Lehre am Institut für Wirtschaftspolitik

• Vertiefung und Einübung der Vorlesungsinhalte, Methoden der empirischen Wirtschaftsforschung
• Bearbeitung von Übungsaufgaben.
• Termin Gruppe 1 (Übungstermin): Freitag 14.30-16.00 Uhr, VII-002
• Termin Gruppe 2 (Testattermin): Freitag 11.00-12.30 Uhr, VII-201

Vergleiche ansonsten Literatur zur Vorlesung »Empirische Wirtschaftsforschung«.

• Aufgaben, Ziele und Prinzipien der empirischen Wirtschaftsforschung
• Daten
• Wirtschaftsindikatoren
• Ökonometrische Grundlagen und Methoden
• Kausalität und Identifikation
• Anwendungen

• Bauer, Fertig, Schmidt (aktuelle Ausgabe): Empirische Wirtschaftsforschung, Springer.
• Winker (aktuelle Ausgabe): Empirische Wirtschaftsforschung, Springer.
• Wooldridge (aktuelle Ausgabe): Introductory Econometrics, CENGAGE Learning Custom Publishing.

• Im Rahmen des Moduls »Empirische Wirtschaftsforschung« werden im WiSe 2026/27 Testate durchgeführt.
• Es können bis zu 15 Punkte (25 Prozent des Modulergebnisses) erzielt werden, die dem Ergebnis der Hauptklausur (45 Punkte) hinzugerechnet werden (60 Gesamtpunkte).
• Die Teilnahme ist freiwillig.
• Die Testate finden im Rahmen des Übungstermins der Gruppe 2 jeweils von 11:00 bis 12:30 Uhr im Raum VII-201 statt. Die genauen Termine werden zu Semesterbeginn über Stud.IP bekannt gegeben.
• Eine verbindliche Anmeldung erfolgt über die Stud.IP Gruppe „Übung zu Empirische Wirtschaftsforschung“.
• Weitere Informationen werden zu Veranstaltungsbeginn bekanntgegeben.

Im Seminar wir ein aktuelles wirtschaftspolitisches Thema auf der Grundlage von Veröffentlichungen in wissenschaftlichen Fachzeitschriften erschlossen und reflektiert. Details werden im Seminarsteckbrief bekanntgegeben.

Bitte auf Ankündigung in Stud.IP achten.

Prüfer: Prof. Dr. Thomsen

1. Empirisches Arbeiten: Forschungsdesigns
2. Korrelation vs. Kausalität
3. Grundlagen der Evaluation
4. Grundlagen der Kausalitätsanalyse
5. Randomisierte Experimente
6. Quasi-Experimente und Natürliche Experimente

Literaturempfehlungen:

• Bauer, Thomas K., Michael Fertig und Christoph M. Schmidt (2009). Empirische Wirtschaftsforschung: Eine Einführung. Springer: Heidelberg.
• Angrist, Joshua D. und Pischke, Jörn-Steffen (2015). Mastering 'Metrics: The Path from Cause to Effect. Princeton University Press.
• Angrist, Joshua D. und Pischke, Jörn-Steffen (2009). Mostly Harmless Econometrics. Princeton University Press.

Grundlagenliteratur:

Wooldridge, Jeffrey M. (2009). Introductory Econometrics: A Modern Approach. Vierte Auflage. Cengage Learning: Mason.

Die Betreuung erfolgt themenbezogen auf individueller Basis.

Within the doctoral seminar on economic policy, current and prospective doctoral students present their own research project (preferably) on a topic in economic policy (e.g. unemployment, education, migration, climate change, etc.) and discuss it with the other seminar participants. The focus is on quantitative-empirical work.

Information for prospective doctoral students (master students): Prospective doctoral students work on an independent research question using scientific methods and present the results. Close supervision of the research progress by the supervisors is an essential part of the seminar. The seminar is an excellent preparation for a later research and academic career (doctoral studies). Prospective doctoral students are expected to have good to very good knowledge of empirical research and quantitative, econometric methods. Data access can be provided by the Institute of Economic Policy (e.g. data from statistical offices, Socio-Economic Panel (SOEP) etc.). Prospective doctoral students write a term paper of about 10-15 pages plus appendices, explanations, codes. They have compulsory attendance at meetings and present their work.

