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Economic growth and happiness in China: A Bayesian multilevel age-period-cohort analysis based on the CGSS data 2005–2015

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  • Su, Yu-Sung
  • Lien, Donald
  • Yao, Yuling

Abstract

This paper introduces a Bayesian multilevel model based on the age-period-cohort framework to examine Chinese happiness. Using 8 waves of the Chinese General Social Survey (CGSS) data between 2005–2015, the model not only solves the co-linearity problem with weakly informative priors and explicit assumptions, it also produces more computationally stable results. Our estimation results show how Chinese happiness changes in an individual’s life circle and how one’s life experience is accumulated to her/his happiness with cognitive development. We identify some different generation patterns and explain generation differences in happiness across the various birth years with narratives of historical events. This paper contributes to existing studies both theoretically and methodologically. The novel modeling strategy and the analytical framework which assisted with historical narratives altogether explain better the age, period, and cohort effects on Chinese happiness.

Suggested Citation

  • Su, Yu-Sung & Lien, Donald & Yao, Yuling, 2022. "Economic growth and happiness in China: A Bayesian multilevel age-period-cohort analysis based on the CGSS data 2005–2015," International Review of Economics & Finance, Elsevier, vol. 77(C), pages 191-205.
    • Handle: RePEc:eee:reveco:v:77:y:2022:i:c:p:191-205
    DOI: 10.1016/j.iref.2021.09.018
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    3. Liu, Feng & Long, Xiao & Dong, Lin & Fang, Mingjie, 2023. "What makes you entrepreneurial? Using machine learning to investigate the determinants of entrepreneurship in China," China Economic Review, Elsevier, vol. 81(C).
    4. Yongsong Wu & Yang Cao, 2023. "Research on the Influence of Ecological Environment Satisfaction and Income Level on Chinese Residents’ Happiness: Empirical Analysis Based on CGSS Data," Sustainability, MDPI, vol. 15(10), pages 1-18, May.

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