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TOKT1127 — ECONOMETRICS 1 | Chương trình đào tạo NEU

TOKT1127 — ECONOMETRICS 1

Credits
3
Self-study hours
90
Showing intake
K68-2026

Course description

Econometrics is the application of statistical techniques to economic models in an effort to achieve numerical results and to verify economic theorems. The purpose of this course is to introduce students to the theory and application of econometric methods. It covers the basic tools of estimation and inference in the context of the single-equation linear regression model, deals primarily with least squares methods of estimation. The course emphasizes the intuitive understanding and practical application of these basic tools of regression analysis, as distinct from their formal theoretical development. Course material is presented predominantly in scalar terms. The practical part introduces the R language as the main tool.

Course requirements

Requirements for Final Examination

Attendance score must be at least 5 (according to University regulations).

See Appendix 2, Rubric 1 for attendance evaluation.

Requirements for Class Attendance

Participate at least 80% of total class

In cases of absence due to force majeure, students are expected to actively acquire the required knowledge through materials provided by the instructor and other assigned readings.

Requirements for In-class Behaviour

Respect between students and instructors.

Contribute to lesson, take notes and answer questions

Read assigned materials in advance, do Homework

Do not disturb the others in class

Do not eat, use cell phone in class

Laptop, ipad are allowed if needed in practicing, calculating only.

Teaching plan

Week 1

Chapter 1. Introduction - Introduction - Basic concepts - Revision of statistics
References
- Syllabus - [1] Chapter 1 - [2] Chapter 1 Revision for statistics
Activities
- Introduce syllabus, software - Assignment requirement - Review, summary statistics
Assessment
- Discuss

Week 2

Chapter 2. Single Regression - Regression model - Least squares estimate - Introduce R
References
[1] Chapter 2 [2] Chapter 2
Activities
Lecture Q and A Introduce Excel and R result
Assessment
- Homework - Discuss, class exercises

Week 3

Chapter 2. (cont.) - Goodness of fit - Inference on regression - Practice R
References
[1] Chapter 2 [2] Chapter 2
Activities
- Lecture - Q and A - Introduces function in Excel and R - Homework check
Assessment
- Homework - Discuss, class exercises

Week 4

Chapter 2. (cont.) - Binary independent variable - Further issues - Practice R
References
[1] Chapter 2 [2] Chapter 2
Activities
Probability distributions and parameters review
Assessment
- Homework - Discuss, class exercises

Week 5

Chapter 3. Multiple Regression model - Model and Matrix form - Least square estimate
References
[1] Chapter 3 [2] Chapter 3, 4
Activities
Lecture, Q and A Homework check Illustrate by Excel or R
Assessment
- Homework - Discuss, class exercises

Week 6

Chapter 3. (cont.) - Inference on T-distribution - Practice R
References
[1] Chapter 3 [2] Chapter 3, 4
Activities
Lecture, Q and A Homework check Illustrate by Excel or R
Assessment
- Homework - Discuss, class exercises

Week 7

Chapter 3. (cont.) - Inference on F-distribution - Inference in dependent variable - Practice R
References
[1] Chapter 3 [2] Chapter 3, 4
Activities
Lecture, Q and A Homework check Illustrate by Excel or R
Assessment
- Homework - Discuss, class exercises

Week 8

Chapter 4. Functional Form - Linear and logarithm form - Polynomial and interaction
References
[1] Chapter 3, 4 [2] Chapter 6, 7
Activities
Lecture, Q and A Homework check
Assessment
- Homework - Discuss, class exercises

Week 9

Chapter 4. (cont.) - Dummy variable model - Forecast, introduce machine learning - Practice R - Discussion on Group work topic
References
[1] Chapter 3, 4 [2] Chapter 6, 7
Activities
Lecture, Q and A Homework check Illustrate by Excel or R
Assessment
- Homework - Discuss, class exercises

Week 10

Chapter 5. Variable Selection - Steps in econometrics - Residual and Influent points
References
[1] Chapter 9, 10 [2] Chapter 12, 13 [4] Chapter 9, 10, 11
Activities
Lecture, Q and A Homework check
Assessment
- Homework - Discuss, class exercises

Week 11

Chapter 5. (cont.) - Multicollinearity - Heteroscedasticity - Model validation - Practice R
References
[1] Chapter 10 [2] Chapter 13 [4] Chapter 11
Activities
Lecture, Q and A Homework check
Assessment
- Homework - Discuss, class exercises

Week 12

Chapter 6. Regression Results - Model in general - Estimation process - Data collection
References
[1] Chapter 10 [4] Chapter 15
Activities
Lecture, Q and A Homework check
Assessment
- Homework - Discuss, class exercises

Week 13

Chapter 6. (cont.) - Result presentation - Result interpretation - Limited, truncated dependent variable Group work submit
References
[1] Chapter 13 [3] Chapter 10 [4] Chapter 14
Activities
Lecture, Q and A Homework check
Assessment
- Homework - Discuss, class exercises

Week 14

Computer test Feedback to Groupwork results
Activities
Lecture, Q and A Homework check

Week 15

Summary and Revision - Introduce to SRM exam
Activities
Summary, answer questions
Final Examination (Entire content / Specific chapters)
References
Multiple choice
Activities
See Appendix 1 (Exam Matrix)

Learning resources

  • 1. Course Books (bắt buộc có ít nhất 01 giáo trình được Đại học phê duyệt, không quá 02 giáo trình, ưu tiên xuất bản trong vòng 5 năm gần nhất), đánh số để kết nối với Bảng 4
  • Regression Modeling with Actuarial and Financial Applications — Edward W. Frees, Cambridge, 2010
  • 2. References
  • Introductory Econometrics - A Modern Approach — Jeffrey M. Wooldridge, 6th Edition, 2016
  • Introduction to Linear Regression Analysis — Douglas C. Montgomery, 5th Edition, 2012
  • Applied Econometrics with R — Christian Kleiber, Springer, 2008
  • SOA Exam SRM Study Manual — Runhuan Feng et al, ACTEX Learning, 2018
  • Standard lecture notes/slides …
  • 3. Other resources available at the University Library