Course ObjectiveThis course introduces students to advanced econometric theory and
methods for analyzing linear multivariate non-stationary time-series and
By the end of this course, participants will:
(1) have detailed knowledge of VAR, VECM and dynamic panel-data models.
(2) understand the limit theory behind spurious regression and
(3) be familiar with advanced unit-root and cointegration tests;
(4) understand the challenges in designing, estimating and analyzing
linear econometric models for non-stationary time-series and panel data.
Course ContentThis course covers both theoretical and practical aspects of modeling
multivariate non-stationary time-series and panel data, with special
emphasis on unit-root processes and cointegration.
The students will be introduced to linear multivariate time-series
models and linear panel data models used in econometrics. Important
topics include marginalizing, conditioning, exogeneity, vector
autoregressive (VAR) models, and vector error correction models (VECM).
Important limit results will be carefully derived providing the students
with a deep understanding of the theory and practice behind a wide range
of advanced unit roots test, spurious regression, cointegration, and
Teaching MethodsLectures and tutorials
Method of AssessmentFinal exam and group assignment – Individual assessment
Davidson (2000), Econometric Theory, Blackwell publishing;
Lutkepohl (2005), New Introduction to Multiple Time Series Analysis,
Hamilton (1994), Time Series Analysis, Princeton University Press;
Pesaran (2015), Time series and Panel Data Econometrics, Oxford
Baltagi (2005), Econometric Analysis of Panel Data, Third edition, John
iley & Sons, Ltd;
Other reading materials:
Lecture notes provided by the teacher;
Journal articles recommended by the teacher: will be uploaded under the
module: Articles to read
Recommended background knowledgeThis course presumes that the students are familiar with econometric
methods, probability theory, mathematical statistics. The theory and
practice behind the regression model should be well understood.
Furthermore, the students should have been introduced to time-series
analysis. In particular, the students should be familiar with the
concepts of stationarity and ARMA models.
|Language of Tuition||English|
|Faculty||School of Business and Economics|
|Course Coordinator||dr. H. Karabiyik|
|Examiner||dr. H. Karabiyik|
dr. H. Karabiyik
You need to register for this course yourself
Last-minute registration is available for this course.
|Teaching Methods||Study Group, Lecture|
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