摘要
为了有效减缓农村居民生活消费碳排放量,加快我国实现节能减排的进程。基于2005-2015年我国30个省域的面板数据,以农村居民可支配收入为门限变量,构建多个不同视角的门限-STIRPAT扩展模型,分析在不同收入阶段下农村居民生活消费碳排放所受的影响效应。结果表明:农村人口规模对碳排放量存在最为显著的负向影响,其余解释变量对其均存在显著的正向影响。农村人口规模和农村能源强度对碳排放的影响均表现出阶段性特征。农村居民可支配收入的提高可显著增大农村人口规模对碳排放的影响,而显著减小农村能源强度对碳排放的影响。
引文
[1]IPCC, 2014:Climate Change 2014:Synthesis Report. Contribution of Working Groups Ⅰ, Ⅱ and Ⅲ to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change[Core Writing Team,R. K. Pachauri and L. A. Meyer(eds.)]. IPCC, Geneva,Switzerland, 151 pp.
[2]汝醒君,汪臻.中国农村居民生活用能碳排放影响因素研究[J].生态经济,2017(1):73-76.
[3]Ramanathan R. A multi-factor efficiency perspective to the relationships among world GDP, energy consumption and carbon dioxide emissions[J]. Technological Forecasting and Social Change, 2006, 73(5):483-494.
[4]Soytas U et al.. Energy consumption, income, and carbon emissions in the United States[J]. Ecological Economics, 2007, 62(3-4):482-489.
[5]Tadhg o’ Mahony. Decomposition of Ireland’s carbon emissions from 1990 to 2010:An extended Kaya identity[J]. Energy Policy,2013, 59.
[6]王泳璇,王宪恩.基于城镇化的居民生活能源消费碳排放门限效应分析[J].中国人口·资源与环境,2016,26(12):94-102.
[7]刘莉娜等.灰色关联分析在中国农村家庭碳排放影响因素分析中的应用[J].生态环境学报,2013,22(3):498-505.
[8]刘晓红.环境规制情景下我国农村居民间接碳排放研究——基于STIRPAT模型和PLS-VIP方法[J].资源开发与市场,2016,32(12):1471-1476.
[9]Hansen B E. Threshold effects in non-dynamic panels:estimation,testing, and inference[J]. Journal of Econometrics, 1999, 93(2):345-368.
[10]Dietz T, Rosa EA. Rethinking the environmental impacts of population, affluence and technology. Human Ecology Review, 1994,2(1):277-300.