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In other words, the same intervention with the same standard deviation effect will generate a bigger percentage point shift in an outcome in a population that has a greater initial disadvantage in that outcome. 60 Adolescents in a changing world. The case for urgent investment If the data are normally distributed, a one standard deviation improvement will move the median student up to the 16th percentile from being the 50th best student in a class of 100.
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For a binary outcome like dropout, a one standard deviation improvement will shift an initial 50% probability of dropping out of school to a 16% chance. Typically, the effect of an intervention is only a small fraction of a standard deviation. For example, if an intervention has a standard deviation improvement in dropout rates of 0.38, this means that the mean of the distribution is shifted 0.38 standard deviations.
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The effectiveness of each intervention refers to the reduction in learning gaps as well as dropout rates. One intervention may affect both dropout and learning gaps. The impact of each intervention is the combined effect of the percentage of the population that is covered and its effect on those people who receive the intervention. Table 6.1 includes the costs of each intervention as a percentage of base unit costs.
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Base unit costs are the estimated costs of education per student in each country prior to the interventions, modelled from World Bank and UIS data, which includes the number of teachers, salaries, materials and ongoing support and school construction. The cost of interventions as the percentage of base unit costs provides a standardized measure of each intervention.
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Table 6.1 List of modelled education interventions, 64 countries Intervention Dropout Learning Cost (% of education base unit costs) % SD % SD Building new schools in underserved areas 17.2% 58.3% 13.9% School meals/nutrition 9.5% 3.2% 35.8% Merit-based scholarships 10.7% 0.223 12.5% Female-friendly schools (WASH) 0.112 5% Deworming and/or malaria 5% 0.200 1% Remedial teaching/teach at the right level 38.3% 0.178 5.9% ICT 0.100 0.420 11.8% Improved pedagogy 25% 0.250 10% Combined CCT and teacher incentives 10.3% 0.263 10% SEL 5% 0.260 7.2% Notes: % refers to the percentage change in the target variable as a result of the interventions; SD means the number of standard deviations by which the intervention shifts the target variable.
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6.3 Results – education outcomes The interventions are forecast to increase female school completions by approximately 215 million and male school completions by 240 million by 2050, excluding China (see Table 6.2). This represents an increase in school completions of 43.3% for females and 45.7% for males. The interventions also lead to an increase in average years of schooling, even where some students do not complete secondary school.
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The average years of schooling increase by 12.8% for females and 14.4% for males. While China is included in the overall analysis and in the subsequent tables, it is excluded from Table 6.2 because it already has high rates of secondary school completions. 61 6.
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Education, skills and employment Table 6.2 Educational outcomes, 64 countries (excluding China) Aggregated countries Base case school completions Intervention case school completion Increased school completions Increased school completion % Increased average years of schooling % Costs US$ million Male 525 551 078 765 869 760 240 318 682 45.7% 14.4% Female 495 472 389 709 771 223 214 298 834 43.3% 12.8% Total 1 021 023 466 1 475 640 983 454 617 516 44.5% 13.6% $3 234 877 The results of the education model are used in the employment model in order to calculate the economic benefits associated with improved education outcomes.
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The model analysis of the nine interventions selected for this study shows that increasing these interventions through to 2035 would increase secondary school completion by approximately 45% for all countries studied, excluding China. The transformative effects of more and better education in the process of economic and social development through the implementation of the interventions are discussed in Chapters 1, 4 and 5.
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6.4 The benefits model – methodology The benefits model uses the results derived from the education model described above for the impact of the education and training initiatives on key component outcomes or channels of macroeconomic effects, individual productivity and mental health and well-being. The benefits model calculates changes relative to a base case resulting from the application of the set of educational interventions across countries.
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The starting point for the benefits model is the base case GDP path and the investment over time in education and training initiatives. The three channels through which these investments and the improved education and training outcomes give rise will provide benefits to affected populations. First, substantial new investment in education and training will have macroeconomic effects.
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These are the multiplier effects of the increased investment expenditure and enhanced ability to innovate locally and by making use of technologies and practices in best-practice countries. The impact of these factors on GDP will be reduced by the high leakage of expenditure into net imports, which is likely to continue for some time. The second component is the impact of better education and training on the individual productivity of the cohorts who receive that education and training.
