Economics (all)
Important information about Economics courses
Bachelor's student can choose their economics courses from the bachelor's level courses only. Master's level courses are usually not open to bachelor/
Exchange students from other schools and departments may only attend economics lectures if they meet the prerequisites. Please contact the exchange coordinator, Ms. Christiane Cischinsky (cischinsky@uni-mannheim.de). Bachelor’s level seminars are usually only open for economics students.
Master's student can choose their economics courses freely from the elective modules available at the department, as long as you fulfill the prerequisites for each course. The core modules (E601–603 and E700–703) are not open to exchange students. If your home university agrees you are also allowed to attend bachelor's level courses.
Exchange students from other schools and departments may contact the exchange coordinator, Mr. Sebastian Herdtweck (econgrad@uni-mannheim.de), to check their eligibility.
Detailed information can be found on the department's websites:
ECTS credits: 6 or 7
6 ECTS for 1 semester hour per week exercise and 7 ECTS for 2 semester hours per week exercise
The second goal is to present the empirical tools used to test related economic theories in the context of China and to discuss the empirical relevance of related theories. We will emphasize the conceptual issues and basic statistical techniques, such as instrumental variable strategy and differences-in-differences-type strategies. Students will also get familiar with several widely used Chinese datasets and learn how to conduct empirical analysis.
Our third goal is to introduce frontier researches to students. We will draw on some recent academic papers from international trade, labor economics, finance, development economics, macroeconomics, and economic growth, which will allow students to have a good understanding of cutting-edge researches and help students outline future research questions.
- Working with text: regular expressions/
regex – text parsing – parts-of-speech tagging – web-scraping – dictionaries - Text as data: – word-embeddings (from bag-of-words to word2vec/
GloVe) – topic models – sentiment analysis – text-similarity - ML with text (in Python): – ML fundamentals – BERT – text-classification We will use recent economics and management science literature applications to illustrate methods and concepts.
Form and usability of the module: Elective module for M.Sc. Economics in study track 1: Economics and study track 2: Competition and Regulation Economics
Responsible teacher of the module: Prof. Kathrine von Graevenitz, Ph.D.
Cycle of offer: Regular
ECTS-Credits: 2.5
Teaching method: Lecture (1) and practical exercises
Workload: 75 working hours, including 14 hours of class time and 61 hours for independent studies, programming project, and project presentation
Course language: English
Prerequisites: E601–603 (or equivalent), coding experience in R is beneficial
Grading: Presentation (15 min, 70%), presentation slides and code (30%), the course will be graded pass/
Goals and contents of the module: This short-course provides an introduction to spatial data. We will discuss what is special about spatial data, introduce software to handle it, and learn to merge data and create simple maps. We will do simple spatial econometric analyses (correlations and regressions) and discuss spatial regression discontinuity research designs. We will also talk about how to geo-code data. The course is intended for students approaching their master’s thesis to get them started with independent research using spatial data.
Expected competences acquired after completion of the module: Students will acquire an understanding of what spatial data is. They will also gain first insights into open source software used for spatial data (QGIS and R).
Further information: The course is limited to 12 participants. If neccessary, students will be selected by lottery with preference for in higher semesters. Further sessions will be scheduled in the organizational meeting in September.
Contact information: Name: Kathrine von Graevenitz; Email: Kathrine.vonGraevenitz@zew.de