Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/95745
DC Field | Value | Language |
---|---|---|
dc.contributor | School of Hotel and Tourism Management | en_US |
dc.creator | Liu, H | en_US |
dc.creator | Wang, Y | en_US |
dc.creator | Song, H | en_US |
dc.creator | Liu, Y | en_US |
dc.date.accessioned | 2022-10-05T03:56:45Z | - |
dc.date.available | 2022-10-05T03:56:45Z | - |
dc.identifier.issn | 1354-8166 | en_US |
dc.identifier.uri | http://hdl.handle.net/10397/95745 | - |
dc.language.iso | en | en_US |
dc.publisher | SAGE Publications | en_US |
dc.rights | © The Author(s) 2022 | en_US |
dc.rights | This is the accepted version of the publication Liu, H., Wang, Y., Song, H., & Liu, Y. (2023). Measuring tourism demand nowcasting performance using a monotonicity test. Tourism Economics, 29(5), 1302-1327. Copyright © 2022 (The Author(s)). DOI:10.1177/13548166221104291. | en_US |
dc.subject | Mixed frequency data | en_US |
dc.subject | Monotonicity test | en_US |
dc.subject | Nowcasting | en_US |
dc.subject | Tourism demand | en_US |
dc.title | Measuring tourism demand nowcasting performance using a monotonicity test | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.spage | 1302 | en_US |
dc.identifier.epage | 1327 | en_US |
dc.identifier.volume | 29 | en_US |
dc.identifier.issue | 5 | en_US |
dc.identifier.doi | 10.1177/13548166221104291 | en_US |
dcterms.abstract | Tourism demand nowcasting is generally carried out using econometric models that incorporate either macroeconomic variables or search query data as explanatory variables. Nowcasting model accuracy is normally evaluated by traditional loss functions. This study proposes a novel statistical method, the monotonicity test, to assess whether the nowcasting errors obtained from the ordinary least squares, generalised dynamic factor model and generalised dynamic factor model combined with mixed data sampling model are monotonically decreasing when new data on explanatory variables become available, based on the mixed frequency data between 1 January 2011 and 31 December 2019. The results of the empirical analysis show that nowcasts generated results based on two data sources combined are superior to that based on a single data source. Compared with traditional loss functions, the monotonicity test leads to a more objective and convincing nowcasting model performance. This study is the first attempt to evaluate tourism demand nowcasting performance using a monotonicity test. | en_US |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | Tourism economics, Aug. 2023, v. 29, no. 5, p. 1302-1327 | en_US |
dcterms.isPartOf | Tourism economics | en_US |
dcterms.issued | 2023-08 | - |
dc.identifier.scopus | 2-s2.0-85131083479 | - |
dc.identifier.eissn | 2044-0375 | en_US |
dc.description.validate | 202210 bckw | en_US |
dc.description.oa | Accepted Manuscript | en_US |
dc.identifier.FolderNumber | a1742 | - |
dc.identifier.SubFormID | 45864 | - |
dc.description.fundingSource | RGC | en_US |
dc.description.pubStatus | Published | en_US |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Liu_Tourism_Monotonicity_Test.pdf | Pre-Published version | 1.33 MB | Adobe PDF | View/Open |
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