Conditional Cash Transfers, Schooling and Child Labor: Micro-Simulating Bolsa Escola 1

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1 Frst Draft: September 00 Ths Draft: May 003 Condtonal Cash Transfers, Schoolng and Chld Labor: Mcro-Smulatng Bolsa Escola Franços Bourgugnon, Francsco H. G. Ferrera and Phllppe G. Lete JEL Codes: Key Words: Abstract: I38, J3, J, J4 Condtonal Transfers; Demand for Schoolng, Chld Labor Cash transfers targeted to poor people, but condtonal on some behavor on ther part, such as school attendance or regular vsts to health care facltes, are beng adopted n a growng number of developng countres. Even where ex-post mpact evaluatons have been conducted, a number of polcy-relevant counterfactual questons have remaned unanswered. These are questons about the potental mpact of changes n program desgn, such as beneft levels or the choce of the means-test, on both the current welfare and the behavoral response of household members. Ths paper proposes a method to smulate the effects of those alternatve program desgns on welfare and behavor, based on mcroeconometrcally estmated models of household behavor. In an applcaton to Brazl s recently ntroduced federal Bolsa Escola program, we fnd a surprsngly strong effect of the condtonalty on school attendance, but a muted mpact of the transfers on the reducton of current poverty and nequalty levels. We are grateful for comments receved from Kaushk Basu, Martn Ravallon, Zafrs Tzannatos, two anonymous referees and from partcpants at the WB/UNICEF/ILO conference on Chld Labor (May 00) and at the Latn Amercan Meetngs of the Econometrc Socety n São Paulo (July 00). Bourgugnon s at Delta and The World Bank, Pars. Ferrera and Lete are at The World Bank and the Pontfíca Unversdade Católca do Ro de Janero (PUC-Ro). The vews expressed n ths paper are those of the authors, and do not necessarly represent the vews of the World Bank, ts Executve Drectors, or the countres they represent.

2 . Introducton Durng the 990s, a new brand of redstrbuton programs was adopted n many developng countres. Although local versons vared, programs such as Food for Educaton n Bangladesh, Bolsa Escola n Brazl, and Progresa n Mexco are all meanstested condtonal cash transfer programs. As the name ndcates, they share two defnng features, whch jontly set them apart from most pre-exstng programs, whether n developng or developed countres. The frst of these s the means-test, defned n terms of a maxmum household ncome level, above whch households are not elgble to receve the beneft. 3 The second s the behavoral condtonalty, whch operates through the requrement that applcant households, n addton to satsfyng the ncome targetng, have members regularly undertake some pre-specfed acton. The most common such requrement s for chldren between 6 and 5 years of age to reman enrolled and actually n attendance at school. In Mexco s Progresa, addtonal requrements appled to some households, such as oblgatory pre- and post-natal vsts for pregnant women or lactatng mothers. The mplementaton of these programs has generated consderable nterest, both n the countres where they took place and n the nternatonal academc and polcy-makng communtes. Accordngly, a great deal of effort has been placed n evaluatng ther mpact. There are two types of approach for evaluatng the effects of these programs on the varous aspects of household welfare that they seek to affect. Ex-post approaches consst of comparng observed benefcares of the program wth non-benefcares, possbly after controllng for selecton nto the frst or the second group f truly random samples are not avalable. An mportant lterature has recently developed on these technques and many applcatons to socal programs have been made n varous countres. 4 3 For verfcaton and enforcement reasons, the means-test s often specfed n terms of a score based on responses to a questonnare and/or a home vst by a socal worker. In some countres, the score s calbrated to be approxmately equvalent to a pre-determned level of household ncome per capta. See Camargo and Ferrera (00) for a dscusson of the Brazlan case. 4 Ths lterature reles heavly on matchng technques, and draws extensvely on the early work by Rubn (977) and Rubn and Rosenbaum (985). For a survey of recent applcatons, see Heckman and Vytlacl (00). For a study of the effects of the Food for Educaton program n Bangladesh, see Ravallon and

3 Ex-ante methods consst of smulatng the effect of the program on the bass of some model of the household. These models can vary wdely n complexty and coverage. Arthmetc smulaton models smply apply offcal rules to determne whether or not a household qualfes for the program, and the amount of the transfer to be made, on the bass of data commonly avalable n typcal household surveys. More sophstcated models nclude some behavoral response by households. Ex-ante and ex-post evaluaton methods are complements, rather than substtutes. To begn wth, they have dfferent objectves. Ex-post methods are meant to dentfy the actual effects of a program on varous dmensons of household welfare, by relyng on the drect observaton of people engaged n the program, and comparng them wth those same dmensons n a carefully constructed comparson group, selected so as to provde a sutable proxy for the desred true counterfactual: how would partcpants have fared, had they not partcpated?. In some sense, these are the only true evaluatons of a program. Even when comparson groups are perfectly belevable proxes for the counterfactual, however, ex-post evaluatons leave some polcy-relevant questons unanswered. These questons typcally refer to how mpact mght change f some aspect of the program desgn such as the level of the means-test; the nature of the behavoral condtons mposed; or the level of the transfer benefts - changes. It s dffcult enough to obtan an actual control group to compare wth a sngle program desgn n realty. It s lkely to be mpossble to test many dfferent desgns n expermental condtons. Exante methods are valuable tools exactly because t s easer to experment on computers than on people. These methods are essentally prospectve, snce they rely on a set of assumptons about what households are lkely to do when faced wth the program. They also permt drect counterfactual analyss of alternatve programs for whch no ex-post data s avalable. Thus, they are ndspensable when desgnng a program or reformng exstng ones. Wodon (000). A number of mportant studes of Progresa were undertaken under the auspces of the Internatonal Food Polcy Research Insttute (IFPRI). See, n partcular, Parker and Skoufas (000) and Schultz (000).

4 3 Smulaton models of redstrbuton schemes based on mcro data sets are wdely used n developed countres, especally to analyze the effect of the numerous and often complex cash transfer nstruments found n those countres. Gven the progress of drect cash transfers n developng countres, buldng the same type of models n developng countres may become necessary. 5 However, the specfc behavoral condtonalty that characterzes these programs requres modfcatons, and a focus on dfferent aspects of household behavor. The present paper takes a step n that drecton by proposng a smple ex-ante evaluaton methodology for condtonal means-tested transfer programs. We apply the method to the new federal desgn of Bolsa Escola, nbrazl,andweare concerned wth both dmensons cted by the program admnstrators as ther objectves: () the reducton of current levels of poverty and nequalty; and () the provson of ncentves for the reducton of future poverty, through ncreased school enrollment among poor chldren today. The paper s organzed as follows. Secton descrbes the Bolsa Escola program, as t was launched at the federal level n Brazl n 00. Secton 3 presents the smple econometrc model used for smulatng the effects of the program. Gven the condtonalty of Bolsa Escola, ths model essentally deals wth the demand for schoolng and therefore draws on the recent lterature on chld labor. The estmaton of the model s dealt wth n Secton 4, whereas the smulaton of program effects and a comparson wth alternatve program desgns are dscussed n Secton 5. Secton 6 concludes.. Man features of the Bolsa Escola program The Brazlan natonal Bolsa Escola program was created by a law n Aprl 00, wthn the broader context of the socal development ntatve known as Projeto Alvorada. It s the generalzaton at the federal level of earler programs, whch were poneered n the Federal Dstrct and n the cty of Campnas (SP) n 995, and later 5 See, for nstance, Hardng (996). On the need for and dffcultes wth buldng the same type of models n developng countres, see Atknson and Bourgugnon (99).

