Forecasting Chinese outbound tourist to Singapore, Malaysia and Thailand destinations: A study of state space approach

• Main Authors: Danhua Jiang, Jianxu Liu, Jirakom Sirisrisakulchai, Songsak Sriboonchitta
• Format: Conference Proceeding
• Published: 2020
• Subjects: Physics and Astronomy
• Online Access: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85074942440&origin=inward; http://cmuir.cmu.ac.th/jspui/handle/6653943832/68094
• Institution: Chiang Mai University

© 2019 IOP Publishing Ltd. All rights reserved. This paper aims to forecast the tourism demand of mainland Chinese residents with regard to visiting Singapore, Malaysia and Thailand (SMT) from 2018 to 2022, and examine the factors that influence outbound tourism demand. The empirical results show that income level, tourism price, and substitute price all have an impact on tourism demand, of which income level and substitution price have a positive impact on tourism arrivals; in contrast, tourism price has a negative effect. Afterward, based on the forecasted performance, the TVP-STSM model in state-space form is better than other benchmark models (Linear Regression model, ARIMA model, BSM model, and CSM model). Finally, this study finds the best model to forecast the number of tourists to SMT in the next 5 years. The results show that the largest increase among the three countries goes to Thailand, followed by Singapore and Malaysia; recommendations are also made on the forecasting of trends.