__Ph.D. Econometrics Sequence__

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The following describes the Economics and Agricultural and Resource
Economics

Ph.D. Econometrics courses**.**

Fall: 239 Econometrics Foundations
(formerly 290).

Winter: 240A Econometrics Methods I

Spring: 240B Econometrics Methods II

Second year:

Fall: 240D Cross-section Econometrics

Winter: 240C Time Series Econometrics

Spring: 240E Topics in Time Series Econometrics

Winter: 240F Topics in Cross-Section Econometrics

[Note the reversal in ordering: 240D is usually taught the quarter
before 240C.]

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**

Much of the second-year sequence is also necessary for applied thesis research,

even though the courses are not formally required.

Time-series is split into essentials (240C) and topics (240E).

Similarly cross-section will be split into essentials (240D) and topics (240F).

For Economics students taking the econometrics field, the field is
240C, 240D and one of 240E/240F.

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**

For academic year 2010-11:

240E will not be taught. 240F will
be taught, in Spring.

This year only 240C is in Fall and 240D is in winter.

Tentative: It is most likely that 240E will be taught and 240F will be not be taught.

239 Richard Green

240A Oscar Jorda

240B Aaron Smith

240C Aaron Smith

240D Colin Cameron

240E Not taught

240F Colin Cameron

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The course descriptions in the course catalog are not perfect
representations of course content.

Here I have modified the 240A and 240B descriptions to provide a better
guide.

240C and 240D will most likely not cover all of the topics listed below.

After Spring 2008 we will most likely update the course catalog
descriptions.

**239 Econometric Foundations**

Lecture—3 hours; discussion—1 hour. Prerequisite: undergraduate
statistics.

Statistical foundations for econometrics.

**240A.** **Econometric Methods I**

Lecture—3 hours; discussion—1 hour. Prerequisite: Economics 290 and a
course in linear algebra or the equivalent.

Least squares, instrumental variables, and maximum likelihood
estimation and inference for single equation linear regression model;
finite sample and large sample theory; linear restrictions;
heteroskedasticity;
autocorrelation.

**240B**. **Econometric Methods II**

Lecture—3 hours; discussion—1 hour. Prerequisite: course 240A.

Maximum likelihood estimation and testing, nonlinear least squares,
systems of equations, simultaneous equation models, introductory time
series regression.

**240C. Time Series Econometrics **

Lecture—3 hours; discussion—1 hour. Prerequisite: course 240B. (Usually
taught after 240D).

Probability theory; estimation, inference and forecasting of time
series models; trends and non-standard asymptotic theory; vector time
series methods and cointegration; time series models for higher order
moments
and transition data; state-space modeling and the Kalman filter.

**240D. Cross Section Econometrics**

Lecture – 3 hours; discussion – 1 hour. Prerequisite: course 240B.
(Usually taught before 240C).

Estimation and inference for nonlinear regression models for
cross-section data; models for discrete data and for limited dependent
variables; models for panel data; additional topics such as bootstrap
and semiparametric regression.

**240E. Topics in Time Series Econometrics**

Lecture—3 hours; discussion—1 hour. Prerequisite: courses 240A and
240B.

Modern econometric techniques for time series data. Expand on topics
covered in Economics 240A, 240B, and 240C. Contents may vary from year
to
year.

**240F. Topics in Cross Section Econometrics**

Lecture—3 hours; discussion—1 hour. Prerequisite: courses 240A, 240B
and 240D.

Modern econometric techniques for cross-section data. Expand on topics
covered in Economics 240A, 240B, and 240D. Contents may vary from year
to year.

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