Bias caused by omitted variables in random regret choice models: Formal and empirical analysis of orthogonal design data

S. Jang, S. Rasouli, H. J.P. Timmermans

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

1 Citation (Scopus)

Abstract

The aim of this study is to explore the bias caused by omitted variables in both random utility and random regret models. Since the behavioural underpinnings of these models differ, the bias is also expected to differ. We focus our analysis on stated choice data, based on orthogonal fractional factorial experimental designs, because the endogeneity, defined as a correlation between selected and omitted explanatory variables is a nonissue in such data. We will show that while the bias caused by omitted variables in the random utility model can be simply neutralised by using alternative specific constants, it still exists in the random regret model because the bias in this type of choice models depends on the attribute dominance structure in the data and thus is not constant.

Original languageEnglish
Title of host publicationProceedings of the 21st International Conference of Hong Kong Society for Transportation Studies, HKSTS 2016 - Smart Transportation
EditorsAllan Wing Gun Wong, Simon Ho Fai Wong, Gordon Lai Ming Leung
PublisherHong Kong Society for Transportation Studies Limited
Pages261-267
Number of pages7
ISBN (Electronic)9789881581457
Publication statusPublished - 2018
Externally publishedYes
Event21st International Conference of Hong Kong Society for Transportation Studies: Smart Transportation, HKSTS 2016 - Hong Kong, Hong Kong
Duration: 10 Dec 201612 Dec 2016

Publication series

NameProceedings of the 21st International Conference of Hong Kong Society for Transportation Studies, HKSTS 2016 - Smart Transportation

Conference

Conference21st International Conference of Hong Kong Society for Transportation Studies: Smart Transportation, HKSTS 2016
Country/TerritoryHong Kong
CityHong Kong
Period10/12/1612/12/16

Keywords

  • Omitted variables
  • Regret minimization
  • Utility maximization

ASJC Scopus subject areas

  • Transportation

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