14.36 Advanced Econometrics
Emphasizes econometric theory, methods, and applications using regression, instrumental variables, differences-in-differences, regression discontinuity designs, machine learning and big data sets, and problems related to standard errors and statistical inference. Includes a project with a theoretical, written and data-analytic component. Familiarity with Stata or a similar statistical programming language recommended. Students taking graduate version complete additional assignments.
This class has 14.32 as a prerequisite.
Lecture occurs 10:30 AM to 12:00 PM on Mondays and Wednesdays in E51-395.
This class counts for a total of 12 credits.
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