Almost without exception, everything we undertake involves a choice. In recent years there has been a growing interest in the development and application of quantitative statistical methods to study choices made by individuals or groups with the purpose of gaining a better understanding both of how choices are made and of forecasting future choices.
Discrete choice analysis and stated choice methods are widely used across diverse fields to study the behavioural responses of individuals, households and other organisations.
This course is designed to provide both theory and practical experience in the building and estimating of simple and more advanced choice models, as well as in generating stated choice experimental designs.
The course also covers future developments in the field of discrete choice analysis; for example, nonlinear in parameters models, risk attitude, and perceptual conditioning. While we will cover theory, we will also spend significant time in a computer lab to build models using real data and generate simple surveys.
The techniques you will gain in this course are transferable to other areas of research.
This is both a practical and theory based course. We will be teaching how to estimate discrete choice models using software, and how to interpret the outputs using a real-life data set for this. We will cover:
The course also includes presentations of the background theory for discrete choice modelling, different methods for combining survey data, and the most recently developed modelling techniques including nonlinear in parameters models, cumulative prospect theory models and process heuristics.
The course explores the entire process, including experimental design, model building, and model estimation (with both stated preference and revealed preference data). Recent advances in tools and methods have been used to model individual behaviour and to analyse market shares and change in demand in response to pricing and income and changes in available choice sets and choice characteristics.
Presentations are augmented by hands-on problems with real data sets. Applications in model estimation will be developed using NLOGIT 6.0 / LIMDEP 11.0 software (Econometric Software, Inc). A 10 per cent discount on the price for this software will be available to course participants wishing to purchase. Experimental designs will be generated using the Ngene 1.2 software (ChoiceMetrics Pty Ltd).
This practical course will be useful for research across a broad range of fields in which consumer demand and choice is of interest, including:
The course is intended for academics and practitioners in government and industry. An appreciation of basic statistical concepts is useful, but not essential for this course. Please contact Andrew Collins if you have any concerns.
Many attendees have come with no background in discrete choice modelling, but have completed the course at a level that has enabled them to develop and estimate a range of choice models immediately.
In 2021, the Discrete Choice Analysis program was held from Monday 26 to Friday 30 July.
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Early bird registration prices conclude one month before course commences.
All fees are inclusive of GST and including course materials (including "Applied Choice Analysis: A Primer" by David Hensher, John Rose and Bill Greene, Cambridge University Press, 2nd Edition 2015).
Group discounts are available for three or more persons from the same organisation. Please email: firstname.lastname@example.org for further information.
Cancellations: No refund will be available for cancellations made two weeks prior to the course commencing.
DCA 2021 has ended.
Please email email@example.com to place your name for “Expression of interest” for DCA 2022.
Please indicate whether it is your preference to participate in person or online. (Format yet to be confirmed).