中国省际能源尾效及其影响因素

doi:10.18402/resci.2019.05.03

Abstract

Abstract:

Studying the influencing factors and the mechanism of growth drag of energy can provide new ideas for solving the problem in China’s economic development. Based on provincial panel data, this study measured the growth drag of energy of 30 provinces in China from 1997 to 2016 by using the partial least squares (PLS) method. The dynamic panel model was used to empirically analyze the influencing factors at the national and group levels. The results show that: (1) Growth drag of energy is a constraint in China, which shows different characteristics in different development periods. (2) The results of the national level analyses show that lag term of growth drag, industrial structure, economic development level, and energy price have a significant positive effect on the growth drag of energy. The level of input in science and technology, level of urbanization, and energy structure have negative contributions, which are conducive to the reduction of grow drag. (3) The results of the group level analyses show that lag item of growth drag, economic development level, and energy price are still unfavorable factors that promote growth drag, while industrial structure, level of input in science and technology, level of urbanization, and energy structure have double sided effects, which differ in different groups. Based on these conclusions, this article provides some recommendations with regard to the quality of economic development, price regulation of the energy market, and urbanization development, in order to find reasonable methods to reduce the growth drag of energy.

Key words: growth drag of energy, influencing factors, panel data, partial least squares method, system GMM

Pinjie XIE, Zhuowen MU. Measurement and influencing factors of the growth drag of energy in China[J].Resources Science, 2019, 41(5): 847-859.

Figures/Tables 6

Table 1

Figure 1

Table 2

Table 3

Table 4

Table 5

References 38

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	北京	天津	河北	山西	内蒙古	辽宁	吉林	黑龙江	上海	江苏
1997	-0.006	-0.015	0.008	-0.010	0.100	-0.028	0.029	0.053	0.028	-0.010
2002	0.07	0029	0.076	0.098	0.092	-0.003	0.109	0.058	0.059	0.055
2007	0.092	0.079	0.059	0.064	0.077	0.121	0.090	0.067	0.088	0.067
2012	0.037	0.065	0.017	0.034	0.031	0.042	0.031	0.048	0.008	0.030
2016	0.023	-0.001	0.010	0.001	0.016	-0.034	-0.013	0.011	0.028	0.018
历年平均	0.046	0.051	0.045	0.035	0.056	0.050	0.031	0.033	0.048	0.048
	浙江	安徽	福建	江西	山东	河南	湖北	湖南	广东	广西
1997	0.035	-0.019	0.01	-0.006	-0.001	0.005	0.038	-0.067	0.017	0.007
2002	0.091	0.03	0.072	0.068	0.099	0.045	0.055	0.09	0.065	0.018
2007	0.064	0.074	0.056	0.05	0.052	0.059	0.096	0.055	0.065	0.072
2012	0.009	0.058	0.025	0.026	0.027	0.015	0.064	0.02	0.014	0.042
2016	0.022	0.023	0.007	0.021	0.012	-0.001	0.026	0.012	0.021	0.022
历年平均	0.046	0.042	0.043	0.043	0.045	0.039	0.055	0.033	0.044	0.05
	海南	重庆	四川	贵州	云南	陕西	甘肃	青海	宁夏	新疆
1997	0.059	0.084	-0.082	0.054	0.123	0.023	-0.098	0.006	0.002	0.070
2002	0.085	0.040	0.068	0.004	0.060	0.138	0.043	0.040	0.051	0.047
2007	0.081	0.107	0.062	0.063	0.044	0.107	0.096	0.047	0.033	0.114
2012	0.030	0.055	0.029	0.056	0.053	0.090	0.098	0.049	0.021	0.251
2016	0.019	0.030	0.016	0.017	0.016	0.035	-0.031	-0.003	0.013	0.054
历年平均	0.048	0.068	0.036	0.037	0.040	0.076	0.063	0.045	0.040	0.116

变量	单位	样本数	均值	标准差	最小值	最大值
尾效滞后项	—	600	0.048	0.052	-0.131	0.258
产业结构	%	600	0.400	0.080	0.254	0.802
城市化水平	%	600	0.479	0.158	0.215	0.896
科技投入水平	%	600	1.848	1.119	0.390	7.200
经济发展水平	%	600	0.111	0.044	-0.025	0.238
能源价格	—	600	1.013	0.055	0.846	1.185
能源结构	%	600	0.251	0.084	0.096	0.569

