Tourism and House Prices: A Wavelet Analysis

This paper aims to examine the relationship between tourism activities and house prices (HP) in first-tier cities of China (Beijing, Shanghai and Guangzhou) using the wavelet transform context structures. This innovative technique allows the decomposition of time-series at different time frequencies. In this work, we used continuous wavelets, wavelet coherence and wavelet phase difference based on Granger causality analysis to investigate the relationship between tourism activities and HP. Results indicate that the relationship is generally positive but changes over time, displaying low to high frequency cycles. There is a unidirectional causal influence of HP on tourism activities. Moreover, the timing and frequency changes when HP co-moves with tourism. Accordingly, it can be recommended that the government increases and promotes tourism demand and further provides and nurtures the expansion of tourism supply.