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	Multi-Criteria Policy Analysis	नीति परिदृश्य विश्लेषण
क्षेत्र	Public Policy	अनुकरण
परिवार	MCDM	Process / pipeline
उद्भव वर्ष	2002	1967–1990s
प्रवर्तक	Valerie Belton & Theodor Stewart (synthesis); MCDA tradition	Kahn, H. & Wiener, A. J. (seminal); adapted for policy by RAND Corporation and OECD
प्रकार	Multi-criteria decision analysis applied to policy appraisal	Qualitative-quantitative hybrid scenario method
मौलिक स्रोत	Belton, V., & Stewart, T. J. (2002). Multiple Criteria Decision Analysis: An Integrated Approach. Boston: Kluwer Academic Publishers. ISBN: 9780792375050	Swart, R., Raskin, P., Robinson, J. (2004). The problem of the future: sustainability science and scenario analysis. Global Environmental Change, 14(2), 137–146.
उपनाम	Multi-Criteria Analysis for Policy, MCDA Policy Appraisal, MCA in Policy, Multi-Criteria Policy Appraisal	PSA, Policy Scenarios, Policy Impact Scenario Analysis, Counterfactual Policy Analysis
संबंधित	3	5
सारांश	Multi-criteria policy analysis applies multi-criteria decision analysis (MCDA) to appraise and rank policy options against several, often conflicting, objectives that cannot be reduced to a single money metric. Each option is scored on a set of explicit criteria — economic, social, environmental, distributional — the criteria are weighted to reflect their relative importance, and the scores are aggregated into an overall value that ranks the options. Set out comprehensively in Belton and Stewart's 2002 textbook and operationalised for government in the UK's widely used Multi-Criteria Analysis Manual, the approach makes the trade-offs in a policy decision transparent and structured rather than implicit.	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.