| Dozent/in |
Prof. Dr. Lukas D. Schmid |
| Veranstaltungsart |
Vorlesung |
| Code |
HS261070 |
| Semester |
Herbstsemester 2026 |
| Durchführender Fachbereich |
Wirtschaftswissenschaften |
| Studienstufe |
Master |
| Termin/e |
Do, 17.09.2026, 10:15 - 12:00 Uhr, HS 5
Do, 24.09.2026, 10:15 - 12:00 Uhr, Inseliquai 12b INQ Auditorium HSLU
Do, 01.10.2026, 10:15 - 12:00 Uhr, HS 5
Do, 08.10.2026, 10:15 - 12:00 Uhr, HS 5
Do, 15.10.2026, 10:15 - 12:00 Uhr, HS 5
Do, 29.10.2026, 10:15 - 12:00 Uhr, HS 5
Do, 05.11.2026, 10:15 - 12:00 Uhr, HS 5
Do, 12.11.2026, 10:15 - 12:00 Uhr, HS 5
Do, 19.11.2026, 10:15 - 12:00 Uhr, HS 5
Do, 26.11.2026, 10:15 - 12:00 Uhr, HS 5
Do, 03.12.2026, 10:15 - 12:00 Uhr, HS 5
Do, 10.12.2026, 10:15 - 11:45 Uhr, Inseliquai 12b INQ Auditorium HSLU (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 |
Binding registration takes place via the UniPortal; see notes below in the «Proof of Performance» field.
For course information and materials, registration on the OLAT e-learning platform is required from 31 August – 25 September 2026. The students themselves are responsible for verifying the course’s creditability towards their degree program.
Direct link to the OLAT course: https://lms.uzh.ch/url/RepositoryEntry/17903616188
|
| Leistungsnachweis |
***IMPORTANT*** To receive course credit and earn academic credits, registration via the Uni Portal within the regular exam registration period (29 October – 12 November 2026) is MANDATORY.
Late registrations and withdrawals will not be accepted. Once the registration period has ended, participation in the course is MANDATORY. If the course is not completed without a valid reason and without proper withdrawal (including supporting documentation; see the Exam Guidelines), the course will be considered failed (grade 1). |
| Abschlussform / Credits |
Written exam / 6 Credits (für Modul Causal Analysis (Vorlesung und Übung))
Written exam / 6 Credits (für Modul Weitere Studienleistungen im Bereich Volkswirtschaftslehre)
Written exam / 6 Credits (für Modul Weitere Studienleistungen im Bereich Volkswirtschaftslehre)
Written exam / 6 Credits (für Modul Master-Veranstaltungen an der Wirtschaftswissenschaftlichen Fakultät)
|
| Hörer-/innen |
Ja |
| Kontakt |
lukas.schmid@unilu.ch |