GRA 6039 Econometrics with Programming
GRA 6039 Econometrics with Programming
The course teaches basic econometrics at a level expected among master students in economics, finance and related disciplines. The course also gives an introduction to programming in the context of data analysis. The programming is also applied to simulation techniques that we use to assess the properties of the econometric methods.
After taking this course:
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students should have a solid knowledge of linear regression models and the theory used for estimation of such models from data.
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students should be familiar with the assumptions for interpreting regression. estimates, know some techniques for assessing these assumptions and know some strategies for estimation when the standard assumption may fail.
After taking this course:
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students should be able to perform regression analysis, including using techniques for panel data, instrumental variable techniques and techniques for limited dependent variables
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students should be able to independently write programs for data analysis, perform simulation experiments, and develop their critical reasoning for econometric investigations.
Through experience with econometric models and computer experiments, the student will reflect on the limitations of econometrics, the issue of subjectivity in reaching statistical conclusions, and the level of trust one may place in statistically based decisions. Further, simulation will be introduced as a tool to assess the validity of econometric techniques. The student will reflect on using large-sample techniques in finite samples, the assessment of econometric assumptions and the concept of robustness in econometrics.
- Linear Regression
- Statistical inference
- Instrumental Variables Estimation and Two Stage Least Squares
- Panel Data Analysis
- Limited Dependent Variables
Please note that while attendance is not compulsory in all courses, it is the student’s own responsibility to obtain any information provided in class.
All parts of the assessment must be passed in order to receive a final grade in the course.
All courses in the Masters programme will assume that students have fulfilled the admission requirements for the programme. In addition, courses in second, third and/or fourth semester can have specific prerequisites and will assume that students have followed normal study progression. For double degree and exchange students, please note that equivalent courses are accepted.
Disclaimer
Deviations in teaching and exams may occur if external conditions or unforeseen events call for this.
| Assessments |
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Exam category: Submission Form of assessment: Submission PDF Exam/hand-in semester: First Semester Weight: 40 Grouping: Group (3 - 4) Duration: 1 Week(s) Comment: Assignment. An oral defense of the assignment might be required. Exam code: GRA 60393 Grading scale: ECTS Resit: Examination when next scheduled course |
Exam category: School Exam Form of assessment: Written School Exam - pen and paper Exam/hand-in semester: First Semester Weight: 60 Grouping: Individual Support materials:
Duration: 3 Hour(s) Exam code: GRA 60394 Grading scale: ECTS Resit: Examination when next scheduled course |
All exams must be passed to get a grade in this course.
| Activity | Duration | Comment |
|---|---|---|
Teaching | 36 Hour(s) | Lectures and Tutorials |
Examination | 15 Hour(s) | Home-exam related work |
Examination | 3 Hour(s) | Final exam |
Student's own work with learning resources | 100 Hour(s) |
A course of 1 ECTS credit corresponds to a workload of 26-30 hours. Therefore a course of 6 ECTS credits corresponds to a workload of at least 160 hours.