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Forecasting tourist arrivals: Google Trends meets mixed-frequency data

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11230%2F21%3A10398967" target="_blank" >RIV/00216208:11230/21:10398967 - isvavai.cz</a>

  • Alternative codes found

    RIV/61384399:31120/21:00054383

  • Result on the web

    <a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=4T2bq00Q0h" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=4T2bq00Q0h</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1177/1354816619879584" target="_blank" >10.1177/1354816619879584</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Forecasting tourist arrivals: Google Trends meets mixed-frequency data

  • Original language description

    n this article, we examine the usefulness of Google Trends data in predicting monthly tourist arrivals and overnight stays in Prague during the period between January 2010 and December 2016. We offer two contributions. First, we analyze whether Google Trends provides significant forecasting improvements over models without search data. Second, we assess whether a high-frequency variable (weekly Google Trends) is more useful for accurate forecasting than a low-frequency variable (monthly tourist arrivals) using mixed-data sampling (MIDAS). Our results suggest the potential of Google Trends to offer more accurate predictions in the context of tourism: we find that Google Trends information, both 2 months and 1 week ahead of arrivals, is useful for predicting the actual number of tourist arrivals. The MIDAS forecasting model employing weekly Google Trends data outperforms models using monthly Google Trends data and models without Google Trends data.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    50201 - Economic Theory

Result continuities

  • Project

    <a href="/en/project/GX19-26812X" target="_blank" >GX19-26812X: Frontiers in Energy Efficiency Economics and Modelling - FE3M</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2021

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Tourism Economics

  • ISSN

    1354-8166

  • e-ISSN

  • Volume of the periodical

    27

  • Issue of the periodical within the volume

    1

  • Country of publishing house

    GB - UNITED KINGDOM

  • Number of pages

    20

  • Pages from-to

    129-148

  • UT code for WoS article

    000490106000001

  • EID of the result in the Scopus database

    2-s2.0-85074075455