Children Time and Poverty

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Children, time and poverty:

The Impact on Children of Easing

Poor Families Credit Constraints

Paola Pereznieto

Javier Escobal

Paper presented at the XVI ISA World Congress of Sociology, 23 29 July, Durban, SouthAfrica, Research Committee 53, Sociology of Childhood


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Introduction

A number of economic models have studied childrens time use, adopting a primarily

utilitarian approach which looks at the value accrued to households of childrensinvolvement in labour and/or education. These models are important to understand poor

families decision-making processes when facing economic constraints, including the use of

different household members time, particularly children, for productive purposes.

However, regarding children as purely economic actors undermines childrens basic rights tosurvival, development, protection and participation. Children who engage in labour activities

(either formal or informal, domestic or external) to complement family livelihoods run the

risk of dropping out of school, not having time for studying or leisure and in many cases,falling into harmful forms of labour which undermine their physical, emotional or mental

development. This is not always the case, however. In some contexts, particularly when it

does not interfere with schooling, work is not harmful to a childs development and where

her/his opinion has been considered in the decision-making, childrens work is accepted aspart of the childs upbringing, and can contribute positively to the households improved

economic status.

This paper draws on examples from Young Lives1quantitative and qualitative research and

analyses to illustrate how household decisions and the policy context can underpin

childrens role as economic actors. It focuses on how credit constraints can influence

household decisions to either invest in childrens schooling or engage them in economicactivities, with potential medium- to long-term repercussions for their wellbeing and level of

human capital accumulation. Additionally, the paper briefly explores the contexts under

which childrens agency, including combining school with work activities, can be positivefor their own development through greater socialisation, strengthening of useful skills,

interaction with family members, as well as contributing to their households livelihood

strategies.

The paper refers to the literature which analyses how factors like credit constraints and

livelihood shocks faced by households tend to limit their ability to invest in activities with

greater medium- to long-term returns, prioritising lower return, short-term gains eg

childrens increased time allocation to work instead of school. The paper then goes on toidentify the gaps in this existing literature, explaining how Young Lives is uniquely placed

to carry out this analysis and draw policy relevant conclusions on the factors enabling

childrens economic agency.

To illustrate Young Lives contribution to this knowledge set, insights will be drawn from

Young Lives quantitative and qualitative research data, to explore the reasons for economicdecisions regarding childrens time allocation, examining childrens perceived roles as

economic actors in relation to their poverty status. The examples are drawn from three of thefour Young Lives countries: Peru, India and Ethiopia facilitating a broader perspective of the

factors that contribute to childrens engagement in economic activities.

Results are consistent with the literature, suggesting that the choice between childrens

schooling and work time allocation is influenced by multiple factors, one of which is

1Young Lives is an international longitudinal study on childhood poverty and policy in Ethiopia, India (Andhra Pradesh),

Peru and Vietnam. Young Lives is funded by the UK Department of International Development, DFID.


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households credit constraints. Understanding these linkages is essential for identifying

specific policy measures and compensatory mechanisms that could be put in place to offsetthe adverse consequences of increased pressures on childrens time to allocate to competing

priorities, mainly school, work and leisure and allow them to exert more agency over this

decision.

Models for childrens time use

Childrens time use has been analysed using a variety of economic models which focus on

the value accrued to households of childrens time allocation to schooling and/or labour in

the short run, with respect to returns on investment in human capital (Becker, 1965). In this

utilitarian approach, the decision on how much time to allocate to these two activitiesdepends on expected returns to work relative to future income. The key variables are the

expected rate of return to human capital accumulation in the future relative to a householdsvaluation of income today. The marginal return to income is higher for poorer households,

so only when their valuation of education (the main component of human capital) issufficiently great (the valuation includes expected returns from more highly skilled jobs,

parents appreciation of education and social acceptance), will they forgo present income for

schooling. This model highlights the fact that, in the presence of inefficient credit markets -

as is often the case in developing countries - households are unable to smooth consumption

in the long run, which influences their inter-temporal decisions2 over work and schooling

(Becker, 1993).

Psacharopoulos (1999) developed a more specific model for time use, based on a

households utility function whereby adult family members and children contribute to

household income with the aim of maximising benefits, subject to time and budgetconstraints. In cases where the optimum utility includes the income derived from childrens

work, the opportunity costs for children is their time for schooling and leisure.