5 4 extended to several other localtes. 6 The law of Aprl 00 made these varous programs unform n terms of coverage, transfer amounts and the assocated condtonalty. It also provded federal fundng. Yet, the montorng of the program tself s left under the responsblty of muncpal governments. The rules of the program are rather smple. Households wth monetary ncome per capta below 90 Reas (R$) 7 per month whch was equvalent to half a mnmum wage when the law was ntroduced - and wth chldren aged 6 to 5 qualfy for the Bolsa Escola program, provded that chldren attend school regularly. The mnmum rate of school attendance s set at 85 per cent and schools are supposed to report ths rate to muncpal governments for program benefcares. The monthly beneft s R$5 per chld attendng school, up to a maxmum of R$45 per household. Transfers are generally pad to the mother, upon presentaton of a magnetc card that greatly facltates the montorng of the whole program. The management of the program s essentally local. Yet, control wll be operated at two levels. At the federal level, the number of benefcares clamed by muncpal governments wll be checked for consstency aganst local aggregate ndcators of affluence. In case of dscrepancy, local governments wll have to adjust the number of benefcares on the bass of ncome per capta rankngs. At the local level, the responsblty for checkng the veracty of self-reported ncomes s left to muncpaltes. It s estmated that some ten mllon chldren (n sx mllon households) wll beneft from ths program. Ths represents approxmately 7 percent of the whole populaton, reached at a cost slghtly below 0. percent of GDP. The latter proporton s hgher n terms of household dsposable ncome: 0.45 percent when usng household ncome reported n the PNAD survey and 0.3 per cent when usng Natonal Accounts. Of course, ths fgure s consderably hgher when expressed n terms of targeted households. Even so, t amounts to no more than 5 percent of the ncome of the bottom two decles. 6 Early studes of these orgnal programs nclude Abramovay et. al. (998); Rocha and Sabóa (998) and Sant Ana and Moraes (997). A comprehensve assessment of dfferent experences wth Bolsa Escola across Brazl can be found n World Bank (00). There s much less wrtten on the federal program, for the good reason that ts mplementaton n practce s only just begnnng. The descrpton gven n ths secton draws on the offcal Mnstéro da Educação webste, at 7 Approxmately US$ 30, at August 00 exchange rates.

6 5 3. A smple framework for modelng and smulatng Bolsa Escola The effects of such a transfer scheme on the Brazlan dstrbuton of ncome could be smulated by smply applyng the aforementoned rules to a representatve sample of households, as gven for nstance by the Pesqusa Naconal por Amostra de Domcílos (PNAD), felded annually by the Brazlan Central Statstcal Offce (IBGE). Ths would have been an example of what was referred to above as 'arthmetc' smulaton. Yet, for a program whch has a change n household behavor as one of ts explct objectves, ths would clearly be napproprate. After all, Bolsa Escola ams not only to reduce current poverty by targetng transfers to today s poor, but also to encourage school attendance by poor chldren who are not currently enrolled, and to dscourage evason by those who are. Any ex-ante evaluaton of such a polcy must therefore go beyond smply countng the addtonal ncome accrung to households under the assumpton of no change n schoolng behavor. Smulatng Bolsa Escola thus requres some structural modelng of the demand for schoolng. Ths secton presents and dscusses the model beng used n ths paper. There s a rather large lterature on the demand for schoolng n developng countres and the related ssue of chld labor. The man purpose of that lterature s to understand the reasons why parents would prefer to have ther kds workng wthn or outsde the household rather than gong to school. Varous motves have been dentfed and analyzed from a theoretcal pont of vew, 8 whereas numerous emprcal attempts have been made at testng the relevance of these motves, measurng ther relatve strength and evaluatng the lkely effects of polces. 9 The emprcal analyss s dffcult for varous nter-related reasons. Frst, the ratonale behnd the decson on chld labor or school enrollment s by tself ntrcate. In partcular, t s an nherently ntertemporal decson, and t wll dffer dependng on whether households behave as n the untary model, or whether nternal barganng takes place. Second, t s dffcult to clam exogenety for most plausble explanatory varables, and yet no obvous nstrument s 8 See the well-known survey by Basu (999) as well as the recent contrbuton by Baland and Robnson (00). 9 Early contrbutons to that lterature nclude Rosenzweg and Evenson (977), as well as Gertler and Glewwe (990). For more recent contrbutons and short surveys of the recent lterature see Freje and Lopez-Calva (000), and Bhalotra (000). On polcy, see Grootaert and Patrnos (999).

7 6 avalable for correctng the resultng bases. Thrd, fully structural models that would permt a rgorous analyss of polces are complex and therefore hard to estmate whle mantanng a reasonable degree of robustness. The econometrc lterature on chld labor and schoolng often reles on reduced form models that permt to test the sgnfcance of partcular varables but not always more structural hypotheses. Few exstng models would allow for the ex-ante evaluaton of a condtonal transfer program lke Bolsa Escola. 0 In lght of these dffcultes, our ams are modest and our approach s operatonal. We do not attempt to estmate a fully structural model of the demand for schoolng based on some representaton of the ntra-household labor allocaton. We am smply to obtan orders of magntude for the lkely effects of transfer programs of the Bolsa Escola type. In dong so, we make the choce to lmt the structural aspects of the modelng exercse to the strct mnmum, and thus to depart as lttle as possble from standard reduced form models of chld occupaton. In partcular, we make four crucal smplfyng assumptons. Frst, we entrely gnore the ssue of how the decson about a chld s tme allocaton s made wthn the household. In partcular, we bypass the dscusson of untary versus collectve decsonmakng models of household. Instead, we treat our model of occupatonal choce as a reduced-form reflecton of the outcome of whchever decson-makng process took place wthn the household. Second, we consder that the decson to send a chld to school s made after all occupatonal decsons by adults wthn the household have been made, and does not affect those decsons. Thrd, we do not dscuss here the ssue of varous sblngs n the same household and the smultanety of the correspondng decson. The model that s dscussed s thus supposed to apply to all chldren at schoolng age wthn a household. Fourth, we take the composton of the household as exogenous. Under these assumptons, let S be a qualtatve varable representng the occupatonal choce made for a chld n household. Ths varable wll take the value 0 f the chld does not attend school, the value f she goes to school and works outsde the household and the value f she goes to school and does not work outsde the household. 0 Ths s even true for an explct structural model lke Gertler and Glewwe (990). For a dscusson of how ntra-household barganng affects labour supply behavour by members, see Chappor (99) or Bourgugnon and Chappor (994).

8 7 When S =0, t wll be assumed that the chld works full tme ether at home or on the market, earnngs beng observed only n the latter case. Smlarly, S = allows for the possblty that the chld may be employed n domestc actvtes at the same tme he/she goes to school. The occupatonal choce varable S wll be modeled usng the standard utlty-maxmzng nterpretaton of the multnomal Logt framework,sothat: S =k ff S k (A,X,H ;Y - +y k )+v k >S j (A,X,H ;Y - +y j )+v j for j k () where S k ( ) s a latent functon reflectng the net utlty of choosng alternatve k (=0, or ) for decders n the household. A s the age of the chld ; X s a vector of her characterstcs; H s a vector of the characterstcs of the household she belongs to - sze, age of parents, educaton of parents, presence of other chldren at school age, dstance from school, etc.; Y - s the total ncome of household members other than the chld and y j s the total contrbuton of the chld towards the ncome of the household, dependng on her occupatonal choce j. Fnally, v j s a random varable that stands for the unobserved heterogenety of observed schoolng/partcpaton behavor. If we collapse all non-ncome explanatory varables nto a sngle vector Z and lnearze, () can be wrtten as: U (j) = S j (A,X,H ;Y - +y j )+v j =Z.γ j +(Y - +y j )α j +v j () Ths representaton of the occupatonal choce of chldren s very parsmonous. In partcular, by allowng the coeffcents γ j and α j to dffer wthout any constrants across the varous alternatves, we are allowng all possble tradeoffs between the schoolng of the chld and hs/her future ncome on the one hand, and the current ncome of the household on the other. Note also that the precedng model mplctly treats the chld's number of hours of work as a dscrete choce. Presumably that number s larger n alternatve 0 than n alternatve because schoolng s takng some tme away. Ths may be reflected n the defnton of the chld s ncome varable, y j, as follows. Denote the Several authors model the jont labor/schoolng decson for chldren as a bnomal or sequental Probt rather than a multnomal logt see for nstance Canagarajah and Coulombe (997) and Grootaert and Patrnos (999). Because ths specfcaton has no drect utlty maxmzng nterpretaton, t s not convenent for the knd of smulaton undertaken n ths paper. A multnomal Probt would be more approprate but ts estmaton s somewhat cumbersome.

