1. Modeling Fiscal Implications of Education Policies
Part 2
Modeling Fiscal Implications of Education Policies
Sajitha Bashir
April 25, 2007
Public Finance Analysis and Management Course, World Bank

2. Structure of the Presentation
Why model fiscal implications of education policy?
Structure of models
Choice of Scenarios
Examples – DRC and Benin
Limitations

3. What will NOT be covered…
How to build a model
Building a model is a technical exercise; takes time and care. But it is a tool which can be done by a technician
For the PER author, what is important is to understand how to use this tool

4. Why Undertake Fiscal Modeling?
PER analysis should reveal areas where public resources are
not aligned with government objectives;
not used efficiently;
do not promote equity
Government Education Plan/Strategy sets out objectives and strategies
Usually no costs, especially costs
No implementation schedule

5. Usefulness of Fiscal Modeling in PER
Identifies fiscal impact of measures recommended to improve efficiency
Which measures create more fiscal space?
Which measures are under control of policy maker?
Assess realism and feasibility of proposed plan, its objectives, strategies and implementation
Fiscal sustainability; Managerial feasibility
Has impact on policy discussions, especially with Ministry of Finance

6. Different Modeling Approaches
Aggregate Fiscal Discipline
Sectoral Expenditure Envelope set by MOF (3-5 years); usually as part of MTEF
Within Sector: determine priorities, objectives, strategies (PER; sectoral analysis)
Cost Strategies
Is it consistent with resource availability?
Iterations – alternative strategies; suggest savings
Simulation Model
Set Sectoral Objectives and Strategies (PER/sectoral analysis/sectoral plan)
Estimate costs
Check macro/budget implications
Estimate domestic resource gap – compare with external financing
Iterations – come up with realistic resource gap

7. Simulation Model Purpose Method Results
Evaluate tradeoffs required to arrive at fiscally sustainable and technically sound educational strategy consistent with government objectives for coverage, quality, equity
Method
Develop different scenarios with varying assumptions
Results
Evolution of expenditures by type
Evolution of education system (pupil numbers, staff, schools, classes…)

8. Structure of Model
Spreadsheet – all quantifiable variables of education system are linked to each other
Five categories of elements
Base year data
Objectives
Assumptions about macro environment
Policy parameters
Results

9. Simple or Complex Models?
Model whole education sector?
Usually desirable to see sub-sectoral trade-offs
Level of complexity should be determined by purpose of exercise and results of sectoral analysis
If focus is on primary, more detailed strategies at primary level

10. Building Scenarios Input data are fixed
However many other things can vary:
Assumptions regarding macro environment
Policy Objectives
Policy parameters

11. Limit Number of Scenarios
Macro Assumptions x Objectives x Policy Parameters = potentially scores of scenarios
Choose 3 –5 scenarios!
Judgment is required – base selections on PER/sectoral analysis
What are the critical decisions confronting the government?

12. Macro Assumptions Usually invariant across scenarios Economic growth
Determines public receipts, public expenditures
Demographic growth
Determines growth of child population entering primary school
Usually invariant across scenarios

13. Years by which objectives are to be achieved can also vary
Sector Objectives
Pre-primary
Population coverage
Primary
Entry and completion rates (usually 100%)
Secondary and higher
Transition rates
Years by which objectives are to be achieved can also vary

14. Key Policy Parameters (1)
Internal efficiency
Repetition and drop out rates
Service delivery targets (access/quality)
School availability (proximity to habitation) and size
Teacher pay (by category of teacher)
Pupil-teacher ratio
Ratio of teachers to non-teaching staff
Use of multigrade teaching
Spending on non-salary items
Year for attainment of target is also variable

15. Key Policy Parameters (2)
Construction
Type of construction (community?)
Financing
% of enrolment in private sector (residual determines maximum for public financing)
Set public financing as ratio of domestic resources
Household financing in public sector (by category of expenditure and sub-sector) – reasonable in relation to household income?
External financing (by category of expenditure and sub-sector) - realistic?