Other models focus on intra-household bargaining (Bourginon and Chiappori, 1994, in

Dehejia and Gatti, 2002 and Basu, 1999), where the time children allocate to work is a result

of a bargaining process within the household, and where the relative power of each family

member depends on her/his contribution to total household resources. In this case, childrenmight find it useful to work because they are awarded more authority within the household.

Although for simplicity these models take into consideration school and work as the two

only possible activities for children, it is important to consider the time children should

spend on leisure activities: eg playing, socialising in the community, or studying, whichcontribute positively to their psycho-social development (Bourdillon, 2006). Leisure tends to

be a substitute for work, and since leisure generates the least utility to families, a shift in

economic conditions that increases the rate of return of childrens work, will cause theirleisure time to be sacrificed (Dehejia and Gatti, 2002).

These economic models reflect a reality: children, mainly in poor households, are seen as

economic agents who have labour as their key asset. By approaching families

2In economics, inter-temporality means that certain actions and decisions can be made at different moments in time,according to what is most beneficial to the economic actor. In this case, it refers to households decisions whether to

optimize their economic wellbeing in the short or the long run.


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decision-making processes from a utilitarian perspective, these models may neglect many

key elements, such as childrens own perspectives and opinions on how to maximise theirown utilities, as well as the importance of respecting the rights of children to ensure their

development needs are met (Feeny and Boyden, 2004).

Debates on Child Labour: when does work conflict with childrens rights?

Child labour has been extensively researched in the development literature, with positionson the subject ranging from total opposition to any form of child labour to more recent

acceptance of child labour as a phenomenon that is necessary in some households for raising

additional income; in this context, child work is also seen as contributing positively to

childrens self-assurance and development (Bourdillon, 2006).

Conceptualising childrens right to education, freedom from economic exploitation and

leisure in developing countries should incorporate an awareness of the different ways ofunderstanding child work, given the diverse situations in which families live and themechanisms they draw on to ensure family survival and wellbeing. This means that certain

forms of work that children in the North would not engage in, are quite common, acceptable

and even appreciated by children and their communities in some developing countries

such is the significance of childrens contribution to the household or in the family farm

(CIDA, n.d.).

There is possibly a consensus around the worst forms of child labour, which are those that

damage childrens physical, psychological, social or moral development, and it is preciselyagainst these that Article 32 in the UN Convention on the Rights of the Child takes an

unambiguous stance. Other forms of child work which are not exploitative may be

considered acceptable or unacceptable according to the perspective and the context (Feenyand Boyden, 2004), but it is acknowledged that in many cases, children are regarded as

economic agents.

There are many factors to consider when analysing the consequences of child labour. One

key factor is the impact with respect to education. There tends to be agreement that work is

harmful when it interferes with schooling and the childs capacity to develop her or hishuman capital potential. Bhalotra (2003) explains that, to the extent that poverty pushes

children into work, child work results in the absence of equality of opportunity in human

capital acquisition, and is a mechanism for the intergenerational transmission of poverty.

Clearly, this implies that full time work is negative for children. Still, empirical research

shows that the majority of children are not employed in full time activities. (Guracello et al.,

2003).

A rights-based analysis of childrens time use focuses particularly on the extent to which

time deprivation may prevent the realisation of a childs rights to quality education (Art. 28)

and to leisure and rest (Art. 31). In most developing countries, childrens involvement inhousehold activities (either domestic or at the family farm / small business) is seen as a

desirable activity, contributing to childrens development and complementary to formal

education (Boyden, 2005; CIDA, n.d.). Where schools are accessible, evidence shows that aslong as households economic livelihoods are not compromised, children will attend school

and the time they spend on work competes marginally with schooling, although it tends to


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compete more significantly with leisure or study time (Dehejia and Gatti, 2002; Brown et

al., 2002).

However, as a result of poor families increased vulnerability to economic changes, childrenwho engage in labour activities (either formal or informal, domestic or external) tocomplement family livelihoods are always at risk of needing to alter their time use in

response to economic hardship. A shock to the household economy generates a change in

childrens opportunity cost of education: the need for short-term income increases, causing a

relative decrease in the discounted value of education.

Harper (2002) argues that child work is a manifestation of poverty, and in particular,tackling childhood poverty and the mechanisms which lead to the transmission of povertybetween generations and across the life course, could be an effective way to address chronic

poverty. One transmission mechanism is the under-investment in childrens human capital,

with consequences for future earnings (Guarcello et al., 2003).

