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The aim of this course is to cover empirical strategies for applied micro research questions. Our agenda includes regression and matching, instrumental variables, differences-in-differences. Topics also will be focused are 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”.


This course does not involve any written exams. Students need to answer 5 assignment questions to complete the course, the answers will be in the form of written work in pdf or word. Students can write the answers in their own time. Each answer needs to be 200 words (1 Page). Once the answers are submitted, the tutor will check and assess the work.


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Course Credit: MIT

Course Curriculum

Topic I Regression Recap 00:30:00
Topic II Matching 00:20:00
Topic IV Instrumental Variables Constant Effects 00:40:00
Topic V Instrumental Variables (Take 2) 00:55:00
Topic VIII. Prediction and Confidence Intervals with a Large Number of Covariates 01:30:00
Topic X Analysis with Large Samples Sizes 00:20:00
Recitation 1 Expectations, Regression, and Controls 00:25:00
Recitation 2 Probits, Logits, and 2SLS 00:20:00
Recitation 3 LATEs, Differences, and Changes 00:25:00
Submit Your Assignment 00:00:00
Certification 00:00:00

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