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U N I V E R S I D A D D E C H I L E F A C U L T A D D E E C O N O M I A Y N E G O C I O S

E S T U D I O S D E E C O N O M I AV O L U M E N 38 - N 1 ISSN 0304-2758 JUNIO 2011

Introduction to the issueDavid Bravo 5

ARTCULOS

How much might human capital policies affect earnings inequalities and poverty?Jere R. Behrman 9

The impact of income adjustments in the Casen Survey on the measurement ofinequality in ChileDavid Bravo, Jos Valderrama 43

The longer-term effects of human capital enrichment programs on poverty and inequality:Oportunidades in MexicoDouglas McKee, Petra E.Todd 67

Alleviating extreme poverty in Chile: the short term effects of Chile SolidarioEmanuela Galasso 101

Evaluating the Chile Solidario program: results using the Chile Solidario panel and theadministrative databases

Fernando Hoces de la Guardia, Andrs Hojman, Osvaldo Larraaga 129Top incomes in Chile using 50 years of household surveys: 1957-2007Claudia Sanhueza, Ricardo Mayer 169

Intergenerational income and educational mobility in urban ChileJavier Nez, Leslie Miranda 195

A cohort analysis of the income distribution in ChileClaudio Sapelli 223

Getting ahead, falling behind and standing still. Income mobility in ChileRodrigo Castro 243

Examinando la prominente posicin de Chile a nivel mundial en cuanto a desigualdad deingresos: comparaciones regionalesJuan Pablo Valenzuela, Suzanne Duryea 259

Estabilidad en la desigualdad. Chile 1990-2003Osvaldo Larraaga, Juan Pablo Valenzuela 295

Depar tamento de Economa

GUEST EDITOR:DAVID BRAVO (CENTRO DE MICRODATOS, UNIVERSIDAD DE CHILE)

SPONSORED BY:INTER-AMERICAN DEVELOPMENT BANK

INICIATIVA CIENTFICA MILENIOCENTRO DE MICRODATOS, UNIVERSIDAD DE CHILE

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Intuctn t the ssue /David Bravo 5

Estus e Ecnm. Vl. 38 - N 1, Jun 2011. Pgs. 5-7

Introduction to the issue

David Bravo*

Chle hs usully been cnsee ne f the utstnng cuntes n theWl n tems f ts ec n eucng pety. At the sme tme, ncme n-equality in Chile remains high by international standards; in fact, cross-country

cmpsns plces Chle mngst thse cuntes wth the hghest spesnf mnety ncme (Wl Bnk 1997, 2001; B n Cntes, 2004).

Ths lume gnte fm Wkshp n Incme Inequlty spnseby the Centro de Microdatos and the Inter-American Development Bank inDecembe 2006. Sme f the ppes n uths tht wee pt f ths semnsent updated versions of their pieces for a refereeing process. The papers of thislume ce we nge f pety n nequlty ssues.

Jere Behrman asks how much might Human Capital policies affect earningsnequltes n pety? It eews sme ecent beneft/cst estmtns fhuman capital intervention in Latin America and the Caribbean, suggesting some

investments in which the returns appear quite high. The contribution of schoolingattainment targeted to the poor in reducing poverty and income inequality is alsoepte n llustte usng Chlen t. Altente smultns suggest tBehrman significant impacts of well-targeted increases in schooling attainmentn eucng pety n nequlty.

Hw es the ncme stbutn f Chle cmpe wth the cuntes?On ths tpc D B n Js Vlem shw tht Chle s ne f thefew cuntes tht justs the nfmtn btne fm husehl sueys tmke the fgues cmptble wth Ntnl Accunts. Ths ppe shws thtths justment les t mptnt chnges n the tp-en f the stbutnn t n eestmtn n the mn nequlty ncts n Chle. Chle lksme unequl n ntentnl elte tems ue t ths justment. B nVlem use Peu n Chle t llustte the pnt. Jun Pbl Vlenzueln Suznne Duye cmpe the ncme stbutns f Chle n Uuguy.They shw tht Chle n 2003 h Gn Ceffcent 8.5 pnts hghe thnUuguy. Usng mcsmultns, they cnclue tht mst f the ffeencecmes fm the welthe husehl, ptcully thse belngng t the tp2%. Anthe fctn f the ffeences s explne by ffeences n etunst hghe euctn n bth cuntes. They ls emphsze tht the ntnl

ccunt justment n Chle s eestmtng the gp between the Gn ceff-cents f thse cuntes.

* Centro de Microdatos, Departamento de Economa, Universidad de Chile. E-mail: dbravo@

ecn.uchle.cl

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Estudios d Ecoo, Vol. 38 - N 110

destinados a reducir la pobreza y cmo una reduccin de la pobreza tiende a

reducir la desigualdad. En primer lugar, se presentan estimaciones de costo/

beneficio recientes de distintas intervenciones en capital humano en Amrica

Latina, sugiriendo que en algunas de estas inversiones los rendimientos parecen

bastante altos. Luego, se profundiza en cmo un aumento en la escolaridadde las personas en situacin de pobreza reducira los niveles de pobreza y la

desigualdad de ingresos. Para ilustrar empricamente este punto se utilizan

los datos de la ronda 2004 de la Encuesta de Proteccin Social de Chile.

Simulaciones alternativas sugieren un impacto significativo del aumento en

los aos de escolaridad, focalizados en personas pobres, en la reduccin de la

pobreza y la desigualdad.

Plbs clv:Desigualdad, Pobreza, Capital humano.

JEL Clssifictio:I24, I3, J24.

As is well-known, economic inequalit long has been relativel high in most

of Latin America and the Caribbean (LAC) in comparison with most other areas

of the world. These inequalities generall have persisted despite some variations

due to changes in political and polic regimes and markets and significant polic

iovtios i ct dcds i LAC coutis fo Cil to Mxico.

At t stt of t 1970s, fo xpl, LAC ico iqulit sud b

the income Gini coefficient ranged from a low of 0.43 in Argentina and Urugua,

to a high of 0.62 in Honduras (Table 1). Average income inequalit in the region

as a whole for this period was 0.53 compared with 0.36 for high-income OECD

coutis, d 0.43 fo Est Asi. Scoolig iqulit ws lso ig i Lti

America in the earl 1970s, with the schooling attainment Gini coefficients

vgig 0.46. T coutis wit t igst scoolig iqulit w lso

some of the poorest in the region (Guatemala, Honduras, Nicaragua and ElSlvdo). I cotst, Agti d Cil w wll blow t LAC vg

on both measures. The average LAC income Gini coefficient subsequentl

dclid to 0.50 i t l 1980s but icsd to bout 0.54 i 2000, toug

t Gii cofficit fo scoolig ttit std t bout 0.46 fo 1980 d

t dclid sowt to bout 0.42 i 2000.

Cocptull distict fo t qustio bout iqulit is t qustio of

povt. Most govts pofss itst i ducig povt d v

undertaken programs that purportedl are directed towards doing so. In the short

run, transfers to the poor are often thought to be among the more effective wasof ducig sot-u povt, toug suc tsfs igt b coditiol o

activities such as work in emploment programs in order to screen beneficiaries

o to liit gtiv ffcts o lbo supplis. I t log u, ivstts i

human resources of the poor are usuall thought to be among the most effective

was of reducing povert because the basic resource of the poor is their time and

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How uc igt u cpitl policis /Jere R. Behrman 11

TABLE

1

LACINCOMEANDSCHOO

LINGGINICOEFFICIENTSFO

REARLy1970s,EARLy1980sANDAROUND2000

Earl1970s

Earl1980s

1998-2000

IncomeGini

Coefficient1970

Sc

hoolingGini

Coefficient

(pe

opleover15)

1970

IncomeGini

Coefficient

1980-1985

SchoolingGini

Coefficient

(peopleover15)

1980

IncomeGini

Coefficient

1998-2000

Schoo

lingGini

Coe

fficient

(peopl

eover15)

2000

Argentina

0.49

0.29

0.4

1

0.29

0.52

0.27

Bolivia

0.46

0.52

n/a

0.52

0.63

0.47

Brazil

0.61

0.48

0.5

7

0.48

0.61

0.43

Chile

0.50

0.37

0.5

3

0.37

0.60

0.37

Colombia

0.57

0.47

0.5

3

0.47

0.57

0.48

CostaRica

0.52

0.40

0.4

8

0.40

0.50

0.42

Ecuador

n/a

0.39

0.4

4

0.39

0.56

0.43

ElSalvador

0.47

0.49

0.5

3

0.49

0.54

0.53

Guatemala

0.54

0.63

0.5

4

0.63

0.60

0.59

Honduras

0.62

0.57

0.5

7

0.57

0.53

0.43

Mexico

0.54

0.50

0.5

0

0.50

0.54

0.36

Nicaragua

n/a

0.62

n/a

0.62

0.56

0.52

Paragua

n/a

0.38

0.4

5

0.38

0.52

0.36

Peru

0.55

0.41

0.5

1

0.41

0.51

0.36

Urugua

0.43

0.36

0.4

4

0.36

0.45

0.35

Venezuela

0.55

0.43

0.4

8

0.43

0.46

0.38

Groupmean

(unweighted)

0.53

0.46

0.5

0

0.46

0.54

0.42

*

AllincomeGini

coefficientestimatesarepopulationbased.For1970thedataforA

rgentina,MexicoandNicaragua

arefor1960andforVenezuela1961.Sourceis

Behrman,BirdsallandPettersson(2006)basedondatafromWDI(2005),WIID2a

(2005),Thomas,WangandFan(2001)andDeiningerandSquire(1996).

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Estudios d Ecoo, Vol. 38 - N 112

enhancing their human resources is likel to increase the return to the use of their

ti. I ct s i LAC, fo xpl, t s b cosidbl xp-

sio of coditiol cs tsf pogs bsd o t Mxic PROGRESA/

Oportunidades xpl i wic t tsfs coditiol o idictos of

ivstts i u cpitl, ost otbl i scoolig ttit (but lso

on investments in health and nutrition)1. Feasible improvements in the positions

of tos i povt i t lft til of t igs ico distibutio, of cous,

likl to duc iqulit.

This paper first considers some recent benefit/cost estimates for human

capital interventions in LAC (Section 1). These suggest that there are some

u cpitl ivstts i wic t stitd tus pp quit ig.

T t pp tus to oug clcultios of ow uc icss i scoolig

ttit t ost psid fo of u cpitl ivstts tgtdtowards the poorer members of societ will reduce povert and income inequali-

tis (Sctio 2). To illustt t piicl ods of gitud, igs d

wage rate function estimates and the distribution of earnings from the 2004

Cil Socil Potctio Suv usd. Sctio 3 t cocluds gdig

t iplictios of t pvious two sctios fo t possibilit of usig u

cpitl ivstts to duc povt d iqulit i LAC.

1. Benefit/Cost Estimates for Human Capital Investmentsin Latin America

T is supisig pucit of good stits of bfit/cost stits fo

u cpitl itvtios i Lti Aic d i ot dvlopig gios.

Tis is i ipott pt bcus of t difficultis i kig good stits2.

O t bfit sid, fo xpl, t oft difficultis i:

Obtiig good stits of ipott ipcts giv bviol coics i

t psc of uobsvd togitis (so tt, fo xpl, scooligis ot icoctl cditd i pt wit t ffcts of uobsvd bilitis,

otivtios d fil bckgoud tt i pt cus o scoolig d

lso dictl ffct outcos tt igt b dictl ffctd b scoolig)

d tt ipcts b distibutd ov dcds ov t lif ccl;

Plcig vlus o ll t lvt ipcts so tt t c b gggtd,

wic is pticull difficult (.g., fo dvtd otlit) but lso difficult

1 T ub of studis tt pot positiv ipct of ts pogs o scoolig,nutrition and other outcomes (e.g., Behrman and Hoddinott (2005); Behrman, Parkerd Todd (2009,b); B, Sgupt d Todd (2005); Fisbi d Scd (2009);Gtl (2004); Hoddiott d Adto (2009); Riv et al. (2004); Scult (2004).

