This paper applies a spatial autocorrelation method to empirical data about the Huaihe River and provides a reference for research concerning other rivers. It uses the method of spatial econometrics to determine the relationship between the existing “Cancer Villages” on the Huaihe River and the economic development and polluting emissions of nearby urban areas, using combined pollution frequency of BOD, COD, Ammonia and industrial wastewater as indices of pollution levels, through the establishment of spatial regression and cross section analysis models. The study aims to analyze cancer villages’ spillover effect on big cities and the importance of the different model parameters. Results show that the ordinary OLS (Ordinary Least Squares) goodness-of-fit is lower than the goodness-of-fit of the SAR (Spatial Auto-Regressive) model on average, further confirming the disadvantage of the OLS model, failing to consider the spatial correlations. Parameter estimation results show the change rate of GDP per capita size is 0.11%, 0.20%, 0.28%, and 0.22% when industrial wastewater emissions increase by 1% in Jiangsu Province, Anhui Province, Henan Province, and Shandong Province, respectively. This method could be used in future research works to highlight some facets of the relationship that are completely hidden in regional relationships and allow the investigator to raise questions about the origin and dynamics of cancer villages, an irreversible damage to the environment and society.

Spatial correlation model of economy-energy-pollution interactions: The role of river water as a link between production sites and urban areas

ULGIATI, Sergio
2017-01-01

Abstract

This paper applies a spatial autocorrelation method to empirical data about the Huaihe River and provides a reference for research concerning other rivers. It uses the method of spatial econometrics to determine the relationship between the existing “Cancer Villages” on the Huaihe River and the economic development and polluting emissions of nearby urban areas, using combined pollution frequency of BOD, COD, Ammonia and industrial wastewater as indices of pollution levels, through the establishment of spatial regression and cross section analysis models. The study aims to analyze cancer villages’ spillover effect on big cities and the importance of the different model parameters. Results show that the ordinary OLS (Ordinary Least Squares) goodness-of-fit is lower than the goodness-of-fit of the SAR (Spatial Auto-Regressive) model on average, further confirming the disadvantage of the OLS model, failing to consider the spatial correlations. Parameter estimation results show the change rate of GDP per capita size is 0.11%, 0.20%, 0.28%, and 0.22% when industrial wastewater emissions increase by 1% in Jiangsu Province, Anhui Province, Henan Province, and Shandong Province, respectively. This method could be used in future research works to highlight some facets of the relationship that are completely hidden in regional relationships and allow the investigator to raise questions about the origin and dynamics of cancer villages, an irreversible damage to the environment and society.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11367/57587
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