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Microsimulation is a technique that uses the capacity of modern computers to make microunits act and interact in such a way that it is possible to aggregate to the level of interest. A microsimulation model can be seen as a set of rules, which operates on a sample of microunits such as individuals, households, and firms. Each microunit is defined and characterized by a set of properties (variables) and as the model is simulated these properties are updated for each and every microunit. The model might simply be a set of deterministic rules such as the income tax rules of a country operating on a sample of taxpayers, and used to compute the distribution of after-tax income, the aggregate income tax revenue, or other fiscal entities of interest. But the model could also include behavioral assumptions usually formulated as stochastic models. Examples are fertility models, models for household formation and dissolution, labor supply, and mobility.

It is not easy to get a long perspective on the distribution of wealth in Sweden because there is no single data source that gives a consistent view for a long period of time. The early estimates of the distribution of wealth were based on the concept of tax-assessed wealth which is the basis of the wealth tax. This definition has the disadvantage of not including assets that were not taxed, and no or very unreliable data were given for the majority of the tax payers who were below the taxation threshold. Furthermore, this variable was defined for individuals and for jointly taxed individuals, but no economically meaningful household concept was available. Register data have since then improved, in particular after the late 1990s when data became available directly from banks, brokers, and insurance companies without the filtering of the tax payers. The problem with the household definition remains, but in SESIM we have made corrections to get a useful definition (see Chapter 3). A relatively large survey (HEK) run by Statistics Sweden which combines survey information about the household with register data on assets estimates the median household wealth to 156000 SEK in 1999 and 197000 SEK in 2003.² The latter estimate is in the 1999 price level.³ These estimates apply to all households independent of age. As will be shown below, the level of wealth depends very much on age.

The challenge of an ageing population is a major concern to policymakers and researchers all over the world. As evident in Figure 1, the percentage of people aged 60 and above will increase substantially between 2000 and 2050 in all parts of the world. Europe has the highest proportion; only Japan has a similar age structure. The already high proportion of older people in Europe is expected to rise to an even higher level by 2050, from currently 19 percent to an estimated 34 percent.

Thus, this volume reports on our empirical studies, our model development, and the results of our scenario simulations. It further presents our experience from the micro-simulation approach and discusses the results of our simulations.

Since SESIM is of a fundamental importance for this analysis, we also give a short presentation of the income-generating mechanisms in the model, focusing on earnings and income from capital.

The predicted increase in the population share of elderly in Sweden is rather modest compared to some of the central and south European countries. The share of 65+ will, in our base scenario, increase from 17.5 to 23.9 percent in the period 2000–2040. Yet, this implies a major increase in the number of elderly. The number of 65+ will increase by 58 percent. The very old and care intensive group 80+ will increase even more, by 75 percent, and their share of the population will increase from 5.1 to 7.9 percent in 40 years. This is likely to put an increased pressure on the political system to match the expected increased demand for health care and social care by an increased supply. In some countries, the increase in the number of elderly will become balanced by a decrease in the number of children, and thus a natural reallocation of resources from children to elderly is possible. This is, according to our simulations, not the case in Sweden. The population share of those below 18 will stay rather stable between 21 and 22 percent.

To allow for an improved health progression for the elderly, we adjusted the health index for those aged 40–90 proportionally to their age minus 40 and the calendar year minus 2000 in such a way that a 90-year-old person in 2040 will have the same health as an 80 years old in the base scenario. This implies that the improvement in health comes gradually and is largest for the oldest.