In addition to poverty, there are a multiplicity of factors that influence the decisions of poor

families regarding child work and schooling, including the quality of school and itsaccessibility, parents education and their valuation of education, among others. Yet, one of

the key factors contributing to child labour is poor households vulnerability to risks and

their inability to access mechanisms to mitigate their impact, which have a direct bearing on

the possibility of fulfilling childrens rights to education and leisure.

Under these conditions, it becomes clear that policies targeted at reducing household povertythrough economic empowerment, particularly through lessening credit constraints, can be

effectively used to address potential trade-offs between childrens time for work, school and

leisure / play, reducing vulnerabilities, and ensure their rights are met in a sustainable way.

Macro-level policies promoting poverty reduction: their links to children

Countries poverty reduction strategies are geared towards promoting economic growth.

They encompass numerous policies that target different aspects of development, including

agricultural development, financial markets, gender empowerment, education, health, etc.The aim is that if effective, these distributional policies should contribute to poverty

reduction, thus achievingpro-poor growth.

In the last few years, one of the mechanisms through which poverty reduction policies have

aimed to promote poor households economic empowerment, encourage livelihooddiversification and reduce vulnerability to risk is through reducing the credit constraints of

the poor. This is usually done at two different levels:

1) Promoting adequate regulatory frameworks that will enable financial markets to develop,

and particularly reaching poorer communities, who are frequently without financialservices because of the risk implied by lack of collateral or legal mechanisms that can

ensure repayment (Beegle et al., 2003).

2) Working with communities at the micro-level, by encouraging microcredit institutions to

provide poor families with options to increase their productivity (when the amount ofcredit is sufficient) or to smooth consumption in the face of shocks (Khandker, 2003).

With respect to the impact of microfinance, the United Nations Capital Development Fund


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(UNDP, 2006) explains that it has been shown to (i) help very poor households meet basic

needs and protect themselves against risks; (ii) improve household economic welfare andenterprise stability or growth; and (iii) contribute to womens empowerment, by supporting

womens economic participation, thus promoting gender equity and improving household

wellbeing. UNICEF (2000), for example, recognises the value of these initiatives bysupporting microcredit schemes when lack of access to small loans is identified as a key

obstacle to improving the situation of women and children. This entails a two-pronged

approach that combines microcredit with social messages, which often contributes to ahigher demand for basic social services.

To understand the impact on children of making microcredit accessible to poor households,

it is essential to move beyond aggregate analysis at the household level and look at the

intra-household impacts of such credit provision.

The role of credit in decisions over childrens time allocation

A number of recent models show that, by preventing households from trading off resources

inter-temporally in an optimal way, credit constraints give rise to inefficiently high childlabour (Dehejia and Gatti, 2002; Beegle et al., 2003; Guarcello et al., 2003). In one sense,

by letting children work, parents are borrowing from the future rather than investing in the

human capital that would make children more productive in the future. This strategy, which

can be optimal for a family faced with time and resource constraints, is not efficient giventhat the present discounted value of another hour of schooling is greater than the return to

another hour of work3 (Brown, et al., 2002).

Basu (1999) explains this phenomenon by the fact that, in developing countries, a common

reason for children to discontinue education is not chronic poverty, but a temporary crisis inthe family. As outlined before, results of both theoretical and empirical studies show that

households, particularly the poor, aim to smooth their consumption to avoid the troughscaused by external shocks (such as droughts, floods, the illness of the main breadwinner,

dowry payments) in the long run, which is difficult in the absence of an adequate credit

markets (Guarcello et al., 2003; Beegle et al., 2003). Thus, when faced with credit

constraints, children in the household are frequently the economic agents that contribute tosmoothing consumption by providing additional income. Conversely, evidence suggests that

if credit is widely available, households can borrow to smooth income variability without

disrupting childrens education or leisure time (Deheijia and Gatti, 2002).

Childrens participation in the workforce, however, does not necessarily imply that they willdrop out of school or that work will cause a loss in school attainment. Sedlacek et al.(2005)

explain that the research establishing the link between child labour and education is limited.

