ประมวลรายวิชา (Course Syllabus)

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Chulalongkorn University: Master of Arts Program in Business and Managerial
Economics
Economics 2949605
Quantitative Methods in Economic Analysis
Chairat Aemkulwat
1st Term, 2015
GENERAL INFORMATION: Classes is scheduled in a one-month module; tentative dates
for lectures, tutorial sessions and examination are in the syllabus. Any change to the lecture
dates will be announced in class and may be accessed at http://pioneer.netserv.
chula.ac.th/~achairat. Students are strongly advised to attend lectures and participate in
class, for attendance will be checked randomly and be used partially to adjust grade
distribution. Since lecture materials involve mathematical statistics and economic intuitions
and thus may be difficult at times, please attend classes punctually and read reading
assignments beforehand. Attendance is highly recommended for tutorial sessions. They are
designed to help you with homework assignments and to provide an additional avenue to
learn econometrics. For computing assignments, you can utilize EVIEWS 4.1 available in
our computer service center, room 316. My office is room number 519; phone number,
2218-6291 and 2218-6215; email, [email protected]
Below are course syllabus, outline and reading assignments, lecture and tutorial
schedule.
Course Syllabus: Quantitative Methods of Economic Analysis
1. Course Number
2949605
2. Course Credit
3
3. Course Title
Quantitative Methods in Economic
Analysis
4. Faculty / Department
Faculty of Economics
5. Semester (First / Second / Summer)
Trimester 1
6. Academic Year
2015
7. Instructor / Academic Staff
Assistant Professor Chairat Aemkulwat,
Ph.D.
8. Condition
8.1 Prerequisite
–
8.2 Corequisite
–
8.3 Concurrent
–
Students are assumed to have familiarity with basic calculus, probability, and
mathematical statistics. Read Wooldridge (2009), Appendix A, B, C for those
who have an inadequate background in these areas. Basic computer literary will
be needed to complete the problem sets.
9. Status (Required / Elective)
Required Course
1
10. Curriculum
Master of Arts Program in Business and
Managerial Economics
11. Degree
Master of Arts
12. Hours / Week
12
13. Course Description
This course is intended to provide an introduction to regression analysis with crosssection and time-series data; topics include estimation, statistical inference, functional
form, unit of measurement, asymptotics, prediction, dummy variables,
heteroskedasticity, serial correlation, weakly dependence and highly persistence.
14. Course Outline
14.1 Learning Content
30/9
1-2
3/10 (Sa)
3-4
4/10 (Su)
5
6/10
6-7
26/10
8-9
27/10
2/11
3/11
8/11 (Su)
9/11
10/11
16/11
17/11
10
11
11
12
13
13
14
14
Lecture 0 Intro to Econometrics
Lecture 1 SLR
Lecture 2 Log and Unit
Lecture 3 MRA Estimation
Lecture 4 MLR Inference
Lecture 5 MLR Asymptotics
Lecture 6 Quadratic Interaction
Lecture 7 Prediction
Lecture 9 Heteroskedasticity
Midterm Examination
Lecture 10 Dummy Dependent Variable
Lecture 11 Basic Regressions
Lecture 11 Basic Regressions
Lecture 12 Trends and Seasonality
Lecutre 13 Weakly Dependent
Lecutre 13 Weakly Dependent
Lecture 14 SC
Lecture 14 SC
Final Examination
14.2 Method
 Lecture
 Lecture and discussion
 Brainstorming and discussion of case
study so that students learn to analyze and
solve problems
 Making a summary of the main points or
presentation of the results of researching
or the assigned tasks
hour/time/period/percent)
14.3 Media
 Visualizer media - opaque sheets
hour/time/period/ 70 percent
hour/time/period/ 20 percent
hour/time/period/ 10 percent
–
5 percent
2
 Powerpoint media
 Electronics and website media
90 percent
5 percent
14.4 Assignment through Network System
14.5.1 Assigning and Submitting Method
Homework assignments can be obtained from my website,
http://pioneer.netserv.chula.ac.th/~achairat .
14.5.2 Learning Management System
Solutions to assigned exercises are given and lecture notes and pertinent
announcements can be obtained from my website.
14.5 Evaluation
14.6.1 Assessment of academic knowledge
85 percent
14.6.2 Assessment of work or classroom activities
–
14.6.3 Assessment of the assigned tasks
15 percent
GRADING SYSTEM: Grade will be based on the following:
15 percent on homework assignments,
40 percent on the midterm examination and
45 percent on the final.
Grade distribution is as follows:
90-100 is A;
80-90, B+;
65-80, B;
55-65, C+;
45-55, C;
35-45, D+;
25-35, D;
below 25, F.
Note that 79.99 is B and 80.01 is B+. Students are strongly advised to
attend lectures, for attendance will be checked randomly and be used
partially to adjust grade distribution.
15. Reading List
15.1 Required Text
Wooldridge, Jeffrey, M., Introductory Econometrics: A Modern Approach, 5th
International Edition (Canada: South-Western Cengage Learning), 2013.
15.2 Supplementary Texts
Eviews 4 User’s Guide, Quantitative Micro Software, 1994-2000.
