A short course on the economics of trade sanctions. We pair macro-level analysis in modern quantitative trade models with micro-level evidence from firm-level customs data — and we get our hands dirty in R.
4.5 hacross three parts
2hands-on R practicals
The thread running through all three parts is the same pair of natural experiments — the 2014 and 2022 sanctions on Russia — seen first through theory and the policy debate, then through the customs records of individual exporters, and finally through a quantitative trade model.
The course
01
90 min · Lecture
Introduction & Frontier
The landscape of modern sanctions: who sanctions
whom, the conceptual frames, the effects on every side, and the
enforcement frontier.
Read the outline →
02
45 min + exercise
Firm-level Adjustment
How sanctions bite through the extensive margin,
the Friendly Fire result, and a hands-on PPML/LPM estimation on
Colombia–Venezuela customs data.
Read the outline →
03
45 min + exercise
Macro Counterfactuals
New quantitative trade models, the public
Get going
KITE package, and a general-equilibrium counterfactual of the
2022 Russia sanctions.
Read the outline →
Setup guide →
Install R, the packages,
KITE, and the prepared data
bundle. ~15–30 min.
Further reading →
~100 works, each with a one-line note on what it is for and a link to
the published version.
Course repository →
Slides, exercises and data on GitHub. Code MIT, lecture material
CC BY 4.0.
Author: Julian Hinz — Bielefeld University & the Kiel Institute for the World Economy.