Econometric Modelling and Forecasting of Tourism Demand
Methods and Applications
Herausgeber: Chenguang Wu, Doris; Song, Haiyan; Li, Gang
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Econometric Modelling and Forecasting of Tourism Demand
Methods and Applications
Herausgeber: Chenguang Wu, Doris; Song, Haiyan; Li, Gang
- Broschiertes Buch
This insightful and timely volume provides a succinct, expert-led introduction to the latest developments in advanced econometric methodologies in the context of tourism demand modelling and forecasting.
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This insightful and timely volume provides a succinct, expert-led introduction to the latest developments in advanced econometric methodologies in the context of tourism demand modelling and forecasting.
Produktdetails
- Produktdetails
- Verlag: Taylor & Francis Ltd
- Seitenzahl: 310
- Erscheinungstermin: 27. Oktober 2022
- Englisch
- Abmessung: 151mm x 227mm x 21mm
- Gewicht: 464g
- ISBN-13: 9781032216416
- ISBN-10: 1032216417
- Artikelnr.: 64358365
- Verlag: Taylor & Francis Ltd
- Seitenzahl: 310
- Erscheinungstermin: 27. Oktober 2022
- Englisch
- Abmessung: 151mm x 227mm x 21mm
- Gewicht: 464g
- ISBN-13: 9781032216416
- ISBN-10: 1032216417
- Artikelnr.: 64358365
Doris Chenguang Wu, Ph.D., is a Professor in the School of Business at Sun Yat-sen University, China. Her research interests include tourism demand forecasting and tourism big data analytics. Gang Li, Ph.D., is a Professor of Tourism Economics at the University of Surrey. His research interests include economic analysis and forecasting of tourism demand. Haiyan Song, Ph.D., is Chan Chak Fu Professor of International Tourism in the School of Hotel and Tourism Management at the Hong Kong Polytechnic University. His research interests are in tourism demand modelling and forecasting, tourism supply chain management, and wine economics.
1. Overview of Econometric Tourism Demand Modelling and Forecasting. 2.
Theoretical Foundations, Key Concepts and Data Description. 3. The
Autoregressive Distributed Lag Model. 4. The Time-Varying Parameter Model.
5. Vector Autoregressive Models. 6. Spatiotemporal Econometric Models. 7.
Mixed-Frequency Models. 8. Hybrid Forecasting Models. 9. Density
Forecasting. 10. Forecast Combinations. 11. Judgmental Forecasting. 12.
Scenario Forecasting during Crises. 13. A Web-based Tourism Forecasting
System. Epilogue.
Theoretical Foundations, Key Concepts and Data Description. 3. The
Autoregressive Distributed Lag Model. 4. The Time-Varying Parameter Model.
5. Vector Autoregressive Models. 6. Spatiotemporal Econometric Models. 7.
Mixed-Frequency Models. 8. Hybrid Forecasting Models. 9. Density
Forecasting. 10. Forecast Combinations. 11. Judgmental Forecasting. 12.
Scenario Forecasting during Crises. 13. A Web-based Tourism Forecasting
System. Epilogue.
1. Overview of Econometric Tourism Demand Modelling and Forecasting. 2.
Theoretical Foundations, Key Concepts and Data Description. 3. The
Autoregressive Distributed Lag Model. 4. The Time-Varying Parameter Model.
5. Vector Autoregressive Models. 6. Spatiotemporal Econometric Models. 7.
Mixed-Frequency Models. 8. Hybrid Forecasting Models. 9. Density
Forecasting. 10. Forecast Combinations. 11. Judgmental Forecasting. 12.
Scenario Forecasting during Crises. 13. A Web-based Tourism Forecasting
System. Epilogue.
Theoretical Foundations, Key Concepts and Data Description. 3. The
Autoregressive Distributed Lag Model. 4. The Time-Varying Parameter Model.
5. Vector Autoregressive Models. 6. Spatiotemporal Econometric Models. 7.
Mixed-Frequency Models. 8. Hybrid Forecasting Models. 9. Density
Forecasting. 10. Forecast Combinations. 11. Judgmental Forecasting. 12.
Scenario Forecasting during Crises. 13. A Web-based Tourism Forecasting
System. Epilogue.