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There are several aspects of this impact: ƒ an increase in productivity for each completed year of schooling; ƒ increased productivity when at work resulting from better quality learning while in school; ƒ increased productivity and employment arising from upgrading an educated workforce from informal to formal work; and ƒ the productivity effects of improved job skills, such as those arising from vocational training and the development of IT/Internet skills and interpersonal skills.
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The third component is the effect of better education and training on the health, including mental health, and well-being of the cohorts and their children. These include: ƒ the benefits (in addition to improved school performance) of these programmes on the mental health of adolescents; ƒ lower child marriage and cohort fertility arising from better education and the demographic dividends arising from these changes; and ƒ reduced infant mortality arising from better maternal education.
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62 Adolescents in a changing world. The case for urgent investment 6.4.1 The investment multiplier Since the writings of John Maynard Keynes (1936), the investment multiplier has been a staple of macroeconomic analysis. The basic idea is that expenditure by a government, for example, will be in the hands of those who do the work or sell the goods. The recipients of the income will spend part of the income and save the rest, leading to new spending, saving and so on.
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The result of this process is that the increase in GDP is likely to be greater than the initial investment. If there are no other factors involved, the multiplier is equal to 1/ (1- Marginal Propensity to Consume) . If the marginal propensity to consume was 60%, the multiplier would be 2.5. But there are always other factors involved. For example, some income will be spent on imports or other leakages.
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If the economy is fully employed, either the initial investment or subsequent spending rounds will substitute for, rather than be additional to, existing activity. Therefore, evidence from actual economies needs to be considered. Economists at the Global Infrastructure Hub (the G20’s infrastructure entity) (GI Hub, 2020) have recently reported the results of their analysis of more than 3000 estimates of the fiscal multiplier from more than 200 academic studies over the last 25 years.
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This meta-analysis, conducted to support the G20’s Action Plan in Response to the COVID-19 Pandemic, found that public investment has an average fiscal multiplier of approximately 0.8 within one year and around 1.5 within two to five years. These multipliers are higher than those found for public spending as a whole across both timeframes.
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They found that this multiplier effect tends to be larger, at around 1.6, during the contractionary phase of the economic cycle, suggesting that public investment is generally less likely to crowd out private economic activity in times of recession. For this study, we used an investment multiplier of 1.2 with equal effects over three years and an import leakage of 20%, falling over time to 10%.
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6.4.2 Education, innovation and human capital As noted earlier, the evidence is clear that better education has many benefits - from better health and increased empowerment to an increased likelihood of securing, and being productive in, a high-quality job.
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In this analysis, we concentrate on two aspects of these benefits: the general impact of better educational outcomes and improved human capital on innovation throughout the economy and the impact of better education on the level and quality of employment obtained by individuals, and hence on their earnings and productivity. An extensive amount of research links educational outcomes, both years of schooling and quality outcomes, to GDP growth at an aggregate level.
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Much of this literature has involved studying the impact of education and human capital more generally on economic growth, partly in the context of seeking to explain the existence of distinct differences between countries in GDP per capita levels and, hence, in living standards. Two main methods have been developed. One stream emerged from the demonstration by Mankiw et al.
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(1992) that introducing a human capital variable based on educational attainment into the production function much improved the predictive power of the Solow/Swan growth model (Solow, 1956). Although some single factor analyses have continued, this literature quickly expanded into an analysis of the role of human capital as one of the many factors that shape cross-country differences in GDP per capita and growth rates.
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Much of this analysis has made use of successive generations of the Barro and Lee cross-country database (2013) and has focused on years of schooling as a measure of educational attainment and, hence, of human capital. Recently, there has been increasing emphasis on the growth effects of improving the quality of educational outcomes.
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The other standard approach has been to start from the Mincer equation (1974) in which log earnings are a function of schooling and experience augmented by other variables that might affect this relationship. The result of estimating this equation, which is the percentage increase in earnings (or productivity) for an additional year of schooling, is often referred to as the return to education.
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Montenegro and Patrinos (2012, 2014) have estimated a return to education for many countries using private sector earnings data. 63 6. Education, skills and employment A variant of these approaches, developed by Barro and Sala-i-Martin (2004) and employed extensively by Hanushek (2013), is to undertake cross-sectional regressions across many countries to estimate the returns to education in terms of enhanced GDP.
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These analyses typically use five-year averages of human capital (education) and GDP growth over the long-term to estimate the impact of education on growth. Given this methodology, this analysis does not produce a result for any specific country.
