Causality between tourism and housing prices: a wavelet-based approach

ABSTRACT

This paper aims to examine the relationship between tourism activities and housing prices (HP) in China’s eight central provinces using wavelet transform context structures. This innovative technique allows the decomposition of a time series at different time frequencies. In this work, the researchers used continuous wavelets, wavelet coherence and wavelet phase-difference based on Granger causality analysis to investigate the relationship between tourism activities and HP. The study results indicate that the relationship is generally positive but changes over time exhibiting low to high-frequency cycles. The government needs to increase tourism demand and further provide and nurture the expansion of tourism supply.

KEYWORDS:

• Tourism activities
• housing prices
• wavelet analysis
• time domains
• frequency domains

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 Here is the website for the data: http://www.stats.gov.cn/english/

2 Without smoothing, the squared wavelet coherence would be always one at any frequency and time. Smoothing is achieved by convolution in time and frequency; see Torrence and Compo (1998) for details.