2019
DOI: 10.1093/jae/ejy024
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Teen Fertility and Female Employment Outcomes: Evidence from Madagascar

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Cited by 14 publications
(11 citation statements)
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References 36 publications
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“…The negative association between female enrolment in education and early female fertility is consistent with micro-level studies from a variety of SSA countries that present causal evidence regarding the negative impact of early female education on early female fertility (Duflo et al 2015;Keats 2018;Osili and Long 2008;Ozier 2018). Herrera et al (2019) provide complementary evidence that first births occurring during adolescence increase the probability of employment, which is partially mediated through school dropout, with the quality of employment being low.…”
Section: Female Labour Supply and Fertilitysupporting
confidence: 82%
“…The negative association between female enrolment in education and early female fertility is consistent with micro-level studies from a variety of SSA countries that present causal evidence regarding the negative impact of early female education on early female fertility (Duflo et al 2015;Keats 2018;Osili and Long 2008;Ozier 2018). Herrera et al (2019) provide complementary evidence that first births occurring during adolescence increase the probability of employment, which is partially mediated through school dropout, with the quality of employment being low.…”
Section: Female Labour Supply and Fertilitysupporting
confidence: 82%
“…Women who have children at a young age face additional time constraint, impairing their human capital formation, which further reduces their competitiveness in the labor market. Herrera et al (2016) find that women whose first birth occurred during adolescence largely find work in low-quality informal jobs. Figure 8 shows that in sub-Saharan African countries, unattended family planning needs are associated with more women working in the informal sector relative to men.…”
Section: B Social Norms and Lack Of Family Planning Curtail Women's Competitivenessmentioning
confidence: 85%
“…At this point, we were able to relate the overall performance level of Italian MOCs with their ownership structure, using the multinomial ordinal probabilistic regression (multinomial ordered probit model; Bhojraj & Sengupta, 2003; García‐Goñi, Maroto, & Rubalcaba, 2007; Herrera, Sahn, & Villa, 2019).…”
Section: Dataset and Methodologymentioning
confidence: 99%