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Although this macroeconomic literature is vast and there are many voices dissenting on various aspects, the central conclusion is that there are very high returns, in terms of higher GDP or higher GDP growth, to improvements in both educational outcomes measured in years of schooling and to educational quality measured by test scores.
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It is also widely agreed that the impact of education is in addition to that of other factors that contribute to higher growth, such as economic and social institutions and convergence in technologies, and that the role of education can be seen as, at least in part, a causal one in generating growth as a response to improved educational outcomes.
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Although these conclusions can be, and have been, criticized in terms of both data and methodology, they undoubtedly point to a strong, long-term link between education and growth. They provide a solid context within which our more disaggregated model was developed.
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6.4.3 The productivity effects of improved human capital In our earlier work (e.g., Sheehan and Shi, 2019), we have stressed the need to be more specific about the mechanisms underlying these aggregate effects and to take account of individual country variation. In doing so, the benefits model is focused on two different types of human capital effect, emerging from the discussion above.
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The first is a generalized effect of higher human capital on growth, considered further in this section, and secondly, the impact of better educational outcomes on individual and cohort productivity. At the economy-wide level, higher human capital would facilitate greater innovation and technology adoption throughout the economy. Higher human capital increases a country’s ability to innovate, both in terms of making use of technologies new to the country and adapting such technologies to meet local needs.
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While this effect is well understood, the precise magnitude of the effect in different countries and circumstances is hard to pinpoint. Given this uncertainty and the complexity of the situation in individual countries, we assume for the current model an elasticity of GDP with respect to secondary school completions of 0.1 with a suitable lag (see Table 6.3). This means that every 10% rise in secondary completions leads, in due course, to a 1% growth in GDP.
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This is a conservative assumption and is well below the elasticities implied by the studies noted above. In the employment model, increased years of schooling and of better quality improve lifetime productivity for the relevant cohort of school leavers, and completing secondary school improves an individual’s chance of obtaining a formal job as opposed to working in the informal sector.
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Post-school training initiatives in trade skills, vocational training and non-formal training in innovation and entrepreneurship increase the individual’s productivity when at work. The increased productivity of each cohort is traced through their working lives, tracking each cohort of school leavers from age 20 to 24 years, with the effect building up as successive cohorts of school leavers with enhanced productivity enter the workforce.
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We measured the impact of these interventions relative to an unchanged policy base case, which is relative to the GDP path that would be generated by these cohorts without the enhanced educational and training outcomes.
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Four key relationships drive the increased productivity of young people as a result of these initiatives: ƒ the increased productivity over the individual’s working life arising from an additional year of schooling; ƒ higher productivity over the working life resulting from higher-quality learning in better schools; ƒ better access to formal employment as a result of completing secondary schooling; and ƒ higher productivity arising from trade, vocational or innovation training.
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Table 6.3 provides a summary of the key parameter settings used in the benefits model for this report. For a further discussion of these values, see Sheehan and Shi (2019). 64 Adolescents in a changing world.
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The case for urgent investment Table 6.3 Parameter settings used in the education benefits model, 64 countries, 2024–2050 Parameter Preferred case Macroeconomic Base case GDP growth rate 4% Investment multiplier 1.2 (over 3 years) Innovation effect – elasticity of GDP with respect to completions 0.1 (lagged 5 years) Import leakage 20% falling to 10% Education and training Return to a year of schooling Country specific Elasticity of productivity with school quality 0.125 (lagged 8 years) Elasticity of employment type with respect to completions +0.307, -0.071, -0.236 (Female) 0.197, -0.171, -0.026 (Male) Productivity increase (relative to average base case Years 9–12) > Upshift > Training in trades (e.g., carpentry, electrical, etc.)
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10% 20% Participation rates > Early school leavers > Persons aged 20–24 0.2 0.6 6.5 Results 6.5.1 Impact of interventions on educational outcomes Table 6.4 summarizes the main outcomes from the education and benefits models arising from the interventions extended out to 2050. We have separated them into three income groups, to show how the results vary across these income groups.
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Table 6.4 Impact of the interventions on selected educational and economic outcomes across 64 countries, by 2050 Low-income Lower middle-income Upper middle-income Total Education Increase in average grade attained (grades) Girls 1.5 1.1 0.8 1.1 Boys 1.6 1.2 0.8 1.3 Share of 20–24-year-olds who have completed secondary school (% increase) Girls 23.4 22.7 22.4 23.6 Boys 24.6 25.2 18.4 24.9 Change in activity of 20–24-year-olds in 2035 (million persons) Formal employment Girls 413 524 109 1046 Boys 181 82 50 313 65 6.
