Bayesian Dynamic Panel-Ordered Probit Model and Its Application to Subjective Well-Being

• Hasegawa, Hikaru

抄録

This article proposes a Bayesian method for estimating the dynamic panel ordered probit model. We compare four alternative algorithms for the estimation of ordered probit models. Furthermore, this article presents the empirical results of the application of the dynamic ordered probit model to subjective well-being based on the micro-level survey data extracted from the Japanese Panel Survey of Consumers. The results of the application reveal that income and savings have positive effects on life satisfaction, whereas our posterior results show that marriage and labor force participation have negative effects on the same.

収録刊行物

• Communications in Statistics : Simulation and Computation

  Communications in Statistics : Simulation and Computation 38 (6), 1321-1347, 2009-06

  Taylor & Francis

キーワード

• Generalized Gibbs sampler
• Life satisfaction
• Markov chain Monte Carlo (MCMC)
• Well-being function

詳細情報

• CRID: 1050564288955562624
• NII論文ID: 120002128715
• HANDLE: 2115/43089
• ISSN: 03610918
• 本文言語コード: en
• 資料種別: journal article
• データソース種別:
  • IRDB
  • CiNii Articles
  • KAKEN