For example, in Latin America, child labour does have a negative and significant effect onschool enrolment, but the greater adverse effect is on the pace of progression through school

3 In the framework of human capital investment, the general principle is that it is more efficient to invest in educationduring childhood to maximize the level of human capital in an individual as an adult, contributing significantly to the

probability of earning a higher income. When discounted at present value, the returns from this more highly paid job are

higher than the returns from the income received through childrens work activities. Thus, credit constraints can pushhouseholds to inefficiently increase the number of a childs work hours, reducing the time the child can invest in

developing its human capital, through schooling.


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and the quality of attainment through attendance. Schooling is not a full time activity, so the

trade off between work and schooling time might not be significant these two activitiesmight co-exist at the expense of leisure activities (Dehejia and Gatti, 2002).

Rosati and Rossi (2003) analyse the decision-making process in a more nuanced way. They

look at the time that children devote to work, both when it is their only activity and when

they combine it with schooling. They emphasise the importance of accounting for thenumber of hours spent working, which is used as a measure of child welfare (a measure of

foregone schooling and leisure), but it is also essential to evaluate the cost of work in terms

of human capital accumulation.

Given that multiple strategies have been attempted to reduce child labour and its impact onschool attainment with few having been successful, promoting access to credit as a means to

reduce household vulnerability, promote livelihoods and reduce child labour is a highly

policy relevant topic. In fact, as Dehejia and Gatti (2002) and Guarcello et al. (2003)

suggest, policies aimed at developing financial and capital markets, and at improving riskcoping and risk reduction mechanisms, could be effective instruments to reduce the extent of

child labour and increase human capital accumulation.

Another issue to consider in relation to access to credit is households asset composition. In

general, assets are found to be negatively correlated with child labour (Brown et al., 2002)

given that assets help to ease the credit constraints for some households since they can be

used as collateral. Cockburn (2001), however, demonstrates how different physical assetshave different effects on child labour supply according to their degree of substitution.

Increased access to physical assets that require relatively more child labour, such as small

animals, will tend to increase child labour participation and reduce child schooling andleisure. Consequently, the choice of assets to be promoted in a poverty alleviation

programme must consider the effects on child labour and schooling. Thus, if access to assets

is being promoted with the policy objective of reducing child labour and increase childschooling, care should be taken to encourage the accumulation of those physical assets that

increase household income, ease credit constraints and encourage substitution away from

child labour. This is not a trivial policy issue as we will see from the example from theYoung Lives research where there was evidence of increased child work after the

implementation of a poverty reduction policy promoting access to credit to acquire assets,

which turned out to be intensive in child labour.

In addition to policies aimed at generating access to credit markets, policies providing safetynets are also powerful instruments to promote school attendance and reduce child work

(Guarcello et al., 2003). Cash transfer programmes, often conditional on school attendance(like Bolsa Escola in Brazil, Oportunidades in Mexico and Juntos in Peru), have been laudedas one of the best ways to tackle this problem (Sedlacek, 2005; Perry et al., 2006). They

work with a similar principle to microcredit: the transfer relieves the households credit

constraint, helps it smooth consumption and thus encourages children to stay in school.Nevertheless, one shortcoming is sustainability: these programmes are expensive,

particularly if provision is comprehensive; they are often unaffordable in developing

countries in the long run. Microcredit, however, has been shown to be sustainable, whether

they are implemented for profit or non-profit; these mechanisms can therefore be more

easily implemented among the countrys poor. This does not mean that social protectionmechanisms such as cash transfer programmes should be ruled out, because not all families


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in poor communities have the characteristics required to access credit (particularly in the

short-term); however, credit schemes can complement these efforts, perhaps in a moresustainable way.

Empirical studies and findings

Although access to credit has been recognised as central to child labour, there has been little

empirical work done on the subject, partly because data sets do not provide all theinformation needed to carry out a comprehensive analysis. One of the main problems is that

credit access is difficult to measure from Living Standard Measurement Surveys, which

usually only ask whether a household had a loan or bank account this is not a good

measure of access to credit, since some households that have access to credit might not havehad to borrow.

In addition, without access to information on the time use of children outside the market,estimation of these models is limited to datasets that do not distinguish clearly between the

time children spend on school, work and leisure, so that the resulting analysis on childrens

time allocation is only partial (Apps, 2002).

Jacoby and Skoufias (1997) carried out the first serious empirical work that addressed theissue of poor households which lack access to credit markets and which might draw on child

labour when faced with income shocks. With data from six Indian villages, the authors

concluded that childrens economic activity is used by poor households as a means to insure

themselves against risks. Dehejia and Gatti (2002), on the other hand, carried out their workat an aggregate level, measuring child labour as a country aggregate and approximating

credit constraints by the countrys level of financial development. Beegle et al. (2003) were

the first to use panel data for their analysis, focusing on Tanzania. The study finds thathouseholds respond to transitory income shocks by increasing child labour, but the extent to

which child labour is used as a buffer is less when households have access to credit.

