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 8241
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
#
Required
X
#
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 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
course should be the first in a two-course PhD field sequence in applied
macroeconomics.
6. Course description exactly as it should appear in the next catalog:
8241. Applied Macro I (3) P: ECON 8211. Development of the models and statistical
techniques used to study time series data with a special emphasis to applications in
macroeconomics.
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
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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
Current staff is adequate
X
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).
Textbooks:
Hamilton, J.D. (1994). Time Series Analysis. Princeton University Press, Princeton, NJ.
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Hayashi, F. (2000). Econometrics. Princeton University Press, Princeton NJ.
Readings:
Description of Macroeconomic Time Series Data:
Baxter, M. and R. King. (1999). Measuring the Business Cycle: Approximate BandPass filters for Economic Time Series. Review of Economics and Statistics.
Stock, J. and M. Watson. (1999). Business Cycle Fluctuations in US Macroeconomic
Time Series. In: Taylor, J.B., Woodford, M. (Eds.). Handbook of Macroeconomics
(15). Amsterdam; New York and Oxford: Elsevier Science, North-Holland.
Ahmed, S., A. Levin, A., and B. A. Wilson. (2004). Recent U.S. Macroeconomic
Stability: Good Policies, Good Practices, or Good Luck? The Review of Economics and
Statistics (86: pp.824-832). MIT Press.
Canova, F. (1998). Detrending and Business Cycle Facts. Journal of Monetary
Economics (41, pp.475-512 ).
Burnside, C. (1998). Detrending and Business Cycle Facts: A Comment. Journal of
Monetary Economics (41, pp. 513-532).
Shapiro, M. and M. Watson. (1988). Sources of Business Cycle Fluctuations. NBER
MacroAnnual.
Vector Autoregression:
Watson, M. (1994). Vector Autoregressions, Handbook of Econometrics (4). Elsevier
Kilian, L. (1998). Small Sample Confidence Intervals for IRFs. Review of Economics
and Statistics.
Pesavento, E. and B. Rossi. (2006). Impulse Response Confidence Intervals for
Persistent Data: What Have We Learned? Journal of Economic Dynamics and Control.
Rossi, E. and E. Pesavento. (2005). Do technology shocks drive hours up or down? A
little evidence from an agnostic procedure. Macroeconomic Dynamics.
Christiano, L., M. Eichenbaum, and C. Evans. (1999). Monetary Policy Shocks: What
Have We Learned and to What End? In: Taylor, J.B., Woodford, M. (Eds.). Handbook
of Macroeconomics (15: pp. 65-148). Amsterdam, New York and Oxford: Elsevier
Science, North-Holland.
Structural Breaks and Model Selection:
Andrews, D.W.K. (1993), Tests for Parameter Instability and Structural Change with
Unknown Change Point. Econometrica (61, pp. 821-856).
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Bai, J. & Perron, P. (1998). Estimating and Testing Linear Models with Multiple
Structural Changes. Econometrica (66, pp. 47-78).
Bai, J. (1997). Estimating Multiple Breaks One at a Time. Econometric Theory (13:
315-52).
Rossi, B. (2005). Optimal Tests for Nested Model Selection in the Presence of
Underlying Parameter Instability. Econometric Theory.
Forecasting:
West, K. (1996). Asymptotic Inference about Predictive Ability. Econometrica (64, pp.
1067-1084).
Chao, J., Corradi, V. & Swanson, N. (2001). An Out-of-sample Test for Granger
Causality. Macroeconomic Dynamics.
Clark, T. & McCracken, M. (2001). Tests of Equal Forecast Accuracy and
Encompassing for Nested Models. Journal of Econometrics (105, 85-110).
b. Course objectives for the course (student – centered, behavioral focus)
Upon completion of this course, students will be able to:
Understand the econometric theory of time series analysis, with an emphasis on recent
developments: analyze selected recent works in theoretical macroeconomic modeling
with an emphasis on their empirical implications and analysis; and integrate time series
data into their PhD research with the tools they need for state-of-the-art empirical
research.
c. Course topic outline
I. Time series models, filtering, and applications to leading indicators and the business
cycle.
II. Vector Auto-Regressions and impulse responses, with applications to monetary
policy analysis and the dynamics of aggregate demand and supply shocks.
III. Modeling and inference in persistent time series, with applications to trends and
random walks, and price convergence.
IV. Forecasting and structural breaks, and applications to the Phillips curve and the
Term Structure as predictors of future GDP growth and inflation dynamics.
d. List of course assignments, weighting of each assignment, and grading/evaluation system
for determining a grade
5 Problem sets:
Midterm Exam:
Course Paper:
Final Exam:
25%
25%
25%
25%
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Evaluation system is A for outstanding performance, B for acceptable performance, C
for inadequate performance, and F for failure.
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