__Suggested Statistics and Mathematics
Courses for Ph.D. Econometrics and Economic Theory__

The following, written July 2017,
lists potential courses in the Statistics and Mathematics
departments that may be useful for Ph.D. Economics students
interested in furthering their skills and background in
econometrics beyond the 240 sequence, and for economic theory,
especially microeconomic theory.

Before taking any of these courses you should consult with
relevant economics faculty and, for the course to count
towards your degree, the Director of Graduate Studies.

__STATISTICS__

It is best to take Ph.D. level courses or the more advanced
Masters courses in Statistics. The basic Masters courses are
if anything less advanced than the Ph.D. econometrics courses.

For the Masters in Statistics (see https://www.stat.ucdavis.edu/grad/ms.html

For the Ph.D. in Statistics see https://www.stat.ucdavis.edu/grad/phd.html

Department of Statistics courses are
listed at http://catalog.ucdavis.edu/programs/STA/STAcourses.html

Probability Theory

Statistics 235A-C (Probability
Theory) cross-listed as Mathematics 235A-C. Prerequisite is
Mathematics 125B (Real Analysis) and Math 135A (probability
theory) or Statistics 131A (probability theory in the more
advanced of the two upper-division probability and statistics
sequences).

This is an advanced course.

Note that Statistics 200A
(Introduction to Probability Theory) is too light. It is for
MA students and overlaps too much with ECN/ARE 239.

**Statistical Theory**

Statistics 231A-C (Mathematical
Statistics I-III) is the core PhD sequence.

Note that Statistics 200B-20C
(Introduction to Mathematical Statistics I-II) is too light.
It is for MA students and overlaps too much with ECN/ARE 239
and 240A.

**Other Statistics Courses that may
be useful for econometrics**

Statistics 208 (Statistical Methods
in Machine Learning) is a Masters level course but is okay as
there is no other machine learning course.

Statistics 225 (Clinical Trials) requires Biostatistics 223 (Generalized Linear Models) which is a required Biostatistics PhD course.

Statistics 233 (Designed
Experiments) may be too easy (requires Statistics 131C)
and specialized. Statistics 225 may be better.

Statistics 240A (Nonparametric Inference) is a
PhD level course.

Statistics 241 (Asymptotic Theory of
Statistics) is a PhD level course.

Statistics 243 (Computational
Statistics) has less lower prerequisites but is required for
the Statistics PhD.

For mathematics requirements see https://www.math.ucdavis.edu/grad/gpc/degree_req/

Math courses are listed at http://catalog.ucdavis.edu/programs/MAT/MATcourses.html

And detailed syllabi are at https://www.math.ucdavis.edu/courses/syllabi/

Real Analysis

Mathematics 125A-B (Real Analysis) is
the upper division undergraduate s sequence which requires
Math 25 (Advanced Calculus) which requires Math 21C
(Calculus).

Mathematics 201A-C (Analysis) is a
PhD in mathematics core requirement so is quite advanced.

**Other Mathematics that may be
useful for economic theory and/or econometrics
**

The following are courses of potential interest, depending on ones’ planned economics specialty. Talk to relevant economics professors for guidance.

This list is not
exhaustive.

Mathematics 108
(Introduction to
Abstract Mathematics) This emphasizes proving theorems.

Mathematics 133 (Mathematical Finance)

Mathematics 135A (Probability)

Mathematics 135B
(Stochastic
Processes)

Mathematics 145
(Topology)

Mathematics 168
(Optimization)

Mathematics 206 (Measure
Theory)
Pre-requisite is Math 125B.

Mathematics 215A-C
(Topology)

Mathematics 239
(Differential
Topology)

Mathematics 235A-C
(Probability
Theory) Same as Statistics 235A-C.

Mathematics 236A-B
(Stochastic
Dynamics and Applications). Course 235A-C recommended so quite
advanced.

A. Colin Cameron / UC-Davis Economics / http://cameron.econ.ucdavis.edu