It is still an open question whether increasing life expectancy as such causes higher health care expenditures (HCE) in a population. According to the ''red herring'' hypothesis, the positive correlation between age and HCE is exclusively due to the fact that mortality rises with age and a large share of HCE is caused by proximity to death. As a consequence, rising longevity through falling mortality rates may even reduce HCE. However, a weakness of many previous empirical studies is that they use cross-sectional evidence to make inferences on a development over time. In this paper, we analyse the impact of rising longevity on the trend of HCE over time by using data from a pseudo-panel of German sickness fund members over the period 1997 2009. Using (dynamic) panel data models, we find that age, mortality and 5-year survival rates each have a positive impact on per-capita HCE. Our explanation for the last finding is that physicians treat patients more aggressively if the results of these treatments pay off over a longer time span, which we call ''Eubie Blake effect''. A simulation on the basis of an official population forecast for Germany is used to isolate the effect of demographic ageing on real per-capita HCE over the coming decades. We find that, while falling mortality rates as such lower HCE, this effect is more than compensated by an increase in remaining life expectancy so that the net effect of ageing on HCE over time is clearly positive.
We derive a simple sufficient-statistics test for whether a nonlinear tax-transfer system is second-best Pareto efficient. If it is not, it is beyond the top of the Laffer curve and there exists a tax cut that is self-financing. The test depends on the income distribution, extensive and intensive labor supply elasticities, and income effect parameters.A tax-transfer system is likely to be inefficient if marginal tax rates are quickly falling in income. We apply this test to the German tax-transfer system and find the structure of effective marginal tax rates likely to be inefficient in the region where transfers are phased-out.
It is still an open question whether increasing life expectancy as such causes higher health care expenditures (HCE) in a population. According to the ''red herring'' hypothesis, the positive correlation between age and HCE is exclusively due to the fact that mortality rises with age and a large share of HCE is caused by proximity to death. As a consequence, rising longevity through falling mortality rates may even reduce HCE. However, a weakness of many previous empirical studies is that they use cross-sectional evidence to make inferences on a development over time. In this paper, we analyse the impact of rising longevity on the trend of HCE over time by using data from a pseudo-panel of German sickness fund members over the period 1997 2009. Using (dynamic) panel data models, we find that age, mortality and 5-year survival rates each have a positive impact on per-capita HCE. Our explanation for the last finding is that physicians treat patients more aggressively if the results of these treatments pay off over a longer time span, which we call ''Eubie Blake effect''. A simulation on the basis of an official population forecast for Germany is used to isolate the effect of demographic ageing on real per-capita HCE over the coming decades. We find that, while falling mortality rates as such lower HCE, this effect is more than compensated by an increase in remaining life expectancy so that the net effect of ageing on HCE over time is clearly positive.
In many countries, social health insurance systems are being reformed in favor of more competition among insurers, while premiums are community rated by regulation. The implicit incentives for insurers to engage in risk selection can only be curtailed using appropriate systems of risk-adjusted equalization payments among insurers. To develop these systems, predictors of individual utilization patterns have to be identified, e.g. via regression analysis using previous utilization data. In some countries such as Germany, such data are hardly ever available. In the early nineties, a number of sickness funds participated in an experiment in which individual utilization data were collected. Our data set covers more than 70,000 members of company sickness funds over a 5-year period. We analyze socio-demographic determinants of utilization which could be used as risk adjusters in a risk equalization scheme. Our results suggest that besides age and sex, the set of risk adjusters should include income, family status and a dummy for the last year of life.
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