Quantitative Service Delivery Surveys: Some lessons from schools surveys Deon Filmer Development Research Group The World Bank Kampala, Uganda July 29, 2009

Why carry out a Quantitative Service Delivery Survey? Outcomes are low …

Starting points: Learning outcomes are low Inequality in TIMSS 2003 Mathematics test scores Source: Analysis of TIMSS 2003 database

Starting points: Learning outcomes are low Inequality in SACMEQ 2000 Mathematics test scores Source: Analysis of SACMEQ 2000 database

Why carry out a Quantitative Service Delivery Survey? Outcomes are low … … is it a lack of money?

Public spending is not enough to improve outcomes Pattern across countries * Difference in logs (x100) form rate predicted by GDP per capita Source: WDR 2004

Public spending is not enough to improve outcomes Pattern across primary schools in Mauritania

Similar changes in public spending can be associated with vastly different changes in outcomes … Source: WDR 2004

… and vastly different changes in spending can be associated with similar changes in outcomes.

How to assess the lack of association between spending and outcomes? Public spending benefits the rich more than the poor – Expenditure incidence analysis of public spending for diagnosis Lack of demand by households – Impact evaluation of programs to promote demand Money fails to reach frontline service providers – Public expenditure tracking surveys (PETS) Poor quality services – Quantitative Service Delivery Survey (QSDS) e.g., absenteeism, time on task

Public spending benefits the rich more than the poor Expenditure incidence of public spending

Lack of demand by households Impact of a scholarship program on girls enrollment in Cambodia: Enrollment probability among recipient and non- recipient girls by economic status decile Source: Filmer and Schady (2008) Impact of a conditional cash transfer on girls and boys middle school enrollment Impact of demand-side programs

Disbursed public spending on school grants that actually reach schools PercentGNI per capita (2000) GNI per capita PPP (2000) Ghana 1997/ Kenya 2004 (secondary school bursary funds) Madagascar Peru 2001 (utilities) 70 / PNG (2001/2002) 72 / Tanzania Uganda /2001 <20 / 80 Zambia 2001 (discretion/rule) 24 / Ye and Canagarajah (2002) for Ghana; Republic of Kenya (2005) for Kenya; Francken (2003) for Madagascar; Instituto Apoyo and World Bank (2002) for Peru; World (Bank 2004) for PNG; MOF, Government of Tanzania (2005) for Tanzania; Reinikka and Svensson (2005) for Uganda; Das et al. (2002) for Zambia. Percent of school grants that actually reach schools

Classic approach to analyzing education outcomes … Inputs School Outputs / Outcomes Money $$ Quality of public services … QSDS are a way to get inside the black box of service delivery at the facility level

What are Quantitative Service Delivery Surveys? Take the facility as the unit of analysis – Could be complemented with a household/users survey Collect quantitative information about – Physical infrastructure – Staff characteristics – Income and expenditures – Governance and management – Characteristics/Quality of service provision – Outcomes

Two different sets of surveys Indonesia: – December 1998: Early days of economic crisis … were schools feeling any impact – April/May 2000: Longer-run school-level impacts of the crisis, decentralization looming PNG – April/May 2002: little knowledge about the status of services in PNG; particular interest in decentralization; explicit concern about expenditure tracking

Some lessons from experience, with a focus on two different sets of surveys Indonesia: – 600 schools – 5 purposively selected provinces – 15 districts (40 schools per district) PNG – 220 schools – 8 purposively selected provinces – 2 districts (10 schools per district)

Activity structure Indonesia: – Close collaboration with research department of ministry of education. – Ministry staff served as full partners in pilot/questionnaire development; served as regional survey supervisors. – Gave the survey some legs within the ministry, enabled substantially lower costs … but cost in terms of capacity and experience. – Study conceived of as stand alone survey, with Ministry/policymakers as primary audience. PNG: – Partners with National Research Institute, an independent agency – Overseen by working group with various government, NGO, and other representatives. – Little hands on input from Ministry of Education. – Study conceived of as a part of WB Poverty Assessment.

