NDLI: Does the choice model method and/or the data matter?

Content Provider	Springer Nature Link
Author	Hensher, David A. Rose, John M. Li, Zheng
Copyright Year	2011
Abstract	The opportunity to have seven data sets associated with a stated choice experiment that are very similar in content and design is rare, and provides an opportunity to look in detail at the empirical evidence within and between each data set in the context of a range of discrete choice estimation methods, from multinomial logit to latent class to scale multinomial logit to mixed logit, and the most general model, generalized mixed multinomial logit that accounts for preference and scale heterogeneity. Given the problems associated with data from different countries and time periods, we estimate separate models for each data set, obtaining values of travel time savings that are then updated post estimation to a common dollar for comparative purposes. We also pooled all data sets for a scaled MNL model, treating each data set as a set of three separate utility expressions, but linked to the other data sets through scale heterogeneity. This is not behaviourally appropriate with MNL, latent class or mixed logit. The main question investigated is whether there exists greater synergy in the willingness to pay evidence within model form across data sets compared to across model forms within data sets. The evidence suggests that there is a relatively greater convergence of evidence across the choice models, with the exception of generalized mixed logit, after controlling for data set differences; and there is strong evidence to suggest that differences between data sets do matter.
Starting Page	351
Ending Page	385
Page Count	35
File Format	PDF
ISSN	00494488
Journal	Transportation
Volume Number	39
Issue Number	2
e-ISSN	15729435
Language	English
Publisher	Springer US
Publisher Date	2011-04-03
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Multiple data sets Stated choice Discrete choice models Scale MNL Latent class Mixed logit Scale MNL Generalized mixed logit Australia New Zealand Innovation/Technology Management Regional/Spatial Science Economic Geography Engineering Economics, Organization, Logistics, Marketing
Content Type	Text
Resource Type	Article
Subject	Development Transportation Civil and Structural Engineering

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