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

Over a ten-year period from 1999-2008, seven toll road studies were conducted in Australia and New Zealand. Stated choice datasets from these studies provide a unique opportunity to examine the empirical evidence within and between each data set in the context of a range of discrete choice estimation methods. These estimation methods include multinomial logit (MNL), latent class, scaled multinomial logit, mixed logit, and generalized mixed multinomial logit that accounts for preference and scale heterogeneity. The authors 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. All data sets are pooled for a scaled MNL model in which each data set is treated as a set of three separate utility expressions but linked to the other data sets through scale heterogeneity. The authors specifically investigate 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. Their findings indicate 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. Findings also indicate that differences between data sets are important.

• Record URL:
  • https://doi.org/10.1007/s11116-011-9329-x
• Corporate Authors:

  Congressional Research Service

  Washington, DC  United States 
• Authors:
  • Hensher, David A
  • Rose, John M
  • Li, Zheng
• Publication Date: 2017-8-16

Language

• English

Media Info

• Media Type: Print
• Features: Figures; References; Tables;
• Pagination: pp 351-385
• Monograph Title: Airport Privatization: Issues and Options for Congress

Subject/Index Terms

• TRT Terms: Choice models; Datasets; Logits; Toll roads; Travel time; Value of time
• Uncontrolled Terms: Stated choice; Willingness to pay
• Geographic Terms: Australia; New Zealand
• Subject Areas: Highways; Planning and Forecasting; I72: Traffic and Transport Planning;

Filing Info

• Accession Number: 01376142
• Record Type: Publication
• Files: TRIS, ATRI
• Created Date: Jul 23 2012 9:11AM