A Portable Dynamic Microsimulation Model for Population, Education and Health Applications in Developing Countries

Spielauer, Martin; Dupriez, Olivier

doi:10.34196/ijm.00205

Cited by 6 publications

(5 citation statements)

References 6 publications

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“…5 In family science, applications range from modelling family and kinship networks (e.g., Wachter 1997;Tomassini and Wolf 2000;Murphy 2004Murphy , 2011Zagheni 2011) and human reproduction and fecundity (Ridley and Sheps 1966) to contraceptive behaviour (Thomas et al 2017). Currently, only a few microsimulations focus on family-building issues, including FAMSIM (Lutz 1997;Spielauer and Vencatasawmy 2001) for the evaluation of family policies, an extension of the MicMac model to mate-matching and couple dynamics (Zinn 2011(Zinn , 2012(Zinn , 2017, and several applications of RiskPaths (Spielauer 2009a(Spielauer , 2009b on the interaction of fertility and union processes (Spielauer, Kostova, and Koytcheva 2007;Bélanger, Morency, and Spielauer 2010;Thomson et al 2012;Spielauer and Dupriez 2017).…”

Section: Microsimulation Of Family Dynamicsmentioning

confidence: 99%

Simulating family life courses: An application for Italy, Great Britain, Norway, and Sweden

Winkler-Dworak¹,

Beaujouan²,

Giulio³

et al. 2021

DemRes

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Section: Microsimulation Of Family Dynamicsmentioning

confidence: 99%

Simulating family life courses: An application for Italy, Great Britain, Norway, and Sweden

Winkler-Dworak¹,

Beaujouan²,

Giulio³

et al. 2021

DemRes

Self Cite

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“…The Technical Panel also stresses the need to model dynamic impacts and what-if scenarios to gain insights on the potential effects of policy changes on macro-economic indicators. Microsimulation allows a more explicit incorporation of theory and policy levers in projections, for example, modeling inter-generational educational dynamics and the analysis of downstream effects of education policy interventions on labor market outcomes (Spielauer and Dupriez, 2019). Microsimulation has proven to be a particularly useful tool to answer 'What if..?'…”

Section: Projecting Labor Force Participationmentioning

confidence: 99%

The Impact of Health and Education on Labor Force Participation in Aging Societies – Projections for the United States and Germany from a Dynamic Microsimulation

et al. 2021

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Using a highly stylized dynamic microsimulation model, we project the labor force of the United States up to the year 2060 and contrast these projections with projections for Germany to assess differential effects on outcomes The projections are consistent with the U S Census Bureau's and Eurostat's demographic projections. Our modeling approach allows to show and quantify how policy changes the future size of the labor force, which we assess with a series of what-if scenarios.Both the US and Germany are expected to undergo demographic aging, but their demographic fundamentals differ starkly. This has strong implications for their labor force developments. According to our microsimulation, the US labor force will, despite population aging, increase by 16.2 percent in the age groups 15 to 74 (corresponding to 25.2 million workers) between 2020 and 2060, while Germany will experience a decline by 10.7 percent (4.4 million workers). In these baseline projections, improvements in the education structure will add about two million persons to the US labor force and about half a million persons to the German labor force by 2060.In the what-if scenarios, we examine the implications of improvements in the educational structure of the population and of policies which address the health impediments for labor force participation. Of the educational scenarios that we evaluate, increasing the number of persons who achieve more than lower education has the strongest positive impact on labor force participation, relative to the number of additional years of schooling implied by the various scenarios. Shifting people from intermediate to higher education levels also increases labor force participation in higher age groups, however, this is partially offset by lock in effects at younger ages.Our projections highlight that improvements in the labor market integration of people with health limitations provide a particularly promising avenue to increase labor force participation rates and thus help to address the challenges posed by demographic aging. If the health gap in participation rates in the United States were similar to that currently observed in Sweden, the labor force in 2060 would be larger by about 14.9 million persons.

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“…Dupriez 52 DYNAMIS-POP is a dynamic micro-simulation model for population and education projections and for the simulation of policies. Adaptation of the model to a specific country only requires adapting a single setup script and simulation module.…”

Section: Authorsmentioning

confidence: 99%

Simulation Framework for Realistic Large-scale Individual-level Data Generation with an Application in the Health Domain

Tikka¹,

Hakanen²,

Saarela³

et al. 2020

Preprint

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We propose a general framework for realistic data generation and simulation of complex systems in the health domain. The main use cases of the framework are predicting the development of risk factors and disease occurrence, evaluating the impact of interventions and policy decisions, and statistical method development. We present the fundamentals of the framework using rigorous mathematical definitions. The framework supports calibration to a real population as well as various manipulations and data collection processes. The freely available open-source implementation in R embraces efficient data structures, parallel computing and fast random number generation which ensure reproducibility and scalability. With the framework it is possible to run daily-level simulations for populations of millions individuals for decades of simulated time. An example on the occurrence of stroke, type 2 diabetes and mortality illustrates the usage of the framework in the Finnish context. In the example, we demonstrate the data-collection functionality by studying the impact of non-participation on the estimated risk models.

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A Portable Dynamic Microsimulation Model for Population, Education and Health Applications in Developing Countries

Cited by 6 publications

References 6 publications

Simulating family life courses: An application for Italy, Great Britain, Norway, and Sweden

Simulating family life courses: An application for Italy, Great Britain, Norway, and Sweden

The Impact of Health and Education on Labor Force Participation in Aging Societies – Projections for the United States and Germany from a Dynamic Microsimulation

Simulation Framework for Realistic Large-scale Individual-level Data Generation with an Application in the Health Domain

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