Wintersemester 2024/25
Kursangebot
BA: Empirische Wirtschaftsforschung / Ökonometrie
| Art | Zeitraum | Tag/Zeit | Raum | Dozent/in |
|---|---|---|---|---|
| VL (2 SWS) | 14.10.2024 - 03.02.2025 | wöch. Montag 14.00 - 16.00 | 3.06.H06 | Dr. Katrin Huber |
| UE 1 (2 SWS) | 16.10.2024 - 05.02.2025 | wöch. Mittwoch 12.00 - 14.00 | 3.06.H08 | Louis Klobes |
| UE 2 (2 SWS) | 16.10.2024 - 05.02.2025 | wöch. Mittwoch 14.00 - 16.00 | 3.06.H08 | Felix Degenhardt |
| UE 3 (2 SWS) | 17.10.2024 - 06.02.2025 | wöch. Donnerstag 10.00 - 12.00 | 3.06.S26 | Sophie Wagner |
Die Veranstaltung wird ergänzt durch das Schlüsselqualifikationsmodul B.SK.VWL.210/ B.SK.MET.210 "Einführung in die computergestützte Datenanalyse". Es wird vom Lehrstuhl für Methoden der empirischen Sozialforschung (Prof. Dr. Kohler) durchgeführt, nähere Informationen erhalten Sie hier.
Zu erbringende Leistung
- Klausur (90 Min) und aktive Teilnahme in der Übung
Anrechenbar als
- B.BM.VWL.420, B.VM.VWL.610, BWL: BA-P-602, BA-SK-W-1 (6 ECTS)
Voraussetzungen
- BA: Statistik dringend empfohlen
Inhalt
Ziel der Veranstaltung ist es, den Studierenden die Grundlagen der empirischen Wirtschaftsforschung zu vermitteln und eine Einführung in die Ökonometrie zu geben. Aufbauend auf der Vorlesung „Statistik“ sollen sie in die Lage versetzt werden, eine empirische Analyse (Thesen- und Modellbildung, Datenerhebung und -auswertung, Auswahl der Schätzmethode, Interpretation der Ergebnisse) selbständig durchführen zu können.
Themen
- Analyse ökonomischer Zusammenhänge
- Einführung in die Ökonometrie
- Schätzen, Testen und Interpretieren im einfachen und multiplen linearen Regressionsmodell
- Probleme und Erweiterungen des multiplen Regressionsmodells
- Policy Evaluation
- Einführung in STATA
Literatur
- Schira, J. (2012): Statistische Methoden der VWL und BWL. Pearson Studium.
- Wooldridge, J. (2016): Wooldridge (2016): Introductory Econometrics. A Modern Approach, Cengage Learning, Ohio.
- Kohler, U., Kreuter, F. (2012): Datenanalyse mit Stata. Oldenburg Verlag.
BA: Kolloquium
| Art | Zeitraum | Tag/Zeit | Raum | Dozent |
|---|---|---|---|---|
| K | 15.10.2024 - 04.02.2025 | Dienstag von 16.00-18.00 | 3.07.039 | Prof. M. Caliendo |
Das Bachelor-Kolloquium wird parallel zur Bearbeitung der Bachelor-Abschlussarbeit belegt.
Anrechenbar als
- B.FK.VWL.110, B.KO.PUW.110 (6 ECTS)
BA: Einführung in die computergestützte Datenanalyse (Schlüsselqualifikation)
Der Kurs wird vom Lehrstuhl für Methoden der empirischen Sozialforschung (Prof. Dr. Kohler) angeboten.
Weitere Informationen finden Sie in PULS und auf der Homepage des Lehrstuhles für Methoden der empirischen Sozialforschung von Prof. Dr. U. Kohler.
BA: Selbstreflexion und Planung (Schlüsselqualifikation)
Nähere Informationen finden Sie hier.
BA/MA: Applied Econometrics and Data Science with R
| Art | Zeitraum | Tag/Zeit | Raum | Dozent/in |
|---|---|---|---|---|
| Seminar | 16.10.2024 - 29.01.2025 | Mittwoch, 12:00 - 14:00 | 03.06.S27 | Felix Degenhardt, Sophie Wagner |
| Seminar | tbc 05.02.2025 | Mittwoch, 09:00 - 18:00 | 03.06.H01 | Felix Degenhardt, Sophie Wagner |
The course is held in English.
Requirements
- BA: Introduction to statistics
- BA: Introduction to econometrics
Credits for
- BVMVWL410 / BVMVWL420
- MA-E-210 / MA-E-230 / MA-M-210 / MA-M-320 / MA-M-410 / MA-W-210 / MA-W-220
Examination
- Regular seminar attendance; 2x R markdown script (extensively annotated R code incl. tables, graphs), once as intermediate submission (without grading) and once as graded examination and poster presentation (between 20 and 30 minutes incl. questions).
Content
This applied seminar has two main objectives: first, to provide students with practical skills in econometrics and data science, with a focus on using R. Students will learn how to manage data comprehensively, from data cleaning and wrangling to automating tasks for greater efficiency. Through practical sessions, they will be guided in conducting exploratory data analysis and creating visualizations, which are crucial for discovering patterns and insights in data.
