Chicago IL 60637
USA. The views expressed herein are those of the authors and not necessarily those of the National Bureau
of Economic Research.
©2003 by James Heckman and Pedro Carneiro. All rights reserved. Short sections of text not to exceed two
paragraphs, may be quoted without explicit permission provided that full credit including notice, is given to
the source.
Human Capital Policy
James Heckman and Pedro Carneiro
NBER Working Paper No. 9495
February 2003
JEL No. I2, I28
ABSTRACT
This paper considers alternative policies for promoting skill formation that are targetted to different
stages of the life cycle. We demonstrate the importance of both cognitive and noncognitive skills
that are formed early in the life cycle in accounting for racial, ethnic and family background gaps
in schooling and other dimensions of socioeconomic success. Most of the gaps in college attendance
and delay are determined by early family factors. Children from better families and with high ability
earn higher returns to schooling. We find only a limited role for tuition policy or family income
supplements in eliminating schooling and college attendance gaps. At most 8% of American youth
are credit constrained in the traditional usage of that term. The evidence points to a high return to
early interventions and a low return to remedial or compensatory interventions later in the life cycle.
Skill and ability beget future skill and ability. At current levels of funding, traditional policies like
tuition subsidies, improvements in school quality, job training and tax rebates are unlikely to be
effective in closing gaps.
Pedro Carneiro James J. Heckman
Department of Economics Department of Economics
The University of Chicago The University of Chicago
1126 E. 59th Street 1126 East 59th Street
Chicago, IL 60637 Chicago, IL 60637
[email protected] and The American Bar Foundation
and NBER
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kd}dug sureohpv1 Iru wkdw uhdvrq/ lw lv lqdssursuldwh wr xvh d orzhu glvfrxqw udwh wkdq wkh pdunhw
udwh iru glvfrxqwlqj ehqhwv dowkrxjk lw pd| eh dssursuldwh wr xvh d orzhu glvfrxqwudwhirufrvwv
udlvhg iurp jryhuqphqw uhyhqxh vrxufhv1
:4
Uhihuhqfhv
Dfhprjox/ G1 dqg M1 Dqjulvw +5334,1 Krz Odujh duh wkh Vrfldo Uhwxuqv wr HgxfdwlrqB Hylghqfh
iurp Frpsxovru| Vfkrrolqj Odzv/ lq E1 Ehuqdqnh dqg N1 Urjr/ hgv1/ QEHU Pdfurhfrqrplfv
Dqqxdo 5333/ Fdpeulgjh/ PD= PLW Suhvv/ <08<1
Dowrqml/ M1 dqg W1 Gxqq +4<<9,1 Wkh Hhfwv ri Idplo| Fkdudfwhulvwlfv rq wkhUhwxuqwr
Hgxfdwlrq/ Uhylhz ri Hfrqrplfv dqg Vwdwlvwlfv/ :;+7,=9<50:371
Duurz/ N1 dqg U1 Olqg +4<:3,1 Xqfhuwdlqw| dqg wkh Hydoxdwlrq ri Sxeolf Lqyhvwphqw Ghfl0
vlrqv/ Dphulfdq Hfrqrplf Uhylhz/ 93+6,=6970:;1
Dvkhqihowhu/ R1 +4<:;,1 Hvwlpdwlqj wkh Hhfw ri Wudlqlqj Surjudpv rq Hduqlqjv/ Uhylhz ri
Hfrqrplfv dqg Vwdwlvwlfv/ 9+4,=7:08:1
Dxwru/ G1 dqg O1 Ndw} +4<<<,1 Fkdqjhv lq Zdjh Vwuxfwxuh dqg Hduqlqjv Lqhtxdolw|/ lq R1
Dvkhqihowhu dqg G1 Fdug/ hgv1/ Kdqgerrn ri Oderu Hfrqrplfv/ Yro1 6D/ Dpvwhugdp= Hovhylhu0Qruwk
Kroodqg/ 4796048881
Eduqhww/ Z1 V1 +4<<6,1 Ehqhw0Frvw Dqdo|vlv ri Suhvfkrro Hgxfdwlrq= Ilqglqjv iurp d 580\hdu
Iroorz0Xs/ Dphulfdq Mrxuqdo ri Ruwkrsv|fkldwu|/ 96+7,=83303;1
bbbbb +5335,1 Sulydwh Frppxqlfdwlrq1
Eduwho/ D1 +4<<5,1 Surgxfwlylw| Jdlqv iurp wkh Lpsohphqwdwlrq ri Hpsor|hh Wudlqlqj Sur0
judpv/ QEHU zrunlqj sdshu Qr1 6;<61
Ehfnhu/ J1 +4<97,1 Kxpdq Fdslwdo= D Wkhruhwlfdo dqg Hpslulfdo Dqdo|vlv zlwk Vshfldo Uhihuhqfh
wr Hgxfdwlrq1 Qhz \run= Froxpeld Xqlyhuvlw| Suhvv1
Ehq0Srudwk/ \1 +4<9:,1 Wkh Surgxfwlrq ri Kxpdq Fdslwdo dqg wkh Olih F|foh Hduqlqjv/
Mrxuqdo ri Srolwlfdo Hfrqrp|/ :8+7/ Sduw 4,=6850981
Elvkrs/ M1 +4<<7,1 Irupdo Wudlqlqj dqg Lwv Lpsdfw rq Surgxfwlylw|/ Zdjhv dqg Lqqrydwlrq/
lq O1 O|qfk/ hg1/ Wudlqlqj dqg wkh Sulydwh Vhfwru= Lqwhuqdwlrqdo Frpsdulvrqv1 Fklfdjr= Xqlyhuvlw|
ri Fklfdjr Suhvv1
Eodx/ I1 dqg O1 Ndkq +5334,1 Gr Frjqlwlyh Whvw Vfruhv H{sodlq Kljkhu XV Zdjh Lqhtxdolw|B
:5
QEHU zrunlqj sdshu Qr1 ;5431
Eorrp/K1/O1Ruu/J1Fdyh/V1Ehoo/dqgI1Grrolwwoh+4<<6,1 Wkh Qdwlrqdo MWSD Vwxg|= Wlwoh
LL0D Lpsdfwv rq Hduqlqjv dqg Hpsor|phqw dw 4; Prqwkv1 Ehwkhvgd/ PG= Dew Dvvrfldwhv1
Eorvvihog/ K1S1 dqg \1 Vkdylw +4<<6,1 Shuvlvwhqw Lqhtxdolw|= Fkdqjlqj Hgxfdwlrqdo Dwwdlqphqw
lq Wkluwhhq Frxqwulhv1 Erxoghu/ FR= Zhvwylhz Suhvv1
Erhvho/ G1/ Q1 Dovdodp dqg W1 Vplwk +4<<;,1 Hgxfdwlrqdo dqg Oderu Pdunhw Shuirupdqfh ri
JHG Uhflslhqwv1 Zdvklqjwrq/ G1F1= X1V1 Ghsduwphqw ri Hgxfdwlrq1
Erumdv/ J1 +4<<<,1 Khdyhq
vGrru1 Sulqfhwrq= Sulqfhwrq Xqlyhuvlw| Suhvv1
Erumdv/ J1/ U1 Iuhhpdq dqg O1 Ndw} +4<<:,1 Krz Pxfk Gr Lppljudwlrq dqg WudghDhfw
Oderu Pdunhw RxwfrphvB Eurrnlqjv Sdshuv rq Hfrqrplf Dfwlylw|/409:1
Erzohv/ V1 dqg K1 Jlqwlv +4<:9,1 Vfkrrolqj lq Fdslwdolvw Dphulfd1 Qhz \run= Edvlf Errnv1
Erzohv/ V1/ K1 Jlqwlv dqg P1 Rveruqh +5334,1 Wkh Ghwhuplqdqwv ri Hduqlqjv= D Ehkdylrudo
Dssurdfk/ Mrxuqdo ri Hfrqrplf Olwhudwxuh/ 6<=446:044:91
Eurzqlqj/ H1 +4<;:,1 Rq wkh Pdujlqdo Zhoiduh Frvw ri Wd{dwlrq/ Dphulfdq Hfrqrplf Uhylhz/
::+4,=440561
Eurzqlqj/ P1/ O1 Kdqvhq dqg M1 Khfnpdq +4<<<,1 Plfur Gdwd dqg Jhqhudo Htxloleulxp
Prghov/ lq M1 Wd|oru dqg P1 Zrrgirug/ hgv1/ Kdqgerrn ri Pdfurhfrqrplfv1 Dpvwhugdp= Hovhylhu/
87609661
Exuhdx ri Oderu Vwdwlvwlfv +5334,1 QOV Kdqgerrn 53341 Zdvklqjwrq/ G1F1= X1V1 Ghsduwphqw
ri Oderu1
Exujkdugw/ M1 dqg S1 Vfkrfkhw +5334,1 Qdwlrqdo Mre Frusv Vwxg|= Lpsdfwv e| Fhqwhu Fkdudf0
whulvwlfv H{hfxwlyh Vxppdu|1 Sulqfhwrq= Pdwkhpdwlfd Srolf| Uhvhdufk/ Lqf1
Fdphurq/ V1 dqg M1 Khfnpdq +4<<6,1 Wkh Qrqhtxlydohqfh ri Kljk Vfkrro Htxlydohqwv/ Mrxuqdo
ri Oderu Hfrqrplfv/ 44=407:1
bbbbb +4<<;,1 Olih F|foh Vfkrrolqj dqg G|qdplf Vhohfwlrq Eldv= Prghov dqg Hylghqfh iru
Ilyh Frkruwv ri Dphulfdq Pdohv/ Mrxuqdo ri Srolwlfdo Hfrqrp|/ 439+5,=59506661
:6
bbbbb +4<<<,1 Fdq Wxlwlrq Srolf| Frpedw Ulvlqj Zdjh Lqhtxdolw|B lq P1 Nrvwhuv/ hg1/
Ilqdqflqj Froohjh Wxlwlrq= Jryhuqphqw Srolflhv dqg Hgxfdwlrqdo Sulrulwlhv1 Zdvklqjwrq/ G1F1=
Dphulfdq Hqwhusulvh Lqvwlwxwh Suhvv1
bbbbb +5334,1 Wkh G|qdplfv ri Hgxfdwlrqdo Dwwdlqphqw iru Eodfn/ Klvsdqlf/ dqg Zklwh
Pdohv/ Mrxuqdo ri Srolwlfdo Hfrqrp|/ 43<=78807<<1
Fdphurq/ V1 dqg F1 Wdehu +5333,1 Eruurzlqj Frqvwudlqwv dqg wkh Uhwxuqv wr Vfkrrolqj/
QEHU zrunlqj sdshu Qr1 ::941
Fdug/ G1 +4<<<,1 Wkh Fdxvdo Hhfw ri Hgxfwlrq rq Hduqlqjv lq R1 Dvkhqihowhu/ dqg G1 Fdug/
hgv1/ Kdqgerrn ri Oderu Hfrqrplfv/ Yro 6D1 Dpvwhugdp= Hovhylhu Vflhqfh/ Qruwk0Kroodqg/ 4;340961
bbbb +5334,1 Hvwlpdwlqj wkh Uhwxuq wr Vfkrrolqj= Surjuhvv rq Vrph Shuvlvwhqw Hfrqrphwulf
Sureohpv/ Hfrqrphwulfd/ 9<+8,=445:0931
Fdug/ G1 dqg D1 Nuxhjhu +4<<5,1 Grhv Vfkrro Txdolw| PdwwhuB Uhwxuqv wr Hgxfdwlrq dqg wkh
Fkdudfwhulvwlfv ri Sxeolf Vfkrrov lq wkh Xqlwhg Vwdwhv/ Mrxuqdo ri Srolwlfdo Hfrqrp|/ 433+4,=4731
bbbbb +4<<:,1 Frpphqw rq Fodvv Vl}h dqg Hduqlqjv/ Mrxuqdo ri Hfrqrplf Shuvshfwlyhv/
44+7,=559055:1
Fdug/ G1 dqg W1 Ohplhx{ +5333,1 Gursrxw dqg Hquroophqw Wuhqgv lq wkh Srvw0Zdu Shulrg=
Zkdw Zhqw Zurqj lq wkh 4<:3vB lq M1 Juxehu/ hg1/ Dq Hfrqrplf Dqdo|vlv ri Ulvn| Ehkdylru
Dprqj \rxwk1 Fklfdjr= Xqlyhuvlw| ri Fklfdjr Suhvv1
bbbbb +5334,1 Fdq Idoolqj Vxsso| H{sodlq wkh Ulvlqj Uhwxuq wr Froohjh iru \rxqjhu PhqB
DFrkruw0EdvhgDqdo|vlv/Txduwhuo|MrxuqdoriHfrqrplfv/449+5,=:380:791
Fduqhlur/ S1 dqg N1 Kdqvhq/ dqg M1 Khfnpdq +5334,1 Uhprylqj wkh Yhlo ri Ljqrudqfh lq
DvvhvvlqjWkhGlvwulexwlrqdoLpsdfwvriVrfldoSrolflhv/QEHUzrunlqjsdshuQr1;;73/dqg
VzhglvkHfrqrplfSrolf|Uhylhz, volume 81
bbbbb+5333,1HvwlpdwlqjGlvwulexwlrqvriWuhdwphqwHhfwvzlwkdqDssolfdwlrqwrwkh
Uhwxuqv wr Vfkrrolqj/ iruwkfrplqj lq Lqwhuqdwlrqdo Hfrqrplf Uhylhz1
Fduqhlur/S1dqgM1Khfnpdq+5335,1WkhHylghqfhrqFuhglwFrqvwudlqwvlqSrvw0Vhfrqgdu|
:7
Vfkrrolqj/HfrqrplfMrxuqdo, 112(482):705- 7341
Fduqhlur/ S1/ M1 Khfnpdq dqg H1 Y|wodflo +5334,1 Hvwlpdwlqj wkh Udwh ri Uhwxuq wr Hgxfdwlrq
