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The connectedness between Hong Kong and China real estate markets: spillover effect and information transmission

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Abstract

Frequently migration between Hong Kong (HK) and China can cause the real estate price standards of HK’s and China’s first-tier cities to resemble one another. This study adopts the real estate prices of HK and four major cities in China, namely Beijing, Shanghai, Shenzhen, and Guangzhou, from January 2001 to April 2019. The results reveal that for both long- and short-term returns, the HK real estate market is influenced by the Shanghai real estate market. The HK real estate market and the Shenzhen real estate market exhibit the most connectedness. This may be because of their geographic closeness; people are more likely to migrate between these two cities. The real estate market in Beijing exhibits the greatest informativeness. In the four cities, only the informativeness of Guangzhou City substantially lags behind that of HK. This study also discovers that in the relationship between those regional real estate markets, exchange rate and stock market returns are key factors. The connection between the housing markets of Beijing and Hong Kong is attributable to the foreign exchange market, whereas the connection between the housing markets of Hong Kong and other first-tier cities is attributable to the stock market. The change in exchange rate influences the volatility of Beijing’s real estate market. After this volatility is transmitted to HK, it influences the correlation between HK and Shanghai real estate markets as well as between HK and Shenzhen real estate markets.

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Notes

  1. The duration of Cheng and Glascock’s (2005) research is from January 1993 to August 2004. Their samples come from the Morgan Stanley Capital International weekly stock market index given in US dollars. Innovation accounting analysis is adopted to observe variance of prediction error, and they discover that only a low percentage of Hong Kong index can be explained by the China index, at most 1.28%.

  2. The study of Huo and Ahmed (2017) was from the period between July 2, 2014 and April 8, 2015. The samples come from the Shanghai Stock Exchange composite index and the Hong Kong Hang Seng Index every minute. The estimation results demonstrate that the stock index of the two places can be predicted by the lagging-period price of itself or the other. After the Shanghai–Hong Kong Stock Connect, Shanghai stock price exerts a significant spillover effect on Hong Kong stock price.

  3. Zhang et al. (2016) point out that the economic structure in China was constantly improved and upgraded, and there have been some new developments in the country's real estate market.

  4. Bodart and Reding (1999) found that that an increase in exchange rate volatility is accompanied by a decline in international correlations between bond and stock markets. Kim et al. (2006) found that real economic integration and the reduction in currency risk have generally had the desired effect of inter-financial market integration.

  5. Figures 3 and 4 present dynamic spillover effects between variables estimated through rolling windows. The spillover index is estimated using variance decomposition based on a generalized VAR model, and thus the length of rolling-sample windows (i.e., the window size) must be determined in consideration of the number of variables and the degree of lag. Numerous variables or a high degree of lag indicates the necessity of a numerous periods (i.e., a large window size) in the estimation. Empirical studies choose their window size according to their sample requirements. For example, Diebold and Yilmaz (2013) determine the length of their rolling-sample windows to be 60 periods, whereas Tsai and Chiang (2019) use 40 periods as their window size. The present study, given the few variables included and to reveal variations in the correlations between different periods, uses a relatively concise model for estimation. This paper estimated total connectedness over 24-month rolling-sample windows.

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Acknowledgements

I am immensely grateful to Professor Robert M. Kunst (Editor) and the anonymous referee for the constructive comments of this paper.

Funding

Funding from the Ministry of Science and Technology of Taiwan under Project No. MOST 110-2410-H-390-008-MY3 has enabled the continuation of this research and the dissemination of these results.

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  1. Department of Finance, National University of Kaohsiung, No. 700, Kaohsiung University Rd., Nanzih District, 811, Kaohsiung, Taiwan

    I-Chun Tsai

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  1. I-Chun Tsai
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Correspondence to I-Chun Tsai.

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Tsai, IC. The connectedness between Hong Kong and China real estate markets: spillover effect and information transmission. Empir Econ 63, 287–311 (2022). https://doi.org/10.1007/s00181-021-02143-y

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