There is some disagreement in the published literature regarding the definition and the measurement of housing bubbles in China. Extending the analytical framework of Black et al. （2006）, the present paper measures ...There is some disagreement in the published literature regarding the definition and the measurement of housing bubbles in China. Extending the analytical framework of Black et al. （2006）, the present paper measures the housing bubbles of China＇s 35 major cities from the second quarter of 1999 to the second quarter of 2010. The results indicate that the housing bubbles in China＇s 35 major cities were relatively small in the sample interval, but the bubbles in eastern metropolises, such as Beijing, Shanghai, Shenzhen, Hangzhou and Ningbo, have been relatively big since 2005. The changing tendency of housing bubbles in most cities highly corresponds with the changes in real estate policies. This paper decomposes the housing bubbles of the 35 cities, and finds a great proportion of irrational bubbles rather than rational intrinsic bubbles generated by price speculation. Based on empirical analysis, this paper proposes policy recommendations for preventing the generation and expansion of housing bubbles.展开更多
Existing literature is characterized by certain deficiencies in measuring housing bubbles in China. By extending the analytical framework of Black et al. （2006） to a spatial panel VAR structure, this paper measures ...Existing literature is characterized by certain deficiencies in measuring housing bubbles in China. By extending the analytical framework of Black et al. （2006） to a spatial panel VAR structure, this paper measures housing bubbles in China＇s 35 major cities from 1999Q2 to 2012Q3 and analyzes the spatial-temporal changes of the housing bubbles in these cities. Results indicate that 1） changes to housing bubbles in most cities highly correspond with changes in the main real estate policies of the country and 2） housing bubbles in eastern developed cities such as Beijing, Shanghai, Shenzhen, Hangzhou, and Ningbo, have been relatively large in recent years although the average housing bubble is not very serious over the 35 major cities. Through the Kernel Density Function and local indicators of spatial autocorrelation analysis, this paper finds that housing bubbles are concentrated in several eastern developed cities. Based on empirical analysis, this paper proposes policy recommendations on inhibiting the expansion and diffusion of housing bubbles.展开更多
In this paper we estimate relative consumer price levels as of 2008 for 36 major Chinese cities, using an innovative method purposely designed to rectify three main defects of the existing literature, which are （1） ...In this paper we estimate relative consumer price levels as of 2008 for 36 major Chinese cities, using an innovative method purposely designed to rectify three main defects of the existing literature, which are （1） the under-representation of marketized services in the sample data, （2） biased consumption weights, and （3） a mismatch between sample classification and consumption weights. Our estimation results show the ＂subnational Penn effect＂ as defined by Tang （2012）, i.e., strong inter-city correlations among population size, the relative price level, per capita nominal and real income, and human capital stock, thereby showing that the theoretical model of inter-city price dispersion proposed by Tang （2012） is applicable in China. Our conclusion, methodology, and estimation results have important implications for various aspects of the Chinese economy including the regional, urban and real-estate economies.展开更多
基金supported by the National Natural Science Foundation of China(No.71173223)the Fundamental Research Funds for the Central Universitiesthe Research Funds of Renmin University of China(No.10XNF049)
文摘There is some disagreement in the published literature regarding the definition and the measurement of housing bubbles in China. Extending the analytical framework of Black et al. （2006）, the present paper measures the housing bubbles of China＇s 35 major cities from the second quarter of 1999 to the second quarter of 2010. The results indicate that the housing bubbles in China＇s 35 major cities were relatively small in the sample interval, but the bubbles in eastern metropolises, such as Beijing, Shanghai, Shenzhen, Hangzhou and Ningbo, have been relatively big since 2005. The changing tendency of housing bubbles in most cities highly corresponds with the changes in real estate policies. This paper decomposes the housing bubbles of the 35 cities, and finds a great proportion of irrational bubbles rather than rational intrinsic bubbles generated by price speculation. Based on empirical analysis, this paper proposes policy recommendations for preventing the generation and expansion of housing bubbles.
文摘Existing literature is characterized by certain deficiencies in measuring housing bubbles in China. By extending the analytical framework of Black et al. （2006） to a spatial panel VAR structure, this paper measures housing bubbles in China＇s 35 major cities from 1999Q2 to 2012Q3 and analyzes the spatial-temporal changes of the housing bubbles in these cities. Results indicate that 1） changes to housing bubbles in most cities highly correspond with changes in the main real estate policies of the country and 2） housing bubbles in eastern developed cities such as Beijing, Shanghai, Shenzhen, Hangzhou, and Ningbo, have been relatively large in recent years although the average housing bubble is not very serious over the 35 major cities. Through the Kernel Density Function and local indicators of spatial autocorrelation analysis, this paper finds that housing bubbles are concentrated in several eastern developed cities. Based on empirical analysis, this paper proposes policy recommendations on inhibiting the expansion and diffusion of housing bubbles.
文摘In this paper we estimate relative consumer price levels as of 2008 for 36 major Chinese cities, using an innovative method purposely designed to rectify three main defects of the existing literature, which are （1） the under-representation of marketized services in the sample data, （2） biased consumption weights, and （3） a mismatch between sample classification and consumption weights. Our estimation results show the ＂subnational Penn effect＂ as defined by Tang （2012）, i.e., strong inter-city correlations among population size, the relative price level, per capita nominal and real income, and human capital stock, thereby showing that the theoretical model of inter-city price dispersion proposed by Tang （2012） is applicable in China. Our conclusion, methodology, and estimation results have important implications for various aspects of the Chinese economy including the regional, urban and real-estate economies.
