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Course, academic year 2024/2025
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Applied Econometrics - JEM116
Title: Applied Econometrics
Guaranteed by: Institute of Economic Studies (23-IES)
Faculty: Faculty of Social Sciences
Actual: from 2023
Semester: summer
E-Credits: 6
Examination process: summer s.:
Hours per week, examination: summer s.:2/2, Ex [HT]
Capacity: 97 / 65 (97)
Min. number of students: unlimited
4EU+: no
Virtual mobility / capacity: no
State of the course: taught
Language: English
Teaching methods: full-time
Additional information: http://ies.fsv.cuni.cz/index.php?module=sylab&action=sylab&id_sylab=140&lng=cs_CZ
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: prof. Roman Horváth, Ph.D.
doc. PhDr. Jozef Baruník, Ph.D.
PhDr. Jiří Kukačka, Ph.D.
Teacher(s): doc. PhDr. Jozef Baruník, Ph.D.
PhDr. Jaromír Baxa, Ph.D.
prof. Roman Horváth, Ph.D.
Mgr. Lukáš Janásek
PhDr. Jiří Kukačka, Ph.D.
Attila Sarkany
Class: Courses for incoming students
Files Comments Added by
download Lecture_2025.pdf Lecture 8 PhDr. Jaromír Baxa, Ph.D.
Annotation -
The course concentrates on the practical use of econometric methods, reviewing the relevant methodology, its use, and possible alternative modeling approaches. The lectures are supplemented by computer classes, where students can gain hands-on experience in applied econometric analysis. During the course, we will especially focus on time series techniques applied to forecasting asset volatility, modeling inflation, exchange rate volatility, and other topics that you may regularly encounter in economic and financial literature. The course focuses on the following topics in econometrics: OLS, IV, ARIMA, GARCH, VAR, cointegration, filters, and limited dependent variables.
Last update: Horváth Roman, prof., Ph.D. (10.02.2023)
Aim of the course -

Students will learn the basics of time series econometrics with an emphasis on how to apply these methods.

Last update: Horváth Roman, prof., Ph.D. (10.02.2023)
Course completion requirements -

G

Grading - in line with the Dean's decree 17/2018. 

Exam at the end of the semester (80% weight)

Term paper (20% weight)

Exam dates:

19th May 2PM room 206, 

2nd  June   2PM room 206,

11th June 10AM room 206

 

Please register for the exam using the SIS.

The details regarding the term paper are available in Lecture 1.pdf and in separate pdf files posted (during the semester) in the SIS.

Last update: Horváth Roman, prof., Ph.D. (17.03.2025)
Literature -

Selected recommended textbooks on applied econometrics:

Brook, Ch.: Introductory Econometrics for Finance, New York: Cambridge University Press.


Enders, W.: Applied Econometric Time Series, 2nd edition, Hoboken: Wiley, 2003.
Harris, R. and R. Sollis: Applied Time Series Modelling and Forecasting, Chichester: Wiley, 2003.
Stewart, K. G.: Introduction to Applied Econometrics, Belmont: Thomson Brooks, 2005.
Verbeek, M.: A Guide to Modern Econometrics, 2nd edition, Chihester: John Wiley, 2004.
Kratzig, M. and H. Lutkepohl ,Applied Time Series Econometrics, New York: Cambridge University Press, 2004.
Kočenda, E. and Černý, A.: Elements of Time Series Econometrics: An Applied Approach, Prague: Karolinum Press, 2007.

 

 

Last update: Horváth Roman, prof., Ph.D. (10.02.2023)
Teaching methods -

Lectures accompanied by seminars in computer room 016.

The software R will be used during the seminars, and materials will be processed in the interactive Jupyter Notebook .ypinb format (freeware, available on all computers in 016). If you want to work on your computer, ensure in advance Jupyter is properly connected to the R kernel.

If you are new to R and have not used Jupyter so far, study the Intro_to_jupyter+R.zip in Files and review the recorded introductory lectures on R basicsData structuresData input, and Basic data management from Data Analysis in R and/or the first recorded lectures from Data Science with R.

Last update: Kukačka Jiří, PhDr., Ph.D. (14.02.2023)
Requirements to the exam -

Grading - in line with the Dean's decree 17/2018. 

Exam at the end of the semester (80% weight)

Term paper (20% weight)

The details regarding the research proposal and term paper are available in Lecture 1.pdf and in separate pdf files posted (during the semester) in the SIS.

Last update: Horváth Roman, prof., Ph.D. (28.02.2025)
Syllabus -

1. Introduction

2. OLS and basics

3. Introduction to Time Series

4. ARIMA Modeling

5. GARCH (2 lectures)

6. Introduction to Cointegration

7. Vector Autoregression

8. TSLS, IV

9. Non-linear time series models

10. Limited dependent variable models in finance

11. Time series filters

12. Networks

13. Guest lecture

Last update: Horváth Roman, prof., Ph.D. (10.02.2023)
 
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