Applied Econometrics: Mostly Harmless Big Data
14.387 · Economics · Graduate · Fall 2014
Prof. Joshua Angrist, Prof. Victor Chernozhukov
This course covers empirical strategies for applied micro research questions. Our agenda includes regression and matching, instrumental variables, differences-in-differences, regression discontinuity designs, standard errors, and a module consisting of 8–9 lectures on the analysis of high-dimensional data sets a.k.a. “Big Data”.
The syllabus, on MIT OpenCourseWare
The full course — syllabus, assigned readings, problem sets, exams, and lecture notes — lives on OCW. These open the real thing:
Syllabus ↗
Course overview, grading, schedule
Readings ↗
The assigned reading list, session by session
Assignments ↗
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Attribution
Prof. Joshua Angrist, Prof. Victor Chernozhukov. 14.387 Applied Econometrics: Mostly Harmless Big Data. Fall 2014. Massachusetts Institute of Technology: MIT OpenCourseWare, https://ocw.mit.edu. License: CC BY-NC-SA 4.0.
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