16. Illustration – Democratic Republic of Congo
Challenges: limited public resources; high dependence on private financing; low coverage even at primary level but rapid growth at other levels; inefficiency in public spending
Policy issues: expansion of post primary levels; abolition of fees; raising teacher salaries
EFA plan sets ambitious objectives and strategies which are not costed

17. DRC- Common Assumptions of Scenarios

18. Key Policy Choices Reflected in Scenarios
Universal pre-school?
School feeding ?
Change some service delivery parameters (staffing norms etc)?
Trade-off between rapid quantitative expansion and quality improvement in post-primary

20. DRC- Cost Saving Measures of Scenarios 3 and 4

21. DRC- Impact on Education Indicators

22. DRC- Expenditure Requirements (FC and 2001US $ )

23. DRC - Preliminary Conclusions
Universal pre-school is not feasible
Staffing rationalization/use of multigrade teaching yields considerable savings
Reducing transition rates in post primary education is still required
Scenario 4 is most acceptable:
Examine relative unit costs and composition of expenditures to further assess suitability

24. Other trade-offs are possible…
Eliminate school feeding - expensive even when targeted to 30 % of pupils
What is its objective ? (increase attendance? improve student attentiveness?) Are resources better used elsewhere – e.g., to raise teachers’ salaries?
Raise pupil-teacher ratio
Stagger construction
Raise private financing share in higher education (but equity trade-off)

25. Benin – Issues
Primary GER – 97 % but high disparities between regions, gender and social groups
Quality very low – less than 10 percent of 3rd graders could read with comprehension
Primary completion rate – 46 %
Repetition rate – 36 % in final primary grade
Less than 2 % of domestic education budget on books and teacher training
Very rapid growth in higher education (mainly private, but also public)

26. Benin – Objectives of Modelling
Not to evaluate policy choices for a plan
Simulation model, used in context of PER, was used to identify the main issues to be addressed by education policy

27. Large Differences in Salaries of Primary Teachers
Salary per teacher in $ (% of per cap GDP)
% of total teachers
Primary teachers
(4.9)
100
Permanent
(7.9)
56.1
Contractual
(2.0)
19.9
Community
(0.8)
23.9
Francophone Africa
(6.3)
Anglophone Africa
(3.6)

28. Distribution of schools by pupil-teacher ratio in grade 1

29. Objectives for Primary Education
Goal
Target
Impact
Primary completion
100 % (1.76 millions pupils by 2015)
Classrooms/ teachers
Quality
Pupil-teacher ratio : 40
Teachers
Internal efficiency
Repetition rate : 10
Reduces rooms/teachers

30. Expenditure requirements – policy trade-offs
Number of teachers will need to double
Using civil servant teachers at current salary levels: expenditure needs will multiply by 4
Using contractual/community teachers: expenditures will multiply by 3
A new statute for teachers?
Post primary transition rate will also need to be reduced

31. Example: Algeria
Simulation model used in context of public expenditure analysis
Government Plan proposed massive expansion of higher education
Focus on infrastructure building; continue existing policy of free student food and accommodation
Modelling identified large impact on recurrent budget of cost of student accommodation/food
No hard budget constraint – oil windfall !
Helped to identify policy focus: should government be focusing on managing student dormitories or quality improvement and institutional reform of higher education?

32. Limitations (1) Powerful tool for decision-making
However, the most important first step is to formulate the policy choices
Hence, not a substitute for analysis and decision

33. Limitations (2) Model links only variables that can be quantified
Outcomes related to quality improvement (eg learning achievement) cannot be modelled
How do you model 1 million “better educated” students versus 1 million “less educated”students?
We model the inputs associated with better quality, hence focus is on costs , rather than outcomes

34. Major Reforms to Improve Quality – Difficult to Model
Example: Benin – French as language of instruction from class 1 may be impeding quality
Alternatives are:
use local language (18 in Benin)
use small groups in classes 1 and 2 (teaching aides?)
Use radio instruction to reinforce learning
How do you model costs?
Use some key cost drivers (eg additional teachers; teacher support; additional materials)

35. Limitations (3)
Many policy parameters are set as policy objectives (eg reducing repetition rate or drop-out rate)
But they are not necessarily under the control of the policy maker
We don’t clearly understand how provision of inputs (schools, teachers, etc) impacts on repetition (make implicit assumptions)
Many demand side factors affect parameters

36. Limitations (4)
Policy parameters with greatest fiscal impact often the most difficult to change (e.g., teacher pay policy, ratios of teachers to administrative staff)
Often difficult to link with budget preparation

37. Conditions for Effective Use of Simulation Models
Sound technical team
Policy makers and managers who use it as a tool for decision-making
Are results communicated for decision-making?
Institutional mechanisms for negotiating resources (for example, with Ministry of Finance, donors) AND technical capacity
Model should be updated regularly
Validation and documentation