9 8 observed market earnngs of the chld as w. Assumng that these are determned n accordance wth the standard Becker-Mncer human captal model, wrte: Log w =X.δ + m*ind(s =) + u (3) where X s the set of ndvdual characterstcs defned earler whch ncludes standard Mnceran varables lke age and schoolng acheved - u s a random term that stands for unobserved earnngs determnants and Ind( ) s the ndcator functon. Assumptons on that term wll be dscussed below. The second term on the rght hand sde takes nto account the precedng remark on the number of hours of work. Chldren who attend school and are also reported to work on the market presumably have less tme avalable and may thus earn less. Based on (3), the chld's contrbuton to the household ncome, y j, n the varous alternatves j s defned as follows: y 0 =Kw ; y =My 0 =MKw ;y =Dy 0 =DKw wth M = Exp(m) (4) where t s assumed that y j values the output of both market and domestc chld labor. Thus domestc ncome s proportonal to actual or potental market earnngs, w,na proporton K for people who do not go to school. Gong to school whle stll workng n the market means a (proportonal -M) reducton n domestc and market ncome. Fnally, gong to school wthout workng on the market means a reducton n the proporton -D of total chld ncome, whch n that case s purely domestc. The proportons K and D are not observed. However, the proporton M s taken to be the same for domestc and market work and may be estmated on the bass of observed earnngs, from equaton (3). Replacng (4) n () leads to : U (j) = S j (A,X,H ;Y - +y j )+v j =Z.γ j +Y - α j + β j.w +v j wth: β 0 = α 0 K; β = α MK; β = α DK (5) We now have a complete smulaton model. If all coeffcents α, β, γ are known, as well as the actual or potental market earnngs, w and the resdual terms v j,thenthe chld s occupatonal type selected by household s: k* = Arg max[u (j)] (6)

10 9 Equaton (5) represents the utlty of household under occupatonal choce j [U (j)] n the benchmark case. If the Bolsa Escola program enttled all chldren 3 gong to school to a transfer T, (5) would be replaced by: U (j) = Z.γ j +(Y -I +BE j ).α j + β j.w +v j wth BE 0 =0 and BE =BE =T (7) Ths smply adds a postve transfer amount T to the household s ncome term whch s ndependent of the chld s occupaton (Y - ), provded that the chld s attendng school (.e n states j= or j=, but not n state j=0). Note that ths s what makes ths transfer condtonal: n solvng ts occupatonal problem, the household knows that T wll only accrue f the household s n states or.e. f the chld s gong to school and that the transfer wll be zero otherwse. An uncondtonal transfer, conversely, would add to famly ncome Y ndependently of state j. Under the assumptons we have made, equaton (7) s our full reduced-form model of the occupatonal choce of chldren, and would allow for smulatons of the mpact of Bolsa Escola transfers on those choces. All that remans s to obtan estmates of β, γ, α, w and the v j 's. Estmaton of the dscrete choce model Assumng that the v j are..d. across sample observatons wth a double exponental dstrbuton leads to the well-known mult-logt model. However, some precautons must be taken n ths case. In ths model, the probablty that household wll select occupatonal choce k s gven by: p k Exp( Z. γ k + Y α k + w. βk ) = Exp( Z. γ j + Y α j + w. β j ) j (8) Takng regme j = 0 as a reference, the precedng probablty may be wrtten as: p j = + Exp j= [ Z.( γ j γ 0 ) + Y.( α j α 0 ) + w ( β j β 0 )] [ Z.( γ γ ) + Y.( α α ) + w ( β β )] Exp and p 0 = p p. j 0 j 0 j 0 for j =, (9) 3 It wll prove smpler to dscuss the estmaton problem under ths smplfyng assumpton. We rentroduce the means test, wthout any loss of generalty, at the smulaton stage.

11 0 The dffculty s that the Multnomal logt estmaton permts dentfyng only the dfferences (α j -α 0 ), (β j -β 0 ), and (γ j -γ 0 ) for j =,. Yet, nspecton of (6) and (7) ndcates that snce the Bolsa Escola transfer s state-contngent, meanng that the ncome varable s asymmetrc across alternatves - t s necessary to know all three coeffcents α 0, α and α n order to fnd the utlty maxmzng alternatve, k*. Ths s where the only structural assumpton made so far becomes useful. Call â j and bˆ j the estmated coeffcents of the multlogt model correspondng to the ncome and the chld earnng varables for alternatves j =,, the alternatve 0 beng taken as the default. Then (5) mples the followng system of equatons: α α = aˆ 0 0 ( α M α ). K = bˆ ( α D α ) K = bˆ 0 0 α α = aˆ (0) M s known from equaton (3). It follows that arbtrarly settng a value for K or for D allows us to dentfy α 0, α and α and the remanng parameter n the par (K,D). The dentfyng assumpton made n what follows s that kds workng on the market and not gong to school have zero domestc producton,.e. K =. In other words, t s assumed that the observed labor allocatons between market and domestc actvtes are corner solutons n all alternatves. 4 It then follows that: α = aˆ ˆ b M, α 0 = α aˆ, α = α + aˆ aˆ bˆ + α 0 and D = α () Of course, a test of the relevance of the dentfyng assumpton s that α 0, α and α must be postve. One could also requre that the value of D be n the nterval (0, ). For completeness, t remans to ndcate how estmates of the resdual terms v j -v 0 may be obtaned. In a dscrete choce model these values cannot be observed. It s only known that they belong to some nterval. The dea s then to draw them for each 4 In effect, ths assumpton mght be weakened usng some lmted nformaton on hours of work avalable n the survey.

12 observaton n the relevant nterval, that s: n a way consstent wth the observed choce. For nstance f observaton has made choce, t must be the case that: Z.γ +Y -. â + ˆb.w +(v -v 0 ) > Sup[0, Z.γ +Y -. â + ˆb.w +(v -v 0 )] The terms v j -v 0 must be drawn so as to satsfy that nequalty. All that s mssng now s a complete vector of chld earnngs values, w. Estmaton of potental earnngs The dscrete choce model requres a potental earnng for each chld, ncludng those who do not work outsde the household. To be fully rgorous, one could estmate both the dscrete choce model and the earnngs equaton smultaneously by maxmum lkelhood technques. Ths s a rather cumbersome procedure. We adopt a smpler approach, whch has the advantages of transparency and robustness. It conssts of estmatng (3) by OLS, and then generatng random terms u for non-workng kds, by drawng n the dstrbuton generated by the resduals of the OLS estmaton. There are several reasons why correctng the estmaton of the earnngs functon for possble selecton bas was problematc. Frst, nstrumentng earnngs wth a selecton bas correcton procedure requres fndng nstruments that would affect earnngs but not the schoolng/labor choce. No such nstrument was readly avalable. Second, the correcton of selecton bas wth the standard two-stage procedure s awkward n the case of more than two choces. Lee (983) proposed a generalzaton of the Heckman procedure, but t s now known that Lee's procedure s justfed and effcent only n a rather unlkely partcular case. 5 For both of these reasons, falng to correct for possble selecton bas n (3) dd not seem too serous a problem. On the other hand, tryng to correct for selecton usng standard technques and no convncng nstrument led to rather mplausble results. Smulatng programs of the Bolsa Escola type 5 See Schmertmann (994), Bourgugnon et al. (00), Dahl (00)

