Data Science for Economists

Hands-on learning with cutting-edge tools and methodologies, from web scraping to satellite imagery analysis.

Authors

Julian Hinz

Irene Iodice

Fields in Kazakhstan.

Summary

This course provides a snapshot of state-of-the-art research in the field of international economics that makes use of big, often unconventional datasets, and novel methods.

Topics include issues in development studies (e.g. using satellite imagery), international trade and migration (large semi-structured administrative data and cellphone trace data) and international finance (data from social networks).

The course combines a weekly lecture that introduces one or more research projects, their data and methods, as well as an application session in which students are tasked with handling similar datasets and methods.

Coursework includes short assignments along the semester, as well as a final project.

Topics

  1. Getting started: Course outlook and good research practice

  2. The toolkit: R and the shell

  3. New sources of economic data: Web scraping and APIs

  4. Large structured data

  5. Networks

  6. Spatial data

  7. Satellite imagery

  8. Event and sensor data

  9. Text as data

  10. Social media data

Schedule

The course takes place on Wednesdays from 10 – 12h and 16 – 18h.

Date Time Location Topic Teacher
April 10 16 – 18 X-E0-216 Course outlook and reproducibility Julian & Irene
April 17 10 – 12 U2-113 R, bash, make and git Julian
16 – 18 X-E0-216
April 24 10 – 12 U2-113 Web scraping, APIs and databases Irene
16 – 18 X-E0-216
May 8 10 – 12 U2-113 Large structured data Irene
16 – 18 X-E0-216
May 15 10 – 12 U2-113 Networks Irene
16 – 18 X-E0-216
May 22 10 – 12 U2-113 Spatial data Julian
16 – 18 X-E0-216
May 29 10 – 12 U2-113 Satellite imagery Julian
16 – 18 X-E0-216
June 5 10 – 12 U2-113 Event and sensor data Irene
16 – 18 X-E0-216
June 12 10 – 12 U2-113 Text as data Irene
16 – 18 X-E0-216
June 19 10 – 12 U2-113 Social media data Julian
16 – 18 X-E0-216

References and additional resources

The course material, both for the lectures and coding examples, is often inspired by fantastic work from other educators and researchers. Here are some references that sometimes go beyond what we do in class:

Questions?

Any general questions? Post them in the dedicated #general Slack Channel in case you think this is a question of general interest. Of course, you can also contact us privately