Coal is the principal form of energy used in China. Hence, coal price variations are expected to have some influence on merchandise prices. Monthly data from January, 2002, to October, 2010, were used to construct a v...Coal is the principal form of energy used in China. Hence, coal price variations are expected to have some influence on merchandise prices. Monthly data from January, 2002, to October, 2010, were used to construct a varying-parameter state space model, and an error correction model, to estimate the influence of coat prices on Chinese merchandise prices. The time lag and the dynamic relationship were determined from the data. A long term equilibrium relationship between coal price and the PPI, and the CPI, can be observed. The long term influence of coal price fluctuations on the PPI is 0.263%. The corresponding value for the CPI is 0.157%. The PPI shows an influence from coal price change in the first period of observation： by eight periods the influence is obvious, after which it diminishes. The effect of coal price change on the CPI is rather weak and has no long term memory. Analysis of variance shows a similar situation. The elas- ticity coefficient of coal prices on the CPI, or the PPI, fluctuates over the 2002-2004 period. From 2002 to 2007 the influence elasticity on the CPI declined and subsequently levelled off after 2009.展开更多
This works examine the responses of housing prices to the monetary policies in various Chinese cities. Thirty-five large and medium sized Chinese cities are classified into six clusters applying the minimum variance c...This works examine the responses of housing prices to the monetary policies in various Chinese cities. Thirty-five large and medium sized Chinese cities are classified into six clusters applying the minimum variance clustering method according to the calculated correlation coefficients between the housing price indices of every two cities.Time difference correlation analysis is then employed to quantify the relations between the housing price indices of the six clusters and the monetary policies.It is suggested that the housing prices of various cities evolved at different paces and their responses to the monetary policies are heterogeneous,and local economic features are more important than geographic distances in determining the housing price trends.展开更多
基金support for this work, provided by the National Natural Science Foundation of China (No. 71003097)Jiangsu Province Social Science Foundation (No. 10EYD025)2008 China University of Mining and Technology Youth Foundation Program (No.2008W04)
文摘Coal is the principal form of energy used in China. Hence, coal price variations are expected to have some influence on merchandise prices. Monthly data from January, 2002, to October, 2010, were used to construct a varying-parameter state space model, and an error correction model, to estimate the influence of coat prices on Chinese merchandise prices. The time lag and the dynamic relationship were determined from the data. A long term equilibrium relationship between coal price and the PPI, and the CPI, can be observed. The long term influence of coal price fluctuations on the PPI is 0.263%. The corresponding value for the CPI is 0.157%. The PPI shows an influence from coal price change in the first period of observation： by eight periods the influence is obvious, after which it diminishes. The effect of coal price change on the CPI is rather weak and has no long term memory. Analysis of variance shows a similar situation. The elas- ticity coefficient of coal prices on the CPI, or the PPI, fluctuates over the 2002-2004 period. From 2002 to 2007 the influence elasticity on the CPI declined and subsequently levelled off after 2009.
基金Supported by the Hundred Talent Program of the Chinese Academy of Sciences,the National Natural Science Foundation of China under Grant Nos.71103179 and 71102129Program for Young Innovative Research Team in China University of Political Science and Law, 2010 Fund Project under the Ministry of Education of China for Youth Who are Devoted to Humanities and Social Sciences Research 10YJC630425
文摘This works examine the responses of housing prices to the monetary policies in various Chinese cities. Thirty-five large and medium sized Chinese cities are classified into six clusters applying the minimum variance clustering method according to the calculated correlation coefficients between the housing price indices of every two cities.Time difference correlation analysis is then employed to quantify the relations between the housing price indices of the six clusters and the monetary policies.It is suggested that the housing prices of various cities evolved at different paces and their responses to the monetary policies are heterogeneous,and local economic features are more important than geographic distances in determining the housing price trends.