13 As mentoned n footnote, the model (6)-(7) does not provde a complete representaton of the choce faced by households n the presence of a program such as Bolsa Escola. Ths s because t takes nto account the condtonalty on the schoolng of the chldren, but not the means-test. Takng nto account both the means-test and the condtonalty leads to choosng the alternatve wth maxmum utlty among the three followng condtonal cases: U (0) = Z. γ + α Y U () = Z. γ + α Y I U () = Z. γ + α ( Y I U () = Z. γ + α ( Y U () = Z. γ + α Y 0 0 I I + β w + T) + β w + β w I 0 + T ) + β w + β w + v + v + v 0 + v + v f Y f Y f f I I Y + Mw + Mw I Y I Y > Y Y > Y () The condtons assocated wth modaltes and stand for the means test, Y beng the ncome threshold. Note that these condtons are defned n terms of monetary ncome, whch explans why the contrbuton of the chld to domestc producton n the case S= s not taken nto account. As mentoned above, only the dfferences between the utltes correspondng to the three cases matter, so that one only needs to know the dfferences (β j -β 0 ), (γ j -γ 0 )and (v j -v 0 ) but all three coeffcents α j. In ths system, one can see how the ntroducton of Bolsa Escola mght lead households from choce (0) no schoolng to choces () or (), but also from choce () to choce (). In the latter case, a household mght not qualfy for the transfer T when the chld both works and attends school, but qualfes f she stops workng. A wde varety of programs may be easly smulated usng ths framework. Both the means-test Y and the transfer T could be made dependent on characterstcs of ether the household (H) or the chld (X). In partcular, T could depend on age or gender. Some examples of such alternatve desgns are smulated and dscussed n Secton 5. Before presentng the model estmaton results, we should draw attenton to two mportant lmtatons of the framework just descrbed. Both arse from the set of assumptons dscussed n the begnnng of ths secton. The frst lmtaton s that we can not model the effects (on the occupatonal choce) of the celng of R$45 on transfers to any sngle household. The reason s that by gnorng mult-chldren nteractons n the

14 3 model, t s as though we had effectvely assumed that all households conssted of a sngle chld, from a behavoral pont of vew. In the non-behavoral part of the welfare smulatons whch are reported n Secton 5 below, however, each chld was treated separately, and the R$45 lmt was appled. The second lmtaton has to do wth the exogenety of non-chld ncome Y -I.Ths exogenety would clearly be a problem f there were more than one chld n schoolng age. But t s also unrealstc even when only adult ncome s taken nto account. It s clearly possble that the presence of the means-test mght affect the labor supply behavor of adults, snce there are crcumstances n whch t mght be n the nterest of the famly to work slghtly less n order to qualfy for Bolsa Escola. Note, however, that ths mght not be so sharply the case f the means-test s based, not on current ncome, but on some score-based proxy for permanent ncome, as appears to be the case n practce. 4. Descrptve statstcs and estmaton results The model consstng of equatons (3) and () was estmated on data from the 999 PNAD household survey. Ths survey s based on a sample of approxmately 60,000 households, whch s representatve of the natonal populaton 6. Although all chldren aged 6-5 qualfy for partcpaton n the program, the model was only estmated for 0-5 year-olds, snce school enrollment below age 0 s nearly unversal. 7 At the smulaton stage, however, transfers are smulated for the whole unverse of qualfyng 6-5 year-olds. Table contans the basc descrpton of the occupatonal structure of chldren aged 0-5 n Brazl, n 999. In ths age range, 77% of chldren report that they dedcate themselves exclusvely to studyng. Some 7% both work and study, and 6% do not attend school at all. Ths average pattern hdes consderable varaton across ages: school attendance consstently declnes and work ncreases wth age. Whereas only.6% of 6 Except for the rural areas of the states of Acre, Amazonas, Pará, Rondôna and Rorama. 7 We know that school enrolment s nearly unversal from answers to schoolng questons n the PNAD. An addtonal reason to lmt the estmaton of the behavoral model to chldren aged ten or older s that the ncdence of chld labor at lower ages s probably measured wth much greater error, snce PNAD ntervewers are nstructed to pose labor and ncome questons only to ndvduals aged ten or older.

15 4 ten year-olds are out of school, the fgure for ffteen year-olds s 3.6%. Whereas some 90% of ten year-olds dedcate themselves exclusvely to studyng, fewer than 60% of ffteen year-olds do so. From a behavoral pont of vew, t s thus clear that most of the acton s to be found among the oldest chldren. It s mportant to stress the PNAD contans data on school enrollment but not on actual school attendance. We are therefore unable to model the Bolsa Escola s mnmum 85% attendance condton as a separate constrant to enrolment. Our results would no longer be vald f a sgnfcant number of enrolled chldren had attendance rates regularly below 85%. The latest admnstratve data from the Secretara do Programa Naconal de Bolsa-Escola (the agency that runs the federal program) ndcates that fewer than 3% of all benefcares had faled to meet the 85% frequency requrement, n the latest quarter for whch data s avalable (July-September, 00). Whether ths s also true for nonbenefcares s the assumpton we are forced to make n the absence of the relevant data. Table presents the mean ndvdual and household characterstcs of those chldren, by occupatonal category. Chldren not gong to school are both older and less educated than those stll enrolled. As expected, households wth school drop-outs are on average poorer, less educated and larger than households where kds are stll gong to school. Droppng out of school and engagng n chld labor are relatvely more frequent among non-whtes and n the North-East. Both forms of behavor are least common n metropoltan areas, and proportonately most common n rural areas. Interestngly, households where chldren both work and go to school are generally n an ntermedate poston between those whose chldren specalze, but are often closer to the group of drop-outs. A remarkable feature of Table s the observed amount of chldren s earnngs, when they work and do not study. Wth age-specfc averages rangng from around R$80 to R$30 per month, chldren's earnngs represent approxmately half the mnmum wage, an order of magntude that seems rather reasonable. These amounts are much above the R$5 transfer that s granted by the Bolsa Escola program for chldren enrolled n school. Note, however, that observed earnngs are not a good measure for the opportunty cost of schoolng, snce school attendance s evdently consstent wth some amount of market work. We return to ths ssue below.

16 5 Tables 3 and 4 contan the estmaton results. Because of the great behavoral varaton across ages even wthn the 0-5 range - as revealed, for nstance, n Table - we estmated the (dentcally specfed) model separately for each age, as well as for the pooled sample of all 0-5 year-olds. Ths allows us to take fully nto account the nteracton between a chld s age, her last grade completed and, by subtracton, age out of school. Ths specfcaton allows for consderably more flexble estmaton of the age effects than the smple ntroducton and nteracton of dummy varables. The smulatons reported n the next secton rely on the age-specfc models, but n ths secton we report only the jont estmaton results, both for ease of dscusson and because the larger sample sze allowed for more precse estmaton n ths case. Table 3 shows the results of the OLS estmaton of the earnngs functon (3), for the pooled sample. 8 Geographcal varables, race and gender have the expected sgns, and the same qualtatve effect as for adults, although the racal dummy s less sgnfcant. The coeffcent on the logarthm of the (drop-out) medan earnngs of chldren of a gven age n hs or her state s postve, and both statstcally and economcally sgnfcant. Ths s n fact an mportant varable, whch s ncluded as a proxy for the spatal varaton n the demand for chld labor of dfferent ages. It s constructed as the medan of the dstrbuton of earnngs for chldren wth exactly 0 (or,, 3, 4, 5, as approprate) years of age, n her state n Brazl, excludng the chld herself, provded there are at least two elements n ths vector. 9 Ths varable s our dentfyng nstrument, and wll not appear n the multnomal logt model (). The ntuton s that demand condtons n the age and spatally specfc labor market facng the chld affect her occupatonal decson only through her potental earnngs varable. It s also the fact that medan earnngs are computed for age-specfc dstrbutons n each state whch explans why the lnear experence term (Age) n Table 3 s nsgnfcant. In an alternatve (unreported) specfcaton for the pooled sample whch omtted the medan earnngs by state varable, an addtonal year of age ncreased earnngs by approxmately 40 per cent. But there was a clear non-lnearty n the way age 8 Analogous results for the 0,,, 3, 4 and 5 year-old samples are avalable from the authors on request. 9 Whenever there were fewer than three workng chldren of a certan age n the 999 PNAD sample for the state, the drop-out medan was taken n the regon (North, Northeast, Southeast, South, Centre-West).

