Comparer des méthodes

	Modèle de Markov stochastique	Microsimulation
Domaine	Simulation	Simulation
Famille	Process / pipeline	Process / pipeline
Année d'origine	1993	1957
Auteur d'origine	Markov, A. A. (probabilistic extension developed by Sonnenberg & Beck and others)	Guy Orcutt (concept, 1957); modern tax-transfer frameworks developed through EUROMOD and related projects
Type	Probabilistic state-transition model with Monte Carlo uncertainty propagation	Policy simulation / computational social science
Source fondatrice	Sonnenberg, F. A., & Beck, J. R. (1993). Markov models in medical decision making: A practical guide. Medical Decision Making, 13(4), 322–338.	O'Donoghue, C. (Ed.) (2014). Handbook of Microsimulation Modelling. Emerald.
Alias	Probabilistic Markov Model, Stochastic Markov Chain, SMM, Monte Carlo Markov Model	Mikrosimülasyon, micro-simulation, policy microsimulation
Apparentées	6	5
Résumé	A Stochastic Markov Model is a simulation technique that represents a system as a set of mutually exclusive health or decision states, moves a cohort (or individual agents) through those states using probabilistically sampled transition parameters, and aggregates outcomes across thousands of Monte Carlo iterations to produce full probability distributions over costs, outcomes, or rankings rather than single point estimates.	Microsimulation is a computational method that simulates policy effects by operating directly on a population of individual micro-units — households, firms, patients — and applying rules to each unit according to its own demographic, economic, and behavioural characteristics. Developed conceptually by Guy Orcutt in 1957, it has become the standard tool for evaluating tax reform, pension systems, and health policy before implementation.