Advanced search
Publication Cover
Applied Economics Letters Volume 22, 2015 - Issue 9
Submit an article Journal homepage
233
Views
5
CrossRef citations to date
0
Altmetric
Original Articles

Predictive validity of stated preference data: evidence from mountain bike park visits before and after trail system expansion

Kevin AtkinsonDepartment of Economics, Appalachian State University, Boone, NC, USAView further author information
&
John C. WhiteheadDepartment of Economics, Appalachian State University, Boone, NC, USACorrespondence[email protected]
View further author information
Pages 730-733 | Published online: 28 Oct 2014
 
Sample our Economics, Finance,Business & Industry journals, sign in here to start your access, latest two full volumes FREE to you for 14 days

Abstract

This article investigates the validity of stated preference data for use in recreation demand estimation. We use stated preference and revealed preference data from users of a mountain bike park collected before and after an expansion of the trail system. The ex-ante stated preference data elicited before the change exhibits hypothetical bias, but it would provide useful information for demand prediction.

JEL Classification:

Additional information

Funding

Funding for this study was provided by the Walker College of Business Dean’s Club Research Grant.

Log in via your institution

Access through your institution

Log in to Taylor & Francis Online

Restore content access

Restore content access for purchases made as guest
Purchase options * Save for later

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 53.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 205.00 Add to cart

* Local tax will be added as applicable
Supercharge Your Next Research Paper: Research and write your next paper with Jenni AI.

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.