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Evaluating sector support using secondary data

This study focuses on evaluating sector support in primary education using secondary data analysis. It explores impact evaluations, methodologies, challenges, and data sources such as school census, test results, and demographic surveys. The analysis includes interventions, school characteristics, and community outcomes.

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Evaluating sector support using secondary data

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  1. Evaluating sector support using secondary data Antonie de Kemp Policy and Operations Evaluation Department Netherlands Ministry of Foreign Affairs

  2. Under construction: IOB impact evaluations • Water and sanitary facilities • Pilot in Shinyanga (Tanzania); program • Primary education (sector support) • Zambia • Uganda

  3. Impact evaluation Primary education • Development of primary education: • access • equity • learning achievement • Main determinants? • Cost-effectiveness of interventions?

  4. Methodology • Regression based approach (education production function) • Analysis at the school level

  5. The evaluation model

  6. Interventions School characteristics Infrastructure Teaching materials Teachers School quality Access Learning achievement Pupil Household Community characteristics Welfare outcomes

  7. Data • Annual school census data (EMIS) • Test and examination results • Population census data (2002) • Demographic and Health surveys (Education data, 2001) • Management information from inspection reports • Additional survey (financial information, attendance rates, teacher absenteeism)

  8. Interventions School characteristics Infrastructure Teaching materials Teachers E M I S School quality Access Learning achievement UNEB Pupil Household Community characteristics Welfare outcomes

  9. Challenges when evaluating sector support • Attribution problem • Selection effects • Unobservables • Heterogeneity of interventions

  10. Treatment of unobservables • Check on random allocation of interventions • Double differencing • Exploitation of natural restrictions • Triangulation

  11. Quality of data • Analyse consistency through the linking of data • Systematic errors may be treated as unobservables

  12. Conclusions • At the sector level, interventions are heterogeneous and therefore an evaluation will rely mainly on secondary data. • In the social sectors, data become increasingly available. • Impact evaluations of sector support may help to analyse important issues. • Evaluation agencies must become familiar with the methods and techniques of rigorous impact evaluations. • We must further develop the methods for analysing secondary data. • It’s important to work closely together with partner countries.

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