Causal Analysis

Dozent/in	Prof. Dr. Lukas D. Schmid
Veranstaltungsart	Vorlesung
Code	HS241131
Semester	Herbstsemester 2024
Durchführender Fachbereich	Wirtschaftswissenschaften
Studienstufe	Master
Termin/e	Do, 19.09.2024, 10:15 - 12:00 Uhr, 4.B55 Do, 26.09.2024, 10:15 - 12:00 Uhr, 4.B55 Do, 03.10.2024, 10:15 - 12:00 Uhr, 4.B55 Do, 10.10.2024, 10:15 - 12:00 Uhr, 4.B55 Do, 17.10.2024, 10:15 - 12:00 Uhr, 4.B55 Do, 24.10.2024, 10:15 - 12:00 Uhr, 4.B55 Do, 31.10.2024, 10:15 - 12:00 Uhr, HS 6 Do, 14.11.2024, 10:15 - 12:00 Uhr, 4.B55 Do, 21.11.2024, 10:15 - 12:00 Uhr, E.509 Do, 28.11.2024, 10:15 - 12:00 Uhr, 4.B55 Do, 05.12.2024, 10:15 - 12:00 Uhr, 4.B55 Do, 12.12.2024, 10:15 - 11:45 Uhr, HS 9 (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 of statistics and introduction to econometrics.
Sprache	Englisch
Anmeldung	Für den Besuch der Lehrveranstaltung / Übung wird die Einschreibung über die E-Learning-Plattform OLAT vorausgesetzt. Die Einschreibung ist vom 2. – 27. September 2024 möglich. Die Studierenden sind selbst dafür verantwortlich, die Anrechenbarkeit der Lehrveranstaltung an ihren Studiengang zu überprüfen.Direktlink zum OLAT-Kurs: https://lms.uzh.ch/url/repositoryentry/17577443407
Prüfung	***IMPORTANT*** In order to acquire credits, resp. 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 exam / 6 Credits (für Modul Causal Analysis (Vorlesung und Übung))
Hörer-/innen	Ja
Kontakt	lukas.schmid@unilu.ch