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Education, skills and employment Low-income Lower middle-income Upper middle-income Total Productivity per employee of 20–24-year-olds (change by 2035, %) Girls Individual earnings effect 21.6 9.6 8.2 13.1 School quality effect 38.8 16.6 9.8 24.3 Employment level effect 1.6 3.0 1.7 2.1 Employment type effect 0.78 1.7 1.1 1.3 Skills training effect 4.7 6.0 6.6 5.7 Total 66.4 37.0 27.4 47.2 Boys Individual earnings effect 17.6 9.9 7.1 11.8 School quality effect 37.8 16.6 7.8 24.2 Employment level effect 2.0 1.5 1.2 1.8 Employment type effect 15.5 10.8 8.0 12.7 Skills training effect 4.2 5.6 6.6 5.3 Total 77.1 44.4 30.8 55.8 In terms of reducing dropout rates and improving retention, the interventions lead to an increase in years of schooling completed across the whole sample of 1.1 years for girls and 1.3 years for boys.
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This increase is much higher than the overall average in LICs where years of schooling are low. A critical variable for the benefits model is the proportion of girls aged 20 to 24 years who complete secondary school. As shown in Table 6.4, the interventions lead to an increase of about 24% in this share with the change relatively common across regions. One linkage in the benefits model is that higher secondary completions allow adolescents aged 20 to 24 years to access better, formal jobs.
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Our estimate of the increase in formal jobs held by adolescents by 2050 is quite high, particularly for girls in LICs.
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In terms of individual cohort GDP, there are four channels by which that GDP is enhanced: ƒ the individual productivity effect of years of schooling using extensive, country-specific estimates of the returns to a year of school; ƒ the productivity value of better quality learning; ƒ the impact of secondary completions on the type and level of employment; and ƒ the impact of skills training on productivity. Table 6.4 shows the model estimates of each of these effects.
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The productivity of the 20–24-year cohort leaving school around 2050 is estimated to be 47.2% higher for girls and 55.8% higher for boys than the opening cohorts of the early 2020s. To generate the potential GDP implications of these effects, we tracked the contributions of each cohort out to 2050 as they age until their retirement at 60 years and compared these to the base case levels.
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These increases in productivity, together with the macroeconomic multiplier and the innovation effect, provide the total increase in GDP arising from the interventions. Table 6.4 (continued) 66 Adolescents in a changing world. The case for urgent investment 6.5.2 Returns to schooling and training Table 6.5 shows the costs of the interventions. These costs are expressed in billions of dollars as an NPV of annual flows discounted at 3% per annum.
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For the period 2024 to 2035 inclusive, total costs are US$ 2 311.5 billion, or an average of US$ 192.6 billion per annum over the 12 years. Table 6.5 Total additional cost of schooling and training initiatives, by region and country, 64 countries, 2024–35, $ billions Low-income Lower middle-income Upper middle-income Total Total cost 61.2 419.8 387.2 2 311.5 Average annual cost 5.1 35 32.3 192.6 Table 6.6 summarizes the BCRs for the same selection of countries.
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The BCRs shown here are the ratio of the NPV, at a 3% discount rate, of total incremental GDP generated by the education intervention programme to that of total costs to 2050. Costs out to 2050 include not only the intervention costs to 2035, shown in Table 6.5, but the costs from 2036 to 2050 that continue from the interventions in place during that period.
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Total incremental GDP is the total increase in GDP relative to the base, arising from the higher cohort productivity detailed in Table 6.4 and from the macroeconomic multiplier and innovation effects. We present BCRs on two bases in Table 6.6. One is the arithmetic mean of the individual BCRs for the group of countries considered. This is termed the unweighted BCR; each country, whatever its size, counts as one observation.
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The other is the ratio of total benefits across a given sample of countries divided by the sum of total costs across those countries. This is termed the weighted mean; the contribution of individual countries to the mean depends on their scale. These measures give different perspectives on the BCR results and preference depends on the purposes for which the BCRs are used.
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Table 6.6 BCRs of investment in interventions in education, 64 countries Low-income Lower middle-income Upper middle-income Total Unweighted Female 41.9 19.3 41.3 31.1 Male 37.3 19.0 35.9 28.4 Both 39.1 18.7 34.8 28.6 Weighted Female 34.0 12.7 14.9 14.8 Male 30.4 16.7 16.3 16.8 Both 31.9 14.9 15.7 15.9 Most of the BCRs reported in Table 6.6 are very high and, in most cases, well above 10.
