Modelling demographic changes using simulation: Supportive analyses for socioeconomic studies

Mielczarek, Bożena; Zabawa, Jacek

doi:10.1016/j.seps.2020.100938

Cited by 11 publications

(3 citation statements)

References 27 publications

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“…However, the variables will change over time, which can be embedded in SDM studies in possible scenarios. Among the macro trends in the country, demographic trends are the issues used in many social and economic studies in education, healthcare, the labor market, and long-term services (such as pension policies, urban development, and social welfare) [ 38 ]. The population is one of the most important factors that should be considered in planning the capacity of hospital beds.…”

Section: Discussionmentioning

confidence: 99%

Development of a model for predicting hospital beds shortage and optimal policies using system dynamics approach

Najibi

Seyedi

Farhadi³

et al. 2022

BMC Health Serv Res

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Background Policymakers use simulation-based models to improve system feedback and model the reality of the problems in the system. This study uses the system dynamics approach to provide a model for predicting hospital bed shortages and determine the optimal policy in Shiraz, Southern Iran. Methods This study was designed based on Sterman's system dynamic modeling (SDM) process. Firstly, we determined the main variables affecting bed distribution using a mixed qualitative and quantitative study which includes scoping review, expert panel, Delphi, and DANP. Then, dynamic hypotheses were designed. Subsequently, we held several expert panels for designing the causal and stock-flow models, formulating and testing a simulation model, as well as developing various scenarios and policies. Results Dynamic modeling process resulted in four scenarios. All of the scenarios predicted a shortage of national hospital beds over a 20-year time horizon. Then, four policies were developed based on the changes in the number of beds and capacity of home care services; finally, the optimal policy was determined. Conclusions Due to the high cost of setting up hospital beds, developing and supporting cost-effective home care services, strengthening the insurance coverage of these services, and improving the quantity and quality of community care, considering the real needs of the community could be considered as an optimal option for the future of the city.

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Section: Discussionmentioning

confidence: 99%

Development of a model for predicting hospital beds shortage and optimal policies using system dynamics approach

Najibi

Seyedi

Farhadi³

et al. 2022

BMC Health Serv Res

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“…The New Territorial Agenda of the European Union stimulates debates that decision-making at local level will affect overall success in regional development and this success will depend on population forecasts (e.g., EU2020. de, 2020;Dr Cormac Walsh Research and Consulting, 2020;Mielczarek & Zabawa, 2021;Park & Heim LaFrombois, 2019). Population forecasts may be obtained from statistical databases such OECD (OECD.Stat, 2021), Eurostat (Eurostat, 2021c) etc.…”

Section: Discussionmentioning

confidence: 99%

Population Forecast with Focus on Emigration: Scenarios for the Case of Peripheral Region

Homutiņins

Šipilova

Aļeksejeva

2021

EJSD

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Sustainable decision-making and policies for regional development need clear understanding of future trends in population change. Emigration as one of the core factors of population change causes the greatest uncertainty in the demographic forecasts. Population change due to emigration is bright especially in peripheral regions what strengthens their unfavourable socio-economic conditions. Within the present study, the authors forecast population change due to emigration in peripheral region with high emigration rates. The authors offer three scenarios – current, half of current, and zero emigration, which demonstrate how differentiated population change due to emigration may be in case of different suppositions. Such approach focuses on the issue at local level. For numerical expression of population change, the authors apply simulation model based on system dynamics methods. Forecast results of future population change due to emigration in each scenario may be as a basis for timely inclusion of issues in regional development policies.

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“…Interest in the application of agent-based modeling and microsimulation methodologies in demographic research and projections has grown in recent years (Billari & Prskawetz, 2012; Hannappel et al, 2012; Jager & Janssen, 2003; Mielczarek & Zabawa, 2021; Silverman, 2018; Wildman et al, 2021). The research presented here is part of an ongoing project that seeks to model multiple religious characteristics and behaviors over a long span of time (1900–2100) and in multiple countries (including Norway) using a simulation model that operates with a nationally representative population of agents.…”

Section: Introductionmentioning

confidence: 99%

Adapting Cohort-Component Methods to a Microsimulation: A case study

Puga-Gonzalez

Bacon²,

Voas

et al. 2022

Social Science Computer Review

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Social scientists generally take United Nations (UN) population projections as the baseline when considering the potential impact of any changes that could affect fertility, mortality or migration, and the UN typically does projections using the cohort-component method (CCM). The CCM technique is computationally simple and familiar to demographers. However, in order to avoid the exponential expansion of complexity as new dimensions of individual difference are added to projections, and to understand the sensitivity of projections to specific conditions, agent-based microsimulations are a better option. CCMs can mask hidden assumptions that are surfaced by the construction of microsimulations, and varying such assumptions can lead to quite different projections. CCM models are naturally the strongest form of validation for population projection microsimulations but there are many complexities and difficulties associated with matching microsimulation projections and CCM projections. Here, we describe our efforts to tackle these challenges as we validated a microsimulation for Norway by replicating a UN CCM projection. This provides guidance for other simulationists who seek to use CCMs to validate microsimulations. More importantly, it demonstrates the value of microsimulations for surfacing assumptions that frequently lie hidden, and thus unevaluated, within CCM projections.

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Modelling demographic changes using simulation: Supportive analyses for socioeconomic studies

Cited by 11 publications

References 27 publications

Development of a model for predicting hospital beds shortage and optimal policies using system dynamics approach

Development of a model for predicting hospital beds shortage and optimal policies using system dynamics approach

Population Forecast with Focus on Emigration: Scenarios for the Case of Peripheral Region

Adapting Cohort-Component Methods to a Microsimulation: A case study

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