The Entry of NGO Schools and Girls’ Educational Outcomes in Bangladesh

1. The Entry of NGO Schools and Girls’ Educational Outcomes in Bangladesh Pataporn Sukontamarn London School of Economics November 29, 2004

2. Outline • Research question and motivation • Theoretical framework • Background and data • Empirical analysis • Conclusions

3. Research Question • How does the entry of NGO schools affect the educational outcomes of girls in Bangladesh? • Does the entry of NGO schools increase girls’ enrollment relative to boys? • Characteristics of NGO and state schools that affect girls’ enrollment • How does attending an NGO school affect test scores?

4. Motivation 1. Rapid increase in girls’ enrollment rates in recent years => Gender equity in primary enrollment 2. Heavy involvement of NGOs in the provision of non-formal primary schools • 1.4 million children • Aim: poorest children (non-enrolled or dropout) • Many different characteristics

5. Theoretical framework • Show how NGO schools might affect girls’ enrollment as compared to boys’ • Schooling decision in cost-benefit framework • Main assumption: disutility of sending a child to school, which differs by gender and by school type

6. Max B(xs) – psjk + U(Y-ckj-xs) (1) {xs} • B(•) = benefits of education U(•) = utility from consumption s = male (m), female (f) k = no school (0), gov. sch. (g), NGO sch. (n) j = village j xs= expenditure on education of child s psjk= disutility of sending child s to school k in village j Y = income ckj = opportunity cost of time of going to school k

7. Assumptions: B(•) increasing & concave in xs U(•) increasing & concave in Y pfgj > pmgj = pmnj = pfnj cgj > cnj Let xj*(Y) be solution to (1) and V(Y) be maximum value function Enrol a child if: V(Y) - U(Y) > 0

8. Results: • Enrollment ↓ in pjk and cj andin Y Let Yjk* be threshold level Y above which a household will enrol child j in school k, then Ymnj* = Yfnj* < Ymgj* < Yfgj* • NGOs contribute to increase in enrollment of boys and girls, with stronger effects for girls Assume NGOs target households Y < Ytg Suppose Ymn* = Yfn* < Ymg* < Ytg < Yfg* • Gender gap disappears for the poor, but exists for the rich

9. Background • BRAC : largest NGO (1.2 million out of 1.4) • BRAC schools: • One-room school built inside village • 33 children & 1 teacher • Over 90% of teachers: female • Class time: decided by parents & teacher • 3-year cycle covering 3 years of gov. school curriculum

10. Data • Education Watch 1998 • 3 survey instruments: (1.) Household Survey Questionnaire (42,584 households, 31,092 children) (2.) Assessment of Basic Competencies (ABC) (3360 children) (3.) School Observation Checklist (885 schools)

11. Empirical analysis (1.) Entry of NGO schools and girls’ enrollment (2.) School characteristics that affect girls’ enrollment (3.) Test scores

12. Entry of NGO schools and girls’ enrollment: an overview

13. (1.1) Exposure to NGO schools and enrollment (11-20 years old) • Pr(Sij = 1) = α0 + α1EXPij + α2Girl*EXPij + α3Cij + α4Girl*Cij + α5Girl + α6Vj +error term where, Sij = 1 if individual i in village j was enrolled at time of survey, and 0 otherwise EXPij = 1 if individual i in village j was exposed to an NGO school in the village Girl = the dummy variable for being a girl Cij = a vector of child and family characteristics Vj= village fixed effects

15. (1.2) Involvement of NGO schools and enrollment (6-10 years old) • For each child, define: ‘the involvement of non-formal schools in a village’ number 6-10 yrs old in NGO schools number 6-10 yrs old enrolled in school excluding the child from the sample ‘ the involvement of government schools in a village’ is similarly defined

16. Pr(Sij=1) = α0 + α1Nij + α2Girl*Nij + α3Gij + α4Girl*Gij +α5Cij + α6Girl*Cij + α7Girl+ α8Aj + α9Vcj + error term where, Girl = dummy variable for being a girl Girl*Njshows the difference in the effects that the involvement of NGO schools has on the enrollment of girls as compared to boys

18. (1.3) Extensions: - Rural versus Urban - BRAC target versus non-target Definition: BRAC target: households with less than 0.5 acre of land and at least one person engaged in manual labor for at least 100 days per year

20. (2) School characteristics that affect girls’ enrollment • Pr(Sij = 1) = α0 + α1Ncj + α2Girl*Ncj + α3Gcj + α4Girl*Gcj + α5Cij + α6Girl*Cij + α7Girl + α8Aj +α9Vcj + error term where, Ncj = a vector of aggregate village-level characteristics of NGO schools in village j Gcj = a vector of aggregate village-level characteristics of government schools in village j

22. (4) Test scores • Yij = α0 + α1Tij + α2Girl*Tij + α3Cij + α4Girl*Cij + α5Vj + error term where, Yij represents (i) whether a child passed the ABC test or not, and (ii) test scores of life-skills, reading, writing, and numeracy sections Tij = dummy variable for the type of school that the child was attending at the time of survey

24. Conclusions • The entry of NGO schools significantly increases girls’ enrollment relative to boys. • It is mainly in the rural areas that NGO schools appear to have strong effects. • The effects of NGO schools are stronger for BRAC target households compared to non-target households.

25. The main characteristics of NGO schools that appear to encourage girls’ enrollment: high percentage of female teachers and having PTAs • Attending NGO schools shows significant effects on ABC test scores.