Abstract
We study the effect of ageing, defined as an extra year of life, on health care utilisation. We disentangle the direct effect of ageing, from other alternative explanations such as the presence of comorbidities and endogenous time to death (TTD) that are argued to absorb the effect of ageing (so-called 'red herring' hypothesis). We exploit individual level end of life data from several European countries that record the use of medicine, outpatient and inpatient care and long-term care. Consistently with the 'red herring hypothesis', we find that corrected TTD estimates are significantly different from uncorrected ones, and their effect size exceeds that of an extra year of life, which in turn is moderated by individual comorbidities. Corrected estimates suggest an overall attenuated effect of ageing, which does not influence outpatient care utilisation. These results suggest the presence of 'more than one red herring' depending on the type of health care examined.
Highlights
Population ageing is commonly portrayed as a central determinant of health care spending (WHO, 2015; Marino et al, 2017
This paper aims to examine the effect of ageing on different types of health care use, to disentangle the effect of additional confounding effects on health expenditure, namely (i) proximity to death, (ii) co-morbidities and lifestyles and (iii) differences in the composition of health care
We are concerned with respect to idiosyncratic heterogeneity, which arises when some of the explanatory variables are correlated with time-varying unobserved shocks. following Card (1999), the correlation between the instrument and the dependent variable through the unobservables can give rise to bias in IV estimates. To address this issue Lin and Wooldridge (2019) propose a test for idiosyncratic exogeneity based on the robustness properties of the Poisson fixed-effects estimator combined with the control function approach, that is robust to distributional misspecification and serial dependence
Summary
Population ageing is commonly portrayed as a central determinant of health care spending (WHO, 2015; Marino et al, 2017). Some studies even go as far as to argue that the effect of ageing on health care reflects a ‘red herring’ given that when time to death (TTD) is accounted for, the effect of ageing disappears (Zweifel et al, 1999; Zweifel et al, 2004; Hall and Jones 2007; Shang and Goldman 2007). In addition to the consideration of TTD, which is potentially endogenous, another source of overestimation (of ageing effects on health expenditure) results from the correlation between morbidity and individual’s age, as it is subject to omitted variable bias. The effect of such omitted variable bias can be analysed using individual longitudinal data, that captures the influence of early lifestyles.
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