Zkhq Lw Ydulhv Dprqj Lqglylgxdov/ zrunlqj sdshu/ Xqlyhuvlw| ri Fklfdjr1
Fduqhydoh/ D1 dqg U1 Iu| +5333,1 Furvvlqj wkh Juhdw Glylgh= Fdq Zh Dfklhyh Htxlw| Zkhq
Jhqhudwlrq \ Jrhv wr FroohjhB Suhsduhg iru wkh Hgxfdwlrqdo Whvwlqj Vhuylfh Ohdghuvkls 5333
Vhulhv/ Sulqfhwrq/ QM1
Fdzoh|/ M1/ M1 Khfnpdq/ O1 Orfkqhu dqg H1 Y|wodflo +5333,1 Xqghuvwdqglqj wkh Uroh ri Frjql0
wlyh Delolw| lq Dffrxqwlqj iru wkh Uhfhqw Ulvh lq wkh Uhwxuq wr Hgxfdwlrq/ lq N1 Duurz/ V1 Erzohv
dqg V1 Gxuodxi/ hgv1/ Phulwrfudf| dqg Hfrqrplf Lqhtxdolw|/ Sulqfhwrq= Sulqfhwrq Xqlyhuvlw| Suhvv1
Fdzoh|/ M1/ M1 Khfnpdq/ dqg H1 Y|wodflo +4<<<,1 Rq Srolflhv wr Uhzdug wkh Ydoxh Dgghg e|
Hgxfdwruv/ Uhylhz ri Hfrqrplfv dqg Vwdwlvwlfv/ ;4+7,=:530:5:1
Frohpdq/ M1 dqg W1 Krhu +4<;6,1 Sxeolf dqg Sulydwh Kljk Vfkrrov1 Qhz \run= Edvlf Errnv1
Frvvd/ U1 +5333,1 Ghwhuplqdqwv ri Vfkrro Dwwdlqphqw lq Dujhqwlqd= Dq Hpslulfdo Dqdo|vlv
zlwk H{whqvlrqv wr Srolf| Hydoxdwlrq/ xqsxeolvkhg Sk1G1 glvvhuwdwlrq/ Wkh Xqlyhuvlw| ri Fklfdjr1
Frxfk/ N1 +4<<5,1 Qhz Hylghqfh rq wkh Orqj0Whup Hhfwv ri Hpsor|phqw Wudlqlqj Sur0
judpv/ Mrxuqdo ri Oderu Hfrqrplfv/ 43+7,=6;30;;1
Fxoohq/ M1/ E1 Mdfre dqg V1 Ohylww +5333,1 Wkh Lpsdfw ri Vfkrro Fkrlfh rq Vwxghqw Rxwfrphv=
Dq Dqdo|vlv ri wkh Fklfdjr Sxeolf Vfkrrov/ QEHU zrunlqj sdshu Qr1 :;;;1
Fxuulh/ M1 dqg G1 Wkrpdv +4<<8,1 Grhv Khdg Vwduw Pdnh d GlhuhqfhB Dphulfdq Hfrqrplf
Uhylhz/ ;8+6,=6740971
GhOrqj/ M1 E1/ F1 Jroglq dqg O1 Ndw} +5335,1 Vxvwdlqlqj X1V1 Hfrqrplf Jurzwk/ zrunlqj
sdshu/ Xqlyhuvlw| ri Fdoliruqld/ Ehunhoh|1
Grqrkxh/ M1 dqg S1 Vlhjhopdq +4<<;,1 Doorfdwlqj Uhvrxufhv Dprqj Sulvrqv dqg Vrfldo Sur0
judpv lq wkh Edwwoh Djdlqvw Fulph/ Mrxuqdo ri Ohjdo Vwxglhv> 5:+4,=40761
Gxqfdq/ J1 dqg M1 Eurrnv0Jxqq +4<<:,1 Lqfrph Hhfwv Dfurvv wkh Olih Vsdq= Lqwhjudwlrq
dqg Lqwhusuhwdwlrq/ lq J1 Gxqfdq dqg M1 Eurrnv0Jxqq/ hgv1/ Frqvhtxhqfhv ri Jurzlqj Xs Srru1
:8
Qhz \run= Uxvvhoo Vdjh Irxqgdwlrq1
G|qduvnl/ V1 +5333,1 Krsh iru ZkrpB Ilqdqfldo Dlg iru wkh Plggoh Fodvv dqg Lwv Lpsdfw rq
Froohjh Dwwhqgdqfh/ Qdwlrqdo Wd{ Mrxuqdo/ 86=95<0951
bbbbb +5334,1 Grhv Dlg PdwwhuB Phdvxulqj wkh Hhfwv ri Vwxghqw Dlg rq Froohjh Dwwhq0
gdqfh dqg Frpsohwlrq/ zrunlqj sdshu/ Kduydug Xqlyhuvlw|1
Hgzdugv/ U1 +4<:9,1 Lqglylgxdo Wudlwv dqg Rujdql}dwlrqdo Lqfhqwlyhv= Zkdw Pdnhv D Jrrg
ZrunhuB Mrxuqdo ri Kxpdq Uhvrxufhv/ 44+4,=8409;1
Hoozrrg/ G1 +5334,1 Wkh Vsxwwhulqj Oderu Irufh ri wkh 54vw fhqwxu|= Fdq Vrfldo Srolf| KhosB
zrunlqj sdshu/ Kduydug Xqlyhuvlw|1
Hoozrrg/ G1 dqg W1 Ndqh +5333,1 Zkr lv Jhwwlqj d Froohjh HgxfdwlrqB= Idplo| Edfnjurxqg
dqg wkh Jurzlqj Jdsv lq Hquroophqw/ lq V1 Gdq}ljhu dqg M1 Zdogirjho/ hgv1/ Vhfxulqj wkh Ixwxuh=
Lqyhvwlqj lq Fkloguhq iurp Eluwk wr Froohjh1 Qhz \run= Uxvvhoo Vdjh Irxqgdwlrq1
Iu|hu/ U1 dqg V1 Ohylww +5335,1 Xqghuvwdqglqj wkh Eodfn0Zklwh Whvw Vfruh JdslqwkhIluvw
Wzr \hduv ri Vfkrro/ QEHU zrunlqj sdshu Qr1 ;<:81
Jduehu/ K1 +4<;;,1 Wkh Plozdxnhh Surmhfw= Suhyhqwlqj Phqwdo Uhwdugdwlrq lq Fkloguhq dw Ulvn1
Zdvklqjwrq/ G1F1= Dphulfdq Dvvrfldwlrq ri Phqwdo Uhwdugdwlrq1
Jod}hupdq/ V1/ S1 ]1 Vfkrfkhw dqg M1 Exujkdugw +5334,1 Qdwlrqdo Mre Frusv Vwxg|= Wkh
Lpsdfwv ri Mre Frusv rq Sduwlflsdqwv* Olwhudf| Vnloov/ Zdvklqjwrq/ G1F1= X1V1 Ghsduwphqw ri
Oderu1
Judqjhu/ U1 dqg U1 F|wurq +4<<;,1 Whhqdjh Sduhqw Surjudpv= D V|qwkhvlv ri wkh Orqj0Whup
Hhfwv ri wkh Qhz Fkdqfh Ghprqvwudwlrq/ Rklr*v Ohduqlqj/ Hduqlqj/ dqg Sduhqw +OHDS, Surjudp/
dqg wkh Whhqdjh Sduhqw Ghprqvwudwlrq +WSG,/ zrunlqj sdshu/ PGUF1
Jud|/ V1/ E1 Udph| dqg U1 Nodxv +4<;5,1 Iurp Wkuhh wr Wzhqw|= Wkh Hduo| Wudlqlqj Surmhfw1
Edowlpruh/ PG= Xqlyhuvlw| Sdun Suhvv1
Julolfkhv/ ]1 +4<::,1 Hvwlpdwlqj wkh Uhwxuqv wr Vfkrrolqj= Vrph Hfrqrphwulf Sureohpv/
Hfrqrphwulfd/ 78+4,=40551
:9
Jurjjhu/ M1 dqg G1 Qhdo +5333,1 Ixuwkhu Hylghqfh rq wkh Hhfwv ri Vhfrqgdu| Vfkrrolqj/
Eurrnlqjv0Zkduwrq Sdshuv rq Xuedq Ddluv/ 48404<51
Kdqvhq/ N1/ M1 Khfnpdq dqg N1 Pxoohq +5335,1 Hgxfdwlrqdo Dwwdlqphqw/ Delolw| dqg Whvw
Vfruhv/ zrunlqj sdshu/ Xqlyhuvlw| ri Fklfdjr1
Kdqxvkhn/ H1 +4<:4,1 Whdfkhu Fkdudfwhulvwlfv dqg Jdlqv lq Vwxghqw Dfklhyhphqw= Hvwlpdwlrq
Xvlqj Plfur0Gdwd/ Dphulfdq Hfrqrplf Uhylhz/ 94+5,=5;305;;1
bbbbb +4<<:,1 Exgjhwv/ Sulrulwlhv/ dqg Lqyhvwphqw lq Kxpdq Fdslwdo/ lq P1 Nrvwhuv/ hg1/
Ilqdqflqj Froohjh Wxlwlrq= Jryhuqphqw Srolflhv Dqg Vrfldo Sulrulwlhv1 Zdvklqjwrq/ G1F1= DHL
Suhvv1
bbbbb +4<<;,1 Wkh Hylghqfh rq Fodvv Vl}h/ zrunlqj sdshu/ Z1 D1 Zdoolv Fhqwhu/ Xqlyhuvlw|
ri Urfkhvwhu1
bbbbb +5333,1 Ixuwkhu Hylghqfh ri wkh Hhfwv ri Fdwkrolf Vhfrqgdu| Vfkrrolqj= Frpphqw/
Eurrnlqjv0Zkduwrq Sdshuv rq Xuedq Ddluv/ 4<70<:1
bbbbb +5335,1 Wkh Idloxuh ri Lqsxw Edvhg Vfkrrolqj Srolflhv/ iruwkfrplqj lq Hfrqrplf
Mrxuqdo1
Kdqxvkhn/ H1 dqg M1 Oxtxh +5333,1 Vpdoohu Fodvvhv/ Orzhu VdodulhvB Wkh Hhfwv ri Fodvv Vl}h
rq Whdfkhu Oderu PdunhwvB lq V1 Odlqh dqg M1 Zdug/ hgv1/ Xvlqj Zkdw Zh Nqrz= D Uhylhz ri
wkh Uhvhdufk rq Lpsohphqwlqj Fodvv0Vl}h Uhgxfwlrq Lqlwldwlyhv iru Vwdwh dqg Orfdo Srolf|pdnhuv/
Rdn Eurrn/ LO= Qruwk Fhqwudo Uhjlrqdo Hgxfdwlrqdo Oderudwru|/ 680841
Kdxvhu/ U1 +4<<6,1 Wuhqgv lq Froohjh Dwwhqgdqfh Dprqj Eodfnv/ Zklwhv/ dqg Klvsdqlfv/ lq F1
Forwihowhu dqg P1 Urwkvfklog/ hgv1/ Vwxglhv ri Vxsso| dqg Ghpdqg lq Kljkhu Hgxfdwlrq1Fklfdjr=
Xqlyhuvlw| ri Fklfdjr Suhvv1
Khfnpdq/ M1 +4<<8,1 D Olih0F|foh Prgho ri Hduqlqjv/ Ohduqlqj dqg Frqvxpswlrq1 lq R1
Dvkhoihowhu dqg N1 Kdoorfn/ hgv1/ Oderu Hfrqrplfv/ Yro1 51 Eurrnhog/ YW= Hojdu2Dvkjdwh1
bbbbb +4<<<,1 Hgxfdwlrq dqg Mre Wudlqlqj= Grlqj Lw Uljkw/ Sxeolf Lqwhuhvw/ +468,=;9043:1
bbbbb +5333,1 Srolflhv wr Irvwhu Kxpdq Fdslwdo/ Uhvhdufk lq Hfrqrplfv/ 87+4,=60891
::
bbbbb +5334,1 Plfur Gdwd/ Khwhurjhqhlw|/ dqg wkh Hydoxdwlrq ri Sxeolf Srolf|= Qreho
Ohfwxuh/ Mrxuqdo ri Srolwlfdo Hfrqrp|/ 43<+7,=9:60:7;1
bbbbb +5335,1 Wkh JHG1 Errn pdqxvfulsw/ Xqlyhuvlw| ri Fklfdjr1
Khfnpdq M1/ F1 Khlqulfk dqg M1 Vplwk +5335,1 Wkh Shuirupdqfh ri Shuirupdqfh Vwdqgdugv/
iruwkfrplqj lq Mrxuqdo ri Kxpdq Uhvrxufhv1
Khfnpdq/ M1/ Q1 Krkpdqq/ P1 Nkrr dqg M1 Vplwk +5333,1 Vxevwlwxwlrq dqg Gursrxw Eldv
lq Vrfldo H{shulphqwv= D Vwxg| ri dq Lq xhqwldo Vrfldo H{shulphqw/ Wkh Txduwhuo| Mrxuqdo ri
Hfrqrplfv/ 448+5,=98409<71
Khfnpdq/ M1/ M1 Kvhh dqg \1 Uxelqvwhlq +5334,1 Wkh JHG lv d cPl{hg Vljqdo*= Wkh Hhfw
ri Frjqlwlyh dqg Qrqfrjqlwlyh Vnloov rq Kxpdq Fdslwdo dqg Oderu Pdunhw Rxwfrphv/ zrunlqj
sdshu/ Xqlyhuvlw| ri Fklfdjr1
Khfnpdq/ M1 dqg S1 Nohqrz +4<<;,1 Kxpdq Fdslwdo Srolf|/ lq P1 Ervnlq/ hg1/ Srolflhv wr
Surprwh Fdslwdo Irupdwlrq1 Vwdqirug/ FD= Krryhu Lqvwlwxwlrq1
Khfnpdq/ M1/ U1 OdOrqgh dqg M1 Vplwk +4<<<,1 Wkh Hfrqrplfv dqg Hfrqrphwulfv ri Dfwlyh
Oderu Pdunhw Surjudpv/ lq R1 Dvkhqihowhu dqg G1 Fdug/ hgv1/ Kdqgerrn ri Oderu Hfrqrplfv/ Yro1
61 Dpvwhugdp= Hovhylhu1
Khfnpdq/ M1/ D1 Od|qh0Iduudu dqg S1 Wrgg +4<<9,1 Kxpdq Fdslwdo Sulflqj Htxdwlrqv zlwk dq
Dssolfdwlrq wr Hvwlpdwlqj wkh Hhfw ri Vfkrrolqj Txdolw| rq Hduqlqjv/ Wkh Uhylhz ri Hfrqrplfv
dqg Vwdwlvwlfv/ :;+9,=89509431
Khfnpdq/ M1 dqg O1 Orfkqhu +5333,1 Uhwklqnlqj P|wkv Derxw Hgxfdwlrq dqg Wudlqlqj= Xq0
ghuvwdqglqj wkh Vrxufhv ri Vnloo Irupdwlrq lq d Prghuq Hfrqrp|/ lq V1 Gdq}ljhu dqg M1 Zdogirjho/
hgv1/ Vhfxulqj wkh Ixwxuh= Lqyhvwlqj lq Fkloguhq iurp Eluwk wr Froohjh1 Qhz \run= Uxvvhoo Vdjh
Irxqgdwlrq1
Khfnpdq/ M1/ O1 Orfkqhu dqg U1 Frvvd +5336,1 Xqghuvwdqglqj wkh Lqfhqwlyh Hhfwv ri wkh
HLWF rq Vnloo Irupdwlrq/ zrunlqj sdshu/ Xqlyhuvlw| ri Fklfdjr1
Khfnpdq/ M1/ O1 Orfkqhu/ M1 Vplwk dqg F1 Wdehu +4<<:,1 Wkh Hhfwv ri Jryhuqphqw Srolf| rq
:;
Kxpdq Fdslwdo Lqyhvwphqw dqg Zdjh Lqhtxdolw|/ Fklfdjr Srolf| Uhylhz/ 4+5,=40731
Khfnpdq/ M1/ O1 Orfkqhu dqg F1 Wdehu +4<<;d,1 H{sodlqlqj Ulvlqj Zdjh Lqhtxdolw|= H{sor0
udwlrqv Zlwk D G|qdplf Jhqhudo Htxloleulxp Prgho ri Hduqlqjv Zlwk Khwhurjhqhrxv Djhqwv1
Uhylhz ri Hfrqrplf G|qdplfv/4=408;1
