An Empirical Analysis of the Relationship between Industrial Structure Adjustment and Environmental Pollution——Based on Fujian Province
Zhan Li-lin
Abstract
Zhan Li-lin
Abstract
This paper conducts empirical research of relationship between industrial adjustment and environmental pollution by constructing the VAR model on the basis of the index date of industrial structure and environmental pollution in Fujian Province from the year 1986 to 2012. The results show that there is mutual action between industrial structure adjustment and environmental pollution, and industrial structure is an important variable of environmental pollution prediction variance. Furthermore,heavy industry structure of secondary industry is an important variable of environmental pollution prediction variance, that is, industrial structure adjustment will aggravate environmental pollution, and especially heavy industry structure has a considerable contribution to it. Finally, in view of analysis,this paper presents relevant suggestions.
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This paper conducts empirical research of relationship between industrial adjustment and environmental pollution by constructing the VAR model on the basis of the index date of industrial structure and environmental pollution in Fujian Province from the year 1986 to 2012. The results show that there is mutual action between industrial structure adjustment and environmental pollution, and industrial structure is an important variable of environmental pollution prediction variance. Furthermore,heavy industry structure of secondary industry is an important variable of environmental pollution prediction variance, that is, industrial structure adjustment will aggravate environmental pollution, and especially heavy industry structure has a considerable contribution to it. Finally, in view of analysis,this paper presents relevant suggestions.
Key concepts: Pollution, Industrial pollution, Variance (accounting), Environmental pollution, Variable (mathematics), Environmental science, Environmental protection, Business