# **Notes**

1 Previous work discussing evidence on the relationship between cash transfers and child labor, building on the earlier papers included also in this review, includes Edmonds (2007) and Fiszbein and Schady (2009). Edmonds (2007) also discusses the effect of a range of other interventions on child labor. Fiszbein and Schady (2009) also examine the effects of conditional cash transfers on various of other outcomes (including adult labor). 2 Over the past decade, developing country governments have begun to adopt conditional cash transfers as social protection instruments at a rapid pace. See Fiszbein and Schady (2009) for a comprehensive review of the recent proliferation of conditional cash transfer schemes in developing countries.

3 The three principal international conventions on child labor recognize this complexity and set the legal boundaries that define children’s work that is targeted for elimination. The ILO Convention No. 138 determines the minimum age below which children should not work and the minimum ages for light and hazardous work. The ILO Convention No. 182 specifies the worst forms of child labor that are prohibited for all children under the age of 18. The United Nations Convention on the Rights of the Child aims to protect children from economic exploitation and from performing any work that is likely to be hazardous or to interfere with the child's education or to be harmful to the child's health or physical, mental, spiritual, moral, or social development. The international legal standards contain a number of flexibility clauses left to the discretion of the competent national authority in consultation (where relevant) with worker and employer organizations (e.g., minimum ages, scope of application). There is no single legal definition of child labor across countries, and concomitantly, there is no single standard statistical measure of child labor consistent with national legislation across countries. (Text in this footnote is adapted from standard Understanding Children's Work description.) 4 Moreover, we must keep in mind that schooling, work, and other activities, including leisure and sleep, are jointly determined. 5 There is also variation in the reference period. Some studies consider work in the seven days prior to the household survey, whereas some studies examine work in the past 12 months. Finally, some studies present results for a few separate categories of activities instead of focusing on a comprehensive indicator for participation in work. 6 Initially, most evaluations of the impact of cash transfer interventions on human capital accumulation focused on selfreported school enrollment or attendance. A new generation of studies focuses on more elaborate outcomes, such as performance on standardized tests. A similar development has not taken place for child labor, and we hope that this review can serve as a starting point. 7 For a formal model, see for instance Ravallion and Wodon (2000). 8 For a theoretical discussion of the effects of cash transfers on school participation see, inter alia, Fiszbein and Schady (2009). 9 If leisure is a normal good. 10 For a discussion of investment of cash transfers in productive assets, see Fiszbein and Schady (2009). 11 The full literature search was conducted in early 2011 by Understanding Children’s Work (UCW) to build a comprehensive database of child labor impact evaluations. The database is updated regularly and can be found at http://www.ucwproject.org/impact-evaluation/inventory-impact-evaluations.aspx. We considered works identified to the end of 2012. We considered only papers written in English and did not consider dissertation chapters that did not appear as separate (working) papers. Of course, relevant impact evaluations continue to appear after this date. Authors of relevant papers not included in this database are invited to share their papers. 12 We exclude simulation studies, such as Bourguignon, Ferreira, and Leite (2003), studies that capture the effect of multiple programs at once, such as Cardoso and Portela Souza (2003), and studies of in-kind transfers, such as Ravallion and Wodon (2000) and Kazianga, de Walque, and Alderman (2009). 13 We do not discuss Rubio-Codina (2010) and Schultz (2004) in the main text because these studies rely on the same data and find results comparable to those of Skoufias and Parker (2001). 14 A table with the exact definition of the outcome variable for each individual study is available on request. 15 Figure 2 does not include the dose-response estimates for South Africa’s Child Support Grant (DSD, SASSA, and UNICEF 2012) discussed in the text, which differ in nature from the “binary” treatment results discussed in the remainder of this paper. 16 This result should be interpreted with some care because the authors do not show whether differences between individuals treated from an early age and those treated from the age of 14 are significant. 17 The program did not affect children’s participation in care for other children in the household, care for adults in the household, or work outside the household for income (other than domestic work). The estimates are not always robust for different specifications. 18 That is, -0.6 hours for children living in a household with a male pensioner and -0.5 hours for children living in a household with a female pensioner. 19 Edmonds (2006) discusses several alternative hypotheses that could explain the observed changes in child labor and school participation in response to the realization of anticipated income but concludes that credit constraints are the most plausible explanation. 20 To correct for age-specific trends not related to the reform, the author compares difference-in-differences estimates for rural households to difference-in-differences estimates for urban households (which were not affected by the reform) in a tripledifference framework. 21 To calculate the standard errors associated with these estimates, we assume that the covariance between the individual estimates is zero. Note that the overall impact of the program may not be statistically significant even if some of the underlying estimates for age and gender subgroups are statistically significant.

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