Intermediate Econometrics II
Lecture
Main Campus
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 panel regression, machine learning, and time series. Among the topics covered are: estimation and linear regression recap; panel data methods including differences in differences, event studies, fixed-effect models, synthetic control; machine learning methods including supervised and unsupervised learning; uses of machine learning as a tool in econometrics and causal inference; statistical decision theory including econometrics with misaligned preferences; time-series models including state-space models and dynamic stochastic general equilibrium models.
ECON 271
Units: 5
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Typically Offered
Not Available
Grading Basis
Letter or Credit/No Credit
Class Level
Graduate
Instructional Mode
In Person
Gen Ed Requirement(s)
None
