Modeling Fiscal Implications of Education Policies

1
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
• 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

• Economic growth
• Determines public receipts, public expenditures
• Demographic growth
• Determines growth of child population entering
  primary school
• Usually invariant across scenarios

13
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

19
(No Transcript)
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
28
Distribution of schools by pupil-teacher ratio in
grade 1
29
Objectives for Primary Education
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
  educatedstudents?
• 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 dont 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