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.
Author(s): Doris Chenguang Wu, Gang Li, Haiyan Song
Publisher: Routledge
Year: 2022
Language: English
Pages: 326
City: London
Cover
Half Title
Title Page
Copyright Page
Table of Contents
List of figures
List of tables
List of contributors
Preface
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 Judgemental forecasting
12 Scenario forecasting during crises
13 A web-based tourism forecasting system
Epilogue
Index