17 6 affected earnngs, whch s reflected n changes n the coeffcent estmates when the model s separately estmated. Indeed, these non-lneartes and nteractons between age and other determnants are the reason why the separate specfcaton was preferred for the smulatons usng the model. Regonal dummes were also all nsgnfcant, and were dropped. The effect of prevous schoolng s postve and sgnfcant. The estmate for m the coeffcent for dummy WS n Table 3 reveals that, as expected, the fact that a chld goes to school at the same tme as she works outsde the household reduces total earnngs n comparson wth a comparable chld who dedcates herself exclusvely to market work. If one nterprets ths coeffcent as reflectng fewer hours of work, then a chld gong to school works on average 34 per cent less than a dropout, for the pooled sample. Ths seems lke a reasonable order of magntude. The results from the estmaton of the multnomal logt for occupatonal choce also appear emnently plausble. Margnal effects and the correspondng p-values for the pooled sample are reported n Table 4. 0 The reference category was not studyng (j = 0), throughout. Once parental educaton s controlled for, household ncome (net of the chld s) has a postve, but very small effect on the schoolng decson, whereas the chld s own (predcted) earnngs have a negatve effect. Household sze reduces the probablty of studyng, compared to the alternatves. Prevous schoolng at a gven age has a postve effect. Whte chldren are more lkely than non-whte chldren to be studyng and not workng. Boys are less lkely than grls to be studyng only, but more lkely to be workng and studyng, whch suggests a possble pattern of specalzaton n domestc work by grls, and market work by boys. Parents' educaton has the expected postve effect on top of the ncome effect - on chldren's schoolng. In vew of ths general consstency of both the earnngs and the dscrete occupatonal choce models, the queston now arses of whether the structural restrctons necessary for the consstency of the proposed smulaton work postve α and α,and0 < D < - hold or not. For the pooled sample and usng (), we fnd that: 0 Analogous results for each of the age-specfc models (for 0,,, 3, 4 and 5 year-olds) are avalable from the authors upon request. To the extent that household sze reflects a larger number of chldren, ths s consstent wth Becker s quantty-qualty trade-off.

18 α = = 0.045, α 0 =.044, α = 0.047, D = Exp( ) = The coeffcents of ncome n the utlty of alternatves j = and are thus postve, whch s n agreement wth the orgnal model. But there are very close to each other, whch suggests that ncome effects are lkely to be small. Accordng to the value obtaned for parameter D, chldren who are gong to school but do not work on the market are estmated to provde domestc producton for approxmately three quarters of ther potental market earnngs. Ths s very close to the estmated value for M [= Exp( ) = 0.709]. Snce M denotes the average contrbuton to household ncome from chldren both studyng and workng, as a share of ther potental contrbuton f not studyng, ths mples that the estmated value of non-market work by chldren studyng (and not workng n the market) s rather smlar to the market value of work by those studyng (and workng n the market). If there was lttle selecton on unobservables nto market work, ths s exactly what one would expect. The values mpled for M and D, as well as for all α and β parameters, for each of the age-specfc models, are reported n Table 5. There s some varaton across agegroups, whch s due at least n part to the lesser precson of the estmaton n the smaller sub-samples. Apart from a value for D just greater than unt n the year-old sample, all of the parameters conform to the theoretcal restrctons. Overall, the estmates obtaned both from the multnomal dscrete occupatonal choce model and from the earnngs equaton seem therefore remarkably consstent wth ratonal, utlty-maxmzng behavor. We may thus expect smulatons run on the bass of these models and of the dentfyng structural assumptons about the parameter K to yeld sensble results. We can now turn to our man objectve: gaugng the order of magntude of the effects of programs such as Bolsa Escola. 5. An ex-ante evaluaton of Bolsa Escola and alternatve program desgns Bolsa Escola and many condtonal cash transfer programs lke t are sad to have two dstnct objectves: () to reduce current poverty (and sometmes nequalty)

19 8 through the targeted transfers, and () to reduce future poverty, by ncreasng the ncentves for today s poor to nvest n ther human captal. Later on n ths secton, we wll turn to the frst objectve. We begn by notng, however, that, as stated, the second objectve s mpossble to evaluate, even n an ex-ante manner, wthout makng strong assumptons about the future path of returns to schoolng. Whether ncreased school enrollment translates nto greater human captal depends on the trends n the qualty of the educatonal servces provded, and there s no nformaton on that n ths data set. Fnally, whether more human captal, however measured, wll help reduce poverty n the future or not, depends on what happens to the rates of return to t between now and then. Ths s a complex, general equlbrum queston, whch goes well beyond the scope of ths exercse. 3 What we mght be able to say somethng about s the ntermedate target of ncreasng school enrollment. Whle the precedng remarks suggest that ths s not suffcent to establsh whether the program wll have an mpact on future poverty, t s at least necessary. 4 An ex-ante evaluaton of mpact on ths dmenson of the program thus requres smulatng the number of chldren that may change schoolng and workng status because of t. Ths s done by applyng the decson system () - wth behavoral parameter values (α, β, γ, M and D) estmated from (9) - (), and polcy parameter values (T and Y 0 ) taken from the actual specfcaton of Bolsa Escola - to the orgnal data. System () s then used to smulate a counterfactual dstrbuton of occupatons, on the bass of the observed characterstcs and the restrctons on resdual terms for each ndvdual chld. Ths s done usng the models estmated separately by age. Comparng the vector of The evdence on educatonal outcomes, from an ex-post evaluaton of a muncpal Bolsa Escola program n Recfe, s not conclusve. Lavnas and Barbosa (forthcomng) appled a maths test to control and treatment groups, and found that test scores were not statstcally sgnfcantly dfferent between them. There s also lmted nformaton n other data sets, such as the Educaton Mnstry s Sstema de Acompanhamento do Ensno Básco (SAEB), but not for suffcently long perods of tme. See Albernaz et. al. (00). 3 See Coady and Morley (003) for a brave and sensble - attempt at estmatng the present value of the gans arsng from the addtonal educaton acqured due to condtonal cash transfer programs. 4 One could argue that t s not even necessary, snce the transfers mght, by themselves, allevate credt constrants and have long-term postve mpacts, e.g. through mproved nutrton. We focus on whether the condtonal nature of these transfers actually has any mpact on the chldren s occupatonal choces (or tme allocaton decsons).

