Econometrics _ syllabus
Course Code: 102 072 030 Teaching object: sophomores
Credits: 3 Course type: platform class categories, compulsory
Prerequisite: higher mathematics, probability and statistics, economics
I. Course Overview
Econometrics is the application of mathematical and statistical reasoning and other measurement techniques, based on the actual statistics on the economic relationship between economic theory suggests conducted an economic analysis of the number of subjects.
The basic econometric theory is mainly to teach this class, method and principles and how to apply theories and methods to solve practical problems.
The focus is on model and explain how to apply the principles of statistical inference techniques to solve practical problems related.
Second, the course learning objectives
a) understanding of the number of economic analysis in economics curriculum system in place, the number of economic analysis to understand the development of economic discipline and economic role in the actual work;
b) to master the classical theory and econometric methods;
c) to establish and apply a simple econometric model of the real relationship between the number of actual economic phenomena analysis;
d) be able to use statistical analysis software for simple empirical analysis;
e) understand the basis of certain relatively complex econometric model, with the ability to have economic theories, methods and models for further study and application of measurement.
Third, the curriculum and hours distribution
| Week |
Teaching Content |
|
| the first week |
Introduction and basic knowledge of econometrics |
|
| the second week |
STATA underlying operating on the demo machine |
|
| The third week |
Knowledge of statistical probability of return (Quiz) |
|
| the fourth week |
Simple linear regression model (1): Basic Concepts and Estimation |
|
| fifth week |
Simple linear regression model (2): interval estimation and hypothesis testing |
1st job |
| Sixth Week |
Simple linear regression model (3): prediction, modeling and fitting STATA estimated demonstration |
|
| Week Seven |
Multiple linear regression model to estimate: estimates range from simple linear regression model to |
|
| Eighth Week |
Multiple linear regression models to infer |
2nd job |
| Week Nine |
Mid-term exam (not sure whether online teaching will affect the progress, temporarily put here) |
|
| The tenth week |
Model specification and modeling |
|
| Week 11 |
Nonlinear regression model |
3rd job |
| Week Twelve |
The use of dummy variables |
|
| Week 13 |
Heteroscedasticity |
|
| For Week |
Metering topics: Endogenous problems and solutions |
4th job |
| Week 15 |
计量专题：Logit与Probit模型 |
|
| 第十六周 |
计量专题：DID估计 |
|
| 第十七周 |
复习及答疑 |
|
注：根据学生掌握的进度和学校放假安排，教学内容会适当调整。
四、 教学方式
课题理论讲解+上机操作
五、 教学过程中应用到的技术手段与工具
PowerPoint，STATA
六、 教材与参考书目
1 计量经济学及其应用（第2版），杜江，李恒，贾文， 机械工业出版社
2.1 【中文版】计量经济学导论：现代观点（第5版），杰弗里.M.伍德里奇，张成思，人民大学出版社
2.2 【英文版】清华经济学系列英文版教材:计量经济学导论:现代方法(第6版)，杰弗里·M.伍德里奇，清华大学出版社）
3.1 【中文版】计量经济学导论(第三版)，詹姆斯·H·斯托克 (James H.Stock)、 马克·M·沃森 (Mark M.Watson)，人民大学出版社
3.2 【英文版】世纪高教·经济学英文版教材:计量经济学(第3版)(英文版)，詹姆斯·H.斯托克 (James H.Stock)、 马克·W.沃森 (Mark W.Watson)，格致出版社
4.【中文版】计量经济学原理（第四版），R.卡特•希尔 (R.Carter Hill) (作者), 威廉•E.格里菲思 (William E.Griffiths) (作者), 瓜伊•C.利姆 (Guay C.Lim) (作者), 邹洋翻译，东北财经大学出版社
七、 学生成绩评定办法（暂定）
- 平时成绩（30%）：包括考勤（20%），作业分（80%）
- 期中考试（30%）
- 期末考试（40%）