2 Fo discussio i uc o dtil of ts difficultis d so illusttiv stitsof bfit/cost tios fo dvlopig coutis, icludig so i LAC, s B,Ald d Hoddiott (2004) d Kowls d B (2004, 2005).

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How uc igt u cpitl policis /Jere R. Behrman 13

if pojcts lg oug to v ipct o kt pics o if pics

v distotd b kt o polic filus; Selecting appropriate discount rates to permit aggregation across time

(Tbl 2 illustts ow uc t coic of discoutig tts, s wll s

tt ipcts of u cpitl ivstts dpd o lif-ccl ptts isuvivl pobbilitis); d

Distiguisig btw pivt d socil (bod t pivt) bfits, distictio tt is ctl fo t fficic otiv fo policis.

TABLE 2PDV OF $ 1000 RECEIVED WITH VARIOUS LAGS STARTING FROM BIRTH AT

ALTERNATIVE DISCOUNT RATES, ADJUSTED FOR SURVIVAL PROBABILITIES*

Discout Rt 3.00% 5.00% 10.00% Suvivl Pob

Lg i ys

10 $ 717 $ 592 $ 372 0.964

40 $ 281 $ 130 $ 20 0.915

60 $ 134 $ 42 $ 3 0.787

100 1 0 0 0.007

Suvivl pobbilitis bsd o WHO Lif Tbls fo Bil t ttp://www.wo.it/coutis.

O t cost sid, t oft difficultis i:

Idtifig t tu pivt d public souc costs (ot t govtlbudgt costs), icludig distotio costs but xcludig tsfs;

Assssig t costs w pojct is scld-up, icludig ot ol t pos-sibilit of cgig gil costs t ico lvl but cgig gilsouc costs toug ipcts o kts; d

Distinguishing between private and social costs, again important for efficienc

cosidtios.

Howv t so ct stits of bfit/cost tios fo ucpitl ivstts i dvlopig coutis tt ttpt to dl wit so ofts pobls but t t s ti illustt so of t pobls. Sctios1.1 suis slctd stits fo ductiol itvtios i LAC dSection 1.2 summarizes selected estimates for nutrition/health interventionswit djustts to plc t i LAC cotxt.

1.1. B/C E T R LAC E-RP

If ductio s lig, t ductio is lif-log pocss d otlimited to schooling though at times the literature inappropriatel seems toqut ductio wit scoolig. Rct stits of dult cogitiv civ-t poductio fuctios i Gutl, fo xpl, illustt tt ssuig

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Estudios d Ecoo, Vol. 38 - N 114

onl schooling matters in the production of adult cognitive skills leads to asubsttil ovstits of t ipct of scoolig d udstits of tipotc of p- d post-scoolig xpics (B et al. (2008)). Ipt fo tis so, I sui t itvtios o p-scool, o

ltd to scoolig, d o post-scoolig.

1.1.1.Bolivian PIDI (Proyecto Integral de Desarrollo Infantil) Pre-SchoolProgram3

Program: PIDI provided dacare, nutritional, and educational services to childrenbtw t gs of 6 ots d 72 ots wo livd i poo, pdoitlub s. T gols w to ipov lt d l cogitiv/socil dv-lopt b povidig cild wit btt utitio, dqut supvisio, dstimulating environments. It was hoped that the program also eased the transitionto lt scool, ipovd pogssio toug lt gds, disd scool pfoc, ll of wic w xpctd to ics post-scoolproductivit. Through PIDI, children attended full-time child care centers locatedi t os of wo livig i low-ico s tgtd b t pog.These women were given training in child care and loans and grants (up to $ 500)to upgd fcilitis i ti os. Ec PIDI ct d up to 15 cild dapproximatel one staff member per five children, with additional staff providedw t ws lg popotio of ifts. T pog povidd food tosuppl 70% of t cilds utitiol ds s wll s lt d utitio

oitoig d ductiol ctivit pogs.

Program benefits: Logitudil ifotio is vilbl o spl of po-g pticipts, spl of ot cild i t s g g livig ipog s d spl of cild i t s g g livig i ouglcopbl s tt did ot v t pog. Tis icluds ifotio op-scool cild topotics, cogitiv dvlopt d pscosocil d-velopment. However baseline pre-program data on critical child attributes (e.g.,topotics) ot vilbl. Bsd o dic odl of ivstig icild, g of stitio tods w usd to ssss t obustss of

estimated program impacts under alternative assumptions about the selection intot pog stdd coss-sctiol gssios, popsit sco tcigwit t two spls of cild ot i t pog, d gil popsitsco tcig (wit t dvtg of cotollig fo uobsvd fctos ttdtid pog pticiptio) focusig o cgs i t outcos witdifft pog xposus d coditiol o cild g w tig tprogram. The estimates show that the program significantl increased cognitiveachievement and pschosocial test scores, especiall for children who participatedi t pog fo t lst sv ots. T ipct stits fil obustto t us of lttiv copiso goups d stitos. Estits obtidb t gil tcig stito td to b lg, pticull t log du-rations and for children aged 6-36 months, than those obtained using traditionalcootic stitos tt ipos stog fuctiol fo ssuptios.

3 Bsd o B, Cg d Todd (2004).

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How uc igt u cpitl policis /Jere R. Behrman 15

To obtain the program benefits, the impacts of these pre-school characteristics

d to b tsltd i t vlu of ti ipct o lifti poductivit. Fou

cls toug wic t pscool pog c ffct lifti igs

cosidd: (1) icsig cogitiv skills s dult (coditiol o gds

copltd), wic dictl ffcts igs, (2) icsig psicl sttu s

dult, wic dictl ffcts igs, (3) icsig t ub of gds

copltd, wic dictl ffcts igs d t g of scool copltio,

d (4) dcsig t g of scool copltio witout cgig t ub

of grades completed. Available data from Bolivia are used for some dimensions

of these processes, such as grade repetition, distribution of completed schooling

ttit d ltd igs. I t bsc of stits fo Bolivi o

ot dd copots, stits fo pvious studis o ot dvlopig

countries are used (e.g., Thomas and Strauss (1997) estimate of the relationshipbetween adult earnings and height in Brazil, the Alderman et al. (1996) estimate

of t cogitiv skills igs ltiosip i Pkist) ud t ssuptio

that increases in height and cognitive abilit as a child have persistent effects that

tslt ito quipopotiol icss s dult. Tis lst ssuptio

sult i ovsttt of t ipcts. O t ot d, i so spcts

ts stits pobbl udstt t pog bfits bcus (1) t do

ot icopot o-lbo-kt ffcts suc s icsd poductivit i t

poductio of lt d utitio d (2) t do ot icopot t vlu of

ti gid toug lss ti i cildc of t cilds ots o otcgivs du to t pog.

Program costs: T pog cost ws stitd b Rui (1996) to v b

ppoxitl $ 43 p bfici p ot, wic is substtil i cout

w p cpit ul GDP t t ti ws $ 800 i xcg-t-covtd

pesos, or $ 2540 in purchasing power parit terms. Approximatel 40% of

t xpditu wt to t utitiol copot of t pog. Tis stud

uss t Rui stit, wit djustt i lttiv stits of 25% fo

t distotio cost of isig vus fo t pog (.g., s Kowls dB 2004). Suc stits ovstt sowt t costs if pt of

t utitiol supplttio fo t cild ffctivl ws tsf tt

plcd food tt t cild otwis would v b povidd b ti

filis, s suggstd b so pvious studis.4

Benefit/cost ratios: Tbl 3 suis t stitd bfit/cost tios wit

alternative assumptions concerning discount rates (3% and 5%), schooling levels,

and whether distortion costs are included. The included estimates range from 1.4

to 3.7, all of which mean that the program has benefits greater than its costs, butt g idicts cosidbl ssitivit to t lttiv ssuptios.

4 Alttivl, t bfits udstitd bcus t i pt pd b otousold bs.

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Estudios d Ecoo, Vol. 38 - N 116

TABLE 3BENEFIT/COST RATIOS FOR BOLIVIAN PIDI PRE-SCHOOL PROGRAM*

Schooling Level

Mean Annual

Earnings

($)

Discount

Rate

3%

Discount

Rate

5%

From To Cost Benefit

Benefit/

Cost

Ratio

Cost Benefit

Benefit/

Cost

Ratio

Intermediate (8) 1224 1352 1394 5107 3.7 1301 3230 2.5

Secondar (11) 1422 1550 1394 3969 2.9 1301 2232 1.7

Intermediate (8) 1224 1352 1743 5107 2.9 1626 3230 2.0

Secondar (11) 1422 1550 1743 3069 2.3 1626 2232 1.4

* Assus tt cild pticipt i pog fo t s sttig t g 2. Ipct: sotsti to coplt scoolig b 1 ; icss scoolig lvl b 1 gd; icss cogi-tiv skills b 5%. Costs i fist two ows $ 516 p bsd o Rui (1996); costs i tscod two ows lso iclud 25% djustt fo distotios du to isig public vusfo t pog.

1.1.2.Colombian Pog d Aplici d Cobtu d l EducciScudi (PACES) Scholarship Program for Poor Urban Secondary

School Students5

Program: The Colombian government created the PACES voucher program forpoo scod scoolg cild i 1991 to bl t to ttd pivtsecondar schools. B 1996, the program was covering about 100,000 students.At t ti t pog ws lucd, ollt i pi scool (coviggrades 1-5) was almost universal, while the enrollment rate in secondar school(i.., covig gds 6-11) ws 73% ovll d 55% fo t poost quitilof studts. T voucs w dsigd to cov bout o-lf of t cost ofpivt scod scools. T could b wd s log s studts iti-

ned satisfactor academic performance. The vouchers were targeted to childrenresiding in poor urban residential areas and who previousl had attended publicpi scools.

Program benefits: T PACES scolsip pog (d scolsip pogsgll) igt b xpctd to v t followig ffcts:

Icsd scoolig ttit (owv, t b gtiv ffcts viscool cowdig).

Eli copltio of giv scoolig lvls. Ipovd cogitiv civt fo giv lvl of scoolig ttit

(assuming that private schools attended b some voucher recipients provided

5 Bsd o Agist et al. (2002) s suid i Kowls d B (2004).

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How uc igt u cpitl policis /Jere R. Behrman 17

btt-qulit scoolig t tt povidd b t public scools tt wouldv b ttdd i t bsc of t voucs).

Reduced work effort b other famil members (an reduction in work effortb t scolsip cipit is cosidd to b pt of t oppotuit cost

of scoolig).

Evlutio of t PACES pog ws fcilittd b t fct tt voucsw iitill wdd b lott i uiciplitis i wic t ub of stu-dts pplig fo voucs xcdd t stitd sotfll i t ub ofspcs vilbl i public scools tt ws usd b locl utoitis to dcidow w voucs to k vilbl i giv scool . Tis i ffctcreated a natural experiment that made it possible to estimate the effect of thevoucs o t tgt popultio uc s o could do if t vouc scd b coductd s doid xpit6, 7.

This evaluation did not find an significant impact on enrollment. However,it did fid tt lott wis w 15 pct o likl to ttd pivtscool8. Aft t s, lott wis lso d copltd 0.12-0.16 ogds of scoolig (piil du to low ptitio ts) d w bout 10pctg poits o likl to v copltd t 8t gd t t d of tprograms third ear. Although the program had no effect on dropout rates, lotterwinners scored 0.2 standard deviations higher on standardized tests. In addition,lott wis potd wokig 2.2 ous p wk lss t o-wis dw lss likl to b it id o cobitig s tgs (owv, tis

lst diffc ffctd ol bout o pct of t spl).The evaluation stud estimates that the additional 0.12-0.16 grades of school-ig copltd b lott wis would is ti ul icos b bout$ 36-48 per ear (based on an estimated rate of return to schooling of 10 percenti Colobi d pdictd vg ul igs of $ 3,000).

