**ECONOMETRIC
FOUNDATIONS
ARE/ECN 239
Department of Economics**

SYLLABUS

**Instructor:**

Professor Colin Cameron

SSH Building 1124

accameron@ucdavis.edu

**Meeting:**

Tues-Thurs 12.10 - 1.30 pm Creuss
107

Friday 12.10 - 1.00 pm Olson 147

**Office Hours:**

Monday 12.30 - 2.00 p.m.

Wednesday 3.30 - 5.00 p.m.

**Teaching
Assistant:**

Yumeng Gu ymgu@ucdavis.edu

Office
hours:
Thursday 2:00 - 4:00 PM at SSH 0116.

**
Course Goals:**
To provide the probability and statistical foundation for
Ph.D. level
coursework in econometrics and in economics.

**Pre-requisites:** Upper division undergraduate sequence in
probability
and statistics, econometrics and linear algebra.

**Course
Outline:**

1. Probability theory: sets, basics, conditional probability CB 1.1-1.3 and **Supplemental
Notes**

2. Random variables, distributions CB
1.4-1.6

3. Transformations and expectations CB
2.1-2.2

4. Moments, moment generating functions CB
2.3-2.4

5. Commonly-used distributions, inequalities CB
3.1-3.6

6. Bivariate random variables: joint and marginal distributions,
transformations, conditional distributions
CB
4.1, 4.3, 4.2

7. Bivariate random variables: conditional distributions,
inequalities CB
4.4-4.5, 4.7

8. Multivariate random variables: CB 4.6
and **Supplemental
Notes**

9. Linear Regression **Supplemental notes**

10. Midterm exam

11. Random samples and properties of the sample mean CB 5.1-5.4

12. Convergence in probability, law of large numbers CB
5.5.1-5.5.2

13. Convergence in distribution, central limit theorem
CB 5.5.3-5.5.5

14. Maximum likelihood estimation CB
6.2.1,
6.3.1, 10.1

15. Maximum likelihood tests CB 10.3

16. Point estimation: Methods, Efficiency and Sufficiency
CB 7.1-7.3 (selected parts)

17. Point estimation (continued)

18. Hypothesis Testing CB
8.1-8.3
(selected parts)

19. Hypothesis Tests and confidence intervals
CB
9.1-9.3 (selected parts)

20. Monte Carlo procedures CB
4.8-4.9

**Required Material:**

**Casella and Berger (2002), Statistical Inference, Second
Edition,
Duxbury.
**This is a different text from past years. It is the most
commonly-used text
in Ph.D. economics courses. I follow it closely, especially for
probability.

We will cover chapters 1-5 in considerable detail and sequentially, and then selected parts of chapters 6-10, not sequentially.

**You need a hardcopy text. This will be your reference book
to go to when
needed in subsequent classes and in research. there is no
perfect text for
everyone.
**(1) Student's background varies enormously for this class,
and so will the
level of book best suited to the student.

(2) We have one quarter whereas the books are intended for a full-year course.

For less prepared students, in particular for those who have not taken an undergraduate upper-division sequence in probability and statistics such as UCD's STA 130A-B or 131A-C you need to have an undergraduate probability and statistics text that presents material more simply and with more examples. Old editions are fine and are cheap. Two such books are

Robert V. Hogg and Elliot Tannis, Probability and Statistics, Pearson.

Richard Larson and Morris Marx, Introduction to Mathematical Statistics and its Applications.

Some supplemental notes on selected topics will be posted on
Canvas under
Files / Supplemental Notes.

These will mostly be on statistical inference. For probability I
follow the
textbook very closely.

**Computer
Materials:**

Assignments will include both theory and data examples using
STATA.

STATA is available on both Econ and ARE computers, as well as
some campus
computers. it is used in subsequent econometrics classes.

For Economics students see https://www.ssds.ucdavis.edu/form/account-request
for account on the L&S Social Sciences Computational
Research Service
server Painter. See also https://www.ssds.ucdavis.edu/computing-0

For ARE students use ARE computer server.

For campus computers see virtual lab http://ats.ucdavis.edu/services/iet-virtual-lab/
and 93 Hutchison and 2016 SciLab if available - see http://computerrooms.ucdavis.edu/available/

If you choose to purchase Stata go to http://www.stata.com/order/new/edu/gradplans/student-pricing/
The
basic Stata/IC version is adequate.

To get started with Stata see http://cameron.econ.ucdavis.edu/stata/stata.html

Course material will be posted at http://canvas.ucdavis.edu with
slides,
assignments, and past exams filed under Files. I will also post,
after
each class, a pdf of what I write during the class.

**Course Grading:**

Assignments 21%

Best 7 out of 9.** Last assignment is compulsory.** Each
worth 3%.

Due Tuesdays October 1, 8, 15, 22, 29, November 12, 21 (Thurs),
26 (Tues), and Friday December 6 (4pm).

Midterm exam (closed book) 29%

Tuesday October 29 in class

Final exam (closed book) 50%

Tuesday December 10 1.00 - 3.00 pm **Comprehensive**.

**Academic Honesty: **Academic dishonesty is unfair to the
majority of
students who are honest. To that end the Davis Division of the
U.C. Faculty
Senate has the following policies and asks that these be
included in course
syllabi.

(1) All undergraduate and graduate course outlines (syllabi)
should list or
provide a link to the U.C. Davis Code of Academic Conduct which
is at
sja.ucdavis.edu/files/cac.pdf
. This provides many leading examples of academic misconduct.
You should read
this.

(2) One specific example of academic honesty is copying from
solutions to
assignments given in previous 239 courses.

(3) If an instructor has a reasonable suspicion of academic
misconduct, whether
admitted by the student or not, the instructor shall report the
matter to the
Office of Student Support and Judicial Affairs.

(4) The instructor has authority to determine a grade penalty
when academic
misconduct is admitted or is determined by adjudication to have
occurred; with
a maximum grade penalty of “F” for the course.

**Out of class collaboration: **You are allowed to work
together in
groups for the assignments, but each student must turn in an
individual
solution. Please indicate on the solution the names of the other
students you
worked with, if any that you worked with you on the problem set.
it is not a
violation of this policy to submit essentially the same answer
on an assignment
as another student, but it is a violation of this policy to
submit a close to
exact or exact copy.