In the second part of the course, students will be introduced to both unsupervised and supervised machine learning techniques, essential tools in contemporary econometric analysis. They will gain hands-on experience applying these methods to real-world data, learning how to integrate these techniques within economic contexts.
Throughout the semester, students will work on projects in small groups, with opportunities to present their progress during the course. At the end of the semester, the students will turn in their R Code and present their results in a poster presentation.
Topics
- Intro R and R-Markdown
- Data Wrangling and the tidyverse
- Automations in R
- ggplot2
- Spatial economics and maps
- Unsupervised and supervised Machine Learning
MA: Advanced Microeconometrics
| Art | Zeitraum | Tag/Zeit | Raum | Dozent/in |
|---|---|---|---|---|
| LE (2 SWS) | 14.10.2024 - 03.02.2025 | see Time Schedule | see Time Schedule | Prof. M. Caliendo |
| A-PR (2 SWS) | 15.10.2024 - 04.02.2025 | see Time Schedule | see Time Schedule | Aiko Schmeißer |
| A-PR (Stata) | 18.10.2024 - 07.02.2025 | see Time Schedule | see Time Schedule | Aiko Schmeißer |
The course is held in English.
Downloads
Credits for
- MA-B-300, MA-600 (9 ECTS)
Examination
- Written exam
- Active participation in practical sessions
- Oral presentations
Content
The aim of this lecture is to familiarize participants with microeconometric estimation techniques. The lecture will be complemented by a practical session.
Topics
- Multiple Regression
- Instrumental Variables
- Panel Data Methods
- Limited Dependent Variables
Literature
- Wooldridge, J. (2013): Introductory Econometrics. A Modern Approach. South-Western Cengage Learning.
- Cameron, C., and P. K. Trivedi (2005): Microeconometrics. Methods and Applications. Cambridge University Press, New York.
- Greene, W. H. (2012): Econometric Analysis. Pearson, Massachusetts.
- Kohler, U., Kreuter, F. (2008): Datenanalyse mit Stata. Oldenburg Verlag, München.
- Cameron, C., and P. K. Trivedi (2010): Microeconometrics Using Stata, Stata Press, College Station, Texas.
MA: Machine Learning
| Art | Zeitraum | Tag/Zeit | Raum | Dozent/in |
|---|---|---|---|---|
| SE | 14.10.2024 | Montag 9.00 - 18.00 | online event | Dr. Marica Valente |
| SE | 18.10.2024 - 01.11.2024 | wöch. Freitag 9.00 - 18.00 | online event | Dr. Marica Valente |
The course is held in English.
Credits for
- MA-W-210, MA-W-220, MA-M-320 (6 ECTS)
Examination
- Oral exam (50%)
- Term paper (50%)
Content
- Statistics, econometrics and machine learning.
- Draw contrasts with traditional approaches.
- How to use machine learning methods for prediction?
- How to use machine learning tools in R?
- Tree-based methods in R.
- Parametric methods.
- Analyze regression-based methods in R
- How to conduct empirical research?
- How to write an empirical paper?
MA: Forschungsseminar
| Art | Zeitraum | Tag/Zeit | Raum | Dozent/in |
|---|---|---|---|---|
| RS/C | 15.10.2024 - 04.02.2025 | see Syllabus | 3.06.S26 | Prof. M. Caliendo, Dr. Katrin Huber, Aiko Schmeißer |
This event is held in English.
Downloads
Requirements
- MA: Microeconometrics
- MA: Policy Evaluation
Credits for
- MA-E-210 / MA-E-230 / MA-M-320 / MA-M-410 / MA-W-210 / MA-W-220 (6 ECTS)
Examination
The final grade will be awarded based on the performance in the 2 referee reports (25%), in 1-2 presentations/discussions (25%), and the research proposal (50%).
Content
Title: "DIY: Research Idea Development Seminar"
This do-it-yourself (DIY) research seminar has two learning goals: In the first part, you will learn some essential skills for research in Economics, such as refereeing and discussing a paper, how to come up with own research ideas and how to write a research outline. We will provide you with an introduction into these skills. For two sessions a list of required readings is provided, you have to write a referee report on one of the papers and for each paper there will be one presentation and one discussion given by the students.
The second part of the course is for you to develop and work on your own research idea. At the end of the semester, you have to submit a research proposal. All ideas in the field of Labor Economics, Policy Evaluation, Population Economics, Political Economy, or related areas are welcome. We will support you with the development of ideas and also in case you want to request access to survey data (e.g. SOEP, BIBB BAuA) or admin data (e.g. IAB FDZ data). You are not expected to implement the idea in this course (no data work is required).
MA: Forschungskolloquium
| Art | Zeitraum | Tag/Zeit | Raum | Dozent |
|---|---|---|---|---|
| K | 15.10.2024 - 04.02.2025 | Dienstag von 18.00-20.00 | 3.06.S13 | Prof. M. Caliendo |
The Master's research colloquium is taken at the same time as the Master's thesis.
The course is held in English.
Creditable as
- MA-F-100, MA-FK-600 (3 ECTS)