Syllabus for Econometrics 01: 220:322:09 Fall 2012

Commenti

Transcript

Syllabus for Econometrics 01: 220:322:09 Fall 2012
Syllabus for Econometrics
01: 220:322:09
Fall 2012
Lecture: 6:40 PM - 8PM, Mondays and Wednesdays
ARC 107, Busch Campus
Instructor: Xuelian Zhang
Office: New Jersey Hall, Room 423
Email: [email protected]
Office hour: Noon – 2PM on Fridays (tentative) or by appointment
Pre- requisites:
Introduction to Microeconomics (220:102)
Introduction to Macroeconomics (220:103)
Calculus I (640:135)
Introduction to Statistics (960:211 or 960:285)
Textbook
James H. Stock & Mark W. Watson, Introduction to Econometrics, 3rd edition,
Addison-Wesley 2011, ISBN 0-13-800900-7
This textbook is REQUIRED for the course. It should be available in the Rutgers’
bookstore. There is a website associated with the textbook. There you can find
solutions to selected exercises at the end of each Chapter of the book. The link is
http://wps.aw.com/aw_stock_ie_3/178/45691/11696965.cw/index.html
Reading Complement
Jeffrey M. Wooldridge , Introductory Econometrics: A Modern Approach, 4th edition,
South-Western 2009, ISBN 978-0-324-66054-8.
This book is NOT REQUIRED for the course. It serves as a reading complement, and
it is up to you if you would like to purchase it or not.
Software:
The software package used in this course is STATA. STATA is available on the
computers in the Rutgers labs and through Rutgers Apps. You can also purchase a
version of STATA from the following website:
1
http://www.stata.com/order/new/edu/gradplans/gp-direct.html
No prior knowledge of this software package is assumed. It will be introduced in class.
However, a STATA tutorial file can be found on the companion website of the
textbook
(http://wps.aw.com/aw_stock_ie_3/178/45691/11696965.cw/index.html),
which is quite helpful for you to get a general idea of STATA.
Grading
The final course grade is based on a final exam (35%), three in-class quizzes (45% in
total), and some take-home assignments (20% in total):
Note:
1. The exact cutoff points for course letter grades will be determined after the
final exam.
2. Students must receive a grade of C or better in this course to fulfill
requirements for an economics major.
3. General course announcements, course material and exam results will be
posted on Sakai. You are responsible for checking Sakai frequently to ensure
you won’t miss any important course information.
4. No extra-credits.
Quizzes and Exams: (Closed-book. No Make-ups.)
Three quizzes and one final exam will be given. All exams will be closed-book. All
exams will be cumulative.
The date and time for the final exam is DEFINITE, but the dates for the in-class
quizzes are APPROXIMATE.
Quiz 1 is scheduled for Oct 1 (tentative), Quiz 2 is scheduled for Oct 22
(tentative), Quiz 3 is scheduled for Nov 19 (tentative). Please, do not plan to be
away or miss class for any reason based on these APPROXIMATE dates since the
actual dates depend heavily on how fast we cover material.
Final exam is scheduled for Monday, Dec 17, from 8PM - 11PM. Please, do not
plan to leave the University before the final exam period is officially over.
The University posts the final exam dates and times at
http://scheduling.rutgers.edu/fallfinals.shtml
You are responsible to verify the date and time for the final exam.
Cell phones, laptops or other electronic devices cannot be used during the exams! You
can only use a basic calculator. You will not be allowed to use graphing calculators or
calculators that allow you to store formulas and other information.
2
Students who miss an exam/quiz will get a grade of zero and there will be no
make-ups, except in case of documented emergency. In this case, you must contact
me within 24 hours of the exam period (after this, no make-ups will be given). If you
are unable to sit for the scheduled exams, you are encouraged to take another section.
IMPORTANT: Cheating is totally prohibited! The University has established
severe penalties for cheating. The University’s policy on academic integrity is found
at http://academicintegrity.rutgers.edu/policy-on-academic-integrity.
Final Remarks:
