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'Education'
<h1>Education</h>
The model forecasts gender- and country-specific access, participation and progression rates at levels of formal education starting from elementary through lower and upper secondary to tertiary. The model also forecasts costs and public spending by level of education. Dropout, completion and transition to the next level of schooling are all mapped onto corresponding age cohorts thus allowing the model to project educational attainment for the entire population at any point in time within the analysis horizon.
The model forecasts gender- and country-specific access, participation and progression rates at levels of formal education starting from elementary through lower and upper secondary to tertiary. The model also forecasts costs and public spending by level of education. Dropout, completion and transition to the next level of schooling are all mapped onto corresponding age cohorts thus allowing the model to project educational attainment for the entire population at any point in time within the analysis horizon.
From simple accounting of the grade progressions to complex budget balancing and budget impact algorithm, the model draws upon the extant understanding and standards (e.g., UNESCO's ISCED classification) about national systems of education around the world. One difference between other attempts at projecting educational participation and attainment and that  of IFs is the embedding of education within an integrated model in which demographic and economic variables interact with education, in both directions, as the model runs.  
From simple accounting of the grade progressions to complex budget balancing and budget impact algorithm, the model draws upon the extant understanding and standards (e.g., UNESCO's ISCED classification) about national systems of education around the world. One difference between other attempts at projecting educational participation and attainment and that  of IFs is the embedding of education within an integrated model in which demographic and economic variables interact with education, in both directions, as the model runs.  
Figure 1 displays the major variables and components that directly determine education demand, supply, and flows in the IFs system.  We emphasize again the inter-connectedness of the components and their relationship to the broader human development system.  For example, during each year of simulation, the IFs cohort-specific demographic model provides the school age population to the education model.  In turn, the education model feeds its calculations of education attainment to the population model’s determination of women’s fertility.  Similarly, the broader economic and socio-political systems provide funding for education, and levels of educational attainment affect economic productivity and growth, and therefore also education spending.
Figure 1 displays the major variables and components that directly determine education demand, supply, and flows in the IFs system.  We emphasize again the inter-connectedness of the components and their relationship to the broader human development system.  For example, during each year of simulation, the IFs cohort-specific demographic model provides the school age population to the education model.  In turn, the education model feeds its calculations of education attainment to the population model’s determination of women’s fertility.  Similarly, the broader economic and socio-political systems provide funding for education, and levels of educational attainment affect economic productivity and growth, and therefore also education spending.

Revision as of 22:23, 13 August 2018

Alert-warning.png Note: The documentation of IFs is 'under review' and is not yet 'published'!

Model Documentation - IFs

Corresponding documentation
Previous versions
Model information
Model link
Institution Frederick S. Pardee Center for International Futures, University of Denver (Pardee Center), Colorado, USA, https://pardee.du.edu/.
Solution concept
Solution method Dynamic recursive with annual time steps through 2100.
Anticipation Myopic

Education</h> The model forecasts gender- and country-specific access, participation and progression rates at levels of formal education starting from elementary through lower and upper secondary to tertiary. The model also forecasts costs and public spending by level of education. Dropout, completion and transition to the next level of schooling are all mapped onto corresponding age cohorts thus allowing the model to project educational attainment for the entire population at any point in time within the analysis horizon. From simple accounting of the grade progressions to complex budget balancing and budget impact algorithm, the model draws upon the extant understanding and standards (e.g., UNESCO's ISCED classification) about national systems of education around the world. One difference between other attempts at projecting educational participation and attainment and that of IFs is the embedding of education within an integrated model in which demographic and economic variables interact with education, in both directions, as the model runs. Figure 1 displays the major variables and components that directly determine education demand, supply, and flows in the IFs system. We emphasize again the inter-connectedness of the components and their relationship to the broader human development system. For example, during each year of simulation, the IFs cohort-specific demographic model provides the school age population to the education model. In turn, the education model feeds its calculations of education attainment to the population model’s determination of women’s fertility. Similarly, the broader economic and socio-political systems provide funding for education, and levels of educational attainment affect economic productivity and growth, and therefore also education spending.