Graduate Curriculum Committee Course Proposal Form
for Courses Numbered 6000 and Higher
Note: Before completing this form, please carefully read the accompanying instructions.
Submission guidelines are posted to the GCC Web site: http://www.ecu.edu/cs-acad/gcc/index.cfm
1. Course prefix and number:
ECON 8412
2. Date:
09/13/2011
3. Requested action:
X New Course
Revision of Active Course
Revision & Unbanking of a Banked Course
Renumbering of an Existing Course from
from
to
#
X
Required
#
Elective
4. Method(s) of delivery (check all boxes that apply for both current/proposed and expected
future delivery methods within the next three years):
Current or
Proposed Delivery
Method(s):
X
On-campus (face to face)
Expected
Future Delivery
Method(s):
X
Distance Course (face to face off campus)
Online (delivery of 50% or more of the instruction is offered online)
5. Justification (must cite accreditation and/or assessment by the graduate faculty) for new course
or course revision or course renumbering:
The graduate faculty of the Department of Economics identified a need in government,
the private sector, and in academia for PhD graduates with advanced analytic and
technical skills necessary for analysis, mitigation, management and regulation of risk—
both environmental and financial. This requires an understanding of the underlying
individual decision maker and firm behavior and their interaction within market and
nonmarket settings. Theoretical modeling and empirical analysis complete the picture
and allow for the identification of effective public policy and regulation. This doctoral
program is unique within the state of North Carolina because it emphasizes risk modeling
and analysis over a broad scope of applications that range from financial markets to
natural hazards. Students with training from this program will be well equipped to
qualify for high level positions within Federal and State Agencies that deal with natural
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hazards and regulation of risk, as well as businesses for management and mitigation of
risk.
The assessment process of the Economics Graduate Faculty has determined that a field in
risk and uncertainty, particularly one dealing with natural and environmental hazards,
requires a course presenting and developing the alternatives to classical expected utility
analysis.
6. Course description exactly as it should appear in the next catalog:
8412. Risk Analysis II (3) P: ECON 8411. Analysis of models relevant to natural
hazards risks.
7. If this is a course revision, briefly describe the requested change:
N/A
8. Course credit:
Lecture Hours
3
3
Weekly
OR
Per Term
Credit Hours
s.h.
Lab
Weekly
OR
Per Term
Credit Hours
s.h.
Studio
Weekly
OR
Per Term
Credit Hours
s.h.
Practicum
Weekly
OR
Per Term
Credit Hours
s.h.
Internship
Weekly
OR
Per Term
Credit Hours
s.h.
Other (e.g., independent study) Please explain.
s.h.
3
Total Credit Hours
s.h.
6
9. Anticipated annual student enrollment:
10. Changes in degree hours of your programs:
Degree(s)/Program(s)
Changes in Degree Hours
PhD/Economics
N/A
11. Affected degrees or academic programs, other than your programs:
Degree(s)/Program(s)
Changes in Degree Hours
12. Overlapping or duplication with affected units or programs:
X Not applicable
Documentation of notification to the affected academic degree programs is
attached.
13. Council for Teacher Education (CTE) approval (for courses affecting teacher education):
X Not applicable
Applicable and CTE has given their approval.
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14. University Service-Learning Committee (USLC) approval:
X Not applicable
Applicable and USLC has given their approval.
15. Statements of support:
a. Staff
Current staff is adequate
Additional staff is needed (describe needs in the box below):
X
Specialist in theories of risk and uncertainty and
applications to hazards related risks.
b. Facilities
X Current facilities are adequate
Additional facilities are needed (describe needs in the box below):
c. Library
X
Initial library resources are adequate
Initial resources are needed (in the box below, give a brief explanation and an
estimate for the cost of acquisition of required initial resources):
d. Unit computer resources
X
Unit computer resources are adequate
Additional unit computer resources are needed (in the box below, give a brief
explanation and an estimate for the cost of acquisition):
e. ITCS resources
X
ITCS resources are not needed
The following ITCS resources are needed (put a check beside each need):
Mainframe computer system
Statistical services
Network connections
Computer lab for students
Software MATLAB
Approval from the Director of ITCS attached
16. Course information (see: Graduate Curriculum and Program Development Manual for
instructions):
a. Textbook(s) and/or readings: author(s), name, publication date, publisher, and
city/state/country. Include ISBN (when applicable).