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bbbbb +4<<;f,1 Wd{ Srolf| dqg Kxpdq Fdslwdo Irupdwlrq/ Dphulfdq Hfrqrplf Uhylhz/
;;+5,=5<605<:1
bbbbb +5333,1 Jhqhudo Htxloleulxp Frvw Ehqhw Dqdo|vlv ri Hgxfdwlrq dqg Wd{ Srolflhv
lq J1 Udqlv dqg O1N1 Udxw/ hgv1/ Wudgh/ Jurzwk dqg Ghyhorsphqw= Hvvd|v lq Krqru ri W1 Q1
Vulqlydvdq/ Fkdswhu 471 Dpvwhugdp= Hovhylhu Vflhqfh/ E1Y1/ 5<406<61
Khfnpdq/ M1/ O1 Orfkqhu dqg S1 Wrgg +5334,1 Iliw| \hduv ri Plqfhu Uhjuhvvlrqv/ zrunlqj
sdshu/ Xqlyhuvlw| ri Fklfdjr1
Khfnpdq/ M1 dqg \1 Uxelqvwhlq +5334,1 Wkh Lpsruwdqfh ri Qrqfrjqlwlyh Vnloov= Ohvvrqv iurp
wkh JHG Whvwlqj Surjudp/ Dphulfdq Hfrqrplf Uhylhz/ <4+5,=478047<1
Khfnpdq M1/ dqg M1 Vplwk +4<<;,1 Hydoxdwlqj wkh Zhoiduh Vwdwh/ lq V1 Vwuûp/ hg1/ Hfrqr0
phwulfv dqg Hfrqrplf Wkhru| lq wkh 53wk Fhqwxu|= Wkh Udjqdu Iulvfk Fhqwhqqldo V|psrvlxp1
Fdpeulgjh= Fdpeulgjh Xqlyhuvlw| Suhvv1
Khfnpdq M1/ M1 Vplwk dqg Q1 Fohphqwv +4<<:,1 Pdnlqj Wkh Prvw Rxw ri Vrfldo H{shulphqwv=
WkhLqwulqvlfXqfhuwdlqw|lqHylghqfhIurpUdqgrpl}hgWuldovZlwkDqDssolfdwlrq Wr Wkh
Qdwlrqdo MWSD H{shulphqw/ Uhylhz ri Hfrqrplf Vwxglhv/ 97+7,=7;:08681
Khfnpdq/ M1 dqg H1 Y|wodflo +5334,1 Lghqwli|lqj wkh Uroh ri Frjqlwlyh Delolw| lq H{sodlqlqj wkh
Ohyho ri dqg Fkdqjh lq wkh Uhwxuq wr Vfkrrolqj/ Uhylhz ri Hfrqrplfv dqg Vwdwlvwlfv/ ;6+4,=40451
Khuuhud/ F1/ F1 Vlsh/ Z1 PfFodqdkdq/ D1 Dueuhwrq/ dqg V1 Shsshu +5333,1 Phqwrulqj Vfkrro0
Djh Fkloguhq= Uhodwlrqvkls Ghyhorsphqw lq Frppxqlw|0Edvhg dqg Vfkrro0Edvhg Surjudpv1 Sklodgho0
skld= Sxeolf2Sulydwh Yhqwxuhv1
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Khuuqvwhlq/ U1 dqg F1 Pxuud| +4<<7,1 Wkh Ehoo Fxuyh1Qhz\run=WkhIuhhSuhvv1
Kloo/ P1 +4<<5,1 Wkh Sdqho Vwxg| ri Lqfrph G|qdplfv= D Xvhu*v Jxlgh1 Qhzexu| Sdun/ FD=
Vdjh Sxeolfdwlrqv1
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Kr{e|/ F1 +5333,1 Grhv Frpshwlwlrq Dprqj Sxeolf Vfkrrov Ehqhw Vwxghqwv dqg Wd{sd|huvB
Dphulfdq Hfrqrplf Uhylhz/ <3+8,= 453<0456;1
Mrkqvrq/ D1 +4<<9,1 Dq Hydoxdwlrq ri wkh Orqj0Whup Lpsdfwv ri wkh Vsrqvru0D0Vfkrodu Surjudp
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Mrkqvrq/ G1 +4<;;,1 Sulpdu| Suhyhqwlrq ri Ehkdylru Sureohpv lq \rxqj Fkloguhq= Wkh Krxv0
wrq Sduhqw0Fklog Ghyhorsphqw Fhqwhu/ lq U1 Sulfh/ H1 Frzhq/ U1 Orulrq/ dqg P1 Udprv0PfNd|/
hgv1/ 47 Rxqfhv ri Suhyhqwlrq= D Fdvherrn iru Sudfwlwlrqhuv/ Zdvklqjwrq/ GF= Dphulfdq Sv|fkr0
orjlfdo Dvvrfldwlrq/ 770851
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Mrujhqvrq/ G1 dqg P1 Kr +4<<<,1 Wkh Txdolw| ri wkh X1V1 Zrun Irufh/ 4<7;0<8/ zrunlqj
sdshu/ Kduydug Xqlyhuvlw|1
Mxgg/ N1 +5333,1 Lv Hgxfdwlrq dv Jrrg dv JrogB D Sruwirolr Dqdo|vlv ri KxpdqFdslwdo
Lqyhvwphqw/ zrunlqj sdshu/ Vwdqirug Xqlyhuvlw|1
Ndqh/ W1 +4<<7,1 Froohjh Hqwu| e| Eodfnv vlqfh 4<:3= Wkh Uroh ri Froohjh Frvwv/ Idplo|
Edfnjurxqg/ dqg wkh Uhwxuqv wr Hgxfdwlrq/ Wkh Mrxuqdo ri Srolwlfdo Hfrqrp|/ 435+8,=;:;0<441
bbbbb +4<<9,1 Froohjh Frvwv/ Eruurzlqj Frqvwudlqwv dqg wkh Wlplqj ri Froohjh Hqwu|/
Hdvwhuq Hfrqrplf Mrxuqdo/ 55+5,=4;404<71
bbbbb +4<<<,1 Wkh Sulfh ri Dgplvvlrq= Uhwklqnlqj Krz Dphulfdqv Sd| iru Froohjh/Zdvk0
lqjwrq/ G1F1= Eurrnlqjv Lqvwlwxwlrq1
bbbbb +5334,1 Froohjh Jrlqj dqg Lqhtxdolw|= D Olwhudwxuh Uhylhz/ zrunlqj sdshu/ Uxvvhoo
;3
Vdjh Irxqgdwlrq1
Nduro|/ O1 +5334,1 Lqyhvwlqj lq wkh Ixwxuh= Uhgxflqj Sryhuw| Wkurxjk Kxpdq Fdslwdo Lqyhvw0
phqwv/ lq V1 Gdq}lqjhu dqg U1 Kdyhpdq/ hgv1/ Xqghuvwdqglqj Sryhuw|/ Qhz \run= Uxvvhoo Vdjh
Irxqgdwlrq1
Nduro|/ O1/ S1 Juhhqzrrg/ V1 Hyhulqjkdp/ M1 Kxeh/ P1U1 Nloexuq/ F1S1 U|ghoo/ P1 Vdqghuv/
dqg M1 Fklhvd +4<<;,1 Lqyhvwlqj lq rxu Fkloguhq= Zkdw Zh Nqrz dqg Grq*w NqrzDerxwwkh
Frvw dqg Ehqhwv ri Hduo| Fklogkrrg Lqwhuyhqwlrqv/ Vdqwd Prqlfd/ FD= Udqg Frus1 HG 74< 9541
Nhdqh/ P1 dqg N1 Zroslq +5334,1 Wkh Hhfw ri Sduhqwdo Wudqvihuv dqg Eruurzlqj Frqvwudlqwv
rq Hgxfdwlrqdo Dwwdlqphqw/ Lqwhuqdwlrqdo Hfrqrplf Uhylhz/ 75+7,=4384044361
Nohlq/ U1/ U1 Vsdg| dqg D1 Zhlvv +4<<4,1 Idfwruv Dhfwlqj wkh Rxwsxw dqg Txlw Surshqvlwlhv
ri Surgxfwlrq Zrunhuv/ Uhylhz ri Hfrqrplf Vwxglhv/ 8;+5,=<5<0871
Nuxhjhu/ D1 +4<<<,1 H{shulphqwdo Hvwlpdwhv ri Hgxfdwlrq Surgxfwlrq Ixqfwlrqv/ Txduwhuo|
Mrxuqdo ri Hfrqrplfv/ 447+5,=7<:08651
bbbbb +5333,1 Hfrqrplf Vfhqh= D Vwxg| Edfnv Xs Zkdw Jhrujh Iruhpdq Douhdg|Vdlg/
Qhz \run Wlphv/ Wkh Mre Frsv Zrunv/ 63 Pdufk/ F51
Odoo|/ M1/ S1 Pdqjlrqh dqg D1 Krqlj +4<;;,1 Wkh V|udfxvh Xqlyhuvlw| Idplo|Ghyhorsphqw
Uhvhdufk Surjudp= Orqj0Udqjh Lpsdfw rq dq Hduo| Lqwhuyhqwlrq zlwk Orz0Lqfrph Fkloguhq dqg
Wkhlu Idplolhv/ lq G1 Srzhoo/ hg1/ Sduhqw Hgxfdwlrq dv Hduo| Fklogkrrg Lqwhuyhqwlrq1 Qruzrrg=
Deoh{/ :<04371
Odxuhqfh/ M1 +5333,1 Wkh Plolwdu| Shuirupdqfh ri JHG Kroghuv/ lq M1 Khfnpdq/ hg1/ Wkh
JHG1 Iruwkfrplqj/ Fklfdjr= Xqlyhuvlw| ri Fklfdjr Suhvv1
Ohyhqvwhlq/ H1/ P1 R*Kdud dqg M1 Phgghq +4<;6,1 Wkh Prwkhu0Fklog Surjudp ri wkh Yhuedo
Lqwhudfwlrq Surmhfw/ lq Frqvruwlxp iru Orqjlwxglqdo Vwxglhv= Dv wkh Wzlj lv Ehqw= Odvwlqj Hhfwv
ri Suh0vfkrro Surjudpv1 Kloovgdoh/ QM= Odzuhqfh Huoedxp/ 56:5961
Oloodug/ O1 dqg K1 Wdq +4<;9,1 Sulydwh Vhfwru Wudlqlqj= Zkr Jhwv Lw dqg ZkdwDuhLwv
HhfwvB Vdqwd Prqlfd/ Fdoliruqld= UDQG/ U066640GRO2UF1
;4
Orfkqhu/ O1 +4<<<,1 Hgxfdwlrq/ Zrun/ dqg Fulph= Wkhru| dqg Hylghqfh/ zrunlqj sdshu/
Xqlyhuvlw| ri Urfkhvwhu1
Orqj/ G1/ F1 Pdoodu dqg F1 Wkruwrq +4<;4,1 Hydoxdwlqj wkh Ehqhwv dqg FrvwvriwkhMre
Frusv/ Mrxuqdo ri Srolf| Dqdo|vlv dqg Pdqdjhphqw/ ;4=88:91
O|qfk/ O1 +4<<5,1 Sulydwh0Vhfwru Wudlqlqj dqg wkh Hduqlqjv ri \rxqj Zrunhuv/ Dphulfdq
Hfrqrplf Uhylhz/ ;5+4,=5<<06451
bbbbb +4<<6,1 Wudlqlqj dqg Wkh Sulydwh Vhfwru= Lqwhuqdwlrqdo Frpsdulvrq1 Fklfdjr= Xql0
yhuvlw| ri Fklfdjr Suhvv1
PdFxug|/ W1 dqg W1 Pur} +4<<8,1 Hvwlpdwlqj Pdfur Hhfwv iurp Uhshdwhg Furvv0Vhfwlrqv/
glvfxvvlrq sdshu/ Vwdqirug Xqlyhuvlw|1
Pduwlq/ M1 dqg G1 Juxee +5334,1 Zkdw Zrunv dqg iru Zkrp= D Uhylhz ri RHFG Frxqwulhv*
H{shulhqfh zlwk Dfwlyh Oderxu Pdunhw Srolflhv/ V0ZrSHf zrunlqj sdshu Qr1471
Phjklu/ F1 dqg P1 Sdoph +4<<<,1 Dvvhvvlqj wkh Hhfw ri Vfkrrolqj rq Hduqlqjv Xvlqj d Vrfldo
H{shulphqw/ LIV zrunlqj sdshu Qr1 Z<<2431
Plqfhu/ M1 +4<:7,1 Vfkrrolqjv/ H{shulhqfh/ dqg Hduqlqjv1 QEHU/ glvwulexwhg e| Froxpeld
Xqlyhuvlw| Suhvv1
bbbbb +4<<6,1 Lqyhvwphqw lq X1V1 Hgxfdwlrq dqg Wudlqlqj/ Froxpeld Xqlyhuvlw| glvfxvvlrq
sdshu Qr1 9:41
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Urph Flw| Vfkrrov/ Urph/ Jhrujld/ xqsxeolvkhg sdshu1
Pxooljdq/ F1 +4<<:,1 Sduhqwdo Sulrulwlhv dqg Hfrqrplf Lqhtxdolw|1 Fklfdjr= Xqlyhuvlw| ri
Fklfdjr Suhvv1
Pxuqdqh/ U1 +4<:8,1 Wkh Lpsdfw ri Vfkrro Uhvrxufhv rq wkh Ohduqlqj ri Lqqhu Flw| Fkloguhq1
Fdpeulgjh= Edoolqjhu Sxeolvklqj Fr1
Qdwlrqdo Fhqwhu iru Hgxfdwlrq Vwdwlvwlfv +QFHV, +4<<:,1 Wkh 4<<: Gljhvw ri Hgxfdwlrq Vwdwlv0
wlfv1 Zdvklqjwrq/ G1F1= QFHV1
;5
Qhdo/ G1 +4<<:,1 Wkh Hhfwv ri Fdwkrolf Vhfrqgdu| Vfkrrolqj rq Hgxfdwlrqdo Dfklhyhphqw/
Mrxuqdo ri Oderu Hfrqrplfv/ 48+4,=<;04561
RHFG dqg Vwdwlvwlfv Fdqdgd +4<<8,1 Olwhudf|/ Hfrqrp| dqg Vrflhw|= Uhvxowv ri wkh Iluvw
Lqwhuqdwlrqdo Dgxow Olwhudf| Vxuyh|1
Ruhog/ J1 +4<<5,1 Prqh|/ Htxlw|/ dqg Froohjh Dffhvv/ Kduydug Hgxfdwlrqdo Uhylhz/ 5+6,=66:0
6:51
Sdophu/ I1 +4<;6,1 Wkh Kduohp Vwxg|= Hhfwv e| W|sh ri Wudlqlqj/ Djh ri Wudlqlqj dqg Vrfldo
Fodvv/ lq Frqvruwlxp iru Orqjlwxglqdo Vwxglhv= Dv wkh Wzlj lv Ehqw= Odvwlqj Hhfwv riSuh0vfkrro
Surjudpv1 Kloovgdoh/ QM= Odzuhqfh Hoedxp1
Shwhuvrq/ S1 dqg E1 Kdvvho +4<<;,1 Ohduqlqj Iurp Vfkrro Fkrlfh1 Zdvklqjwrq/ G1F1= Eurrnlqjv
Lqvwlwxwlrq Suhvv1
Skhosv/ H1 +4<<:,1 Uhzduglqj Zrun= Krz wr Uhvwruh Sduwlflsdwlrq dqg wr Vhoi0Vxssruw Iuhh
Hqwhusulvh1 Fdpeulgjh/ PD= Kduydug Xqlyhuvlw| Suhvv1
Skloolsv/ P1/ M1 Eurrnv0Jxqq/ J1 Gxqfdq/ S1 Nohedqry/ dqg M1 Fudqh +4<<;,1 Idplo| Edfn0
jurxqg/ Sduhqwlqj Sudfwlfhv/ dqg wkh Eodfn0Zklwh Whvw Vfruh Jds/ lq F1 Mhqfnv dqg P1 Skloolsv/
