Disentangling the Age, Period, and Cohort Effects Using a Modeling Approach

Abstract

Disentangling age, period, and cohort effects in explaining health trends is crucial to assess future prevalences of health disorders. The identification problem - age, period, and cohort effects are perfectly linearly related - is tackled by modeling cohort and period effects using lifetime macro-indicators. This approach - innovative in analyses on health trends - handles the identification problem and explains mechanisms underlying cohort and period effects. The modeling approach is compared with graphical and two-factors methods. The methods are applied on Dutch trends in functional limitations using data from the Longitudinal Aging Study Amsterdam. We argue that the modeling approach is a highly appropriate alternative. We find that the prevalence of functional limitations increases in the nineteen-nineties due to adverse cohort and period effects. Cohort effects are explained by hygienic and socio-economic conditions during childhood and period effects by restrictions in availability of health care services.

Keywords: Age-Period-Cohort Analysis, Trends in Functional limitations, Aging

JEL Classification: I1, C4