Study On The Influencing Factors Of Yuan Industrial Added Value Of Water In Jiangsu Province

Industry occupies a very large proportion of the economic development of Jiangsu Province, While the low efficiency of industrial water and scarce water resources has seriously hampered the development of the industrial economy. This paper focuses on the analysis of industrial water use efficiency of the driving factors in Jiangsu Province, through the establishment of yuan industrial added value of water as the dependent variable, the mathematical model of each factor as independent variables, using multiple linear regression equation based on principal component analysis of its analysis and research. Eventually filter out the five most influential factors provide reference and basis for the management and regulation of water resources in Jiangsu Province.In the widely read papers on the basis of the relevant literature, mainly in the following research:(1)analyzing the content yuan industrial added value of water, and explains the principles of multiple linear regression model based on principal component analysis and overview of Jiangsu Province industrial water efficiency, including water resource endowments Jiangsu Province, Jiangsu Province,as well as the status and characteristics of industrial water stage Jiangsu Province have taken measures to improve industrial efficiency water.(2)through the relevant literature and research results of reading research and reference expert guidance on the factors that may affect Jiangsu Province yuan industrial added value of water is classified and identification,will be divided into environmental resources,industrial economy,technology management in four areas of the average annual temperature is selected, the per capita water resources and other12indicators as independent variables and the dependent variable yuan industrial added value of water together to build regression models,time series from1997to2012.(3) Because among the index may have a strong correlation, this paper first principal component analysis of various indicators for processing, and the establishment of multiple linear regression equations were analyzed on the basis of the results. Final results showed that:the Tariff (TF),the pollutant emission concentration (EP), the Industrial added value per capita(CI), the industrial output value of the high industry accounted for the proportion of industrial output (HT) and medium-sized industrial enterprises in R&D expenditures accounted for the proportion of main business income (MI)of its more significant impact.(4) make a summary of the main content and future research are discussed.