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
ECON 8411 09/13/2011
1.
Course prefix and number: 2. Date:
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):
Expected
Future Delivery
Method(s):
X On-campus (face to face) 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 societal need 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 hazards and regulation of risk, as well as businesses for
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management and mitigation of risk.
The assessment process of the Economics Graduate Faculty has determined that this is an essential core course for the field of Risk Economics. It is also a fundamental course for the applied macro and micro economic fields in dealing with issues raised by coastal natural hazards.
6.
Course description exactly as it should appear in the next catalog:
8411. Risk Analysis I (3) P: ECON 8011, 8012; MATH 5102, 5801. Foundations of risk analysis; Modeling risk and uncertainty; Choice in the face of risk – expected utility analysis; extensions of expected utility; models of choice under uncertainty, incomplete information/knowledge, and/or ambiguity; dynamic models of decision making and the resolution of uncertainty, ambiguity, and/or risk.
7.
If this is a course revision, briefly describe the requested change:
N/A
8.
Course credit:
Lecture Hours
Lab
3 Weekly OR Per Term Credit Hours
Weekly OR Per Term Credit Hours
3 s.h. s.h.
Studio
Practicum
Internship
Total Credit Hours
Weekly OR Per Term Credit Hours
Weekly OR Per Term Credit Hours
Weekly OR Per Term Credit Hours
Other (e.g., independent study) Please explain.
s.h. s.h. s.h. s.h.
3 s.h.
9.
Anticipated annual student enrollment:
10.
Changes in degree hours of your programs:
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Degree(s)/Program(s) Changes in Degree Hours
PhD in 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.
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13.
Council for Teacher Education (CTE) approval (for courses affecting teacher education):
X Not applicable
Applicable and CTE has given their approval.
14.
University Service-Learning Committee (USLC) approval:
X Not applicable
Applicable and USLC has given their approval.
15.
Statements of support: a. Staff
X Current staff is adequate
Additional staff is needed (describe needs in the box below): 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).
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Arrow, K.J. (1970). Essays in the Theory of Risk Bearing . New York: Markham.
De Groot, M. (1970). Optimal Statistical Decisions . New York: McGraw Hill.
Fishburn, P.C. (1970). Utility Theory for Decision Making . New York: Wiley.
Gilboa, I. (2009). The Theory of Decision under Uncertainty . Cambridge, UK:
Cambridge.
Kreps, D. (1988). Notes on the Theory of Choice . Boulder : Westview.
Savage, L.J. (1954). The Foundations of Statistics . New York : Dover.
12 articles from recent theoretical literature. b. Course objectives for the course (student – centered, behavioral focus)
Upon completion of this course, students will be able to:
Apply fundamental mathematical models of risk and uncertainty, to analyze the decision theory of choices in the face of both risk and more fundamental uncertainty;
Apply expected utility models and their dynamic extensions to situations involving risk, uncertainty, and/or ambiguity in both static and dynamic settings; Use the classic tools of risk analysis and implement their standard applications. c. Course topic outline
1.
Mathematical formulation of risk, measures of levels of ‘riskiness’
2.
Review of the foundations of expected utility theory
3.
Classical Decision Theory in the face of Risk
4.
Subjective Probability and Choice under Uncertainty
5.
Modeling Ambiguity and Ambiguity Aversion
6.
Intertemporal, Recursive Utility Models of Decision Making
7.
Learning and Updating
Generalizations of State Space approach to modeling uncertainty and decisions d. List of course assignments, weighting of each assignment, and grading/evaluation system for determining a grade

6 problem sets (40%), due approximately every other week;

Mid-term Exam or Writing Assignment (25%);

Comprehensive Final Exam (35%).
Grading System:
A – Outstanding; B – Satisfactory; C – Insufficient; F – Failing.
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