1
课程详述
COURSE SPECIFICATION
以下课程信息可能根据实际授课需要或在课程检讨之后产生变动。如对课程有任何疑问，请
联系授课教师。
The course information as follows may be subject to change, either during the session because of unforeseen
circumstances, or following review of the course at the end of the session. Queries about the course should be
directed to the course instructor.
1.
课程名称 Course Title
经济管理中的实证方法 Empirical Methods in Economics and Management
2.
授课院系
Originating Department
信息系统与管理工程系 Department of Information Systems & Management Engineering
3.
课程编号
Course Code
MIS308
4.
课程学分 Credit Value
3
5.
课程类别
Course Type
选修课 Elective Courses
6.
授课学期
Semester
秋季 Fall
7.
授课语言
Teaching Language
中英双语 English & Chinese
8.
授课教师、所属学系、联系方
式（如属团队授课，请列明其
他授课教师）
Instructor(s), Affiliation&
Contact
（For team teaching, please list
allinstructors）
李崇，信息系统与管理工程系
Chong Li, Department of Information Systems & Management Engineering,
lic6@sustech.edu.cn
9.
实验员/助教、所属学系、联系
方式
Tutor/TA(s), Contact
无 NA
10.
选课人数限额(可不填)
Maximum Enrolment
（Optional）
2
11.
授课方式
Delivery Method
讲授
Lectures
习题/辅导/讨论
Tutorials
实验/实习
Lab/Practical
其它(请具体注明)
Other（Pleasespecify）
总学时
Total
学时数
Credit Hours
32
32
64
12.
先修课程、其它学习要求
Pre-requisites or Other
Academic Requirements
无 None
13.
后续课程、其它学习规划
Courses for which this course
is a pre-requisite
无 None
14.
其它要求修读本课程的学系
Cross-listing Dept.
无 None
教学大纲及教学日历 SYLLABUS
15.
教学目标 Course Objectives
经济和金融学中的许多研究混淆了相关性和因果关系或者不能干净的确定经济系统中相关变化或冲击的的因果效应。这是
由于对因果关系缺乏理解或者是没有一个巧妙的研究设计，内生性效应被当作外生性，因此不能得到一致性的估计。这堂
课将教会学生一套实证经济学研究中用来估计特定效应的常用微观计量工具箱。
A lot of the research in economics and finance confuses correlation with causality or cannot cleanly identify the causal
effects of certain variation or shocks in the economic system. This is due to the lack of understanding of causality or the
lack of delicate research design; endogenous factors are taken to be exogenous and thus has led to inconsistent
estimation. This class will provide students with a micro econometric toolbox that include a broad class of methods used
in empirical research to identify certain effects cleanly.
16.
预达学习成果 Learning Outcomes
在学习过程中，我们将更加强调每种方法背后的计量经济学直觉，而不是估计量的近似特征。我们将通过研究经济和金融
中实证研究，以及劳动经济学，产业组织，发展和公共财政等领域的例子来学习这些方法。我们将通过在真实数据上实现
每种方法，通常这些方法要求不同的计量经济学技巧。这里微观计量经济学意味着我们通常将更注重横截面和面板数据方
法。
During the learning process, we will put more emphasis on the econometric intuition behind each method, instead of
asymptotic properties of the estimators. We will learn these methods referring to examples of research mainly in the
field of economics and finance, and sometimes from other fields in economics including labour, industrial organization,
development, and public finance. We will try to implement each method on live data that requires manipulating and
analyse data using the various econometric techniques. The micro-econometric means that we will focus on cross-
sectional and panel data methods.
3
17.
课程内容及教学日历 （如授课语言以英文为主，则课程内容介绍可以用英文；如团队教学或模块教学，教学日历须注明
主讲人）
Course Contents (in Parts/Chapters/Sections/Weeks. Please notify name of instructor for course section(s), if
this is a team teaching or module course.)
理论和实验课（64 课时）：
1. 线性回归 (4 课时)
2. 线性面板数据模型 (4 课时)
3. 简单线性回归和面板数据回归实验（4 课时)
4. 空间面板数据分析 (4 课时)
5， 空间面板数据回归实验（4 课时）
6. 非参数方法：核密度估计 (4 课时)
7. 核密度估计实验（4 课时）
8. 因果关系和工具变量 (4 课时)
9. 自然实验 (4 课时)
10. 工具变量和自然实验实验课 （4 课时）
11. 断点回归设计 (4 课时)
12. 断点回归设计实验（2 课时）
13. 匹配方法 (4 课时)
14. 匹配方法实验（2 课时）
15. 离散变量模型 (4 课时)
16. 离散变量模型实验（2 课时）
17. 生存模型 (4 课时)
18. 生存模型实验（2 课时）
Lectures and Tutorial (64 credit hours)
1. Linear Regression (4 credit hours)
2. Linear Panel Data Model (4 credit hours)
3. Simple Linear Regression and Panel Data Regression Lab Session (4 credit hours)
4. Spatial Panel Data Analysis (4 credit hours)
5. Spatial panel data regression Lab Session (4 credit hours)
6. Nonparametric Methods: Kernel Density Estimation (4 credit hours)
7. Kernel Density Estimation Lab Session (4 credit hours)
8. Causation and Instrumental Variables (4 credit hours)
9. Natural Experiment (4 credit hours)
10. Instrumental Variables and Natural Experiment Lab Session (4 credit hours)
11. Regression discontinuity design (4 credit hours)
12. Regression discontinuity design Lab Session (2 credit hours)
13. Matching Method (4 credit hours)
14. Matching Method Experiment Lab Session (2 credit hours)
15. Limited Dependent Variable Model (4 credit hours)
16. Limited Dependent Variable Model Lab Session (2 credit hours)
17. Survival Analysis (4 credit hours)
18. Survival Analysis Lab Session (2 credit hours)
4
18.
教材及其它参考资料 Textbook and Supplementary Readings
Jeffrey Wooldridge, Econometric analysis of cross-section and panel data, MIT Press,
Massachusetts.
Joshua Angrist, and Jorn-Steffen Pischke, 2009, Mostly Harmless Econometrics, Princeton
University Press, New Jersey.
Cameron, C., and Travedi, P. (2005). Microeconometrics: Methods and Applications. Cambridge
University Press.
课程评估 ASSESSMENT
19.
评估形式
Type of
Assessment
评估时间
Time
占考试总成绩百分比
% of final
score
违纪处罚
Penalty
备注
Notes
出勤 Attendance
课堂表现
Class
Performance
小测验
Quiz
课程项目 Projects
平时作业
Assignments
期中考试
Mid-Term Test
40
期末考试
Final Exam
40
期末报告
Final
Presentation
20
其它（可根据需要
改写以上评估方
式）
Others (The
above may be
modified as
necessary)
20.
记分方式 GRADING SYSTEM
A. 十三级等级制 Letter Grading
B. 二级记分制（通过/不通过） Pass/Fail Grading
课程审批 REVIEW AND APPROVAL
21.
本课程设置已经过以下责任人/委员会审议通过
5
This Course has been approved by the following person or committee of authority