hgv1/ Wkh Eodfn0Zklwh Whvw Vfruh Jds1 Zdvklqjwrq G1F1= Wkh Eurrnlqjv Lqvwlwxwlrq Suhvv1
Txljoh|/ M1 dqg H1 Vprohqvn| +4<<3,1 Lpsurylqj H!flhqf| lq wkh Wd{ Wuhdwphqw ri Wudlqlqj
dqg Hgxfdwlrqdo H{shqglwxuhv/ lq O1 Edvvl/ dqg G1 Fudzirug/ hgv1/ Oderu Hfrqrplfv dqg Sxeolf
Srolf|= Uhvhdufk lq Oderu Hfrqrplfv/ Yro1 441 Juhhqzlfk/ FW= MDL Suhvv/ ::0<81
Udph|/ F1/ G1 Eu|dqw/ I1 Fdpsehoo/ M1 Vsduolqj dqg E1 Zdvln +4<;;,1 Hduo| Lqwhuyhqwlrq iru
Kljk0Ulvn Fkloguhq= Wkh Fdurolqd Hduo| Lqwhuyhqwlrq Surjudp/ lq U1 Sulfh/ H1 Frzhq/ U1 Orulrq/
dqg P1 Udprv0PfNd|/ hgv1/ 47 Rxqfhv ri Suhyhqwlrq= D Fdvherrn iru Sudfwlwlrqhuv1 Zdvklqjwrq/
GF= Dphulfdq Sv|fkrorjlfdo Dvvrfldwlrq/ 650761
Urxvh/ F1 +4<<:,1 Sulydwh Vfkrro Yrxfkhuv dqg Vwxghqw Dfklhyhphqw= Dq Hydoxdwlrq ri wkh
Plozdxnhh Sduhqwdo Fkrlfh Surjudp/ QEHU zrunlqj sdshu Qr1 8<971
Vfkrfkhw/ S1/ M1 Exujkdugw/ dqg V1 Jod}hupdq +5334,1 Qdwlrqdo Mre Frusv Vwxg|= Wkh Lpsdfw
;6
ri Mre Frusv rq Sduwlflsdqwv* Hpsor|phqw dqg Uhodwhg Rxwfrphv/ Zdvklqjwrq/ G1F1= Xqlwhg
Vwdwhv Jryhuqphqw Sulqwlqj R!fh1
Vfkzhlqkduw/ O1/ K1 Eduqhv dqg G1 Zhlnduw +4<<6,1 Vljqlfdqw Ehqhwv= Wkh Kljk2Vfruh Shuu|
Suh0Vfkrro Vwxg| Wkurxjk Djh 5:1 \svlodqwl/ PL= Kljk Vfrsh Suhvv1
Vhlw}/ Y1 +4<<3,1 Lqwhuyhqwlrq Surjudpv iru Lpsryhulvkhg Fkloguhq= D Frpsdulvrq ri Hgxfd0
wlrqdo dqg Idplo| Vxssruw Prghov/ lq U1 Ydvwd/ hg1/ Dqqdov ri Fklog Ghyhorsphqw= D Uhvhdufk
Dqqxdo/ Yro1 :/ Orqgrq/ X1N1= Mhvvlfd Nlqjvoh| Sxeolvkhuv/ :604361
Vkhd/ M1 +5333,1 Grhv Sduhqw*v Prqh| PdwwhuB Mrxuqdo ri Sxeolf Hfrqrplfv/ ::+5,=4880;71
Vkrqnr/ M1 dqg G1 Skloolsv/ hgv1 +5333,1 Iurp Qhxurqv wr Qhljkerukrrgv= Wkh Vflhqfh ri
Hduo| Fklogkrrg Ghyhorsphqw1 Zdvklqjwrq G1F1= Qdwlrqdo Dfdghp| Suhvv1
Vshqfh/ P1 +4<:7,1 Pdunhw Vljqdoolqj1 Fdpeulgjh/ PD= Kduydug Xqlyhuvlw| Suhvv1
Vwdqoh|/ P1 +4<<<,1 Hgxfdwlrq/ Rssruwxqlw|/ dqg wkh Plg0Fhqwxu| J1L1 Eloov/ zrunlqj sdshu/
Kduydug Xqlyhuvlw|1
Vwhuqehuj/ U1 +4<;8,1 Eh|rqg LT= D Wuldufklf Wkhru| ri Kxpdq Lqwhooljhqfh1 Fdpeulgjh/ X1N1=
Fdpeulgjh Xqlyhuvlw| Suhvv1
Wdehu/ F1 +5334,1 Wkh Ulvlqj Froohjh Suhplxp lq wkh Hljkwlhv= Uhwxuq wr Froohjh ru Uhwxuq
wr Xqrevhuyhg Delolw|B Uhylhz ri Hfrqrplf Vwxglhv/ 9;+6,=9980<41
Wdjjduw/ U1 +4<<8,1 Txdqwxp Rssruwxqlw| Surjudp Rssruwxqlwlhv1 Sklodghoskld= Lqgxvwuldol}d0
wlrq Fhqwhu ri Dphulfd1
Wlhuqh|/ M1 dqg M1 Jurvvpdq +4<<8,1 Pdnlqj d Glhuhqfh= Dq Lpsdfw Vwxg| ri Elj Eurwkhuv2Elj
Vlvwhuv1 Sklodghoskld= Sxeolf2Sulydwh Yhqwxuhv1
Xqlwhg Vwdwhv Ghsduwphqw ri Oderu +4<<8,1 Zkdw*v Zrunlqj +Dqg Zkdw*v Qrw,= D Vxppdu|
ri Uhvhdufk rq wkh Hfrqrplf Lpsdfwv ri Hpsor|phqw dqg Wudlqlqj Surjudpv1 Zdvklqjwrq G1F1=
X1V1 Ghsduwphqw ri Oderu1
Xqlwhg Vwdwhv Jhqhudo Dffrxqwlqj R!fh +4<<9,1 Mre Wudlqlqj Sduwqhuvkls Dfw= Orqj0Whup
Hduqlqjv dqg Hpsor|phqw Rxwfrphv/ Uhsruw Qr1 JDR2KHKH <90731 Zdvklqjwrq/ G1F1= Jhqhudo
;7
Dffrxqwlqj R!fh/ 550561
Xutxlrod/ P1 dqg F1 Kvlhk +5335,1 Zkhq Vfkrrov Frpshwh/ Krz Gr Wkh| FrpshwhB Dq
Dvvhvvphqw ri Fkloh*v Qdwlrqzlgh Vfkrro Yrxfkhu Surjudp/ zrunlqj sdshu/ Fruqhoo Xqlyhuvlw|1
Yhqwxud/ V1 M1 dqg F1 D1 Edfkudfk +5333,1 Qrqpdulwdo Fklogehdulqj lq wkh Xqlwhg Vwdwhv/
4<730<</ Qdwlrqdo Ylwdo Vwdwlvwlfv Uhsruwv/ 7;+49,1 K|dwwvylooh/ PG= Qdwlrqdo Fhqwhu iru Khdowk
Vwdwlvwlfv1
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Sulydwh Yhqwxuhv1
Zloolv/ U1 +4<;9,1 Zdjh Ghwhuplqdqwv= D Vxuyh| dqg Uhlqwhusuhwdwlrq ri Kxpdq Fdslwdo
Hduqlqjv Ixqfwlrqv/ lq R1 Dvkhqihowhu dqg G1 Fdug/ hgv1/ Kdqgerrn ri Oderu Hfrqrplfv/ Yro1 4/
Fkdswhu 431 Qhz \run= Qruwk Kroodqg1
Zloolv/ U1 dqg V1 Urvhq +4<:<,1 Hgxfdwlrq dqg Vhoi0Vhohfwlrq/ Mrxuqdo ri Srolwlfdo Hfrqrp|/
;:+8,=V:0V691
Zlqvkls/ F1 dqg V1 Nruhqpdq +4<<:,1 Grhv Vwd|lqj lq Vfkrro Pdnh \rx VpduwhuB Wkh Hhfw
ri Hgxfdwlrq rq LT lq Wkh Ehoo Fxuyh/ lq E1 Ghyolq/ V1 Ihlqehuj/ G1 Uhvqlfn/ dqg N1 Urhghu/
hgv1/ Lqwhooljhqfh/ Jhqhv/ dqg Vxffhvv= Vflhqwlvwv Uhvsrqg wr Wkh Ehoo Fxuyh1 Qhz \run= Vsulqjhu/
Frshuqlfxv/ 5480671
Zlwwh/ M1 +5333,1 Wkh Pdunhw Dssurdfk wr Hgxfdwlrq= Dq Dqdo|vlv ri Dphulfd*v Iluvw Yrxfkhu
V|vwhp/ Sulqfhwrq= Sulqfhwrq Xqlyhuvlw| Suhvv1
;8
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9
44
1
94
6
1948
1950
1
9
52
1
95
4
1956
1
9
58
1
96
0
1
9
62
1
96
4
1
96
6
1
9
68
1
97
0
1
97
2
1
9
74
1
97
6
1978
1
9
80
Year of Birth
% Participating
0
10
20
30
40
50
60
70
80
1920
1922
1924
1926
1928
1930
1932
1934
1936
1938
1940
1942
1944
1946
1948
1950
1952
19
54
1956
19
58
1960
19
62
19
64
19
66
19
68
19
70
19
72
19
74
1976
1978
19
80
Year of Birth
0
10
20
30
40
50
60
70
80
90
1920
1922
19
24
1926
19
28
1930
19
32
1934
19
36
1938
1940
1942
1944
1946
1948
1950
1952
1
9
54
1956
19
58
1
9
60
1
9
62
1964
19
66
1968
1970
1972
19
74
1976
197
8
198
0
Year of Birth
Figure 1
Schooling Participation Rates by Year of Birth
Data from CPS 2000
A. Whites
B. Blacks
C. Hispanics
College Enrollment High School Graduates and GEDs* High School Dropout**
* GEDs are known for the birth cohort 1971-1982 ** Dropouts exluded GEDs
% Participating
% Participating
A. College Participation Rates by Year of Birth
Data from CPS 2000
0
10
20
30
40
50
60
70
1
91
0
1
91
2
1
91
4
1
91
6
1
91
8
1
92
0
1
92
2
1
92
4
1
92
6
1
92
8
1
93
0
1
93
2
1
93
4
1
93
6
1
93
8
1
94
0
1
94
2
1
9
4
4
1
94
6
1
9
4
8
1
9
5
0
1
9
5
2
1
95
4
1
9
5
6
1
95
8
1
9
6
0
1
9
6
2
1
96
4
1
9
6
6
1
96
8
1
9
7
0
1
97
2
1
9
7
4
1
97
6
1
97
8
Year of Birth
%
Overall
Natives
Immigrants
% of Immigrants in Overall Population
B. High School Dropout Rates (Not Including GEDs) by Year of Birth
0
10
20
30
40
50
60
70
80
1
9
1
0
1
9
1
2
1
9
1
4
1
9
1
6
1
9
1
8
1
9
2
0
1
9
2
2
1
9
2
4
1
9
2
6
1
9
2
8
1
9
3
0
1
9
3
2
1
9
3
4
1
9
3
6
1
9
3
8
1
9
4
0
1
9
4
2
1
94
4
1
94
6
1
94
8
1
95
0
1
95
2
1
95
4
1
95
6
1
95
8
1
96
0
1
96
2
1
96
4
1
96
6
1
96
8
1
97
0
1
97
2
1
97
4
1
97
6
1
97
8
Year of Birth
%
Overall
Natives Immigrants % of Immigrants in Overall Population
C. Percentage of Overall Educational Participation Rates due to Immigrants by Year of Birth
0
10
20
30
40
50
60
70
80
1
91
0
1
91
2
1
91
4
1
91
6
1
91
8
1
92
0
1
9
2
2
1
92
4
1
92
6
1
92
8
1
93
0
1
93
2
1
93
4
1
9
3
6
1
93
8
1
9
4
0
1
94
2
1
94
4
1
94
6
1
94
8
1
95
0
1
95
2
1
95
4
1
95
6
1
95
8
1
96
0
1
96
2
1
96
4
1
96
6
1
96
8
1
97
0
1
97
2
1
97
4
1
97
6
1
97
8
Year of Birth
% of high school dropouts (not including GEDs) who are immigrants % of people who attended college who are immigrants
%%
Figure 2
Figure 3
A. The Share of High School Dropouts in the USA, 1971-1998
10. 0
15. 0
20. 0
25. 0
30. 0
35. 0
1
97
1
1
97
1
9
7
1
97
1
97
1
9
7
1
97
1
9
7
1
9
7
1
9
8
1
9
8
1
9
8
1
98
1
98
4
1
98
5
1
9
8
6
1
9
8
7
1
98
8
1
98
9
1
99
0
1
99
1
1
9
9
3
1
99
4
1
99
5
1
9
9
6
1
99
7
1
99
8
% of high school graduates in the population of 17-year-olds
B. People Receiving High School Equivalency Credentials as a Percent of Total
High School Credentials Issued by Public Schools, Private Schools
and the GED Program USA, 1971- 1999
5.0
7.0
9.0
11.0
13.0
15.0
17.0
1
97
1
1
9
7
2
1
97
3
1
9
7
4
1
97
5
1
9
7
6
1
9
7
7
1
9
7
8
1
9
7
9
1
98
0
1
9
8
1
1
9
8
2
1
98
3
1
9
8
4
1
9
8
5
1
9
8
6
19 87
1
9
8
8
19
89
1
9
9
0
1
9
9
1
19
92
1
9
9
3
19 94
19
95
19 96
19 97
1
9
9
8
19 99
C. High School Graduates of Regular Day School Programs, Public and Private
as a Percent of 17 Years Old Population
USA, 1971-1999
66.0
68.0
70.0
72.0
74.0
76.0
78.0
1
9
7
1
1
9
7
2
1
9
7
3
1
9
7
4
1
9
7
5
1
9
7
6
1
9
7
7
1
9
7
8
1
9
7
9
1
9
8
0
1
9
8
1
1
9
8
2
1
9
8
3
1
9
8
4
1
9
8
5
1
9
8
6
1
9
8
7
1
9
8
8
1
9
8
9
1
9
9
0
1
9
9
1
1
9
9
2
1
9
9
3
1
9
9
4
1
9
9
5
1
9
9
6
1
9
9
7
1
9
9
8
1
9
9
9
% of high school dropouts in the population of 16- to 24-year-olds
Source: U.S. Based on data from (1) The Department of Education National Center for Education Statistics
and (2) American Council on Education, General Educational Development Testing Service.
