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Title: Essays on Bayesian semiparametric ordinal-response models
Author: Dimitrakopoulos, Stefanos
Awarding Body: University of Warwick
Current Institution: University of Warwick
Date of Award: 2013
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Bayesian nonparametric modelling has been widely applied to statistics and econometrics due to the various simulation methods that have been developed and in particular of Markov Chain Monte Carlo (MCMC) techniques. This thesis develops novel Bayesian nonparametric ordinal-response models and proposes efficient MCMC algorithms to estimate them. In chapter 21, we set up a model for inference on panel ordered data and apply it to sovereign credit ratings. In chapter 3, a model for ordinal-valued time series data is considered and is used to examine contagion across stock markets. Using real and simulated data, we show that the proposed models provide a great deal of flexibility in modelling and overcome the standard weakness of Bayesian methods due to the usual parametric assumptions.
Supervisor: Not available Sponsor: University of Warwick
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: HB Economic Theory