Time series and panel data analysis 2400-ENSM109A
The course aim is to help each participant prepare MA dissertation devoted to time series and panel data modeling.
The course will cover the following topics:
- preparation, submission and grading MA dissertations
- data and literature sources
- tools and guidelines for editing documents
- hypotheses verification
- planning a MA dissertation
- structure of a MA dissertation
Depending on students’ interests, the course will follow selected topics in time series and panel data analysis: stationarity, time series regressions, state space models, long and short panel models, dynamic panel models, models with endogeneity.
Type of course
Course coordinators
Learning outcomes
The course aim is to help each participant prepare MA dissertation devoted to time series and panel data modeling. Students will learn how to formulate hypotheses, verify them, and how to prepare scientific reports.
KW01, KW02, KW03, KU01, KU02, KU03, KK01, KK02, KK03
Assessment criteria
Grading is based on each student’s progress in preparing MA dissertation.
Additional information
Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system: