Econometrics
Course No.: SMI1132130 Credit(s): 3
Course Description
Econometrics is not only an economics discipline which based on certain economic theory and statistical data, using mathematical, statistical methods and computer technology, to establish the econometric model as the main means and Study on the relationship of economic variables with random characteristics by quantitative analysis ,but also a compulsory core course for each specialty in economics.
Course Learning Outcomes
Understand the characteristics of modern economics, understand the status of economic quantitative analysis course in economics course system, and understand the role of economic quantitative analysis in the development of economic discipline and actual economic work. Master the basic theory of econometrics and have a conceptual understanding of the new development of econometric theories and methods.Have the foundation and ability to further study and apply econometrics theories, methods and models.
Relationship to Other Courses
The prerequisite for this course is Calculus, Linear Algebra, Mathematical Statistics and Economics.
Textbook and Reading Lists
Textbook:
Zinai Li, Econometrics (3rd edition). Higher Education Press, 2010.
Suggested reading lists:
(America)Guharatti, Econometrics Essentials (4th edition). Trans, Tao Zhang, Machinery Industry Press, 2010.
(America)Guharatti, Econometrics Fundamentals (4th edition). Trans, Jianping Fei, China Renmin University Press, 2005.
(America)Woodrich, Econometrics Introduction (4th edition). Trans, Jianping Fei, China Renmin University Press, 2010.
(America)Morey, Modern Econometrics. Trans, Jianping Fei, Machinery Industry Press, 2009.
(America)Stuttund, Applied Economic Metrology (6th edition). Trans, Jiang Du, Machinery Industry Press, 2013.
Course Assessment
Item | Title | Weighting (%) |
1 | Task in home | 10% |
2 | Test and Questions in class | 10% |
3 | Final exam | 80% |
Course Schedule
Week | Topics | Text |
1 | Introduction to Econometrics | Chapters 1 |
2-5 | Linear Regression Model | Chapters 2 |
6 -7 | Heteroscedastic Problems | Chapters 3 |
8-9 | Sequence Related Problems | Chapters 4 |
10 | Multiple Collinearity Problems | Chapters 5 |
11-13 | Random Explanatory Variable Problem | Chapter 6 |
14 | Model Setting Error Problem | Chapter 7 |
15 | Dummy Variable Model | Chapter 8 |
16-17 | Simultaneous Equation Model | Chapter 9 |
18 | Review | |