6 The implicit assumption is that the excess demand for vouchers occurred randoml acrossmunicipalities (and therefore was not associated with other municipalit-level factors that

might affect education). If, for example, excess demand for vouchers more likel occurredwhere recent expectations were higher regarding the returns to schooling because of greatercooic ctivit t lsw, t stitd ipcts ot b pplicbl to otuiciplitis wit low xpcttios gdig t tus to scoolig. Ufotutl,the stud does not provide information with which to assess whether the excess-demanduiciplitis w siil to o difft fo ot uiciplitis.

7 I fct, t vlutio foud tt ol bout 90% of lott wis ctull usd tivoucs, wil bout 24% of lott uss civd scolsips fo ot soucs. Tocorrect for the effects of such contamination, the evaluation also used lotter success as istut to pdict wt giv out civd scolsip. T istutlvariable estimates of the grade completion effect were about 50% greater than the reduced-

fo OLS stits of big lott wi. T stits of ffctivss usd i tpublisd stud to obti t cost-bfit stits t ducd-fo stits. Itis cs, t psubl o ccut istutl vibl stits gubl souldv b usd.

8 Bcus of t potd poo qulit i so of t w scod scools tt gdto sv vouc cipits, ligibilit to pticipt i t pog ws liitd to ot-fo-pofit scools fo 1996 o.

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Program costs: T cooic cost of t PACES pog icluds:

Additional schooling costs (some of which ma be incurred directl bhouseholds, including the opportunit cost of the additional time scholarship

studts ggd i scoolig-ltd ctivitis). Pog diisttio costs. Distotio costs ltd to t ficig of t pog (.g., t dd-

weight cost of collecting the necessar taxes to finance the program) orto ducd wok ffot o t pt of ot ousold bs (du to possibl ico ffct).

T costs of scolsip pogs do ot iclud t cost of t scol-sips tslvs (i.., t cost of t vouc, i t PACES pog), wicis tsf.

Tbl 4 suis ifotio o t costs of t PACES pog s -potd i t vlutio stud. T tbl idicts tt t potd socil costsof t pog (t lst colu i t tbl) t lst US$ 195 p lottwi fo t s (ft djustig fo difft ts of vouc tk-up ieach ear of the program). However, several cost items are not reported, includ-ig t ddwigt cost of ficig t dditiol govtl xpdituof $ 109 p lott wi, t possibl distotio cost o dult wok ffoti lott-wiig ousolds, d t pogs diisttiv costs.

TABLE 4THREE-yEAR COSTS PER LOTTERy WINNER IN THE COLOMBIA

PACES PROGRAM (US$)

It GovtLottWis

AllHousolds

Socit

Cost of t voucs 336 336 0

Ddwigt cost of

govt ficig ? ?Effct of vouc odult wok ffot ? ?

Adiisttiv costs ? ?

Rducd publicxpditu oscod scoolig 227 227

Additiol outspt o scoolig blott wis 236 236

Oppotuit cost ofstudt ti 186 186

Totls 109 86 0 195

Source: Agist, et al. (2003). Estitd o t bsis of potd ductios i ti wokd b lott wis s copd

to o-wis.

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How uc igt u cpitl policis /Jere R. Behrman 19

Program benefit/cost estimates: The evaluation does not include a formal benefit/cost lsis, cocludig tt t bfits cll xcd t costs usig plusibl discout t. Howv Kowls d B (2004) build o tvlutio stud sults to obti bfit/cost stits. A lif-ccl ppoc

is usd wit t followig ssuptios:

T t- costs of t pog iclud t stitd pojct costs of$ 195 per lotter winner from Table 4 but also administrative and distortionarcosts of $ 32.65 p lott wi (i.., 30% of t ics i govtxpditu fo Tbl 4)9 d tt ll pog costs occu t gs 13-15i qul ul istllts.

Lott wis coplt 0.12 dditiol gds of scoolig, wit cadditional grade of schooling resulting in a 10% increase in annual earningsof $ 3,000 p .

Aul bfits occu t gs 16 to 60. T discout t is lttivl 3, 5 o 10% p u, d bfits d

costs discoutd to g 13.

Ud ts ssuptios, t bfit-cost tio is 3.8 wit discout tof 3%, 2.7 wit discout t of 5%, d 2.4 wit discout t of 10%. Tdiscout t gi, s i t p-scool pog cosidd i Sctio 1.1.1d t lt d utitio pogs cosidd i Sctio 1.2, s stogffct o t stitd bfit/cost tio bcus t bfits spd ov

xtdd piod of ti. Tbl 5 psts t stitd bfits d costs tselected ages for illustrative purposes using a discount rate of 5%. The estimatedbfits fo t icsd ub of scool s copltd pstdi colu 1, wil t pogs cost is pstd i colu 4 (t ot col-us discussd blow). T clcultios sow tt t bfits vildiscoutd (copig t lst two ows of t tbl).

These estimates of the benefit/cost ratio are conservative, however, notol bcus t ssu t low liit to t stitd gi i t ubof scool gds copltd (0.12, s copd to t upp liit of 0.16)10 butlso bcus t glct t ot stitd ffcts of t itvtio, i..,

t fidig tt lott wis w 10% o likl to v copltd t 8tgd t t ti of t vlutio d tt t scod 0.2 stdd dvitiosig o stddid tsts11.

9 T 30% stit fo diisttiv anddistotio costs is pobbl cosvtiv,based on the discussion in Knowles and Behrman (2004, Section 3.2.3) where it is recom-mended that an estimate of 20-25% be used as an estimate of the cost of raising additionaltx vu.

10 If t stitd ipct of t vouc sc o t ub of scool s copltd

is ssud to b 0.16, istd of 0.12, t stitd bfit/cost tio icss fo 2.7to 3.6 wit discout t of 5%.

11 There ma be other biases as well that are not explored here. On one hand, the estimate of 10% t of tu to scoolig ttit b upwd-bisd du to t filu tocontrol for unobserved endowments (e.g., innate abilit, famil connections, motivations)i t igs fuctio stits. O t ot d, t b o-lbo-kttus tt dditiol to lbo kt tus.

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TABLE

5

CALCULATIO

NSOFDISCOUNTEDBENEFITSANDCOSTS(US$)PERLOTTERyWINNERFORTHECO

LOMBIAPACESVOUCHERSC

HEME

Age

Be

nefits

Cost

Increasednumberof

schoolgradescompleted

Earliercompletionof

sch

ooling

Improvedtestscores

13

0.00

0.00

0

.00

75.8

8

14

0.00

0.00

0

.00

75.8

8

15

0.00

303.60

0

.00

75.8

8

16

36.00

0.00

360

.00

0.0

0

17

36.00

0.00

360

.00

0.0

0

18

36.00

0.00

360

.00

0.0

0

19-59

36.00

0.00

360

.00

0.0

0

60

36.00

0.00

360

.00

0.0

0

61

0.00

0.00

0

.00

0.0

0

62

0.00

0.00

0

.00

0.0

0

63-69

0.00

0.00

0

.00

0.0

0

70

0.00

0.00

0

.00

0.0

0

Totals

1,620.00

303.60

16,200

.00

227.6

5

Discountedto

age13a

580.38

275.37

5,803

.78

216.9

8

Source:Seetext.

a

Usingadiscountrateof5%.

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How uc igt u cpitl policis /Jere R. Behrman 21

Cosidig fist t ffct of t vouc sc o t g of copltigt 8t gd, it is ssud tt t stitd ffct iplis tt lott wisgain an additional 0.1 ear of full-time work at age 15. This additional benefit isdispld i ow 3, colu 2 of Tbl 5. Lik costs, tis bfit is ol sligtl

discoutd bcus it occus t g 15. T ffct of ddig tis bfit is toics t stitd bfit-cost tio fo 2.7 to 3.9 (usig discout tof 5%). Tis is sigifict ics, idictig tt i t cotxt of cooicanalsis earlier completion of a given grade or level of schooling is an importantscoolig outco12.

T PACES vlutio stud stits tt t ics of 0.2 stdd d-viations in standardized test scores among lotter winners is equivalent to aboutone full additional grade of schooling completed (based on the mean test scoresb gd of Uitd Stts Hispic studts tkig t s tst). If coct,tis tslts ito dditiol ul igs bfit of $ 300, copd tot pviousl icludd ul igs bfit of $ 36 bsd o t ub ofadditional grades completed. This additional benefit is displaed in column 3 ofTbl 5. Lik t bfit ssocitd wit t icsd ub of scool gdscompleted, this benefit is heavil discounted because it occurs during the personsentire assumed working life (ages 16-60). Not surprisingl, including this benefiticss t stitd bfit/cost tio dticll, fo 3.9 (icludig tli copltio bfit d usig discout t of 5%) to 30.7.

1.1.3.Argentinean Pog Jov Youth Job Training Program13

Program: The target population ofPrograma Joven was the large number of poorout, l d fl, wit liitd ductio d witout wok xpicd wo w uplod, ud-plod o ictiv. T slctio citifor the program were minimum age of 16 ears, no more than secondar educa-tio copltd, b of poo ousold, d ot cutl plod. Tpog povidd itsiv tiig (200 ous ov piod of 6 to 12 wks)for positions in the productive sectors of the econom, including reimbursementof transportation expenses, a stipend for females with children under 5, medicalcckups, books, tils, wok clotig d 8-wk itsip i fi.

Program benefits: Pog ipcts w stitd b usig popsit scomatching to compare program participants with one or more similar (in termsof observed characteristics) non-participants using three different samples/soucs of ifotio:

12 Moreover, its relative importance increases with the discount rate. For example, with a 5%discout t, t li copltio bfit ccouts fo 32% of totl stitd bfitsi tis xpl, ws wit 10% discout t it ccouts fo 46% of totl stitdbfits. Of cous t gi fo copltig giv lvl of scoolig t oug gs b otd i ot studis, icludig t o i Sctio 1.1.1, goig bck t lst toGlww d Jcob (1995).

13 Bsd o Ado d Nu (2001) s suid i Kowls d B (2004).

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t tis (fo xpl, t stipds pid to fl pticipts wit cildud 5)16. T stud ssus tt t oppotuit cost of ti ti is o,which is a strong assumption17. The stud also assumes a zero deadweightloss fo t govtl soucs usd to fud t pog (ltoug 50%

ddwigt loss is lttivl ssud i ssitivit lsis potd i tstud). Indirect costs were estimated to be 32.7% of direct costs (with an indirectcost tio of 15% usd i ssitivit lsis).

Program benefit/cost estimates: Benefit/cost analsis was done for oung malesd dult fls (pstig tgtd pog) d ll fou goups cobi-d (pstig t ctul pog). T stitd ffct of t pog ootl igs (t vg of t stits obtid fo c goup) wsssud to b t pogs ol bfit d ws ssud to i costtduig piod of ti tt ws lttivl ssud to lst fo 1, 3, 6, 9, 12,15 s o fo uliitd piod of ti. Two lttiv discout ts wusd (5% d 10%).

In the case of the four groups combined, representing the actual program, thestitd t pst vlu of bfits ws positiv wit discout t of 5%after 12 ears (but was still negative with a discount rate of 10% after 15 ears).18Wit t lsis stictd to oug ls d dult fls, pstig pog tgtd ol to ts two goups, t stitd t pst bfits positiv ft 9 s wit discout t of 5% (o wit idict costtio of 15%) d ft 12 s wit discout t of 10%. If ddwigt

loss of 50% of t pogs totl xpditu is ssud s t distotiocost of govtl ficig, stitd t pst bfits of t xistigpog o-positiv ft 15 s, v wit discout t of 5%, wilfo tgtd pog (i.., o stictd to oug ls d dult fls),t positiv ol ft 15 s wit discout t of 5% (but ol w uliitd ti piod is ssud wit discout t of 10%).

