Next Article in Journal
Can Environmental Laws Fulfill Their Promise? Stories from Canada
Next Article in Special Issue
Sustainable E-Governance: The Relationship among Trust, Digital Divide, and E-Government
Previous Article in Journal / Special Issue
Sources of China’s Economic Growth: An Empirical Analysis Based on the BML Index with Green Growth Accounting
Article Menu

Export Article

Open AccessArticle
Sustainability 2014, 6(9), 6005-6023; doi:10.3390/su6096005

Carbon Emissions in China: A Spatial Econometric Analysis at the Regional Level

1
Institute of Policy and Management, Chinese Academy of Sciences, Beijing 100190, China
2
Economic Forecasting Department, State Information Center, Beijing 100045, China
3
Postnet Suite 122, Private Bag X1, Die Wilgers 0041, Pretoria, South Africa
4
College of Economics and Management, China Agricultural University, Beijing 100083, China
*
Author to whom correspondence should be addressed.
Received: 23 July 2014 / Revised: 1 September 2014 / Accepted: 2 September 2014 / Published: 5 September 2014
(This article belongs to the Special Issue Special issue of Sustainable Asia Conference 2014)
View Full-Text   |   Download PDF [734 KB, uploaded 24 February 2015]

Abstract

An extended Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) model, incorporating factors that drive carbon emissions, is built from the regional perspective. A spatial Durbin model is applied to investigate the factors, including population, urbanization level, economic development, energy intensity, industrial structure, energy consumption structure, energy price, and openness, that impact both the scale and intensity of carbon emissions. After performing the model, we find that the revealed negative and significant impact of spatial-lagged variables suggests that the carbon emissions among regions are highly correlated. Therefore, the empirical results suggest that the provinces are doing an exemplary job of lowering carbon emissions. The driving factors, with the exception of energy prices, significantly impact carbon emissions both directly and indirectly. We, thus, argue that spatial correlation, endogeneity and externality should be taken into account in formulating polices that seek to reduce carbon emissions in China. Carbon emissions will not be met by controlling economic development, but by energy consumption and low-carbon path. View Full-Text
Keywords: carbon emissions; spatial Durbin panel data model; spatial externality; Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) carbon emissions; spatial Durbin panel data model; spatial externality; Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT)
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Liu, Y.; Xiao, H.; Zikhali, P.; Lv, Y. Carbon Emissions in China: A Spatial Econometric Analysis at the Regional Level. Sustainability 2014, 6, 6005-6023.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sustainability EISSN 2071-1050 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top