Benefit estimation of transport projects--a representative consumer approach
Yukihiro Kidokoro
Transportation Research Part B: Methodological, 2006, vol. 40, issue 7, 521-542
Abstract:
In this paper, by focusing on the forms of the utility function of a representative consumer, we explain the three typical models of benefit estimation for transport projects: the basic model, the Wardrop model, and the logit model. The basic model is a representative consumer model with a quasi-linear utility function that is additively separable between numeraire and transport services. The paper clarifies the relationship between these models and derives their implications for benefit estimation. We find that the Wardrop and logit models are special cases of the basic model and that the logit model degenerates to the Wardrop model in a limiting case. Although this relationship implies that one can apply the benefit estimation method for the basic model whatever method is used to estimate transport demand, the Wardrop and logit models have useful features for conducting benefit estimation for new routes.
Date: 2006
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (11)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0191-2615(05)00077-9
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:transb:v:40:y:2006:i:7:p:521-542
Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01
Access Statistics for this article
Transportation Research Part B: Methodological is currently edited by Fred Mannering
More articles in Transportation Research Part B: Methodological from Elsevier
Bibliographic data for series maintained by Catherine Liu ().