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New dynamic optimization models for tax loss valuation and sourcing problems

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TitleInfo
Title
New dynamic optimization models for tax loss valuation and sourcing problems
Name (type = personal)
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Varzgani
NamePart (type = given)
Nilofar
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Nilofar Varzgani
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author
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Katehakis
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Michael N.
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Michael N. Katehakis
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Advisory Committee
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chair
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Govindaraj
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Suresh
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Suresh Govindaraj
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Advisory Committee
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co-chair
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Vaidya
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Jaideep
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Jaideep Vaidya
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Advisory Committee
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internal member
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Papadimitriou
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Spiros
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Spiros Papadimitriou
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Advisory Committee
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internal member
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Chidambaran
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N. K.
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N. K. Chidambaran
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Advisory Committee
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Rutgers University
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degree grantor
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Graduate School - Newark
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school
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theses
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2017
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2017-10
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2017
Place
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xx
Language
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eng
Abstract (type = abstract)
The dissertation comprises of three essays on multi-period dynamic optimization models. The first and second essays address the problem of valuing tax loss-carryforward(s) (TCLFs) and Carryback(s) (TLCBs) that arise frequently in theory and practice. While there have been a number of empirical papers that have shown TLCFs (TLCBs) are value relevant, there is little guidance on how to actually value these. The first essay introduces the valuation problem and provides a survey of literature in the area. The few analytical papers that have attempted to provide valuation formulas are highly stylized, do not capture the institutional complexity of the tax code, and are generally inadequate. In the second essay we develop a finite horizon discrete time stochastic dynamic programming framework for valuing TLCFs (TLCBs) that allows for piece-wise linear progressive taxation, and also incorporates many of the institutional features of the tax code. In the third essay we investigate a multi-product, multi-echelon contract manufacturer based business model. The decision problem faced by the manufacturing company is twofold: (a) how many contract manufacturers to get involved in business with (one supplier model vs a multi-supplier model, (b) how much volume should be allocated to each contract manufacturer, if the multiple supplier model is chosen. The objective is to maximize savings from the volume allocation process. Such problems arise often in many manufacturing industries such as electronics, pharmaceuticals, energy etc., for Original Equipment Manufacturing (OEM) firms. We provide a discrete time stochastic dynamic programming framework, and use numerical methods to study different volume allocation scenarios first in a one period setting, later extending the analysis to a multi-period model.
Subject (authority = RUETD)
Topic
Management
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Rutgers University Electronic Theses and Dissertations
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ETD_8471
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electronic resource
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application/pdf
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text/xml
Extent
1 online resource (xi, 86 p. : ill.)
Note (type = degree)
Ph.D.
Note (type = bibliography)
Includes bibliographical references
Subject (authority = ETD-LCSH)
Topic
Mathematical optimization
Note (type = statement of responsibility)
by Nilofar Varzgani
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TitleInfo
Title
Graduate School - Newark Electronic Theses and Dissertations
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rucore10002600001
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NjNbRU
Identifier (type = doi)
doi:10.7282/T3K35XRB
Genre (authority = ExL-Esploro)
ETD doctoral
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Rights

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The author owns the copyright to this work.
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Name
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Varzgani
GivenName
Nilofar
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Permission or license
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2017-10-01 10:43:55
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Nilofar Varzgani
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Rutgers University. Graduate School - Newark
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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
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Copyright protected
Availability
Status
Open
Reason
Permission or license
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2017-10-11T12:54:32
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