Estimating the environmental Kuznets curve for ecological footprint at the global level: A spatial econometric approach

Abstract

a b s t r a c tThe national ecological footprint of both consumption and production are significantly spatially autocorrelated at global level. This violates the assumption of independently distributed errors of most conventional estimation techniques. Using a spatial econometric approach, this paper re-examine the relationship between economic growth and environmental impact for indicator of ecological footprint. The results do not show evidence of inverted U-shape Environmental Kuznets Curve. The domestic ecological footprint of consumption (or production) was obviously influenced by the ecological footprint of consumption (or production), income and biocapacity in neighborhood countries. We also found that the consumption footprint is more sensitive to domestic income, while production footprint is more sensitive to domestic biocapacity, which is often unnoticed in EKC hypothesis analyses that focus exclusively on the consumption-based or production-based indictors.

China’s farewell to coal: A forecast of coal consumption through 2020

“…In a recent study, Zhang et al (2014) found evidence for the long-run causality from China's economic growth to energy consumption-related CO 2 emissions. In addition, Wang et al (2013) tested and verified a similar relationship between economic growth and energy consumption using the concept of the ecological footprint. 2 Sheng et al (2014) employed an instrumental regression technique to verify the positive relationship between economic growth and energy demand in China.…”

GHG Emissions, Economic Growth and Urbanization: A Spatial Approach

“…Later, the classical OLS, spatial error and spatial lag models were used to prove that the United States sample does not support the EKC curve relationship, where the spatial lag model is optimal [23]. Wang (2013) used a spatial econometric analysis to prove that the environmental indicators of the local area are affected by other regions [24]. Cirilli (2014), on the basis of the spatial analysis of Italian samples, proved the spatial correlation of city development and carbon emissions [25].…”

Economic Growth and Pollution Emission in China: Structural Path Analysis

“…With the expected increase of environmental quality, the specific pollutants that empirical studies are concerned with have gradually expanded from the traditional sulfur dioxide [5], nitrogen oxides [6] and waste water [7] to greenhouse gases [8] and particulate matter 2.5 (PM2.5) [9]. The other is comprehensive environmental pressure indicators, such as the ecological footprint [10,11] and ecological efficiency [12,13]. In addition, with the increase in resource pressure, scholars have started to pay attention to the empirical relationship between resource utilization and economic growth, mainly to test whether economic growth has an EKC empirical relationship to land utilization [14], energy consumption [15,16], or water resource consumption [17].…”