Courses Master Display 2023-2024
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Course title | Time Series Econometrics | |||||||||||||||||||||||||||||||||||||||
Course code | EBC4008 | |||||||||||||||||||||||||||||||||||||||
ECTS credits | 6,5 | |||||||||||||||||||||||||||||||||||||||
Assessment | Whole/Half Grades | |||||||||||||||||||||||||||||||||||||||
Period |
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Level | Advanced | |||||||||||||||||||||||||||||||||||||||
Coordinator |
Ines Wilms For more information: i.wilms@maastrichtuniversity.nl |
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Language of instruction | English | |||||||||||||||||||||||||||||||||||||||
Goals |
The objectives of this course are :
- to provide students with an understanding/intuition of the concepts of modern time series methods that are used in econometrics. - introduce the student to fundamental methodological issues in dynamic econometric modelling (nonstationarity, nonstandard asymptotic theory). - to provide students with some experience in analyzing univariate and multivariate time series from economics or business. |
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Description |
The emphasis of this course will be on studying in depth methods and techniques for the analysis of (nonstationary) economic and financial time series. We will cover and discuss issues related to: - dynamic econometric modelling - modelling nonstationary processes - asymptotic theory for dependent and integrated processes - unit roots (representation, tests, properties), cointegration and VECMs. Empirical applications as well as simulation experiments will also be considered to provide students with practical experience in analyzing economic and business time series.
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Literature |
The main textbook used in this course will be: - Hamilton, J.D. (1994), Time Series Analysis, Princeton University Press, Princeton.
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Prerequisites |
- Econometric methods (EBC2111), Stochastic Processes (EBC4004).
- Exchange students need to have a solid background in econometric methods, probability theory, mathematical statistics, and some knowledge in stochastic processes (some familiarity with Brownian Motion theory is important). Exchange students need to have obtained a Bachelor degree and an advanced level in mathematics and probability and statistics. An advanced level of English. |
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Teaching methods (indicative; course manual is definitive) | PBL / Presentation / Lecture / Assignment / Groupwork | |||||||||||||||||||||||||||||||||||||||
Assessment methods (indicative; course manual is definitive) | Participation / Written Exam / Assignment / Presentation | |||||||||||||||||||||||||||||||||||||||
Evaluation in previous academic year | For the complete evaluation of this course please click "here" | |||||||||||||||||||||||||||||||||||||||
This course belongs to the following programmes / specialisations |
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