Duke University - Department of Economics - Fall 2008
Economics 139D/239D: Introductory Econometrics
September 3, 2008
This course introduces students to the statistical tools that economists use to test models, evaluate quantitatively policy
changes, learn about economic behavior, and more generally study the relation between variables. The goal is to learn
enough theory and get enough practice to be able to do some simple but sensible data analysis on your own. Also, we
will insist on the *motivations* guiding the use of different econometric tools. Why should we use a tool instead of
another? What are the assumptions needed for each of these tools to work well? We will see many real-life applications,
but this course is, above all, an introduction to econometric TECHNIQUES, which means that there will be a LOT of
algebra and statistics to go through. Unfortunately, technicalities ARE necessary to discriminate between sound analysis
and descriptive accounts (sometimes interesting, too often sloppy and superficial). The course will also introduce
students to the use of STATA, a powerful and widely used statistical package that can be used for both very simple and
very complex applied work. Several problem sets will involve data analysis with STATA using actual data. A good
working knowledge of probability theory, statistics, and calculus is necessary for this course.
Prerequisites:
Econ 55D, Math 32 and Stats 103.
Lectures:
Instructor:
Tu Th 8:30 AM - 9:45 AM (Social Sci 139)
Alessandro Tarozzi - taroz@econ.duke.edu
Office hours: in 202 Social Sciences, Monday 8PM-10PM.
Teaching assistants:
E-mail
Office hours
Anumeha Goel
anumeha.goel@duke.edu
Geoffrey Yih
Eric Pince
Andrew Lee
g.yih@duke.edu
eric.pince@duke.edu
andrew.lee@duke.edu
Thursday
Friday
Wednesday
Thursday
1:00PM-2:30PM
11:30AM-1:00PM
noon-2PM
10AM-noon
SocSci 105
SocSci 107
SocSci 02A
SocSci 02A
Tuesday
4PM-6PM
Old Chem 01
Sections:
(all in Social Sciences 229)
Tu
Tu
Tu
W
W
W
Th
Location
11:55AM - 12:45PM
3:05PM - 3:55PM
4:40PM - 5:30PM
11:55AM - 12:45PM
1:30PM - 2:20PM
6:15PM - 7:05PM
4:40PM - 5:30PM
Eric
Andrew
Geoff
Anumeba
Andrew
Geoff
Eric
Handouts and grades will be available on the course’s web page (http://courses.duke.edu), so please check
regularly the course web page for announcements and course material.
Stock and Watson, “Introduction to Econometrics”, Second Edition
Addison-Wesley, 2006, ISBN: 0321278879.
Supplementary online material: http://wps.aw.com/aw_stock_ie_2.
Required Textbook:
Econometric Package: STATA, which is available on the computers in 229 Social Sciences as well as in
the Basement (Room 01) of the Old Chem Building. If you wish, you can purchase your
own copy of Intercooled Stata (see http://www.stata.com/order/new/edu/gradplan.html).
The cost is $95 for a one-year license, and $155 for a perpetual license. See also
http://www.socsci.duke.edu/it/compute/stata.html.
Other textbooks for undergraduate econometrics courses (not required, just for your reference):
Goldberger, “Introductory Econometrics”, Harvard University Press (Short, great for intuition, but requires a certain degree
of confidence with the material to be appreciated);
Wooldridge, “Introductory Econometrics: A Modern Approach”, South-Western College Publishing (excellent “standard”
textbook, very widely used).
In case you would like to have more advanced references (e.g. graduate-level textbook), just ask me!
RULES, RULES, RULES!!!! It is your responsibility to read and understand the “rules of the game”.
1. GRADING:
1. Midterm 1
2. Midterm 2
3. Final (comprehensive)
35%
25%
40%
The relative weight of each exam is fixed and with the exception indicated in point 2 below, under no
circumstance will be changed.
2. There will be no makeup midterms, and there are NO exceptions to this rule. If you miss a midterm, and you
can document that you have a good excuse for missing the midterm, the weight of the missed exam will be placed
on the final.
3. All exams are comprehensive, so you will be responsible for all the material covered until the exam.
4. All exams will be closed books, but you will be allowed to use a “cheat sheet” that summarizes most results.
5. If you think that an exam should be re-graded, you have to submit in writing the detailed reasons why you think
this is the case. Take into account that if you ask for re-grading, the whole exam will be checked again. You have to
submit requests for midterms’ re-grading within two weeks from the day the exams are returned.
6. Class attendance is strongly encouraged, but it is not required. I know that 8:30AM is not a very “popular” time for
an econometrics class, but 8:30AM is when we have been assigned to begin. It is distracting to have latecomers
enter the room after class starts. If you plan to attend, please be in class on time.
7. There will be 6-8 problem sets, part pencil & paper, part to be solved using Stata. Problem sets are NOT
mandatory and grades will NOT be recorded. However, you are strongly encouraged to turn in one or two
exercises (no more than two) from each problem set, which will then be carefully graded (again, without recording
the grade) and returned to you. This is a way for you to test your understanding of the material on problems that
follow a format analogous to what you should expect on exam day (indeed most problem sets will be based on past
exams), and to familiarize yourself with how your exams will be graded. You will see that partial credit is always
granted for partial but meaningful answers, but full credit requires complete and rigorous reasoning.
8. For any problem related to Stata and problem sets you should talk to your TA. But please do use my office
hours for everything related to the content of the course. If you have doubts about the materials, do not wait
until a few hours before the exam! You are also welcome to use my office hours to discuss extra-material we do not
discuss in class or any other matter related or unrelated to the course.
