: Master of Arts Program in Business and Managerial
Economics
Economics 2949605
Quantitative Methods in Economic Analysis
Chairat Aemkulwat
1 st
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, chairat.a@chula.ac.th.
Below are course syllabus, outline and reading assignments, lecture and tutorial schedule.
1.
Course Number
2.
Course Credit
3.
Course Title
4.
Faculty / Department
5.
Semester (First / Second / Summer)
6.
Academic Year
7.
Instructor / Academic Staff
2949605
3
Quantitative Methods in Economic
Analysis
Faculty of Economics
Trimester 1
2015
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
Period 1-2
Lecture 0 Intro to Econometrics
Lecture 1 SLR
Period
Period
Period
Period
Period
Period
Period
Period
3-4
5
6-7
8-9
10-11
12
13
14
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 8 Dummy
Lecture 9 Heteroskedasticity
Midterm Examination
Lecture 10 Dummy Dependent
Lecture 11 Basic Regressions
Lecture 12 Trends and Seasonality
Lecutre 13 Weakly Dependent
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

Powerpoint media

Electronics and website media hour/time/period/ 70 percent hour/time/period/ 20 percent hour/time/period/ 10 percent
–
5 percent
90 percent
5 percent
2

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
14.6.2 Assessment of work or classroom activities
14.6.3 Assessment of the assigned tasks
85 percent
–
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),
McGraw-Hill, 1998.
Ramanathan, R. Introductory Econometrics with Applications , (5e), Thomson,
2001
3

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

1
Orientation
2
QMEA
3
9:00-15:00
9:00-12:00
QMEA
10
17
9:00-12:00
Midterm
4
Tutor: 10:00-
12:00 Eviews
13:00-16:00
HW1
11
10:00-12:00
QMEA
Tutor: 13:00-
16:00 HW3
18
10:00-12:00
QMEA
Tutor: 13:00-
16:00 HW4
24
9:00-12:00
QMEA
31
9:00-12:00 Final
25
10:00-12:00
QMEA
5
19
6
9:00-15:00
QMEA
12 13
Queen Birthday 10:00-16:00
QMEA
10:00-16:00
QMEA
20
26 27
9:00-15:00 QMEA Tutor: 13:00-
16:00 HW6
7
9:00-15:00
QMEA
14
21
Tutor: 13:00-
16:00 HW5
28
8
Tutor: 13:00-
16:00 HW2
15
Tutor: 9:00-
16:00 Midterm
22
29
Tutor: 9:00-
16:00 Midterm
9
16
23
30
Eviews Homework: Thursday, August 6, 2015, 9:00 A.M. in class.
Homework 1:
Homework 2:
Friday, August 7, 2015, 9:00 A.M. in class.
Monday, August 10, 2015, 9:00 A.M. in class.
Homework 3:
Homework 4:
Homework 5:
Homework 6:
Thursday, August 13, 2015, 10:00 A.M. in class.
Thursday, August 20, 2015, 10:00 A.M. in class.
Monday, August 24, 2015, 9:00 A.M. in class.
Saturday, August 29, 2015, 9:00 A.M. to our staff.
6

7