Causal Analysis

Dozent/in	Prof. Dr. Lukas D. Schmid
Veranstaltungsart	Vorlesung
Code	HS191152
Semester	Herbstsemester 2019
Durchführender Fachbereich	Wirtschaftswissenschaften
Studienstufe	Master
Termin/e	Do, 19.09.2019, 10:15 - 12:00 Uhr, 4.B55 Do, 26.09.2019, 10:15 - 12:00 Uhr, 4.B55 Do, 03.10.2019, 10:15 - 12:00 Uhr, 4.B55 Mi, 09.10.2019, 12:15 - 14:00 Uhr, 4.B47 Do, 10.10.2019, 10:15 - 12:00 Uhr, 4.B55 Mi, 16.10.2019, 12:15 - 14:00 Uhr, 4.B47 Do, 17.10.2019, 10:15 - 12:00 Uhr, 4.B55 Do, 24.10.2019, 10:15 - 12:00 Uhr, 4.B55 Do, 31.10.2019, 10:15 - 12:00 Uhr, 4.B55 Do, 14.11.2019, 10:15 - 12:00 Uhr, 4.B55 Do, 21.11.2019, 10:15 - 12:00 Uhr, 4.B55 Do, 28.11.2019, 10:15 - 12:00 Uhr, 4.B55 Do, 05.12.2019, 10:15 - 12:00 Uhr, 4.B55 Do, 12.12.2019, 10:15 - 11:30 Uhr, HS 3 (Prüfung) Do, 12.12.2019, 10:15 - 11:30 Uhr, HS 8 (Prüfung)
Umfang	2 Semesterwochenstunden
Turnus	weekly
Inhalt	This course provides an introduction to causal inference. We will primarily be concerned with how and when we can make causal claims from empirical research. In the lecture, we will discuss statistical techniques and the necessary assumptions to make causal statements. In the tutorials, we will learn these techniques by actually implementing them and discussing the plausibility of the assumptions. After this class, you should understand and be able to apply the standard set of causal inference tools in the social sciences. These include randomized experiments, matching, instrumental variables, regression discontinuity designs, fixed effects regressions, and differences-in-differences.
Lernziele	1. Understand the concept of causation 2. Make distinctions between observational and experimental studies 3. Define the assumptions required to make causal claims from quantitative data 4. Implement a range of statistical methods which aim to estimate causal effects 5. Use the R statistical software in applied research 6. Critically evaluate the use of causal inference designs used in published work
Voraussetzungen	Introduction to of statistics and introduction to econometrics.
Sprache	Englisch
Anmeldung	To attend the course / exercise, enrolment via the e-learning platform OLAT is required. Registration is possible from 2 to 27 September 2019. The students themselves are responsible for checking the creditability of the course to their degree programme. Direct link to the OLAT course: https://lms.uzh.ch/url/RepositoryEntry/16616980794
Leistungsnachweis	***IMPORTANT*** In order to take part in the examination, registration via the UniPortal within the examination registration period is REQUIRED. Further information on registration for the examination: www.unilu.ch/wf/pruefungen
Abschlussform / Credits	Written examination (75%), Take home exam (25%) / 6 Credits
Hörer-/innen	Ja
Kontakt	lukasdavid.schmid@unilu.ch