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The unweighted BCR for all countries is 28.6 (31.1 for females and 28.4 for males) while the weighted BCR for all countries is lower at 15.9 (14.8 for females and 16.8 for males). For the three country groupings, the BCRs are very strong indeed. 67 7. Violence and injuries 7. Violence and injuries 7.1 Introduction In this chapter, we review the evaluation literature related to interventions that address violence and injuries.
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We acknowledge that there are a number of areas where there is a lack of sufficient evidence to develop investment cases based on cost-benefit analysis. However, for child marriage and road traffic accidents, strong economic cases can be built for investment in intervention programmes to reduce their prevalence.
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Violence and unintentional injuries, which includes all forms of inter-personal violence (IPV), injuries (particularly road traffic injuries) and self-harm, has an impact on a large section of the adolescent population (WHO 2023a). Suicide is a leading cause of death among 15-19-year-olds (WHO, 2021b). Child marriages, FGM, intimate partner violence, sex trafficking and sexual violence are all types of violence experienced by young women.
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Around 30% of children worldwide have experienced some type of bullying, including cyberbullying (UNESCO, 2019). Traffic accidents, gang violence, recruitment into war, terrorism and IPV have a larger impact on young men. Young people from the LGBTIQ+ community face stigma, discrimination, violence and criminalization. The impacts of any type of violence can be long-lasting and intergenerational whilst also incurring high economic costs.
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The results of our structured review of intervention evaluations to reduce violence and injuries in adolescents are shown in Table 7.1. This table provides a summary of the investment evaluations employing cost-benefit analysis. There are others such as programmes to prevent intimate partner violence and suicide where the investment case has not been successfully evaluated using cost-benefit analysis.
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This partly reflects an absence of intervention studies that measure their serious economic impacts, such as school non-attendance or long-term employment loss. 7.2 IPV Base case estimates by Hillis et al. (2016) indicate that globally over half of all children (one billion children aged two to 17 years) have experienced past-year violence. However, the figure is likely to be higher as much violence goes unreported (UNICEF, 2014).
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The 1989 UN Convention on the Rights of the Child recognizes freedom from violence as a fundamental human right of children.
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Overall, the costs of violence: ƒ in a range of countries, can be up to 5% of GDP (UNICEF, 2022b); ƒ for physical, psychological and sexual violence globally can be as high as 8% of GDP (Pereznieto et al., 2014); ƒ for violence in and around schools that negatively impacts education outcomes can result in an estimated loss of US$ 11 trillion in lost lifetime earnings (Wodon et al., 2021); ƒ for violence against women, is estimated at US$ 1.5 trillion or 2% of global GDP in 2016 (UN Women, 2016); and ƒ for child marriage, is estimated at US$ 5 trillion globally from 2014 to 2030 mainly due to increased fertility and population growth, reduced child health and nutrition, education and earnings (Wodon et al., 2017).
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Ending child marriage could contribute to welfare gains of over US$ 500 billion per year globally, solely from lower population growth (Wodon et al., 2017). 68 Adolescents in a changing world. The case for urgent investment Table 7.1 Summary, benefit-cost ratios for interventions to reduce violence and injuries in adolescents Author Location Interventions Benefits BCR Rasmussen, Maharaj et al.
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(2019) 31 countries Educational interventions, improving life skills, community mobilization and conditional economic incentives to reduce child marriage, improve retention in school, etc of girls Reduce child marriage, decrease school dropout rates, increase secondary school completions for girls, and address some of the broader social and cultural disadvantage 7.4 Rasmussen et al.
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(2021) India As above As above 16.8 all interventions 21.0 marriage only 13.1 education only UNFPA (2022) 70 countries Testing for least-cost most effective selection of interventions as above Practical elimination of child marriage by 2030 33.6 optimized intervention selection 11.7 all interventions This report 70 countries Education and community programmes to empower girls and reduce child marriage Reduce child marriage 25.6 UNFPA (2022) 31 countries with high rates of FGM Legal and policy frameworks and community-led engagement to eliminate FGM Reducing FGM, health care costs avoided, healthy years of life gained and associated economic and social benefit 10.1 Kuklinski et al.