The seminar takes place weekly during the semester. Depending on the number of registered students, the rhythm of the seminar may be irregular.

Further information about the seminar for PhD students

Further information about the seminar for master students

The laboratory will first introduce the problem, motivation, state of the art, techniques and solutions. We will introduce services and techniques for the production and publication of analysis-ready machine-processable scientific knowledge as well as the machine-assisted reuse of scientific knowledge. During the hands-on second part of the laboratory, students will apply the learned techniques to articles authored by research staff at selected university institutes or, if applicable, also to articles the students have co-authored themselves. Finally, the laboratory will showcase how machine-assisted use of scientific knowledge can support advanced knowledge presentation (visualization) and knowledge synthesis in research.

(1) Ghaemi et al. (2025) "Advancing Scientific Knowledge Retrieval and Reuse with a Novel Digital Library for Machine-Readable Knowledge" https://doi.org/10.1145/3726302.3730134 (pre-print https://arxiv.org/abs/2511.08476);

(2) Stocker et al. (2025) "Rethinking the production and publication of machine-readable expressions of research findings" https://doi.org/10.1038/s41597-025-04905-0.

Link: https://knowledgeloom.tib.eu

This is an interdisciplinary laboratory open to interested students from all institutes and faculties. The laboratory is of particular relevance to students in disciplines that employ (statistical) data analysis methods and open computing environments such as Python and R. Research staff, e.g. doctoral students, are welcome to attend the introductory lectures. The hands-on second part of the laboratory is limited to approximately 20 students.

Mo. 14:00 - 17:30 in Raum 235, Gebäude 3703.

Literature

• Cameron, A. C., & Trivedi, P. K. (2005). Microeconometrics: Methods and Applications. Cambridge: Cambridge University Press.
• Cunningham, S. (2021). Causal Inference: The Mixtape. New Haven: Yale University Press.

Note: Both textbooks are useful references for the main topics of this course. Further required readings will be listed in the syllabus.

Die Prüfung besteht aus einer schriftlichen Replikationsstudie (70%) mit anschließender mündlicher Prüfung (30%).

Dieser Kurs verschafft Teilnehmenden eine Übersicht über (1) das Publizieren in Fachzeitschriften, (2) die Struktur solcher Fachartikel, (3) dem Review-Prozess inklusive des Lesens und Verstehens eines Decision Letters eines Editors und (4) dem Verfassen eines Response Letters auf ein solches Schreiben.

Wright, M., Ketchen Jr, D. J., & Clark, T. (Eds.). (2020). How to get published in the best management journals. Edward Elgar Publishing.

Paltridge, B., & Starfield, S. (2016). Getting published in academic journals: Navigating the publication process. University of Michigan Press.

Prüfer: Prof. Dr. Thomsen

Leistungsnachweis: Präsentation

Within the doctoral seminar on economic policy, current and prospective doctoral students present their own research project (preferably) on a topic in economic policy (e.g. unemployment, education, migration, climate change, etc.) and discuss it with the other seminar participants. The focus is on quantitative-empirical work.

Information for prospective doctoral students (master students): Prospective doctoral students work on an independent research question using scientific methods and present the results. Close supervision of the research progress by the supervisors is an essential part of the seminar. The seminar is an excellent preparation for a later research and academic career (doctoral studies). Prospective doctoral students are expected to have good to very good knowledge of empirical research and quantitative, econometric methods. Data access can be provided by the Institute of Economic Policy (e.g. data from statistical offices, Socio-Economic Panel (SOEP) etc.). Prospective doctoral students write a term paper of about 10-15 pages plus appendices, explanations, codes. They have compulsory attendance at meetings and present their work.

The seminar takes place weekly during the semester. Depending on the number of registered students, the rhythm of the seminar may be irregular.

Further information about the seminar for PhD students

Further information about the seminar for master students