Required:
Gilboa, I. (2009). The Theory of Decision under Uncertainty. Cambridge, UK:
Cambridge. ISBN: 978-0521741231
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Gilboa, I. (2010). Making Better Decisions: Decision Theory in Practice. New York:
Wiley. ISBN: 978-1444336528
Kreps, D. (1988). Notes on the Theory of Choice, Boulder: Westview). ISBN: 9780813375533
Selected Readings from:
Dow, J. & Werlang, S. (1992). Uncertainty Aversion, Risk Aversion, and the Optimal
Choice of Portfolio. Econometrics (60, pp.179-204). ISBN: 978-0691010182
Ellsberg, D. (1961). Risk, Ambiguity, and the Savage Axioms. Quarterly Journal of
Economics (75, pp. 643-669).
Embrechts, P., Klüppelberg, C., & Mikosch, T. (2003). Modeling Extremal Events,
Berlin: Springer-Verlag. ISBN: 978-3642082429
Falconer, K. (1990). Fractal Geometry: Mathematical Foundations and Applications,
New York: Wiley. ISBN: 978-0470848623
Geweke, J. (Ed.). (1992). Decision Making under Uncertainty---New Models and
Empirical Findings. Amsterdam: Kluwer. ISBN: 978-0792319047
Gilboa, I. & Schmeidler, D. (2001). A Theory of Case-Based Decisions. Cambridge,
UK: Cambridge. ISBN: 978-0521003117
Kahneman, D. & Tversky, A. (1979). Prospect Theory: An Analysis of Decision under
Risk. Econometrica (47, pp.263-291).
Kahneman, D. & Tversky A. (Eds.). (2000). Choices, Values, and Frames. Cambridge,
UK: Cambridge. ISBN: 978-0521627498
Karni, E. (1985). Decision Making Under Uncertainty: The Case of State Dependent
Preference. Cambridge, MA: Harvard. ISBN: 978-0674195257
Machina, M.J. (1987). Choice Under Uncertainty: Problems Solved and Unsolved.
Journal of Economic Perspectives (1, pp.121-154).
Mukerji, S. & Talon, J.M. (2001). Ambiguity /Aversion and the Incompleteness of
Financial Markets. Review of Economic Studies (68, pp. 883-904).
Rigotti, L. & Shannon, C. (2005). Uncertainty and Risk in Financial Markets.
Econometrica (73, pp.203-243).
Wakker, P.P. (2008). Prospect Theory, Cambridge, UK: Cambridge. ISBN: 9780521748681
And recent research papers on alternatives to, and extensions of, expected utility
theory.
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b. Course objectives for the course (student – centered, behavioral focus)
Upon completion of this course, students will be able to:





Compare and contrast alternative approaches to understanding decision-making
in the face of uncertainty;
Utilize behavioral models to evaluate the impact of risk, ambiguity, true
uncertainty on decision-making;
Model risks with “fat tails”, and extremal events;
Analyze “optimal” decisions in the face of extreme events, and natural
catastrophes;
Apply these models to analyze natural hazards risks and their consequences.
c. Course topic outline
1. Difficulties with Expected Utility Theory: Behavioral Contradictions.
2. Behavioral Models of Choice under Risk and Uncertainty.
3. Non-expected Utility Models: Sets of distributions; capacities; purely finitely
additive measures.
4. Optimal Decisions with ‘fat-tailed’ risks, extremal events.
5. Applications to finance and the pricing of market securities.
6. Fractal Models of risky/uncertain decision environments.
d. List of course assignments, weighting of each assignment, and grading/evaluation system
for determining a grade



Problem sets
(42%)
Survey Paper
(25%)
Comprehensive Final Exam (33%)
Evaluation System
A
90% to 100%
B
89% to 80%
C
79% to 70%
F
Below 70%
Outstanding Performance
Acceptable Performance
Inadequate Performance
Failure
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