88353 - GIS Tools Laboratory

Course contents

This course provides theory and tools to use Geospatial Data in Economic Research.

First, it presents some examples of economic papers based on this type of data and stresses why spatial data are useful in order to address meaningful research questions.

Second, the course introduces the technicalities related to the construction and use of geographic data using R.

Attendance is recommended. Nonetheless, the program is the same regardless of attendance.

Readings/Bibliography

The technical references for using R to handle GIS data will comprise both the slides and codes provided.

Some useful readings:

• Donaldson, D. and Storeygard, A., 2016. The view from above: Applications of satellite data in economics. Journal of Economic Perspectives, 30(4), pp.171-98.

• Lovelace, R., Nowosad, J. and Muenchow, J., 2019. Geocomputation with R. Chapman and Hall/CRC.

• Pebesma, E., 2018. Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10 (1), 439-446.

• Wickham, H. and Grolemund, G., 2016. R for data science: import, tidy, transform, visualize, and model data.” O’Reilly Media, Inc.”.

Teaching methods

Classes with discussions, papers and methods, and laboratory-like sessions in class.

Slides and R classes as teaching methods.

Assessment methods

• Participation and In-class Exercise (20%). This will be evaluated considering attendance, task replication and active participation.

• Take-home Exam (80%). A written exam will take place at the end of the course. It consists in task replication and in the proposal of a research idea. It must be sent by email in pdf.

Grading is as follows:

• <18 fail
• 18-23 pass
• 24-27 good
• 28-30 very good
• 30L excellent

Teaching tools

Participants are asked to have bring own laptop (or at least one every two people) to follow and replicate the codes.

Office hours

See the website of Giacomo Novelli