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(2021) 24 communities in various states in the United States of America CTC – provides manuals, tools, training and technical assistance to activate communities Reducing adolescent substance use, delinquency, and related health and behaviour problems 12.9 WSIPP (2023) United States of America PATHS – curriculum promotes emotional and social competencies Reduces aggression and improves ability to resolve conflicts 24.4 Stelmach et al.
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(2022) 36 countries Hospital-based suicide prevention programme School-based suicide prevention programme Reduce suicide 62 (hospital) 3.5 (school) This report 77 countries Broad-based programme to reduce road traffic injuries > infrastructure > alcohol > speed > helmets Reducing fatalities and serious injuries 9.1 7.2.1 Causes of violence and proposed intervention strategies The ecological framework shown in Fig. 7.1 is based on evidence that no single factor can be attributed as the cause of violence.
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Instead, it is the outcome of the interaction among several factors, working at four levels: the individual, the relationship, the community and the societal. Personal history or biological factors contribute to the individual level and relationships include having violent friends or experiencing domestic violence.
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Unemployment, population density and related factors contribute at the community level while socioeconomic inequalities, the availability of weapons and social and cultural norms contribute to societal factors (WHO, n.d.). Several strategies have been proposed for ending violence against children. These include: ƒ INSPIRE, which takes into account the above risk factors and includes areas such as norms and values and education and skills (WHO, 2016b; Butchart and Hillis, 2016); 69 7.
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Violence and injuries ƒ LIVES, which is a handbook for front-line responders (WHO, 2014); and ƒ RESPECT (WHO, 2002), which is a framework for interventions (Kerr-Wilson et al., 2020), adopted, for instance, by Ferrari et al. (2022) in their study of IPV. Fig. 7.1 The ecological framework, examples of risk factors at each level Source: WHO (nd).
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WHO’s Departments of Gender, Rights and Equity – Diversity, Equity and Inclusion (GRE-DEI), Global HIV, Hepatitis and Sexually Transmitted Infections Programmes, and Sexual and Reproductive Health and Research are currently developing a guideline on the health of transgender and gender diverse people. The new guideline will provide evidence and implementation guidance on health sector interventions (WHO, 2023c). Kerr-Wilson et al.
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(2020, p3) provided categories of interventions: ƒ economic interventions such as economic transfer programmes, microfinance and economic empowerment; ƒ relationship and family-level interventions such as parenting programmes and couples intervention; ƒ community-level interventions such as approaches to change gender norms, social marketing and edutainment and digital technology; and ƒ school-based interventions such as preventing dating and sexual violence and preventing gendered peer violence.
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7.2.2 ROI – child marriage A recent systematic review by Malhotra and Elnakib (2021) has provided an assessment of 20 years of intervention evaluations to shed light on their effectiveness in reducing child marriage. The outcome of this work is to emphasize the importance of education interventions, such as CCT or in-kind transfers for schooling support, in enhancing girls’ own human capital and employment opportunities.
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Other interventions that have been successful have included conditional asset transfers for delayed marriage, LST (including gender rights), and, to a lesser extent, community mobilization. Interventions that have had little success include unconditional cash transfers. These have been directed largely at addressing poverty, a factor in child marriage.
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Societal Community Relationship Individual Poverty High crime levels High residential mobility High unemployment Local illicit drug trade Situational factors Victim of child maltreatment Psychological/personality disorder Alcohol/substance abuse History of violent behaviour Rapid social change Gender, social and economic inequalities Weak economic safety nets Poor rule of law Cultural norms that support violence Poor parenting practices Marital discord Violent parental conflict Low socioeconomic household status Friends that engage in violence 70 Adolescents in a changing world.
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The case for urgent investment Box 7.1 Estimating the economic and social benefits of reducing child marriage This section provides the results from our Child Marriage Benefits Cost (CMBC) model. It summarizes the analysis and assumptions used to estimate the BCR of investing in child marriage prevention in 70 countries. The economic benefits largely arise from increased schooling, leading to greater productivity and formal employment.
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Prevention interventions encourage greater access to education, especially programmes that reduce dropouts due to early marriage, as well as specific measures to delay marriage. It was assumed that reducing child marriage rates would result in an increase in average years of schooling and secondary school completion. Increasing the length of schooling leads, on average, to higher lifetime earnings; each additional year of education boosts income.
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Since the employment benefits of greater education are long-term, benefits were considered up to 2050. Two scenarios were compared: ƒ Baseline/business-as-usual scenario developed from the most recent estimates of child marriage based on cohabitation trend rates from household survey data. These were projected from 2024 to 2050. ƒ Full scale-up, with interventions increasing linearly from 2024 to 2035 and fully implemented to achieve an average 5% child marriage rate for 17-year-olds by 2035.
