Parental Morbidity, Child Work, and Health Insurance in Rwanda

Abstract

Measuring direct and indirect effects of extending health insurance coverage in developing countries is a key issue for health system development and for attaining universal health coverage. This paper investigates the role played by health insurance in the relationship between parental morbidity and child work decisions. We use a propensity score matching technique combined with hurdle models, using data from Rwanda. The results show that parental health shocks have a substantial influence on child work when households do not have health insurance. Depending on the gender of the sick parent, there is a substitution effect not only between the parent and the child on the labor market, but also between the time the child spends on different work activities. Altogether, results reveal that health insurance protects children against child work in the presence of parental health shocks.

The effects of teenage childbearing on education, physical health, and mental distress: evidence from Mexico

“…Moreover, recent studies use propensity score matching methods to explore various relationships in developing countries. For example, Woode et al (2017) employ a propensity score matching method to explore the role of health insurance in the relationship between parental health shocks and child work in Rwanda.…”

Health Insurance in Sub-Saharan Africa: A Scoping Review of the Methods Used to Evaluate its Impact

“…In 19 out 66 studies (28.8%) [14,16,18,23,24,28,34,40,42,44,46,47,53,57,60,66,68,71,72], there was no mention of the study methodological limitations. Self-selection into voluntary insurance and the subsequent sample bias were discussed in 20 studies [13, 15, 17, 19, 22, 25, 26, 41, 50-52, 58, 62, 63, 67, 69, 70, 73, 75, 77], openly acknowledging the related identification problems.…”

“…Most studies included were conducted in Ghana (n = 32; 48.5%) , followed by Burkina Faso (n = 8; 12.1%) [42][43][44][45][46][47][48][49]; Nigeria [50][51][52][53][54][55]; Rwanda [56][57][58][59][60][61] (n = 6; 9.1%); Kenya (n = 4; 6.1%) [62][63][64][65]; and Tanzania (n = 2; 3%) [66,67]. Ethiopia [68], South Africa [69], Mauritania [70], Mali [71] and Zambia [72] contributed one study each (Fig.…”

“…All six studies (9% of the total) from Rwanda concerned the "Mutuelles" Health Organizations [56][57][58][59][60][61], which are community-based health insurance schemes first piloted in 1999 and scaled up to the national level starting in 2006. Over 100 MHO schemes were created between 2000 and 2003.…”

“…Among the three quasi-experimental studies relying on repeated cross-sectional data (5% of the total), one study (33%) relied on a difference-in-differences approach [16]; one on an instrumental variable approach [17]; and one used both propensity score matching and instrumental variable [56]. Finally, among the 16 quasi-experimental studies relying on cross-sectional data (24% of the total), 12 (75%) used propensity score matching [18,19,21,22,25,47,53,57,58,62,69,73], four (25%) instrumental variables [20,23,24,46] and none used difference-in-difference. Table 1 presents a summary of the designs and analytical approaches used in relation to the study outcomes.…”