Ph.D. Econometrics Sequence

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The following describes the Economics and Agricultural and Resource Economics
Ph.D. Econometrics courses.

First year:

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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The first-year sequence covers the basics and is required of all Economics and ARE Ph.D. students.

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.

For academic year 2011-12:
Tentative: It is most likely that 240E will be taught and 240F will be not be taught.

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Instructors for 2010-11 are

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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