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These interventions are then continued out to 2050. Investments The cost of preventing child marriage entails funding two sets of intervention programmes. One set, which includes providing economic incentives, life skills and community mobilization programmes, is directed specifically at reducing child marriage. The other is a set of education programmes to keep girls in school, which include improved access to school, girl-friendly schools, better teaching and economic incentives to stay in school.
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Benefits The economic benefits of investing in child marriage prevention arise from: ƒ education: measures to reduce school dropouts, which were assumed to prevent child marriage and keep more girls in school effectively; and ƒ formal employment participation and productivity: increased formal employment and greater productivity, which arise from higher levels of education and secondary school completion.
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The positive effects on employment were modelled through more accessible education programmes that reduce dropouts that make early marriage much more likely, as well as specific interventions to delay marriage. Reduction of child marriage rates results in an increase in average years of schooling and secondary school completion. The CMBC model employs the same assumptions as the VEM about the relationship between increased education and productivity gains.
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Reduced child marriage rates Better education outcomes • Lower dropout rates • Increased years of schooling • Increased completions CM specific • Life skills • Conditional economic incentives • Community mobilisation Interventions to reduce child marriage Education-based • Rural schools • Transfer payments to girls • School infrastructure • Pedagogical changes/teacher training Reduced child marriage rates Better education outcomes • Lower dropout rates • Increased years of schooling • Increased completions Economic benefits • Increased productivity • Increased formal employment Cost-benefit analysis Cost interventions Higher GDP per capita Fig.
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B7.1 Modelling framework for child marriage estimations 71 7. Violence and injuries Modelling framework The modelling framework had several components. First, it used parameters from the literature to estimate the impact of interventions on the child marriage rate as well as intervention costs. Three interventions had direct impacts. Five had indirect impacts through educational interventions that improved school attendance through reduced dropout rates.
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The interdependence between child marriage and education is illustrated in Figure B7.1. First, increased enrolments tend to reduce child marriage. Second, reduced child marriage increases likely enrolments. Both effects are modelled. The second step for the direct interventions was to estimate the impact of reduced child marriage on educational outcomes, notably early dropouts, years of schooling and the completion of secondary schooling.
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This used an education model similar in type and structure to one in Wils et al. (2019). For girls who stay longer in school due to educational interventions, the model assumed that reduced dropout rates occurred in the same proportion among those who would otherwise have been married or unmarried out of school. Country-specific dropout rates were estimated. A third step was to use the results from the education model in an employment model based on Sheehan et al. (2017).
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(2017). This estimated the economic benefits of better educational outcomes for girls, namely country-specific higher productivity and access to formal employment, leading to higher GDP per labour force participant. Results The intervention package for the 70 countries would avert a total of 194 million marriages by 2050. One of the key drivers of success in reducing child marriages is for girls to stay enrolled to complete secondary school.
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As shown in Figure B7.2, by 2050 101 million additional girls would have completed secondary school. The total benefits for 70 countries generated by reducing child marriage and increasing time in education equates to total economic benefits of US$ 7.7 trillion at a cost of US$ 301 billion. Economic benefits and costs were discounted at 3% per year and are presented in 2022 dollars. The BCR was estimated to be 25.9.
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The BCR was estimated to be 25.9. Figure B7.3 illustrates the relative importance of education and community-based programmes. Education programmes are almost half of the benefits, with rural school supply and improved (girl-friendly) school infrastructure being the largest contributors. Community mobilization and life skills Fig. B7.2 Number of school completions before and after the interventions, 2035 and 2050, 70 selected countries Fig.
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B7.3 Total additional cost and economic benefits of child marriage prevention, US$ billion, 2024–2050, 70 selected countries $3,000,000 $2,500,000 $2,000,000 $1,500,000 $1,000,000 $500,000 $0 $3,500,000 Malaria prevention Life skills Conditional economic incentives Community mobilisation Cash transfers to poor students Pedagogical changes Improve school infrastructure Rural school supply Total additional cost Total economic benefits Economic benefits (by category) programmes are direct child marriage interventions that address community social and cultural attitudes, and help provide girls with a range of life skills to help delay marriage and transition to the workforce.
