ECON526 - Fall 2026

This is a MA-level course in quantitative economics, data science, and causal inference in economics.

This course will have a combination of coding, theory, and development of mathematical background. All coding is done in Python.

Course materials

All materials will be on github, and canvas will be used to submit assignments/communication.

Course notes:

• Link to Jesse's Lecture Slides
• Paul's HTML Slides, source

There is no assigned physical textbook, but we will be using lecture notes from:

• Causal Inference for The Brave and True
• QuantEcon Python and Data Science Lectures

Computing Environment

See here for instructions. All course code will be done in python

• Get a GitHub ID and apply for the Student Developer Pack to get further free features
• We strongly recommend using VS Code as your primary code editor and uv for your python and package management.
• After setup you can clone a variety of repositories onto your local machine using a terminal, using either git directly (e.g. in terminal go git clone https://github.com/ubcecon/ECON526.git and https://github.com/jlperla/grad_econ_datascience_notebooks.git, or VS Code (recommended).

Syllabus

See Syllabus for more details

Problem Sets and Exams

The course has one or two midterms (depending on computer room scheduling), weekly to bi-weekly problem sets, and a final data project due at the end of term.

See canvas and the two schedules for problem sets and lecture notes.

Jesse

See the schedule for all problem sets and lectures associated with the first half of the course.

Paul

Go here for a list of topics, reading, and slides.

Here is the source for my slides.

See "Sources and Further Reading" (2nd last slide) on each set of slides for additional reading.

Important Dates

• November 11 (Midterm Break)
• November 13 (Midterm Break)

• December 15
  • PROJECT DUE