156-0580/01 – Applied econometrics (APE)

Gurantor departmentDepartment of National EconomyCredits5
Subject guarantordoc. Ing. Zuzana Brixiová, Ph.D.Subject version guarantordoc. Ing. Zuzana Brixiová, Ph.D.
Study levelundergraduate or graduateRequirementCompulsory
Year1Semestersummer
Study languageEnglish
Year of introduction2019/2020Year of cancellation
Intended for the facultiesEKFIntended for study typesFollow-up Master
Instruction secured by
LoginNameTuitorTeacher giving lectures
BRI0043 doc. Ing. Zuzana Brixiová, Ph.D.
PYT005 doc. Ing. Mariola Pytliková, Ph.D.
Extent of instruction for forms of study
Form of studyWay of compl.Extent
Full-time Credit 1+4

Subject aims expressed by acquired skills and competences

The objective of this course is to apply econometric methods to real world problems. The emphasis is on perspective of professional users of econometrics and illustrate how empirical researchers think about and apply econometrics methods. The aim is to equip students with broad and rigorous tools that would allow them to (i) conduct an independent econometric analysis of problems they may encounter in their work and (ii) where suitable, draw operational and/or policy recommendations.

Teaching methods

Lectures
Tutorials

Summary

Compulsory literature:

Wooldridge, J. M. (2016), Introductory Econometrics: A Modern Approach (6th edition), Cengage Learning, Inc.

Recommended literature:

Acock, A. C. (2018), A Gentle Introduction to Stata, 6th edition, A Stata Press Publication. Heiss, F. (2016), Using R for Introductory Econometrics, 1st edition. This textbook is compatible with "Introductory Econometrics" by J. M. Wooldridge in terms of topics, organization, terminology and notation. Verbeek, M. (2017), A Guide to Modern Econometrics, Wiley Publisher.

Way of continuous check of knowledge in the course of semester

E-learning

Další požadavky na studenta

Course requirements include active class participation and home-works, class presentation, a mid-term exam and a final exam and a short paper. Grade will be based on: (1) active class participation and home-works (15 %); (2) individual or joint small group presentation (15 %); (3) midterm exam (20 %) and (4) final exam (50 %).

Prerequisities

Subject has no prerequisities.

Co-requisities

Subject has no co-requisities.

Subject syllabus:

1. Introduction to economics and Stata, and its use for descriptive statistics. 2. Least squares method, linear regression and OLS estimator properties. 3. Credibility of estimation, hypothesis testing, measurement errors and feedback in the presence of stochastic variables. 4. Interpretation and comparison of models (including model selection criteria). 5. Basics of forecasting and simulation. 6. Heteroskedasticity and autocorrelation. 7. Principles of time series analysis and volatility (conditional and variance modeling). 8. Endogenity, estimation using instrumental variables. 9. Logit and probit models. 10. Multinomial models and models of ordered answers. 11. Count data (Poisson regression model, negative binomial model, general count regression), “duration” data. 12. Tobit models (censored variables), treatment effects. 13. Linear models of panel data: fixed and random effects. 14. Linear models of panel data: static and dynamic models, incomplete panels (/ attrition), tests of non-stationarity and cointegration.

Conditions for subject completion

Full-time form (validity from: 2019/2020 Summer semester)
Task nameType of taskMax. number of points
(act. for subtasks)
Min. number of points
Credit Credit 100  51
Mandatory attendence parzicipation: Conditions stated by lecturer.

Show history

Occurrence in study plans

Academic yearProgrammeField of studySpec.FormStudy language Tut. centreYearWSType of duty
2019/2020 (N0311A050013) Applied Economics (S01) Economic Development P English Ostrava 1 Compulsory study plan

Occurrence in special blocks

Block nameAcademic yearForm of studyStudy language YearWSType of blockBlock owner