ADVICE (free and disposable)
1.
The whole course builds on what we will cover in the first three weeks of class. During these weeks, we will
review important concepts from statistics and we will introduce a few ones which will likely be new to you. If you
understand well this material, the rest of the course will be fairly straightforward.
2.
Believe it or not, failing this course is exceedingly hard. If you work hard enough, you may be able to get a Cor less, but that’s not easy, and only few have succeeded in the past. The vast majority of you will most likely do
better or much better than that. However, and more seriously, excellence is also hard to achieve and requires a
good working knowledge of the econometric theory that we will cover in class. More than half of exam
questions are usually empirical, but theory and proofs always account for part of the exam too.
3.
In my experience, the best way to learn how to do understand theory and learn how to do proofs is to
replicate independently the proofs we see in class and to solve independently problem sets and past
exams (of which many will be posted on blackboard during the course). If you simply come to class and/or review
your notes without checking whether you can replicate the crucial steps without looking at solutions you will likely
find out on exam day that… you cannot replicate the crucial steps without looking at solutions.
4.
Questions are welcome during class. Always keep in mind that if you are paying attention and you find that you
are missing something in what I am saying, any or all of the following are likely to be true: 1. others in the class are
as confused as you are; 2. The instructor has made a mistake; 3. The instructor has tragically mispronounced some
words, or he has invented new words altogether in his goofy mental translation from Italian.
5.
Just to re-iterate… use my and your TA office hours if you want to review material, and start doing so
immediately if you feel lost!
Course Outline
The course outline is tentative (hopefully not too much). Please keep in mind that there will be NO MAKE-UP
MIDTERMS, and that both midterms have been scheduled during class time, so please make sure you do not
have other commitments on those dates.
Part I - Statistics Review
1.
Aug 26 Tu
Introduction, course descriptions & “rules”.
+ A very brief & quick introduction to Stata:
2.
Aug 28 Th
Statistics review: (Ch. 2) random variables, continuous & discrete; probability
function and CDF, expected value & variance. Relationship between two
random variables: marginals, joint, conditional;
3.
Sep 2 Tu
Statistics review: (Ch. 2) law of iterated expectations (L.I.E.), Covariance,
Independence, uncorrelation. What iid means; estimators & estimates; the sample
mean.
4.
Sep 4 Th
Statistics review: (Ch. 2 & 3) properties of estimators; bias, variance (efficiency).
5.
Sep 9 Tu
Statistics review: (Ch. 2 & 3) Consistency, Asymptotic Normality; a simple Central
Limit Theorem.
6.
Sep 11 Th
Statistics review: (Ch. 3) Tests and Confidence Intervals.
Part II - Econometrics proper: the use of Ordinary Least Squares to study the causal relationship between
different economic variables.
7.
Sep 16 Tu
Conditional expectations: why we care, and how to estimate them. Ordinary
Least Squares with only one conditioning variable. Terminology & formulae. (Ch. 4)
8.
Sep 18 Th
The OLS assumptions & properties of the estimators: unbiasedness. OLS
again, variance, and Asymptotic normality. (Ch. 4)
9.
Sep 23 Tu
Asymptotic normality. R-squared: what it is, and what it is not. (Ch. 4)
10.
Sep 25 Th
Applications. Tests and C.I. A simplifying assumption: homoskedasticity, its
consequences, and the Gauss-Markov theorem (OLS is BLUE). (Ch. 5)
11.
Sept 30 Tu
OLS and nonlinearities, Dummy variables, interactions. (Ch. 5, 8)
12.
Oct 2 Th
1st Midterm. (IN CLASS, DURING CLASS TIME)
13.
Oct 7 Tu
OLS in multivariate regressions. Multicollinearity. Omitted variable bias. (Ch. 6)
14.
Oct 9 Th
Properties of OLS with multiple regressors, R-squared, adjusted R-squared.
Tests & C.I. Inference with multiple regression. Joint hypothesis. (Ch. 6, 7)
Oct 14 Tu
Fall Break
Oct 16 Th
Assessing Studies Based on Multiple Regression (Ch. 9)
15.
Part III - Beyond OLS
16.
Oct 21 Tu
Nonlinearities again, and limited dependent variables. Linear Probability
Model, logit and probit. (Ch. 8, 11)
17.
Oct 23 Th
Logit & Probit. How do we estimate the coefficients now? What about
standard errors, R-squared and so on? Maximum Likelihood Estimation. (Ch. 11)
18.
Oct 28 Tu
MLE, and Regression with limited dependent variables at work. (Ch. 11)
19.
Oct 30 Th
MLE again, pseudo-R2. (Ch. 11)
Nov 4 Tu
2nd Midterm. (IN CLASS, DURING CLASS TIME)
20.
Nov 6 Th
Analysis of panel data.(Ch. 10)
21.
Nov 11 Tu
When the regressors are endogenous: estimation using Instrumental
Variables. (Ch. 12)
22.
Nov 13 Th
Instrumental variables. (Ch. 12)
23.
Nov 18 Tu
Instrumental variables. (Ch. 12, Ch. 13.7, Appendix 13.4)
24.
Nov 20 Th
TBA
25.
Nov 25 Tu
TBA
Nov 27 Th
Thanksgiving recess.
26.
Dec 2 Tu
TBA
27.
Dec 4 Th
Q&A
Dec 13 Saturday
9:00AM – 12PM
Final Examination