2. Removing Institutional Constraints
Following the World Development Report (2012), we discuss policies that can change the price of schooling under three categories: (i) direct costs; (ii) indirect costs; and (iii) opportunity costs.
Universal (Free) Primary Education initiatives launched across sub-Saharan Africa caused massive jumps in enrollment, allowing girls to close the enrollment gaps with boys at the primary level. For example, a large-scale tuition-waiver program for secondary schools in Gambia increased access to school and learning – equally for boys and girls (Blimpo, Gajigo, and Pugatch 2014). Elimination of fees in the public sector may cause a shuffle in the larger education sector by increasing access among the poor but also by shifting children from better-off families into private schools, which generally dominate public schools in performance even they’re of the low-cost variety (Bold et al. 2011; Lucas & Mbiti 2012; Bold, Kimenyi, and Sandefur 2013; and Adelman & Holland 2015). The evidence brings up the question of whether governments should eliminate fees in public schools or subsidize all accredited schools if the aim is to reduce the cost of quality schooling. Reducing the direct costs of schooling by subsidizing school supplies can also work: for example a low-cost program in Kenya that provided school uniforms to 6th graders decreased dropout and increased attainment among both boys and girls (Duflo, Dupas, and Kremer 201X. However, provision of textbooks, also in Kenya, did not lead to any improvements in schooling, other than among the strongest students at baseline (Glewwe, Moulin, and Kremer 2009).
Recent evidence also suggest that reducing the indirect costs of schooling can substantially reduce gender gaps in enrollment and test scores. Building so-called “girl-friendly schools” is a highly effective means of increasing access to schooling, whether it is by building schools within villages, especially in areas with minorities or marginalized groups (Burde & Linden 2013; Jacoby & Mansuri 2011; and Kazianga et al. 2013); building girls’ secondary schools (Andrabi, Das, and Khwaja 2013); building schools with girl-friendly amenities (Kazianga et al. 2013); or providing safe transportation for girls by, for example, providing bicycles (Muralidharan & Prakash, 2014).
Finally, it is also possible to increase access to school by reducing its opportunity cost for girls. A number of factors compete for girls’ time in developing countries, hence increasing their opportunity cost of schooling both in absolute terms and relative to boys. For example, collecting water is often the work of adolescent girls in many countries, and estimates suggest that reducing distance to the water source or piped-in supply of water would significantly reduce the enrollment gap between boys and girls in a diverse array of countries (World Bank 2011). Similarly, caring for younger siblings competes for school time: opening community daycare centers can increase school attendance among 10-15 year-olds (Martinez, Naudeau, and Pereira 2012). Child labor is the main alternative to school attendance in many countries, especially in Latin America and South Asia. Increased wages in the labor market increase child labor, with the effect generally being larger for boys than girls, but banning child labor may be counterproductive and actually decrease child wages and increase its prevalence (Bharadwaj, Lakdawala, and Li 2013). On the other hand, there is suggestive evidence that the expansion of garment industry was more effective in increasing girls’ schooling after the child labor ban in that industry in Bangladesh (Heath and Mobarak 2015). Finally, high demand for young brides in many parts of the world implies that young women who delay marriage can suffer costs in the marriage market – in the form of higher dowry prices or lower quality husbands (Field and Ambrus 2008). Preliminary results from a program in Bangladesh that is providing families of girls aged 15-17 with cooking oil (enough to compensate the increase in dowry from the delayed marriage) on the condition that they remain unmarried until age 18 suggest increases in highest grade completed, as well as higher math and literacy test scores (Glennerster et al. 2007; Bakhtiar 2014).
Next post (Monday, October 26): Part 3: Removing Household Constraints
Adelman, Melissa A., and Peter A. Holland, “Increasing Access by Waving Tuition,” World Bank Policy Research Working Paper No. 7175, 2015.