20 9 occupatonal choces thus generated wth the orgnal, observed vector, we see that the program leads to some chldren movng from choce S = 0 to choces S = or, and from S = to choce S =. The correspondng transton matrx s shown n Table 6 for all chldren between 0 and 5, as well as for all chldren n the same age group lvng n poor households. 5 In nterpretng Table 6, we should remember that the observed orgnal vector corresponds to the actual stuaton n September 999, pror to the ntroducton of the Federal Bolsa Escola program we are smulatng. It s therefore an approprate control sample for comparng wth the counterfactual treatment populaton obtaned from the smulatons. 6 Despte the small value of the proposed transfer, Table 6 suggests that four out of every ten chldren (aged 0-5) who are presently not enrolled n school would get enough ncentve from Bolsa Escola to change occupatonal status and go to school. Among them, just over a thrd would enroll, but reman employed on the labor market. The other two thrds would actually cease work outsde ther household. Ths would reduce the proporton of chldren n that age range outsde school from 6.0% to 3.7% - a rather szable effect. The mpact on those currently both studyng and workng would be much smaller. Barely % of them would abandon work to dedcate themselves exclusvely to ther studes. As a result of ths small outflow, combned wth an nflow from occupatonal category S = 0, the group of chldren both studyng and workng would actually grow n the smulated scenaro, albet margnally. The mpacts are even more pronounced among the poor who are the target populaton for the program. Accordng to the poverty lne beng used, the ncdence of 5 A household was consdered poor f ts (regonally prce-deflated and mputed rent-adjusted) per capta ncome was less than R$74.48 n the reference month of the 999 PNAD survey. For the dervaton of the poverty lne, see Ferrera et al. (forthcomng). 6 There were a number of smlar muncpal programs n operaton at the tme, such as the Recfe Scholarshp Program. There were few of them, however, and they were usually very small, so that the frequency of benefcares of these programs n the natonal 999 PNAD sample would have been tny. The Recfe program, for nstance, reached an estmated sxteen hundred famles by December 999 (see Lavnas and Barbosa, forthcomng). Addtonally, a number of these local programs have contnued n exstence concurrently wth the federal program, so that the ncluson of any ncome from them among other ncomes n any famly that mght have been sampled n the PNAD 999 s also approprate n a comparson between the no-treatment control group, and the counterfactual treatment sample. The pont s that treatment, defned as the federal desgn of the Bolsa Escola program, only came nto beng n Aprl 00.

21 0 poverty n Brazl s 30.5%. However, because there are more chldren n poor households ths beng one of the reasons why they are poor the proporton of 0-5 chldren n poor households s much hgher: 4%. The second panel n Table 6 shows that dropouts are much more frequent among them 8.9 nstead of 6.0 per cent for the whole populaton. It also shows that Bolsa Escola s more effectve n ncreasng ther school enrollment. The fall n the proporton of dropouts s of almost 60%, rather than 40%. As a result, the smulaton suggests that Bolsa Escola could ncrease the school enrollment rate among the poor by approxmately 5. percentage ponts. Once agan, ths ncrease comes at the expense of the not studyng category, whose numbers are more than halved, rather than of the workng and studyng category, whch actually becomes margnally more numerous. That the mpact of the program s stronger among the poor smply reflects the bndng nature of the means test. Famles whch report monthly per capta ncomes greater than R$90 smply do not qualfy to receve the transfer T. Nothng changes n the equatons n system () that are relevant to them, and they thus do not respond to the program n any way. Therefore, all chldren changng occupatonal status n Table 6 lve n households wth ncomes lower than that threshold. Snce the poverty lne s approxmately R$75, most of them are poor. Ths beng sad, a 60% reducton n the proporton of poor chldren outsde school s by no means an nsubstantal achevement, partcularly n lght of the fact that t seems to be manageable wth farly small transfers (R$5 per chld per month). Ths s partly due to the fact that the value of the current contrbutons of chldren who are enrolled n school s a szable proporton of ther potental earnngs when completely outsde school. Those proportons are exactly the nterpretaton of the parameters M (for those who work on the market as well as study) and D (for those who work at home as well as study), whch we estmated to be n the 70-75% range. Applyng that factor to R$00, as a rough average of the earnngs of chldren n category j = 0 (see Table ), we are left wth some R$5 as the true monthly opportunty cost of enrollng n school. Consequently, those chldren who change occupaton from that category n response to the R$5 transfer must have average personal present valuatons of the expected stream of benefts from

22 enrollng greater than R$0 (and less than R$5). Those who do not, must on average value educaton at less than that. Because our smulatons suggest that Bolsa Escola, as currently formulated, would stll leave some 3.7% of all 0-5 year-olds outsde school, t s nterestng to nvestgate the potental effects of changng some of the program parameters. Ths ndeed was one of the ntal motvatons for undertakng ths knd of ex-ante counterfactual analyss. Table 7 shows the results of such a comparatve exercse n terms of occupatonal choce, by reportng the factual and counterfactual occupatonal dstrbutons, once agan both for all chldren and then separately for poor households only. Table 8 compares the mpact of each scenaro wth that of the benchmark program specfcaton, n terms of poverty and nequalty measures. Four standard nequalty measures were selected, namely the Gn coeffcent and three members of the Generalzed Entropy Class: the mean log devaton, the Thel-T ndex and (one half of the square of) the coeffcent of varaton. For poverty, we present the three standard FGT (0,, ) measures, wth respect to the aforementoned Ferrera et. al. (forthcomng) poverty lne. Ths latter table allows us to gauge mpact n terms of the frst objectve of the program, namely the reducton of current poverty (and possbly nequalty). In both tables, the smulaton results for fve alternatve scenaros are presented. In scenaro, the elgblty crtera (ncludng the means test) are unchanged, but transfer amounts (and the total household celng) are both doubled. In scenaro, the means-test remans unchanged, but transfer amounts and the total household celng are quadrupled.e. doubled from Scenaro. In scenaro 3, the unform R$5 per chld transfer s replaced by an age-contngent transfer, whereby 0 year-olds would receve R$5, year-olds would receve R$0, year-olds would receve R$5, 3 year-olds would receve R$35, 4 year-olds would receve R$40, and 5 year-olds receved R$45. In addton, the household celng s removed. 7 In scenaro 4, transfer amounts were unchanged, but the means-test was rased from R$90 to R$0. Scenaro 5 smulated a targeted transfer exactly as n Bolsa Escola, but wth no condtonalty: every chld n households below the means-test receved the beneft, wth no requrement relatng to school enrollment. 7 The means-test remans at R$90.

23 Table 7 gves rse to three man results. Frst of all, a comparson of Scenaro 5 and the actual Bolsa Escola program suggests that condtonalty plays a crucal role n nducng the change n chldren s tme-allocaton decsons. The proportons of chldren n each occupatonal category under Scenaro 5 are almost dentcal to the orgnal data (.e. no program). Ths s consstent wth the very small margnal famly ncome effect reported n Table 4, and suggests that t s the condtonal requrement to enroll n order to receve the beneft rather than the pure ncome effect from the transfer - whch s the prmary cause of the extra demand for schoolng shown n the Bolsa Escola column. Second, scenaros and reveal that the occupatonal mpact of the program s reasonably elastc wth respect to the transfer amount. The proporton of un-enrolled chldren drops by almost one percentage pont (.e. some 5%) n response to a doublng of the transfers n Scenaro, and then another 5% as transfers double agan from Scenaro to Scenaro. Ths effect s even more pronounced among poor famles, where the R$60 transfers n Scenaro cause a reducton n the un-enrolled to 0.6%, from 3.7% under the current program desgn. Scenaro 3 suggests that t doesn t matter much, n aggregate terms, whether ths ncrease n transfers s unform across ages, or rses wth the age of the chld. Fnally, scenaro 4 suggests that occupatonal effects are less senstve to rses n the means-test than to the transfer amounts. Results are consderably less mpressve n terms of the program s frst stated objectve, namely the reducton n current poverty (and nequalty) levels. Table 8 suggests that the program, as currently envsaged, would only mply a.3 percentage pont declne n the short-run ncdence of poverty n Brazl, as measured by P(0). However, there s some evdence that the transfers would be rather well targeted, snce the nequalty-averse poverty ndcator P() would fall by proportonately more than P(0), from 8% to 7%. Ths s consstent wth the nequalty results: whereas the Gn would fall by only half a pont as a result of the scheme, measures whch are more senstve to the bottom, such as the mean log devaton, fall by a lttle more. Overall, however, the evdence n column of Table 8 falls consderably short of a rngng endorsement of Bolsa Escola as a program for the allevaton of current poverty or nequalty. The stuaton could be somewhat mproved by ncreases n the transfer amounts (scenaros - 3). Quadruplng the transfers to R$60 per chld, up to a celng of R$80