1.. H C I R H M

Behrman, Alderman and Hoddinott (2004) present benefit/cost ratios for four

sets of interventions related to hunger and malnutrition in a low-income countrcotxt, bsd o xtsiv discussio of t vilbl ifotio wit wicto ssss bfits d costs d t ssitivit of t stits to difft s-suptios. Tis ws pt of t Copg Cossus i wic pl ofigt distiguisd cooists, icludig fou Nobl Luts, kd bout40 pojcts i t bod topic s o t bsis i pt of bfit/cost lss

16 Tis lst ctgo is ctull tsf d sould ot v b icludd i t pogsouc costs.

17 Psubl, of t tis would v b plod i t ifol scto o iouswok if t d ot pticiptd i t pog. Tis ssuptio lso iplicitlssus tt its did ot cotibut positivl to t output of t fis i wic tw wokig fo 8 wks.

18 Howv, wit idict cost t of 15% stitd t pst bfits w positivft 15 s v wit discout t of 10%. I dditio, ud t bsic ssuptiosusd, t pog d stitd positiv t bfits ov ifiit ti piod.

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Estudios d Ecoo, Vol. 38 - N 124

prepared b experts in each of the areas (Lomborg 2004). In the final ranking oft lttivs pojcts ltd to ug d lutitio w igl kdi ts of pioitis.

H, I pst w stits bsd o siil ppoc, but usig pics

d icos fo t LAC 2005 vg19, Bili suvivl pobbilitis20 dlttiv s of vluig dvtd otlit i ts of t vlu plcd ovalue per DALy (Disabilit Adjusted Life years) of $1,000 (low) and $ 5,000(high), which are the values suggested b the Copenhagen Consensus for newestimates in initial Problem Papers for a 2008 Copenhagen Consensus exercise21.I cosid t sts of utitiol itvtios:

Reducing the Prevalence of low birth weight (LBW):Man of the 12 million LBWifts bo c di t oug gs, cotibutig sigifictl to otlotlit, wic ks up t lgst popotio of ift otlit i developing countries. Unfortunatel, rates of LBW have remained relativelsttic i ct dcds. Bcus LBW ifts 40% o likl to di it otl piod t ti ol wigt coutpts, ddssig LBW issstil to civ ductios i ift otlit. Moov, of t LBWcild wo suviv ifc suff cogitiv d uologicl ipit dare stunted as adolescents and adults. Thus, in addition to contributing to excessotlit, LBW is ssocitd wit low poductivit i g of cooicd ot ctivitis. LBW lso b ipott i ligt of w vidc ttsows tt LBW ifts v icsd isk of cdiovscul diss,

dibts d ptsio lt i lif. LBW lso b itgtiolproblem because LBW girls who survive tend to be undernourished when preg-t wit ltivl ig icidc of LBW cild. Wil t pvlc ofLBW is pticull ig i Sout Asi, t substtil ubs of LBWbbis i ot pts of t dvlopig wold, icludig i LAC.

T bfits fo ducig LBW copss t PDV of t six ipctsov t lifccl d t o coss gtios tt suid i tprevious paragraph. Under the assumptions used here, the most important effects fo dvtig otlit (11 to 50% of t totl), itgtio ffcts(18-39%), coic disss (8-38%), d poductivit (6-27%). Not tt ts

ltiv cotibutios diff lot dpdig o t discout ts (5% o 10%)d t DALyS ($ 1,000 o $ 5,000). T ig t discout t, t o

19 In particular, I use the Gross National Income per capita (Atlas method) of $4008 for LatinAmerica in 2005 from http://web.worldbank.org/WBSITE/EXTERNAL/DATASTATISTICS/0(24 November 2006) relative to the $ 500 value for the target population in a context suchs Sout Asi i B, Ald d Hoddiott (2004) to djust ll t pics dicos i tt stud fo t pst pupos.

20 Survival probabilities are relevant since some impacts occur onl if the individual affected

b t itvtio livs log oug. T souc usd is t WHO Lif Tbl fo Bilt ttp://www.wo.it/coutis s of 24 Novb 2006.

21 I B, Ald d Hoddiott (2004) fo ou pfd stits w followdSummers (1992, 1994) and used instead of DALys at such levels, the alternative resourcecost tt ts socitis d cos to lloct to dvt ift otlit, wic wsestimated to be $ 1250 in PDV terms (from inoculations) a much lower value than impliedb DALys of $ 1,000 o $ 5,000.

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Basic description of inequality and poverty in the 2004 Chilean SPS: Table 8summarizes some relevant sample-weighted statistics from the 2004 SPS regardingt distibutio of scoolig ttit, lbo kt igs, d wg tsp ou fo t 51,244 dults g 21 s o old fo wo tis ifotio

ll is vilbl. As is wll-kow, vg scoolig ttit lvls i Cil ltivl ig i copiso wit dvlopig coutis, icludig ub of ots i LAC. Ts stits suggst tt t distibutio ofscoolig ttit lso is ltivl qul, wit Gii cofficit of 0.23, icopiso ubs potd fo ot coutis i LAC (Tbl 1)22. Alost fift of t spl (18%) d scoolig ttit blow six gds, d boutt tts d scoolig ttit blow igt gds.

TABLE 8CHILEAN 2004 SPS, BASIC STATISTICS FOR SCHOOLING, EARNINGS AND WAGE

RATES FOR 51,244 ADULTS AGE 21+ yEARS*

MSD

GiiCofficit

SE

Povt Hdcout

LowSE

HigSE

Scoolig Attit 9.5 .3 .18 .3(Gds) 4.3 0.001 0.002 0.002

Eigs 19 .53 . .36(1000 Psos p ) 3195 0.003 0.002 0.002

Wg Rt 1193 .9 .17 .33(Psos p ou) 1751 0.004 0.002 0.002

* The low and higher povert lines for schooling are < 6 and < 8 grades, for earnings < 500000d < 1000000 psos p , d fo wgs < 400 d < 600 psos p ou. T stdderrors for the Gini coefficients are calculated b bootstrapping with 50 repetitions. All estimates wigtd to flct t spl dsig.

The 2004 SPS earnings Gini coefficient is 0.53, significantl below the valuefor Chile given in Table 1 for around 2000 and at about the mean for LAC in thattable. The 2004 wage rate Gini coefficient is somewhat lower at 0.49, suggestingtt so of t iqulit i ctul igs ico is du to coics of toswo v ig kt wg ts to spd o ti wokig. Tfo tGii cofficit fo t wg t o, quivltl, fo full ico, is sowtlower. For both earnings and the wage rate I define low and higher povertcutoffs. These are notrelated to an official or unofficial efforts to define povertcosuptio bskts i igful w, fo wic so I put povt

in quotation marks here. The are just convenient benchmarks at rounded valuesof psos p d p ou, spctivl, tt dct t poits blowwic i t 2004 SPS distibutio t bout fift (0.20 fo igs,

22 Icludig t Gii cofficit potd fo Cil i 2000 i Tbl 1. I do ot v xpltio fo t diffc.

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0.17 fo t wg t) d bout tid (0.36 fo igs, 0.33 fo t wgt) of t idividuls wit positiv igs d wg ts.

Semilog earnings and wage rate functions based on the 2004 SPS: To b bl

to siult ow difft potticl ptts of scoolig ttit wouldaffect the earnings and wage rate distributions, I need estimates of these relations.Of cous t is cosidbl cotovs bout ow bst to stit tsltios d to wt xtt d i wt dictio OLS stits bisd(e.g., Card 1999, Behrman and Rosenzweig 1999). For the illustrative purposes, I vtlss us OLS stits, wit splis i scoolig to llow fooliitis wit difftil tus to t fist six gds (pi) vsust scod six gds (scod) vsus o t 12 gds (tti).I lso iclud qudtic i pottil wok xpic (g-scoolig tti-t six) d llow fo ll t cofficit stits to diff btw lsd fls.

Table 9 summarizes the resulting estimates. The first two rows of coefficientstits f to t silog igs fuctio d t scod two ows fto t silog wg t fuctio, wit t vlus i itlics bt c poitstit. Witi c pi of ows, t fist ow givs t stits fo flsand the second row gives the extent to which the point estimate for males differssigifictl (t t 5% lvl) if it dos.

TABLE 9WEIGHTED SEMI-LOG EARNINGS AND WAGE FUNCTIONS FOR 51,244 ADULTSAGE 21+ IN 2004 CHILEAN SPS*

Spli i Scoolig Pot Expic Cost R sq

Pi Sc T Lvl Squ F

l Eigs . .1 .35 . 0.00048 12.412 0.201

5.31 22.90 36.69 28.79 22.50 286.00 1009

xMl .36 .15 0.038 .1694.16 2.84 4.20 4.05

l Wg .39 .1 .7 . 0.00030 5.81 0.339

9.06 49.16 77.89 21.37 16.44 220.08 2810

xMl .1

30.42

* t-statistics in italics beneath coefficient estimates; potential experience is age schooling attain-t 6; t ow wit xMl icluds ll sigifict cofficits fo t itctio btwl d t igt-sid vibl i tt colu.

Ovll t silog igs fuctio is cosistt wit bout fift of tspl vic d t silog wg t fuctio is cosistt wit bout tid of t spl vic. Tt s, of cous, tt t cosidbl

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How uc igt u cpitl policis /Jere R. Behrman 31

ss of t vic tt ot ffctd b scoolig ttit fou-fiftsfo l igs d two-tids fo l wg ts. T qudtics i xpic igl sigifict, d suggst icsig ipct t diiisig tof xpic wit o sigifict diffcs btw fls d ls. T

schooling coefficient estimates also are highl significant and also suggest strongnonlinearities, with much larger effects for an additional grade of tertiar schoolttit t fo dditiol gd of scod scool ttit d uc lg ffct fo dditiol gd of scod scool ttit tfo dditiol gd of pi scool ttit. Mls v stitd16.9% gt igs idpdt of scoolig ttit d pottil x-pic, d v sigifictl ig scoolig cofficits fo bot piand secondar schooling, though females have a significantl higher coefficientfor tertiar schooling in the ln earnings function. However, except for the highercoefficient for males for primar schooling, the gender differences in the ln earn-igs fuctio stits bsicll flct gd diffcs i ous wokd it pid lbo foc. Tfo, wit t xcptio gi of pi scoolig,t o sigifict gd diffcs i t l wg t fuctio.

Simulations of the impact of alternative targeted schooling attainment increaseson inequality and poverty: Table 10 summarizes eight simulations of the impactof lttiv tgtd cgs i scoolig ttit o Gii cofficits foiqulit d t low d ig povt cutoff dcouts fo igs dfo wg ts. Ts siultios ssu tt t silog igs d wg

t ltios i Tbl 9 old. Tt is, t ssu tt t cofficit stits ubisd stits of t tu cusl ffcts of scoolig ttit o ligs d l wgs23, tt o of t siultio itvtios is so lg tochange the relevant coefficients, and that each individual receives the same shock(i.e., has the same residual) as in the estimates in Table 924. The Gini coefficientsd t povt dcout sus i bold, wit t stdd os to tigt i itlics. Not tt t stdd os gll sll ltiv to tsiultd cgs, so t siultd cgs gll sigifict.

At the top of Table 10 the Gini coefficient estimates and povert headcountsfo t bs dt giv, s i Tbl 8, fo s fc. T qustio of

itst is ow uc do c of t lttiv siultios diff fo tsbs vlus. T igt siultios tt icludd i t tbl :

23 Tt is, tt t ot oittd vibl biss bcus ts stits do ot cotolfo uobsvd bilit d ot spcts of fil bckgoud d fo scool qulit,toug so vilbl stits suggst tt t filu to cotol fo suc fctos result in substantial overestimates of the impact of schooling attainment because schoolingttit ptill is poxig fo idividul d fil bckgoud d scool qulit(.g., B d Bidsll (1983), B d Roswig (1999)). A lttiv

interpretation of the simulations with regard to school qualit is that the underling assump-tio is tt scool qulit is positiv coltd wit scoolig ttit (s suggstdb t odlig d t piicl sults i B d Bidsll (1983)) d tt it siultios scoolig qulit is big icsd togt wit scoolig ttiti od to iti t ssocitio btw t two tt xists i t spl dt.