%
%
%
College Participation, 18 to 24 Yrs, HS Grads and GED Holders
White Males
40.00%
45.00%
50.00%
55.00%
60.00%
65.00%
70.00%
75.00%
80.00%
85.00%
90.00%
1
97
0
1
9
7
2
1
97
4
1
9
7
6
1
97
8
1
9
8
0
1
9
8
2
1
9
8
4
1
98
6
1
9
8
8
1
99
0
1
99
2
1
99
5
1
99
7
1
99
9
Percent
Family Income Bottom Quartile
Family Income Third Quartile
Family Income Top Half
Figure 4
Source: These numbers were computed from the CPS P-20 School Reports and the October CPS.
*Dependent is living at parental home or supported by parental family while at college.
De
p
endent* White Males
Table 1
Effects of a $1,000 Increase in Gross Tuition (Both Two- and Four-Year)
on the College Entry Probabilities of High School Completers
By Family Income Quartile and By AFQT Quartile
Whites Hispanics
(1)
(3)
A. Overall Gross Tuition Effects
(1) No explanatory variables except -.17 -.10 -.10
tuition in the model
(2) Baseline specication (see note at -.06 -.04 -.06
table base, includes family income and
background, and so forth)
(3) Adding AFQT to the row (2) -.05 -.03 -.06
specification
B. By Family Income Quartiles (panel A row (2) specification)
(4) Top Quartile -.04 -.01 -.04
(5) Second Quartile -.06 -.03 -.05
(6) Third Quartile -.07 -.07 -.08
(7) Bottom Quartile -.06 -.05 -.08
(8) Joint Test of Equal Effects .49 .23 .66
Across Quartiles (P-values)
C. By Family Income Quartiles (panel A row (3) specification)
(9) Top Quartile -.02 -.02 -.02
(10) Second Quartile -.06 .00 -.05
(11) Third Quartile -.07 -.05 -.09
(12) Bottom Quartile -.04 -.04 -.07
(13) Joint Test of Equal Effects .34 .45 .49
Across Quartiles (P-values)
D. By AFQT Quartiles (panel A row (3) specification
plus tuition-AFQT interaction terms)
(14) Top Quartile -.03 -.02 -.03
(15) Second Quartile -.06 -.01 -.05
(16) Third Quartile -.06 -.03 -.07
(17) Bottom Quartile -.05 -.03 -.05
(18) Joint Test of Equal Effects .60 .84 .68
Across Quartiles (P-values)
Gross tuition is the nominal sticker-price of college and excludes scholarship and loan support.
Notes: These simulations assume both two-year and four-year college tuition increase by $1,000
for the population of high school completers. The baseline specification used in row (2) of panel A and
rows (4) through (7) of panel B includes controls for family background, family income, average wages in
the local labor market, tuition at local colleges, controls for urban and southern residence, tuition-family
income interactions, estimated Pell grant award eligibility, and dummy variables, that indicate the proxim-
ity of two- and four-year colleges. Panel D specification adds AFQT and an AFQT-Tuition interaction to
Source: Cameron and Heckman (1999)
(2)
Blacks
the baseline specification.
College Participation by Race
Dependent High School Graduates and GED Holders
Males, Ages 18-24
0.4
0.45
0.5
0.55
0.6
0.65
0.7
1971
1973
1975
1977
1979
1981
1983
1985
1987
1989
1991
1993
1995
1997
Year
Rate
White Black Hispanic
Note: Three-year moving averages are shown
Figure 5
Source: These numbers were computed from the CPS P-20 School Reports and the October CPS.
*Dependent is living at parental home or supported by parental family while at college.
Preschool School
Post School
Preschool Programs
Schooling
Job Training
Age
Rate of
Return to
Investment
in Human
Capital
Figure 6-1
Rates of Return to Human Capital Investment Initially
Setting Investment to be Equal Across all Ages
0
Opportunity
Cost of Funds
r
Rates of Return to Human Capital Investment Initially Setting Investment to be Equal Across all Ages
Preschool School
Post School
0
Figure 6-2
Optimal Investment Levels
Optimal Investment by Age
Age
Table 2
Adjusted Gaps in College Participation
A. P ercentage of Population Credit Constrained
White Black Hispanic Overall
Males Females Males Females Males Females
Enrollment .0515 .0449 -.0047 .0543 .0433 -.0789 .0419
Complete 4-year College -.0621 .0579 -.0612 -.0106 .0910 .0908 -.0438
Complete 2-y ear College .0901 .0436 -.0684 -.0514 .2285 .0680 .0774
Proportion of People Not Delaying College Entry .0872 -.0197 -.1125 -.1128 .1253 -.0053 .0594
Enrollment in 4-year vs. 2-year College .0646 .0491 .1088 .0024 .1229 -.0915 .0587
B. Percentage of the Population Credit Constrained - Only Statistically Significant Gaps
White Black Hispanic Overall
Males Females Males Females Males Females
Enrollment 0 .0095 0 .0164 .0278 -.0139 .0018
Complete 4-ye ar College -.0545 .0089 -.0596 0 0 0 .0461
Complete 2-ye ar College 0 0 0 0 0 .0409 .0020
Proportion of People Not Delaying College Entry .0714 -.0318 -.0190 .0459 .0487 0 .0538
Enrollment in 4-year vs. 2-year College .0530 0 0 0 0 -.0451 .0391
C. Percentage of Population Family Constrained
White Black Hispanic Overall
Males Females Males Females Males Females
Enrollment .3123 .3280 .2658 .2420 .3210 .2923 .2623
Complete 4-year College .2723 .2338 .1435 .0738 .4950 .0205 .1958
Complete 2-year College -.1718 -.0350 -.0763 -.0565 -.1945 .2168 -.0785
Proportion of People Not Delaying College Entry .1965 .1898 .1910 .0460 .1950 .1360 .1135
Enrollment in 4-year vs. 2-year College .0568 .2423 .1643 .1143 .1533 .0738 .1155
D. Percentage of Population Family Constrained - Only Statistically Significant Gaps
White Black Hispanic Overall
Males Females Males Females M ales Females
Enrollment .3123 .3280 .2378 .2420 .3210 .2923 .2623
Complete 4-year College .2723 .2338 .0960 0 .4950 0 .1958
Complete 2-year College -.1408 0 0 0 0 .1678 -.0730
Proportion of People Not Delaying College Entry .1718 .1328 .1403 0 .1560 0 .1135
Enrollment in 4-year vs. 2-year College .0333 .2423 .1350 .0848 .1225 0 .1155
Notes: Credit constraint s are measured in the following way. Within each AFQT tertile, regress enrollment (completion,
delay) on quartiles of the distribution of family income at 17 and family bac kground variables (south, broken, urban,
mother’s education, father’s education): | = + I + T
1
1
+ T
2
2
+ T
3
3
, where | is enrollment (completion, delay),
I is a vector of family background variables, T
1
is a dummy for being in the first quartile of the family income distribution,
T
2
for the second and T
3
for the third. Within each AF QT tertile, the percentage of people constrained in eac h
quartile of family income is measured by
1
,
2
and
3
, which are gaps in average enrollment (completion, delay) between
each quartile and the top quartile of the family income. To get the numbers in the table we multiply the measured gap in
enrollment (completion, delay) for each quartile relativ e to the highest quartile by the percentage of people in that AFQT
tertile-Family Income quartile. Within each AF QT tertile we add over the three bottom quartiles of family income and then
add over the three tertiles of AFQT to get the number of credit constrained people in the population. When computing
family constraints we use a family background index which is a linear combination of south, broken, urban, mother’s
education, father’s education and AFQT. The coe!cien ts for this linear combination are obtained by doing a linear
regression of enrollmen t (completion, delay) on the variables composing the index. We then construct quartiles of this index.
Family constraints are measured in the following way. Regress enrollment (completion, delay) on the family background
quartile and family income at age 17: | = + T
1
1
+ T
2
2
+ T
3
3
+ Lqf17, where | is enrollmen t (completion , delay),
T
1
is a dummy for being in the first quartile of the family background index, T
2
for the second and T
3
for the third,
and Lqf17 is family income at age 17. The percenta ge of people constrained in each quartile of the family background
index is measured by
1
,
2
,and
3
, which are gaps in average enrollment (completion, delay) between each quartile
and the top quartile of the family background index. To get the numbers in the table we multiply the measured gap in
enrollment (completion, delay) for each quartile relative to the highest quartile by the percentage of people in that quartile.
Then we add over the three bottom quartiles to get the n umber of family constrained people in the population. The
coe!cien ts for these regressions for white males are presented in the appendix tables B-1 and B-2. Results for the other
demographic groups are available on request from the authors.
Table 3
Regressions of Enrollment in College on Per Capita Permanent Income,
Per Capita Early Income, and Per Capita Late Income: Children of NLSY
Variable (1) (2) (3) (4)
Family Income 0-18 (Permanent Income) 0.3114 0.2752 0.311 0.2645
(Standard Error) (0.0463) (0.0755) (0.0613) (0.0996)
Income 0-5 - 0.0498 - 0.053
(Standard Error) (0.0821) (0.0877)
Income 16-18 - - -0.0005 0.013
(Standard Error) (0.0605) (0.0645)
PIAT-Math at Age 12 0.0074 0.0073 0.0073 0.0073
(Standard Error) (0.0018) (0.0018) (0.0018) (0.0018)
Cons tant 0.154 0.1521 0.1523 0.1506
(Standard Error) (0.0259) (0.0261) (0.0260) (0.0262)
Observations 863 863 854 854
R
2
.1 .1 .1 .1
Notes: Family income (permanent income) 0-18 is average family income between the ages of 0 and 18.
Income 0-5 is average family income b etween the ages of 0 and 5. Income 16-18 is average family income
between the ages of 16 and 18. Income is measured in per capita terms (dividing family income by family
size year by year) in tens of thousands o f 199 3 dollars.
Average discounted family income: We used a discount rate of 5%. PIAT-Math is a math test
score. For details on this sa m pl e see BL S (2 001 ). Le t
\
l>w
be the per capita family income at age w for child l.
Family income
0-18 =
18
P
w=0
\
l>w
(1+u)
w
·
1
1+u
1
(
1
1+u
)
19
1
> resources in present value term s over the life of
the child where
u is theinterest rate = =05= Incom e 0-5 =
5
P
w=0
\
l>w
(1+u)
w
·
1
1+u
1
(
1
1+u
)
6
1
=
Incom e 16- 18 =
1
(1+u)
15
18
P
w=16
\
l>w
(1+u)
w
·
1
1+u
1
(
1
1+u
)
3
1
=
A. Percentage Enrolled in 2-Year and 4-Year Colleges B. Adjusted Percentage Enrolled in 2-Year and 4-Year Colleges
C. 4-Year College Completion Rate
D. Adjusted 4-Year College Completion Rate
F. Adjusted Percentage with No Delay in College Entry
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Bottom Middle Top
AFQT Terciles
Lowest Income Quartile Second Income Quartile Third Income Quartile Highest Income Quartile
E. Percentage with No Delay in College Entry
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
0.80
0.90
1.00
Bottom Middle Top
AFQT Terciles
Lowest Income Quartile Second Income Quartile Third Income Quartile Highest Income Quartile
Figure 7-1
Enrollment, Completion and No Delay Rates by Family Income Quartiles and Age-Adjusted AFQT Terciles
White Males, NLSY79
Note: To draw these graphs we performed the following steps. 1) Within each AFQT tercile, we regress percentage enrolled,
completion rate, and percentage with no delay on family background: y = a + Fg +Q
1
b
1
+Q
2
b
2
+Q
3
b
3
, where y is percentage
enrolled, completion rate, or percentage with no delay, F is a vector of family background variables (southern origin, broken
home, urban origin, mother's education and father's education), Q
1
is a dummy for being in the first quartile of the distribution
of family income at 17, Q
2
is for being in the second quartile and Q
3
is for being in the third quartile. 2) Then, within each AFQT
tercile, the height of the first bar is given by a + F
_
g+b
1
, the second is given by a + F
_
g+b
2
, the third by a + F
_
g+b
3
and the fourth
by a + F
_
g (where F
_
is a vector of the mean values for the variables in F). The coefficients for the regression are given in the
appendix table B-3.
