The objective of the course is to teach students how to use econometric methods to identify and quantify economic relations, how to deal with the data and interpret the results. Together with Econometrics I, the course will prepare students to carry out independent empirical projects (e.g. for a bachelor thesis) and to take the Advanced Econometrics course.
Poslední úprava: Pertold-Gebicka Barbara, Mgr., M.A., Ph.D. (26.09.2023)
The objective of the course is to teach students how to use econometric methods to identify and quantify economic relations, how to deal with the data and interpret the results. Together with Econometrics I, the course will prepare students to carry out independent empirical projects (e.g. for a bachelor thesis) and to take the Advanced Econometrics course.
Poslední úprava: Pertold-Gebicka Barbara, Mgr., M.A., Ph.D. (26.09.2023)
Sylabus -
Detailed course contents:
Lecture 1: Unbiasedness, consistency, and efficiency (Chapters 2 and 5)
Lecture 2,3,4: Time Series (Chapters 10 - 12) Basic Regression analysis with time series data. - Properties of OLS with time series data. - Trends and seasonality. - Stationarity, nonstatinarity and weak dependence. - Serial correlation and heteroskedasticity in time series regressions.
Lecture 5,6: Panel Data (Chapters 13 - 14) - Pooling cross sections across time: Simple panel data methods. - Fixed effects estimation - Random Effects Models
Lecture 7: Midterm exam
Lecture 8: Instrumental Variables & 2SLS (Chapter 15) - Instrumental variables estimation. - Two Stage Least Squares (2SLS).
Poslední úprava: Pertold-Gebicka Barbara, Mgr., M.A., Ph.D. (18.09.2024)
Detailed course contents:
Lecture 1: Unbiasedness, consistency, and efficiency (Chapters 2 and 5)
Lecture 2,3,4: Time Series (Chapters 10 - 12) Basic Regression analysis with time series data. - Properties of OLS with time series data. - Trends and seasonality. - Stationarity, nonstatinarity and weak dependence. - Serial correlation and heteroskedasticity in time series regressions.
Lecture 5,6: Panel Data (Chapters 13 - 14) - Pooling cross sections across time: Simple panel data methods. - Fixed effects estimation - Random Effects Models
Lecture 7: Midterm exam
Lecture 8: Instrumental Variables & 2SLS (Chapter 15) - Instrumental variables estimation. - Two Stage Least Squares (2SLS).