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:
Presentation (30%), report (40%), and report refereed (30%)
Prerequisites: solid understanding of Basic Statistics and Basic Econometrics
Goals and contents of the module: In large part, economic data is based on time series, which is data collected on the same observational unit at multiple time periods (e. g. yearly, quarterly or monthly). Analyzing time series data requires specific statistical models and methods, which are usually not taught in basic statistics and basic econometrics courses. Subject of this course is to provide an overview about the most important standard methods for describing and analyzing time series data. Thereby the main focus is on the practical application of forecasting methods. The Statistical Software R will intensively be used upon many real data examples. Contents: Introduction to TSA, Review of Basic Essentials, Basic Elements of TSA, Basic Properties of Time Series, Forecasting Theory, AR(I)MA Processes, ADL- and VAR-Models, Nonstationarity, Estimation of Dynamic Causal Effects, Additional Topics in TSA
Expected competences acquired after completion of the module: At the end of the semester students
Prerequisites: solid understanding of Basic Statistics and Basic Econometrics
Goals and contents of the module: In large part, economic data is based on time series, which is data collected on the same observational unit at multiple time periods (e. g. yearly, quarterly or monthly). Analyzing time series data requires specific statistical models and methods, which are usually not taught in basic statistics and basic econometrics courses. Subject of this course is to provide an overview about the most important standard methods for describing and analyzing time series data. Thereby the main focus is on the practical application of forecasting methods. The Statistical Software R will intensively be used upon many real data examples. Contents: Introduction to TSA, Review of Basic Essentials, Basic Elements of TSA, Basic Properties of Time Series, Forecasting Theory, AR(I)MA Processes, ADL- and VAR-Models, Nonstationarity, Estimation of Dynamic Causal Effects, Additional Topics in TSA
Expected competences acquired after completion of the module: At the end of the semester students
Veranstaltungsort und -zeit:
Einführungsveranstaltung: 14.02.2022, 17:15 Uhr bis 18:00 Uhr, via Zoom.
Blockseminar: 19.05.2022 und 20.05.2022, je 08.30 Uhr bis 17.30 Uhr, Ort wird noch bekanntgegeben.