Firstly, you are expected to be at every class. Late arrivals and early departures are not
encouraged. If you expect to miss one or two classes (NOT EXAMS!) due to illness
or a family emergency, please use the University absence reporting website
https://sims.rutgers.edu/ssra/ to indicate the date and reason for your absence. An
email is automatically sent to me.
Secondly, I strongly suggest you spend enough time in reviewing materials covered in
class, do not leave everything to the night before the exam when it’s too late. Please
ask questions in class or in office hours if you have any problems or
misunderstandings.
Thirdly, the best way to learn is by doing. I recommend attempting as many exercises
at the end of each chapter of the text as you can.
Course learning outcomes:
Students who successfully complete Econ 322 should be comfortable with basic
statistics and probability. They should be able to use a statistical/econometric
computer package to estimate an econometric model and be able to report the results
of their work in a nontechnical and literate manner. In particular a student who
successfully completes Econ 322 will be able to estimate and interpret linear
regression models and be able to distinguish between economic and statistical
importance. They should be able to critique reported regression results in applied
academic papers and interpret the results for someone who is not trained as an
economist.
3
Tentative course outline
Date
Sep 5
Sep 10 – Sep 24
Sep 26 – Oct 17
Oct 22 – Nov 12
Nov 14 – Dec 12
Dec 17
Topics
Introduction
Review of Probability Theory and Statistics
Quiz 1 (Oct 1, tentative)
Linear Regression with One Regressor
Hypothesis Test and Confidence Intervals in Single
Regression
Quiz 2 (Oct 22, tentative)
Linear Regression with Multiple Regressors
Hypothesis Test and Confidence Intervals in Multiple
Regressions
Quiz 3 (Nov 19, tentative)
Regression with a Binary Dependent Variable ( selected
topics )
Instrumental Variable Regression ( selected topics )
Final Exam : 8PM - 11PM
Chapters
Ch 1
Ch 2, Ch 3
Ch 4, Ch 5
Ch 6, Ch 7
Ch 11, Ch 12
Lecture Outline
The following is a list of lecture topics. I have indicated the relevant Chapters of the
text for each topic. This should be used as a rough guide for your reading. The lecture
material will be greatly enhanced for you if you are up to date with your readings.
1. Introduction (Chapter 1)
• Brief introduction to course
• What is Econometrics?
• Sources and types of data
2. Review of Probability Theory and Statistics (Chapter 2 and Chapter 3)
• Random Variables
• Review of probability concepts
• Moments of population distribution
• The joint distribution
• Marginal probability distribution, conditional distribution and conditional
mean
• Independence
• Covariance and correlation
• The Normal, chi-squared, t and F distributions
• Random sampling and the distribution of the sample average
• Large-sample approximations to sampling distributions
4
•
Hypothesis tests and confidence intervals concerning the population mean and
difference of population means
3. The Simple Linear Regression Model (Chapters 4, 5)
• The econometric model
• The least squares principle
• Estimating the econometric model and interpreting the results
• The properties of the least squares estimates of an econometric model
• Inference and prediction in the Simple Linear Regression Model
• Interval estimation and hypothesis testing
4. The Multiple Linear Regression Model (Chapters 6, 7)
• The econometric model with more than one independent variable
• The least squares principle
• Estimating the MLRM and interpreting the results
• Inference and prediction in the MLRM
• Single and joint hypothesis tests of the parameters of the econometric model
• Multicollinearity
5. Selected Topics in Regression Analysis
• Regression Models with Binary Dependent Variable (Chapter 11)
• Instrumental Variable Estimation (Chapter 12)
5

Documenti analoghi

Department of Economics

Department of Economics between economic and statistical importance of the results. Students should be able to critique reported regression results in applied academic papers and interpret the results for someone who is n...

Dettagli