Abstract:

We develop an age-period-cohort model for repeated cross-section data with individual covariates, which identifies the non-linear effects of age, period and cohort. This is done for both continuous and binary dependent variables. The age, period and cohort effects in the model are represented by a parametrization with freely varying parameters that separates the identified non-linear effects and the unidentifiable linear effects. We develop a test of the parametrization against a more general ‘time-saturated’ model. The method is applied to analyse the obesity epidemic in England using survey data. The main non-linear effects we find in English obesity data are age-related among women and cohort-related among men.

Citation:

Fannon, Z., Monden, C., & Nielsen, B. (2021), 'Modelling Non-Linear Age-Period-Cohort Effects and Covariates, With an Application to English Obesity 2001–2014', Journal of the Royal Statistical Society Series A: Statistics in Society, Vol. 184, Issue 3, pp. 842–867, Oxford University Press (OUP), https://doi.org/10.1111/rssa.12685
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