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EC315: Computational Economics

Subject Area: Economics

Course details

  • Department
    Department of Economics
  • Application code
Session oneNot running in 2023
Session twoNot running in 2023
Session threeNot running in 2023


Applications are closed

We are not currently accepting applications for this course. Register your interest below to be notified when applications open again.


This course introduces students to a broad set of computational methods used by economists.

The approach is hands-on: start with an economic problem, select an appropriate numerical technique for analysing it, apply the technique to the problem, and present your findings. The programming language of choice is Python.

Although the numerical techniques should be those indicated in the Programme Structure, the economic topics may be adapted to the interest of the audience, and the aim is to have economic examples also when presenting the basics of Python. For example, the programming concept of recursion and for loops can be illustrated with the Solow growth model; linear quadratic programming can be developed while talking about dynamic monopoly with durable goods, or a Stackelberg game.

Computational techniques are illustrated in lectures along with the economic models, and complemented with guided exercises during the classes.

Key information

Prerequisites: Intermediate microeconomics and macroeconomics, knowledge of multivariate calculus and linear algebra.

Level: 300 level. Read more information on levels in our FAQs

Fees: Please see Fees and payments

Lectures: 36 hours

Classes: 18 hours

Assessment: A mid-session take-home assignment (40%) and a final take-home assignment (60%).

Typical credit: 3-4 credits (US) 7.5 ECTS points (EU)

Please note: Assessment is optional but may be required for credit by your home institution. Your home institution will be able to advise how you can meet their credit requirements. For more information on exams and credit, read Teaching and assessment

Is this course right for you?

This course is suited to those who would like a hands-on approach to learn a broad set of computation methods used by economists. If you are interested in the use of coding and models within the study of economics, this course is for you.


  • Command the basics of Python for scientific computing
  • Establish a computational strategy to solve an economic model
  • Use visualization techniques for presenting computational findings
  • Master numerical methods for economic analysis
  • Have a working knowledge of the Github platform.


Krisha Patel, USA

The course will help my career, as it taught me a new side of economics and helped me to better understand the fundamentals of my subject in the real world.


The design of this course is guided by LSE faculty, as well as industry experts, who will share their experience and in-depth knowledge with you throughout the course.


The LSE Department of Economics is one of the largest and most prestigious in the world. It is the highest ranked faculty in Europe, according to the 2022 QS World University Rankings, with no fewer than 13 Nobel Prizes among current and former professors and alumni. The Department’s reputation is far-reaching, with research that has influenced responses to major global challenges, such as climate change, economic instability, development and growth, at a global level.

In our highly international faculty, students will learn from global thought-leaders and gain a thorough understanding of economic principles grounded in rigorous research. A long-standing commitment to remaining at the cutting-edge of developments in the field has ensured the lasting impact of the work of the Department on the discipline as a whole. This ensures that students are equipped with the necessary analytical skills to tackle the world’s most pressing problems.


Applications are closed

We are not currently accepting applications for this course. Register your interest below to be notified when applications open again.