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Essays on Bayesian inference of time-series and ordered panel data models
Descriptive
TitleInfo
Title
Essays on Bayesian inference of time-series and ordered
panel data models
panel data models
Name
(type = personal)
NamePart
(type = family)
Park
NamePart
(type = given)
Jeehyun
NamePart
(type = date)
1981-
DisplayForm
Jeehyun Park
Role
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author
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Tsurumi
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Hiroki
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Hiroki Tsurumi
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Advisory Committee
Role
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chair
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Russell
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Louise B
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Louise B Russell
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Advisory Committee
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internal member
Name
(type = personal)
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(type = family)
Landon-Lane
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(type = given)
John
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John Landon-Lane
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Advisory Committee
Role
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(authority = RULIB)
internal member
Name
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(type = family)
Goldman
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(type = given)
Elena
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Elena Goldman
Affiliation
Advisory Committee
Role
RoleTerm
(authority = RULIB)
outside member
Name
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NamePart
Rutgers University
Role
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(authority = RULIB)
degree grantor
Name
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NamePart
Graduate School - New Brunswick
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(authority = RULIB)
school
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Text
Genre
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theses
OriginInfo
DateCreated
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2012
DateOther
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(type = degree)
2012-10
Place
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xx
Language
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(authority = ISO639-2b);
(type = code)
eng
Abstract
(type = abstract)
At the heart of my dissertation is the study of Markov chain Monte Carlo algorithms and their applications. My dissertation consists of three essays as follow. The first chapter is on MCMC algorithms for the dynamic ordered probit model with random effects. I have tried to estimate the model with four representative MCMC algorithms: two algorithms by Albert and Chib (1993) and Albert and Chib (2001), Liu and Sabatti (2000), and Chen and Dey (2000). I have found that the autocorrelations still remain high in the cutoffs compared to other parameters even though the levels of autocorrelation are reduced in the algorithms by Liu and Sabatti (2000), and Chen and Dey (2000). In the second chapter, I have developed the dynamic ordered probit model studied in the first chapter. It is natural for panel data to have missing data problem because there is no guarantee that subjects will stay over the study periods. This chapter provides Bayesian statistical methods that permit non-ignorable missing data in panel datasets. In order to incorporate non-random missing data in the model, I jointly model observed and non-ignorable missing ordinal data with selection model approach. In the empirical section, I have used the model to examine determinants of self-rated health of old people in the Health and Retirement Study. I have concluded that in this elderly American population, the longest occupation that respondents have held over their careers is strongly associated with self-rated health. In the third chapter of my dissertation, I analyze financial time-series data before and after the Wall Street meltdown in 2008. In this chapter, I develop MCMC algorithms for the CKLS model and examine (1) time-series characteristics of the credit default swap index, stock index and federal funds rate from January 2007 to September 2009, the highly volatile period. (2) The lead-lag relationship between the credit default swap and stock markets are examined using the CKLS model employing multivariate analysis.
Subject
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Topic
Economics
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TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
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ETD
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ETD_4171
PhysicalDescription
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electronic resource
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application/pdf
InternetMediaType
text/xml
Extent
xi, 112 p. : ill.
Note
(type = degree)
Ph.D.
Note
(type = bibliography)
Includes bibliographical references
Note
(type = vita)
Includes vita
Note
(type = statement of responsibility)
by Jeehyun Park
Subject
(authority = ETD-LCSH)
Topic
Bayesian statistical decision theory
Subject
(authority = ETD-LCSH)
Topic
Markov processes
Identifier
(type = hdl)
http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000066936
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TitleInfo
Title
Graduate School - New Brunswick Electronic Theses and Dissertations
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rucore19991600001
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NjNbRU
Identifier
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doi:10.7282/T3W094QN
Genre
(authority = ExL-Esploro)
ETD doctoral
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Rights
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The author owns the copyright to this work.
RightsHolder
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Name
FamilyName
Park
GivenName
Jeehyun
Role
Copyright Holder
RightsEvent
Type
Permission or license
DateTime
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(qualifier = exact);
(point = start)
2012-07-09 17:37:56
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Name
Jeehyun Park
Role
Copyright holder
Affiliation
Rutgers University. Graduate School - New Brunswick
AssociatedObject
Type
License
Name
Author Agreement License
Detail
I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
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