Examining the Dutch Disability Trends in the Nineteen-nineties: Age, Period, and Cohort Effects
AbstractThe paper focuses on changes in the prevalence of disability at older ages in the Netherlands during the nineteen-nineties. Disability is characterized by two selfreported indicators of mild and severe disability and two self-reported and objective measures of functional limitations. Age, period, and cohort (APC) factors are potential determinants of disability at older ages. Understanding the role of APC factors is crucial to get insight into current and future disability trends. To reach this objective, we had to deal with the well-known identification problem -- namely year of birth plus age equals calendar year of measurement. The identification problem is tackled by modeling cohort and period effects using lifetime macro-indicators. This approach -- innovative in analyses on disability trends also explains mechanisms underlying period and cohort effects. Analyses are conducted using data from the Longitudinal Aging Study Amsterdam. We produce evidence of increasing trends in functional limitations and disability at all ages above 60 and for both genders. These are largely caused by adverse period effects due to restrictions in acute and home care services. In addition, we find evidence of cohort effects -- mainly because of differences in exposure to tuberculosis mortality in year of birth on functional status and disability. This holds more specifically for females.
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Bibliographic InfoPaper provided by Utrecht School of Economics in its series Working Papers with number 04-20.
Length: 12 pages
Date of creation: Mar 2004
Date of revision:
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Find related papers by JEL classification:
- I12 - Health, Education, and Welfare - - Health - - - Health Production
- J14 - Labor and Demographic Economics - - Demographic Economics - - - Economics of the Elderly; Economics of the Handicapped; Non-Labor Market Discrimination
- C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Longitudinal Data; Spatial Time Series
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