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dc.contributor.authorRudkin, Simon*
dc.contributor.authorSharma, Abhijit*
dc.date.accessioned2017-08-23T11:47:16Z
dc.date.available2017-08-23T11:47:16Z
dc.date.issued2017-09
dc.identifier.citationRudkin S and Sharma A (2017) Enhancing understanding of tourist spending using unconditional quantile regression. Annals of Tourism Research. 66: 188-191.en_US
dc.identifier.urihttp://hdl.handle.net/10454/12963
dc.descriptionyesen_US
dc.description.abstractThis 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.en_US
dc.language.isoenen_US
dc.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.en
dc.subjectUnconditional quantile regression; Tourist spending; Spending analysisen_US
dc.titleEnhancing understanding of tourist spending using unconditional quantile regressionen_US
dc.status.refereedYes.en_US
dc.date.Accepted2017-06-14
dc.date.application2017-06-22
dc.typeArticleen_US
dc.type.versionAccepted manuscripten_US
dc.identifier.doihttps://doi.org/10.1016/j.annals.2017.06.003
refterms.dateFOA2019-06-25T12:50:44Z


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