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Anàlisi dePolítica Escenaris×Simulació Monte Carlo×
CampSimulacióPresa de decisions
FamíliaProcess / pipelineMCDM
Any d'origen1967–1990s1949
Autor originalKahn, H. & Wiener, A. J. (seminal); adapted for policy by RAND Corporation and OECDMetropolis, N., Ulam, S.
TipusQualitative-quantitative hybrid scenario methodRobustness wrapper — Monte Carlo uncertainty propagation
Font seminalSwart, R., Raskin, P., Robinson, J. (2004). The problem of the future: sustainability science and scenario analysis. Global Environmental Change, 14(2), 137–146. DOI ↗Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association DOI ↗
ÀliesPSA, Policy Scenarios, Policy Impact Scenario Analysis, Counterfactual Policy Analysis
Relacionats50
ResumPolicy 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.MONTE-CARLO-SIMULATION (Monte Carlo Simulation — Stochastic uncertainty propagation through MCDM model) is a ranking multi-criteria decision-making (MCDM) method introduced by Metropolis, N., Ulam, S. in 1949. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.
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ScholarGateCompara mètodes: Policy Scenario Analysis · MONTE-CARLO-SIMULATION. Recuperat el 2026-06-18 de https://scholargate.app/ca/compare