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Education Participation in Sri Lanka – Why all are not in school

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Education Participation in Sri Lanka – Why all are not in school

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  1. Education Participation in Sri Lanka – Why all are not in school Nisha Arunatilake Institute of Policy Studies of Sri Lanka

  2. Background • Formal education in Sri Lanka is provided through an extensive network of more than 10,000 schools spread across the country • Since the Free education act of 1949 education has been free up to first degree University level • Only 93% of 5-14 year olds are in school • 97% - among the richest one fifth • 92% among the poorest one fifth

  3. Background contd… • Since 1987 Education has been decentralized • But all policies formulated and implemented from the centre • Provincial authorities largely limited to administrative functions • Ambitious development plans, but funding problems impeding implementation • Often recurrent expenditure takes priority over much needed physical and human capital investment related expenditure

  4. Background contd. • Although education is provided “free” of charge, out of pocket expenditure on education is quite high • 27% of total spending on education from private sources on: • tuition , books, stationery and clothing • Although education is accessible in terms distance and affordability, wide disparities in quality of available education

  5. Availability of resources in govt. Schools

  6. Children in communities with poor school resources – by expenditure quintile (per cent)

  7. Motivation for the present study • In January 1998, Sri Lanka legislated compulsory education for 5-14 year olds • Implemented through local committees whose job is to confront parents of non-schooling children to persuade them to send children to school • Persuasion alone may not succeed in getting children to attend school • This study evaluates the reasons for school non-attendance • It hopes to help formulate policy that would facilitate school participation

  8. Data • Sri Lanka Integrated Survey 1999/2000 • 7,500 households representing all provinces in 500 urban rural and estate communities • The survey collected information both at the household and the community levels

  9. Sample and Estimation • Sample is restricted to children between 5 to 14 years • Dependent variable – school participation • Results estimated using binary logit

  10. Explanatory Variables • School quality indicators • Poor resources (learning and teaching) [m=0.56] • Teacher vacancies [m=0.38] • Poor school facilities [m=0.71] • Out of pocket expenditure on education (annual community averages) • Essential school expenditure [m=Rs. 1,160] • Tuition expenditure [m=Rs.630]

  11. Explanatory Variables • Individual characteristics • gender, age • Household characteristics • Time to school, ethnicity, sector, province • Number of children in the hh • Education of hh_head and spouse • Employment of hh_head • Expenditure/Income group • Community level characteristics • Main livelihood of community

  12. Main Findings • School Quality Indicators • Teacher vacancies • Negatively affected school attendance • In overall, richest, poorest and under_9 • Poor Physical facilities in school • Unexpectedly, positively influences school participation of children nine and younger • Possibly due to subjective evaluation of school facilities

  13. Main Findings • Direct costs of schooling • Tuition expenditure • Negatively influences school participation • In the overall and poorest, 9 or less, 9 plus samples • Essential school expenditure (text books, stationery, etc.) • Negatively influences school participation • In the poorest and the 9 plus samples

  14. Main Findings • Location and Community Level Characteristics • Community livelihood • Being in a community where main livelihood is agriculture or fishing negatively influences school participation • Overall, poorest and richest samples, and 9 or less (?)

  15. Main Findings • Other HH characteristics • Ethnicity influences school participation significantly • Relative to Sinhalese (main ethnic group) children from other ethnic groups less likely to be in schools (explanation – teacher vacancies?/ cultural factors?) • Employment of hh_head • HH_head owning a farm, in informal employment or not working negatively affects schooling • HH composition • Children from HHs with young kids (0 to 6) less likely to be in school

  16. Main Findings • Access to schools • Did not influence school participation significantly • HH expenditure/income • Relative to children in the richest group children in the poorest group, less likely to attend school

  17. Main Findings • Individual level characteristics • Being a male (in the poorer samples) decreased the likelihood of attending school • (unusual for most developing countries/ possibly due to larger opportunity cost of attending school) • Age • Children seem to start schooling late (not at age 5) and drop out as they age – school attendance is highest for children in 9 – 11 age group

  18. Summary • Poverty influences schooling negatively • School quality affects schooling decision • (teacher vacancies/ tuition expenditure) • Opportunity costs of schooling affects schooling decision • Being in an agricultural/ fishing community • Employment of hh_head • Coming from families with small children

  19. Summary • Limited know-how/ motivation of parents affects schooling • Starting school late, cultural factors

  20. Discussion • Appointment of local communities to compel parents to send children to school is not a sustainable solution • Despite government’s attempts to assist school attendance through the provision of free uniforms and text books, high out of pocket expenditure is keeping children away from school

  21. Discussion • Children from farming communities and families owning farms are probably not attending school due to high opportunity costs. School calendars in these areas should take into account the high demand periods for farm labour • More attention should be given to improve quality of schooling

  22. Discussion • Lastly, inadequacy of government funding seems to affect many problems related to school quality. Especial attention should be given to improve funding for the sector – either public or private • Thank you