In the study, an improved approach was proposed to identify the contribution shares of three group factors that are climate, technology and input, social economic factors by which the grain production is shaped. In or...In the study, an improved approach was proposed to identify the contribution shares of three group factors that are climate, technology and input, social economic factors by which the grain production is shaped. In order to calibrate the method, Jiangxi Province, one of the main paddy rice producers in China was taken as an example. Based on 50 years (1961-2010) meteorological and statistic data, using GIS and statistical analysis tools, the three group factors that in certain extent impact China's paddy rice production have been analyzed quantitatively. The individual and interactive contribution shares of each factor group have been identiifed via eta square (η2). In the paper, two group ordinary leasr square (OLS) models, paddy models and climate models, have been constructed for further analysis. Each model group consists of seven models, one full model and six partial models. The results of paddy models show that climate factors individually and interactively contribute 11.42-15.25%explanatory power to the variation of paddy rice production in the studied province. Technology and input factors contribute 16.17%individually and another 8.46%interactively together with climate factors, totally contributing about 25%. Social economic factors contribute about 7%of which 4.65%is individual contribution and 2.49%is interactive contribution together with climate factors. The three factor groups individually contribute about 23%and interactively contribute additional 41%to paddy rice production. In addition every two of the three factor groups also function interactively and contribute about 22%. Among the three factor groups, technology and input are the most important factors to paddy rice production. The results of climate models support the results of paddy models, and display that solar radiation (indicated by sunshine hour variable) is the dominate climate factor for paddy rice production.展开更多
This paper improves the slacks-based method for estimating inefficiency,derives the criteria for the selection of the weights of output and input inefficiencies in the objective function,and creates a new nonparametri...This paper improves the slacks-based method for estimating inefficiency,derives the criteria for the selection of the weights of output and input inefficiencies in the objective function,and creates a new nonparametric method for accounting economic growth.Based on this method,the paper estimates the sources of China s economic growth from 1978 to 2013.Our findings suggest that factor input and especially capital is a major source of economic growth for China as a whole and its major regions,and that economic growth in recent years is increasingly dependent on capital.For a rather long period of time before 2005,China s northeast,central and western regions lagged behind the eastern region in terms of economic growth,and TFP and factor input are major reasons behind such regional growth disparities.Although other regions have narrowed their disparities with and even overtaken the eastern region in terms of economic growth,the key driver is the rapid increase in the contribution of factor input.Advanced technologies of eastern region should be utilized to promote TFP progress in other regions,which is vital to economic growth in these regions and China as a whole.展开更多
基金financed by the National Basic Research Program of China(2010CB951502)
文摘In the study, an improved approach was proposed to identify the contribution shares of three group factors that are climate, technology and input, social economic factors by which the grain production is shaped. In order to calibrate the method, Jiangxi Province, one of the main paddy rice producers in China was taken as an example. Based on 50 years (1961-2010) meteorological and statistic data, using GIS and statistical analysis tools, the three group factors that in certain extent impact China's paddy rice production have been analyzed quantitatively. The individual and interactive contribution shares of each factor group have been identiifed via eta square (η2). In the paper, two group ordinary leasr square (OLS) models, paddy models and climate models, have been constructed for further analysis. Each model group consists of seven models, one full model and six partial models. The results of paddy models show that climate factors individually and interactively contribute 11.42-15.25%explanatory power to the variation of paddy rice production in the studied province. Technology and input factors contribute 16.17%individually and another 8.46%interactively together with climate factors, totally contributing about 25%. Social economic factors contribute about 7%of which 4.65%is individual contribution and 2.49%is interactive contribution together with climate factors. The three factor groups individually contribute about 23%and interactively contribute additional 41%to paddy rice production. In addition every two of the three factor groups also function interactively and contribute about 22%. Among the three factor groups, technology and input are the most important factors to paddy rice production. The results of climate models support the results of paddy models, and display that solar radiation (indicated by sunshine hour variable) is the dominate climate factor for paddy rice production.
文摘This paper improves the slacks-based method for estimating inefficiency,derives the criteria for the selection of the weights of output and input inefficiencies in the objective function,and creates a new nonparametric method for accounting economic growth.Based on this method,the paper estimates the sources of China s economic growth from 1978 to 2013.Our findings suggest that factor input and especially capital is a major source of economic growth for China as a whole and its major regions,and that economic growth in recent years is increasingly dependent on capital.For a rather long period of time before 2005,China s northeast,central and western regions lagged behind the eastern region in terms of economic growth,and TFP and factor input are major reasons behind such regional growth disparities.Although other regions have narrowed their disparities with and even overtaken the eastern region in terms of economic growth,the key driver is the rapid increase in the contribution of factor input.Advanced technologies of eastern region should be utilized to promote TFP progress in other regions,which is vital to economic growth in these regions and China as a whole.