BPE_INEC Introduction to Econometrics

Ekonomicko-správní fakulta
podzim 2024
Rozsah
1/2/0. 6 kr. Ukončení: zk.
Vyučováno kontaktně
Vyučující
Thi Hoang Hieu Nguyen (přednášející)
Thi Hoang Hieu Nguyen (cvičící)
Garance
doc. Ing. Daniel Němec, Ph.D.
Katedra ekonomie – Ekonomicko-správní fakulta
Kontaktní osoba: Mgr. Jarmila Šveňhová
Dodavatelské pracoviště: Katedra ekonomie – Ekonomicko-správní fakulta
Rozvrh
Pá 9:00–9:50 VT105, kromě Pá 20. 9., kromě Pá 8. 11.
  • Rozvrh seminárních/paralelních skupin:
BPE_INEC/01: Pá 10:00–11:50 VT105, kromě Pá 20. 9., kromě Pá 8. 11., T. Nguyen
Předpoklady
(! BPE_AIEC Introduction to Econometrics ) && (!NOWANY( BPE_AIEC Introduction to Econometrics ))
elementary probability and mathematical statistics
Omezení zápisu do předmětu
Předmět je nabízen i studentům mimo mateřské obory.
Předmět si smí zapsat nejvýše 24 stud.
Momentální stav registrace a zápisu: zapsáno: 24/24, pouze zareg.: 2/24, pouze zareg. s předností (mateřské obory): 1/24
Mateřské obory/plány
Cíle předmětu
The course is designed to give students experience of using econometric methods important in economics, finance and other business subjects. It provides skills in regression essential for understanding much of the literature of economics, finance, and empirical studies in other areas of business.
We begin with the simple regression and multiple regression models. They are treated in depth and in range of applications. Careful attention is given to the interpretations of regression results and hypothesis testing. A part of the course introduces various modern tools for analyzing models with binary dependent variables.
By the end of the course students should be able to use regression models in many different applications, and to critically examine reported regression results in empirical research in economics and other business studies. They will be able to identify and deal with a number of econometric problems in the analysis of time series and cross-section data, and will have experience of a range of basic econometric methods.
Výstupy z učení
The course is designed to give students an understanding of why econometrics is necessary and to provide them with a working knowledge of basic econometric tools so that:
They can apply these tools to modeling, estimation, inference, and forecasting in the context of real world economic problems.
They can evaluate critically the results and conclusions from others who use basic econometric tools.
They have a foundation and understanding for further study of econometrics.
They have an appreciation of the range of more advanced techniques that exists and that may be covered in later econometric courses.
Osnova
  • 1. Introduction to Econometrics and Working with Data (The Nature of Econometrics and Economic Data)
  • 2. The Simple Regression Model (Linear Regression Model and Ordinary Least Squares Estimator)
  • 3. Multiple Regression Model: Estimation (Motivation, Interpretation, OLS Estimator Properties)
  • 4. Multiple Regression Model: Inference (Hypothesis Testing, Testing Multiple Linear Restricions, Reporting Regression Results)
  • 5. Multiple Regression Model: OLS Asymptotics (Consistency and Large Sample Inference)
  • 6. Multiple Regression Model: Further Issues (More on Functional Form, Goodness-of-Fit, Slection of Regressors, Prediction and Residual Analysis)
  • 7. Multiple Regression Analsysis with Qualitative Information (Using Dummy Variables, The Linear Probability Model)
  • 8. Heteroskedasticity (Robust Inference, Testing for Heteroskedasticity)
  • 9. More on Specification and Data Issues (Functional Form Misspecification)
  • 10. Introduction to Limited Dependent Variable Models (Logit and Probit Models)
Literatura
    povinná literatura
  • WOOLDRIDGE, Jeffrey M. Introductory econometrics : a modern approach. Seventh edition. Boston: Cengage Learning, 2020, xxi, 826. ISBN 9781337558860. info
    doporučená literatura
  • HEISS, Florian. Using R for introductory econometrics. 2nd edition. Düsseldorf: Florian Heiss, 2020, 368 stran. ISBN 9788648424364. info
  • HEISS, Florian a Daniel BRUNNER. Using Python for introductory econometrics. 1st edition. Düsseldorf: Florian Heiss, 2020, 418 stran. ISBN 9788648436763. info
  • KOOP, Gary. Introduction to econometrics. Chichester: John Wiley & Sons, 2008, 371 s. ISBN 9780470032701. info
  • HILL, R. Carter, William E. GRIFFITHS a Guay C. LIM. Principles of econometrics. Fifth edition. Hoboken: Wiley Custom, 2018, xxvi, 878. ISBN 9781119510567. info
Výukové metody
tutorials, class discussion, computer labs practices, drills
Metody hodnocení
homework assignments, written exam
Vyučovací jazyk
Angličtina
Informace učitele
Any copying, recording or leaking tests, use of unauthorized tools, aids and communication devices, or other disruptions of objectivity of exams (credit tests) will be considered non-compliance with the conditions for course completion as well as a severe violation of the study rules. Consequently, the teacher will finish the exam (credit test) by awarding grade "F" in the Information System, and the Dean will initiate disciplinary proceedings that may result in study termination Students in this course are expected to adhere to the Masaryk University’s high standards of integrity as spelled out in the Disciplinary Code for Students and Directive N.3/2008. Anyone who cheats on tests or exams, will be subject to the penalties set forth in the Code.
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Předmět je zařazen také v obdobích podzim 2009, podzim 2010, podzim 2011, podzim 2012, podzim 2013, podzim 2014, podzim 2015, podzim 2016, podzim 2017, podzim 2018, podzim 2019, podzim 2020, podzim 2021, podzim 2022, podzim 2023, jaro 2024.
  • Statistika zápisu (nejnovější)
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