Courses NonDegree Display 2024-2025
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| Course title | Forecasting for Economics and Business | ||||||||||||||||||||||||||||||||||||||||||||
| Course code | EBC2089 | ||||||||||||||||||||||||||||||||||||||||||||
| ECTS credits | 6,5 | ||||||||||||||||||||||||||||||||||||||||||||
| Assessment | Whole/Half Grades | ||||||||||||||||||||||||||||||||||||||||||||
| Period |
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| Level | Advanced | ||||||||||||||||||||||||||||||||||||||||||||
| Coordinator |
Alain Hecq For more information: a.hecq@maastrichtuniversity.nl |
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| Language of instruction | English | ||||||||||||||||||||||||||||||||||||||||||||
| Goals |
Understand the importance of knowing the mechanisms that generate univariate time-series data.
Learn the basic tools for making forecasts including software (E-Views). Learn and understand methods to investigate dynamic characteristics of time-series data. Gain practical experience in analysing, modelling and forecasting a time series and reporting the results in course paper. |
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| Description |
This course will cover static and dynamic forecasting models, models with trends and seasonals, and cover the Box-Jenkins methodology for modeling cycles in stationary data. The course will provide students with a thorough understanding of time-series and with the empirical skills to estimate, test, and forecast the most appropriate dynamic models.
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| Literature |
The book by Diebold (2014), 'Forecasting' (available online).
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| Prerequisites |
This course is in transition for the bachelor Fiscal Economics.
See the Bachelor Education and Examination Regulations for more information. The following rule applies to bachelor Fiscal Economics students. TRANSITIONAL REGULATION (EBC2089): The bachelor Fiscal Economics has been discontinued. There will be repeat education for year 1 and year 2 courses up to and including academic year 2025-2026 and exam-only up to and including academic year 2026-2027. For year 3 courses there will be repeat education up to and including 2026-2027 and exam-only up to and including academic year 2027-2028. Whether a course is in transition, cancelled, or replaced may depend on the cohort you are in. Sometimes there are additional criteria. It is therefore very important to carefully read the EER and any addendum so you can apply the rules to your individual situation. PREREQUISITES: This course can be chosen as an elective by students in the Bachelor program of IBE and IES. Students must have a good and solid foundation in empirical econometrics and applied statistics, in particular statistics including knowledge about the multiple linear regression model. James H. Stock and Mark W. Watson : Introduction to Econometrics provides a good level indication of the prerequisites knowledge students must have to be able to follow this course successfully. An advanced level of English. |
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| Teaching methods (indicative; course manual is definitive) | PBL / Presentation / Lecture / Assignment | ||||||||||||||||||||||||||||||||||||||||||||
| Assessment methods (indicative; course manual is definitive) | Final Paper / Participation / Written Exam | ||||||||||||||||||||||||||||||||||||||||||||
| 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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