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Faculty: Amitabh Chandra
|Term Start Date||1/23|
|Meet Day||M/W||10:15 AM - 11:30 AM||Littauer Bldg 280 (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.
Review Session: Friday 11:45am-1:00pm (Starr)