Instructors: Amitabh Chandra
Faculty Assistant: Wendy Carney (617)384-9001
Intended as a continuation of API-201, this course equips students with an understanding of common tools of empirical analysis in policy applications. 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 selection effects; the advantages and disadvantages of experimental, quasi-experimental, and observational data; and instrumental variable 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.
The Z section uses calculus in order to cover more ground quickly. Fluency in derivatives and integration is assumed. Students who took API-201 (any section) should have received an A or A- to enroll in the Z section of API-202. May not be taken for credit with API-210.