Dimitrakopoulos, Stefanos (2013) Essays on Bayesian semiparametric ordinal-response models. PhD thesis, University of Warwick.

Preview

PDF WRAP_THESIS_Dimitrakopoulos_2013.pdf - Submitted Version - Requires a PDF viewer. Download (2162Kb) | Preview

Request Changes to record.

Abstract

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.

Item Type:	Thesis or Dissertation (PhD)
Subjects:	H Social Sciences > HB Economic Theory
Library of Congress Subject Headings (LCSH):	Bayesian statistical decision theory, Econometric models, Markov processes, Monte Carlo method
Official Date:	December 2013
Dates:	Date Event December 2013 Submitted
Institution:	University of Warwick
Theses Department:	Department of Economics
Thesis Type:	PhD
Publication Status:	Unpublished
Supervisor(s)/Advisor:	Smith, Jeremy (Jeremy P.) ; Pitt, Michael K.
Sponsors:	University of Warwick ; University of Warwick. Department of Economics
Extent:	xiii, 147 leaves : charts
Language:	eng

Request changes or add full text files to a record

Repository staff actions (login required)

View Item

Downloads