方法对比

	离散选择模拟	个体模拟	蒙特卡洛模拟
领域	仿真	仿真	决策
方法族	Process / pipeline	Process / pipeline	MCDM
起源年份	1974 (McFadden's Nobel-cited logit); simulation extensions throughout 1990s–2000s	1957	1949
提出者	Daniel McFadden (random utility theory); Kenneth Train (simulation methods)	Guy Orcutt (concept, 1957); modern tax-transfer frameworks developed through EUROMOD and related projects	Metropolis, N., Ulam, S.
类型	Discrete choice modelling with Monte Carlo simulation	Policy simulation / computational social science	Robustness wrapper — Monte Carlo uncertainty propagation
开创性文献	Train, K.E. (2009). Discrete Choice Methods with Simulation (2nd ed.). Cambridge University Press.	O'Donoghue, C. (Ed.) (2014). Handbook of Microsimulation Modelling. Emerald.	Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association
别名	stated preference simulation, SP simulation, revealed preference modelling, Ayrık Seçim Simülasyonu (Stated Preference / SP Simulation)	Mikrosimülasyon, micro-simulation, policy microsimulation	—
相关	5	5	0
摘要	Discrete choice simulation is a behavioural modelling method — grounded in random utility theory formalised by Daniel McFadden in the 1970s and extended to simulation-based estimation by Kenneth Train — that estimates how individuals choose among mutually exclusive alternatives and then uses those estimated preference parameters to forecast how choice shares would shift under hypothetical policy or market scenarios. It is the dominant quantitative tool in transport demand analysis, health economics, environmental valuation, and marketing research.	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.	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.