方法对比
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| 政策情景蒙特卡洛模拟× | 政策情景分析× | |
|---|---|---|
| 领域 | 仿真 | 仿真 |
| 方法族 | Process / pipeline | Process / pipeline |
| 起源年份≠ | 1990s–2000s | 1967–1990s |
| 提出者≠ | Developed within health economics and policy modeling communities; foundational work by Briggs, Claxton, and Sculpher | Kahn, H. & Wiener, A. J. (seminal); adapted for policy by RAND Corporation and OECD |
| 类型≠ | Probabilistic scenario simulation | Qualitative-quantitative hybrid scenario method |
| 开创性文献≠ | Briggs, A. H., Claxton, K., & Sculpher, M. J. (2006). Decision Modelling for Health Economic Evaluation. Oxford University Press. ISBN: 9780198526629 | Swart, R., Raskin, P., Robinson, J. (2004). The problem of the future: sustainability science and scenario analysis. Global Environmental Change, 14(2), 137–146. DOI ↗ |
| 别名 | PS-MCS, Policy MC Simulation, Scenario-Based Monte Carlo, Policy Uncertainty Simulation | PSA, Policy Scenarios, Policy Impact Scenario Analysis, Counterfactual Policy Analysis |
| 相关≠ | 4 | 5 |
| 摘要≠ | Policy Scenario Monte Carlo Simulation combines pre-defined discrete policy scenarios with probabilistic Monte Carlo sampling to quantify uncertainty in outcomes across each scenario. Rather than evaluating a single stochastic model, analysts define two or more policy alternatives and run thousands of Monte Carlo iterations within each, producing probability distributions of outcomes that support evidence-based policy comparison. | Policy Scenario Analysis is a structured method for evaluating how different policy interventions perform across a range of plausible future states. By pairing specific policy levers with alternative scenarios, analysts can assess robustness, trade-offs, and unintended consequences of policy choices before implementation — making it a cornerstone of evidence-based policy design in fields from climate to public health. |
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