Guarcello et al. (2002) analysed the response of child labour to income shocks (loss ofemployment, death in the family, droughts in the region, etc.) in Guatemala. They identified

a sub-sample of credit-constrained households and found that credit rationing is associated

with higher child labour and that shocks significantly increase the proportion of working

children. Ersado (2002) found that in Nepal, Peru and Zimbabwe, improving access to credithas potential for alleviating child labour and enhancing school enrolment in rural areas,

although less so in urban areas. Given that Living Standard Measurement Surveys, often

used to analyse households economic situation, have little information on credit accessErsado used data from commercial banks at the community level as proxy measures of

access to the formal credit market. Acknowledging it as a partial source of information on

credit access, he warned that results should be interpreted with caution. However, despite thelimits of his information, the results are still consistent with other findings in the literature.

The empirical work to date has therefore clearly endorsed the thesis that improving credit

access has great potential to reduce child labour. Given the policy relevance of such a

conclusion, it is critical to have a broader and more precise evidence base that can be useful

for influencing policy.


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Young Lives research and findings

The existing evidence strongly suggests that easing poor families credit constraints has a

positive impact on the reduction of child labour and on the promotion of schooling andleisure activities for children. However, there is an acknowledgement in the literature of

insufficient information and data linking credit constraints and households decisions

resulting in studies having to approximate their analysis through aggregate variables orproxies for information on credit and time allocation. Beegle et al. (2003) were closer to

having a good dataset in their panel survey for Tanzania; but as the survey was not designed

to research the connection between access to credit and child labour, the findings are not asprecise.

Young Lives is in a strong position to do research on identifying the conditions which push

household members, including children themselves, to make decisions during their lifetime

regarding childrens time allocation, particularly with respect to consumption, shocks, credit

markets, availability of schools and childrens agency.

Young Lives carries out both quantitative and qualitative research which it frequentlyanalysed in tandem to develop a more comprehensive perspective on the policy issues it is

examining. This research generates informative conclusions and messages to inform

policy-makers.

Focusing on childrens time allocation and the impact of credit constraints, we have some

interesting findings from the data available to date, which we will look at below. However,given its longitudinal nature and the fact that the second round of data collection has been

revised to include precise and specific questions that will enable an understanding of the

connections between credit constraints and child labour, from the first half of 2007, Young

Lives will be a unique source of information on the factors that make credit markets workfor children.

Let us look at three examples based on Young Lives current research which suggest some

initial conclusions; we will then briefly outline the possibilities of the projects futureresearch based on the its second round of data collection and further qualitative research

during its second phase.

Quantitative analysis: Improvement of credit constraints and child labour in Peru

In line with the review of the literature, when credit constraints are prevalent, as is the case

for most poor households in urban and rural Peru, short-term economic shocks may haveimportant long-term consequences, particularly on educational outcomes.

Based on panel data from Peruvian households, Escobal et al. (2005) looked at how shocks

affect the progress of 6 to 14 year-olds children in the Peruvian school system. The authors

found no evidence of negative shocks resulting in further overage4. However, although

Peruvian parents seem to be reluctant about taking their children out of school when facing

an economic shock, there is evidence that negative shocks reduce the effective accumulation

of human capital through cuts in educational expenditure both in urban and rural areas.Escobal, et al identified two ways in which households modify expenditure on education

4Overage occurs if the child repeats a school year or drops out temporarily or permanently from the school system.


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when faced with adverse economic shocks: moving their children from private to public

schools5 and reducing educational spending on children

6. This result is consistent with

Patrinos and Psacharopoulos (1997) who found that child labour and schooling in Peru may

be complementary, which means that rather than substituting school time for work, both

activities are carried out by the child during the course of a day.

To explore this issue further, we analyse data from the 8-year-old cohort in the PeruvianYoung Lives sample. We explore the relationship between credit constraints and changes in

the time devoted to school and work. It is important to highlight from the outset that, as seen

in table 1, in this sample consisting of nearly 1000 children, most of them, with theexception of 6 (1.5% of the sample) go to school. Nevertheless, approximately 20% of the

sampled children acknowledged they work to earn additional income for their families.