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
0.80
0.90
Botton Middle Top
AFQT Test Tercile
Lowest Income Quartile Second Income Quartile Third Income Quartile Highest Income Quartile
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
Botton Middle Top
AFQT Test Tercile
Lowest Income Quartile Second Income Quartile Third Income Quartile Highest Income Quartile
Highest Income Quartile
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
0.80
0.90
Botton Middle Top
AFQT Test Tercile
Lowest Income Quartile Second Income Quartile Third Income Quartile Highest Income Quartile
0.00
0.20
0.40
0.60
0.80
1.00
1.20
Botton Middle Top
AFQT Test Tercile
Lowest Income Quartile Second Income Quartile Third Income Quartile Highest Income Quartile
A. Enrollment
B. Adjusted Enrollment
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
Lowes t S econd T hird Highes t
C. Completion of 4-Year College
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
Lowes t S econd T hird Highes t
D. Adjusted Completion of 4-Year College
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
Lowes t S econd T hird Highes t
E. Proportion Not Delaying College Entry
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
Lowes t S econd T hird Highes t
F. Adjusted Proportion Not Delaying College Entry
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
Lowes t S econd T hird Highes t
Family Background - AFQT Quartile
Family Background - AFQT Quartile
Family Background - AFQT Quartile
Family Background - AFQT Quartile
Family Background - AFQT Quartile
Family Background - AFQT Quartile
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
Lowes t Sec ond T hird Highes t
Figure 7-2
NLSY79 White Males
Enrollment, Completion and Delay
by Family Background - AFQT Quartiles
We correct for the effect of schooling at the test date on AFQT. The family background-AFQT index is based on a linear
combination of south, broken home, urban, mother's education, father's education and AFQT. For the residual plots, we
condition on family income at age 17. See table B-4 in the appendix for the coefficients of the linear combination of the
variables forming this index.
A. Average Percentile Rank on PIAT-Math Score, by Income Quartile*
35
40
45
50
55
60
65
6 8 10 12
Age
*The income measure we use is average family income between the ages of 6 and 10. Income quartiles are
then computed from this measure of income
Score Percentile
Lowest Income Quartile Second Income Quartile Third Income Quartile Highest Income Quartile
B. Average Percentile Rank on PIAT-Math Score, by Income Quartile*
Whites Only
45
50
55
60
65
70
681012
Age
*The income measure we use is average family income between the ages of 6 and 10. Income quartiles are
then computed from this measure of income
Score Percentile
Lowest Income Quartile Second Income Quartile Third Income Quartile Highest Income Quartile
C. Average Percentile Rank on PIAT-Math Score, by Race
30
35
40
45
50
55
60
65
681012
Age
Score Percentile
Hispanic Black White
Figure 8
Children of NLSY
A. Residualized Average PIAT-Math Score Percentiles by Income Quartile*
35
40
45
50
55
60
65
681012
Age
*Residualized on maternal education, maternal AFQT and broken home at each age (we use AFQT
corrected for the effect of schooling).
Score Percentile
Lowest Income Quartile Second Income Quartile Third Income Quartile Highest Income Quartile
C. Residualized Average PIAT-Math Score Percentile by Race*
30
35
40
45
50
55
60
65
681012
Age
*Residualized on maternal education, maternal AFQT and broken home at each
age and family income at each age (we use AFQT corrected for the effect of schooling).
Score Percentile
Hispanic Black White
Figure 9
Children of NLSY
B. Residualized Average PIAT-Math Score Percentiles by Income Quartile*
Whites Only
45
50
55
60
65
70
681012
Age
*Residualized on maternal education, maternal AFQT and broken home at each
age (we use AFQT corrected for the effect of schooling).
Score Percentile
Lowest Income Quartile Second Income Quartile Third Income Quartile Highest Income Quartile
A. Average Percentile Rank on Anti-Social Score, by Income Quartile*
20
25
30
35
40
45
50
55
4681012
Age
*The income measure we use is average family income between the ages of 6 and 10. Income quartiles are
then computed from this measure of income
Score Percentile
Lowest Income Quartile Second Income Quartile Third Income Quartile Highest Income Quartile
B. Average Percentile Rank on Anti-Social Score, by Income Quartile*
Whites Only
25
30
35
40
45
50
55
60
65
4681012
Age
*The income measure we use is average family income between the ages of 6 and 10. Income quartiles are
then computed from this measure of income
Score Percentile
Lowest Income Quartile Second Income Quartile Third Income Quartile Highest Income Quartile
C. Average Percentile Rank on Anti-Social Score, by Race
30
35
40
45
50
55
4681012
Age
Score Percentile
Hispanic Black White
Figure 10
Children of NLSY
A. Residualized Average Anti-Social Score Percentile by Income Quartile*
20
25
30
35
40
45
50
55
60
4681012
Age
*Residualized on maternal education, maternal AFQT, broken home at
each age (we use AFQT corrected for the effect of schooling).
Score Percentile
Lowest Income Quartile Second Income Quartile Third Income Quartile Highest Income Quartile
B. Residualized Average Anti-Social Score Percentile by Income Quartile*
Whites Only
25
30
35
40
45
50
55
60
65
4681012
Age
*Residualized on maternal education, maternal AFQT and broken home at each age (we use AFQT
corrected for the effect of schooling).
Score Percentile
Lowest Income Quartile Second Income Quartile Third Income Quartile Highest Income Quartile
C. Residualized Average Anti-Social Score Percentile by Race*
30
35
40
45
50
55
4681012
Age
*Residualized on maternal education, maternal AFQT, family income at each age and broken home at
each age (we use AFQT corrected for the effect of schooling).
Score Percentile
Hispanic Black White
Figure 11
Children of NLSY
GED Recipients and High School Graduates with Twelve Years of Schooling
Figure 12
Density of Age Adjusted AFQT Scores,
Black Males
0
5
10
15
20
25
30
35
-2.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5 2 2.5
White Males
0
5
10
15
20
25
30
-2.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5 2 2.5
White Females
0
5
10
15
20
25
30
35
-2.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5 2 2
HS graduates
GEDs
Hispanic Males
0
5
10
15
20
25
30
-2.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5 2 2.5
Hispanic Females
0
5
10
15
20
25
30
35
-2.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5 2
2
Black Females
0
5
10
15
20
25
30
35
40
-2.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5
Source: Heckman, Hsee and Rubinstein (2002)
Figure 13
Density of Gross Lifetime Earnings Differences (College-High School)
Earnings Differences (1000's)
Density(Earnings Differences)
High School*
College**
-500 0 500 1000 1500 2000
0
0.2
0.4
0.6
0.8
1
1.2
1.4
x 10
-3
*E(PV
c
-PV
h
|Choice=High School)
**E(PV
c
-PV
h
|Choice=College)
Source: Carneiro, Hansen and Heckman (2003)
All densities are estimated using a 100 point grid over the domain and a Gaussian kernel with bandwidth of 0.12.
Figure 14
Density of Lifetime E arnings Differences (C ollege-High S chool)
Under Different Information Sets
Density(E arnings Differences)
E arnings Differences (1000's)
Using all predictors**
Using no predictors*
Source: Carneiro, Hansen and Heckman (2003)
*mean=$412.71
**mean=$361.41
-500 0 500 1000 1500 2000
0
0.5
1
1.5
x 10
-3
All densities are estimated us ing a 100 point grid over the domain and a G auss ian kernel with bandwidth of 0.12.
Table 4
Annualized Returns to College for High School and Beyond W hite Males
†
High Ability Low Ability
Average Returns in the Population 0.1985 0.1765
(Average Treatmen t Eect)
Returns to Persons Who Attend College 0.3157 0.2700
(Treatment on the Treated)
Returns to Marginal Person* 0.2865 0.1974
Notes:
†
We us e wages i n year 1991. TT is Treatment on the Treated. We proceed in several steps. First we estimate
the Marg ina l Treatment Eect (MTE). Then we estimate the weights for TT and apply them to the MTE to get the
treatme nt pa ram eters. We ap p ly an an alogous meth od to get the ATE. See C arn eiro, H eckman a nd Vytlacil (2 00 1).
High ab ili ty ind ivid u als have m a th test scores a bove 4000. They co m pri se ap proxim ately 3 0% of the overall pop ul atio n
of white m ales. The average score in the population is 3325 and the standard devi atio n is 9 86. Low ab il ity individual s
are below the 4000 thresh ol d. They co mprise the remaini ng 7 0%. Col lege graduates have ap proxima tely 3.1 years of
scho oling more than high school graduates. This is the number we use to annualize the returns.
*Th is is a weighted average of returns to persons in high school at the marg in o f atten ding college. Fo r detai ls see
Carneiro , Heckman a nd Vytlacil (2001).
Table 5
Evaluating School Quality Policies: Discoun t ed Net Returns to Decreasing
Pupil-Teacher Ratio by 5 for People with 12 Years of Sc hooling in 1990
Annual Rate of Return
Productivit y Includes 50% to Earnings from
Growth Social Cost School Quality Change
Rate of Funds 1% 2% 4%
7% Discount Rate
0% Yes -9056 -8092 -6163
0% No -5716 -4752 -2823
1% Yes -8878 -7736 -5451
1% No -5538 -4396 -2111
5% Discount Rate
0% Yes -9255 -7537 -4103
0% No -5597 -3880 -445
1% Yes -8887 -6802 -2632
1% No -5230 -3145 1025
3% Discount Rate
0% Yes -8840 -5591 905
0% No -4810 -1562 4934
1% Yes -8036 -3984 4119
1% No -4007 45 8149
Notes: All val ues , in 1990 d ol lars , are given a s net pre sent values at age 6 of a n
individual;costsofschoolingimprovementsareincurredbetweenages6to18and
benefits from increas ed ea rni ng s occu r between ag es 19 and 65. Data for co sts are
from NCE S (19 93). C osts of add in g new teachers inclu de sa laries an d ca pi tal,
adm in is trative a nd maintenanc e expen ditures. Estimates of the increases in earning s
resulting from a decrease in the pupil-teacher ratio by 5 come from Card and
Krueger (1992), Table 3, wh ich p rodu ces a range of e stim ated earnin gs increases
from abou t 1% to 4% whereas most of the estimates are in the 1-2 % ra ng e. To
capture the b enefits of s malle r clas s sizes, students must attend 12 years of h ighe r
quality of schooling. We calculate the costs for one year of imp rove m ents an d then
calculate the present value of the costs over the 12 years of school attendance.
Ta b l e 6
E¤ects of Early Intervention Programs
Program/Study Costs
¤
Program Description Test Scores Schooling Pre-Delinquency
Crime
Abecedarian full-time year round classes high scores at 34% less grade retention by
Project
¤¤
for children from infancy ages 1-4 2nd grade; better reading and
(Ramey, et. al, 1988) through preschool math pro…ciency
part-time classes for
Early Training
¤¤
children in summer; weekly higher scores at 16% less grade retention;
(Gray et al., 1982) home visits during school ages 5-10 21% higher HS grad.rates
year
Harlem Study individual teacher-child higher scores at 21% less grade retention
(Palmer, 1983) sessions twice-weekly for ages 3-5
young males
home visits for parents for rated less aggressive
Houston PCDC
¤¤
2 yrs; child nursery care 4 higher scores at and hostile by mothers
(Johnson, 1988) days/wk in year 2 age 3 (ages 8-11)
(Mexican Americans)
full-time year-round classes
Milwaukee Project
¤¤
for children through 1st higher scores at
(Garber, 1988) grade; job training for ages 2-10 27% less grade retention
mothers
N/A
N/A
N/A
N/A
N/A
Program/Study Costs
¤
Program Description Test Scores Schooling Pre-Delinquency
Crime
Mother-Child Home
Program home visits with mothers higher scores at 6% less grade retention
(Levenstein, O’Hara, and children twice weekly ages 3-4
& Madden, 1983)
Perry Preschool
Program
¤¤
weekly home visits with 2.3 vs. 4.6 lifetime
(Schweinhart, $13,400 parents; intensive, high higher scores in 21% less grade retention or arrests by age 27
Barnes, & Weikart, quality preschool services all studied years special services; 21% 7% vs. 35% arrested
1993) for 1-2 years (ages 5-27) higher HS grad. rates 5 or more times
Rome Head Start $5,400 part-time classes for 12% less grade retention;
(Monroe & (2 yrs) children; parent 17% higher HS grad. rates
McDonald, 1981) involvement
Syracuse University 6% vs. 22% had
Family Development $38,100 weekly home visits for higher scores at probation …les;
(Lally et al., 1988) family; day care year round ages 3-4 o¤enses were less
severe
better-school attendance & rated less aggressive
family support; home visits better language adjustment; fewer special & pre-delinquent by
Yale Experiment $23,300 and day care as needed for development at adjustment; school services teachers and parents
30 months 30 months (age 12 1/2) (ages 12 1/2)
Notes: All comparisons are for program participants vs. non-participants. * Costs valued in 1990 dollars. ** Studies used a random assignment
experimental design to determine program impacts. Data from Donohue and Siegelman (1998), Schweinhart, Barnes, and Weikart (1993),
and Seitz (1990) for the impacts reported here. Source: Heckman, Lochner, Smith, and Taber (1997).
N/A
Table 6 (continued)
Table 7
Perry Presc h ool: Net Present Values of Costs & Benefits through Age 27
1. Cost of Preschool, Child Ages 3 to 4 $12148
2. Decrease in Cost to Government of K-12
Special Education Courses for Child, Ages 5 to 18 6365
3. Decrease in Direct Criminal Justice System Costs
+
of Child’s Criminal Activity, Ages 15 to 28 7378
4. Decrease in Direct Criminal Justice System Costs
+
of Child’s Projected Criminal Activity, Ages 29 to 44 2817
5. Income from Child’s Increased
Employment , Ages 19 to 27 8380
6. Projected Income from Child’s
Increased Employment, Ages 28 to 65 7565
7. Decrease in Tangible Losses to Crime
Victims, Ages 15 to 44 10690
Total Benefits: 43195
Total Benefits Excluding Projections
32813
Benefits minus Cost 31047
Benefits minus Cost Excluding Projections
20665
Notes:
All values are net present values in 1996 dollars at age 0
calculated using a 4% discount rate.
