Economic Data Analysis Software

Fall, 2011

陈媛媛

Office: School of Economics, Room 422

Tel: 65903121

Email:

Office Hours: Tuesday 2:30-3:30pm

TA： 谭新龙

Email:

Tel: 18801927734

Text:

应用Stata做统计分析 （美）汉密尔顿（Hamilton，L） 著；郭志刚 等译/2008年08月/重庆大学出版社

An Introduction to Modern Econometrics using Stata, Christopher Baum, Stata Press Publication

References:

Statawebsite: http://www.stata.com/

Stata webbook: http://www.ats.ucla.edu/stat/stata/webbooks/

Stata Data Source: http://www.stata-press.com/data/r11/g.html

Stata BBS: http://www.pinggu.org/BBS/

Reference Book for Basic Econometrics:

Stock, J.H and Watson, M.W, Introduction to Econometrics. 上海财经大学出版社

Wooldridge, J.M.(2003) Introductory Econometrics, 2nd Edition.清华大学出版社

Prerequisites:

Statistics and Econometrics skills are this course not only require programming but also economic interpretation of the program result.

Course Objective:

The purpose of this course is to guide how to use Stata to do basic data input, transformation, descriptive statistics, reporting tables and graphs, as well as econometric models, including general linear regression models, tests, binary choice models, and models of panel data estimation. The materials covered will be very useful for doing empirical economic analyses.

Section Arrangement:

Two sections will be conducted each week. In general, the first section of the week will mainly focus on particular topics with Stata Demos, the second will focus on student exercises. Problem sets and exercises are required each week and must be conducted in the computer room and turned in as the class finishes.

Grading:

Your score of the course will be based on your class exercises and problem sets, as well as midterm and final exam. All exams are close book and can only be conducted in the computer room. Grading Scheme is as follows:

Class Attendance and Problem Sets 30%

Midterm Project 35%

Final Exam 35%

Policies

I don’t accept any excuse for the missing of exams and quizzes unless you can provide proof of emergency such as serious illness. If you miss the exam or quiz for any reason that does not qualify as a proven emergency, you get zero. You can work with your classmates on the homework assignments, but you are not allowed to copy someone else’s work. TA has the right to do not grade the late homework assignment turned in.

Academic Dishonesty

Academic dishonesty by the student code of conduct includes cheating on the assignments or exams; plagiarizing; altering; forging, or misusing a University academic record; taking, acquiring, or using test materials without faculty permission; and acting alone or in cooperation with another to enhance a grade, etc. A minimum penalty for academic dishonesty is a grade of zero. Other penalties may include a F in course and a complaint to university authorities so that they act consequently with the corresponding university policy.

Course Outline and Schedule (Subject to Change)

Data Organizing and Tranformation
1st week / ¨  Introduction of Stata
¨  Basic Command
2nd week / ¨  Data Input and Output
3rd -4th week / ¨  Data Transfermation
5th -6th week / ¨  Organizing Panel Data
7th week / ¨  Exercise on Panel Data
8th week / Midterm
Linear Regression Model and Test
9th week / ¨  OLS regression and test
10th week / ¨  Regression output
11th week / ¨  Regression with indicator variables
12th week / ¨  Heteroskedasiticity
13th week / ¨  IV estimator
Nonlinear Regression
14th week / ¨  Models with limited dependent variable
Panel Data Models
15th week / ¨  Panel Data Models
Programming
16th week / ¨  Programming (Including loops and sub program definition)
17th week / ¨  Install outside program: qreg, IV qreg, GMM etc.
TBD / Final exam