Details of the modelling approach to health spending (continued)

Source: Treasury

Based on history, the average annual residual growth factor over the period since 1950 is 1.2% (for unit income elasticity) or 1.0% (when income elasticity is equal to 1.16). Note that in the early 1980s, real health spending growth slowed, forcing the residual to be negative. For the projection period, the paper assumes an income elasticity of 1.0, but also runs a scenario for 1.16. Note that a higher estimate for the income elasticity requires a smaller estimate for the residual. The residual captures the effect of technology, preferences, and so on.

Over the projection period to 2050, we derive the growth of personal health spending from three effects:

• the effects of rising population and the changing mix of ages are derived by applying the cost weights to the demographic projection[34]
• the growth due to increases in income, and
• the residual growth factor.

In other words,

where E is health spending, cw = growth of ∑_acost weights_a x pop groups_a (summing over ages and genders, a), ε = income elasticity of demand for health services, g = nominal GDP growth (as a proxy for income), and r = the residual growth factor, tapering down to 0 in 2050.

By 2050 the life expectancy of a 65-year-old is five years more than it is now. Effectively we assume that a 65-year-old in 2050 has the same health status - and will require the same public spending - as a 60-year-old does now. The cost curves are therefore moved out to capture this compression of morbidity.

This equation differs from the standard LTFM equation in that it has the residual growth term and it tracks nominal GDP growth (as we are assuming that ε = 1 in the base case). Aside from the labour force effects in GDP growth, the major differences are the residual growth factor and the shifts to the right in the cost profiles.

For long-term care (proxied here by disability support, which includes home support, residential care and equipment), following Bryant, Teasdale et al., we assume that the incidence of disability decreases over time (paralleling the reduction in personal health costs with rising longevity). The provision of informal care is negatively related to labour participation of 50-64 year olds to capture choices between the provision of care to a relative at home and a job in the labour market.

where E = public spending on disability support, cw is the growth of cost weights times the age and gender groups, g = growth of nominal GDP, r = growth of the residual, which tapers down to 0 in 2050, h = growth in the participation of the 50-64 age group and p = is the rate of change in the prevalence of disability (falling by 0.5% a year).

The pure ageing effect (where we look at the effect of the changing mix in the age structure of the population – the first bracketed term in the above equations) contributes a rising amount to the growth of health expenditure until it reaches 1.5% in the mid-2020s and then it slows to 0.4% by 2050.

We illustrate in Figure 24 the effect of changing the income elasticity from the base level of 1 (with the accompanying residual 1.2 tapering to 0 in 2050 – the solid black line) to 1.16 (where the residual growth falls from 1.0 to 0 in 2050 – dotted line).

The figure shows that the effects of changes in the elasticity and residual are not offsetting: the elasticity change has more effect than the residual change. The chart also shows the sensitivity of the assumption about reductions in the prevalence of disability in the population. The base case assumes disability rates fall by 0.5% a year. The dashed line reflects the assumption that disability rates do not change.

Figure 24: The GDP share of Core Crown Health spending continues to grow

Source: The Treasury