What worked well Indonesia – Trends in enrollments at the school level Non-conventional wisdom result that enrollment impacts were mainly urban and at the secondary level; and in non-private/non- secular schools. But difficulty: enrollment levels/trends … not enrollment rates. – Perceptions of impact of crisis Identified general impact and school functioning as two main impacts (exploratory PC analysis) – Status of crisis-relief government programs (scholarship and grant programs) Schools grants: Coverage; use; interesting substitution between grants and other sources of government (especially local government) sources of fundingsubstitution Scholarships: Coverage (among students) – Trends in charging of fees

Indonesia 2000: Sources of school funding by grant receipt and public/private status Primary schoolsJunior Secondary schools In public schools, local government spending adjusted in response to grant No adjustment in private schools Substitution between grants and local government funding

Zambia 2001: Effect of a 100 Kwacha increase in expected and unexpected school grants on household expenditures on education Household spending falls by about 45 for each additional 100 Kwacha spent on anticipated grants Substitution between grants and household spending Source: Jishnu Das, Stefan Dercon, James Habyarimana, Pramilla Krishnan (2004)

What worked well PNG – Descriptive status of schools (very little prior information) – Good documentation of delays in subsidies / teacher paydelays in subsidies – Reasonable assessment of teacher absenteeism (pre-announced window for visit) – Good data to construct ghost teacher estimate (with substantial effort in matching to government payroll records)

Delay in ability to use subsidy: PNG 2001 Percent who received any subsidyWeeks delay Note: Q1,Q3=National, Q2,Q4=Provincial

Absence rates among teachers and health workers Note: Surveys were all fielded in 2002 or Sources: Chaudhury et al (2006) except for PNG, World Bank (2004) and Zambia, Das et al (2005).

PNG 2002: Depletion of the effective supply of teachers Source: PESD Results from QSDS: Effective supply of teachers

Percent of time officially allocated to schooling; when a teacher is present; and spent in teaching and learning activities Beyond absenteeism: Effective supply of teaching Sources: Egypt, Yemen and Lebanon from Lane and Millot (2002); Tunisia, Pernambuco, Morocco and Ghana from Abhadzi, Millot and Prouty (2006); Cambodia from Benveniste, Marshall and Caridad Araujo (2008); and Laos from Benveniste, Marshall and Santibanez (2007).

Investigating accountability in education service delivery PNG 2002: Teacher absence declines with parent and community involvement Source: PNG PESD 2002.

What was harder Indonesia: – Trends in overall school incomes never clear we had full picture (what we did have was worrisome, especially for private schools) – But, incredibly complicated system … is this worth doing when the system is so complex? PNG: – Complex funding system … but able to track some specific payments (school subsidies)school subsidies – But … school financial data very spotty only about half of the schools had documentation about spending, half about receipts Only 30% of schools had both expenditures and receipts documentation

Funding education in PNG 2001, million Kina Source: Based on information collected during the PESD 2002 survey. Q1,3 Q2,4

What I would think twice about doing again Enrollment trends (unless have information on universe of schools and on population trends by area) – Hard (time consuming) to collect, hard to interpret Too many instruments – PNG had 9 instruments, 7 at the school level. Non-representative/random sample of parents

Survey instruments in PNG: – School (head teacher); – teacher roster; – select teachers; – data appendix; – grade 5 teacher; – board of management member; – parent; – District Education Advisor; – Provincial Education advisor.

I would think (very) hard about what financial data to collect The more specific the better – But even there, school officials often don t associate specific transfers to official name Anything more than tracking a clearly defined transfer is very hard. Even that is hard: – missing information at schools; – missing records at provincial level; – defining the base Official declarations in Government Circulars Budget disbursements School level expectations

What I would never do again Data entry using a package not designed for that purpose Sophisticated survey/tracking exercise in a country where policy environment not conducive to use information

Thank you!