Econometrics II - JEB110

• Title: Econometrics II
• Form of teaching: lecture+practicals
• Guaranteed by: Institute of Economic Studies (23-IES)
• Faculty: Faculty of Social Sciences
• Actual: from 2025
• Duration in semesters: 1
• Semester: winter
• E-Credits: 6
• Examination process: winter s.:
• Hours per week, examination: winter s.:2/2, Ex [HT]
• Capacity: 97 / 97 (100)
• Maximum number of enrolled students: 100
• Min. number of students: unlimited
• 4EU+: no
• Virtual mobility / capacity: no
• State of the course: taught
• Language: English
• Teaching methods: full-time
• Repeated enrollment: 2 / 2 / 1 / 2
• Note: course can be enrolled in outside the study plan; enabled for web enrollment; priority enrollment if the course is part of the study plan
• Guarantor: Mgr. Barbara Pertold-Gebicka, M.A., Ph.D.
• Teacher(s): Mgr. Ing. Kseniya Bortnikova; Mgr. Barbara Pertold-Gebicka, M.A., Ph.D.; Mgr. Veronika Plachá; Bc. Oliver Škultéty, M.Sc.; Ing. Kai Wang
• Class: Courses for incoming students
• Pre-requisite : JEB109
• Is pre-requisite for: JEB125

Annotation

English

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.

Due to National Holiday on October 28, we move Lecture 5 to Friday, October 23 (2pm).
Seminars will take place on October 29, 2pm,
October 29, 6:30pm,
October 30, 2pm.

Last update: Pertold-Gebicka Barbara, Mgr., M.A., Ph.D. (16.09.2026)

Syllabus

English

Note that:
Due to National Holiday on October 28, we move Lecture 5 to Friday, October 23 (2pm).
Seminars will take place on October 29, 2pm, 
                                             October 29, 6:30pm,
                                             October 30, 2pm.

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).

Lecture 9:  Simultaneous equations (Chapter 16)
- Simultaneous equations models (simultaneity bias in OLS, etc.).

Lecture 10, 11 Limited Dependent Variable models (Chapter 17)
- Binary response models (linear probability, logit, probit).
- Corner solution, censored and truncated data models.

Lecture 12: Repetition (Chapters 10-17)

Last update: Pertold-Gebicka Barbara, Mgr., M.A., Ph.D. (16.09.2026)