24 Fo o coss-sctio o c ot idtif wt ts tsito o ptsocks.

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Estudios d Ecoo, Vol. 38 - N 136

psos p dop b 0.02 d t popotio blow t ig cutoff of1000000 psos p dops b fo 0.03 to 0.04. Toug ll fou of tsiultios dictd towds low wg t cipits v t s ipct oducig t igs Gii cofficit, t diff fi out wit spct

to ti ipcts o t popotios blow t povt cutoffs. I pticul i-csig scoolig ttit b o gd fo ll tos wit wg ts blow400 Psos p ou is siultd to duc t olid popotio blow tlow povert cutoff of 500000 pesos per ear b 0.08 (simulation 1), while att ot xt og t fist fou siultios, icsig scoolig tti-t b t gds fo ll tos wit wg ts blow 600 psos p ou issiultd to duc t olid popotio blow t s low povtcutoff b ol 0.03 (siultio 4). Tis is itstig illusttio of w itis ipott ot to psu tt ducig iqulit d ducig povt sufficitl siil objctivs tt t ld to t s polic pioitis.

Wage rate inequality: All of ts siultios duc t Gii cofficits fowage rates at least as much or slightl more (i.e., b an additional 0.01 in threeof the eight simulations) than for earnings. That the simulations, if anthing, areslightl more effective for reducing wage rate than earnings inequalities reflectsthat the simulations presented are targeted towards low wage rates rather than lowigs but tt t diffcs ot ll tt gt flcts t ltivl igcoltio btw igs d wg ts. As fo igs, ts ductios uc lg (fo 1.5 to fou tis s lg) fo t siultios tgtd

towards those with low wage rates (i.e., simulations 1-4) rather than those targetedto tos wit low scoolig ttit (i.., siultios 5-8). T olidcgs i t Gii cofficits fo wg ts 0.03 to 0.04 fo t fousiultios wit low wg ts tgtd d 0.01 to 0.02 fo t fousiultios wit low scoolig tgtd. If t gol w ol to duc wgt o full ico iqulit, tus, it would b dsibl to tgt ffctivltos wit low wg ts. T qustio of ow to tgt tos wit low wgts fo itvtios to ics scoolig ttit, of cous, is cllg giv lif-ccl scoolig-igs squcig ptts.

Wage rate poverty headcounts: The same general point again holds, again notsupisigl, fo t wg t povt dcouts. Fo t siultios tgtdtowds tos wit low wg ts, t popotio of t popultio blow tlow cutoff of 400 psos p ou dop b 0.06 to 0.12 d t popotioblow t ig cutoff of 600 psos p ou dops b fo 0.00 to 0.14.Fo t siultios tgtd towds tos wit low scoolig ttit, tpopotio of t popultio blow t low cutoff of 400 psos p ou dopb 0.02 to 0.03 and the proportion below the higher cutoff of 1000000 pesosper ear drops b from 0.03 to 0.05. Though all four of the simulations directedtowds low wg t cipits v bout t s ipct o ducig twage rate Gini coefficient, the differ a fair amount with respect to their impactso t popotios blow t povt cutoffs. I pticul icsig scooligttit lo fo tos wit wg ts blow 400 psos p ou is siul-td to duc t olid popotio blow t low povt cutoff of 400psos p ou b 0.11 o 0.12 (siultios 1-3), wil icsig scooligttit b t gds fo ll tos wit wg ts blow 600 psos p

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How uc igt u cpitl policis /Jere R. Behrman 37

ou is siultd to duc t olid popotio blow t s lowpovt cutoff b ol bout lf s uc t 0.06 (siultio 4). O t otd t ltt siultio is uc o ffctiv t ducig t popotioblow t ig povt cutoff of 600 psos p ou (b 0.14) t t

fist t siultios (fo 0.00 to 0.06). Tis is itstig illusttio ofow ssitiv polic ffctivss kigs igt b to wic pt of t lowd of t wg t distibutio is of itst29.

3. Conclusions

Hu souc ivstts tgtd towds t low pt of wg t,igs o ico distibutios oft tougt to b jo s tougwic t psistt ig LAC iqulitis i gl, icludig tos i Cil,igt ffctivl b ddssd, wit cocoitt ffcts of ducig povt.

Previous and new benefit/cost estimates for a range of human resource invest-ts ptiig to difft spcts of ductio d lt/utitio, tougsubject to a number of caveats because of the problems in making such estimatesd ti ssitivit to lttiv ssuptios suc s gdig discout tsand the value of adverting mortalit, suggest that there are likel to be a numberof ig t-of-tu optios fo suc ivstts i LAC. Ts iclud dif-ferent dimensions of education, including pre- and post-school experiences andot just scoolig, d ub of possibl ig t-of-tu itvtios

in health/nutrition. These estimates suggest that there are opportunities that LACgovernments should evaluate in their own particular contexts, including thextt of t subpopultios fo wic dficits ipott d t tu ofdliv ciss. Tis is likl to ld to so ig t-of-tu optiosfo u souc itvtios.

Will suc u souc itvtios, if wll-tgtd, duc subst-till iqulit i t d povt gio? To ptill xplo tis qustio,t Cil 2004 SPS dt usd to xi t ipct of scoolig tti-t, t ost psid u cpitl ivstt (d o toug wici ipott pt ot itvtios suc s tos ltd to l cildood

lt d utitio wok), usig wg t d igs fuctios ttprobabl are optimistic about the impact of schooling (because the ignoresuc fctos s bilit bis d kt-lvl ffcts). Alttiv siultiossuggst sigifict ipcts of wll-tgtd icss i scoolig ttiton reducing inequalit and povert headcounts in schooling, earnings, and wagets. T lso illustt t dsibilit of tgtig dictl towds t out-co of itst (.g., towds tos wit low wg ts, ot low scoolig, iffull ico is of pi coc) dspit t possibl difficultis i doig so(sic wg xpics tpicll ot vld util ft ost popl v

29 Tis poit is closl ltd, of cous, to t qustio of wt povt su to us i.e., headcount versus povert gap versus povert depth measures within the Foster, Greerand Thorbecke (1984) measures. For simplicit in this paper I present onl the headcountsus, toug s pt of t lsis fo t pp ll t of t sus v bsiultd.

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How uc igt u cpitl policis /Jere R. Behrman 39

t old o t w tit sst fo t lst o ot t ti duigt 1981-2001 ti sp31.

Aot oud of t suv ws diistd i 2004, wic icludd scod wv fo pviousl suvd spodts, plus w suvs fo sub-

spl of idividuls ot ffilitd wit t socil scuit sst (idividulsv plod i t fol scto) d lso subspl of w tts itot AFP sst btw 2002 d 2004. I dditio ost of w lt dwlt qustios w itoducd fo t fist ti32. Accodigl, t 2004surve is representative of the entire Chilean population33. Furthermore in 2004,the research project received permission to merge responses to the sampledspodts wit diisttiv cods o psio cotibutios d igsi t PAyGO d AFP ssts sic 1980, dt o t outs of cogi-tio bods; d otl dt o ccout cgs i t idividul ivsttccouts, switcs btw AFPs, AFP coissios cgd, d ivsttreturns earned on all accounts in the AFP sstem. The surve data has also beenmerged with monthl Social Securit records, available since 198134. The 2004EPS ws t lst oud vilbl w tis pp ws witt fo t Dcb2006 woksop.

References

Aedo, C. and S. Nez (2001). The Impact of Training Policies in LatinAmerica and the Caribbean: The Case of Programa Joven. Processed,Gogtow Uivsit (M).

Ald, H., J.R. B, D. Ross, d R. Sbot (1996). T Rtus toEdogous Hu Cpitl i Pkists Rul Wg Lbo Mkt,Oxford Bulletin of Economics and Statistics 58: 1 (Fbu); 29-55.

Angrist, J.D., E. Bettinger, E. Bloom, E. King and M. Kremer (2002). Vouchersfor Private Schooling in Colombia: Evidence from a Randomized NaturalExpit,American Economic Review 92: 5 (Dcb); 1535-59.

Barro, R., J. and J.-W. Lee (2000). International Data on Educational Attainment:Updts d Iplictios. CID Wokig Pp 42. Cbidg, MA:

Ct fo Ittiol Dvlopt.Behrman, J.R., H. Alderman and J. Hoddinott (2004). Hunger and Malnutritioni d. B. Lobog, Global Crises, Global Solutions, Cbidg, UK:Cbidg Uivsit Pss; 363-420.

31 Ifotio o t todolog d xtt of t suv c b foud i Bvo (2004),Bvo et al. (2006) d Bvo et al. (2008). Mbs of t Ad Focs o policcovd b spt govt psio ssts w xcludd, s wll s v sll

pctg of t Cil popultio sidig i iccssibl o spsl popultd s(.g. islds).

32 A ub of t qustios w dptd fo t Uitd Stts Hlt d RtitStud (HRS) wit t ittio of povidig coss-tiol copisos.

33 Wigts vilbl to wigt to do splig popotios.34 Additiol ouds of t suv w diistd i 2006 d 2009 d t pls

to udtk fut ouds i t futu (s www.potcciosocil.cl).

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Th pct f nc jutnt /David Bravo, Jos A. Valderrama Torres 47

2. Methodological Issues

Although ideally the micoeconomic (household suveys) and macoeconomic

(Ntn Accunt) tttc hu b t, n pctc, th cntuctn f

National Accounts figues is not based on infomation fom elevant units (such huh), ng t u cpnc n th tttc. Sy,ravallion (2001), efeing to household consumption expenses, claims thatth fgu fng t th pt n ntn ccunt y b nhuh uy ut n, n th bt f c, ny cpnnt fth tkn nt ccunt.

These discepancies have led the National Accounts System fo 1993 to pointut tht th ut f huh nc uy hu b jut t c-pnt f ctn typc b t k th cptb wth th Ntn

Accuntng fgu. Th Cnb Gup (2001) h pnt ut tht t ncy t k th jutnt:

It undoubtedly causes considerable harm to users when two sets of statisticsknown as household income produce very different results which will, in

turn, have a significant impact on social policies. Despite this need, national

statistics offices rarely look to reconcile their results.

In an attempt to esolve this poblem and unde the assumption that the National

Accounting infomation offes moe tustwothy figues than household suveys,

a vaiety of methodologies have been developed to adjust the infomation to theNational Accounts figues. In any case, the methodologies depend substantiallyn th uptn f ch uth n tn t th u f ctn tht g t th tbutn f th u f th ffnc btwn th tt ncof households epoted by income suveys among the households o goupsf huh n th Ntn Accuntng. Th b ntn ctnu h bn ct wth th f huh nc, cptnby huh nc uc (wg-nng, f-pynt, tc.) thcbntn f th f huh nc n t cptn ccng

t ffnt uc.Ung th f tt huh nc gu, th pt wy fjutng cnt f cctng th fgu by utpyng cntnt fctcpnng t th t f huh nc f th huh n thnc ccng t Ntn Accunt n th gggt nc f thuy huh.

The methodology suggested by Altimi (1987) is athe moe elaboatednc t phz th cpnc by nc uc th cntn fth jutnt. At pp, whch th Ecnc Cn F LtnAc n th Cbbn (ECLAC) h b t ccutn, cnt f

jutng th nc f y huh ccng t t cptn, ungpcfc jutnt fct f y nc uc; npnnty f th f nc f th huh, xcpt n wht cpn t ppty nc,whch h z jutnt fct f 80% f th huh wth ncn hgh thn n f 20% f ch huh. Th jutnt fct byuc btn f ng th tt nc pt f y ctgy

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Etu Ecn, V. 38 - N 148

f nc f th Ntn Accunt wth th cpnng t th hu-h uy.

