Curriculum Vitae (pdf) - Southern Illinois University

SABRI YILMAZ June 2012
Department of Economics, Mail Code 4515
Cell Phone: 1-618-303-4174
Southern Illinois University Carbondale
Fax: 1-618-453-2717
1000 Faner Drive
E-mail: sabri@siu.edu
Carbondale, IL 62901
http://mypage.siu.edu/sabri
EDUCATION
Ph.D. in Economics, Southern Illinois University Carbondale (SIUC), Carbondale, IL, (May
2012)
Title: “Trade Networks under Asymmetric Information”
Advisor: Professor Alison Watts
M.A. in Economics, University of Missouri-Columbia (UMC),
Columbia, MO, (December 2004)
Title: "A Generalized Binomial Model for Pricing European Call Options in the
Non-recombinant Tree Case"
Advisors: Professors Allanus Tsoi and X.H. Wang
M.S. in Applied Mathematics, University of Missouri-Columbia (UMC),
Columbia, MO, (December 2004)
Title: "A Generalized Binomial Model for Pricing European Call Options in the
Non-recombinant Tree Case"
Advisors: Professors Allanus Tsoi and X.H. Wang
B.S. in Mathematics, Marmara University- Istanbul, Turkey, (July 1999)
PAPERS
Papers Accepted for Publication
“Connectivity Restoration in Delay Tolerant Sensor Networks using Game Theory”, with I.
F. Senturk and K. Akkaya, accepted for publication with minor revision, International
Journal of Ad Hoc and Ubiquitous Computing (Special Issue on: "Algorithms and Protocols
for Opportunistic and Delay-Tolerant Networks")
“Distributed Relay Node Positioning for Connectivity Restoration in Partitioned Wireless
Sensor Networks”, with I. F. Senturk and K. Akkaya, forthcoming in the Proceedings of
IEEE ICSC 2012 and IEEEXplore
“A Game-Theoretic Approach to Connectivity Restoration in Wireless Sensor and Actor
Networks”, with I. F. Senturk and K. Akkaya, forthcoming in the Proceedings of IEEE ICC
2012 Workshops and IEEEXplore
Working Papers
“Trade Networks Under Asymmetric Information”, Job Market Paper
“Multiple Traders’ Networks Under Asymmetric Information”
“Middlemen in the Housing Market: An Application to Trade Networks”
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“Optimal Pricing Strategy in Freight Transportation Networks under Asymmetric
Information”, with M. Y. Sir and E. Sisikoglu, work in progress
“A Generalized Binomial Model for Pricing European Call Options in the Non-recombinant
Tree Case”, November 2004, Master’s Project Paper
TEACHING AND RESEARCH INTERESTS:
Microeconomics, Game Theory, Economic Development, International Economics,
Mathematical Economics, Applied Microeconomics, Financial Economics, Public Finance.
WORK EXPERIENCE
Term Faculty, Department of Business Education, John A. Logan College, 2011-present
Courses:
ECO 201(Introduction to Macroeconomics), Summer 2011, Fall 2011, Instructor
ECO 202 (Introduction to Microeconomics), Summer 2011, Fall 2011, Spring 2012 (two
sections), Summer 2012 (assigned to teach), Instructor
Instructor, Department of Economics, SIUC, (2010 – 2011)
Courses:
Econ 241(Introduction to Macroeconomics), Spring 2011, Instructor
Econ 113 (Economics of Contemporary Social Issues), Fall 2010, Instructor
Teaching Assistant, Department of Economics, SIUC, (2009 – 2010)
Courses:
Econ 511 (Mathematical Economics II), Econ 463 (Applied Econometrics), Econ 113
(Economics of Contemporary Social Issues) as a T.A.
T.A. duties include holding office hours, grading homework, quizzes and examinations,
proctoring and tutoring.
Instructor, Department of Mathematics, UMC, (2005 – 2008)
Courses:
Math 1100 (College Algebra for Calculus Bound Students), Fall 2008, Spring 2008, Fall
2007, Spring 2006, Fall 2005, Instructor
Math 1300 (Finite Mathematics for Business undergraduates), Spring 2007(2 sections),
Instructor
Teaching Assistant, Department of Mathematics, UMC, (2003 – 2007)
Courses:
Math 1500 (Analytic Geometry & Calculus I), Fall 2006 (3 sections); Spring 2005 (1
section); Fall 2003, Spring 2004, Fall 2004 (2 sections each), as a T.A.
Math 4140 (Matrix Theory), Summer 2007, as a grader.
T.A. duties include teaching several sections by helping with problem-solving, holding office
hours, grading homework, quizzes and examinations, proctoring and tutoring in help
sessions.
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Teaching Assistant, Department of Mathematics, Istanbul Technical University (ITU),
Istanbul, TURKEY, (2000 – 2002)
Courses:
Math 102(Calculus) as a T.A.
T.A. duties include teaching several sections by helping with problem-solving, holding office
hours, grading homework, quizzes and examinations, proctoring and tutoring.
Graduate Student Assistant, Department of Mathematics, Istanbul Technical University
(ITU), Istanbul, TURKEY (2000)
Course:
Math 102(Calculus) as a grader
HONORS AND AWARDS
Travel Fund, Department of Economics, SIUC, 2010, 2011
Departmental Fellowship, Department of Mathematics, University of Missouri-Columbia,
2002.
