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Seán Caulfield Curley

Publications and source records attributed to Seán Caulfield Curley.

2 recordsLinked to original sources

Ireland in 2057: Projections using a Geographically Diverse Dynamic Microsimulation

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.

cs.CY↗

Predicting Long-Term Self-Rated Health in Small Areas Using Ordinal Regression and Microsimulation

This paper presents an approach for predicting the self-rated health of individuals in a future population utilising the individuals' socio-economic characteristics. An open-source microsimulation is used to project Ireland's population into the future where each individual is defined by a number of demographic and socio-economic characteristics. The model is disaggregated spatially at the Electoral Division level, allowing for analysis of results at that, or any broader geographical scales. Ordinal regression is utilised to predict an individual's self-rated health based on their socio-economic characteristics and this method is shown to match well to Ireland's 2022 distribution of health statuses. Due to differences in the health status distributions of the health microdata and the national data, an alignment technique is proposed to bring predictions closer to real values. It is illustrated for one potential future population that the effects of an ageing population may outweigh other improvements in socio-economic outcomes to disimprove Ireland's mean self-rated health slightly. Health modelling at this kind of granular scale could offer local authorities a chance to predict and combat health issues which may arise in their local populations in the future.

cs.MA↗