A Novel Weighting-Based Approach to Cohort Replenishment in Dynamic Microsimulations
We propose a new method for generating replenishment cohorts in dynamic microsimulation models. Standard dynamic microsimulations project the future states of an initial population through the recursive application of one-step-ahead predictions. Over time, sample size declines due to attrition (e.g., mortality), and without the integration of new individuals, the projected population progressively departs from the target population structure. To preserve representativeness, replenishment cohorts must therefore be introduced at each simulation step.
Read MoreDemand and Supply of Care Over the Life Course
We project the effects of changes in fertility and mortality rates on both the receipt and provision of care in the UK. We investigate the impact on the level and cost of care, as well as its share of total GDP, through the life course and across income and wealth distributions. SimPaths, an open-source dynamic microsimulation model, is employed to design different scenarios over a half-century period. This framework projects life histories over time, developing detailed representations of career paths, family and intergenerational relationships, health, and financial circumstances. Our estimates show that the value of care, as a share of GDP, almost doubles over the five decades of our analysis, with informal care accounting for most of the projected rise.
Read MoreForecasting ADRD in European Elderly Population Using Dynamic Microsimulation
Population ageing is rapidly increasing the prevalence of Alzheimer’s disease and related dementias (ADRD) across Europe, creating major challenges for health and long-term care systems. Existing European projections typically rely on static prevalence assumptions or self-reported diagnoses and rarely model individual cognitive trajectories within a unified, forward-looking framework. This paper presents a major extension of the European Future Elderly Model (EU-FEM), introducing a dedicated microsimulation module for dementia and cognitive decline applicable across multiple European countries. Using harmonized longitudinal data from SHARE Waves 1–9 (2004–2022), we develop and integrate a dynamic ADRD module that simulates transitions in cognitive status for individuals aged 50 and over. Cognitive decline status is defined using the Langa–Weir (LW) classification, adapted to the European context by combining episodic memory tests with functional limitations in instrumental activities of daily living (IADLs). Country-specific cut-offs are calibrated against OECD dementia prevalence benchmarks and tested for robustness across alternative SHARE waves. The classification algorithm incorporates deterministic and stochastic imputation procedures and enforces the absorptive nature of dementia over time. The ADRD module is embedded within EU-FEM’s first-order Markov Monte Carlo framework, allowing cognitive decline to evolve jointly with chronic conditions, demographic characteristics, and socioeconomic factors. Transition equations condition on prior Socio Economic Status (education, income, wealth, labour market status), health and cognition, enabling heterogeneous life-course trajectories. The enhanced model expands EU-FEM coverage to twelve European countries, including new Central and Eastern European populations, and produces internally consistent projections of dementia prevalence and cognitive trajectories. Validation exercises show close alignment with external epidemiological benchmarks and substantial improvements over self-reported dementia measures. This work demonstrates how dynamic microsimulation can be used to model cognitive decline in a harmonized, multi-country setting, providing a flexible platform for forecasting dementia prevalence and evaluating counterfactual scenarios involving risk-factor modification, prevention policies, and future care needs. The extended EU-FEM establishes a foundation for integrating cost-of-illness and long-term care modules, supporting policy analysis in ageing European societies.
Read MoreFrom Marital Entitlements to Individual Risks: Vertical Solidarity and the Future of Survivors’ Pensions in Beveridgean Systems
Survivors’ pensions have long served as a central pillar of social protection in Beveridgean pension systems, offering intrafamilial insurance against the economic consequences of widowhood. Yet demographic ageing, evolving family structures, and gendered labour‑market patterns increasingly call into question the appropriateness and sustainability of marital-status‑based entitlements. Drawing on recent European jurisprudence and ongoing reform debates in Switzerland, Finland, Germany, and Japan, the project examines how the abolition or redesign of survivors’ pensions would affect vertical solidarity in a Beveridgean first‑pillar pension system. Using the Swiss Old‑Age and Survivors’ Insurance (OASI) as an illustrative case, the analysis explores how interpersonal redistribution, intrafamilial solidarity, and spousal equalisation mechanisms jointly shape pension outcomes across marital statuses and along the pension‑income distribution. The study employs MIDAS‑CH, a dynamic microsimulation model calibrated to Swiss SILC data, to generate long‑term counterfactual life‑course trajectories under shifting gender labour‑market behaviours. This enables an assessment of how redistribution embedded in the Swiss first pillar—minimum and maximum pensions, care credits, splitting rules, and survivor benefits—operates in a context where men’s and women’s participation, hours, and wages converge. As family structures diversify and dual-earner