城市化、产业结构、能源消费、经济增长与碳排放的关联性分析——基于中国省际收入水平异质性的实证研究

doi:10.12006/j.issn.1673-1719.2019.192

摘要/Abstract

摘要：

在全国推崇节能减排,寻求低碳经济发展的大环境下,探究不同收入水平下各影响因子与碳排放的关联性有助于区域异质性碳减排政策的制定。根据2002—2016年的经济发展水平数据,将中国30个省及直辖市（不包含西藏及港、澳、台地区）划分为4个不同收入水平,分别建立面板向量自回归（PVAR）模型,并运用面板格兰杰因果检验、脉冲响应和方差分解探究城市化、产业结构、能源消费、经济增长与碳排放之间的关联性。研究结果表明,处于不同收入水平下的省份各影响因子与碳排放之间的关系存在异质性。收入水平较高的省份当前城市化水平已产生显著的减排效应,而欠发达地区仍处于城市化进程加速碳排放阶段;4个收入水平下能源消费均会长期影响碳排放,但欠发达地区更加需要摆脱能源依赖的经济发展路径,并且提高能源利用率从而降低碳排放;非高收入水平省份产业结构对碳排放造成的影响明显高于高收入水平省份。此外,实证结果表明,中国仍处于碳排放与经济发展的同步增长阶段,减排政策将会对经济增长产生负向反馈,故现有减排路径的选择需要高度审慎的设计与实施。

关键词: 城市化, 产业结构, 能源消费, 经济增长, 碳排放, 面板向量自回归（PVAR）

Abstract:

Under the overall environment that the whole country is advocating energy conservation and emission reduction and seeking low-carbon economic development, exploring the correlation between various impact factors and carbon emissions at different income levels is conducive to the formulation of regional heterogeneous carbon emission reduction policies. Based on the data from 2002 to 2016, China's 30 provinces (except Tibet, HongKong, Macao and Taiwan) were divided into four income levels, and a panel vector autoregressive (PVAR) model was established. Moreover, Granger causality test, impulse response and variance decomposition were used to explore the correlation between urbanization, industrial structure, energy consumption, economic growth and carbon emissions. The results show that there is heterogeneity in the relationship between the impact factors and carbon emissions in the provinces at different income levels. The urbanization of provinces at higher income level has produced significant emission reduction effect, while the less developed areas are still in the stage which urbanization promotes carbon emissions. Energy consumption at all four income levels will affect carbon emissions in the long run. However, less developed areas have a more urgent need for getting rid of energy dependence for economic development, and should improve energy efficiency to reduce carbon emissions. The impact of industrial structure on carbon emissions in non-high-income provinces is significantly higher than that in high-income provinces. In addition, the empirical results show that China is still in the stage of synchronous growth of carbon emission and economic development, and emission reduction policies will generate negative feedback on economic growth. Therefore, the selection of existing emission reduction path needs highly prudent design and implementation.

Key words: Urbanization, Industrial structure, Energy consumption, Economic growth, Carbon emissions, Panel vector autoregression (PVAR)

原嫄, 孙欣彤. 城市化、产业结构、能源消费、经济增长与碳排放的关联性分析——基于中国省际收入水平异质性的实证研究[J]. 气候变化研究进展, 2020, 16(6): 738-747.

YUAN Yuan, SUN Xin-Tong. Exploring the relationship between urbanization, industrial structure, energy consumption, economic growth and CO₂ emissions: an empirical study based on the heterogeneity of inter-provincial income levels in China[J]. Climate Change Research, 2020, 16(6): 738-747.

