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Introduction to SMILE

SMILE forecasts life-cycle for all individuals in the Danish population, which allows for a much higher level of detail than is possible in the DREAM-group’s other models.

Objective

The microsimulation model, SMILE, has been developed to forecast and analyse the long-run developments in demographics, household relocation patterns, labour market affiliation, education level, income, pensions as well as housing demand. An essential property of a microsimulation model, and indeed SMILE, is that it is based on individuals rather than groups of individuals. This property makes it possible to analyse individual life cycles and to calculate distributions rather than averages of income, pension, etc.

Description

SMILE is a dynamic microsimulation model that forecasts and analyses the life cycles of the Danish population on an individual-specific level. The model uses register data which means that the initial population represents the actual Danish population on an individual level. Each individual has a wide array of variables that describe characteristics such as education, labour market status, family status, municipality of residence, housing characteristics, etc.

Every individual in the population are subjected to a variety of probabilistic events each year that could for example be death, moving, enrolling in a new education, or a change in their labour market status. If the event is considered to occur, the individual moves to a new condition. On the basis of these events, a life cycle is formed for all individuals.

Read more about microsimulation

Application

SMILE has many potential applications. It is possible to analyse life cycles (e.g. pension via pension accumulated payments or health records), forecast income distributions and utilise interrelationships in a family (such as educational behaviour depending plausibly on parent’s educational level). In the follow links there are more examples of analysis using SMILE regarding expectations of:

Development in housing demand in Danish municipalities (in Danish)

Development in population income distribution (in Danish)

Accumulation of pension wealth (in Danish)

Background

SMILE has been under development since 2010 where it was first used to forecast household demand in Denmark. The model has since been developed further and has gradually become very extensive. As a result, it can now provide insight into future developments in the Danish population as described by a wide array of demographic characteristics such as family structure, education choice, socioeconomic status, income, savings and wealth, moving patterns and housing choices.

Underlying Theory

Overall, the projection in SMILE is determined by estimated behavioural patterns that, via Monte Carlo simulations, determine the behaviour of model agents, i.e. individuals and families. The aim is that the selection of algorithms used to estimate the transition probabilities are data driven and are selected by using cross-validation. The development of the model is also in part a reflection of the experience of the researchers themselves. The experience-driven model development primarily reveals itself in the selection of estimation period, relevant data and the selection of relevant algorithms to calculate transition probabilities.

Other important methods in microsimulation are alignment, i.e. adapting the model to the development of, for example, the population and the workforce from other projections and matching individuals to families.

Read more about the structure of SMILE