156-0580/01 – Applied econometrics (APE)
| Gurantor department | Department of Applied Economics | Credits | 5 |
| Subject guarantor | doc. Ing. Jiří Balcar, Ph.D., MBA | Subject version guarantor | doc. Ing. Jiří Balcar, Ph.D., MBA |
| Study level | undergraduate or graduate | Requirement | Compulsory |
| Year | 1 | Semester | summer |
| | Study language | English |
| Year of introduction | 2019/2020 | Year of cancellation | 2020/2021 |
| Intended for the faculties | EKF | Intended for study types | Follow-up Master |
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
Other requirements
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
Occurrence in study plans
Occurrence in special blocks
Assessment of instruction
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