Intermediate Econometrics II
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Course Description
Second course in the PhD sequence in econometrics at the Economics Department (as Econ 271) and at the GSB (as MGTECON 604). This course presents modern econometric methods with a focus on regression. Among the topics covered are: linear regression and its interpretation, robust inference, asymptotic theory for maximum-likelihood und other extremum estimators, generalized method of moments, Bayesian regression, high-dimensional and non-parametric regression, binary and multinomial discrete choice, resampling methods, linear time-series models, and state-space models. As a prerequisite, this course assumes working knowledge of probability theory and statistics as covered in Econ 270/MGTECON 603. Prerequisites: Econ 270/MGTECON 603 or equivalent.
Grading Basis
ROP - Letter or Credit/No Credit
Min
3
Max
5
Course Repeatable for Degree Credit?
No
Course Component
Discussion
Enrollment Optional?
Yes
Course Component
Lecture
Enrollment Optional?
No
Does this course satisfy the University Language Requirement?
No
Courses
ECON271
is a
prerequisite
for:
Programs
ECON271
is a
completion requirement
for:
- (from the following course set: )