图/表 6

图1 碳排放影响机制

Fig. 1 The influence mechanism of carbon emission

图2 不同收入水平地理分布

Fig. 2 Geographical distribution of different income levels

表1 各种能源碳排放参考系数

Table 1 Various energy carbon emission reference modulus

图3 面板格兰杰检验结果注：A→B表示A是B的格兰杰原因,A?B表示A和B互为格兰杰原因。

Fig. 3 Panel Granger test results

图4 脉冲响应图

Fig. 4 Impulse response diagram

图5 方差分解结果注：饼状图内各变量为冲击变量,碳排放为响应变量。

Fig. 5 The results of the variance decomposition

参考文献 28

[1]	Azomahoua T, Laisney F, van Nguyen P. Economic development and CO₂ emissions: a nonparametric panel approach[J]. Journal of Public Economics, 2005,90(6):1347-1363
[2]	Wang S, Li G, Fang C. Urbanization, economic growth, energy consumption, and CO₂ emissions: empirical evidence from countries with different income levels[J]. Renewable & Sustainable Energy Reviews, 2018,81:2144-2159
[3]	Liu Z, Guan D, Crawford-Brown D, et al. Energy policy: a low-carbon road map for China[J]. Nature, 2013,500(7461):143-145
[4]	Dong K Y, Sun R J, Li H, et al. A review of China's energy consumption structure and outlook based on a long-range energy alternatives modeling tool[J]. Petroleum Science, 2017,14(1):214-227
[5]	British P. Statistical review of world energy [M]. Beijing: China Statistics Press, 2017
[6]	Dong K, Sun R, Wu J, et al. The growth and development of natural gas supply chains: the case of China and the US[J]. Energy Policy, 2018,123:64-71
[7]	马慧强, 刘嘉乐, 弓志刚. 山西省旅游交通碳排放测度及其演变机理[J]. 经济地理, 2019,39(4):223-231.
	Ma H Q, Liu J L, Gong Z G. Carbon emission and evolution mechanism of tourism transportation in Shanxi province[J]. Economic Geography, 2019,39(4):223-231 (in Chinese)
[8]	韩坚, 盛培宏. 产业结构、技术创新与碳排放实证研究: 基于我国东部15个省(市)面板数据[J]. 上海经济研究, 2014 (8):67-74.
	Han J, Sheng P H. An empirical study about industrial structure, technological innovation and carbon emissions: panel data based on the 15 provinces (city) of eastern China[J]. Shanghai Journal of Economics, 2014 (8):67-74 (in Chinese)
[9]	程叶青, 王哲野, 张守志, 等. 中国能源消费碳排放强度及其影响因素的空间计量[J]. 地理学报, 2013,68(10):1418-1431.
	Cheng Y Q, Wang Z Y, Zhang S Z. Spatial econometric analysis of carbon emission intensity and its driving factors from energy consumption in China[J]. Journal of Geographical Sciences, 2013,68(10):1418-1431 (in Chinese)
[10]	雷于蓝, 张枫, 彭希哲, 等. 广东省“十二五”人口发展战略研究[M]. 上海: 复旦大学出版社, 2012.
	Lei Y L, Zhang F, Peng X Z, et al. Research on population development strategy of Guangdong province during the 12th Five-Year Plan [M]. Shanghai: Fudan University Press, 2012 (in Chinese)
[11]	徐丽杰. 中国城市化对碳排放的影响关系研究[J]. 宏观经济研究, 2014 (6):63-70, 79.
	Xu L J. Research on the influence relationship of urbanization on carbon emission[J]. Macroeconomics, 2014 (6):63-70, 79 (in Chinese)
[12]	刘梦琴, 刘轶俊. 中国城市化发展与碳排放关系: 基于30个省区数据的实证研究[J]. 城市发展研究, 2011,18(11):27-32.
	Liu M Q, Liu Y J. The relationship between the development of China's urbanization and carbon emissions: an empisical study based on 30 provinces' data[J]. Urban Development Studies, 2011,18(11):27-32 (in Chinese)
[13]	王少剑, 黄永源. 中国城市碳排放强度的空间溢出效应及驱动因素[J]. 地理学报, 2019,74(6):1131-1148.
