Elucidating the complex mechanism between urbanization, economic growth, car- bon dioxide emissions is fundamental necessary to inform effective strategies on energy saving and emission reduction in China. Based on a ...Elucidating the complex mechanism between urbanization, economic growth, car- bon dioxide emissions is fundamental necessary to inform effective strategies on energy saving and emission reduction in China. Based on a balanced panel data of 31 provinces in China over the period 1997-2010, this study empirically examines the relationships among urbanization, economic growth and carbon dioxide （CO2） emissions at the national and re- gional levels using panel cointegration and vector error correction model and Granger cau- sality tests. Results showed that urbanization, economic growth and CO2 emissions are inte- grated of order one. Urbanization contributes to economic growth, both of which increase CO2 emissions in China and its eastern, central and western regions. The impact of urbanization on CO2 emissions in the western region was larger than that in the eastern and central re- gions. But economic growth had a larger impact on CO2 emissions in the eastern region than that in the central and western regions. Panel causality analysis revealed a bidirectional long-run causal relationship among urbanization, economic growth and CO2 emissions, in- dicating that in the long run, urbanization does have a causal effect on economic growth in China, both of which have causal effect on CO2 emissions. At the regional level, we also found a bidirectional long-run causality between land urbanization and economic growth in eastern and central China. These results demonstrated that it might be difficult for China to pursue carbon emissions reduction policy and to control urban expansion without impeding economic growth in the long run. In the short-run, we observed a unidirectional causation running from land urbanization to CO2 emissions and from economic growth to CO2 emissions in the eastern and central regions. Further investigations revealed an inverted N-shaped re- lationship between CO2 emissions and economic growth in China, not supporting the envi- ronmental Kuznets curve （EKC） hypothesis. Our empirical findin展开更多
With Granger causality method, this paper examines the causal dynamics among three economic fundamentals: construction investment, other investment and the gross domestic product (GDP). Short-run and long-run interact...With Granger causality method, this paper examines the causal dynamics among three economic fundamentals: construction investment, other investment and the gross domestic product (GDP). Short-run and long-run interactive effects among these three time series are analyzed from 1981 to 2001. The empirical results show that construction investment has a stronger short-run effect on economic growth than other investment, and economic growth has a long-term effect on both construction and other investments. These findings indicate that construction investment is an important factor influencing short-term economic growth fluctuations, with its growth stimulating economic growth and its slumps leading to downside fluctuations. At the same time, invest-ment growth cannot be sustained without the support of the national economy. These empirical results have im-portant implications for economic policy makers in China.展开更多
This paper presents an investigation of the interaction between housing prices and general eco- nomic conditions in China for the period of 1986-2002. The empirical results indicate that housing prices in China are pr...This paper presents an investigation of the interaction between housing prices and general eco- nomic conditions in China for the period of 1986-2002. The empirical results indicate that housing prices in China are predictable by market fundamentals, which could explain most of the variations in housing prices. The results of Granger causality tests confirm that unemployment rate, total population, changes in con- struction costs, changes in the consumer price index (CPI) are all Granger causalities of housing prices, with feedback effects observed to affect the vacancy rate of new dwellings, changes in CPI, and changes in per capita disposable income of urban households. Studies with impulse response functions further illustrate these relationships in terms of the degree of the impact on housing prices from the determinants and the feedbacks. The findings indicate that there is a long-term equilibrium relationship between housing prices and market fundamentals in China and it is the identified fundamentals that drive housing prices up, rather than a bubble.展开更多
小时尺度水面蒸发可影响水面大气边界层热力和动力结构,分析湖泊小时尺度水面蒸发主要影响因素,选取准确模拟其特征的蒸发模型,将有助于改善流域天气预报和空气质量预报.基于太湖避风港站2012—2013年通量、辐射和气象观测数据,分析太...小时尺度水面蒸发可影响水面大气边界层热力和动力结构,分析湖泊小时尺度水面蒸发主要影响因素,选取准确模拟其特征的蒸发模型,将有助于改善流域天气预报和空气质量预报.基于太湖避风港站2012—2013年通量、辐射和气象观测数据,分析太湖小时尺度水面蒸发主要影响因子和3个模型(传统质量传输模型、Granger and Hedstrom经验模型、DYRESM模型)的模拟效果.结果表明:影响太湖小时尺度水面蒸发的主要因子为水气界面水汽压差和风速的乘积,而非净辐射.传统质量传输模型、Granger and Hedstrom经验模型、DYRESM模型模拟值与全年实测值的一致性系数分别为0.92、0.87和0.89,均方根误差分别为28.35、41.58和38.26 W/m^2.传统质量传输模型对太湖小时尺度水面蒸发的日变化和季节动态模拟效果最佳,其夜间模拟相对误差小于3%,除秋季外,其他季节的模拟绝对误差均小于4 W/m^2.Granger and Hedstrom经验模型系统性地高估太湖潜热通量,在大气较为稳定的午后(高估22~32 W/m^2)和冬季(高估72%)高估最为明显,模拟效果最差.DYRESM模型也系统地高估太湖潜热通量,模拟效果居中.考虑水汽交换系数随风速的变化特征将有助于改善传统质量传输模型和DYRESM模型对太湖小时尺度水面蒸发的模拟精度.展开更多
