Microsimulation (a.k.a. microanalytic simulation) is a research area in applied econometrics. It tries to simulate the behaviour of individuals over time. Microsimulation can either be dynamic or static. If it is dynamic the behaviour of people changes over time, whereas in the static case a constant behaviour is assumed. There are several microsimulation models for taxation, pension etc. run by governmental bodies or academics. One example is Pensim2 which dynamically simulates pension income for the next 50 years in the UK. Euromod is a static microsimulation model for 15 EU states.
According to the International Microsimulation Association, the microsimulation is a modelling technique that operates at the level of individual units such as persons, households, vehicles or firms. Within the model each unit is represented by a record containing a unique identifier and a set of associated attributes – e.g. a list of persons with known age, sex, marital and employment status; or a list of vehicles with known origins, destinations and operational characteristics. A set of rules (transition probabilities) are then applied to these units leading to simulated changes in state and behaviour. These rules may be deterministic (probability = 1), such as changes in tax liability resulting from changes in tax regulations, or stochastic (probability <=1), such as chance of dying, marrying, giving birth or moving within a given time period. In either case the result is an estimate of the outcomes of applying these rules, possibly over many time steps, including both total overall aggregate change and, crucially, the distributional nature of any change.
Microsimulation is also a term used in traffic modelling and is typified by software packages such as VISSIM, CORSIM (and daughter models DYNACAN (Canada) and POLISIM (United States)), SESIM (Sweden) Transims, Cube Dynasim, LISA+, Quadstone Paramics, SiAS Paramics, Simtraffic and Aimsun. Empirical modelling software such as LINSIG, TRANSYT or aaSIDRA represent a different class of models based on deterministic methods.
Traffic microsimulation models simulate the behaviour of individual vehicles within a predefined road network and are used to predict the likely impact of changes in traffic patterns resulting from changes to traffic flow or from changes to the physical environment.
Microsimulation has its greatest strength in modelling congested road networks due to its ability to simulate queueing conditions. Microsimulation models will continue to provide results at high degrees of saturation, up to the point of absolute gridlock. This capability makes these type of models very useful to analized traffic operations in urban areas and city centers, including interchanges, roundabouts, unsignalized and signalized intersections, signal coordinated corridors, and area networks. Microsimulation also reflects even relatively small changes in the physical environment such as the narrowing of lanes or the relocation of junction stop lines.
In recent years, microsimulation modelling has gained attention in its ability to visually represent predicted traffic behaviour through 3D animation, enabling laypeople such as politicians and the general public to fully appreciate the impacts of a proposed scheme. Further advances are being made in this area with the merging of microsimulation model data with cinematic quality 3D animation.
In health sciences Microsimulation refers to a type of simulation modeling that generates individual life histories. The technique is used when 'stock-and-flow' type modeling of proportions (macrosimulation) of the population cannot sufficiently describe the system of interest. This type of modeling does not necessarily involve interaction between individuals (as described above) and in that case can generate individuals independently of each other, and can easily work with continuous time instead of discrete time steps. Several examples of microsimulation models in health sciences have been brought together in the U.S. National Cancer Institute's CISNET program (http://cisnet.cancer.gov/).