Altimi attibutes the diffeences between the household suvey and NationalAccunt t un-ptng f th uy ptcpnt, th unty

nunty, n u tht th unt b ct wthth typ f nc thn wth th f nc. It upp tht un-epoting fo each type of income can be estimated accoding to the discepancybtwn wht pt by th uy n wht pt by th NtnAccuntng fgu, wth th xcptn f th c wh th tt thnthe fist. If what is epoted in the suvey is highe than what is shown in NationalAccounting, and thee is no clea evidence of oveestimation due to design, thenth fgu hwn by th uy hu b ccpt tu.

Ung th At th, tw huh wth th f ncght ung ffnt jutnt n gntu f th typ f nc ffnt. Cnunty, th th ffct th tuctu f th nc t-butn n cn nc c nuty n pty, pnng n thcptn f huh nc n n th pcfc jutnt fct fch nc uc. Wht n bc c tht, whn cn n t fct, th ttnt f cpt nc tn t nc nuty,nc th jutnt n th ctgy c ut ny n 20% f th chthuh.

In addition to the selection of the pecentile fom which the adjustmentfct f th b (cpt nc) tp bng nut, th utnb

chaacteistics of this type of adjustment is the fact that its application supposescpnc wth th fwng uptn:

1. Tht th nc nf by th Ntn Accunt t t cb th f huh nc uy.

2. That the diffeences between both souces ae fundamentally due to poblemsf un-ptng (ny f th uy ptcpnt y thy h wincome than the one they actually do) and not to poblems of tuncation (thecht huh nt uy).

3. Tht th u f ctn tht w t tbut huh

income, at a macoeconomic level, to the (expanded) income of each house-h ptnng t th nc uy p (ccnc ).

Th ft uptn p tht th fgu f huh nc f thNtn Accuntng yt c t ty, nc thy c f wvaiety of souces and that thei design makes them necessaily compatible withth t f th cpnnt f th ccuntng yt. On th th hn, thcn uptn f t th fct tht huh uy ptcpnt pt nc thn thy y c n tht th th ny n bhn thcpncy btwn th tt huh nc pt by th uy nth nc pt by th Ntn Accunt.

Th n tht t u tht bth uc f xcty t th population. Nevetheless, in counties whee the eal ineuality in income disti-bution is so high that an extemely small faction of population paticipates with ntby hgh pptn f tt nc, t unky tht th fw ppn th nc pnt n th uy p. Th, bcu n th

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Etu Ecn, V. 38 - N 150

huh n th t ptnt pg tht cnttut c pnng3.It ut-pup uy tht p nftn but th ccnccntn f th cunty ffnt c ct, t t ptnt fcn-c, th nn n chcttc f pty n nc tbutn f

th huh. Atny, th uy pt n th cg n pf fthe beneficiaies of social pogams, thei monetay and non-monetay con-tbutn t huh nc whch ntc t c ct tht nt h cc t th b-ntn pg, whch k t pb tccut th t tnc htf. Such nftn gu th gnf nw pjct n ny fctn n bnft ctn yt t pth fcu f th tht h ct chct.

Th uy h bn pnt n th fwng y: 1985, 1987,1990, 1992, 1994, 1996, 1998, 2000, 2003, 2006 n 2009. Th c-sectional suvey implemented egulaly in Novembe by the Ministy of

Planning (MIDEPLAN). MIDEPLAN has usually hied the Univesity of Chilef th pnttn f th fwk n nc th t h bn cctth Ecnc Cn f Ltn Ac n th Cbbn (ECLAC) pnb f kng th jutnt f pn .

4. Assessing the Impact of the Income Adjustments in the CasenSurvey

4.1. T b ECLAC

Th jutnt by ECLAC t th uy cct t c ftw uc: nn-pn n nc ptng. T wth th cnpb, nftn f Ntn Accunt p by th Cnt Bnk fCh u n, n ptcu, n ttn f th pncp gggt f thnc n pnng ccunt f huh pp pcy f th tk.Th puttn pc hwn n Fgu 4.

Th ft tg f th jutnt pc th cctn f nftntht h bn tt, tht t y, th pp wh h c tht thyeceive some type of income, but that have not declaed the amount o the

cpnng tt. Th cctn pc n gnng typ fpn t th gup f pp wh y thy c ctn nc, but nt gn ny u.

Th gup cn n th pc:

1. Pp wh c thy py n ctgy ffnt t nn-pfy b n wh nt pt th nc c f nccuptn.

2. Pp wh c thy t n ctzn wh c pnnn wh nt pt th nc.

3. Huh tht nhbt th h tht thy wn n nt c thput nt.

3 This section is based on the methodological epots of the suveys caied out in 2003 and 2006

(Mpn, 2005 n Mpn 2006).

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Etu Ecn, V. 38 - N 152

Onc th b cct ccng t th nn-ctn f ctn n-

c, t pb t k th cpnng jutnt ccng t th

Ntn Accunt fgu. Th nc utp by ctn fct, tht

the income figues obtained by CASEN ae compatible with the infomation fo

th wh cunty n th Ntn Accunt Syt4.

Accng t th typ f nc, jutnt pp t b t

t th fwng:

S n wg

Inc f th py n f-py Sc cuty bnft Iput nt

Ppty nc

F ctg but th t, th jutnt pp cty, n th

ny unt t knw whch fct w u n th b t

t ch typ f nc. In th c f ppty/cpt nc th jutnt

n ccutng th tt cpt nc f th uy (nt, ntt

n n) n th cpncy btwn wht pt by CASEN n

th Ntn Accunt fgu (wy n p cpt t) ttbut t

th cpnt f utnu nc bngng t th t unt, n uch

wy tht th gp tbut pptny t th c utnunc.

The autonomous income consideed fo this pupose is the one that is

puy jut n t cpnnt, ncung ny th cpt nc

tht w c. Fny, th tn nc gn cpt nc

put t pp n th t unt, cct th u f th utnu

nc. F xp, f th 2006 fgu, th cpnt f nc f th

t unt w put n tn nc un th cncpt f cpt

nc f th unt f 0.035 t th utnu nc gt n

th uy.Tb 1 hw th ffnt u f th jutnt fct ccng t

th typ f nc. Tw chcttc tn ut. Ft, th bty th

y n cn, wth th xcptn f th put nt, th b

untt by th pp uy, whch why th jutnt fct

xc th unt. (In th c f ppty nc, th jutnt t,

whch xpn why th fct thn n).

4 Th cpn c ut t n g f p cpt nc, xp n tnt th nt pputn f th cunty, bcu n Ntn Accunt th nub f cpnt

f ch nc typ unknwn.

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Th pct f nc jutnt /David Bravo, Jos A. Valderrama Torres 53

TABLE 1CASEN, 1990-2006 ADJUSTMENT FACTOS

Wgn

S

Incf Sf-

pynt

ScScutyBnft

Ppty/CptInc

Iputnt

1990 1.208 1.980 1.473 0.129 0.6641992 1.071 1.992 1.633 0.067 0.5481994 1.071 1.513 1.435 0.064 0.4751996 0.990 2.043 1.398 0.064 0.4541998 1.004 1.955 1.347 0.069 0.4392000 0.957 1.826 1.471 0.054 0.4492003 1.000 1.976 1.145 0.028 0.437

2006 1.010 1.976 1.126 0.035 0.437

Source: Mpn.

4.2. R 2006

In this section we will eview the 2006 CASEN suvey to undestand the impactf th -ptng puttn n nc tbutn5. W ptcuyntt n ntgtng f th pg chct tht th puttn f

th pct nt f wn-hung wu uffcnty cpnt th g- ffct f th th jutnt. A w h n, n th ft n th n ttn n wht c n n th t th un-ptng,whch why th nt ffct n th tbutn unctn.

Additionally, by decomposing the figues fom these diffeent souces,w cn th nc f ch typ f puttn whn xpnng ttnuty.

4.2.1. Comparison between indicators with and without adjustment

Tb 2 hw th ntty f th p cpt huh nc tbu-tn t th jutnt t Ntn Accunt fgu. Th ut f th Gncffcnt nct tht th jutnt tt th nuty nx n 3.4pnt ( 7%) f th tt nc. Nth, w xpct, th t g-nfcnt chng ccu n th t-n f th tbutn, n ch n ncn nuty f up t 22% ( n th c f th c t n th tt nc).Th ny nct tht fct cnt n nuty cnunc f thjutnt t th ntn ccunt fgu th t f nc c f thn ccuptn. Th cn b xpn by th fct tht f-py wk

ae ove-epesented in the fist 10%, and they ae pecisely the people fo whomincome is almost duplicated. This is why the atio deceases afte the adjustment cp wth th t wthut th jutnt.

5 A th tt f 2006 w pp t 2003, wth ut.

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Th pct f nc jutnt /David Bravo, Jos A. Valderrama Torres 55

4.2.2. Changes along the distribution

A cn b n n Fgu 5, th n nt ttn t th t-n f

th tbutn u t th jutnt. In th c f nc f th n c-

cupation and autonomous income (labo-elated and non-labo elated income),

th wy n ttn, pcy n th w n up t th 20 p-

cnt n n th upp n f th 80 pcnt nw. In bth c th

ttn hgh thn 20%.

Th pctu f tt nc (utnu nc pu nty tnf

plus imputed ent) is somewhat diffeent: in the fist centiles the National

Accunt Ajutnt c th nc; up t th 40th cnt th n

gnfcnt chng by th jutnt; hw ttng f th cnt

th jutnt nc th nc chng u n 30%. F tht wcan conclude that the net effect of the imputation on the vaiable is a eduction in

th nc f th pt (up t th 5th pcnt f tbutn), n ttn

t th nc f huh ct n th w- pt f th tbutn

cu (btwn th 5th n 40th cnt) n n nc n th nc f th

wh n (cnt 40 n upw).

FIGUE 5

PECENTAGE OF DISCEPANCY BETWEEN DISTIBUTIONSWITH AND WITHOUT ADJUSTMENT

Note: Th ccutn xcu nc f tc wk wh n th py hu.Incu th pb z tht ght b pnt n huh.

Mn ccuptn ncAutnu ncTt nc

0 20 40 60 80 100

Cnt f p cpt nc

%c

hangeofaveragei

ncome

60

40

20

0

20

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Etu Ecn, V. 38 - N 156

If we conside that total income incopoates the imputed ent which is

c wth th jutnt n th nc tht nc wth th

jutnt, th th cncun t b . In th w pt f th

total income distibution pedominates the effect of the downwad adjust-

nt, pbby xpn by -ptng f th u f th put nt

by uch huh; wh n th hgh pt f th tbutn th ffct

xc by th puttn f th b, pcy f th ppty

nc ctgy, tht, w h puy tt, put ny t pp

f th t unt f nc.

An tn t f th gph tht tn ut th U f hwn

by th utnu nc cpncy cu n th n ccuptn nc

discepancy cuve. This can be explained by the afoementioned ove-pesentation

f f-py wk n th ft cnt wh, w h n, thnc ny ub by th jutnt wh th nc f wg n

ccy chng.

4.2.3. Impact according to the significance of each component of total

income

The pogessive o egessive chaacte and the significance that each income

uc h n nc nuty cn b fz by th cptn p-

p by Shck (1982).Accoding to this poposal and consideing income as Y and its components

ae expessed geneically by Yf

, whee Y Yf

= , an indicato of the contibution

f ch cpnnt t nuty gn by:

Sf f

Y

Y

f=

*

Whee f is the coelation coefficient between facto Yf , and total income

Y and denotes the standad deviation. Similaly, Sf

is the egession slope

fYf

n tt nc Y, wh t y t hw tht Sf= 1. Cpnnt

with a positive value fo Sf

have a de-equalizing contibution meanwhile

cpnnt wth ngt u h n uzng cntbutn6.

