Local level governance and schooling in decentralizing Indonesia

1. Local level governance and schooling in decentralizing Indonesia Vivi Alatas (EASPR) and Deon Filmer (DECRG) Conference on Governance and Accountability in Social Sector Decentralization February 2004

2. Status of study / focus of presentation • Preliminary and incomplete study: • What has been the impact of decentralization on education outcomes? • But • Limited time that decentralization been implemented in Indonesia; • Lags involved in the realization of impacts; • Lags in measurement of impacts. • This paper and presentation are a description of the assessment strategy and a discussion of some preliminary findings

3. BackgroundDecentralization in Indonesia • In 2000: Big-bang decentralization to district (Kabupaten) level • In addition to the overall changes, the education sector was particularly affected: • Junior Secondary schooling was previously administered by central authorities (through their deconcentrated structures) and is now administered through the local government office along with Primary schooling. • Funding for Basic Education now comes from the Local Government budget, and is therefore determined by the local political process.

4. BackgroundDecentralization in Indonesia • Simultaneously, a general move to increased school-based management • All this against the backdrop of the East Asian financial crisis which was particularly harsh in Indonesia

5. BackgroundOpportunities and risks of decentralization • Potential benefits • Reflect demands of local population • Potential efficiency gains • Innovation • Local-level ownership • Risks • Local allocations to education less than (nationally) socially optimal • Local elite capture • Lack of experience of the local administration • Increase in inequality • Literature points to potential importance of autonomy and accountability at the local level

6. Research strategy • “Big-bang” rules out any simple counter-factual …“what would have happened without decentralization?” • The approach used is to exploit the fact that decentralization will lead to increased variability in factors that affect outcomes • Documenting this variability, and relating it to changes in outcomes, is how we propose to assess the impact of decentralization on outcomes

7. WDR2004: A framework for how decentralization might affect outcomes? Policymakers Compact and management Voice Students/ Parents Schools/ teachers Client power

8. WDR2004: A framework for how decentralization might affect outcomes? Policymakers Compact and management Voice Students/ Parents Schools/ teachers Client power

9. Building accountability into the systemVoice Ah, there he is again! How time flies! It’s time for the general election already! By R. K. Laxman

10. WDR2004: A framework for how decentralization might affect outcomes? Policymakers Compact and management Voice Students/ Parents Schools/ teachers Client power

11. Building accountability into the systemClient Power I can’t understand these people. Not a soul here knows how to read or write and yet they want a school By R. K. Laxman

12. Decentralization: increased variability of accountability relationships Local Policymakers Policymakers Local Policymakers Students/ Parents Schools/ teachers Students/ Parents Schools/ teachers Students/ Parents Schools/ teachers Local Policymakers Policymakers Local Policymakers Students/ Parents Schools/ teachers Students/ Parents Schools/ teachers Students/ Parents Schools/ teachers

13. Research strategy • Identify district and school level indicators of • Voice • Compact • Management • Client power • And exploit how those have changed over time in order to assess the impact of decentralization

14. Current paper • Use baseline data to describe patterns and relationships between the indicators and outcomes

15. Data • Governance and Decentralization Survey • 177 Districts • Conducted in early 2002 • Instruments to: • local administration officers (including the Dinas office) • as well to school head teachers • School census from MONE • All schools • Includes data on revenues; expenditure, school characteristics, teacher background, • And, our outcome of interest, school average results on national standardized tests (NEM)

16. Data • District budget data • Development (investment) and routine (operational) data for 1994-1999 period • Household survey data from SUSENAS • District average household per capita expenditures (and its standard deviation)

17. Combining data—the “matched” and “unmatched” samples • The limited number of schools in the GDS means that if school level indicators derived from the GDS are used, the sample size shrinks dramatically (about 140 JS schools). • So much so that it is hard to identify any statistically significant results in the data analysis.

18. Combining data—the matched an unmatched samples • Using district average indicators derived from the GDS allows the analysis to include all schools in the school census (e.g. about 3300 JS schools) • Focus (for the moment) on Secondary schools

19. Empirical model • Dependent variable = test scores • Independent variables = • Measures of voice, compact, management, client power • Control variables • One specification includes school-level education inputs • “Cross-sectional” data combining school (and other) data from 1999 with GDS data data from early 2002 • OLS regression

20. Results • Voice • More NGO involvement as measured by • the number of meetings between NGOs and local government; • and NGOs as channels for complaints about education services is associated with higher test scores • The • Frequency of media publicity about problems in education is associated with lower test scores (reverse causality?)

21. Results • Compact • Clarity of the schools objectives as measured by • head teacher’s involvement in setting the school’s vision and mission is associated with higher test scores • The • number meetings between local government education administrators and head teachers is not associated with test scores (quality of the meetings?)

22. Results • Management • Greater • head teacher involvement in teacher recruitment and in • school based management is consistently associated with better test scores • But • involvement in curriculum, • budget allocation, and decisions regarding • teacher discipline are negatively associated with test scores (reverse causation?)

23. Results • Client power • Appears to be a weak force, although • involvement of Parent Teacher Associations in teaching tools procurement and • in curriculum are associated with higher test scores (JS level) • But involvement in none of the other areas, e.g. • teacher discipline, school based management, textbooks are associated with outcomes.

24. Looking forward • Decentralization is expected to affect indicators that appear associated with learning outcomes • Assessing the “impact” of decentralization will be made even harder: • Centralized data collection efforts are weakening • National standards are falling by the way (e.g. NEM) • Ensuring sufficient sample sizes to measure effects is difficult. • Hope that new rounds of GDS can overcome some of these constraints, as will working with counterparts to ensure complete and timely data collection