Econometric Modelling and Forecasting of Tourism Demand
Methods and Applications
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Book Description
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.
Table of Contents
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
Editor(s)
Biography
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.