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Microsimulation
Microsimulation is the use of computerized analytical tools to perform analysis of activities such as highway traffic flowing through an intersection, financial transactions, or pathogens spreading disease through a population on the granularity level of individuals. Synonyms include microanalytic simulation and microscopic simulation. Microsimulation, with its emphasis on stochastic or rule-based structures, should not be confused with the similar complementary technique of multi-agent simulation, which focuses more on the behaviour of individuals.
For example, a traffic microsimulation model could be used to evaluate the effectiveness of lengthening a turn lane at an intersection, and thus help decide whether it is worth spending money on actually lengthening the lane.
Microsimulation can be distinguished from other types of computer modeling in looking at the interaction of individual units such as people or vehicles. Each unit is treated as an autonomous entity and the interaction of the units is allowed vary depending on stochastic (randomized) parameters. These parameters are intended to represent individual preferences and tendencies. For example, in a traffic model some drivers are cautious and wait for a large gap before turning, while others are aggressive and accept small gaps. Similarly, in a public health model individuals could vary in their resistance to a virus, as well as in personal habits that contribute to the spread of the virus (e.g. how frequently/thoroughly they wash their hands).
The International Microsimulation Association, defines microsimulation as 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 (importantly) the way this change is distributed in the population or location that is being modeled.
In applied econometrics research, microsimulation is used to simulate the behavior of individuals over time. The microsimulation can either be dynamic or static. If it is dynamic the behavior of people changes over time, whereas in the static case a constant behavior is assumed.
There are several microsimulation models for taxation, pensions, and other types of economic and financial activity. These models are typically implemented by government agencies or academics. One example is Pensim2 (a dynamic microsimulation pension model) which dynamically simulates pension income for the next 50 years in the United Kingdom. EUROMOD is a static microsimulation model for 27 European Union states, while SOUTHMOD adopts the same framework for several countries in the Global South. North American microsimulation models include the longitudinal, dynamic microsimulation CORSIM, and daughter models DYNACAN (Canada, terminated June 1, 2009) and POLISIM (United States). The U.S. Department of Health and Human Services uses the static microsimulation Transfer Income Model (TRIM) to understand the potential impacts of changes to tax, transfer, and health programs. A related example that provides spatially detailed microsimulation of urban development is PECAS.
Econometric microsimulation models can be classified into two types:
One of the clearest examples of this distinction is the treatment of marriage within the two types of models. While open models can simply generate an appropriate spouse for the key individual, closed models must, instead, determine which people within its population are likely to marry, and then to match them.
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Microsimulation AI simulator
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Microsimulation
Microsimulation is the use of computerized analytical tools to perform analysis of activities such as highway traffic flowing through an intersection, financial transactions, or pathogens spreading disease through a population on the granularity level of individuals. Synonyms include microanalytic simulation and microscopic simulation. Microsimulation, with its emphasis on stochastic or rule-based structures, should not be confused with the similar complementary technique of multi-agent simulation, which focuses more on the behaviour of individuals.
For example, a traffic microsimulation model could be used to evaluate the effectiveness of lengthening a turn lane at an intersection, and thus help decide whether it is worth spending money on actually lengthening the lane.
Microsimulation can be distinguished from other types of computer modeling in looking at the interaction of individual units such as people or vehicles. Each unit is treated as an autonomous entity and the interaction of the units is allowed vary depending on stochastic (randomized) parameters. These parameters are intended to represent individual preferences and tendencies. For example, in a traffic model some drivers are cautious and wait for a large gap before turning, while others are aggressive and accept small gaps. Similarly, in a public health model individuals could vary in their resistance to a virus, as well as in personal habits that contribute to the spread of the virus (e.g. how frequently/thoroughly they wash their hands).
The International Microsimulation Association, defines microsimulation as 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 (importantly) the way this change is distributed in the population or location that is being modeled.
In applied econometrics research, microsimulation is used to simulate the behavior of individuals over time. The microsimulation can either be dynamic or static. If it is dynamic the behavior of people changes over time, whereas in the static case a constant behavior is assumed.
There are several microsimulation models for taxation, pensions, and other types of economic and financial activity. These models are typically implemented by government agencies or academics. One example is Pensim2 (a dynamic microsimulation pension model) which dynamically simulates pension income for the next 50 years in the United Kingdom. EUROMOD is a static microsimulation model for 27 European Union states, while SOUTHMOD adopts the same framework for several countries in the Global South. North American microsimulation models include the longitudinal, dynamic microsimulation CORSIM, and daughter models DYNACAN (Canada, terminated June 1, 2009) and POLISIM (United States). The U.S. Department of Health and Human Services uses the static microsimulation Transfer Income Model (TRIM) to understand the potential impacts of changes to tax, transfer, and health programs. A related example that provides spatially detailed microsimulation of urban development is PECAS.
Econometric microsimulation models can be classified into two types:
One of the clearest examples of this distinction is the treatment of marriage within the two types of models. While open models can simply generate an appropriate spouse for the key individual, closed models must, instead, determine which people within its population are likely to marry, and then to match them.