Further, more than half of the sampled households admitted to having a credit burden. It is

interesting to note that households that have important debt are slightly more likely to have

children that combine school and work. The analysis presented in table one provides ageneral overview of the link between households debt status and childrens participation in

school and work. However, at this stage the analysis explicitly excludes other variables that

might also have an impact on the school/work decision, which need to be controlled for in

further analysis to asses whether serious debt has a strong impact on schooling outcomes.

Table 1Relationship Between Debt Status and Children School/Labour Outcomes

Only Studies Studies and

Works

Only

Works

Does not

Work orStudy

Total

Has an important debt 41.6% 11.1% - - 52.7%Has no important debts 36.7% 9.1% - - 45.8%

No response 0.4% 0.3% 0.3% 0.6% 1.5%

Total 78.7% 20.4% 0.3% 0.6% 100.0%

Source: Peruvian Young Lives 8 year cohort sample.

On the other hand table 2 shows that those children combining work and school in general

have lower mathematics, reading and writing skills as assessed by the YL survey than thoseonly attending school. Items evaluating these competencies were included in the Young

Lives questionnaire and administered to the 8 year cohort7. Cueto et al (2005) indicate that

since each achievement area was only evaluated through a single item and correlationsbetween were positive, a factor analysis was carried out to generate a composite

achievement for the three areas tested. The last column in Table 2 presents this overall skill

score.

Table 2

5 Perus public education has fared poorly in international evaluations (see results from PISA, www.pisa.oecd.org)6This refers to expenditure on books, uniforms, school utensils and in some cases, extra tuition, even when there are noschool fees.7The reading evaluation required children to read three letters (N, A, P); one word (pan, Spanish for bread), and one

sentence (El pan es rico, Spanish for the bread is tasty). The item to measure writing skills required children to write thesentence me gustan los perros (Spanish for I like dogs). Finally to asses numeracy skills, children were required to solve

a basic multiplication (2 x 4).


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Work and Skills

(Percentage of Children Doing Excercises Right)

Math Skills Reading Skills Writing

Skills

Skills Score

Only Goes to School 59.8% 84.5% 59.9% 1.219

Goes to School and Works 53.3% 72.9% 40.9% 1.018

Difference is Statistically Significant

(95%) NO YES YES YES

Source: Peruvian Young Lives Sample (8 Year Old)

Appendix 1 shows the results from a regression analysis looking at the effect that credit

constraints may have on school and work decisions, as well as the effect that these decisions

can have on childrens accumulation of skills though schooling. The table shows the

following: column 1 has the determinants of the score for children that combined school and

work; column 2 shows the same determinants for those who only attended school; column 3shows the probability of working in addition to going to school. The three equations have

been estimated simultaneously. To identify the selection equation adequately, twoexogenous variables were used: (a) household has a serious debt; and (b) there is no father in

the household. We hypothesized that these variables affect the decision of the child

attending school or/and work, but only contribute to childrens performance when the childworks. Interestingly both variables were jointly significant in the selection equation and

neither appears significant if included in the skill equation8.

Our results show that having an important debt can affect, though marginally, the probability

of children working in addition to attending school. Other key determinants of work are alow socio economic status (proxied by access to electricity and mothers educational level),

the distance to school and having no father in the household. It is interesting to note thatcontrolling for the decision to combine work and schooling, mother education plays a largerrole in increasing skills for those children that just attending school. This implies that even if

combining both activities, children learn more at school when supported at home by a better

educated mother. However, for these children with more highly educated mothers who havethe skills to find a better paid job outside the house, younger siblings may generate a

competing demand for mothers time, so children might be required to look after their

younger siblings. In this case, the data shows that a larger number of children under 3 in the

household may result in less time for studying and lower school achievement. Policies thatpromote access to free or cheap child care facilities may help to shift childrens time away

from caring for their sibling and increase their time for learning or leisure.

To ensure these results are robust to alternative skills indicators, we carried out a second

regression replacing the skills index with the composite score constructed from the Ravens

test administrated to the eight year cohort9. Although the appropriateness of this test for

Peruvian eight year olds has not been validated, it interesting to note that the results seem

reliable10

. Given these results we can safely claim that the overall item indicator does

represent a good measure of general ability.