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Such an intervention programme would have a transformative effect not only on the lives of the girls immediately affected but also on the growth and development of the countries in which they live. The modelling estimates that the intervention programme will avert 194 million child marriages over the period to 2050. The estimated economic and social benefits of reducing child marriage represent about 3% of world GDP. Source: Modeling estimates, partly based on UNFPA (2022).
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2024 to 2030 700 600 500 400 300 200 100 0 1,000 900 800 2024 to 2040 2024 to 2050 Intervention Base case 400 million additional school completions Million 72 Adolescents in a changing world. The case for urgent investment The Girls Not Brides evidence review (2023) confirmed how effective CCT can be in keeping girls at school, particularly highlighting the Punjab Government’s CCT programme (Mathers, 2021).
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The review also pointed out the need to ensure that the supply side of girls’ education can be as important as the demand side; often girls are unable to stay at school due to poor availability and quality of schools, particularly at secondary levels (Malhotra and Elnakib, 2021). Cohen et al. (2023) argued that educational interventions are not enough to reduce child marriage but need to be bundled with interventions to change social norms.
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Favourable job markets can have a positive impact on keeping girls in school (Rose, 2021) as can vocational training in areas including tailoring, hairdressing, catering or carpentry with a view to improving adolescent girls’ financial independence (Freccero and Taylor, 2021). Greene et al. (2023) pointed to the need for country-specific studies while Feyissa et al. (2023) indicated that contextual information should be sought before implementing certain incentive-based programmes.
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Some strategies combine different interventions. Rasmussen, Maharaj et al. (2019) evaluated the benefits of interventions such as improving life skills, community mobilization and conditional economic incentives that target risk factors to reduce child marriage. They found an average BCR for 31 countries to be 7.4 at a 3% discount rate. Rasmussen et al.
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Rasmussen et al. (2021) estimated the BCRs of interventions, including CCT, to reduce child marriage in India and found the interventions resulted in an average BCR of 16.8. In a project for the UNFPA, VISES estimated that to end child marriage, the 70 countries and 13 states in India with the largest numbers of child marriages would need to spend an additional US$ 38 billion from 2022 to 2030 with continued investment thereafter to sustain programming and educate children (UNFPA, 2022).
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Overall, an additional US$ 151.7 billion would be needed from 2022 to 2050 to continue programming to achieve the practical elimination of child marriage beyond 2030 and to educate children. This aligned with an earlier modelling effort for the UNFPA (2020) using a similar methodology. This estimated the cost but not the benefits of practically ending child marriage for 68 countries over the period 2020 to 2030 to be an additional US$ 35 billion above current programmes.
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VISES found that the investment of US$ 151.7 billion would avert 230 million cases of child marriage and help 386 million girls to complete school (UNFPA, 2022). This would have an economic benefit of US$ 5.1 trillion between 2022 and 2050; every dollar spent would give a return of US$ 33.6.
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The modelling methodology employed for both UNFPA reports (2020, 2022) included an optimization approach that enabled the least cost and most effective set of interventions for ending child marriage to be selected for each country. Interventions included providing economic incentives, life skills and community mobilization programmes and education programmes to keep girls in school, including improved access to school, girl-friendly schools, better teaching and economic incentives to stay in school.
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VISES’ most recent modelling of child marriage interventions presented in this report is discussed in Box 7.1. This uses an updated modelling methodology compared with UNFPA (2022) in both optimization and non-optimization forms. The model uses updated baseline data for each country.
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It also uses a different approach to estimating current child marriage trends, which reduces the baseline projections, prior to interventions, of the decline in child marriage for those countries experiencing declining trends. The implementation period has also been extended from 2030 to 2035. It uses the same set of interventions as UNFPA (2022). These are consistent with the findings of Malhotra and Elnakib (2021) referred to above.
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However, the range of educational interventions is broader and more comprehensive than those included in their review. In particular, they include infrastructure investments aimed at improving physical access to schools for girls. 7.2.3 ROI – other outcomes of intervention evaluations FGM UNFPA (2022) estimated the impact of interventions on FGM cases averted by converting health care costs avoided, healthy years of life gained and associated economic and social benefits.
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For the 31 high incidence countries, it estimated they would need to spend an additional US$ 2.751 billion to end FGM. The BCR was estimated to be 10.1. 73 7. Violence and injuries Katz et al. (2021) estimated that reaching the high-coverage targets for 31 countries by 2030 would require an investment of US$ 3.3 billion. This would result in more than 24 million cases of FGM averted at an average cost of US$ 134 per case averted.
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