Poverty has significant, detrimental, and long-ranging effects on child development (Walker and others 2011). Programs and policies around the world have attempted to address poverty to improve outcomes for children and adolescents, and one popular approach is to use cash transfer (CT) programs (Engle and others 2011). CT programs support vulnerable populations by distributing transfers to low-income households to prevent shocks; protect the chronically poor; promote capabilities and opportunities for vulnerable households; and transform systems of power that exclude certain marginalized groups, such as women or children (Devereux and Sabates-Wheeler 2004). The economic rationale for CT programs is that they can be an equitable and efficient way to address market failures and reach the most vulnerable populations (Fiszbein and others 2009).When the provision of CTs is tied to mandatory behavioral requirements, they are conditional cash transfer (CCT) programs, which operate by giving cash payments to families only if they comply with a set of requirements (the “conditions” of the cash transfer), usually related to health and education (de Janvry and Sadoulet 2006). For example, many CCT programs distribute benefits conditional on the use of preventive health care services, attendance at health and nutrition education sessions designed to promote positive behavioral changes, or school attendance for school-age children (Barrientos and DeJong 2006; Lagarde, Haines, and Palmer 2007). Definitions of age groupings and age-specific terminology used in this volume can be found in chapter 1 (Bundy and others 2017).Unconditional cash transfer (UCT) programs are those in which families receive cash benefits because the household falls below a certain income cutoff or lives within a geographically targeted region; however, no conditions are tied to the transfer (Barrientos and DeJong 2006). Given that UCTs do not monitor the behavior of households or require visits to health clinics, these programs are operationally less complex and easier for governments to implement because they do not require a well-functioning health care sector. Thus, administrative costs are often substantially lower for UCTs than for CCTs. School feeding is an example of a noncash transfer and is discussed in chapter 12 of this volume (Drake and others 2017).Both CCTs and UCTs assume that parents are income constrained, and thus do not have the money to spend to meet the most pressing needs of their families (for example, nutritious food, medical treatment). Providing greater purchasing power allows parents to choose what goods to buy and in what quantity and of what quality. The economic rationale for conditioning transfers on certain behaviors is that individuals or households do not always behave rationally because they have imperfect information, they behave myopically, or there are conflicts of interest between parents and children (Fiszbein and others 2009). In addition, conditioning transfers on human capital creates positive externalities and usually has more political support. However, many argue that conditioning transfers is paternalistic and costly to monitor and that the neediest households might find it too costly to comply (Grimes and Wangnerud 2010; Handa and Davis 2006; Popay and others 2008; Shibuya 2008).Mexico’s Prospera (previously Progresa and Oportunidades) and Brazil’s Bolsa Familia were among the first CCTs to be designed in the late 1990s and have been models for programs throughout Africa, Latin America, and the United States (Aber and Rawlings 2011; Fiszbein and others 2009). By 2011, CT programs covered an estimated 750 million to 1 billion people worldwide; India (48 million households), China (22 million households), Brazil (12 million households), and Mexico (5 million households) were among the countries with the largest programs (DFID 2011). In spite of the common features of many CTs, there is a large degree of heterogeneity across countries and programs with regard to program benefits, conditions, requirements, payments, and targets. For example, in Ecuador and Peru, the transfer is a fixed payment per family per month that does not vary by household size, whereas in Brazil, Malawi, and Mexico the benefits depend on the number, age, and gender of children in the household. In some programs (for example, Prospera in Mexico and Familias en Accion in Colombia), the payment is greater for secondary-school-age children than for primary-school-age children. Similarly, the average transfer amount varies greatly, ranging from 6 percent in Brazil to 22 percent to 29 percent in Mexico and Nicaragua to 200 percent of pretransfer consumption in Malawi (Fiszbein and others 2009; Miller, Tsoka, and Reichert 2010). The size of the transfer reflects the goal of the program, which can be to move households to a minimum level of consumption (Colombia, Jamaica, Mexico) or to base the size of the transfer on the opportunity cost of health care (Honduras) or on the transportation costs to the public health facility (Nepal) (Gaarder, Glassman, and Todd 2010).This chapter first reviews the evidence from CT programs, both conditional and unconditional, throughout low- and middle-income countries (LMICs), focusing specifically on the direct effects on child and adolescent health and education outcomes. It then discusses the design of CT programs and why and how they could theoretically affect outcomes for young children and adolescents. Although there are other types of social safety net programs, such as voucher schemes, food transfers, and user fee removals, we focus on CTs because many countries are switching to such programs given that they are easier to distribute. In addition, the evidence for many other types of programs is too sparse for them to be included in the analysis.CT programs are hypothesized to improve child and adolescent outcomes via the family investment model, according to which families have more money to spend on inputs (Guo and Harris 2000; Yeung, Linver, and Brooks-Gunn 2002) or more time to spend with children (Del Boca, Flinn, and Wiswall 2014), and the family stress model, according to which maternal depression and stress are lower because household resources are higher (Mistry and others 2004).CCT and UCT programs can vary widely in their objectives, design, and context. While many programs have the broad goals of reducing poverty and improving human capital, some are more focused on decreasing poverty, some on improving education outcomes, some on improving health outcomes, and some on improving nutrition outcomes. Program designs reflect these differences in objectives with differences in conditions, targeting, transfer size, beneficiaries, and complementary components. Consequently, although CCT and UCT programs have the potential to effect multiple outcomes by lessening a household’s budget constraints, some programs and contexts may be better suited to improving child and adolescent health and education outcomes. For example, programs in a handful of countries are beginning to experiment with the integration of parenting support or nutritional support—a direct intervention to promote child development—within CT programs (for example, in Colombia, see Attanasio and others 2014; in Mexico, see Fernald and others 2016).The literature review proceeded as follows. We began by examining the conclusions in the 2011 Lancet series on early child development in LMICs (Engle and others 2011; Walker and others 2011) and in five systematic reviews addressing CCTs published since 2011 (Bassani and others 2013; Fernald, Gertler, and Hidrobo 2012; Glassman, Duran, and Koblinsky 2013; Manley, Gitter, and Slavchevska 2013; Ruel, Alderman, and Maternal and Child Nutrition Study Group 2013). We then conducted a literature search to find papers that had been published since those systematic reviews. The search used Google Scholar, JSTOR, and PubMed for peer-reviewed articles and websites of the International Food Policy Research Institute, United Nations Children’s Fund, and the World Bank for gray papers. The search was restricted to studies that used experimental or quasi-experimental techniques such as randomization, regression discontinuity, propensity score matching, or difference-in-differences.We found evidence from studies examining the effects of CTs on birth weight (3 studies); infant mortality (6 studies); height-for-age (or stunting) (23 studies); weight-for-age (or underweight) (12 studies); weight-for-height (or wasting) (10 studies); hemoglobin (or anemia) (10 studies); morbidity (16 studies); cognitive, language, and behavioral development (11 studies); and sexual and reproductive health (9 studies) (table 23.1).