households become the norm, traditional justifications for marital entitlements weaken, suggesting that solidarity mechanisms may need to shift from status-based to individualised forms. To identify the redistribution channels at work, the project applies a Recentered Influence Function (RIF) decomposition, which separates differences in characteristics (earnings histories, contribution years, care credits) from differences in coefficients, interpreted as the redistributive valuation embedded in the benefit formula. This distinction allows a distribution‑sensitive quantification of vertical solidarity and an assessment of how strongly various institutional components compensate gendered labour‑market inequalities. The RIF approach provides insight into nonlinear redistribution at the bottom, middle, and top of the pension distribution—precisely where floors, ceilings, credit valuation, and splitting rules bite. Simulation results show that survivors’ benefits play a meaningful but declining role in equalising outcomes, particularly as women accumulate stronger contributory records. Removing survivor pensions lowers intrafamilial solidarity but increases the relative importance of interpersonal redistribution, especially for low‑income individuals. When labour‑market participation, work intensity, and wages between men and women are equalised, women’s pensions rise markedly, while men’s decline modestly. Consequently, the gender pension gap narrows substantially through improved earnings capacity rather than through marital entitlements. In scenarios of full labour‑market convergence, marital-status‑based mechanisms—splitting, capping, and survivors’ benefits—become less central, while individualised solidarity instruments such as minimum pensions and care credits remain decisive. These findings highlight a fundamental shift in the organisation of solidarity within Beveridgean pension systems. As gender labour‑market trajectories converge and family forms diversify, the rationale for marital entitlements weakens, and the effectiveness of solidarity increasingly depends on individualised, needs‑based instruments rather than derived rights. Vertical solidarity remains essential for cushioning fragmented careers and low earnings, but its incidence evolves as women’s labour‑market attachment strengthens. In this environment, survivor protection can be better targeted through time‑limited or earnings‑tested supplements, while care credits and progressive benefit formulas remain central to mitigating gendere
Read MoreMeasuring and Modelling Migrant Fertility: Using Hazard Models and Dynamic Microsimulation to Simultaneously Account for Multiple Clocks
The share of individuals with a migration background in European societies is increasing, both directly because of migration and indirectly because migrants’ descendants give rise to an increasing second and third generation, raising questions on the potential impact of unfolding diversity by migration background on fertility trends in Europe. Life course research has identified a large number of mechanisms and clocks that shape patterns of family formation in migrant populations, but the translation of such micro-level (inter)actions into macro-level population outcomes remains a key challenge. Using population-wide longitudinal microdata from Belgian registers, we use a multistate discrete-time hazard model of entry into parenthood and parity progression that simultaneously considers conventional determinants of family formation (e.g. age, education, parity, time since index birth), migration-specific factors (origin group, migrant generation, age and parity at migration, duration of residence), while additionally incorporating unobserved heterogeneity that shapes transitions over the life course. We subsequently feed parameter estimates and variance estimates into a dynamic microsimulation model that allows to quantify the sensitivity of macro-level demographic trends in timing and quantum of order-specific fertility to unfolding diversity by migration background and contrasting migration scenarios.
Read MoreModelling cancer incidences and mortality in the Austrian population using dynamic microsimulation
Population projections indicate that by 2045, the Austrian population aged 65 and older will increase by approximately 47% compared to 2023. Since the likelihood of a cancer diagnosis increases with age, a corresponding rise in cancer cases is expected. To address this and support evidence-based decision-making, a model has been developed on behalf of the Ministry of Health to project cancer incidence, prevalence, and mortality within the population up to the year 2045. Our cancer projection model builds on the microsimulation model used by Statistics Austria for official population projections (Pohl et al, 2025). It introduces a new module for calculating cancer diagnoses and refines existing ones, such as the module for calculating mortality. A key advantage of microsimulation is its ability to account for individual characteristics, allowing factors such as existing diagnoses to influence future disease states and determine cause specific mortality outcomes. In addition, microsimulation offers the possibility of further developing the model in the future, e.g. through extensions such as the consideration of risk factors, as is already done in well-known microsimulation models such as OncoSim. (Ruan et al., 2023). The model parameters are calculated using administrative register data, including the Central Population Register and Cause of Death Statistics, linked with the National Cancer Register – enabling detailed tracking of individual life histories.
