Paul H. Nitze SAIS Bologna Center
Johns Hopkins University
Econometrics(EC.39)
Spring 2008 (Wednesdays, 3:00pm to 4:50pm)
Contact Information
Prof. David Cheong
Rm. 211
Email: dcheong@jhubc.it
Phone: 051 2917 824
Office Hours: Tuesdays and Wednesdays, 5:00-7:00 pm or by appointment
Course Overview
What is the effect of an additional year of education on an individual’s hourly wage? How do
minimum wages affect employment? Is there a wage gap between men and women? These
are typical questions for which econometrics can provide answers by using statistical
methods. This course aims to provide you with the standard econometric tools that can be
used to read and conduct empirical research. It emphasizes the three basic concepts in
econometrics: quantifying uncertainty with confidence intervals, using regression to infer
causal relationships, and using regression for prediction. The course combines an in-depth
study of the assumptions, implications, and limitations of simple and multiple linear
regression models with practical applications of econometric methods using the Stata
statistical software package. The course will also cover certain elementary time-series topics,
panel data models, instrumental variables estimation, simultaneous equations, and limited
dependent variable models.
Textbook
The textbook for this course is Jeffrey Wooldridge’s Introductory Econometrics (3rd. edition,
2006). This text presents material at the advanced undergraduate/basic graduate level and
provides a good background of the fundamentals and applications of econometrics.
Prerequisites
EC.20 (Statistical Methods for Business & Economics) or equivalent. The material in this
course assumes that students are comfortable with calculus, properties of summations, and
basic concepts in probability and statistics. Appendices A, B, and C of the textbook provide
a concise review of the necessary mathematics used in this course.
Course Schedule
The table below contains dates for lectures, distribution and submission of problem sets, the
mid-term exam, and econometric project deliverables. The date of the final exam will be set
by the Registrar. For each lecture, students are required to prepare by reading the relevant
textbook chapter(s).
Class
Dates
13-Feb
20-Feb
Lecture Topics and Readings
INTRODUCTION & BRIEF STATISTICAL REVIEW
Wooldridge Chapter 1 & Appendices A, B, and C
THE SIMPLE LINEAR REGRESSION MODEL
Wooldridge Chapter 2
Problem Set 1 Distributed
27-Feb
MULTIPLE REGRESSION ANALYSIS: Estimation
Wooldridge Chapter 3
Problem Set 1 Due
5-Mar
MULTIPLE REGRESSION ANALYSIS: Inference
Wooldridge Chapter 4
Econometric Project Proposal Due
12-Mar
MULTIPLE REGRESSION ANALYSIS: Asymptotics and Further Issues
Wooldridge Chapters 5 and 6
Problem Set 2 Distributed
2-Apr
MULTIPLE REGRESSION ANALYSIS: Dummy Variables and Heteroskedasticity
Wooldridge Chapters 7 and 8
Problem Set 2 Due and Project Proposal Due
9-Apr
Mid-Term Exam
SPECIFICATION AND DATA PROBLEMS, INTRODUCTION TO TIME-SERIES ANALYSIS
Wooldridge Chapters 9 and 10
Problem Set 3 Distributed
16-Apr
23-Apr
ISSUES IN TIME-SERIES OLS
Wooldridge Chapters 11 and 12
Problem Set 3 Due
30-Apr
PANEL DATA METHODS
Wooldridge Chapters 13 and 14
7-May
INSTRUMENTAL VARIABLE (IV) ESTIMATION AND TWO-STAGE LEAST SQUARES (2SLS)
Wooldridge Chapter 15
14-May
SIMULTANEOUS EQUATIONS, LIMITED DEPENDENT VARIABLE MODELS
Wooldridge Chapters 16 and 17
Problem Set 4 Distributed and Econometric Project Draft Report Due
21-May
COURSE REVIEW and PRESENTATIONS
Problem Set 4 Due
Course Evaluation
Problem Sets (20%)
There will be four problem sets assigned during the semester. Each will make up 5% of your
final grade. Problem sets will be distributed in class or by email; solutions will be posted on
CIAO. You will have one week to complete each problem set once it is assigned. You are
encouraged to work in groups, but each student should submit an individual solution set.
Midterm Exam (40%)
This course will have one midterm exam, comprising 40% of your final grade. Sample
problems for this exam will come from the odd-numbered problems in Wooldridge (for
which detailed solutions are available on the textbook webpage), the questions on the
problem sets, and other examples provided and done either in class or at the review sessions.
Econometric Project (40%)
Throughout the semester; you will each be working on an econometric project—where you
choose your topic, gather your data, and carry out an analysis. Your project should address
an economic question (no projects on the mating habits of fruit flies or statistical analyses of
text patterns in Shakespearean sonnets, interesting as these may be) for which there is data
available. Your job will be to analyze the data using the appropriate econometric techniques
and to write a report of between 15-20 pages, including tables and graphs. Chapter 19 of
Wooldridge is an excellent guide on how to carry out an econometric project. For a sample
of how to write and format an Econometrics project paper, please refer to:
http://www.union.edu/PUBLIC/ECODEPT/dvorakt/43/sample_paper.htm
The three main deliverables will be: i) A one-page project proposal (due April 2, 2008), ii)
A draft project report with initial results and analysis (due May 14, 2008), and iii) The
final project report (due May 25, 2008). Please abide by this schedule as late submissions
will be penalized. The five best projects will be presented at our last lecture.
Review and Lab Sessions
There will be review sessions in which you will go over the lecture material and practice
solving problems. There will also be lab sessions in the BC computer lab on how to use Stata
for data management and econometric analysis. These sessions are meant to familiarize you
via simple exercises with the relevant Stata commands and programming techniques used in
econometrics. The current version of Stata is v.10, however v.9 and v.8 can be used.
Communication
As the class meets only once a week, I will use email to make any urgent announcements or
carry on any prematurely-ended class discussions. So, please check your email regularly. If
you wish to contact me, my coordinates and contact details are on the first page of this
syllabus. You are welcome to see me during my office hours without an appointment. If you
would like to see me at other times, please email me to fix an appointment. Email is the
most efficient means of communicating with me outside of class or office hours.