Foundations of and current issues in spatial/network economics/econometrics. Applied spatial data analysis (i.e. handling, exploring, visualizing, and analysing spatial data) in R.

Students should understand intricacies of analyzing dependent (spatial, network) data, particularly in an economic context, and gain a solid understanding of related economic theory, and, particularly, econometric methods.

Attendance is mandatory; one missed unit is tolerated.

Frontal presentations

Assignments

Applied work and demonstrations

• 10% Participation
• 40% Assignments
• 50% Final exam

Grades

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

A good understanding and grasp of the econometric curriculum is required; good prior knowledge of the R programming language is crucial for the applied parts of the course.

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