| 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. |
| 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 |