Unconditional quantile regression analysis of UK inbound tourist expenditures

Abhijit Sharma, Richard Woodward, Stefano Grillini

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)
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Using International Passenger Survey (2017) data, this paper employs unconditional quantile regression (UQR) to analyse the determinants of tourist expenditure amongst inbound tourists to the United Kingdom. UQR allows us to estimate heterogeneous effects at any quantile of the distribution of the dependent variable. It overcomes the econometric limitations of ordinary least squares and quantile regression based estimates typically used to investigate tourism expenditures. However, our results reveal that the effects of our explanatory variables change across the distribution of tourist expenditure. This has important implications for those tasked with devising policies to enhance the UK’s tourist flows and expenditures.
Original languageEnglish
Article number108857
Number of pages4
JournalEconomics Letters
Early online date21 Nov 2019
Publication statusPublished - Jan 2020

Bibliographical note

NOTICE: this is the author’s version of a work that was accepted for publication in Economics Letters. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Economics Letters, 186, (2020) DOI: 10.1016/j.econlet.2019.108857

© 2019, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/


  • Tourist expenditures
  • Unconditional quantile regressions
  • United Kingdom

ASJC Scopus subject areas

  • Finance
  • Economics and Econometrics


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