Forecasting tourist accommodation demand in New Zealand
Tourism accounts for about 9% of New Zealand’s Gross Domestic Product, 10% ofemployment and 18% of export earnings in 2007 (Ministry of Tourism, 2008a). The industry is NewZealand’s largest export earner and its major tourist source markets include Australia, UK, USA, Japan and China. International...
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| Format: | Conference Paper |
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The Modelling and Simulation Society of Australia and New Zealand Inc.
2009
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| Online Access: | http://hdl.handle.net/20.500.11937/7159 |
| _version_ | 1848745285952471040 |
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| author | Lim, C. Chan, Felix |
| author2 | Anderssen, R.S |
| author_facet | Anderssen, R.S Lim, C. Chan, Felix |
| author_sort | Lim, C. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Tourism accounts for about 9% of New Zealand’s Gross Domestic Product, 10% ofemployment and 18% of export earnings in 2007 (Ministry of Tourism, 2008a). The industry is NewZealand’s largest export earner and its major tourist source markets include Australia, UK, USA, Japan and China. International and domestic tourists in New Zealand use a range of accommodation in their travel, from private homes to commercial and other accommodation. Tourist accommodation types are classified under the following five categories: hotels (include resorts), motels (motor inns, apartments and motels), hosted (private hotels, guesthouses, bed and breakfast and farm stays), backpackers/hostels, and caravan parks/camping grounds (Ministry of Tourism, 2008b). Figure 1 shows that tourist accommodation available from 1997 to 2007 is predominantly hotels and motels.Seasonality has attracted considerable interest in empirical tourism research and forecasting. However, the analysis of such recurring phenomenon is sparse in hospitality research, with only one study to date having analysed seasonal unit roots prior to forecasting guest nights for the tourist lodging industry. This paper examines the seasonality of hotel-motel occupancy in New Zealand using monthly time series from 1997 to 2007. The presence of seasonal unit roots is detected using the HEGY procedures. Numerous Box-Jenkins models are estimated and the twelve differenced SARMA(2,2)(0,2)12 is the optimal model selected to forecast hotel-motel room nights. |
| first_indexed | 2025-11-14T06:14:56Z |
| format | Conference Paper |
| id | curtin-20.500.11937-7159 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T06:14:56Z |
| publishDate | 2009 |
| publisher | The Modelling and Simulation Society of Australia and New Zealand Inc. |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-71592022-12-09T05:23:43Z Forecasting tourist accommodation demand in New Zealand Lim, C. Chan, Felix Anderssen, R.S R.D. Braddock, L.T.H. Newham HEGY procedures Seasonality unit roots nonstationarity forecasting hotel-motel room nights Tourism accounts for about 9% of New Zealand’s Gross Domestic Product, 10% ofemployment and 18% of export earnings in 2007 (Ministry of Tourism, 2008a). The industry is NewZealand’s largest export earner and its major tourist source markets include Australia, UK, USA, Japan and China. International and domestic tourists in New Zealand use a range of accommodation in their travel, from private homes to commercial and other accommodation. Tourist accommodation types are classified under the following five categories: hotels (include resorts), motels (motor inns, apartments and motels), hosted (private hotels, guesthouses, bed and breakfast and farm stays), backpackers/hostels, and caravan parks/camping grounds (Ministry of Tourism, 2008b). Figure 1 shows that tourist accommodation available from 1997 to 2007 is predominantly hotels and motels.Seasonality has attracted considerable interest in empirical tourism research and forecasting. However, the analysis of such recurring phenomenon is sparse in hospitality research, with only one study to date having analysed seasonal unit roots prior to forecasting guest nights for the tourist lodging industry. This paper examines the seasonality of hotel-motel occupancy in New Zealand using monthly time series from 1997 to 2007. The presence of seasonal unit roots is detected using the HEGY procedures. Numerous Box-Jenkins models are estimated and the twelve differenced SARMA(2,2)(0,2)12 is the optimal model selected to forecast hotel-motel room nights. 2009 Conference Paper http://hdl.handle.net/20.500.11937/7159 http://creativecommons.org/licenses/by/4.0/ The Modelling and Simulation Society of Australia and New Zealand Inc. fulltext |
| spellingShingle | HEGY procedures Seasonality unit roots nonstationarity forecasting hotel-motel room nights Lim, C. Chan, Felix Forecasting tourist accommodation demand in New Zealand |
| title | Forecasting tourist accommodation demand in New Zealand |
| title_full | Forecasting tourist accommodation demand in New Zealand |
| title_fullStr | Forecasting tourist accommodation demand in New Zealand |
| title_full_unstemmed | Forecasting tourist accommodation demand in New Zealand |
| title_short | Forecasting tourist accommodation demand in New Zealand |
| title_sort | forecasting tourist accommodation demand in new zealand |
| topic | HEGY procedures Seasonality unit roots nonstationarity forecasting hotel-motel room nights |
| url | http://hdl.handle.net/20.500.11937/7159 |