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HIGH-LEVEL PROJECTIONS FOR EDUCATION (HIPE)
A Resource Planning Tool for Effective Policy Makers Collaborative Africa Budget Reform Initiative meeting Accra, Ghana February 25-27, 2013
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FHI 360 GLOBAL LEARNING GROUP
FHI 360 is a nonprofit human development organization advancing integrated, locally driven solutions in health, education, nutrition, environment, economic development, civil society, gender equality, youth, research and technology FHI 360 serves more than 60 countries FHI 360 Global Learning Group programs emphasize the use of data for decision making and foster student- centered learning in fragile and post-conflict areas.
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Data Management Data Visualization Data Analysis
One of the largest online databases for education data from around the world Administrative and household survey data Learning outcomes from achievement studies Data Visualization A state-of-the-art resource in online data visualization: Publication quality country education profiles Data Analysis Research on key issues in education (e.g.: orphans and vulnerable children, out-of-school) Education trend analysis and projections of future enrollment
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Education projections
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Introduction Projections are a management and planning tool for researchers and policy makers in different fields Demography Environment Finance Health Education Projections in education are used to set expectations of pupil enrollment and resource needs within an area of interest
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FHI 360 EPDC projections expertise
Education trend projections for multilateral and bilateral agencies (USAID, UNESCO, UNICEF, AusAID, GPE) Target-driven projections for local governments and education authorities (Pakistan, Namibia) Each set of projections has its rationale and assumptions Projections are only as good as the baseline data and the realism of the assumptions that drive them
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Stage 1: Pupil enrollment projections
Use available current and historical pupil enrollment data Apply known or target rates of new intake, repetition, and dropout, to model the flow of cohorts and calculate total number of pupils in each grade Disaggregate by geographic area, level of education, gender, etc Use pupil/teacher ratio, pupil/ classroom ratio, pupil/ textbook ratio data to estimate total need for teachers and classrooms
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EPDC projections: the Cohort method
EPDC employs the Cohort method, where pupils are traced through a time series, starting from latest historical year Intake, repetition and dropout rates are applied to the available population and pupil data to model cohort movement Grade 3 Students, Year 3 Grade 2 Students, Year 2 Grade 1 Students, Year 1 New entrants, Year 0
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General principles Projections of pupil enrollment are driven by a set of manipulable parameters: Gross intake rate (i.e. proportion of pupils in Grade 1 over the population of starting age) Repetition rates, by grade and gender if possible Dropout rates, by grade and gender if possible Pupil-teacher, pupil-classroom, pupil textbook ratios Training costs, if available Therefore, the assumptions about the expected change in these key indicators determines the outcome, in terms of pupil enrollment
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Constant method: Fix the parameter at most recent available historical value
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Linear Trend Method
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Target method: Reach 100% by 2025
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Flexible trend: EPDC model for GPE
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Flexible trend: EPDC model for GPE
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Once the driver parameter assumptions are set:
Pupil projections Once the driver parameter assumptions are set: For each year in the projection period (e.g ), a value for GIR and flow rates is calculated The resulting value for each year is applied towards relevant population and pupil data to obtain a projection of pupils
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Pupil cohort projections in a nutshell
Grade 1 projection = New entrants + Repeaters in G1 New entrants = Gross intake rate * Relevant population Repeaters = Repetition rate * Relevant Enrollment in G1 Grade 2 projection= Promoted pupils+ Repeaters in G2 Promotion= Enrollment from G1, minus repetition (those who stay in G1), minus dropout (those who leave the system permanently) Repeaters = Repetition rate * Relevant Enrollment in G2 Grade 3 and above: Same method as for Grade 2 (promotion from previous grade + repetition from same grade)
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Results: Total primary enrollment
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Education cost projections
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Stage 2: Cost projections
Enrollment projections are transformed into projections of resource needs: Teachers: total enrollment / pupil-teacher ratio (PTR) New teacher need is estimated as the difference between existing teacher force and total teacher need Teachers to be trained (if available, based on proportion of teachers known to be untrained) Classrooms: total enrollment / pupil classroom ratio Textbooks: total enrollment / pupil textbook ratio Unit costs are then applied to convert resource needs into anticipated expenditures
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Costing it out: Teacher salaries
= Projected Teachers X Annual teacher salary (can be set as target or kept constant ) Teacher salary cost teacher salary
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Costing it out: Teacher training costs (South Sudan HIPE module only)
Teacher training need = % Trained teachers X Total teachers projected Training may be disaggregated by type of training: in-service or pre-service, set by the user (in-service may be higher cost)
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Costing it out: Teacher training cost
Cost of pre-service training Cost of in-service training X Proportion of teachers that need training
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Costing it out: Classroom costs
Classroom costs consist of: New classroom construction cost Classroom maintenance cost (usually a percentage of construction cost) Total classroom need = Enrollment / PCR New construction need = Total need – Existing classrooms All existing classrooms should be included in maintenance costs
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Costing it out: Classroom costs
Classroom construction may be further broken down by type of classroom: permanent, semi-permanent, or other, as in this example:
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Costing it out: Classroom costs
Even as the total number of classrooms needed decreases in South Sudan, the new classroom building costs increase as the Ministry aims to build more permanent classrooms
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Costing it out: Textbook costs
= Textbook need X Cost per textbook Total textbook costs can be set by the user – held constant, or vary across future years
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Costing it out: Textbook costs
In the South Sudan HIPE model, textbook costs were projected separately for English, Math, and other subjects, based on target costs set for future years
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Costing it out: Total expenditure and gap estimation
Combine all costs: teacher salary costs teacher training costs (if estimated) classroom construction and maintenance costs textbook costs Add other recurrent cost projection (set as % of salaries, or broken out by individual line items) IF IMPORTANT: Separate out PUBLIC expenditure Project budget availability Education budget as % of total government budget, by level (primary and secondary)
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Summing it up for South Sudan
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Summing it up for South Sudan
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Flexibility and richness of HIPE projection modeling
Can be adapted to any context and scenario Is flexible and driven by user-set parameters, which can be either aspirational (target) or trend-based Can span multiple national and subnational units: For South Sudan, the national model combines several state-specific modules, each with state-level data and projections A model developed for Pakistan develops projections within one province, at the district level A model for UNESCO and GPE spans across multiple countries
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More information is available upon request: epdc@fhi360.org
THANK YOU More information is available upon request: Carina Omoeva, Ph.D. Education Policy and Data Center Global Learning Group FHI 360
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