Read MorePopulation Ageing Trajectories in the United Kingdom: A Microsimulation Approach
Population ageing in the United Kingdom is shaped by the interaction of multiple demographic processes, including longevity improvements, fertility dynamics, and migration flows. This paper presents ongoing work using SimPaths to study plausible population ageing paths in the UK from a life-course perspective. The analysis models individual-level demographic transitions, including age- and sex-specific mortality, fertility behaviour, and migration. Particular attention is given to immigration, distinguishing age at arrival, cohort replacement effects, and heterogeneity in demographic characteristics between migrant and native-born populations. The framework allows population ageing to emerge endogenously from cohort size, survival, and population composition. We outline a set of counterfactual scenarios that vary assumptions on longevity improvements, fertility patterns, and migration regimes. Planned simulations will compare resulting population age structures, cohort distributions, and old-age dependency measures across alternative demographic trajectories. By using microsimulation to decompose population ageing into its underlying demographic mechanisms, the analysis provides a structured basis for refining longer-term research on demographic change in the UK and for identifying which population dynamics are most influential for future ageing trajectories.
Read MorePopulations remember: projecting the intergenerational consequences of heat extremes
Extreme heat events cause substantial excess mortality, yet their long-term demographic consequences extend far beyond immediate death counts. Each heatwave creates demographic memory—the cascading effects of lost individuals who would have reproduced, aged, and shaped future population structures. In this work, I will develop a microsimulation framework to quantify how a single extreme heat event reshapes population trajectories over subsequent decades, comparing outcomes with and without the heatwave to isolate its lasting demographic imprint.
Read MoreProjecting Demand for Senior Day-Care Facilities in Slovakia
Population ageing represents one of the most significant long-term challenges for social and health care systems in Europe, with powerful implications for long-term care infrastructure. In Slovakia, demographic ageing is expected to intensify markedly over the coming decades, generating substantial pressure on the capacity and spatial distribution of residential care facilities for older persons. This paper aims to quantify the future demand for residential senior day-care facilities using the Slovak Labour Microsimulation Model (SLAMM). The analysis employs a dynamic microsimulation approach that models individual life-course transitions related to ageing, household structure, health status, and care dependency. Based on demographic projections of the Slovak population, the model simulates the evolution of the senior population and estimates the number of individuals requiring institutional or semi-institutional care services. The analysis is conducted at the district (LAU 1) level, allowing for the identification of significant regional disparities in both demographic ageing and projected care needs. The primary output of the model is a district-level forecast of demand for residential day-care facilities for seniors over the medium- and long-term horizon. Building on these demand estimates, the paper further quantifies the investment costs associated with expanding care infrastructure. Using unit cost estimates for the construction and capacity expansion of senior care facilities, the study derives projected capital expenditure requirements necessary to meet future demand under different demographic scenarios. The results provide a comprehensive picture of how population ageing will translate into spatially differentiated demand for senior care services in Slovakia. By linking microsimulation-based demand projections with infrastructure cost estimates, the paper offers an integrated analytical framework that supports evidence-based planning of long-term care capacity. The findings are particularly relevant for policymakers and regional authorities responsible for social service provision, as they highlight districts facing the most significant future capacity gaps and investment needs. Overall, the study demonstrates the usefulness of microsimulation modelling as a tool for strategic planning in the area of ageing and long-term care, enabling policymakers to anticipate demographic pressures and to design more efficient and equitable infrastructure investment strategies.
Read MoreRecent developments of the SimPaths dynamic microsimulation framework
SimPaths is an open-source framework for modelling individual and household life course events, jointly developed at the Centre for Microsimulation and Policy Analysis and the University of Glasgow (Bronka et al., 2025). The framework is designed to project life histories through time, building up a detailed picture of career paths, family (inter)relations, health, and financial circumstances. The modular nature of the SimPaths framework is designed to facilitate analysis of alternative assumptions concerning the tax and benefit system, sensitivity to parameter estimates and alternative approaches for projecting labour/leisure and consumption/savings decisions. SimPaths builds upon standardised assumptions and data sources, which facilitates adaptation to alternative countries.
