DXE_EMT2 Econometrics 2

Faculty of Economics and Administration
Spring 2010
Extent and Intensity
24/0. 12 credit(s). Type of Completion: zk (examination).
Teacher(s)
Prof. Dr. Peter Hackl (lecturer)
Ing. Daniel Němec, Ph.D. (assistant)
Guaranteed by
Ing. Daniel Němec, Ph.D.
Department of Economics - Faculty of Economics and Administration
Contact Person: Mgr. Klára Šmídová
Timetable
Fri 19. 3. to Fri 23. 4. Fri 10:15–13:45 S313
Course Enrolment Limitations
The course is only offered to the students of the study fields the course is directly associated with.
fields of study / plans the course is directly associated with
there are 22 fields of study the course is directly associated with, display
Course objectives
Topics of basic econometrics (covered in Econometrics) will be reviewed and expanded into more advanced level. Advanced econometric topics include instrumental variable estimations, maximum likelihood estimation, GMM, etc. The course is designed to provide students with a good knowledge of basic and advanced econometric tools so that:
- They can apply these tools to modeling, estimation, inference, and forecasting in the context of economic problems;
- They can evaluate critically the results from others who use econometric methods and tools;
- They have a foundation and understanding for further study of econometric theory.
Syllabus
  • Lectures:
  • 1. Review of linear regression and the OLS estimator;
  • - The linear regression model and assumptions;
  • - The OLS estimator and properties;
  • - Diagnostic tools;
  • - The linear model and statistical inference;
  • - Repressors selection: Effects and tools;
  • - Limitations of the linear model in economic analyses;
  • 2. Heteroskedasticity and autocorrelation;
  • - Consequences for the OLS estimator;
  • - Alternative estimator;
  • - Heteroskedasticity;
  • - Testing for heteroskedasticity;
  • - Autocorrelation;
  • - Testing for autocorrelation;
  • - Alternatives for inference;
  • 3. Endogenity, instrumental variables and GMM;
  • - A review of the properties of the OLS estimator;
  • - Cases where the OLS estimator cannot be saved;
  • - The instrumental variables estimator;
  • - The generalized instrumental variables estimator;
  • - The Generalized Method of Moments;
  • 4. Maximum likelihood estimation and specification tests;
  • - The concept of maximum likelihood;
  • - Specification tests;
  • - Tests in the normal linear regression model;
  • - Quasi-maximum likelihood and moment conditions tests;
  • 5. Univariate time series models;
  • - ARMA processes;
  • - Stationarity and unit roots;
  • - Testing for unit roots;
  • - Estimation of ARMA models;
  • - Choosing a model;
  • - Predicting with ARMA models;
  • - Autoregressive conditional heteroskedasticity;
  • 6. Multivariate time series models;
  • - Dynamic models with stationary variables;
  • - Models with nonstationary variables;
  • - Vector autoregressive models;
  • - Cointegration: the multivariate case;
Literature
    required literature
  • VERBEEK, Marno. A guide to modern econometrics. 3rd ed. Chichester: John Wiley & Sons, 2008. xv, 472. ISBN 9780470517697. info
Language of instruction
English
Further Comments
Study Materials
The course can also be completed outside the examination period.
The course is taught annually.
The course is also listed under the following terms Spring 2011, Spring 2012, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2018, Spring 2019, Spring 2020, Spring 2021.
  • Enrolment Statistics (Spring 2010, recent)
  • Permalink: https://is.muni.cz/course/econ/spring2010/DXE_EMT2