基于混合地理加权回归的中国省域碳生产率影响因素分析

doi:10.18402/resci.2017.12.02

摘要/Abstract

摘要：

低碳经济成为应对全球气候变化的根本途径。低碳经济实质上就是要求单位碳排放产生更多的经济产出,即提高碳生产率。涉及地区低碳发展的影响因素很多,具有显著空间相关性的因素和无显著空间相关性的因素往往同时作用,在构建模型时需要综合考虑。本文在空间自相关方法的基础上首先确定了中国省域碳生产率影响因素的空间相关性,其中产业结构是全局变量,能源结构、技术进步和劳动生产率均是局域变量,再通过混合地理加权回归估计了“十一五”末和“十二五”末4个影响因素的回归参数值并作分析。研究结果显示：①能源结构（火电比重）对于碳生产率具有负向影响,而产业结构（服务业比重）、技术进步（年专利授权数量）和劳动生产率（单位从业人员的工业增加值）对于碳生产率具有正向影响;从回归参数估计值来看,产业结构的影响程度占据主导地位,其次是能源结构,再次是技术进步,最后为劳动生产率;②产业结构对碳生产率的正向影响程度在增大,能源结构对碳生产率的负向影响在空间分布上呈现出明显的自南向北递减特征,而技术进步和劳动生产率的正向影响则呈现出明显的自北向南递减特征;“十一五”末到“十二五”末,总体上能源结构和劳动生产率对碳生产率的影响程度在减小,而技术进步的影响在增大。最后,提出了相关的政策建议。

Abstract:

A low-carbon economy is an essential way to tackle global climate change. The essence of a low-carbon economy is to increase carbon productivity. Carbon productivity is often affected by impact factors of regional low-carbon development,including global variables and local variables. We need to consider these together in order to establish a precise model. Here we determined factors influencing carbon productivity in Chinese provinces based on spatial autocorrelation method. We found that the industrial structure is a global variable and that energy structure,technological progress and labor productivity are local variables. Four impact factors and regression parameter values at the end of 11th Five-Year Plan and 12th Five-Year Plan were estimated and analyzed based on mixed geographically weighted regression. We found that the structure of energy （power ratio）has a negative effect on carbon productivity,and industrial structure （service industry）,technology （patent authorization number）and labor productivity （employees of the industrial added value）has a positive effect on carbon productivity. Judging from the estimated value of regression parameters,the influence degree of industrial structure occupies a leading position,followed by energy structure and technological progress,and finally for labor productivity. The impact of industrial structure on carbon productivity is increasing. The negative impact of energy structure on carbon productivity showed obvious decline from south to north spatially,while the positive impact of technical progress and labor productivity showed obvious declines from north to south. From the end of 11th Five-Year Plan to the end of the 12th Five-Year Plan,the impact of energy structure and labor productivity on carbon productivity decreased,and the impact of technological progress increased. Some policy suggestions are discussed.

Key words: carbon productivity, spatial autocorrelation, mixed geographically weighted regression, impact factor, China

唐志鹏, 刘卫东, 宋涛. 基于混合地理加权回归的中国省域碳生产率影响因素分析[J]. 资源科学, 2017, 39(12): 2223-2232.

Zhipeng TANG, Weidong LIU, Tao SONG. Factors affecting China’s provincial carbon productivity based on mixed geographically weighted regression modeling[J]. Resources Science, 2017, 39(12): 2223-2232.

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	变量名称	计算指标	经济含义
被解释变量	碳生产率/（万元/t碳）	GDP/碳排放	每吨碳产生的经济效益,衡量碳排放利用效率
解释变量	能源结构/%	火电/发电量	火电占发电量的比重,衡量能源结构的变化
	产业结构/%	服务业增加值/GDP	服务业所占GDP比重,衡量产业结构的变化
	技术进步/（件/年）	年专利授权数量	衡量年度技术创新活动的程度
	劳动生产率/（万元/人）	工业增加值除以从业人员数	衡量碳排放主要来源工业部门的劳动生产率

	影响要素	样本数	极大值	极小值	平均值	标准差
2010年	碳生产率	30	4.72	0.36	1.75	0.98
	能源结构	30	0.99	0.21	0.78	0.22
	产业结构	30	75.10	28.60	34.75	8.66
	技术进步	30	138 382	264	22 757	36 529
	劳动生产率	30	8.76	0.60	2.09	1.95
2015年	碳生产率	30	8.15	0.37	2.59	1.63
	能源结构	30	0.99	0.10	0.73	0.26
	产业结构	30	79.65	38.80	40.71	8.70
	技术进步	30	250 290	1 217	48 501	69 227
	劳动生产率	30	15.59	1.07	3.19	3.12

	影响要素	Moran's I	Z值	p值	空间相关性
2010年	能源结构	0.429	4.154	0.000	显著正相关
	产业结构	0.123	1.410	0.159	无显著相关
	技术进步	0.214	2.228	0.026	显著正相关
	劳动生产率	0.209	2.188	0.029	显著正相关
2015年	能源结构	0.485	4.667	0.000	显著正相关
	产业结构	0.055	0.804	0.421	无显著相关
	技术进步	0.222	2.297	0.022	显著正相关
	劳动生产率	0.161	1.753	0.079	显著正相关

	变量	最小值	1/4分位数	中位数	3/4分位数	最大值
2010年	能源结构（局域变量）	-0.610 2	-0.559 7	-0.521 3	-0.491 5	-0.428 2
	产业结构（全局变量）	0.879 9	0.879 9	0.879 9	0.879 9	0.879 9
	技术进步（局域变量）	0.228 2	0.250 2	0.258 8	0.269 3	0.282 0
	劳动生产率（局域变量）	0.043 9	0.048 4	0.054 9	0.062 9	0.081 4
2015年	能源结构（局域变量）	-0.504 4	-0.473 3	-0.451 3	-0.434 7	-0.398 8
	产业结构（全局变量）	1.040 2	1.040 2	1.040 2	1.040 2	1.040 2
	技术进步（局域变量）	0.335 0	0.348 0	0.353 5	0.360 2	0.369 0
	劳动生产率（局域变量）	0.022 6	0.042 6	0.053 9	0.068 5	0.090 8