Course for international guest/part time students
- Faculty
- Faculty of Economics
- Organization
- GTK Department of Comparative Economics
- Code
- GTI23AN508EN
- Title
- Econometrics
- Usual semester
- Autumn
- Published semester
- 2024/25/2
- ECTS
- 6
- Language
- en
- Learning outcomes
- This course introduces the foundations of regression analysis. In doing so, we discuss the basic econometric methods and concepts of the analyses of cross-sectional and time-series data. The course aims at equipping students with the fundamental knowledge and skills needed for conducting original empirical research – from setting the hypotheses, through the choice of the appropriate methods, to the interpretation of results. The individual methods are always demonstrated through case studies based on real data. The everyday use of econometric theory requires the knowledge of a particular econometric software. In the frame of the course, the free, open-source software: GRETL, is used. Intended learning outcomes: On successful completion of this course, students should be able to: understand and apply the basic statistical methods of working with data and modelling economic and social processes quantitatively analyse micro- and macroeconomic issues evaluate and forecast business processes and macroeconomic/social tendencies Links to Sustainable Development Goals: On successful completion of this course, students should be able to connect topics taught to the SDGs: Ensure inclusive and equitable quality education and promote lifelong learning opportunities for all (SDG 4) Promote sustained, inclusive and sustainable economic growth, full and productive employment and decent work for all (SDG 8)
- Course content
- I. Analyses of cross-sectional data Simple and multivariate linear regressions, OLS Inference and model selection Binary (dummy) explanatory variables Non-linear models: Non-linearity in the variables Further issues: data scaling, outliers etc. Heteroskedasticity and model diagnostics II. Analyses of time series data OLS estimation of time-series models Deterministic time series models Basic concepts in stochastic time series analysis Stationarity & unit root processes ARIMA models
- Assessment method
- Grades offered during the semester: 60-69% satisfactory, 70-84% good, 85-100% excellent Examination grade: 50-54% pass, 55-69%, satisfactory, 70-84% good, 85-100% excellent The current assessment and evaluation requirements of the ELTE GTK apply, which can be found on the GTK TH website under the student's level of training. https://gtk.elte.hu/bscorarend?m=6656
- Bibliography
- Wooldridge, J.M. (2016): Introductory econometrics: A modern approach. 6th ed., Cengage Learning: Boston (MA), USA. (designated chapters)