Population ageing and health care expenditure: a school of 'red herrings'?
This paper revisits the debate on the 'red herring', viz. the claim that population ageing will not have a significant impact on health care expenditure (HCE). It decomposes HCE into seven components, includes both survivors and deceased individuals, and estimates a two-part model of the demand for health care services, using a large Swiss data set for 1999. It finds no or weak age effects on HCE for the components of HCE when proximity to death is controlled for, and points to differences between users and non-users of long-term care (LTC). For deceased non-users of LTC services, a falling age curve for all components of HCE except for inpatient care is observed, while survivors show a weak age effect in ambulatory and inpatient care once proximity to death is controlled for. As to surviving users of LTC services, their probability of incurring LTC expenses markedly increases in old age, while most of the components of their conditional HCE show a decreasing age profile. Thus, a 'school of red herrings' can be claimed to exist-with the possible exception of LTC, where ageing might matter regardless of proximity to death.
Werblow
Andreas
A
Faculty of Business Management and Economics, Technical University Dresden, Magdeburg, Germany.
Felder
Stefan
S
Zweifel
Peter
P
D000328:Adult; D017677:Age Distribution; D000368:Aged; D000369:Aged, 80 and over; D000375:Aging; D000553:Ambulatory Care / Q000191:economics / Q000706:statistics & numerical data; D005260:Female; D005102:Health Expenditures / Q000706:statistics & numerical data*; D006296:Health Services / Q000191:economics* / Q000706:statistics & numerical data*; D006301:Health Services Needs and Demand / Q000191:economics* / Q000458:organization & administration; D006801:Humans; D007297:Inpatients / Q000706:statistics & numerical data; D008017:Life Expectancy; D008134:Long-Term Care / Q000191:economics / Q000706:statistics & numerical data; D008297:Male; D008875:Middle Aged; D017059:Models, Econometric; D011157:Population Dynamics; D012737:Sex Factors; D013222:State Medicine; D013557:Switzerland