Model selection and misspecification in discrete choice welfare analysis

Ju-Chin Huang and Min Qiang (Kent) Zhao

Applied Economics, 2015, vol. 47, issue 39, 4153-4167

Abstract: This study extends the work by Herriges and Kling (1997) to further evaluate the impact of discrete choice modelling techniques on welfare measures. Particularly, we evaluate the performance of the increasingly popular mixed logit model and the computational strategy for deriving discrete choice welfare measures. Our simulation results show that model misspecification can have profound effects on welfare measures. In general, the flexible mixed logit model performs relatively well in the presence of misspecification. However, when the nesting structure can be appropriately identified (via statistical tests and a priori knowledge/experience), the nested logit model provides more reliable welfare measures than the mixed logit model.

Date: 2015
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://hdl.handle.net/10.1080/00036846.2015.1026581 (text/html)
Access to full text is restricted to subscribers.

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:taf:applec:v:47:y:2015:i:39:p:4153-4167

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RAEC20

DOI: 10.1080/00036846.2015.1026581

Access Statistics for this article

Applied Economics is currently edited by Anita Phillips

More articles in Applied Economics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().