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    Enhancing understanding of tourist spending using unconditional quantile regression

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    Publication date
    2017-09
    Author
    Rudkin, Simon
    Sharma, Abhijit
    Keyword
    Unconditional quantile regression; Tourist spending; Spending analysis
    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.
    
    Metadata
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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.
    URI
    http://hdl.handle.net/10454/12963
    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.
    Link to publisher’s version
    http://dx.doi.org/10.1016/j.annals.2017.06.003
    Type
    Article
    Collections
    Management and Law Publications

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