Interaction between the stock market and property market prices in China: An empirical analysis

Yang, Xia

Abstract

The importance of the Chinese real estate sector stems from its role as a primary funding source for local governments, enabling infrastructure projects and fostering economic growth. Simultaneously, the Chinese stock market has become a significant indicator of domestic macroeconomic activity and a measure of the nation's financial health. Therefore, understanding the extent of interaction between these markets and the direction of spillover effects is crucial for policy formulation within China and beyond.

To address this issue, the current thesis examines the degree of interaction between the two markets and the broader Chinese economy in the context of a Johansen vector error correction model, which is estimated using monthly data. While such modelling is common in the literature, this study is unique in suggesting that these markets operate without money illusion, with spillover effects primarily reflecting interactions between real equity prices, real house prices, and their corresponding rates of change. Additionally, the study highlights the influence of macroeconomic uncertainty, measured as the predicted latent variable from a dynamic factor model, on market behaviour and interaction. The analysis applies Diebold and Yilmaz's (2014) connectedness measures to examine price spillovers and the impact of uncertainty across markets.

The core of the thesis comprises three empirical chapters analysing data from January 2011 to December 2018 collected from various sources. Chapters 3 and 4 use cointegration analysis to focus on the dynamic relationship between the Chinese property market, the stock market, and the broader economy. The results show that while house and share prices do not cointegrate in a bivariate system, they do in an augmented model, suggesting that their interactions operate through direct and indirect channels involving industrial production and real money balances. The results also indicate that market interactions occur in the absence of money illusion, as spillovers between house and equity prices are in real terms.

Chapter 4 extends the modelling framework to include a broad measure of uncertainty. This measure is derived from a dynamic factor model that consolidates data from three uncertainty proxies, with uncertainty corresponding to the predicted value of the latent factor driving the movement of commonly used uncertainty proxies. Introducing this broad uncertainty measure into the cointegration analysis has implications for the preferred model specification and the dynamic interactions between the property and equity markets.

Chapter 5 examines the magnitude and direction of spillovers between China’s property and equity markets and the impact of uncertainty on these markets in the short and long term. Utilising the connectedness measure developed by Diebold and Yilmaz (2014), the analysis examines the scale and direction of spillover between the real estate market and the stock market in China and how this interaction is influenced by uncertainty. The findings indicate that house prices are a net recipient of spillover effects from the stock market in the long run, with the effect of aggregate uncertainty transmitted through real share prices.

Citation

Yang, X. (2025). Interaction between the stock market and property market prices in China: An empirical analysis. (Thesis). Keele University. Retrieved from https://keele-repository.worktribe.com/output/1110006

• Thesis Type: Thesis
• Deposit Date: Mar 21, 2025
• Keywords: Real Estate/Stock Market price; Real Property Market/Real Equity Market Price; Macroeconomic Conditions; China Economic Policy Uncertainty Index; Chicago Board Options Exchange China ETF Volatility Index; the CBOE Crude Oil Volatility Index; Aggregate Economic Uncertainty
• Public URL: https://keele-repository.worktribe.com/output/1110006
• Additional Information: Embargo on access until 3 November 2029 - The thesis is due for publication, or the author is actively seeking to publish this material.
• Award Date: 2025-03