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The University of Southampton

ECON2040 Computational Economics

Module Overview

This module will familiarise students with various computational methods and software tools used in economics and econometrics. Topics include programming, numerical simulation and optimisation, data processing and estimation. The module will provide students with a firm foundation in state-of-the-art techniques and software for each topic. The module will go through applications in economics and econometrics.

Aims and Objectives

Learning Outcomes

Knowledge and Understanding

Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:

  • fundamental programming methods relevant for data science
  • numerical methods for statistical data analysis, including using large data sets
  • adequate computational tools for quantitative economic and econometric analysis.
Subject Specific Intellectual and Research Skills

Having successfully completed this module you will be able to:

  • retrieve, organise, analyse and present data from large datasets in an informative manner.
  • use state of the art programming techniques relevant for econometric data analysis.
Transferable and Generic Skills

Having successfully completed this module you will be able to:

  • analyse and interpret data using state of the art computational methods;
  • successfully collaborate with others in a group on programming assignments.


This module will cover three main areas. It will cover programming skills and give an introduction to computer programming for economists and econometricians. A second focus is on methods of data processing, manipulation and analysis that are relevant for economists and econometricians. The module will also cover techniques of numerical simulation with an emphasis on optimisation and its economic and econometric applications.

Learning and Teaching

Teaching and learning methods

Lectures, masterclasses, computer lab sessions

Independent Study120
Total study time150

Resources & Reading list

Lecture Notes on Blackboard.


Assessment Strategy

Continuous assessment through three take-home programming assignments, supported by formative assessment in form of programming exercises. There is no final exam. This is the same for an internal repeat. Assessment for external repeat and referral is through a single piece of coursework.


MethodPercentage contribution
Coursework assignment(s) 15%
Coursework assignment(s) 35%
Coursework assignment(s) 50%


MethodPercentage contribution
Coursework assignment(s) 100%


MethodPercentage contribution
Coursework assignment(s) 100%

Repeat Information

Repeat type: Internal & External

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