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Econometric essays on nonlinear methods and diffusion index forecasting

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TitleInfo
Title
Econometric essays on nonlinear methods and diffusion index forecasting
Name (type = personal)
NamePart (type = family)
Kim
NamePart (type = given)
Hyun Hak
NamePart (type = date)
1978-
DisplayForm
Hyun Hak Kim
Role
RoleTerm (authority = RULIB)
author
Name (type = personal)
NamePart (type = family)
Swanson
NamePart (type = given)
Norman R
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Norman R Swanson
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Advisory Committee
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chair
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NamePart (type = family)
Klein
NamePart (type = given)
Roger
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Roger Klein
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Advisory Committee
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internal member
Name (type = personal)
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Landon-Lane
NamePart (type = given)
John
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John Landon-Lane
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Advisory Committee
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RoleTerm (authority = RULIB)
internal member
Name (type = personal)
NamePart (type = family)
Armah
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Nii Ayi
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Nii Ayi Armah
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Advisory Committee
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outside member
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Rutgers University
Role
RoleTerm (authority = RULIB)
degree grantor
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NamePart
Graduate School - New Brunswick
Role
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school
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Text
Genre (authority = marcgt)
theses
OriginInfo
DateCreated (qualifier = exact)
2012
DateOther (qualifier = exact); (type = degree)
2012-05
Place
PlaceTerm (type = code)
xx
Language
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eng
Abstract (type = abstract)
This dissertation comprises two essays in macroeconomic forecasting. The first essay empirically examines approaches to combining factor models and robust estimation, and presents the results of a "horse-race" in which mean-square-forecast-error (MSFE) "best" models are selected, in the context of a variety of forecast horizons, estimation window schemes and sample periods. For the majority of the target variables that we forecast, it is found that various of these shrinkage methods, when combined with simple factors formed using principal component analysis (e.g. component-wise boosting), perform better than all other models. It is also found that model averaging methods perform surprisingly poorly, given our prior that they would "win" in most cases. The second essays outlines and discusses a number of interesting new forecasting methods that have recently been developed in the statistics and econometrics literature. It focuses in particular on the examination of a variety of factor modeling methods, including principal components, independent component analysis (ICA) and sparse principal component analysis (SPCA). Further, it outlines a number of approaches for creating hybrid forecasting models that use these factor modeling approaches in conjunction with various type of shrinkage methods. The results show that pure factor modeling approaches alone are not enough to lead to our overall finding that simple linear econometric models as well as models based on various forecast combination strategies are dominated by more complicated (factor/shrinkage) type models.
Subject (authority = RUETD)
Topic
Economics
RelatedItem (type = host)
TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
Identifier (type = RULIB)
ETD
Identifier
ETD_3882
PhysicalDescription
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electronic resource
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application/pdf
InternetMediaType
text/xml
Extent
x, 106 p. : ill.
Note (type = degree)
Ph.D.
Note (type = bibliography)
Includes bibliographical references
Note (type = vita)
Includes vita
Note (type = statement of responsibility)
by Hyun Hak Kim
Subject (authority = ETD-LCSH)
Topic
Macroeconomics--Forecasting
Identifier (type = hdl)
http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000065173
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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 (type = doi)
doi:10.7282/T3BP01RC
Genre (authority = ExL-Esploro)
ETD doctoral
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Rights

RightsDeclaration (ID = rulibRdec0006)
The author owns the copyright to this work.
RightsHolder (type = personal)
Name
FamilyName
Kim
GivenName
Hyun Hak
Role
Copyright Holder
RightsEvent
Type
Permission or license
DateTime (encoding = w3cdtf); (qualifier = exact); (point = start)
2012-04-10 12:17:57
AssociatedEntity
Name
Hyun Hak Kim
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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