Cnng th u t hn, th xc wu b t tbh th gn

n th z f th cntbutn f th ffnt typ f puttn ttng

f th fwng ntty:

Y Y Dif Dif Dif Dif Dif f o

= + + + + +1 2 3 4 5

6 F t f th cptn, Shck (1980). Th ppnx utn thcptn f tw uc f nc.

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Etu Ecn, V. 38 - N 158

4.3. E

Consideing that the least impotant components when explaining ineuality

ae social secuity and othe incomes and that we cannot ecove the databases

f f th y n th pct f th b n th nuty f tt

nc, w h xcu th tw fct whn cyng ut n ny f

th tn n th 1990-2006 p

Fgu 8, 9 n 10 hw th ny. Th cpn btwn th n-

ct hw tht, wth th xcptn f th Gn Cffcnt whch kp

cntnt ffnc (7% n g), th chng nt yttc n

tht th g nc hw th t ptnt chng (29% n 1990 n

6% n 2000).

In th c f pty, th htgnu bh: bf 1996 th

effect of imputations on both indicatos without adjustment is an undeestimation

tht ch t hght u n 1990 f th c f pty, y n whch

th nct untt by but 25%. Aft th y th nct

oveestimated eaching its highest value in 2000 fo the indigent people categoy

wth 15%. In ht, nt hng ny puttn wu h fct

bgg uctn n th f pty tht th pnty knwn.On th th hn, Fgu 10 hw tht th cpnnt f nc wthut

adjustment has an inceasing paticipation when explaining total inequality,

gng f 63% f tt nuty n 1990 t 79% n 2006. At th t,

th ptnc f th puttn n b-t nc h c

ng f ccuntng f 27% n 1990 t 19% n 2006.

FIGUE 7IMPOTANCE OF THE IMPUTATIONS IN THE 2006 GAP.

Shck Dcptn

Note: Oth nc ncu f-cnuptn, wthw f pft, pu wk n thnc.

120%

90%

60%

30%

0%

30%

In ch Sc Iput Cpt Oth Ttb cuty nt nc nc gp

nc bnft

100%

15%8%

10%

1%

86%

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Th pct f nc jutnt /David Bravo, Jos A. Valderrama Torres 59

FIGUE 8INEqUALITY AND AVEAGE INCOME, ATIO BETWEEN ADJUSTED

VAIABLES AND THOSE WITHOUT ADJUSTMENT

FIGUE 9POVETY, ATIO BETWEEN ADJUSTED AND UNADJUSTED VAIABLES

1990 1992 1994 1996 1998 2000 2003 2006

1990 1992 1994 1996 1998 2000 2003 2006

140%

130%

120%

110%

100%

1.2

1.1

1.0

0.9

0.8

0.7

Ag. nc

Th

Gn

Dc 10/1 t

Cf. tn

Ingnc Pty

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Etu Ecn, V. 38 - N 160

4.4. C bw b P C

This section compaes the distibutions of income in Peu and Chile using the thgy, tht t y ung p cpt huh nc7 jutny f nn-pn n ny b.

Th t ptnt ut pp n th f nuty.Aung tht th f th th cunt n Fgu 3 nt chng,

Ch bc n f th cunt wth w nuty n th gn, -

tkn ny by Vnzu n Ct c, wh Pu nc t fnuty ng f cunty wth w f nuty t n tht cnb cn n th ng f th gn nkng. Du t th fct thtthe same methodology is used fo both counties, Chile and Peu exchangeptn n tn t th nkng pnt by ECLAC n t tttc 2007ybk ( Fgu 3 n 11).

Table 3 shows the levels of inequality accoding to the souces of totalnc. F th tb w cn w th fwng cncun: t c thtinequality of income eceived by self-employed wokes is highe in Chilethn n Pu. Th tutn th ppt f wg. Whn w cn th nt

ffct f bth uc w tht nc nuty f th n ccuptn w n Ch thn n Pu.

7 In Peu the official infomation on povety and inequality ae estimated fom the National

Huh uy (ENAHO) ung th p cpt cnuptn th b f ny;

nth th uy w th nc p cpt t b ccut.

FIGUE 10IMPOTANCE OF THE COMPONENTS FO TOTAL INCOME IN THE 1990-2006 PEIOD

Shck Dcptn

1990 1992 1994 1996 1998 2000 2003 2006

Inc wthut jutnt

Iput nt

In ch b nc

Cpt nc

63.466.6 65.6 68.3

70.179.7 75.0 79.4

27.130.4 29.4 29.2

26.217.4

24.519.4

11.2

6.1 6.0 5.96.4

5.1 2.7 3.4

1.7 3.1 0.9 3.4 2.7 2.3 2.2 2.2

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Etu Ecn, V. 38 - N 162

InctPu

(A)

Ch

(B)

Dffnc

(B) (A)

Gn cffcnt

Sf-pynt Inc 0.74 0.89 0.15

S 0.73 0.61 0.13

Mn Occuptn Inc 0.59 0.56 0.03

+t 0.61 0.74 0.13

Autnu Inc 0.52 0.52 0.00

+Sub 0.70 0.82 0.12

+Iput nt 0.72 0.61 0.10

Tt Inc 0.511 0.488 0.02

Cffcnt f Vtn:Sf-pynt Inc 2.57 4.01 1.44

S 2.20 1.64 0.56

Mn Occuptn Inc 1.65 1.54 0.11

+t 2.19 4.03 1.84

Autnu Inc 1.52 1.71 0.19

+Sub 4.31 2.63 1.68

+Iput nt 2.42 1.54 0.88

Tt Inc 1.480 1.550 0.07

Th nx:

Sf-pynt Inc 1.17 2.03 0.86

S 1.11 0.73 0.39

Mn Occuptn Inc 0.67 0.61 0.06

+t 0.80 1.27 0.47

Autnu Inc 0.53 0.56 0.02

+Sub 1.11 1.52 0.41

+Iput nt 1.09 0.73 0.36

Tt Inc 0.515 0.487 0.03

Note: FGT th Ft-G-Thbck tc, gnz u f pty. Ifz: ptyn;N: th nub f pp n th cunty;H: th nub f p (th wth nc t bwz);yi : nu nc; = ntty pt. Thn:

FGTN

z y

z

i

i

H

=

=1

1

FGT0: FGT f= 0 (th Hcunt t pty t u n Ch).FGT1: FGT f= 1 (th g pty gp ung ntnty f pty).

FGT2: FGT if= 2 (an index that combines infomation on both povety and incomenuty ng th p).S Ft, G n Thbck (1984).

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Th pct f nc jutnt /David Bravo, Jos A. Valderrama Torres 63

5. Discussion and Conclusions

Th pp h hwn tht nuty nct n pty n Ch oveestimated by vitue of the imputations fo adjustment to National Accounts

fgu. In th c f nuty, th ttn ny 22% ( n thc f th t btwn th c n 2006), wh th t w-knwnnct, th Gn cffcnt, tt n but 7%, n ttntht cntnt n th p 1990-2006.

In th c f pty, bth xt n nn-xt, th ttn but 10% n 4% pcty, whch cn b xpn by th wnwjutnt f th u f put nt, th ny b tht h n put-tn n th ctn (n tht ccng t th ut wu h hgh ntpct n th huh wth w nc). Atny, pty thny chcttc tht h py htgnu bh n th 1990-2006 p: bf 1996, whn th f pty w hgh thn th nb n th t fw y, th f pty w untt nft 1996 thy tt.

Th w u t cncu tht f th h bn n jutnt ppt nc, th uctn f th pty n Ch n th p un nywu h bn pnunc. Th g nc w ttn ch y nyz n th b xpnc th t ptnt t-py chng, gn tht t f n ttn f 29% n 1990t 9% n 2006.

Once the stuctue of the imputations accoding to national accounts figuesw knwn, th CASEN fgu w cntuct n th th-gy w pp bth t Pu n Ch t btn pty n nutynct tht wu nb n ut ntntn cpn. Th utnct tht nc nuty hgh n Pu thn n Ch.

It ptnt t pnt ut tht thugh w cn c th gn nf-tn, whn n f th jutnt fct n b n n thjutnt knwn (whch nt hppn n ctn y), f th k ftnpncy n ffcncy, nc th pc f cy nt nggb, thffc tb hu ncu th nn-jut b. Th pcy

impotant when making intenational compaisons, since the pactice of incomejutnt nt un.

Futhemoe, the advantage of conguence between the mico and the macoccunt cn b k f t t tw n: Ft, chng n th cindicatos can eflect the adjustments applied and not necessaily the eal dynam-ics of the socioeconomic indicatos. Second, the fact that the National Accountsfgu n th Huh Suy f t ffnt un nc th pf pp wth hgh nc typcy untt n ny cnntnhuh uy (tunctn n th tp-n f tbutn), k jutntbetween the maco and the mico accounts necessay. Since this euies specificknwg f wht pt f th cpncy f th Huh Suy wth thNtn Accunt cpn t ub-ptng n wht pt cpn ttunctn n nc th nt knwn, th ctn t th huh n thuy f th tt cpncy t n -cctn f nc n pt f th huh uy.

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Ei Enm, V. 38 - N 168

humano paa analiza cmo Oportunidades afecta los ingesos futuos de los

paticipantes del pogama. Simlamos de manea no-paamtica las disti-

bciones de ingeso, con y sin el pogama, y pedecimos qe Opniamenta los ingesos medios ftos peo slo tiene efectos modestos en la

tasa de pobeza y la desigaldad de ingesos.

Pb v:Opni, Capital hmano, Escolaidad, Sald, Pobeza,Desigaldad.

JEL Cifiin:H50, I00, J24, O12, O54, O15.

1. Introduction

In recent years, governments in many Latin American countries have adopted

niin h nf (CCT) pm pimy y f viinpvy n imin invmn in hmn pi. Th pm ypiypvi h n p fmii if hy n hi -iib hin h n bii f y viiin hh ini. Mxi n Bzifi p CCT pm in h 1990. Sin hn, pm wih imiinniv hv bn in in Anin, Chi, Cmbi, C Ri, ESv, E, Hn, Ni, P n Uy1.

Th Mxin Opotnidades pm (fmy PROGRESA) wiy v in bh xpimn n nn-xpimn vinin. In h fi w y (1998-1999) f i impmnin in ,the program was evaluated using a place-based social experiment that randomized

506 vi in f h pm. Th xpimn mnstatistically significant program impacts on increasing schooling enrollment

n inmn, in hi b, impvin hh n niin mn in pvy2. Py n h bi f h bv piiv pmimp, h Mxin vnmn xpn h pm in bn in

2002. By 2005, h pm v fiv miin fmii n h n nnb f U.S. $2.1 biin. A nn-xpimn vin i in bn fn iiy inifin pm imp imi in mni h fn in .

A n, pvi vin i f h Opotnidades pm -mented the programs short-term impacts. This paper takes as a point of departure

h bv imp n in n niin n im h ff fthese changes on the future earnings distributions of the children currently

piipin in h pm. Th qin w ni i hw h pm

1 Some similar programs also have been introduced in Asian countries, such as Bangladesh

n Pkin.2 See, e.g., Schultz (2000,2004), Gertler (2000), Behrman, Sengupta and Todd (2005),

Pk n Skfi (2000), Bmy n Skfi (2003), T n Wpin (2006)n Fij, Bn n A (2006).

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Ei Enm, V. 38 - N 170

O mpii nyi i b n h fi wv f h Mxin FmiyLife Survey (MxFLS-1) which was collected in 2002. The survey collected

f mmb f 8,440 hh n in infmin b bforce participation, income for both primary and secondary jobs (including

f-mpymn), in, n hh. I nin m f fmiybkn, h w im pm in. O fin ny bmp f 5,171 inivi 25 40.

Thi pp p fw. Sin w ib h nnpmiimin mh n hw w p n i y hw Opotnidadesaffects employment and the overall earnings distribution. Section three describes

the Mexican Family Life Survey and our analysis samples. The empirical results

pn in in f. Sin fiv n.

