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

DOI10.1080/03610910902903133zbMath1167.62490OpenAlexW2019968055MaRDI QIDQ3391874

Hikaru Hasegawa

Publication date: 13 August 2009

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/2115/43089

zbMATH Keywords

Markov chain Monte Carlo (MCMC)generalized Gibbs samplerlife satisfactionwell-being function

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Applications of statistics to social sciences (62P25) Bayesian inference (62F15)

Related Items (3)

Joint Bayesian longitudinal models for mixed outcome types and associated model selection techniques ⋮ Discrete-response state space models with conditional heteroscedasticity: an application to forecasting the federal funds rate target ⋮ Making inference of British household's happiness efficiency: a Bayesian latent model

Uses Software

• Ox

Cites Work

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• Sequential Ordinal Modeling with Applications to Survival Data
• Fitting and comparison of models for multivariate ordinal outcomes
• Panel Data and Unobservable Individual Effects
• Ordinal Data Modeling
• Reparameterizing the generalized linear model to accelerate gibbs sampler convergence
• Generalised Gibbs sampler and multigrid Monte Carlo for Bayesian computation

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