QuantEcon Summer Course in Quantitative Economics

The Summer Course in Quantitative Economics 2023 will be run by QuantEcon in partnership with the African School of Economics (ASE), and the Institute of Statistics and Applied Economics (ENSEA). The target audience for the course is talented young economists from ASE, ENSEA, and other African institutions who want to learn about data science and computer-driven economic modeling.

The course will provide students with an introduction and exposure to key tools in quantitative economics that are in high demand in academia and industry.

The workshop will run in 2023 over the weeks

1. Monday-Friday July 03-07
2. Monday-Friday July 10-14

Classes will be 3 hours per day, 5 days per week.

The lead instructor and academic coordinator for the program is Thomas J. Sargent, co-founder of QuantEcon, Professor of Economics at New York University, and 2011 Nobel Laureate in Economic Sciences.

How will the workshops work?

The course will consist of a mixture of pre-recorded and (a small number of) live lectures. New course videos will be released each day of the workshop, along with exercises.

Teaching assistants will run online live discussions and the organizers will provide a forum for interaction with instructors and peers.

All students will require access to a computer.

Students are encouraged to form study groups to foster working in teams (a valuable skill in industry, government, and academia).

Syllabus

The language of instruction will be English.

The programming language used in the course will be Python.

The course will cover selected topics about

• Foundations of programming in Python
• Data engineering with Pandas
• Elementary economics with Python including
  • geometric series and multiplier models
  • demand and supply curves
  • competitive equilibria
  • monopoly
  • models of economic growth
  • networks
  • elementary Markov chains
  • some elements of probability and statistics
• Economic dynamics
• Linear algebra
• Optimization, filtering and dynamic programming
• Search and matching models
• Asset pricing
• Bayesian and frequentist statistics
• Quantitative economic history
• High-performance computing with Python

Background reading on these topics can be found in the lecture series Python Programming for Economics and Finance and in a soon to be released lecture series about elementary economics, at the quantecon site.

Learning outcomes

Participants will learn how to connect economic modeling problems to numerical implementations in Python using clear, efficient and effective code. Participants will be able to apply basic software engineering principles to organize, share and collaborate on coding problems.

These skills are in high demand for economists and data scientists at leading tech companies and universities around the world.

Eligibility

We shall strive to make classes accessible to students who want to learn Python and how to use it in economics. That said, the course material will be challenging. Ideal candidates will already have had at least some exposure to probability, linear algebra and principles of economics, including part of an undergraduate degree in economics or computer science.

Programming experience will be helpful but is not a prerequisite.

Registration Details

Please register through this site

Contact

Organizers of the program can be reached through contact@quantecon.org.