114-0380/01 – Applied econometrics (APE)

Gurantor departmentDepartment of EconomicsCredits5
Subject guarantordoc. Ing. Jiří Balcar, Ph.D.Subject version guarantordoc. Ing. Jiří Balcar, Ph.D.
Study levelundergraduate or graduateRequirementCompulsory
Study languageCzech
Year of introduction2020/2021Year of cancellation
Intended for the facultiesEKFIntended for study typesFollow-up Master
Instruction secured by
LoginNameTuitorTeacher giving lectures
BAD0012 Ing. Ondřej Badura, Ph.D.
BAL112 doc. Ing. Jiří Balcar, Ph.D.
JAW127 doc. Ing. Jan Janků, Ph.D.
FIL03 Ing. Lenka Johnson Filipová, Ph.D.
KON0310 Ing. Vojtěch Koňařík
PYT005 doc. Ing. Mariola Pytliková, Ph.D.
BRI0043 doc. Ing. Zuzana Schwidrowski, 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



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


Other requirements

Course requirements include active class participation and home-works, and a final exam.


Subject has no prerequisities.


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: 2020/2021 Winter semester)
Task nameType of taskMax. number of points
(act. for subtasks)
Min. number of points
Credit Credit 100 (100) 51
        Test Written test 100  51
Mandatory attendence parzicipation: -

Show history

Occurrence in study plans

Academic yearProgrammeField of studySpec.ZaměřeníFormStudy language Tut. centreYearWSType of duty
2022/2023 (N0311A050012) Applied economics (S02) Economic Development P Czech Ostrava 1 Compulsory study plan
2021/2022 (N0311A050012) Applied economics (S02) Economic Development P Czech Ostrava 1 Compulsory study plan

Occurrence in special blocks

Block nameAcademic yearForm of studyStudy language YearWSType of blockBlock owner