Econometric Modelling and Forecasting of Tourism Demand "Methods and Applications"

por Wu, Doris Chenguang
Econometric Modelling and Forecasting of Tourism Demand "Methods and Applications"
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ISBN: 978-1-03-221641-6
Editorial: Routledge
Fecha de la edición: 2022
idioma: Ingles
Nº Pág.: 326


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Resumen del libro

Reseña: 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. Written by a plethora of worldwide experts on this topic, this book offers a comprehensive approach to tourism econometrics. Accurate demand forecasts are crucial to decision-making in the tourism industry and this book provides real-life tourism applications and the corresponding R code alongside theoretical foundations, in order to enhance understanding and practice amongst its readers. The methodologies introduced include general to specific modelling, cointegration, vector autoregression, time-varying parameter modelling, spatiotemporal econometric models, mixed-frequency forecasting, hybrid forecasting models, forecasting combination techniques, density forecasting, judgemental forecasting, scenario forecasting under crisis, and web-based tourism forecasting. Embellished with insightful figures and tables throughout, this book is an invaluable resource for those using advanced econometric methodologies in their studies and research, including both undergraduate and postgraduate students, researchers, and practitioners.
indice: 1. Overview of Econometric Tourism Demand Modelling and Forecasting Haiyan Song and Hongrun Wu 2. Theoretical Foundations, Key Concepts and Data Description Vera Shanshan Lin, Xinyi Zhang and Richard T. R. Qiu 3. The Autoregressive Distributed Lag Model Anyu Liu and Xinyang Liu 4. The Time-Varying Parameter Model Gang Li, Jason Li Chen and Xiaoying Jiao 5. Vector Autoregressive Models Zheng Chris Cao 6. Spatiotemporal Econometric Models Xiaoying Jiao and Jason Li Chen 7. Mixed-Frequency Models Han Liu, Ying Liu and Peihuang Wu 8. Hybrid Forecasting Models Mingming Hu, Mei Li and Xin Zhao 9. Density Forecasting Long Wen 10. Forecast Combinations Doris Chenguang Wu and Chenyu Cao 11. Judgmental Forecasting Vera Shanshan Lin and Yuan Qin 12. Scenario Forecasting during Crises Richard T. R. Qiu 13. A Web-based Tourism Forecasting System Xinyan Zhang Epilogue Doris Chenguang Wu, Gang Li and Haiyan Song