+
Direct Criminal Justice System
costs are the administrativ e costs of incarceration.
Benefits from
projected criminal activity (4) and projected income from increased
employment (6) are excluded. Sources: Karoly et al. (1998) and Barnett (1993).
Table 8
Outcomes of Early Intervention Programs
Followed Up Age When Treatment Eect Control Change in
Program (Years of Operation) Outcome to Age Last Statistically Significant Group Treated Group
C
ognitive Measures
Early Training Project (1962 - 1965) IQ 16-20 6 82.8 +12.2
P erry Preschool Project (1962 - 1967) IQ 27 7 87.1 +4.0
Houston PCDC (1970 - 1980) IQ 8-11 2 90.8 +8.0
Syracuse FDRP (1969 - 1970) IQ 15 3 90.6 +19.7
Carolina Abecedarian (1972 - 1985) IQ 21 12 88.4 +5.3
Project CARE (1978 - 1984) IQ 4.5 3 92.6 +11.6
IHDP (1985 - 1988 ) IQ (HLBW sample) 8 8 92.1 +4.4
E
ducational Outcomes
Early Training Project Special Education 16-20 18 29% -26%
P erry Preschool Project Special Education 27 19 28% -12%
High School Graduation 27 45% +21%
Chicago CPC (1967 - present) Special Education 20 18 25 % -10%
Grade Retention 15 38% -15%
High School Graduation 20 39% +11%
Carolina Abecedarian College Enrollment 21 21 14% +22%
E
conomic Outcomes
P erry Preschool Project Arrest Rate 27 27 69% -12%
Employment Rate 27 32% +18%
Monthly Earnings 27 $766 + $453
Welfare Use 27 32% -17%
Chicago CPC (preschool vs. no preschool) Juvenile Arrests 20 18 25% -8%
Syracuse FDRP Probation Referral 15 15 22% -16%
Elmira PEIP (1978 - 1982) Arrests (HR sample) 15 15 0.53 -.029
N
otes: HLBW = heavier, low birth weight sample; HR = high risk. Cognitive measures include Stanford-Binet and Weshler Intelligence Scales, California
A
chievement Tests, and other IQ and achievement tests measuring cognitive ability. All results significant at .05 level or higher. Source: Karoly, 2001.
F
or a discussion of the specific treatments oered under each program see Heck man (2000) and Karoly (2001).
Table 9
Estimated Benefits of Mentoring Programs (Treatment Group Reductions Compared to Control Group)
Program Outcome Measure Change Program Costs per Participant
Big Brother / Big Sister $500 - $1500*
Initiating drug use -45.8%
Initiation alcohol use -27.4%
# of times hit someone -31.7%
# of times stole something -19.2%
Grade Point Average 3.0%
Skipped Class -36.7%
Skipped Day of School -52.2%
Trust in Parent 2.7%
Lying to Parent -36.6%
Peer Emotional Support 2.3%
Sponsor - A - Sch olar $1485
10th Grade GPA (100 point scale) 2.9
11th Grade GPA (100 point scale) 2.5
% Attending College (1 year after HS) 32.8%
% Attending College (2 years after HS) 28.1%
Quantum Opportunity Program
Graduated HS or GED +26%
Enrolled in 4-year college +15%
Enrolled in 2-year college +24%
Curren tly employed full time +13%
Self receiving welfare -22%
% ever arrested -4%
Sources: Benefits from Heckman (1999) and Taggart (1995), costs from Johnson (1996) and Herrera et al. (2000).
Notes: *Costs, in 1996 dollars, for school-based programs are as low as $500 and more expensive
community based mentoring programs cost as high as $1500; HS = high school
Table 10
E¤ects of Selected Adolescent Social Programs on Schooling, Earnings, and Crime
Program/Study Costs
¤
Program Description Schooling Earnings
¤
Crime
¤
disc. pres.
7 mo. of educ. value of Estimated
Job Corps and vocational training for no e¤ect increased Reduction in crime
(Long et al., 1981) $11,000 16-21 yr. olds earnings of valued at approx.
(mostly male) $10,000
2 summers of short-run gains
employment, academic in test scores; no
STEP remediation & life e¤ect on school
(Walker and skills for 14 & 15 completion rates
Viella-Velez, 1992) year olds
4% vs. 16%
Quantum Opportunities counseling; educ., comm., 34% higher HS convicted; .28 vs.
Program
¤¤
$10,600 & devp. services; grad./GED rates .56 avg. number of
(Taggart, 1995) …nancial incentives for part. (4 yrs. (2 yrs. post-program) arrests (2 yrs. post-
beginning in program)
9th grade)
N/A
Table 11
RatesofReturnonInvestment
in Private Job Training
Data Set: Return
PSID, all males 2 3.5
NLS 16.0
N LS (Old NLS) 2 6.0
Source: Mincer (19 93 )
Table 12
Av erage Marginal Eect on P articipation in Com pany Training
Av erage Marginal Eect
Varia b le s White Males Black Males Hispanic Males
(1)(2)(1)(2)(1) (2)
Age-Adjusted AFQT 0.0149 - 0.0182 - 0.0066 -
(0=0024) - (0=0033) - (0=0037) -
Family Income in 1979 -0.0021 -0.0005 -0.0047 -0.0019 0.0011 0.0015
(in $10,000) (0=0012) (0=0011) (0=0024) (0=0023) (0=0024) (0=0023)
Grade Completed 0.0382 - 0.0060 - 0.0036 -
(0=001) - (0=0014) - (0=0014) -
Father’s Education -0.0014 0.0007 0.0003 0.0010 0.0002 0.0008
(0=0006) (0=0005) (0=0008) (0=0008) (0=0007) (0=0007)
Variables White Females Black Females Hispanic Females
(1)(2)(1)(2)(1) (2)
Age-Adjusted AFQT 0.0076 - 0.0169 - 0.0159 -
(0=0025) - (0=0038) - (0=0045) -
Family Income in 1979 -0.0007 0.0001 -0.0006 0.0014 -0.0065 -0.0043
(in $10,000) (0=0011) (0=0011) (0=0024) (0=0023) (0=0031) (0=0029)
Grade Completed 0.0027 - 0.0014 - 0.0013 -
(0=0010) - (0=0016) - (0=0016) -
Father’s Education 0.0001 0.0009 0.0015 0.0021 -0.00001 0.0007
(0=0006) (0=0006) (0=0008) (0=0008) (0=0009) (0=0008)
Notes: The panel data set was constructed usin g NLSY79 data from 1979-199 4. Da ta on training in 1987 is
combined with 1988 in the ori gin al data set. Com p any training consists of form al trainin g run by e m ployer,
and military training e xcl ud ing basic training. Stan da rd errors are reported in parentheses.
Specification (1) includes a constant, ag e, father’s education, moth er’s education, number of si bl in gs,
southern residence at age 14 dummy, urban residen ce at age 14 dummy, and year dummies.
Specification (2) d rop s age-adj u sted AFQT a nd grad e comp le ted. Average m arginal eec t is
estima te d using average deriva tives f rom a probit regress ion .
Table 13
Eects of Accounting for Discounting, Expected Horizon and Welfare Costs of Taxes:
Benefit Minus Cost Estimates for JTPA under Alternative Assumptions
Regarding Benefit Persistence, Discounting, and Welfare Costs of Taxation
(National JTPA Study, 30-Month Impact Sample)
Direct 6-Mon th Welfare
Benefit Costs Interest Cost of Adult Adult Male Female
Duration Included? Rate Taxes Males Females Youth Youth
30 Months No 0.000 0.00 1,345 1,703 -967 136
30 Months Yes 0.000 0.00 523 532 -2,922 -1,180
30 Months Yes 0.000 0.50 108 -54 -3,900 -1,838
30 Months Yes 0.025 0.00 433 432 -2,859 -1,195
30 Months Yes 0.025 0.50 17 -154 -3,836 -1,853
7 Years No 0.000 0.00 5,206 5,515 -3843 865
7 Years Yes 0.000 0.00 4,375 4,344 -5,798 -451
7 Years Yes 0.000 0.50 3,960 3,758 -6,775 1,109
7 Years Yes 0.025 0.00 3,523 3,490 -5,166 -610
7 Years Yes 0.025 0.50 3,108 2,905 -6,143 -1,268
Notes: (1) “Benefit D uration” indicates how long the estimated b e nefits from JTPA are a ssumed
to persist. A ctual e stimates are use d for the first 30 months. For t he 7-year duration case, the average of
the b enefits in m onths 18-24 and 25-30 is used for the b enefits in each future p eriod.
(2) “Welfare C ost of Tax es” indicates th e additional cost in terms of lost output due to each a dditional
dollar of taxe s raised. T he value 0.50 lies in the range suggested by B rowning (1987).
(3) Estimates are constructed by break ing up the time after random assignment into 6-m onth periods.
Allcostsareassumedtobepaidinthefirst 6-month p eri od, wh i le be n efits are rece ived in each
6-month period and discounted by the am ount indicated for each row of t he table.
Source: Heckman and Sm ith (199 8)
Programmes Appears to help Appears not to help General observations on
effectiveness
Formal classroom
training
Women re-entrants Prime-age men and older
workers with low initial
education
Important that courses have strong
labour market relevance, or signal
“high” quality to employers.
Should lead to a qualification that is
recognised and valued by
employers.
Keep programmes relatively small
in scale.
On-the-job training Women re-entrants; single
mothers
Prime-age men (?) Must directly meet labour market
needs. Hence, need to establish
strong links with local employers,
but this increases the risk of
displacement.
Job-search
assistance (job
clubs, individual
counselling, etc.)
Most unemployed but in
particular, women and
sole parents
Must be combined with increased
monitoring of the job-search
behaviour of the unemployed and
enforcement of work tests.
Of which:
re-
employment
bonuses
Most adult unemployed Requires careful monitoring and
controls on both recipients and their
former employers.
Special youth
measures (training,
employment
subsidies, direct job
creation measures)
Disadvantaged youths Effective programmes need to
combine an appropriate and
integrated mix of education,
occupational skills, work-based
learning and supportive services to
young people and their families.
Early and sustained interventions
are likely to be most effective.
Need to deal with inappropriate
attitudes to work on the part of
youths. Adult mentors can help.
Subsidies to
employment
Long-term unemployed;
women re-entrants
Require careful targeting and
adequate controls to maximise net
employment gains, but there is a
trade-off with employer take-up.
Of which:
Aid to
unemployed
starting
enterprises
Men (below 40, relatively
better educated)
Only works for a small subset of the
population.
Direct job creation Most adult and youth
unemployed
Typically provides few long-run
benefits and principle of
additionality usually implies low
marginal-product jobs.
Source
: Martin and Grubb, 2001
Lessons from the Evaluation Literature
Table 14
Table 15
Benefits and Costs of Job Corps from Different Perspectives
Perspective
Benefits or Costs Society P articipants Rest of Society
(1) Year 1 -1,933 -1,621 -313
(2) Years 2-4 2,462 1,626 836
(3) After Observation Period 26,678 17,768 9,009
Output Produced during
Vocational Training in Job Corps. 225 0 225
Benefits from Increased Output 27,531 17,773 9,758
Benefits from Increased Output
Excluding Extrapolation Beyond Observation 754 5 749
Benefits from Reduced Use of Other
Programs and Services 2,186 -780 2,966
Benefits from Reduced Crime 1,240 643 597
Program Costs -14,128 2,361 -16,489
(1) Benefits Minus Costs 16829 19,997 -3,168
(2) Benefits Minus Costs Excluding
Extrapolation Beyond Observation -9,949 2,229 -12,177
Net Benefits per Dollar of Program Expenditures
1
2.02
Net Benefits per Dollar of Program Expenditures
Excluding Extrapolation Beyond Observation
1
0.40
Notes: All figures in 1995 dollars.
1
The ratio’s denominator is the operating cost of the program ($16,489). The ratio’s numerator
is the benefit to society plus the cost of student pay, food and clothing ($2,361). The cost of student pay, food and clothing is
included to oset the fact that it is included in the denominator even though it is not a cost to society.
Source: Glazerman, Schocket and Burghart, 2001 National Job Corps Study: The Impact of Job Corps. on Participants’ Employment and Related Outcomes.
-5 -4 -3 -2 -1 0 1 2 3 4 5
-0.4
-0.2
0
0.2
0.4
0.6
0.8
Average
Marginal
Return
a
Notes:
a
Average marginal return to persons at the margin of attending college for a given level of index
b
Variables related to schooling (higher level of index leads to a higher probability of attending
college)
Source: Carneiro, Hansen, and Heckman (2001)
Figure 15
Annualized Average Marginal Return for Those at the Margin
of Indifference Between College and High School
NLSY79, White Males
Average Marginal Return
Confidence Interval
Index of Factors Promoting College Attendance
b
DEGREES, DIPLOMAS, AND CERTIFICATES RECEIVED
47.3
41.6
5.3
37.5
1.3
34.4
26.6
7.5
15.2
1.5
GED or
High School
Diploma
GED High School
Diploma
Vocational
Certificate*
Two-Year or
Four-Year
Degree
0
10
20
30
40
50
60
Percentage Ever Received Credential During the 48-Month Period
Program Group Control Group
a
*
a
*
a
*
Job Corps. Evaluation
Figure 16
Source: Baseline and 12- , 30- , and 48-month follow-up interview data for those who completed 48-month interviews.
a
Figures pertain to those who did not have a high school credential at random assignment.
*Difference between the mean outcome for program and control group members is statistically significant
at the 5 percent level. This difference is the estimated impact per eligible applicant.
