Modelling Non-Linear Age-Period-Cohort Effects and Covariates, With an Application to English Obesity 2001–2014
提出一种识别年龄、时期和队列非线性效应的模型，适用于重复截面数据，并应用于英格兰肥胖数据分析，发现女性肥胖主要与年龄相关，男性则与队列相关。
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.