基金National Natural Science Foundation of ChinaNo.41130748+2 种基金No.41471143Major Program of National Social Science Foundation of ChinaNo.15ZDA021
文摘Elucidating the complex mechanism between urbanization, economic growth, car- bon dioxide emissions is fundamental necessary to inform effective strategies on energy saving and emission reduction in China. Based on a balanced panel data of 31 provinces in China over the period 1997-2010, this study empirically examines the relationships among urbanization, economic growth and carbon dioxide （CO2） emissions at the national and re- gional levels using panel cointegration and vector error correction model and Granger cau- sality tests. Results showed that urbanization, economic growth and CO2 emissions are inte- grated of order one. Urbanization contributes to economic growth, both of which increase CO2 emissions in China and its eastern, central and western regions. The impact of urbanization on CO2 emissions in the western region was larger than that in the eastern and central re- gions. But economic growth had a larger impact on CO2 emissions in the eastern region than that in the central and western regions. Panel causality analysis revealed a bidirectional long-run causal relationship among urbanization, economic growth and CO2 emissions, in- dicating that in the long run, urbanization does have a causal effect on economic growth in China, both of which have causal effect on CO2 emissions. At the regional level, we also found a bidirectional long-run causality between land urbanization and economic growth in eastern and central China. These results demonstrated that it might be difficult for China to pursue carbon emissions reduction policy and to control urban expansion without impeding economic growth in the long run. In the short-run, we observed a unidirectional causation running from land urbanization to CO2 emissions and from economic growth to CO2 emissions in the eastern and central regions. Further investigations revealed an inverted N-shaped re- lationship between CO2 emissions and economic growth in China, not supporting the envi- ronmental Kuznets curve （EKC） hypothesis. Our empirical findin
基金Supported by the National Natural Science Foundation of China (No. 79930500)
文摘With Granger causality method, this paper examines the causal dynamics among three economic fundamentals: construction investment, other investment and the gross domestic product (GDP). Short-run and long-run interactive effects among these three time series are analyzed from 1981 to 2001. The empirical results show that construction investment has a stronger short-run effect on economic growth than other investment, and economic growth has a long-term effect on both construction and other investments. These findings indicate that construction investment is an important factor influencing short-term economic growth fluctuations, with its growth stimulating economic growth and its slumps leading to downside fluctuations. At the same time, invest-ment growth cannot be sustained without the support of the national economy. These empirical results have im-portant implications for economic policy makers in China.
基金Supported by the National Natural Science Foundation of China (No. 79930500)
文摘This paper presents an investigation of the interaction between housing prices and general eco- nomic conditions in China for the period of 1986-2002. The empirical results indicate that housing prices in China are predictable by market fundamentals, which could explain most of the variations in housing prices. The results of Granger causality tests confirm that unemployment rate, total population, changes in con- struction costs, changes in the consumer price index (CPI) are all Granger causalities of housing prices, with feedback effects observed to affect the vacancy rate of new dwellings, changes in CPI, and changes in per capita disposable income of urban households. Studies with impulse response functions further illustrate these relationships in terms of the degree of the impact on housing prices from the determinants and the feedbacks. The findings indicate that there is a long-term equilibrium relationship between housing prices and market fundamentals in China and it is the identified fundamentals that drive housing prices up, rather than a bubble.
文摘小时尺度水面蒸发可影响水面大气边界层热力和动力结构,分析湖泊小时尺度水面蒸发主要影响因素,选取准确模拟其特征的蒸发模型,将有助于改善流域天气预报和空气质量预报.基于太湖避风港站2012—2013年通量、辐射和气象观测数据,分析太湖小时尺度水面蒸发主要影响因子和3个模型(传统质量传输模型、Granger and Hedstrom经验模型、DYRESM模型)的模拟效果.结果表明:影响太湖小时尺度水面蒸发的主要因子为水气界面水汽压差和风速的乘积,而非净辐射.传统质量传输模型、Granger and Hedstrom经验模型、DYRESM模型模拟值与全年实测值的一致性系数分别为0.92、0.87和0.89,均方根误差分别为28.35、41.58和38.26 W/m^2.传统质量传输模型对太湖小时尺度水面蒸发的日变化和季节动态模拟效果最佳,其夜间模拟相对误差小于3%,除秋季外,其他季节的模拟绝对误差均小于4 W/m^2.Granger and Hedstrom经验模型系统性地高估太湖潜热通量,在大气较为稳定的午后(高估22~32 W/m^2)和冬季(高估72%)高估最为明显,模拟效果最差.DYRESM模型也系统地高估太湖潜热通量,模拟效果居中.考虑水汽交换系数随风速的变化特征将有助于改善传统质量传输模型和DYRESM模型对太湖小时尺度水面蒸发的模拟精度.
