Ireland in 2057: Projections using a Geographically Diverse Dynamic Microsimulation

TL;DR

SEMIPro presents an open-source dynamic microsimulation for Ireland that projects population and socioeconomic outcomes from 2022 to 2057 by modeling births, deaths, internal migration, and international migration for individuals defined by seven attributes at the ED level. The method leverages an IPF-generated synthetic base population, CSO data for calibration, and multiple migration scenarios to produce internally consistent, regionally rich projections that closely align with CSO Demographic Component Method results. Key findings include substantial growth in education attainment (nearly 70% of young people achieving a third-level degree) and a declining unemployment rate, alongside striking ED-level dynamics such as Maynooth’s surge and Derrylaur’s decline. The work provides a flexible, policy-relevant tool for long-horizon planning and highlights avenues for future enhancements, including Bayesian small-area estimation and household-level extensions.

Abstract

This paper presents a dynamic microsimulation model developed for Ireland, designed to simulate key demographic processes and individual life-course transitions from 2022 to 2057. The model captures four primary events: births, deaths, internal migration, and international migration, enabling a comprehensive examination of population dynamics over time. Each individual in the simulation is defined by seven core attributes: age, sex, marital status, citizenship, whether the person was living in Ireland in the previous year, highest level of education attained, and economic status. These characteristics evolve stochastically based on transition probabilities derived from empirical data from the Irish context. Individuals are spatially disaggregated at the Electoral Division level. By modelling individuals at this granular level, the simulation facilitates in-depth local analysis of demographic shifts and socioeconomic outcomes under varying scenarios and policy assumptions. The model thus serves as a versatile tool for both academic inquiry and evidence-based policy development, offering projections that can inform long-term planning and strategic decision-making through 2057. The microsimulation achieves a close match in population size and makeup in all scenarios when compared to Demographic Component Methods. Education levels are projected to increase significantly, with nearly 70% of young people projected to attain a third level degree at some point in their lifetime. The unemployment rate is also projected to decrease as a result of the increased education levels.

Figures (11)

• Figure 1: The order in which the annually-computed modules are calculated. All of the possible characteristics which could be used as inputs are outlined along with the major functions of each module.
• Figure 2: The changes in the population size for all three international migration scenarios using both microsimulation and DCM methods
• Figure 3: Changes in population size at the regional level
• Figure 4: A comparison of the average births per intercensal period in each region using both SEMIPro and DCM
• Figure 5: A comparison of the average deaths per intercensal period in each region using both SEMIPro and DCM