Introduction to microsimulation
The current version of SMILE forecasts demography, household structure, education level, socioeconomic characteristics, housing demand, income, taxation, public benefits, and labour market pensions.
SMILE is a microsimulation model. A defining feature of such models is that they are based on individual “entities” which can be either individual persons or families.
The model is based on an initial population where each individual is described by a number of characteristics including gender, age, education, family type, labour market status, income level etc. It is also registered which family an individual belongs to, and which type of dwelling the family occupies. The simulation forecasts the initial population from period to period where each period corresponds to one year. In the process the characteristics of each individual are updated each period. The updating is achieved by “exposing” individuals and households to a number of possible events. For an individual, possible events include to begin or finish an education, shift in income level, and of course to die. For a family, examples of events include marriage, divorce, and to move to another dwelling. In order to determine whether or not a specific event is realized, each person is “asked” a question to which the answer is either “yes” or “no”. The questions depend on the characteristics of the person. A typical question would be to ask a 30 year old male in a singleadult household whether he will find a partner during the following year.
Answers to these questions are randomly determined using transitional probabilities which depend on the characteristics of the individual. This is the probability that a specific event takes place during the following year. In the example given above, this is the probability that a single 30 year old male finds a partner during the following year. Transitional probabilities are calculated based on historical observations. If the event is found to take place, the effects of it will be implemented in the model. To continue the example, this requires that a single female also has answered “yes” to the question of whether she will find a partner, and in this case the two individuals will form a couple. In the following period, the male (and the female) will not be asked whether he (or she) will find a partner. However, if the event does not take place, the individuals will be asked the same question in the following period. In this way, it is possible to simulate the remaining life cycle for all individuals in the initial population and thereby form long-run projections.