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364-1026-00L  Identification and Causal Inference

SemesterFrühjahrssemester 2016
DozierendeJ.‑E. Sturm
Periodizität2-jährlich wiederkehrende Veranstaltung
LehrveranstaltungFindet dieses Semester nicht statt.
LehrspracheEnglisch


KurzbeschreibungMost policy relevant research questions in economics face the same challenge: How can we identify a causal impact of one variable on another, when we cannot use a controlled experiment? This course will teach econometric methods based on observational, i.e., non-experimental, data, cover a number of program evaluation methods, derive the underlying theory and discuss recent applications.
LernzielThe main objective of this course is to make PhD students familar with program evaluation methods such as Instrumental Variables Estimators, Regression Discontinuity Design and Matching Methods. The course will cover the underlying theory and show how these different methods relate to each other and how they differ in terms of the required identifying assumptions as well as data needs. Recent research papers will be discussed to illustrate their use. The goal of this course is to place students in the position to have a broad toolkit of quasi-experimental methods and to apply these methods in their empirical economic research.
LiteraturLecture notes will be provided and course will also draw on recent research papers. No specific text book is required.