Project

Approach:

We develop, solve and implement numerically an intertemporal general equilibrium model with overlapping generations subject to endogenous mortality, the latter depending on individual health care and medical technology. In so doing, we explicitly study a three sector model, where a medical sector (e.g. hospitals) and an R&D sector developing medical technology operate beside a production sector.

We derive from individual choice an age-specific demand for health care as well as its underlying value. Aggregating across cohorts, we show how the total demand for health care translates, via the medical sector, into a demand for medical innovation. We assess the efficiency of the allocation and study how it depends on the competitive and institutional Environment as well as economic and social changes.

Numerical Implementation:

Calibrating the model to US data, we examine numerically how the dynamics are shaped by medical progress, by population change (e.g. exogenous ageing, baby-boom/bust), by climate change (Taiwan data) and by the expansion of health insurance. Our numerical model allows us to trace the out-of-steady-state dynamics.

Key Project Findings:

• Life-saving medical progress leads to an expansion of the demand for health care and an increase in the price for health care, both implying a higher health share in GDP. However, (a) the demand expansion is strongly dampened in general equilibrium owing to the price increase, and (b) for an economy with US-style social security / health insurance, the expansion of the health care sector does not compromise GDP. This is because it leads to an expansion of savings for consumption and for the purchase of more effective health care in old age. The resulting increase in the capital stock more than offsets the decrease in the labour support ratio. See Frankovic et al. (2017)

• In a world in which medical R&D is (at least partially) driven by profits, the expansion of health insurance, as experienced in the US over the time span 1965-2005, induces additional medical innovation. While the increase in health expenditure caused by the expansion of health insurance generates few additional gains in longevity and is, therefore, wasteful for a status-quo path of medical technology, this inefficiency is more than compensated by the welfare gain from the longevity improvement associated with insurance-induced medical innovations. See Frankovic and Kuhn (2018a)

• An economy in which life-saving medical progress is driven by the current market size is subject to a positive intergenerational externality: the gains to future cohorts from medical innovations are not taken into account by contemporary individuals deciding on their consumption of health care. This leads to an undersupply of medical innovation. Health insurance is then generating an offsetting externality: Here it is particularly the elderly who over-consume health care from a static point of view. From a dynamic point of view, however, this is efficient as the young are compensated for the higher health insurance and tax payments in the form of the future benefits from medical innovations. See Frankovic and Kuhn (2018a)

• The growing gap in life expectancy across income and/or education strata can be well explained by the interaction of skill-biased productivity growth in the general economy, leading to divergent incomes, and by skill-biased access to state-of-the-art medical technology. Importantly even if the unskilled enjoy the same access to medical technology, the longevity gap grows, as they are less prone to benefit from medical innovations due to their lower demand for costly health care. See Frankovic and Kuhn (2018b)

• Climate change has an ambivalent impact on health care expenditure. On the one hand, it tends to raise health care expenditure that helps to mitigate the detrimental effects of e.g. heat waves on health. On the other hand, by reducing (i) productivity and income, and (ii) longevity it leads to a reduction in the value of life and, thus, in the willingness to pay for health care as opposed to consumption. Furthermore, the impacts are prone to differ strongly by age, implying that it is important to know both the specificity of the health and productivity impacts of climate change as well as the age structure of the population when seeking to assess the impact on future health expenditures. See Frankovic (2017)

• A baby boom does not only generate the expected peak in aggregated health care expenditures at the point at which the baby boom cohorts are reaching advanced ages with high individual levels of health care spending, but a more complex pattern of peaks and troughs. This includes an early supply driven peak in health care and a late trough in health care spending that stretches beyond the demise of the baby boom cohorts. The latter reflects the lower available income of young post-baby-boom cohorts who are forced to accommodate the high economic dependency of the retired baby boomers. See Frankovic et al. (2016)