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Course, academic year 2023/2024
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Econometrics I - JEB109
Title: Econometrics I
Guaranteed by: Institute of Economic Studies (23-IES)
Faculty: Faculty of Social Sciences
Actual: from 2021
Semester: summer
E-Credits: 6
Examination process: summer s.:
Hours per week, examination: summer s.:2/2, Ex [HT]
Capacity: 120 / 110 (120)
Min. number of students: unlimited
4EU+: no
Virtual mobility / capacity: no
State of the course: taught
Language: English
Teaching methods: full-time
Teaching methods: full-time
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. PhDr. Ladislav Krištoufek, Ph.D.
Teacher(s): PhDr. Jiří Kukačka, Ph.D.
Hieu Nguyen Thi Hoang, M.A.
Dipl.-Ing. Mathieu Petit, B.Sc.
Mgr. Kumar Chandrakamal Pramod Kumar
Class: Courses for LLEP
Courses for incoming students
Pre-requisite : JEB105
Is pre-requisite for: JEB110
Annotation -
Last update: PhDr. Jiří Kukačka, Ph.D. (28.01.2023)
Introductory course of econometrics focusing on cross-sectional data analysis within the Ordinary Least Squares framework.
Aim of the course -
Last update: PhDr. Jiří Kukačka, Ph.D. (30.01.2023)

The course aims to train students to properly analyze a cross-sectional dataset using the OLS framework, construct models, interpret the results, and prepare students for further econometrics courses.

Literature -
Last update: PhDr. Jiří Kukačka, Ph.D. (12.02.2023)

Core textbook:
   Wooldridge, J. M. (2012). Introductory Econometrics: A Modern Approach. Cengage Learning, 5th Ed., .pdf (6th Ed. from 2016 or 7th Ed. from 2018, e-book available, also possible).

Compare editions and pagination in Wooldridge_textbooks_contents.pdf.

Alternative (more advanced):
   Baltagi, B. H. (2021). Econometrics. Springer, 6th Ed. (e-book or .pdf available).
   Greene, W. H. (2018). Econometric Analysis. Pearson Education, 8th Ed. (e-book 7th Global Ed. available).
   Wooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data. MIT Press, 2nd Ed. (e-book available).

Entry requirements -
Last update: PhDr. Jiří Kukačka, Ph.D. (14.02.2023)

Strongly suggested courses:

Data Analysis in R (if you are completely new to R, review at least the recorded introductory lectures on R basicsData structuresData input, and Basic data management)

Mathematics I + II

Registration requirements -
Last update: PhDr. Jiří Kukačka, Ph.D. (15.02.2023)

Statistics (mandatory course)

Please get in touch with only Jiri Kukacka for any information regarding the organization of the course.

Students outgoing on Erasmus+ for the whole semester register for the seminar on Wednesdays from 15:30.

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