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This paper investigates the use of dynamic microsimulation (DM) models and the application of Monte Carlo (MC) simulation as an uncertainty analysis (UA) technique in socio-economic policy analysis. Based on a structured review of 44 studies, the analysis identifies key shortcomings in how uncertainty is addressed in existing modeling practices and related reporting of probabilistic outcomes. Key findings reveal also a lack of standardized guidelines for validating simulation results, as well as a use of updated data and finer temporal resolution in models. The paper advocates for a methodological shift toward more agile, transparent, and frequently updated models that can better support timely, evidence-based policymaking. Establishing common standards for UA and related reporting would enhance both the interpretability and policy relevance of DM-based research.

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Uncertainty Analysis in Socio-economic Dynamic Microsimulation Models: A Literature Review

  • 会议论文

  • 发表日期：

    2026年

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  • Miia Rissanen,
  • Jyrki Savolainen

摘要

This paper investigates the use of dynamic microsimulation (DM) models and the application of Monte Carlo (MC) simulation as an uncertainty analysis (UA) technique in socio-economic policy analysis. Based on a structured review of 44 studies, the analysis identifies key shortcomings in how uncertainty is addressed in existing modeling practices and related reporting of probabilistic outcomes. Key findings reveal also a lack of standardized guidelines for validating simulation results, as well as a use of updated data and finer temporal resolution in models. The paper advocates for a methodological shift toward more agile, transparent, and frequently updated models that can better support timely, evidence-based policymaking. Establishing common standards for UA and related reporting would enhance both the interpretability and policy relevance of DM-based research.