Introduction to Spatial Econometrics and Statistics
Christian Oberst, 7 September to 11 September
This course will introduce basic techniques to analyze the spatial dimension of economic activities and characteristics. At the end of the course students should be able to visualize spatial data, design, implement, and critically evaluate empirical spatial studies. The course comprises datasets, research papers, and estimation implementation in R. Also, students will engage in independent empirical analyses of spatial data and in replicating published empirical work based publicly available regional datasets (e.g. from Eurostat and the Regional Database Germany).
After participating in this course, students should be in a position to:
- Understand fundamental spatial concepts (spatial dependency, heterogeneity, etc.)
- Create own spatial data sets and visualize data
- Design, implement, and apply spatial data analysis
a) Carry out exploratory spatial data analysis (ESDA)
b) Conduct a spatial regression analysis
- Critically review published empirical spatial studies
- Solid command of English.
- Essential basis in calculus, probability, statistics and econometrics.
- Basic knowledge of R is advantageous.
Students will be provided with precise textbook references for those that do not possess the pre-requisites
- Presentation (50%)
- Presentation defence & oral examination (30%)
- Class participation (20%)