Courses Bachelor Display 2021-2022
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| Course title | Introduction to Software in Econometrics | |||||||||||||||||||||||||||||||||||||||
| Course code | EBS2072 | |||||||||||||||||||||||||||||||||||||||
| ECTS credits | 4,0 | |||||||||||||||||||||||||||||||||||||||
| Assessment | Whole/Half Grades | |||||||||||||||||||||||||||||||||||||||
| Period |
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| Level | Advanced | |||||||||||||||||||||||||||||||||||||||
| Coordinator |
Nalan Bastürk For more information: n.basturk@maastrichtuniversity.nl |
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| Language of instruction | English | |||||||||||||||||||||||||||||||||||||||
| Goals |
1. The student will learn to model simple econometric problems in the Bayesian framework.
2. The student will learn how to implement simulation-based Bayesian inference procedures for standard econometric models in the statistical programming software R and how to interpret estimation results. 3. The student will learn how to assess the appropriateness and accuracy of different simulation methods in different examples. |
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| Description |
Students will learn basic principles of Bayesian inference in econometrics focusing on computational techniques. They will acquire the skills to implement simulation based Bayesian inference procedures for standard econometric models in the statistical programming software R. Being able to implement and apply simulation based statistical methods is fundamental for the application of Bayesian methods to econometric problems.
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| Literature |
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| Prerequisites |
Econometric Methods 1 (EBC2111)
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| Keywords |
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| Teaching methods (indicative; course manual is definitive) | ||||||||||||||||||||||||||||||||||||||||
| Assessment methods (indicative; course manual is definitive) | ||||||||||||||||||||||||||||||||||||||||
| 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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