Ripple Effect of Housing Prices Fluctuations among Nine Cities of China
This paper applies cointegration test, error correction model, vector error correction model, impulse response analysis and variance decomposition to examine the ripple effect of housing prices fluctuations among Chinese cities during the period of first quarter of 1999 to third quarter of 2008. Empirical analysis indicates that housing prices fluctuations among nine Chinese cities do have ripple effect. We divide the cities into three layers: Beijing, Shanghai as the first layer; Shenyang, Tianjin and Xi’an as the second; and Qingdao, Chongqing, Guangzhou and Dalian as the third one. Empirical results show that: (1) housing prices of municipalities directly under the central government such as Beijing and Shanghai representing the first layer have strong influence and still be the main regulatory objects; (2) cities in the second layer can transmit the fluctuations of housing prices and should be concerned; (3) intense fluctuations of housing prices of cities in the third layer should be avoided. So, the government should make targeted regulatory policies to cities in different layers, which is a more efficient way to control the whole system of housing prices, maintain housing prices in a reasonable range, and eventually achieve the goal of building a harmonious society.Key Words: housing prices; ripple effect; cointegration test; error correction model; vector error correction model
housing prices; ripple effect; cointegration test; error correction model; vector error correction model
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