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Enhancing understanding of tourist spending using unconditional quantile regression
Rudkin, Simon Sharma, Abhijit
Rudkin, Simon
Sharma, Abhijit
Publication Date
2017-09
End of Embargo
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Rights
© 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
Yes
Open Access status
openAccess
Accepted for publication
14/06/2017
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Department
Awarded
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Abstract
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 manuscript
Citation
Rudkin S and Sharma A (2017) Enhancing understanding of tourist spending using unconditional quantile regression. Annals of Tourism Research. 66: 188-191.
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Type
Article