Non-contributory social protection for adolescents in low- and middle-income countries: a review of government programmes and impacts

ABSTRACT

Poverty in early life can have lasting effects on health and human capital; social protection can counter these effects to promote the development of capabilities across the life course. This paper examines how social protection can promote adolescent well-being and facilitate safe and productive transitions to adulthood in lower and middle-income countries. Focusing on governmental non-contributory programmes the paper investigates (i) whether and how current non-contributory social protection programmes are adolescent-sensitive and (ii) what the impact of non-contributory social protection programmes on adolescents is. To examine these questions, we conducted an extensive review of the literature on existing non-contributory social protection programmes and related impact evaluations.

KEYWORDS:

• Social protection
• adolescence
• child and youth poverty
• transitions to adulthood
• low- and middle- income countries
• review

JEL CLASSIFICATION:

• I3 Welfare
• Well-Being
• and Poverty I38 Government Policy
• Provision and Effects of Welfare Programs J13 Children
• Youth J18 Public Policy P46 Health
• Education and Training
• Welfare
• Income
• Wealth
• and Poverty

Disclosure statement

No potential conflict of interest was reported by the author(s).

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/13600818.2024.2376613.

Notes

1 Definition developed by SPIAC-B, the Social Protection Interagency Committee – Board.

2 The COVID-19 pandemic underscored the need for adequate social protection coverage and exposed existing gaps, some of which were temporarily addressed during the pandemic (Gentilini et al., 2022).

3 This definition is subject to debate: research has demonstrated that the brain continues to develop beyond this period and reaches maturity later than the end of adolescence as typically defined (Blakemore & Choudhury, 2006).

4 For further details see Cirillo et al. (2021).

5 As an exception we included also some high-income country, from the mapped regions, with existing social protection programmes in place, namely Chile, Kuwait, Oman, Palau, Panama, Qatar, Saudi Arabia, United Arab Emirates, Uruguay.

6 The rationale for this choice was that these programmes are often targeted to specific categories of workers (e.g. farmers) or demographic age groups (e.g. elderly, newborn, working age adults), excluding by design adolescents as direct beneficiaries.

7 For example, conditional cash transfers (CCT) require beneficiaries to accomplish with specific requirements, often related to health check-up or to school enrollment, attendance or attainments. By design, CCTs may have positive effects on these outcomes because they are programmes requirements. Conversely, unconditional cash transfers do not require any co-responsibility to the beneficiaries, therefore the impact on certain indicators, ceteris paribus, depend on beneficiaries’ behaviours.

8 The inventories we mapped report all the existing non-contributory SP programmes for which information is available and reliable. See the original sources for more information about the methods used to map programmes.

9 The TP is a collaborative network between the United Nations Children’s Fund (UNICEF), the Food and Agriculture Organization of the UN (FAO), University of North Carolina, national governments, and local research partners.

10 Each programme may involve only one component (e.g. an unconditional cash transfers) or more components depending on the target group (e.g. an unconditional cash transfers, a conditional cash transfer and a public work intervention).

11 Bastagli et al. (2016) reviewed a large number of studies and existing reviews of evidence. Hence, the papers mentioned in Bastagli et al. (2016) pertain also to other existing reviews.

12 Our search of the existing reviews and TP documents was completed by the end of January 2019. The process to select reviews was as follows. First, we started from the Bastagli et al. (2016) review. Second, for each topic (e.g. education, health, etc.) we looked for the most updated reviews of the evidence, particularly for topics not covered by Bastagli et al. (2016). Finally, we added all the TP evaluations, which include quasi-experimental and experimental impact evaluations of government cash transfer programmes in Africa and the Middle East. At the time of our search, TP evaluations had been conducted in 10 countries in Africa and one in the Middle East (Lebanon). For each of the mapped reviews, we checked the criteria used to select impact evaluation papers.

13 The methodological approach we used to map the impact of programmes has some limitations. In fact, additional impact evaluations looking at heterogeneous effects on adolescence might be found if the search of studies were enlarged.

14 The geographical coverage of the mapped impact evaluations is as follows: 46% on Sub-Saharan Africa; 31% on Latin America and the Caribbean; 11% on East Asia and the Pacific; 8% South Asia; 4% on Middle East and North Africa.

15 For programmes which included individuals above 19 for age-related eligibility, we right censored this data at 19 for calculation purposes in Figure 2. Programmes targeted generically at households with children not including clear information about the maximum (child) age of eligibility are not included in Figure 2.

16 Argentina raised the maximum age eligible for Familias por la Inclusión Social from 18 to 19 years. Honduras increased the age threshold from 12 to 14 years old in PRAF/IDB Tranche III. Nicaragua moved the age threshold from 13 to 15 years in the Atencion a Crisis Pilot Programme (ECLAC, n.d.). In Peru the Juntos programme targeted only children and younger adolescents before 2014, while today the maximum age for eligibility is set to 19 years (Alcázar & Espinoza, 2014). Finally, for the Child Support Grant in South Africa, the maximum eligible age was increased multiple times until from 1998 to 2012, when it was extended to cover children until their eighteenth birthday (Heinrich & Brill, 2015).

17 In our descriptive statistics, programmes targeted to specific age groups and those targeted to students do not overlap, meaning that if the eligibility criteria set a clear age threshold we counted them in the programme components focusing on age (Figure 3 – Panel A), while if the criterium is only the education level we count them apart from the first group (Figure 3 – Panel B). The number of programme components targeting adolescents by school level or by age are 142 and 198, respectively.

18 The source of information for each geographic region are the inventories mentioned in Section 2.

19 This is the case of two programmes not mapped by our study: Mozambique’s Child Grant Programme (rolled out in 2019) and Ghana’s LEAP 1000 (a pilot initiative which began in 2015 and was later included as a category of the national LEAP programme). These programmes do not necessarily set out to be adolescent-sensitive, but by targeting based on reproductive status without age minimums (e.g. legal majority age) they potentially respond to life cycle and gender-related vulnerabilities of adolescent girls.

20 For inclusion criteria, see the methodology section. Only papers specifically studying adolescents (or adolescents combined with other age groups) were included. Studies assessing the impact solely on children (below 10 years old) or on adults (above 19 years old) were excluded.

21 For the purpose of this review, we considered as significant all indicators with a minimum 10% significance level.