Andrabi, Tahir, Jishnu Das, and Asim Ijaz Khwaja, “Students Today, Teachers Tomorrow: Identifying Constraints on the Provision of Education,” Journal of Public Economics, 100(2013): 1-14.
Bakhtiar, Mehrab Bin, “Report on “Issues in Education and Health: Policy Insights from Evidence Based Research” – a seminar organized by the International Growth Centre,” available at: http://www.theigc.org/wp-content/uploads/2014/08/Report-Dhaka-IGC-seminar.pdf
Bharadwaj, Prashant, Leah Lakdawala, and Nicolas Li, “Perverse Consequences of Well-Intentioned Regulation: Evidence from India’s Child Labor Ban,” NBER Working Paper 19602, 2013.
Blimpo, Moussa P., Ousman Gajigo, and Todd Pugatch, “Financial Constraints and Girls Post-Primary Education: Evidence from a School Fee Elimination Program in Gambia,” IZA Discussion Paper No. 9129, 2015.
Bold, Tessa, Mwangi Kimenyi, Germano Mwabu, and Justin Sandefur, “Why Did Abolishing Fees not Increase Public School Enrollment in Kenya?” CGD Working Paper 271, 2011.
Bold, Tessa, Mwangi Kimenyi, and Justin Sandefur, “Public and Private Provision of Education in Kenya,” Journal of African Economies, 22(2013): ii39-ii56.
Burde, Dana, and Leigh L. Linden, "Bringing Education to Afghan Girls: A Randomized Controlled Trial of Village-Based Schools" American Economic Journal: Applied Economics, 5(2013): 27-40.
Duflo, Esther, Pascaline Dupas, and Michael Kremer, “Education, HIV, and Early Fertility: Experimental Evidence from Kenya,” American Economic Review, forthcoming.
Field, Erica, and Attila Ambrus, “Early Marriage, Age of Menarche, and Female Schooling Attainment in Bangladesh,” Journal of Political Economy, 116(2008): 881-930.
Glennerster, Rachel, Erica Field, and Shahana Nazneen Sayeed, “Age at Marriage, Women's Education, and Mother and Child Outcomes in Bangladesh,” 3ie Impact Evaluation Study: http://www.3ieimpact.org/evidence/impact-evaluations/details/5/
Glewwe, Paul, Michael Kremer, and Sylvie Moulin, "Many Children Left Behind? Textbooks and Test Scores in Kenya," American Economic Journal: Applied Economics, 1(2009): 112-35.
Heath, Rachel, and A. Mushfiq Mobarak, “Manufacturing Growth and the Lives of Bangladeshi Women,” Journal of Development Economics, 115(2015): 1-15.
Jacoby, Hanan G., and Ghazala Mansuri, “Crossing Boundaries : Gender, Caste and Schooling in Rural Pakistan,” World Bank Policy Research Working Paper No. 5710, 2011.
Kazianga, Harounan, Dan Levy, Leigh L. Linden, and Matt Sloan, "The Effects of "Girl-Friendly" Schools: Evidence from the BRIGHT School Construction Program in Burkina Faso," American Economic Journal: Applied Economics, 5(2013): 41-62.
Lucas, Adrienne M., and Isaac M. Mbiti, “Access, Sorting, and Achievement: The Short-Run Effects of Free Primary Education in Kenya,” American Economic Journal: Applied Economics, 4(2012): 226-253.
Martinez, Sebastian, Sophie Naudeau, and Vitor Pereira, “The Promise of Preschool in Africa: A Randomized Impact Evaluation of Early Childhood Development in Rural Mozambique,” 3ie Series Report, 2012: http://www.3ieimpact.org/evidence/impact-evaluations/details/106/.
Muralidharan, Karthik, and Nishith Prakash, “Cycling to School: Increasing Secondary School Enrolment for Girls in India, ” NBER Working Paper No. 19305, 2014.
World Bank, “World Development Report 2012: Gender Equality and Development,” Washington, DC, The World Bank, 2011.