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| 정책 시나리오 분석× | 확률적 시나리오 분석× | |
|---|---|---|
| 분야 | 시뮬레이션 | 시뮬레이션 |
| 계열 | Process / pipeline | Process / pipeline |
| 기원 연도≠ | 1967–1990s | 1955–1980s |
| 창시자≠ | Kahn, H. & Wiener, A. J. (seminal); adapted for policy by RAND Corporation and OECD | Dantzig, G. B.; Birge, J. R.; and others in stochastic programming tradition |
| 유형≠ | Qualitative-quantitative hybrid scenario method | Probabilistic scenario enumeration and evaluation |
| 원전≠ | 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 ↗ | Birge, J. R., Louveaux, F. (2011). Introduction to Stochastic Programming (2nd ed.). Springer. ISBN: 9781461402374 |
| 별칭 | PSA, Policy Scenarios, Policy Impact Scenario Analysis, Counterfactual Policy Analysis | Probabilistic Scenario Analysis, SSA, Stochastic What-If Analysis, Monte Carlo Scenario Analysis |
| 관련≠ | 5 | 4 |
| 요약≠ | 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. | Stochastic Scenario Analysis evaluates a system or decision across multiple explicitly defined scenarios, each assigned a probability of occurrence. Unlike deterministic scenario analysis, it propagates uncertainty through probability distributions and computes expected outcomes, variance, and risk metrics across the scenario space, giving decision-makers a structured view of what could happen and how likely each outcome is. |
| ScholarGate데이터셋 ↗ |
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