8The SmithBlundell test for exogeneity was conducted to confirm these results.9Raven's Progressive Matrices, a test of general ability, is often suggested as a means of identifying non verbal IQ.10 As measured by Cronbach's alpha reliability coefficient, which is reasonably high for each of the three sections of the

test (0.769, 0.843 0.858) and is even higher when calculated for all items together (0.929).


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Thus, Young Lives results in Peru show that although work does not generally cause

children to drop out of school, combining both activities has a significant impact onchildrens learning and thus their accumulation of human capital. This is exacerbated when

the family faces an important debt burden. By promoting mechanisms to release households

credit constraints, debt burdens could be better managed and thus result in children beingable to allocate more time to school and learning.

Findings from Young Lives Qualitative Research in Andhra Pradesh, India

Box 1 outlines the second example from Young Lives research, illustrating the connection

between poor households access to credit and childrens increased time allocation to

schooling. It draws on a sub-sample of four sites in Andhra Pradesh, India, where in-depthqualitative research was undertaken with beneficiaries of womens Self Help Groups

(SHGs) and their leaders to find out how the SHG and the loans received by members, arebeing used to improve household wellbeing, particularly that of children. The general

conclusion was that, despite the small size of the loans, they are contributing positively tosmoothing families consumption and thus allowing children to stay in school.

Box 1: Self Help Groups in Andhra Pradesh (AP), India

(see Jones and Mukherjee, 2006)

In the context of poverty reduction and economic development in AP, the promotion of

microfinance has been identified as a primary engine for community development.

In particular, womens SHGs, whose main objective is the provision of small loans to womenmembers, have been promoted extensively by the Indian government as a model for community

development at the grassroots level.

Microcredit institutions have thrived and there are public, NGO, private and donor funded

initiatives.

Young Lives research has found several limitations in these mechanisms, such as the fact that

the small loans provided are insufficient for channelling women into productive investments to

become self-employed, which is their original intention.

However, interviews with members of self help groups revealed that these small loan are used

for consumption spending, mainly allocating resources to childrens wellbeing, primarily

spending on schooling and nutrition, and reducing the likelihood of children dropping out ofschool. This illustrates clearly that a relaxation of credit constraints tends to have a positive

impact on investment in human capital, as more time is allocated away from work to school.

An additional positive externality of SHGs in AP is that womens greater control over resources

has strengthened their role in decision-making in the household, translating into more resources

being spent on child development.

From this preliminary evidence, in the case of AP, microcredit for women can be used as a

policy measure to ensure that childrens rights are pursued.


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Findings from Young Lives Quantitative and Qualitative Research in Ethiopia

The next example, in box 2, draws on research carried out in Ethiopia by the Young Lives

team, targeted mainly at identifying how the first phase Ethiopias Poverty ReductionStrategy Paper had performed in terms of improving child wellbeing by making policy

recommendations to improve the attention given to children in the second PRSP. The

research draws on a sample of 1,999 households with at least one child aged 6 to 17 in 2002,and on additional household data collected from 3,115 children aged 7 to 17 years from 20

sentinel sites. From this, the Young Lives project sought to understand the impact on child

labour and schooling of public policy interventions formulated within the PRSP(Woldehanna et al., 2005). These quantitative findings were complemented by in-depth

interviews. In this case, the findings endorse Cockburns (2001) research, which suggests

that if credit is used to buy assets, it will only have a positive impact on childrens schooling

if such assets are not intensive in child labour.

Box 2: Ethiopia and Agricultural Development Led Industrialisation

(See Woldehannaet al., 2005)

Ethiopias Agriculture Development Led Industrialisation (ADLI) is one pillar of Ethiopias

PRSP. Its aim is promoting economic growth by stimulating Ethiopias agricultural sector which

has comparative advantage.

The policy promotes labour-intensive agricultural activities through diverse mechanisms, one of

which is credit provision to families for buying agricultural equipment and assets, like livestock.

Although the programme has had some initial achievement in promoting sectoral development

and the livelihoods of families involved in it, Young Lives research shows that it has had some

unexpected impacts on childrens time allocation: ownership of livestock in Ethiopia is

negatively associated with child enrolment since children's labour is usually used for herding

cattle.

Children with increased responsibilities for rearing livestock were shown to spend less time in

school and on school-related activities.

This means that in this context, even if the policy is raising the sectors productivity with a

positive effect on aggregate rural household income and a relaxation of credit constraints, it has

had some unexpected impacts on child wellbeing mediated through intra-household dynamics.

