3.2  Some published models

Table 3 summarizes the main features of some published studies that use the same modelling strategy as we do[3]. For comparison, information on our model is shown at the bottom of the table. The models differ from each other, and from that of Table 2, mainly in the way that they disaggregate the population. Some classify the population only by age and sex, while others add one or more extra dimensions, to capture changes in health status.

Johnston and Teasdale (1999) classify the population by age and sex. Past trends for cost growth are estimated by “back-casting”: by calculating the cost growth that the model suggests would be necessary to reconcile observed population trends with observed expenditure trends. Johnston and Teasdale back-cast over the period 1978-1998, and obtain an average growth rate for underling costs of 0.9% per year. They use a rounded-up figure of 1.0% in their projections. They adopt Treasury’s assumption that labour productivity grows at 1.5% per year. With these assumptions, government health expenditure, as defined in the report, reaches 8.4% of GDP in 2051, compared with 6.5% in 2001. The New Zealand Treasury, in its Long-Term Fiscal Model, and the Australian Treasury, in its Intergenerational Report, use essentially the same methodology as Johnston and Teasdale. Some of the differences in the implementation are described in the table.

*The latest version of the Long-Term Fiscal Model can be downloaded from [http://www.treasury.govt.nz/government/longterm/fiscalmodel]

**A description of the model methodology and results is available at http://www.budget.gov.au/2002-03/bp5/html/index.html.

Note – ‘NA’ denotes ‘not applicable.’

Cutler and Sheiner (1998) were an important source of ideas for our model and use a finer typology than just age and sex. Within each age-sex group, they distinguish between people who are in their last year of life (decedents), and those who are not (survivors). Survivors are further disaggregated by their degree of disability. They are therefore able to relate changes in health expenditure to changes in disability and distance to death. As Section 2.1 argues, disability and distance to death are more fundamental determinants of service use than age.

Jacobzone, Cambois, and Robine (2000) distinguish between people with disabilities and people without, and between those who are in institutions providing long-term care and those who are not. Separate projections are constructed for each of the nine OECD countries in the study. The projections extrapolate forward recent trends in each country’s disability and institutionalization rates. Miller (2001) uses age, sex, and distance to death. His typology by distance to death is very detailed: he distinguishes between people who are less than one year from death, less than two years from death, and so on up to 10 years.