GRA 6648 Research Methodology - Economics
GRA 6648 Research Methodology - Economics
This course is a graduate level introduction to Econometrics.
Students will learn to use statistical methods for estimating economic relationships, testing economic theories, and using estimated models to analyze the effect of policy intervention for the public and the private sector. The focus will be on time series econometrics.
The students will learn about the fundamentals of time series modelling, and how to use panel data in a time series context. Applications in macroeconomics and finance, using both traditional economic data and Big Data sources, will be covered. The students will master univariate and multivariate models of stationary and non stationary time series, and learn methods for conducting structural (counterfactual) inference when working with this type of data. In the end, they should be able to design and execute applied econometric projects.
The students will also obtain an understanding of information search strategies. Including:
- Acquaintance with methods for information, harvesting and search techniques
- Know what a critical literature review is and how this type of articles may be searched for and used
- Critical evaluation of sources
Students should be able to reflect and understand the basic techniques used in applied econometrics, so that eventually they can master and produce sophisticated applied econometric analysis.
I Data Management
- Traditional data (time series and panel data)
- Big data
- Data reduction
II Time series – Stationary and non-stationary univariate time series
- White noise, moving average, autoregressive models
- Forecasting
- Deterministic and stochastic trends, unit roots, structural change
- Applications
III Vector autoregression (VAR) methodology
- Structural VARs specification and estimation
- Identification, impulse responses, variance decomposition
- Spurious regression and log run economic relationships
- Applications
IV Panel data analysis
- Difference in difference methodology
- Fixed effects
- Applications
V Introduction to information search strategies
- Acquaintance with methods for information, harvesting and search techniques
- Know what a critical literature review is and how this type of articles may be searched for and used
- Critical evaluation of sources
VI Setting up an econometric project
- Research ethics, data handling, specification, modeling, policy analysis
Lectures and practical exercises that must be solved on the computer using Matlab/R or similar software.
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.
This is a course with continuous assessment (several exam components) and one final exam code. Each exam component is graded by using points on a scale from 0-100. The components will be weighted together according to the information in the course description in order to calculate the final letter grade for the examination code (course). Students who fail to participate in one/some/all exam elements will get a lower grade or may fail the course. You will find detailed information about the point system and the cut off points with reference to the letter grades when the course starts.
At resit, all exam components must, as a main rule, be retaken during next scheduled 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 |
|---|
Exam category: Activity Form of assessment: Presentation Weight: 20 Grouping: Group (3 - 6) Comment: Group assignment and presentation Exam code: GRA 66486 Grading scale: Point scale leading to ECTS letter grade Resit: All components must, as a main rule, be retaken during next scheduled course |
Exam category: Submission Form of assessment: Written submission Weight: 10 Grouping: Group/Individual (1 - 3) Duration: 1 Week(s) Comment: Library assignment Exam code: GRA 66486 Grading scale: Point scale leading to ECTS letter grade Resit: All components must, as a main rule, be retaken during next scheduled course |
Exam category: Submission Form of assessment: Written submission Invigilation Weight: 70 Grouping: Individual Support materials:
Duration: 3 Hour(s) Comment: Final written examination under supervision. Exam code: GRA 66486 Grading scale: Point scale leading to ECTS letter grade Resit: All components must, as a main rule, be retaken during next scheduled course |
| Activity | Duration | Comment |
|---|---|---|
Teaching | 36 Hour(s) | |
Seminar groups | 12 Hour(s) | |
Student's own work with learning resources | 120 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.