Applied econometrics: mostly harmless big data
Master
In Maynard (USA)
Description
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Type
Master
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Location
Maynard (USA)
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Start date
Different dates available
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".
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Start date
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Course programme
Lectures: 2 sessions / week, 1.5 hours / session
14.382 Econometrics I is the prerequisite for this course.
Students are expected to do the readings. In addition, there are three graded problem sets, which must be submitted on time to be graded for credit (the course is graded pass / fail). The atmosphere is informal, but we ask you to put all electronic devices away when class is in session. We encourage questions and class discussion—we'll be asking you questions too!
Angrist, J. D., and J. S. Pischke. Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press, 2009. ISBN: 9780691120355. [Preview with Google Books]
Basic and review material for the first two-thirds of the course come mostly from this book. A few core and frontier articles are also listed for each topic.
This course is co-taught by Prof. Joshua Angrist and Prof. Victor Chernozhukov. Prof Angrist teaches topics I–VII. Prof. Chernozhukov's section begins at topic VIII.
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Applied econometrics: mostly harmless big data
