The core of micro-simulation has been defined as “a means of modelling real life events by simulating the actions of the individual units that make up the system where the events occur” (Brown and Harding, 2002), and as “computer-simulation of a society in which the population is represented by a large sample of its individual members and their behaviours” (Spielauer, 2011). This has been broadened to encompass its role in policy so that “micro-simulation models are computer programs that simulate aggregate and distributional effects of a policy, by implementing the provisions of the policy on a representative sample of individuals and families, and then summing up the results across individual units using population weights” (Martini & Trivellato, 1997, p. 84).

Micro-simulation operates at the level of individual units, for example children, each possessing a set of associated attributes as a starting point. A set of rules, typically derived from statistical analyses, is then applied in a stochastic manner to each and every individual to simulate changes in state or behaviour. The primary strength of micro-simulation techniques is their use of actual individual-level data, which allows them to reproduce social reality and the intricacy of policy structures. These data can come from various sources, which micro-simulation is able to combine into a cohesive whole. The model can then be used to estimate the outcomes of “what if” scenarios (Brown & Harding, 2002, p. 4).

Spielauer (2011) notes that micro-simulation is certainly the preferred modelling choice in three situations: (1) if population heterogeneity matters and if there are too many possible combinations of considered characteristics to split the population into a manageable number of groups; (2) if behaviours are complex at the macro level but better understood at the micro level; and (3) if individual histories matter, that is, when processes possess memory (Spielauer, 2011, pp. 6-8).

Related terms: Simulation Model


Brown, L, Harding A. (2002). Social modeling and public policy: Application of microsimulation modeling in Australia. Journal of Artificial Societies and Social Simulation 5(4)6.

Martini A, Trivellato U. (1997). The role of survey data in microsimulation models for social policy analysis. Labour, 11(1), 83-112.

Spielauer M. (2011). What is social science microsimulation? Social Science Computer Review, 29(1), 9-20.

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