Enhancing understanding of tourist spending using unconditional quantile regression

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2017-09Rights
© 2017 Elsevier. Reproduced in accordance with the publisher's self-archiving policy. This manuscript version is made available under the CC-BY-NC-ND 4.0 license.Peer-Reviewed
YesOpen Access status
openAccessAccepted for publication
14/06/2017
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This note highlights the value of using UQR for addressing the limitations inherent within previous methods involving conditional parameter distributions for spending analysis (QR and OLS). Using unique data and robust analysis using improved methods, our paper clearly demonstrates the over-importance attached to length of stay and the inadequate attention given to business travelers in previous research. There are clear benefits from UQR’s methodological robustness for assessing the multitude of variables related to tourist expenditures, particularly given UQR’s ability to inform across the spending distribution. Given tourism’s importance for the UK it is critical for expensive promotional activities to be targeted efficiently for ensuring effective policy making.Version
Accepted manuscriptCitation
Rudkin S and Sharma A (2017) Enhancing understanding of tourist spending using unconditional quantile regression. Annals of Tourism Research. 66: 188-191.Link to Version of Record
https://doi.org/10.1016/j.annals.2017.06.003Type
Articleae974a485f413a2113503eed53cd6c53
https://doi.org/10.1016/j.annals.2017.06.003