API-202 Z: Empirical Methods II

Semester: Spring

Credit: 4.0

Syllabus: Click here for syllabus

Faculty: Amitabh Chandra


Day Time Location
Term Start Date 1/23
Meet Day M/W 10:15 AM - 11:30 AM Belfer 200 Starr Aud (HKS)


Intended as a continuation of API-201, this course equips students with an understanding of common tools of empirical analysis in policy applications, with a particular emphasis on causal inference. Much of the learning will take place through hands-on analysis of data sets. The course will cover regression analysis, including multiple regression, dummy variables, and binary dependent variables; as well as program evaluation, including experimental, quasi-experimental, and observational techniques. The final part of the course includes an integrative exercise in which students will have the opportunity to assess empirical analysis in an open-ended and professionally realistic project.

Prerequisite: API-201 or equivalent. May not be taken for credit with API-210.

Enrollment in API-202Z requires a grade of B+ or better in API-201Z or a grade of A- or better in API-201ACD. Students who earn exemption from API-201, are eligible to enroll in API-202Z. There are no exceptions to this rule.

Students are responsible for all material covered in section and in recitation.

Review Session: Friday 11:45am-1:00pm (Starr)

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