Spatial econometrics test of pollutant discharge system's driving on green technological innovationby taking 29 provinces and regions' manufacturing industries as examples

Abstract

Abstract: Based on the theory of spatial econometrics, we build up a geographical weighed regression model to analyze the pollutant discharge system's driving on the green technological innovation. In this model, green technological innovation is regarded as explained variable, pollutant discharge system is as explanatory variable, and industrial scale and innovation human resource input are as controlled variables. By taking 29 provinces and regions' manufacturing industries as examples, we apply global Moran's I indexes, local Moran scatter diagrams and LISA clustering maps to explore the spatial autocorrelation of pollutant discharge system and green technological innovation. The GWR model also is used to estimate the driving effect of pollutant discharge system on green technological innovation. The results show that pollutant discharge system and green technological innovation both reveal the characteristics of spatial autocorrelation. The driving effect of pollutant discharge system on green technological innovation also presents spatial differential characteristics, namely the characteristic in developed areas supports Potter hypothesis.The higher the level of economic development, the more significant the driving effect. While in developing areas it does not support Potter hypothesis, the backward economic progress level inhibits the achievement of driving effect.

Key words: pollutant discharge system, spatial correlation, green technological innovation, GWR model

CLC Number:

F273.1

Li Wanhong. Spatial econometrics test of pollutant discharge system's driving on green technological innovationby taking 29 provinces and regions' manufacturing industries as examples[J]. Science Research Management, 2015, 36(6): 1-9.

References

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