See Schochet et alt., 2001
Figure 17
Trends in Unhealthy Child Environments
0
5
10
15
20
25
30
35
40
45
50
1940
1942
1944
1946
1948
1950
1952
1954
1956
1958
1960
1962
1964
1966
1968
1970
1972
1974
1976
1978
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
Year
% of All Births to Unmarried Women 15-44 Birth rate for 1000 Unmarried Women 15-44
Birth Rate per 1000 Unmarried Women 15-19 % of All Children Under 18 Living W/ 1 Parent
% of All Children Under 18 Living in Poverty
Data for births and birth rates are from Ventura and Bachrach (2000). Data for children living with one parent are available at the census bureau at
http://www.census.gov/population/socdemo/hh-fam/tabCH-1.txt. Data for children living in poverty is available at www.childtrendsdatabank.org/
Appendix A
Figure A-1
Prototypical Payoff Streams
Periods
Dollars
0 5 10 15 20 25 30 35 40 45
15
10
5
0
5
10
15
Job Training
Preschool
Table B-1
NLSY79 White Males - Gaps in Enrollment, Completion, Delay, Type of College
(Measured from the Highest Income Quartile) Conditioning on Parental Education,
Number of Siblings, Broken Home, South, and Urban
AFQT Tercile 1 AFQT Tercile 2 AFQT Tercile 3 Not Conditioning on AFQT
Beta Std. Err. t-stat Beta Std. Err. t-stat Beta Std. Err. t-stat Beta Std. Err. t-stat
Panel A - Enrollment in College
q4-q1 0.1178 0.0718 1.64 0.0807 0.0687 1.18 0.0366 0.0679 0.54 0.1054 0.0374 2.81
q4-q2 0.0808 0.0671 1.20 0.0584 0.0580 1.01 0.0398 0.0568 0.70 0.0782 0.0332 2.36
q4-q3 0.0870 0.0663 1.31 0.0126 0.0511 0.25 0.0966 0.0519 1.86 0.0678 0.0309 2.19
All Gaps = 0 F(3,454) = 0.94 F(3,499) = 0.65 F(3,491) = 1.18 F(3,1606) = 3.09
Panel B - Complete 4-Year College
q4-q1 -0.2815 0.1439 -1.96 0.0703 0.1123 0.63 -0.0379 0.0906 -0.42 -0.0076 0.0618 -0.12
q4-q2 -0.2943 0.1416 -2.08 0.0714 0.0885 0.81 0.0316 0.0712 0.44 0.0265 0.0512 0.52
q4-q3 -0.1918 0.1377 -1.39 -0.0658 0.0719 -0.92 0.0681 0.0638 1.07 -0.0215 0.0453 -0.47
All Gaps = 0 F(3,100) = 1.75 F(3,252) = 1.08 F(3,272) = 0.65 F(3,692) = 0.30
Panel C - Complete 2-Year College
q4-q1 0.5377 0.3541 1.52 0.0520 0.1713 0.30 0.0584 0.0665 0.88 0.0891 0.0967 0.92
q4-q2 0.2472 0.2339 1.06 0.1164 0.1449 0.80 0.0348 0.0546 0.64 0.0290 0.0802 0.36
q4-q3 0.0983 0.2242 0.44 -0.0716 0.1382 -0.52 -0.0399 0.0533 -0.75 -0.1358 0.0760 -1.79
All Gaps = 0 F(3,41) = 1.01 F(3,68) = 0.57 F(3,76) = 0.86 F(3,219) = 2.66
Panel D - Proportion of People not Delaying College Entry
q4-q1 0.1637 0.2111 0.78 -0.0375 0.1537 -0.24 -0.1483 0.1316 -1.13 0.0039 0.0874 0.04
q4-q2 0.4207 0.1931 2.18 0.0616 0.1091 0.56 0.0786 0.0917 0.86 0.1668 0.0655 2.55
q4-q3 0.3717 0.1907 1.95 -0.0596 0.0890 -0.67 0.0525 0.0925 0.57 0.0492 0.0599 0.82
All Gaps = 0 F(3,54) = 1.98 F(3,123) = 0.50 F(3,135) = 1.17 F(3,349) = 2.53
Panel E - Enrollment in 4-Year vs. 2-Year College
q4-q1 0.0400 0.1264 0.32 0.0089 0.0806 0.11 0.1103 0.0764 1.44 0.0272 0.0483 0.56
q4-q2 0.2185 0.1119 1.95 0.0448 0.0662 0.68 0.1169 0.0607 1.92 0.0654 0.0400 1.64
q4-q3 0.2700 0.1072 2.52 -0.0361 0.0556 -0.65 0.0197 0.0563 0.35 0.0278 0.0361 0.77
All Gaps = 0 F(3,150) = 3.01 F(3,329) = 0.53 F(3,357) = 1.60 F(3,920) = 0.90
Within each AFQT Tertile we regress college enrollment (completion, delay, type of college) on family background and indicator
variables for each income quartile.
q4-q1 —Gap in enrollment between quartiles 4 and 1
q4-q2 —Gap in enrollment between quartiles 4 and 2
q4-q3 —Gap in enrollment between quartiles 4 and 3
Notes: All gaps are measured relative to the highest income group within each ability class. Each of the Þrst three columns
in these tables represents a di erent AFQT tercile. The last column groups all test score terciles in one group. Each of the
Þrst three rows corresponds to a di erent comparison between two income quartiles. The baseline quartile is the richest.
In the column with the title ’not conditioning on ability’ we compute gaps in college enrollment (completion, delay,
type of college) for the whole population, without dividing it into di erent AFQT tertiles. Ex: The gap in college enrollment
between the lowest and the highest income quartile within the highest AFQT tercile is 0.037.
Source: Carneiro and Heckman (2002)'
Appendix B
Table B-2
Family Bac kground Gaps for White Males, NLSY79
(Measured Relative to the Highest Family Background/AFQ T Quartile)
Enrollment in College 2-Year College Com pletion
Gap: Coe!cient Std. Err. w-stat Coe!cient Std. Err. w-stat
q4-q1 0.580 0.042 13.810 -0.374 0.154 -2.429
q4-q2 0.370 0.034 10.882 -0.189 0.077 -2.455
q4-q3 0.299 0.029 10.310 -0.124 -0.067 -1.851
4-Year College Completion Percentage with No Delay of Entry
Coe!cient Std. Err. w-stat Coe!cient Std. Err. w-stat
q4-q1 0.615 0.108 5.694 0.499 0.159 3.138
q4-q2 0.337 0.060 5.617 0.188 0.075 2.507
q4-q3 0.137 0.043 3.186 0.099 0.056 1.768
Yea rs of Delay Enrollment in 4-Year vs. 2-Year College
Coe!cient Std. Err. w-stat Coe!cient Std. Err. w-stat
q4-q1 -2.793 0.817 -3.419 0.040 0.084 0.476
q4-q2 -1.301 0.387 -3.362 0.133 0.045 2.956
q4-q3 -0.627 0.286 -2.192 0.054 0.034 1.588
Variable: Coefficient Std. Err.
t- stat
Coefficient Std. Err.
t- stat
Coefficient Std. Err.
t- stat
q1-q4 -0.118 0.072 -1.640 -0.081 0.069 -1.180 -0.037 0.068 -0.540
q2-q4 -0.081 0.067 -1.200 -0.058 0.058 -1.010 -0.040 0.057 -0.700
q3-q4 -0.087 0.066 -1.310 -0.013 0.051 -0.250 -0.097 0.052 -1.860
Southern Residence at Age 14 -0.012 0.047 -0.260 -0.006 0.047 -0.130 0.070 0.049 1.430
Broken Home -0.076 0.051 -1.500 0.002 0.060 0.040 -0.069 0.057 -1.200
Urban Residence at Age 14 0.054 0.048 1.120 0.042 0.048 0.870 -0.013 0.047 -0.280
Mother's Education 0.024 0.011 2.310 0.035 0.011 3.150 0.023 0.011 2.100
Father's Education 0.029 0.008 3.640 0.042 0.008 5.390 0.042 0.008 5.160
Constant -0.213 0.138 -1.550 -0.347 0.136 -2.550 -0.133 0.137 -0.970
Variable: Coefficient Std. Err.
t- stat
Coefficient Std. Err.
t- stat
Coefficient Std. Err.
t- stat
q1-q4 -0.538 0.354 -1.520 -0.052 0.171 -0.300 -0.058 0.066 -0.880
q2-q4 -0.247 0.234 -1.060 -0.116 0.145 -0.800 -0.035 0.055 -0.640
q3-q4 -0.098 0.224 -0.440 0.072 0.138 0.520 0.040 0.053 0.750
Southern Residence at Age 14 0.010 0.204 0.050 -0.156 0.119 -1.310 0.046 0.050 0.900
Broken Home -0.188 0.268 -0.700 -0.057 0.154 -0.370 0.240 0.056 4.320
Urban Residence at Age 14 -0.084 0.182 -0.460 -0.247 0.139 -1.770 -0.036 0.045 -0.790
Mother's Education -0.067 0.053 -1.270 0.020 0.028 0.720 -0.012 0.012 -0.990
Father's Education 0.007 0.038 0.190 0.012 0.021 0.570 0.010 0.010 1.090
Constant 1.510 0.618 2.450 0.133 0.340 0.390 0.040 0.136 0.290
Variable: Coefficient Std. Err.
t- stat
Coefficient Std. Err.
t- stat
Coefficient Std. Err.
t- stat
q1-q4 0.281 0.144 1.960 -0.070 0.112 -0.630 0.038 0.091 0.420
q2-q4 0.294 0.142 2.080 -0.071 0.088 -0.810 -0.032 0.071 -0.440
q3-q4 0.192 0.138 1.390 0.066 0.072 0.920 -0.068 0.064 -1.070
Southern Residence at Age 14 -0.040 0.107 -0.370 0.008 0.074 0.110 0.015 0.060 0.240
Broken Home -0.186 0.120 -1.550 0.091 0.100 0.910 0.008 0.077 0.110
Urban Residence at Age 14 0.004 0.128 0.030 0.121 0.075 1.610 0.007 0.061 0.120
Mother's Education 0.029 0.023 1.230 0.027 0.017 1.610 0.017 0.013 1.320
Father's Education 0.035 0.018 1.960 0.026 0.012 2.260 0.015 0.009 1.640
Constan
t
-0.584 0.378 -1.550 -0.223 0.214 -1.050 0.338 0.169 2.000
Lowest AFQT Tertile Middle AFQT Tertile Highest AFQT Tertile
Lowest AFQT Tertile Middle AFQT Tertile Highest AFQT Tertile
Panel B - 2-Year College Completion Rate
Table B-3
Gaps in Enrollment, Completion, Delay, Type of College
White Males, NLSY79
(Measured from Highest Family Background / AFQT Quartile)
Panel A - Enrollment in College
Lowest AFQT Tertile Middle AFQT Tertile Highest AFQT Tertile
Panel C - 4-Year College Completion Rate
Variable: Coefficient Std. Err.
t- stat
Coefficient Std. Err.
t- stat
Coefficient Std. Err.
t- stat
q1-q4 -0.164 0.211 -0.780 0.038 0.154 0.240 0.148 0.132 1.130
q2-q4 -0.421 0.193 -2.180 -0.062 0.109 -0.560 -0.079 0.092 -0.860
q3-q4 -0.372 0.191 -1.950 0.060 0.089 0.670 -0.053 0.093 -0.570
Southern Residence at Age 14 0.209 0.145 1.440 0.023 0.092 0.250 -0.090 0.086 -1.040
Broken Home 0.023 0.185 0.120 0.117 0.119 0.980 -0.242 0.095 -2.540
Urban Residence at Age 14 -0.180 0.152 -1.190 0.142 0.096 1.480 0.009 0.080 0.110
Mother's Education 0.056 0.030 1.860 0.022 0.024 0.930 0.025 0.020 1.280
Father's Education -0.028 0.027 -1.030 0.013 0.015 0.870 0.010 0.014 0.680
Constant 0.511 0.488 1.050 0.151 0.289 0.520 0.371 0.258 1.440
Variable: Coefficient Std. Err.
t- stat
Coefficient Std. Err.
t- stat
Coefficient Std. Err.
t- stat
q1-q4 -0.629 1.418 -0.440 0.851 0.781 1.090 0.106 0.555 0.190
q2-q4 1.652 1.298 1.270 1.258 0.554 2.270 0.747 0.386 1.930
q3-q4 0.781 1.281 0.610 0.299 0.452 0.660 0.302 0.390 0.770
Southern Residence at Age 14 -1.559 0.976 -1.600 -0.403 0.467 -0.860 0.332 0.364 0.910
Broken Home 1.158 1.245 0.930 -0.370 0.605 -0.610 0.146 0.401 0.360
Urban Residence at Age 14 -1.050 1.019 -1.030 -0.054 0.489 -0.110 -0.057 0.335 -0.170
Mother's Education -0.363 0.203 -1.790 -0.061 0.122 -0.490 -0.157 0.084 -1.870
Father's Education 0.149 0.182 0.820 -0.035 0.078 -0.450 -0.022 0.060 -0.370
Constant 5.242 3.277 1.600 1.847 1.467 1.260 2.776 1.088 2.550
Variable: Coefficient Std. Err.
t- stat
Coefficient Std. Err.
t- stat
Coefficient Std. Err.
t- stat
q1-q4 -0.040 0.126 -0.320 -0.009 0.081 -0.110 -0.110 0.076 -1.440
q2-q4 -0.219 0.112 -1.950 -0.045 0.066 -0.680 -0.117 0.061 -1.920
q3-q4 -0.270 0.107 -2.520 0.036 0.056 0.650 -0.020 0.056 -0.350
Southern Residence at Age 14 0.044 0.089 0.490 -0.057 0.055 -1.030 0.014 0.052 0.260
Broken Home 0.103 0.104 0.990 -0.012 0.073 -0.170 -0.019 0.065 -0.290
Urban Residence at Age 14 0.128 0.096 1.330 -0.055 0.057 -0.960 -0.045 0.052 -0.850
Mother's Education -0.014 0.020 -0.700 0.027 0.012 2.210 0.025 0.011 2.170
Father's Education -0.007 0.015 -0.480 0.013 0.009 1.550 0.013 0.009 1.540
Constan
t
0.963 0.301 3.200 0.298 0.157 1.900 0.340 0.147 2.320
Lowest AFQT Tertile Middle AFQT Tertile Highest AFQT Tertile
Panel D - Percentage With No Delay of Entry
Table B-3 (continued)
Gaps in Enrollment, Completion, Delay, Type of College
White Males, NLSY79
(Measured from Highest Family Background / AFQT Quartile)
Lowest AFQT Tertile Middle AFQT Tertile Highest AFQT Tertile
Panel E - Years of Delay of Entry
Lowest AFQT Tertile Middle AFQT Tertile Highest AFQT Tertile
Panel F - Type of School
Table B-4
Coe!cients for the Construction of the Family Background Index
Regression of College Enrollment on South ern and Urban Origin,
Brok enHome, and Paren tal Education, White Males, NLSY79
Variable: Coe!cient Std. Err.
Southern Origin 0.0266 0.0233
Broken Home -0.0544 0.0270
Urban Origin 0.0603 0.0235
Mother’s Education 0.0310 0.0054
Father’s Education 0.0400 0.0033
AF QT 0.0046 0.0006
Constant -0.6814 0.0538