24 3 per famly, for nstance, would further reduce the Brazlan poverty headcount by 4. percentage ponts. 8 But program costs would clmb from R$bllon to R$8.5bllon, that s from. to.85% of GDP. An ncrease n the means-test would not help much, as ndcated by Scenaro 4. Ths s consstent wth our earler suggeston that the program already appears to be well-targeted to the poor. If t fals to lft many of them above the poverty lne, ths s a consequence of the small sze of the transfers, rather than of poor targetng. These results contrast wth the arthmetc smulatons reported by Camargo and Ferrera (00), n whch a somewhat broader, but essentally smlar program would reduce the ncdence of poverty (wth respect to the same poverty lne and n the same sample) by two-thrds, from 30.5% to 9.9%. Ths was despte the fact that the absence of a behavoral component n that smulaton weakened ts power, by excludng from the set of recpents those households whose chldren mght have enrolled n response to the program. The reason s smple: Camargo and Ferrera smulate much hgher transfer levels, rangng from R$50 to R$0 per household (rather than chld). The more szable poverty reductons smulated under our scenaro, n whch transfers are more generous, pont n the same general drecton. 6. Conclusons In ths paper, we proposed a mcro-smulaton method for evaluatng and expermentng wth condtonal cash-transfer program desgns, ex-ante. We were concerned wth the mpacts of the Brazlan Bolsa Escola program, whch ams to reduce both current and future poverty by provdng small targeted cash transfers to poor households, provded ther chldren are enrolled n and n actual attendance at school. We were nterested n assessng two dmensons of the program: ts mpact on the occupatonal choce (or tmeallocaton) decsons of chldren, and the effects on current poverty and nequalty. For ths purpose, we estmated a dscrete occupatonal choce model (a multnomal logt) on a natonally representatve household-level sample, and used ts 8 The smulated. percentage-pont declne n the P() s also qute respectable.

25 4 estmated parameters to make predctons about the counterfactual occupatonal decsons of chldren, under dfferent assumptons about the avalablty and desgn of cash transfer programs. These assumptons were bascally expressed n terms of dfferent values for two key polcy parameters: the means-test level of household ncome; and the transfer amount. Because predcted earnngs values were needed for all chldren n the smulaton, ths procedure also requred estmatng a Mnceran earnngs equaton for chldren n the sample, and usng t to predct earnngs n some cases. Also, because the ncome values accrung to each household were not symmetrc across dfferent occupatonal choces, standard estmaton procedures for the multnomal logt were not vald. An dentfcaton assumpton was needed, and we chose t to be that chldren whch are not enrolled n school work only n the market, and make no contrbuton to domestc work. Under ths assumpton, the estmaton of the model generated remarkably consstent results: margnal utltes of ncome were always postve, and very smlar across occupatonal categores. Tme spent workng by those enrolled n school, as a fracton of tme spent workng by those not enrolled, was always n the (0, ) nterval and was n the range, ndependently of whether work was domestc or n the market. When ths estmated occupatonal choce model was used to smulate the offcal (Aprl 00) desgn of the federal Brazlan Bolsa Escola program, we found that there was consderable behavoral response from chldren to the program. About forty percent of 0-5 year-olds not currently enrolled n school would accordng to the model enrol n response to the program. Among poor households, ths proporton was even hgher: sxty percent would enter school. The proporton of chldren n the mddle occupatonal category ( studyng and workng n the market ) would not fall. In fact, t would rse, margnally. Results n terms of the reducton of current poverty, however, were less heartenng. As currently desgned, the federal Bolsa Escola program would reduce poverty ncdence by just over one percentage pont only, and the Gn coeffcent by half a pont. Results were better for measures more senstve to the bottom of the dstrbuton, but the effect was never remarkable.

26 5 Both the proporton of chldren enrollng n school n response to program avalablty and the degree of reducton n current poverty turn out to be rather senstve to transfer amounts, and rather nsenstve to the level of the means-test. Ths suggests that the targetng of the Brazlan Bolsa Escola program s adequate, but that poverty reducton through ths nstrument, although effectve, s not magcal. Governments may be transferrng cash n an ntellgent and effcent way, but they stll need to transfer more substantal amounts, f they hope to make a dent n the country s hgh levels of deprvaton.

27 6 References Abramovay, M.; C. Andrade and J.J. Waselfsz (998): Melhora Educaconal e Redução da Pobreza, (Brasíla: Edções UNESCO). Albernaz, Ângela; Francsco H.G. Ferrera and Creso Franco (00): Qualdade e Eqüdade na Educação Fundamental Braslera, Dscusson Paper #455, Departamento de Economa, Pontfíca Unversdade Católca, Ro de Janero. Atknson, Anthony and Franços Bourgugnon (99): Tax-Beneft Models for Developng Countres: Lessons from Developed Countres, n J. Khallzadeh-Shraz and A. Shah, (eds.), Tax Polcy n Developng Countres, (Washngton, DC: The World Bank). Baland, Jean-Mare and James A. Robnson (000): Is Chld Labor Ineffcent?, Journal of Poltcal Economy, 08, pp Basu, Kaushk (999): Chld Labor: Cause, Consequence and Cure, wth Remarks on Internatonal Labor Standards, Journal of Economc Lterature, XXXVII, pp Bhalotra, Sona (000): Is Chld Work Necessary?, Mmeo, Cambrdge Unversty. Bourgugnon, Franços; M. Fourner and M. Gurgand (00): Selecton Bas Correcton Based on the Multnomal Logt Model, Workng Paper #003-04, CREST/INSEE, Pars. Bourgugnon, Franços and Perre-Andre Chappor (994): The Collectve Approach to Household Behavor, n Blundell, Preston and Walker (eds.), The Measurement of Household Welfare, (Cambrdge: Cambrdge Unversty Press). Camargo, José Márco and Francsco H.G. Ferrera (00): O Benefco Socal Únco: uma proposta de reforma da polítca socal no Brasl, Dscusson Paper #443, Departamento de Economa, Pontfíca Unversdade Católca, Ro de Janero. Canagarajah, Sudharshan and Haroold Coulombe (997), Chld Labor and Schoolng n Ghana, The World Bank, Washngton. Chappor, Perre-Andre (99): Collectve Labor Supply and Welfare, Journal of Poltcal Economy, 00, pp Dahl, Gordon B. (00), Moblty and the Return to Educaton : Testng a Roy Model wth Multple Markets, Econometrca, 70(6), Ferrera, Francsco H.G., Peter Lanjouw and Marcelo Ner (forthcomng): "A Robust Poverty Profle for Brazl Usng Multple Data Sources", Revsta Braslera de Economa.

