Seminar-style discussion and presentations of research papers in spatial/network economics/econometrics, and an applied introduction to spatial data analysis with R.

Students should be able to apply in-depth knowledge from the "Spatial Economics" field course to independently carry out and assess empirical economic research.

Readings and discussion

Coding sessions

Research projects

• 20% Presentation
• 20% Referee report
• 20% Participation
• 40% Paper proposal

Grades

• 1: [88, 100]
• 2: [75, 88)
• 3: [62, 75)
• 4: [50, 62)
• 5: [0, 50)

Participation in the field course "Spatial Economics".

Good prior knowledge of the R programming language is crucial for the applied parts of the course.

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