2. Methodology for Simulating Program Effects on PopulationEarnings Distributions

Th imin mh h w y pm ff n ninand employment outcomes is adapted from a wage decomposition method

iiny pp in DiN et al. (1996). Thi y h mh invi h ff f iniin n b mk f n hn inh U.S. w iibin v im. Thi pph wi h v w

niy im t, f w tw=

( | ) in m f h niin w nii, whniinin i n f b mk iniin f,z, wh ffn nin hy nyz:

f w t f w z t f z t dzw wz z( | ) ( | , ) ( | ) .=

In hi y,z in vib iniin nin , ini ,n whh h w f bv bw h minimm w. Cnfwage densities are constructed by replacing f z tz ( | ) by a different hypotheticalniin niy, g z t

z

( | ).We apply the DiNardo et al. (1996) method to simulate earnings densities with

and without a program intervention, where the program intervention changes the

iibin fz. W xn h mh n f imn nyi fbh mpymn n nin by pmiin h nin iibin hv m pin z nnpiipin. In hi in, w fi ibh imin pph in n m, n hn hw i ppi vinh ff f h Opotnidades pm.

2.1. B

Dn m m f in (nin) byy n fin i niyin m f i niin niy (niin n m bv h-iix):

f y f y x dx f y x f x dxx x

( ) ( , ) ( | ) ( ) .= =

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Th n-m ff f hmn pi /Doglas McKee, Peta E. Todd 71

Spp h h pm invnin hn h iibin fxfm

f(x) to f x( ) but that the distribution ofy conditional on xstays the samef y x f y x( | ) ( | )=( ) . Th nw nniin iibin fy w b ivn

by:

f y f y x f x dxx

( ) ( | ) ( ) .=

We wish to simulate the effect of the program intervention on the outcome

y i p hh hnin x. F xmp, pp h h vib

x represents years of schooling attained and height and that the program

intervention increases schooling attainment and height by some amount,

i.. x x x= + . Spp h w hv mp f iz n wn fm h

nniin niy,f(x). If w knw

xw n n f h inivix xi i xi

= + . We can simulate the post-program earnings density f y( ) at a

piny0 by h v:

( ) ( | )

( ,

f yn

f y x x

n

f y x

x Xi i x

i

i0 0

0

1

1

= = +

=

ii

ix Xf x

i

)

( ),

wh ( , )f y xi

n ( )f xi

nnpmi im f h nniinnii mp fm h iin (p-pm) mp:

( , )f y x

nK

y yK

x x

iy x j

nj

y

j i

x0

1

01=

=

=

=

( )

.

f x

n

Kx x

i

x j

nj i

x

1

1

y n x bnwih h m ify h qimn fnin kn niy imin4.

Th MxFLS ifi mp, mpin wih qi

wih h mp bk ppin ppin. Inpin mpin

weights into the simulation method is straightforward. Assume each observation

has a sampling weight, i, and that the weights are scaled so that i n = . Thewih n b inp in h imin f f y( ) fw:

( )

( , )

( ),f y

n

f y x

f xi

x x

i

ii

=

1

4 W qi ax 0,ay 0, n n ayaxn.

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Th n-m ff f hmn pi /Doglas McKee, Peta E. Todd 77

f e h x

na a aK

e e

ae h xe h x i

ni

e, ,

( , , )0 0 0

1

01=

=

K

h h

aK

x x

a

i

h

i

x

0 0 ,

wh ae, ah n ax h bnwih hi. In nyi bw, w Gin kn n ppy Sivmn f nivi iibin hdimension of the data (Silverman, 1986). We also experimented with otherbnwih hi n fn min w qi b. T imh niin niy f y e h x( | , , ), bv h h niin niy nb xp h i f w jin nniin nii:

f y e h xf y e h x

f e h x( | , , )

( , , , )

( , , ),=

h f whih n b nnpmiy im by n kn niyim.

Th nvn f pinwi nnpmi niy im wwn h imniniy in, pbm knwn h f imn-sionality. However, the proposed estimators average over the nonparametricim n hf nv f .

3. Description of the Analysis Subsamples

W nyz fm h Mxin Fmiy Lif Svy (MxFLS-1), whihconducted interviews with 8,440 households in 150 communities in 2002.Every household member age 15 or older was interviewed, yielding about38,000 inivi inviw. 16 f Mxi 32 /ii pn(roughly 70% of the population resides in these states). Weights are provided tomk h mp niny pniv. Th vy in mphnivinfmin n mpymn n inm f bh pimy n ny jbin h fm n infm . Th vy in infmin nhousehold structure, education, and health. The key variables used in simulating

nf m inm, mpymn, in v, hih nlabor market experience. Appendix A describes in more detail how we constructh f h vib fm h .

Tb 1 pn ipiv ii f w min nyi mp:A mn n wmn 25 40. Ab 10% f mn n 64% f wmnreport zero labor income. Mean monthly earnings for males are 3,945 pesos andf wmn 1,140 p, wh h mn in z f nnwk7. Thaverage education level for men is 8.8 years, which is about one year higher thanh v f wmn f 7.7 y. Mn n v 166 nim ,

and women are on average 153 centimeters tall. The Gini coefficient for earnings

7 In 2002 h v iy xhn w 1 USD q 9.68 p. B mnmb f h h nin v m b i, w impmn imminp n mi inivi wh p inm hih hn 40,000 p/mnh. Thi pn 9 f 5,180 bvin h p 0.2%.

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Ei Enm, V. 38 - N 180

Table 2 presents descriptive statistics for these variables. In the sample, 37%of children participate in Opotunidades. The program is most active in the poorersouthern states (Chiapas, Oaxaca, Guerrero, Michoacan, and Puebla), where 31%f h hin iv. On v, h hin in h mp hv mh wih

4.7 y f hin in n fh wih 5.2 y. Ony 46% f hhin iv in hh wih in pmbin. Tb 3 hw h imffiin fm h pbi m f pm piipin10. A xp,pn in, in pmbin, n h pn f yn hin in hhh hihy inifin pi f pm piipin.

TABLE 2DESCRIPTIVE STATISTICS FOR VARIABLES USED IN TARGETING ANALYSIS

Chin A 9-12

Chin 9-12

Piip in Opotnidades 0.37(0.05)

Mh hin 4.7(0.28)

Fh hin 5.2(0.21)

Mximm f pn hin 6.1

(0.22)Hh h in pmbin 0.46(0.05)

Nmb f hin 0-10 in hh 2.1(0.08)

Liv in P Shn S 0.31(0.07)

Smp Siz 1699

Chip, Ox, G, Mihn, Pb.

Nx, w mp ppniy (h pi pbbiiy f biniib n piipin in h pm) f h 25 40 in him pbi m ffiin n m f hi fmiy bkn(pn in, hii f h hh whn hy w 12,n n ppximin f h nmb f hin 0 10 in h hh h im). Ahh h in fOpotnidades i b n viin vib, w hv i h nyi h b vib inh f bh hin n , whih fny in h mj

10 The participation model is estimated only for children in rural and semi-urban areas,

b in 2002 (h im f in) h pm h n bn inifinyxn bn . Th nin infmin pinin inviw wih hparents of 1,970 children age 9-12 in rural areas. After dropping observations with missing

vib, w f wih 1,699 bvin.

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Ei Enm, V. 38 - N 182

TABLE 4DESCRIPTIVE STATISTICS FOR MEN AND WOMEN, AGE 25-40, BY PROJECTED

OPOrTuNIDADESPARTICIPATION

Mn Wmn

40%T

60%Nn-

40%T

60%Nn-

Mh hin 1.9(0.14)

4.4(0.22)

1.9(0.12)

4.1(0.21)

Fh hin 2.7(0.17)

5.1(0.26)

2.6(0.13)

4.6(0.25)

Mx Pnin

3.2(0.19)

5.7(0.24)

3.2(0.14)

5.3(0.24)

In pmbin 0.18(0.03) 0.85(0.03) 0.18(0.03) 0.80(0.03)# hin 0-10in hh

2.5(0.12)

1.1(0.07)

2.5(0.10)

1.2(0.06)

Livin in phn

0.34(0.06)

0.11(0.05)

0.35(0.06)

0.11(0.04)

Mn mnhynin (in 1000f p)

3.3(0.28)

4.3(0.25)

0.7(0.07)

1.5(0.20)

Shin 7.4(0.25)

9.6(0.30)

6.3(0.20)

8.7(0.22)

Hih 164.4(0.56)

166.9(0.55)

152.1(0.50)

154.3(0.43)

Expin 19.5(0.40)

16.1(0.42)

20.7(0.26)

16.9(0.33)

Smp Siz 867 1083 1629 1592

Th mn v in Tb 4 hw h h p i vnthan the non-target group. In particular, mean monthly earnings are 3,300 pesosp mnh f mn n 4,300 p p mnh f nn- mn.T wmn n xp b hf (700 p p mnh) h b inm

f nn- wmn (1,500 p p mnh). B h i i bnivp in h w nin iibin, hwn in Fi 1. Th p pnib mn b inm whi h bm pn ib wmn. Thi in in h pn i nnpmi im f h niy f piivearnings, while the two dashed lines correspond to the densities of positivenin in h n nn p12. Ain, h mn f h h subsample is clearly lower than that of the nontarget, but a substantial proportionf h p n xp iv nin bv h ppin mnn ppin f h nn p iv vy i inm13.

12 Th niy h bn by f f 0.4 n h nn- by f f 0.6 h h hy p q h ppin niy.

13 The fraction of men receiving no labor income differs very little between the target

(11.4%) n nn (10.6%) p, b h iffn i y qi mnwmn wh 71% f wmn iv n b inm mp 58% f hnn- p.

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Th n-m ff f hmn pi /Doglas McKee, Peta E. Todd 83

FIGURE 1DENSITIES OF INCOME FOR MEN AND WOMEN

Soce: MxFLS 2002.A nii nnpmiy im in nn-z v f inm.

0.2

0.18

0.16

0.14

0.12

0.1

0.08

0.06

0.04

0.02

00 5 10 15 20

Mens Monthly Income (1000s pesos)

Total Sample (Men)

Scaled Target SubsampleScaled Non-target Subsample

0.25

0.2

0.15

0.1

0.05

00 5 10 15 20

Womens Monthly Income (1000s pesos)

Total Sample (Men)Scaled Target Subsample

Scaled Non-target Subsample

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Th n-m ff f hmn pi /Doglas McKee, Peta E. Todd 85

FIGURE 2DENSITY OF MENS INCOME CONDITIONAL ON SCHOOLING AND HEIGHT

Soce: MxFLS 2002A nii nnpmiy im in nn-z v f inm.

inmn in h bn f h pm xpin ivy inin inm f h pm, i i n h h h p f h p xpin h bnfi. Th n f h mpn hpm ff n inqiy i h in hin fm p bknny impfy f w-nin , b f bni in-nin mbiiy.

0.25

0.2

0.15

0.1

0.05

0

0.3

0.25

0.2

0.15

0.1

0.05

0

Monthly Income (1000s pesos)

Schooling (years)0

1015

02

46

810

12 14

5

20

1618

Monthly Income (1000s pesos)

Height (cms)0

1015

5

20

180

140145

150155

160165170

175

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Th n-m ff f hmn pi /Doglas McKee, Peta E. Todd 87

TABLE5A

SIMULATEDEF

FECTSOFOPOrTuNIDADES

IMPACTSONINCOMEDISTRIBUTION

BASED

ONNONPARAMETRICEARN

INGSDENSITYESTIMATIONS

Men,Age2

5-40

Original

Schooling

(+0.6yrs

)

Height

(+1cm)

Schooling

(+0.6

yrs)

Height

(+1cm)

Schooling

(+3yrs)

Height

(

+3cm)

(a)

(b)

(c

)

(d)

(e)

Proportionwith

zeroearnings

0.098

0.099

0.099

0.099

0.097

0.101

Meanearnings

3.931

3.944

3.961

3.974

4.255

4.037

Std.Dev.earnings

4.382

4.382

4.455

4.456

4.857

4.631