Ranked first among Mathematics Graduates in 1999, Marmara University, 1999.
PRESENTATIONS
The Fourth World Congress of Game Theory Society, Games 2012, Istanbul, Turkey, (paper
accepted for presentation, July 22-26, 2012)
Midwest Economics Association, 2012 Annual MEA Meeting, Evanston, IL, (March 31,
2012)
Missouri Valley Economics Association, 48 th Annual Meeting, Kansas City, MO, (October
21, 2011)
Midwest Economics Association, 2011 Annual MEA Meeting, St. Louis, MO, (March 20,
2011)
Missouri Valley Economics Association, 47 th Annual Meeting, St. Louis, MO, (October 29,
2010)
Illinois Economic Association, 40 th Annual Meeting, Chicago, IL, (October 15, 2010)
Department of Economics, SIUC, Brown Bag Seminar, Carbondale, IL (October 28, 2011)
Department of Economics, SIUC, Brown Bag Seminar, Carbondale, IL (December 3, 2010)
COMPUTER SKILLS
Programming Languages including Basic, GwBasic, Pascal
Experience with MS Windows, MS Office, Mathematica, Eviews, STATA, RATS, GAUSS.
LANGUAGES
Turkish (native), English (fluent), German (beginner)
MEMBERSHIP
American Economic Association
Midwest Economics Association
Royal Economic Society
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REFERENCES
Alison Watts, Professor, Department of Economics, SIUC
Mail Code 4515, 1000 Faner Drive, Carbondale, IL 62901
Phone: 1-618-453-5072
E-mail: wattsa@siu.edu
Chifeng Dai, Associate Professor, Department of Economics, SIUC
Mail Code 4515, 1000 Faner Drive, Carbondale, IL 62901
Phone: 1-618-453-5347
E-mail: daic@siu.edu
Sajal Lahiri, Professor and Vandeveer Chair, Department of Economics, SIUC
Mail Code 4515, 1000 Faner Drive, Carbondale, IL 62901
Phone: 1-618-453-9472
E-mail: lahiri@siu.edu
Jason D. Tanner, Ph.D., Professor of Business, Department of Business Education
John A. Logan College
700 Logan College Road, Carterville, IL 62918
Phone: 1-618-985-2828 Ext. 8170
E-mail: jasontanner@jalc.edu
DISSERTATION OUTLINE
“Trade Networks under Asymmetric Information”, Job Market Paper
Buyer and seller interactions are analyzed with intermediaries called traders using a network
structure. Goods are traded in the market through those networks. Each seller and buyer is linked
to a trader through a network but not directly linked to each other. Our main contribution to the
literature is that we introduce asymmetric information on the valuation of goods by sellers and
buyers. Our model basically consists of a two-stage game with incomplete information. First, the
trader offers bid prices to the sellers and ask prices to the buyers. Second, trade takes place when
the sellers and/or buyers accept the trader`s offers. The trader tries to maximize his profit.
First, we analyze even network structures: one seller-one trader-one buyer and two buyers-one
trader-two sellers. Our main finding for the one seller-one buyer network is that the trader never
sets the same bid and ask prices to the seller and the buyer, respectively. Another result in the
second setting is that the trader sometimes offers different prices to sellers or to buyers when the
penalty is almost zero. For the asymmetric network case when one trader is linked to one seller
and two buyers, we find that offering the same ask price to both buyers usually yields the
maximum expected payoff to the trader. However, when the trader is linked to two sellers and
one buyer, we see that that the trader sometimes offers the same price to all three parties to
receive the maximum profit.
“Multiple Traders’ Networks under Asymmetric Information”
In this paper, we allow there to be multiple traders and analyze how buyer and seller prices are
influenced by competition among traders in a model of uncertainty. We start by considering a
network with one seller, two traders and one buyer. The seller and buyer have strong positions
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and they both will try to benefit from the competition between the two traders. The traders
compete in the sense of a Bertrand duopoly to choose the price where each trader aims to
maximize his profit. We also examine different network structures involving two sellers and one
buyer with two traders and the network formation with three sellers-two traders-one buyer. We
note that the sellers who are not subject to the competition between two traders suffer from the
consequences of the monopoly competition. We compute the equilibrium bid and ask prices
offered by the traders for all three networks. There will not be one fixed price that the traders
offer the seller and buyer both of whom benefit from the competition in the last two network
structures. Finally, we look for the maximum expected payoff for each trader by investigating the
best responses to the given bid and ask price schedules. We find that one trader’s best responses
depend on the conditions on the valuations for the traded good.
“Middlemen in the Housing Market: An Application to Trade Networks”
Middlemen, either as individuals or realtors, seem to have influential effects on the pricing
strategy in the housing market. In this paper, we analyze the contribution of the middlemen in the
housing market as an application to trade networks. We work on a specific dataset related to the
housing prices for two main neighborhoods in Atlanta, Georgia. The characteristics of those
neighborhoods differ in terms of being close to downtown or far from downtown but including
mainly high-valued residential houses. We start by examining the returns that individuals who
are defined to be intermediaries in the market get during each housing transaction. Finally, we
compare and contrast the returns for those two neighborhoods with distinct properties in order to
investigate if any of these neighborhoods yield higher returns for the middlemen.
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