Modern City

Discrete Choice Models 

The course covers the estimation and usage of discrete choice models that are increasingly estimated using simulation methods. Discrete choice models are used to examine the choices of individual consumers, households, firms and other agents. The course will cover the main discrete choice models and a variety of specifications that build on these models, as well as standard maximum likelihood and simulation-based estimation techniques. Discrete choice models are applicable in many fields, including energy, environmental studies, health, labour, marketing, urban economics and transportation.

This module can be taken on its own, or as part of a PG Certificate, PG Diploma or Full Masters Program. 

Key Skills

By the end of this course, participants should have knowledge and understanding of:

Non-linear binary models

Probit models and estimation.

Logit models and estimation.

Present, interpret and analyse the results of automatic model selection.

Desired Skills

By the end of this course, students should be able to: 

Use automatical model selection to build econometric models.

Use saturation estimation.

Present, interpret and analyse the results of automatic model selection.

Utilise effectively PcGive and the R gets package.

Structure

 

Discrete Choice Models is an elective 10 credit course and therefore students are expected to input approximately 100 hours of study into the course.

 

The total number of contact hours is 15 hours. This leaves 85 hours for private study.

Lectures

 

 

 

This module consists of 2- hour lectures per day, for 5 consecutive days, plus a 1 - hour tutorial per day.

 There will be optional clinics on the last day of the course.