Demographic Microsimulation Modeling: The Future of Türkiye's Population and Policy Implications

Abstract

This thesis underscores the critical need for accurate information on future population composition, an essential factor in addressing the challenges posed by societal aging and transformation. We utilise microsimulation, a method that replicates real-life dynamics, to estimate both demographic and economic aspects of Türkiye's population. To this end, we integrated the 2018 Türkiye Demographic and Health Survey microdata with data from the Household Labor Force Survey and apply a dynamic microsimulation approach over a continuous time period. For the dynamic microsimulation implementation, we crafted a customized syntax within the R statistical software, aligning it with the specific data and their attributes. This programming enables the simulation of various individual characteristics, including region, age, sex, education, marital status, and labor force status, projecting up to the year 2030. The simulation result anticipates a steady population growth rate of approximately 0.5 percent annually, foreseeing a population reaching 86.6 million by 2030. Furthermore, our analysis indicates a decline in the total fertility rate from 2.1 to 1.6 by 2026, with a subsequent stabilization at this level. Our assertion is that microsimulation serves as an ideal tool for population estimation and demographic analysis, offering rich features that other methods may not consistently deliver. Moreover, we assert that this approach is adaptable, dynamic, and flexible in the context of Türkiye. Furthermore, our research demonstrates that dynamic microsimulation offers valuable opportunities for reevaluating population policies, and we propose solutions based on our findings.