The objective of the course is to establish, revise, and systematize students' econometrics knowledge. First, we will recapitulate the essentials of statistics and afterwards, we will mainly focus on the practical applications of econometric techniques. For most of the semester we will be discussing the linear regression model and its Ordinary Least Squares (OLS) estimation, a simple, yet very powerful method in every economist’s toolbox. During the course we will together go through the basics of econometrics: from the statistical background through the theory and intuition behind the OLS estimation; properties of OLS; hypotheses testing; the linear regression model assumptions, their potential violations, and proper remedies; to some advanced topics such as the issue of endogeneity. For a good understanding of the limitations of the regression analysis, the issue of causality will be repeatedly discussed. Each topic will be backed up with an applied example and practised during seminars.
Last update: Mgr. Michaela Čuprová (06.05.2020)
Cílem kurzu je vybudovat, zrevidovat a systematizovat ekonometrické znalosti studentů. Nejdříve zopakujeme základy statistiky a následně se zaměříme především na praktickou aplikaci ekonometrických technik. Po většinu semestru se budeme zabývat lineárním regresním modelem a jeho odhadem pomocí metody nejmenších čtverců (OLS), základní, leč efektní techniky v arzenálu každého ekonoma. Během kurzu společně probereme základy ekonometrie: od opakování statistiky přes teorii a intuici odhadu metodou OLS, testování hypotéz, předpoklady lineárního regresního modelu, jejich možná narušení a vhodné nápravy, až po pokročilejší témata jako např. problém endogenity. Pro dobré pochopení limitací regresní analýzy bude opakovaně diskutována problematika kauzality. Každé téma bude ilustrováno na aplikovaném příkladě a procvičeno na seminářích.
Aim of the course -
Last update: PhDr. Jiří Kukačka, Ph.D. (16.01.2024)
The primary objective of this course is to enhance students' understanding of econometrics by establishing, revising, and systematizing their knowledge in this field. This course is highly recommended for students who have completed introductory statistics and seek to learn the fundamental principles of quantitative empirical analysis in economics and finance. Econometrics is essential for understanding the relationships between economic variables, serving as the vital link that connects economic theories with real-world data.
Econometrics equips you with the necessary skills and tools to succeed in your interests, whether they are in economic forecasting, the careful empirical testing of scientific hypotheses from various fields, the accurate estimation of numerical relationships between economic variables to inform policymakers or academic audiences, or just satisfying your natural curiosity.
Last update: PhDr. Jiří Kukačka, Ph.D. (16.01.2024)
The primary objective of this course is to enhance students' understanding of econometrics by establishing, revising, and systematizing their knowledge in this field. This course is highly recommended for students who have completed introductory statistics and seek to learn the fundamental principles of quantitative empirical analysis in economics and finance. Econometrics is essential for understanding the relationships between economic variables, serving as the vital link that connects economic theories with real-world data.
Econometrics equips you with the necessary skills and tools to succeed in your interests, whether they are in economic forecasting, the careful empirical testing of scientific hypotheses from various fields, the accurate estimation of numerical relationships between economic variables to inform policymakers or academic audiences, or just satisfying your natural curiosity.
Literature -
Last update: PhDr. Jiří Kukačka, Ph.D. (18.11.2019)
Core textbooks (selected chapters): Studenmund, A. H. (2016). Using Econometrics: A Practical Guide. Pearson Education, 7th Edition, pdf (e-book 7th Global Ed. from 2017 or 6th International Ed. from 2014 also possible). Wooldridge, J. M. (2016). Introductory Econometrics: A Modern Approach. Cengage, 6th Edition, pdf (5th Ed. from 2012 or 7th Ed. from 2018 also possible).
Compare editions and pagination in Textbooks_contents.pdf
Last update: PhDr. Jiří Kukačka, Ph.D. (18.11.2019)
Základní učebnice (vybrané kapitoly): Studenmund, A. H. (2016). Using Econometrics: A Practical Guide. Pearson Education, 7th Edition, pdf (případně e-book 7th Global Ed. z 2017 či 6th International Ed. z 2014). Wooldridge, J. M. (2016). Introductory Econometrics: A Modern Approach. Cengage, 6th Edition, pdf (případně 5th Ed. z 2012 či 7th Ed. z 2018).
Porovnání edic a stránkování naleznete v souboru Textbooks_contents.pdf
Entry requirements -
Last update: PhDr. Jiří Kukačka, Ph.D. (02.02.2024)
Knowledge of basic statistical concepts is expected and will be recapitulated during the first lecture. A brief overview can be found in the Studenmund textbook (2016, [2014]), Chapter 17 [15]: Statistical Principles, see the 'Files' section. A more advanced summary can be found in the Wooldridge textbook (2016), Appendices B and C-1 to C-3. A useful introduction to statistics (Harvard University) is available on youtube.
Knowledge of basic matrix algebra is also expected and important for understanding the content of some lectures and exercises. A summary of matrix algebra can be found in the Wooldridge textbook (2016), Appendix D. Useful matrix tutorials with exercises to practice and solutions can be found, e.g., here or at Khan Academy.
Last update: PhDr. Jiří Kukačka, Ph.D. (02.02.2024)
Knowledge of basic statistical concepts is expected and will be recapitulated during the first lecture. A brief overview can be found in the Studenmund textbook (2016, [2014]), Chapter 17 [15]: Statistical Principles, see the 'Files' section. A more advanced summary can be found in the Wooldridge textbook (2016), Appendices B and C-1 to C-3. A useful introduction to statistics (Harvard University) is available on youtube.
Knowledge of basic matrix algebra is also expected and important for understanding the content of some lectures and exercises. A summary of matrix algebra can be found in the Wooldridge textbook (2016), Appendix D. Useful matrix tutorials with exercises to practice and solutions can be found, e.g., here or at Khan Academy.
