The real estate industry in China has boomed since 1998 (Fung, Jeng, & Liu, 2010). The real estate market is an important part of China's economy. Real property composes major part of social wealth. Real estate price index is one of national economy vanes. Meanwhile, Chinese stock market develops from a weak efficient market to a semi-strong efficient market, and becomes an important barometer of national economy. Research on interaction mechanism of Chinese real estate market and stock market will help investors choose reasonable assets and establish efficient portfolios, and help Chinese government carry out effective supervision on capital markets. For example, Chinese government should control the amount of "hot money" that flows into stock market in order to avoid stock bubble while squeeze real estate bubble.
This study applies time series analysis to divide Chinese real estate market into three sub-periods based on real estate sales price indexes from January 1999 to November 2009. ADF test, co-integration test, and Granger Causality test results show that the fluctuations of Chinese real estate prices and stock prices have stage correlation, in some sub-periods the real estate market led the stock market. It might provide helpful information for investors to establish effective portfolios and for Chinese government to make relevant policies.
The arguments about the relationship and interaction mechanism of real estate market and stock market are mainly divided into two sides: segmented or integrated. Liu, Hartzell, Greig, & Grissom (1990) researched the relationship between the U.S real estate market and stock market with asset pricing model and concluded that two markets were segmented. However, Ibbotson & Siegel (1984) analyzed the relationship between the U.S real estate prices and S&P 500 stock index and found the existence of negative correlation. Studies of Okunev & Wilson (1997), Okunev, Wilson & Zurbruegg (2001), and Ullah & Zhou (2003) showed the existence of correlation between the U.S real estate market and stock market, and the stock market played a leading role. Quan & Titman (1999) studied relationship between real estate prices and stock prices of 17 countries, and concluded there was significant positive correlation in the long run. Studies of Stone & Ziemba (1993), Liow (2006), and Shen & Lu (2008) separately showed positive correlations between real estate markets and stock markets in Japan, Singapore and China. Hence it is unclear whether real estate market and stock market are segmented or integrated.
METHODOLOGY AND EMPIRICAL RESULTS
The monthly data of Chinese Real Estate Sales Price Index (CRPI) is selected to analysis Chinese real estate fluctuating cycles. Data is from China Economic Information Network Statistics Database.
Shanghai Composite Index HCPI and Shenzhen Component Index SCPI are chosen as the indexes to measure prices changes in Chinese stock market. HCPI and SCPI are published by Shanghai Stock Exchange and Shenzhen Stock Exchange.
In order to remove heteroscedasticity and reduce volatility, the indexes are made dimensionless and taken logarithm to get the corresponding new variables which are LCRPI, LHCPI and LSCPI.
Time Series Analysis and Test
The basic principle of time series analysis is that any economic time series can be composed of its first order differential sequence. To increase the symmetry of differential sequence, mean of all differential values are calculated. Then a new time series can be generated with the first order differences and the mean.
First, we define Y(t) as time series of Chinese real estate price index (CRPI). Then the first order differential sequence of Y(t) is generated:
Y[??](t)= Y(t + 1)- Y(t) (t = 1, 2, 3, ...., n) (n=131)
The results of ADF test indicate that Y[??](t) is stationary at the 1 percent level of significance.
[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII]
H is the average value of Y[??](t) covered t - 1 years. Here, H = 0.1323> 0, which indicates the trend of Y(t) is upward.
Y[??](f)= Y[??](t)- H (1[pounds sterling] t [pounds sterling] n - 1)
Then the new differential time series Y[??](t) is generated and shown in figure 1.
[FIGURE 1 OMITTED]
Overall, the fluctuating trend of Chinese real estate market is upward. Combined with major events during the period, Chinese real estate market can be divided into three sub-periods: January 1999 to April 2005, May 2005 to January 2008, and March 2008 to October 2009.
Augment Dickey-Fuller Test (ADF test)
ADF test is applied respectively on time series of LCRPI, LHCPI, and LSCPI and their first order differences DLCRPI, DLHCPI, and DLSCPI in three sub-periods. ADF statistic values are less than critical values at the 1 percent significance level after the first order difference. So the first order difference sequences are stationary.
Cointegration Causal Test
First, we estimate equations with OLS method.
LCRPI = [c.sub.1] + a xLHCPI + [e.sub.1]
LCRPI = [c.sub.2] + b xLSCPI + [e.sub.2]
a, b are parameters, and [e.sub.1], [e.sub.2] are residuals.
In the total period, there are equations as follows:
LCRPI = 4.384371+ 0.033060LHCPI + [e.sub.1]
(61.07283) (3.472573) [R.sup.2] =0.085488 S.E=0.043307 F=12.05876
LCRPI=4.437370+0.023084LSCPI + [e.sub.2]
(75.04605) (3.320789) [R.sup.2] =0.078753 S.E=0.043466 F=11.02764
Then, we test the unit roots of residuals series.
Residuals series are stable. The equations are not spurious regressions. So LCRPI is integrated with LHCPI, and LSCPI.
Granger Causality Tests
n order to obtain the Granger causes of stock market and real estate market, the lags of first to tenth orders are calculated based on the Granger test method of Vector Auto Regression (VAR) model. Results are showed in table 4.
The results show that the fluctuations of Chinese real estate prices and stock prices appear stage correlation. In the period of 1999 to 2007, LCRPI was Granger cause of LHCPI and LSCPI. So the real estate market led the stock market in the sub-period.
This study examines the relationship between Chinese real estate market and stock market. It applies time series analysis to divide Chinese real estate market into three sub-periods based on real estate sales price indexes. ADF test, co-integration test, and Granger Causality test results show that Chinese real estate market and stock market are integrated, in some sub-periods the real estate market led the stock market.
This relationship can be explained by many factors and theories. First, many economic factors including national economic development, inflation rates, interest rates and others affect real estate prices and stock prices at the same time, so the changes of real estate prices and stock prices might exist some correlation. Then, real estate and stock are symbols for both wealth and investment tools. The relationship between real estate and stock can be interpreted by wealth effect, crowding-out effect, substitution effect and portfolio theory.
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Xiaohui Gao, Shanghai University of Finance and Economics
Jingyi Li, Shanghai Taxation Bureau
Anthony Yanxiang Gu, State University of New York at Geneseo
Table 1: The Results of ADF Tests On Y(t) and Y'(t) ADF Test PROB. Statistic Y (t) -3.156089 0.0983 Y