28 7 Freje, Samuel and Luz F. Lopez-Calva (000): Chld Labor and Poverty n Venezuela and Mexco, mmeo, El Colégo de Mexco, Mexco Cty. Gertler, Paul and Paul Glewwe (990): The Wllngness to Pay for Educaton n Developng Countres: Evdence from Rural Peru, Journal of Publc Economcs, 4, pp Grootaert, Chrstaan and Harry Patrnos (eds.) (999): The Polcy Analyss of Chld Labor: A Comparatve Study, (New York: St Martn's Press). Hardng, Ann (ed) (996): Mcrosmulaton and Publc Polcy, (Amsterdam: Elsever). Heckman, James and E. Vytlacl (00), Econometrc evaluaton of socal programs, n J. Heckman and E. Leamer (eds), Handbook of Econometrcs, vol. 5, (Amsterdam: North- Holland) Lavnas, Lena and and Mara Líga Barbosa (forthcomng): An Evaluaton of the Urban Bolsa Escola n Brazl: The Recfe Experence, n Orazem, P., G. Sedlacek and P.Z. Tzannatos (eds.): (forthcomng). Parker, Susan and Emmanuel Skoufas (000): The Impact of Progresa on Work, Lesure and Tme Allocaton, IFPRI Fnal Report on Progresa, IFPRI, Washngton, DC. Ravallon, Martn and Quentn Wodon (000): Does Chld Labor Dsplace Schoolng? Evdence on Behavoral Responses to an Enrollment Subsdy, Economc Journal, 0, pp.c58-c75. Rocha, Sôna and João Sabóa (998): Programas de Renda Mínma: Lnhas Geras de uma Metodologa de Avalação, Dscusson Paper #58, IPEA/UNDP, Ro de Janero. Rosenzweg, Mark and Robert Evenson (977): Fertlty, Schoolng and the Economc Contrbuton of Chldren n Rural Inda: An Econometrc Analyss, Econometrca, 45 (5), pp Rubn, Donald (977): Assgnment to a Treatment Group on the Bass of a Covarate, Journal of Educatonal Statstcs,, pp.-6. Rubn, Donald and Paul Rosenbaum (985): The Bas Due to Incomplete Matchng, Bometrca, 4 (), pp Schmertmann, Carl P (994), Selectvty Bas Correcton Methods n Polychotomous Sample Selecton Models, Journal of Econometrcs, 60(-), 0-3 Sant Ana, S.R. and A. Moraes (997): Avalação do Programa Bolsa Escola do GDF, (Brasíla: Fundação Grupo Esquel Brasl).

29 8 Schultz, T. Paul (000), The Impact of Progresa on School Enrollment, IFPRI Fnal Report on Progresa, IFPRI, Washngton, DC. World Bank (00), Brazl: An Assessment of the Bolsa Escola Programs, Report 008- BR, Washngton, DC. Table : School enrollment and occupaton of chldren by age (0-5 years old) Total Not gong to school.6%.3% 3.4% 5.9% 8.5% 3.6% 6.% Gong to school and workng 8.0%.0% 4.0% 8.3%.5% 7.% 6.8% Gong to school and not workng 89.4% 86.7% 8.6% 75.8% 69.0% 59.3% 77.% Total 00.0% 00.0% 00.0% 00.0% 00.0% 00.0% 00.0% Source: PNAD/IBGE 999 and author's calculaton Table : Sample means. Characterstcs of chldren and of the households they belong to (0-5 years old only) Not Studyng Workng and Studyng Studyng Total Age Years of schoolng Household per capta ncome Earnng's chldren (observed) Years of schoolng of the most educated parent Age of the oldest parent Number of household members Race (Whte) 37.% 40.9% 5.6% 48.9% Gender (Male) 5.8% 65.% 46.9% 50.3% North 6.% 5.6% 6.0% 5.9% Northeast 40.3% 45.6% 9.9% 33.% Southeast 3.8% 6.% 43.5% 39.9% South 4.% 5.9% 3.7% 4.% Center-West 6.7% 6.7% 6.9% 6.9% Metropoltan area 8.%.8% 30.9% 7.% Urban non metropltan 47.5% 37.9% 53.0% 50.% Rural areas 34.3% 49.3% 6.%.8% Proporton of unverse 6.% 6.8% 77.% 00.0% Populaton,99,5 3,335,0 5,65,0 9,799,456 Source: PNAD/IBGE 999 and author's calculaton

30 9 Table 3: Log earnngs regresson (0-5 year-old chldren reportng earnngs) 0 to 5 years old Coeffcent S.E. P> z n obs 43 R 0.35 Dummy WS Age Years of schoolng (Age-Years of schoolng) Male Whte Urban non metropltan Rural Log of medan of earnngs by State Intercept Source: PNAD/IBGE 999 and author's calculaton Table 4: Occupatonal Structure Multnomal Logt Model: Margnal Effects and p-values Workng and Studyng Studyng Pseudo-R #obs ME P> z ME P> z 0 to 5 years old Total household ncome Earnng's chldren (What) Total people by household Age Years of schoolng (Age-Years of schoolng) Whte Male Max parent's educaton Max parent's age Number of chldren below Rank of chld Urban non metropltan Rural Source: PNAD/IBGE 999 and author's calculaton

31 30 Table 5: Impled Values for the Structural Parameters n the Occupatonal Choce Models (pooled and age-specfc) M α 0 α α D β 0 β β % % % % % % % % % % % % % % Source: PNAD/IBGE 999 and author's calculaton Table 6: Smulated effect of Bolsa Escola on schoolng and workng status (all chldren 0-5 years old) All Households Not gong to school Gong to school and workng Gong to school and not workng Total Not gong to school 60.7% 4.0% 5.3% 6.0% Gong to school and workng %.% 6.9% Gong to school and not workng % 77.% Total 3.7% 7.3% 79.0% 00.0% Poor Households Not gong to school Gong to school and workng Gong to school and not workng Total Not gong to school 4.3%.7% 37.0% 8.9% Gong to school and workng %.% 3.% Gong to school and not workng % 68.% Total 3.7% 4.7% 7.6% 00.0% Source: PNAD/IBGE 999 and author's calculaton

32 3 Table 7: Smulated effect on schoolng and workng status of alternatve specfcatons of condtonal cash transfer program (all chldren 0-5 years old) All Households Orgnal Bolsa escola's program Scenaro Scenaro Scenaro 3 Scenaro 4 Scenaro 5 Not gong to school 6.0% 3.7%.9%.%.8% 3.% 6.0% Gong to school and workng 6.9% 7.3% 7.4% 7.4% 7.4% 7.5% 6.8% Gong to school and not workng 77.% 79.0% 79.7% 80.3% 79.8% 79.3% 77.% Total 00.0% 00.0% 00.0% 00.0% 00.0% 00.0% 00.0% Poor Households Orgnal Bolsa escola's program Scenaro Scenaro Scenaro 3 Scenaro 4 Scenaro 5 Not gong to school 8.9% 3.7%.9% 0.6%.8% 3.6% 8.9% Gong to school and workng 3.% 4.7% 5.% 5.4% 5.% 4.9% 3.0% Gong to school and not workng 68.% 7.6% 7.9% 74.0% 73.0% 7.4% 68.% Total 00.0% 00.0% 00.0% 00.0% 00.0% 00.0% 00.0% Source: PNAD/IBGE 999 and author's calculaton note: Scenaro : transfer equal R$30, maxmum per household R$90 and means test R$90 Scenaro : transfer equal R$60, maxmum per household R$80 and means test R$90 Scenaro 3: dferent values for each age, no household celng and means test R$90 Scenaro 4: transfer equal R$5, maxmum per household R$45 and means test R$0 Scenaro 5: Bolsa escola wthout condtonalty

33 3 Table 8. Smulated dstrbutonal effect of alternatve specfcatons of the condtonal cash transfer program Orgnal Bolsa escola's program Scenaro Scenaro Scenaro 3 Scenaro 4 Scenaro 5 Mean Income per capta Inequalty measures Gn coeffcent Mean of logarthmc devaton Thel ndex Square coeffcent of varaton Poverty measures Poverty headcount 30.% 8.8% 7.5% 4.6% 7.7% 8.8% 8.9% Poverty gap 3.%.9% 0.8% 8.8% 0.9%.9%.0% Total square devaton from poverty lne 7.9% 6.8% 5.9% 4.6% 6.0% 6.8% 6.8% Annual cost of the program (mllon Reas) Source: PNAD/IBGE 999 and author's calculaton note: Scenaro : transfer equal R$30, maxmum per household R$90 and means test R$90 Scenaro : transfer equal R$60, maxmum per household R$80 and means test R$90 Scenaro 3: dferent values for each age, no household celng and means test R$90 Scenaro 4: transfer equal R$5, maxmum per household R$45 and means test R$0 Scenaro 5: Bolsa escola wthout condtonalty