Abstract
Using a randomized controlled trial design, we examine the effects of savings incentives (match rate 1:1 versus 1:2) with mentorship and financial trainings on child poverty among 1383 orphaned children (mean age 12.7 years at baseline) in rural Uganda. Given the difficulty to capture child poverty using monetary measures, we use a multidimensional class of poverty that captures four dimensions: health, assets, housing, and behavioral risks. Results show that children in treatment groups experienced reductions in poverty incidence by 10 percentage points (or deprivation score by 8 percent) relative to control group counterparts at four years post-baseline, and a higher savings incentive led to stronger effects. Further, children in treatment groups were more likely to escape the poverty trap. Finally, we assess the robustness of these results to various weighting structures. This study offers a unique evidence on effectiveness of a multifaceted intervention targeting children in alleviating poverty.
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Notes
A child is defined as an individual aged 18 and below at baseline. All participants in the last two grades of primary school were under the age of 18 at baseline.
Detailed power analysis of this study can be found in Wang et al. (2018). Overall, results from a power analysis indicated that this study could detect small to small-medium effects.
The account is held by the caregiver and the child because, according to the contractual laws in Uganda, a child cannot individually hold a binding contract. Nevertheless, no withdrawals can be made without the child’s approval and signature.
It is important to note that with funding from the National Institute of Mental Health (NIMH), the Bridges to the Future study has been adapted under the Suubi4Her study (1 R01 MH113486-01), specifically focused on younger girls (ages 14–17)—regardless of whether they are orphaned or not orphaned. Preliminary findings from the adapted Suubi4Her intervention indicate similar positive findings in improving educational, behavioral, and mental health outcomes as shown in the Bridges to the Future study (Ssewamala et al., 2018).
We further test whether the attrition status is associated with observable characteristics. We run a regression model with attrition status at Year 4 as the outcome and we included the following predictors: treatment status (Control (ref.), Bridges, and Bridges PLUS), observable characteristics (double orphan status, primary caregiver, age, female, years living in the households, household size, number of children, employment status of the caregiver), and the interactions between each treatment status and each observable characteristic. Among all 20 independent variables included in the analysis, coefficients of 19 variables are not statistically significant, except for the interaction between female and Bridges PLUS (β = 0.069, SE = 0.027, p-value = 0.011) is significant, indicating that female participants in the Bridges PLUS group were more likely to drop out from the study.
This study did collect information on self-rated health. Due to the concern that children may change their reference groups over time (e.g., children who benefited from the intervention more may have better educational attainment; hence they may have a different reference group when they respond to the self-rated health question), we opted not to include this measure.
This study did collect information on social participation at school. However, in longitudinal analysis, some children were no longer in school during later follow-ups, making this measure on social participation non-applicable to many children in later time points.
In Appendix Fig. 3, we present the multidimensional poverty index (MPI) patterns using varying cutoffs. In Appendix Table 10, we present our main findings using alternative cutoffs: 0/4 and 2/4 of all indicators. When the poverty cutoff is 0/4 (a child is not deprived in any indicator), the average proportion of MPI poor children is 99.8% at baseline and 97.4% at Year 4. When the poverty cutoff is 2/4 (a child is deprived in a total of two dimensions or six indicators), the average proportion of MPI poor children is 3.8% at baseline and 2.1% at Year 4. This suggests that 1/4 is a better cutoff that capture variations in multidimensional poverty transitions.
Average of weighted deprivation scores among the poor.
The adjusted headcount ratio (M0) is calculated as H x A. M0 is “the sum of the weighted deprivations that the poor (and only the poor) experience, divided by the total population” (Alkire & Santos, 2014).
We also experimented with the three-level multilevel model used in Wang et al.’s (2018) paper. The results are presented in Appendix Table 9 and are similar to our main findings in Table 6. We also experimented with ANCOVA analysis accounting for baseline differences in outcomes, and the results are more robust compared to main findings in Table 6 (see Appendix Table 11).
We also conducted sensitivity analyses controlling for additional characteristics, and the results are presented in Appendix Table 8. Model 1 presents the results from the same model as in the model presented in Table 6 while controlling for baseline characteristic differences across the three groups: double-orphan status and relationship to the primary caregiver. Model 2 presents the results from the same model as Model 1 while additionally controlling for characteristics that differ by attrition status: age, gender, years living in the household, and primary caregiver. Model 3 presents results from the same model as in Model 2 while additionally controlling for other characteristics, such as household size, number of children, and caregiver employment status. The results are qualitatively the same as the main results presented in Table 6.
We further tested the association between school characteristics and the three study groups. We found that the schools do not differ significantly by district, nearest town, distance to the main road, school size, and educational performance (Wang et al., 2018).
Although the differences in coefficients between the Bridges and Bridges PLUS groups were not statistically different, when we restricted the analyses to respondents aged 18 or below, the difference between Bridges and Bridges PLUS children was statistically significant.
We also experimented with allowing a wider range of weights by only ruling out any combination that gave a single dimension less than 10% or more than 90% weight; which left us with 455 different weighting structures. We present the results from this analysis in Appendix Fig. 4
Although the poverty incidence and deprivation score between Bridges and Bridges PLUS were not statistically significantly different from each other, when we restrict the sample to children aged 18 and below, the intervention effect was statistically significantly stronger for Bridges PLUS children than Bridges children.
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Acknowledgements
The Bridges to the Future study was supported by the Eunice Kennedy Shriver National Institute of Child Health & Human Development (NICHD) under Award Number 1R01HD070727-01, PI: Fred M. Ssewamala. The study received Institutional Review Board approvals from Columbia University (IRB # AAAI1950) and the Uganda National Council for Science and Technology (Ref. SS2586). The authors acknowledge the support of the 48 public schools and local institutions, including Reach the Youth-Uganda and the Diocese of Masaka in Western Uganda that engaged in this study. We are also thankful to the children and their caregivers who participated in the study. Malaeb acknowledges the support of the Economic and Social Research Council (ESRC)’s Grant No. ES/N01457X/1 on evaluating integrated policies to reduce multidimensional poverty.
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Appendix
Appendix
See Tables
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See Figs.
Changes in M0 for the different study groups
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Robustness Check: Effect Sizes Across Various Random Weighting Structure (10–90). Note: The X-axis for the MPI poor outcome: differences in MPI poverty incidence from baseline to a given time point (range: − 1 to 1). The X-axis for the C vector outcome: differences in deprivation scores from baseline to a given time point (range: -1 to 1). Bars represent the 95% confidence interval
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Wang, J.SH., Malaeb, B., Ssewamala, F.M. et al. A Multifaceted Intervention with Savings Incentives to Reduce Multidimensional Child Poverty: Evidence from the Bridges Study (2012–2018) in Rural Uganda. Soc Indic Res 158, 947–990 (2021). https://doi.org/10.1007/s11205-021-02712-9
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DOI: https://doi.org/10.1007/s11205-021-02712-9