Age, Sex and Education Specific Urbanization Projections up to 2100 for Kenya

Alessandra Garbero, International Institute for Applied Systems Analysis (IIASA)
Warren C. Sanderson, Stony Brook University, State University of New York (SUNY)

We present a new methodology for producing urbanization projections disaggregated by age, sex and level of educational attainment. Using micro-data from the IPUMS international database, we computed historical education-specific age and sex distributions of individuals living in urban and rural areas and compared such distributions at different points in time. From this empirical analysis, we observed that age, sex and education-specific patterns of urbanization are remarkably regular and identified “model” pathways of urbanization trajectories over time. To project such urbanization rates up to 2100, we applied the education-dependent model schedules to the base year estimates, projected the population forward using a multistate cohort component method (K.C. et al., 2010) and obtained differential urbanization trajectories under three education scenarios (General Enrollment Trend (GET), Constant Education Numbers (CEN) and Fast Track (FT)). Cognizant of limitation of this approach, and acknowledging definitional and reclassification issues, we present age/sex and education-specific urbanization forecasts for Kenya.