Accordingly, to ensure that the policy incorporates childrens wellbeing as one of its objectives, it

is essential to identify specific actions. One way is ensuring that the loan provided to thehousehold is sufficient not only to buy livestock, but to ensure that they can employ additional

external help to free childrens time from herding and shifting it to school or leisure, and

encouraging their human capital development.

From these three examples, we can see the current potential of Young Lives to do analyses

relating child labour and the reduction of constraints for access to credit. But the projects

real potential to generate unique new knowledge on this issue will be realised after thesecond round of quantitative data collection because:


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1. The new questionnaire asks specific questions on childrens time allocation, not only to

childrens carers, but to children themselves. This will be critical in analysingcontinuous and precise changes in time allocated to work, school and leisure; this

information is seldom available from household questionnaires, and will enable us to

track the marginal changes that cause shifts from one activity to another.

2. The questions on loans are very detailed, including a question on whether the individualwould get a loan in response to a shock.

3. There are comprehensive questions on shocks and household responses to them.

4. The same households and children will be asked the same questions again three years

later, enabling us to understand their household decisions, and the implications for

children.

5. Having a panel, after the second round of data collection, will allow to better control for

un-observable factors that can skew the estimated relationship between creditconstraints and child time allocation.

Conclusions

Childrens involvement in work is not always problematic, but it can be a violation of

childrens rights when it is exploitative or interferes with their possibilities to fulfil other

rights, such as the right to quality education and leisure, and undermines their potential todevelop their human capital and thus potentially causes an intergenerational poverty trap.

Understanding household and childrens decisions over time use is essential in trying to

identify the factors that will help keep children in school and minimise their work time,particularly in circumstances of economic adversity like external shocks.

Understanding the linkages between macro-level policies, such as microfinancemechanisms, is essential in terms of identifying the different compensatory policies

governments can put into place to offset the potentially negative consequences of childlabour, and maximising the potential to ensure that childrens wellbeing is promoted in

context-appropriate ways. This implies that families are able to preserve their level of

consumption and thus mitigate vulnerabilities through the use of credit, and not childrens

work.


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Appendix 1

Skill Test Performance Conditional on School and Working Decisions

(Endogenous switching regression model)

Skills Score Selection Equation(1) (2) (3)

ChildrenStudies and Work

ChildrenOnly Studies

(Probability of Workingand Studying)

Gender of the Child 0.045 -0.002 0.202 *

(0.067) (0.026) (0.121)

Child Age (in months) 0.362 *** 0.136 *** -0.019

(0.102) (0.042) (0.194)

Age at which Child Started School -0.083 -0.084 *** -0.051

(0.062) (0.026) (0.120)

Number of Rooms in Dwelling 0.001 0.009 -0.016

(0.021) (0.008) (0.039)Has Electricity -0.158 ** 0.056 -0.389 ***

(0.085) (0.037) (0.149)

Parents own their Dwelling -0.088 0.026 0.161

(0.070) (0.029) (0.132)

Mother's Education -0.008 0.021 *** -0.034 ***

(0.010) (0.004) (0.016)

Speaks a Native Language 0.047 -0.103 *** 0.202

(0.100) (0.051) (0.199)

Body Mass Index - Mother 0.012 0.004 -0.033 ***

(0.009) (0.004) (0.017)

Body Mass Index - Child -0.008 0.013 ** 0.001(0.018) (0.007) (0.034)

School is Private -0.176 -0.069 0.223

(0.147) (0.043) (0.249)

# family member above 3 years -0.005 -0.027 *** 0.027

(0.018) (0.007) (0.034)

# of young siblings under 3 -0.094 -0.025 -0.045

(0.069) (0.028) (0.129)

Distance to School -0.006 ** 0.000 -0.012 ***

(0.003) (0.001) (0.006)

Area is Urban 0.127 0.058 -0.299 ***

(0.082) (0.036) (0.153)Father is missing 0.279 ***

(0.128)

Household has a Important Debt 0.130 *

(0.684)

Constant -2.046 -0.436 1.188

(1.012) (0.427) (1.937)

Number of obs 638

Wald chi2(15) 35.23 Prob > chi2 0.0023

LR test: indep. eqns. chi2(1) 3.85 Prob > chi2 0.0499

Source: Own Estimation based on Peruvian Young Lives 8 year cohort sample.


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