Bayesian hierarchical age-period-cohort models with time-structured effects: An application to religious voting inthe US, 1972-2008


Journal Article

To examine dynamics of political processes using repeated cross-section data, effects of age, cohort, and time period have to be disentangled. I propose a Bayesian dynamic hierarchical model with cohort and period effects modeled as random walk through time. It includes smoothly time-varying effects of covariates, allowing researchers to study changing effects of individual characteristics on political behavior. It provides a flexible functional form estimate of age by integrating a semi-parametric approach in the hierarchical model. I employ this approach to examine religious voting in the United States using repeated cross-sectional surveys from 1972 to 2008. I find starkly differing nonlinear trends of de- and re-alignment among different religious denominations. © 2013 Elsevier Ltd.

Full Text

Duke Authors

Cited Authors

  • Stegmueller, D

Published Date

  • March 1, 2014

Published In

Volume / Issue

  • 33 /

Start / End Page

  • 52 - 62

International Standard Serial Number (ISSN)

  • 0261-3794

Digital Object Identifier (DOI)

  • 10.1016/j.electstud.2013.06.005

Citation Source

  • Scopus