Handbook of Choice Modelling
Show Less

Handbook of Choice Modelling

Edited by Stephane Hess and Andrew Daly

Choice modelling is an increasingly important technique for forecasting and valuation, with applications in fields such as transportation, health and environmental economics. For this reason it has attracted attention from leading academics and practitioners and methods have advanced substantially in recent years. This Handbook, composed of contributions from senior figures in the field, summarises the essential analytical techniques and discusses the key current research issues. It will be of interest to academics, students and practitioners in a wide range of areas.
Buy Book in Print
Show Summary Details
You do not have access to this content

Chapter 23: Numerical methods for optimization-based model estimation and inference

David S. Bunch


Researchers frequently use quantitative models to study and analyze choice behavior. They may obtain data on observed choice behavior through a variety of sources and methods (see Chapters 6 and 7) and then use the data to estimate or calibrate models that can be used for a variety of purposes, such as to develop and test theories, or to support the needs of decision makers. This chapter assumes a classical modeling framework where a dataset is viewed as a collection of observed outcomes from a data-generating process (DGP).

You are not authenticated to view the full text of this chapter or article.

Elgaronline requires a subscription or purchase to access the full text of books or journals. Please login through your library system or with your personal username and password on the homepage.

Non-subscribers can freely search the site, view abstracts/ extracts and download selected front matter and introductory chapters for personal use.

Your library may not have purchased all subject areas. If you are authenticated and think you should have access to this title, please contact your librarian.

Further information

or login to access all content.