Gujarati, D., Essentials of Econometrics (2e), McGraw-Hill, 2005.
Gujarati, D., Basic Econometrics (4e), McGraw-Hill, 2003
Johnston, J. and DiNardo, J., Econometric Methods (4e), McGraw-Hill, 1997.
Kennedy, P., A Guide to Econometrics, (3e), The MIT Press, 1994.
Pindyck, R. and Rubinfeld, L., Econometric Models and Economic Forecasts (4e),
3
McGraw-Hill, 1998.
Ramanathan, R. Introductory Econometrics with Applications, (5e), Thomson,
2001
Theil, H., Principles of Econometrics, John Wiley, 1976.
15.3 Research Articles / Academic Articles (If any)
15.4 Electronic Media or Websites
http://pioneer.netserv.chula.ac.th/~achairat
http://www.msu.edu/~ec/faculty/wooldridge/books.htm
http://aise.swlearning.com
16. Teacher Evaluation
16.1 Which of the 12 types of teacher evaluation provided by the University is used in
your class? If another form is used, please submit the form to The Quality
Assurance Division
02 Problem Based Learning
04 Lecture Learning
08 Lecture and Discussion
09 Tutorial Sessions
16.2 Changes made in accordance with the previous evaluation
The course has made adjustment in content and intended to be more participatory.
16.3 Discussion or analysis which creates desirable qualifications of Chulalongkorn
University graduates
1) Academic Knowledge: Students will learn linear statistical techniques both in
theory and economic and business application.
2) Professional Knowledge: Students will be able to understand papers
involving regression analysis.
3) Ethics: Lectures and discussions will encourage students to have ethics in
applying linear statistical techniques in their career.
4) Social Responsibility: Lectures, homework assignments, and punctuality will
implant sense of responsibility and help understand his role in society.
4
OUTLINE AND READING ASSIGNMENTS
I.
Overview: Nature of Econometrics
Wooldridge, Chapter 1
Wooldridge, Appendix A, B, and C
II.
Regression Analysis with Cross-Section Data
1. Simple Regression Model: Estimation
Wooldridge, Chapter 2
2. Logarithmic Functional Form and Units of Measurement
Wooldridge, Appendix A.3-A.4; Chapter 2.4 and 6.1-6.2
3. Multiple Regression Analysis: Estimation
Estimation: Wooldridge, Chapter 3
Omitted Variable Bias: Wooldridge, Chapter 3.3
Multicollinearity: Wooldridge, Chapter 3.4
4. Inference: Hypothesis Testing and Confidence Interval
Wooldridge, Chapter 4
5. OLS Asymptotoics: Estimation and Inference
Wooldridge, Chapter 5
6. Further Issues in Multiple Regression Analysis
Quadratic and Interaction Terms: Wooldridge, Chapter 6.2
(Adjusted) R-Squared and Selection of Regressors, Chapter 6.3
7. Prediction
Wooldridge, Chapter 6.4
8. Dummy (Binary) Explanatory Variable
Wooldridge, Chapter 7
9. Heteroskedasticity
Wooldridge, Chapter 8
10. Other Topics:
Dummy Dependent Variable: Wooldridge, Chapter 7.5 and 8.5
Functional Form Misspecification: Wooldridge, Chapter 9.1
III.
Regression Analysis with Time-Series Data
1. Basic Time Series Regression Analysis
Wooldridge, Chapter 10
2. Weakly Dependent and Highly Persistent Time Series
Wooldridge, Chapter 11 and 18.2
3. Serial Correlation and Heteroskedasticity
Wooldridge, Chapter 12
,
5
Tentative Lecture schedule for PT15 in 2015
October
MONDAY
28
5
TUESDAY WEDNESDAY THURSDAY
FRIDAY
SATURDAY
SUNDAY
29
30
18:00-20:30
QMEA
1
2
3
9:00-16:00
QMEA
4
9:00-15:00
QMEA
6
7
8
9
10
11
18:00-20:30
QMEA
12
3
10:30-12:00
Tutor: Eviews
13:00-15:30
Tutor: HW1
14
15
16
17
18
9:30-12:00
Tutor: HW2
19
26
18:00-20:30
QMEA
20
27
18:00-20:30
QMEA
21
28
23
24
Chulalongkorn
Day
9:30-12:00
Tutor: HW3
30
31
29
25
10:30-15:00
Tutor Midterm
November
MONDAY
TUESDAY WEDNESDAY THURSDAY
FRIDAY
SATURDAY
SUNDAY
1
2
3
18:00-20:30
QMEA
18:00-20:30
QMEA
9
10
18:00-20:30
QMEA
18:00-20:30
QMEA
16
17
18:00-20:30
QMEA
18:00-20:30
QMEA
23
24
4
11
18
5
12
19
6
13
20
7
8
9:00-12:00
Midterm
9:00-16:00
QMEA
14
15
9:30-12:00
Tutor: HW4
9:30-12:00
Tutor: HW5
21
22
9:30-12:00
Tutor: HW6
25
26
27
28
9:00-12:00 Final
30
6
10:00-15:00
Tutor Final
29
7
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