Read MoreThe future of long-term care in Europe. A microsimulation analysis of potential demand based on benefit eligibility rules
European long-term care (LTC) systems face mounting sustainability pressures as population ageing increases the number of older adults living with functional and cognitive limitations. Yet projections of future LTC needs often rely on simplified “need” definitions (e.g., at least one ADL/iADL limitation), overlooking a critical institutional determinant of public expenditure: eligibility rules. Access to publicly funded LTC is not automatic; it is regulated by national (and in some cases regional) legislation that combines multiple vulnerability dimensions—limitations in activities of daily living (ADL), instrumental ADL (iADL), cognition, behavioural issues, and medical needs—into non-linear thresholds for benefit entitlement. Because these rules differ markedly across Europe, they can generate substantially different trajectories of potential demand for publicly financed LTC even under identical demographic and epidemiological trends. This study investigates how the heterogeneity of LTC eligibility criteria shapes the evolution of potential demand for formal domiciliary LTC across European countries in the coming decades. We use longitudinal microdata from the Survey of Health, Ageing and Retirement in Europe (SHARE), Waves 1–9 to operationalize country-specific eligibility rules. Using SHARE’s information on ADL/iADL limitations, mobility constraints, depression symptoms, and cognitive impairment, we construct harmonized indicators of “objective vulnerability” consistent with the assessment-of-need frameworks embedded in legislation. These eligibility indicators are then embedded in a dynamic microsimulation model, the EU-FEM (the SHARE-based version of the Future Elderly Model), which simulates individual life courses through a first-order Markov Monte Carlo process. Transition models generate probabilities of changes in health and functional status over time, allowing heterogeneous trajectories by age, risk factors, and baseline conditions, while the simulated population evolves by ageing and cohort replacement. We produce projections of the population-level prevalence of eligibility for publicly funded domiciliary LTC—interpreted as potential demand—under a baseline “no policy change” scenario. We then conduct counterfactual exercises to disentangle the role of rules versus epidemiology: (i) applying alternative countries’ eligibility rules to the same underlying population trajectories; (ii) simulating a synthetic “single-country” setting to isolate institutional effects; and (iii) evaluating stylized healthy-ageing interventions that reduce the incidence of selected physical and mental limitations by 25% among individuals aged 65–75. The simulations highlight that eligibility-rule heterogeneity translates into markedly different projected pathways of potential LTC demand across Europe. Moreover, the same healthy-ageing intervention can yield very different reductions in projected eligibility depending on which functional domains are targeted and how each country’s rules weight physical, cognitive, and mental limitations. These findings imply that cross-country comparisons of future LTC burdens—and evaluations of prevention-oriented strategies—must explicitly account for institutional eligibility design. Ongoing work extends the framework by incorporating newer SHARE waves, improving harmonization with broader international platforms, and translating projected eligibility into cost trajectories of potential demand.
Read MoreThe Impact of Demographic Change on Spousal Caregiving and Future Gaps in Long-term Care: Microsimulation Projections for Austria and Italy
As populations age, the sustainability of long-term care systems increasingly depends on the availability of informal care, particularly from partners. This paper addresses the question of how much care we may expect partners to provide in the future by projecting demand for long-term care (LTC), the care supply mix based on current patterns, and the resulting care gaps up to 2070. Using a comparative dynamic microsimulation model, we contrast the results for Austria and Italy, two countries at very different stages in the ageing process and with pronounced institutional differences. Our results suggest that delayed widowhood due to improvements in mortality is a mitigating factor for the increased need for formal care in ageing societies, although it can only offset this increase to a limited extent. Even under optimistic assumptions, potential care gaps substantially increase in both countries, primarily due to demographic change. The size of these gaps is influenced by institutional settings, partnership patterns and gains in longevity, but no scenario reverses the overall upward trend. These findings emphasize the need for comprehensive LTC reforms that extend beyond merely promoting informal care and highlight the necessity for substantial investment in formal care infrastructure.
Read MoreUse of Microsimulation Methods to Assess Nutrition-associated Health Outcomes of Climate Change in Northwest Kenya
In the arid and semi-arid lands of northwest Kenya, climate change threatens to compound existing disparities in agricultural activities and health infrastructure and exacerbate food insecurity and malnutrition. To estimate the distribution of nutrition-associated health outcomes and assess projected disease burdens under climate change scenarios, a microsimulation model was combined with health impact assessment methods. A synthetic population covering Turkana, Samburu, and Laikipia counties was generated from census data and a survey conducted in the study region in 2025 provided socioeconomic attributes and baseline dietary intake data. Population growth estimates were obtained from the national statistics authority and forecasts of future edible food availability were estimated up to 2050 from a validated open-source agricultural land-use model. Relative risks of nutrition-associated health outcomes were simulated at the individual-level using standard exposure-response functions at baseline and then at five-year intervals under four representative concentration pathways. The attributable burden in disability-adjusted life years was then estimated to generate the projected morbidity burden in demographic groups. This work expands on an earlier microsimulation model framework developed to assess policies to promote the use of clean cooking fuels on individual exposure to ambient and household air pollution emissions and associated gender-specific mortality in three densely populated Kenyan municipalities. With this additional iteration, we demonstrate how geographic- and hazard-specific assessments of disease burdens in rural and urban populations may contribute toward an improved understanding of differential climate vulnerability in Kenya.
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