Assessing Frontline Service Delivery in Education

Ritva Reinikka

World Bank - DECRG

HD week 2002

Motivation and Context

Public spending traditionally analyzed from efficiency and equity viewpoint using budget allocations data

Government performance becoming more of an issue

Relationship between public spending and outcomes ambiguous at best – Large literature on growth and education and health

outcomes

Identification Problem

Budget allocations poor predictors of services beneficiaries receive when institutions are weakProblem of identification

Household survey evidence shows that when measured by actual output education or credit, services important for poverty reductionThe “black box” of service delivery

how to get this:

The question is

Real outcomes Improved learning Better health status Welfare

– distribution– risk

From this:

?Government expenditure

services

Public providers

Government expenditure

Real outcomesLearningHealth statusWelfare

– distribution– risk

Private providers

Household behavior

Things are not that easy

Provision of Services

Financing and provision are two key aspects of service delivery– Until now financing been given most attention– Provision becoming more of an issue (WDR 2003/04)

Different types of providers– Government– Non-profits– Private for profit

Provider surveys

Public expenditure tracking surveys (PETS)– Information on actual spending is scarce– Follow money through different tiers of government down to

frontline facilities using sample survey techniques– Interviews and data collection from records

Quantitative service delivery surveys (QSDS)– Frontline service providers/facilities in basic services– Inspired by micro-level household and firm surveys– Cover different type of providers (by ownership)– Triangulation of data

Uses of provider surveys

PETS/QSDS can be combined– With each other– Downstream with household surveys– Upstream with public officials surveys

Diagnostic tool– Stylized facts of service provision– Quantify “moral hazard” (asymmetric information)– Capacity building when a collaborative effort

Policy research

Primary data for empirical research– Applies know microeconomic approaches to

evaluation of public spending– Design of incentives – Decentralization– Voice, asymmetric information– Accountability and oversight– Participation of users and partnership with others

Uganda PETS

Aggregate spending kept in check since 1992 (cash budgeting) and allocations improved in the late-1990sLittle information on actual spending & service delivery– Only a perception survey of households– Diagnostic objective initially but panel also allowed research

Hypothesis: primary enrollment stagnant despite a large increase in public spendingNo accounting information available on frontline service delivery units

Uganda PETS: school survey

Survey of 250 schools to collect detailed quantitative data from school recordsNot possible to do on all spending items, sectors, or tiers of government– Aggregated salary data available at the center– Little data at the local government level and not

forthcoming from officials

Schools kept relatively good records

Uganda school survey

Only 13% of non-wage expenditure reached the schools in 1991-95 on averageVariation between schools– Statistical analysis shows that leakage depends on school

characteristics (size, income, share of qualified teachers)

PTA primary source of school fundingEnrollment increased much more than indicated by national statistics (60% in 5 years)Health facility survey also carried out but didn’t work

Uganda PETS findings

Responsibility for primary education delegated to districts– Decentralization initially worsened leakage

Poor oversight by central governmentAllocation of resources based on relative bargaining power rather than efficiency and equity considerations

Impact

Power of systematic information vs. anecdotesInformation on transfers of funds to local governments regularly published in national media since 1996Posters at schools to inform citizens about school-level funding from central governmentPublicity also signals central government oversightIn 2000 and 2001 PETS carried out locally – 80-90% of non-wage spending reaches schools but

delaysTracking surveys expanded to other basic services

Tanzania PETS

Accounting firm (1999), and NGO and research institute have implemented (2001) as part of PERTrack pro-poor expenditures in priority sectors at all levelsCombinations of documents, records, facility visits, interviewsIn 2001, for example, survey of 5 districts, 4 primary schools and 4 clinics in each districts (small sample)

Tanzania PETS Findings

Non-wage leakage 57% in education 41% in health (1999)Larger delays in rural areas and non-wage recurrent (rather than salaries)Priority to council departments rather than service facilitiesCash budgeting and aggregated records undermine transparencyInformation asymmetry, e.g. local administration versus parents

Ghana PETS

Primary and secondary school and health facility pilot surveys– Recall method instead of records (not preferable)

Central government and district level80% of salary and 50% of non-salary expenditures reached primary schoolsOnly 20% of public health spending reached districts

Honduras PETS

Moral hazard and frontline health education workers

– Ghost workers• 2% in health;3-5% in education

– Absenteeism• 27% in health; 14% in education

– Job migration• 5% in health

Follow-up

Cannot be overemphasizedUganda followed up immediately producing a huge improvementTanzania initiated information dissemination and is beginning a public awareness campaignIn Ghana little follow-upIn Honduras little follow-up

Pilot Round of QSDS

EducationLaos: household survey linkPapua New GuineaUganda: information and voice Zambia: household survey link

Lessons from provider surveys

Can be used to study different problems in service deliveryDiagnostics of leakage in AfricaStaff behavior in Honduran social services– Ghost, absenteeism, job capture by employees– Rigorous sampling, pre-testing required

Qualitative approach yields hypotheses, quantitative surveys diagnosis and analysis