	Wang S J, Huang Y Y. Spatial spillover effect and driving forces of carbon emission intensity at city level in China[J]. Journal of Geographical Sciences, 2019,74(6):1131-1148 (in Chinese)
[14]	Sheng P F, Guo X H. The long-run and short-run impacts of urbanization on carbon dioxide emissions[J]. Economic Modelling, 2016,53:208-215
[15]	Sharma S S. Determinants of carbon dioxide emissions: empirical evidence from 69 countries[J]. Applied Energy, 2011,88(1):376-382
[16]	Li C, Kuang Y Q, Huang N S. The long-term relationship between population growth and vegetation cover: an empirical analysis based on the panel data of 21 cities in Guangdong province, China[J]. International Journal of Environmental Research and Public Health, 2013,10(2):660-677
[17]	Martínez-Zarzoso I, Maruotti A. The impact of urbanization on CO₂ emissions: evidence from developing countries[J]. Ecological Economics, 2011,70(7):1344-1353
[18]	姬世东, 吴昊, 王铮. 贸易开放、城市化发展和二氧化碳排放: 基于中国城市面板数据的边限协整检验分析[J]. 经济问题, 2013 (12):31-35.
	Ji S D, Wu H, Wang Z. Openness to trade, urbanization and carbon dioxide emissions: based on panel data of China's urban bound co-integration analysis[J]. On Economic Problems, 2013 (12):31-35 (in Chinese)
[19]	Tucker M. Carbon dioxide emissions and global GDP[J]. Ecological Economics, 1995,15(3):215-223
[20]	杨子晖. “经济增长”与“二氧化碳排放”关系的非线性研究: 基于发展中国家的非线性Granger因果检验[J]. 世界经济, 2010,33(10):139-160.
	Yang Z H. Nonlinear study of the relationship between“economic growth” and “carbon dioxide emissions”: based on the nonlinear Granger causality test in developing countries[J]. The Journal of World Economy, 2010,33(10):139-160 (in Chinese)
[21]	原嫄, 席强敏, 孙铁山, 等. 产业结构对区域碳排放的影响: 基于多国数据的实证分析[J]. 地理研究, 2016,35(1):82-94.
	Yuan Y, Xi Q M, Sun T S, et al. The impact of the industrial structure on regional carbon emission: empirical evidence across countries[J]. Geographical Research, 2016,35(1):82-94 (in Chinese)
[22]	Grossman G M, Krueger A B. Economic growth and the environment[J]. Quarterly Journal of Economics, 1995,110(2):353-377
[23]	陶长琪, 彭永樟, 琚泽霞. 经济增长、产业结构与碳排放关系的实证分析: 基于PVAR模型[J]. 经济经纬, 2015,32(4):126-131.
	Tao C Q, Peng Y Z, Ju Z X. An empirical study on economic growth, industrial structure and the carbon emissions: based on PVAR model[J]. Economic Survey, 2015,32(4):126-131 (in Chinese)
[24]	Holtz-Eakin D, Newey W, Rosen H S. Estimating vector autoregressions with panel data[J]. Econometrica, 1988,56(6):1371-1395
[25]	Antonakakis N, Chatziantoniou I, Filis G. Energy consumption, CO₂ emissions, and economic growth: an ethical dilemma[J]. Renewable and Sustainable Energy Reviews, 2017,68:808-824
[26]	邹平. 金融计量学[M]. 上海: 上海财经大学出版社, 2014.
	Zou P. Financial econometrics [M]. Shanghai: Shanghai University of Finance & Economics Press, 2014 (in Chinese)
[27]	Dinda S. Does environment link to economic growth[J]. Human Security and Climate Change, 2005: 1-26
[28]	臧良震, 张彩虹. 中国城市化、经济发展方式与CO₂排放量的关系研究[J]. 统计与决策, 2015 (20):124-126.
	Zang L Z, Zhang C H. Study on the relationship between urbanization, economic development pattern and CO₂ emission in China[J]. Statistics & Decision, 2015 (20):124-126 (in Chinese)