Evaluating sector support using secondary data
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Evaluating sector support using secondary data. Antonie de Kemp Policy and Operations Evaluation Department Netherlands Ministry of Foreign Affairs. Under construction: IOB impact evaluations. Water and sanitary facilities Pilot in Shinyanga (Tanzania); program

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Evaluating sector support using secondary data

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Evaluating sector support using secondary data

Antonie de Kemp

Policy and Operations Evaluation Department

Netherlands Ministry of Foreign Affairs


Under construction: IOB impact evaluations

  • Water and sanitary facilities

    • Pilot in Shinyanga (Tanzania); program

  • Primary education (sector support)

    • Zambia

    • Uganda


Impact evaluation Primary education

  • Development of primary education:

    • access

    • equity

    • learning achievement

  • Main determinants?

  • Cost-effectiveness of interventions?


Methodology

  • Regression based approach (education production function)

  • Analysis at the school level


The evaluation model


Interventions

School characteristics

Infrastructure

Teaching

materials

Teachers

School quality

Access

Learning achievement

Pupil

Household

Community characteristics

Welfare outcomes


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)


Interventions

School characteristics

Infrastructure

Teaching

materials

Teachers

E M I S

School quality

Access

Learning achievement

UNEB

Pupil

Household

Community characteristics

Welfare outcomes


Challenges when evaluating sector support

  • Attribution problem

  • Selection effects

  • Unobservables

  • Heterogeneity of interventions


Treatment of unobservables

  • Check on random allocation of interventions

  • Double differencing

  • Exploitation of natural restrictions

  • Triangulation


Quality of data

  • Analyse consistency through the linking of data

  • Systematic errors may be treated as unobservables


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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