Laurie Brown and Ann Harding (2002)
Social Modelling and Public Policy: Application of Microsimulation Modelling in Australia
Journal of Artificial Societies and Social Simulation
vol. 5, no. 4
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Received: 28-Sep-2002 Published: 31-Oct-2002
Dynamically ageing microsimulation models, on the other hand, involves updating each attribute for each micro-unit for each time interval. Dynamic models are more complicated in that a temporal element is introduced into the modelling. Individuals are aged and stochastically undergo transitions, as well as being subject to modified policy regimes (Halpin 1999; Sauerbier 2002). Dynamic models often start from exactly the same cross-section sample surveys as static models. However, the individuals within the original microdata (the model's cohort) are then progressively moved forward through time. This is achieved by making major life events - such as education and training, labour force participation, family formation and dissolution (marriage, children, separation, divorce), migration, retirement, death etc - happen to each individual, in accordance with the probabilities of such events happening to real people within a particular country. Thus, within a dynamic microsimulation model, the characteristics of each individual are recalculated for each time period. This involves the use of large transition matrices or econometric techniques to determine the various year-to-year shifts. Hence, dynamic microsimulation models are generally much more complex and expensive to build.
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Figure 1. Estimated Percentage Gain in Disposable Income from the Final GST Tax Reform Package (Source: Harding et al 2000) |
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Figure 2. Forecast Superannuation Assets for Women Aged 55 to 64 Years, 2000 to 2030 (Source: Kelly et al. 2001) |
2 Newstart is for unemployed people aged over 21 or people who are temporarily unable to work due to illness, injury or disability.
3 The APMA Model basefile excludes persons (and their families) that have no expenditure on prescribed drugs, and persons living in institutionalised care, for example, hospitals or nursing homes. Prescribed drug usage figures at ages above 70 years, therefore, are likely to be under-estimates.
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