	混合效应模型	固定效应模型	随机效应模型	系统GMM模型
ln[1+Drag(-1)]	0.338*** [6.20]	0.254*** [4.04]	0.338*** [3.99]	0.435*** [7.91]
lnIS3	0.025* [1.70]	0.034 [1.38]	0.025* [1.70]	0.036** [1.98]
lnUZS	-0.011 [-1.39]	-0.028** [-2.27]	-0.011 [-1.35]	-0.016 [-1.44]
lnRD	-0.006 [-1.58]	-0.014* [-1.86]	-0.006** [-1.99]	-0.009* [-1.67]
ln△GDP	0.034*** [2.73]	0.043** [2.68]	0.034*** [2.72]	0.021** [2.46]
lnEP	0.249*** [6.03]	0.244*** [5.92]	0.249*** [6.56]	0.280*** [7.07]
lnES	-0.014 [-0.82]	-0.011 [-0.23]	-0.014 [-0.97]	-0.011 [-0.33]
β₀	0.127*** [3.29]	0.148*** [3.03]	0.127*** [3.32]	0.099*** [3.27]
AR(2)检验	/	/	/	0.202
Sargan检验	/	/	/	0.499

分组	分组依据	类别	包含省（市、区）
地域	国民经济和社会发展第七个五年计划	东	北京、天津、河北、辽宁、上海、江苏、浙江、福建、山东、广东、海南
		中	黑龙江、吉林、山西、安徽、江西、河南、湖北、湖南
		西	内蒙古、广西、重庆、四川、贵州、云南、陕西、甘肃、青海、宁夏、新疆
能效	《中国统计年鉴》能效数据（1997—2016）	低	宁夏、山西、内蒙、贵州、青海、甘肃、新疆、河北、云南、吉林
		中	陕西、四川、黑龙江、河南、重庆、辽宁、湖南、安徽、湖北、山东
		高	天津、广西、北京、江西、浙江、上海、江苏、海南、广东、福建
尾效	本文尾效测度结果	低	吉林、黑龙江、湖南、山西、四川、贵州、河南、云南、宁夏、安徽
		中	福建、江西、广东、青海、河北、山东、北京、浙江、上海、江苏
		高	海南、辽宁、广西、天津、湖北、内蒙、甘肃、重庆、陕西、新疆

		ln[1+Drag(-1)]	lnIS3	lnUZS	lnRD	ln△GDP	lnEP	lnES	cons	AR（2） Sargan
地域	东	0.260*** [3.98]	0.031 [1.51]	-0.021 [-1.26]	-0.002 [-0.30]	0.040*** [4.23]	0.216*** [4.68]	-0.006 [-0.19]	0.138*** [4.48]	0.350 0.815
	中	0.204*** [5.58]	0.136*** [6.36]	-0.033** [-1.90]	-0.002 [-0.17]	0.055*** [6.36]	0.353*** [3.95]	-0.014 [-0.16]	0.264*** [4.99]	0.308 0.378
	西	0.486*** [7.17]	-0.024 [-0.75]	-0.003 [-0.25]	-0.012 [-0.88]	0.025* [1.68]	0.248*** [3.82]	-0.047 [-1.16]	0.069 [1.45]	0.936 0.887
能效	低	0.333*** [5.78]	-0.001 [-0.53]	-0.025 [-1.41]	-0.045*** [-3.06]	0.036*** [2.82]	0.236*** [4.17]	-0.062 [-0.88]	0.111** [1.98]	0.188 0.138
	中	0.199*** [4.54]	0.086** [2.57]	-0.005 [-0.25]	0.007 [0.50]	0.025** [2.45]	0.486*** [6.87]	-0.134 [-1.26]	0.191*** [3.85]	0.778 0.242
	高	0.116** [2.23]	0.053*** [3.26]	-0.026** [-2.51]	-0.008 [-1.54]	0.071*** [6.87]	0.169*** [5.91]	-0.067** [-2.32]	0.253*** [7.94]	0.288 0.132
尾效	低	0.270*** [4.03]	0.058* [1.89]	-0.020 [-1.48]	-0.008 [-0.88]	0.033*** [3.03]	0.319*** [4.61]	-0.105 [-1.57]	0.167*** [3.97]	0.451 0.388
	中	0.088 [1.16]	0.038** [2.03]	-0.024* [-1.85]	0.002 [0.42]	0.071*** [4.69]	0.159*** [3.28]	-0.027 [-1.22]	0.224*** [5.08]	0.159 0.614
	高	0.445*** [6.96]	-0.011 [-0.32]	0.007 [0.53]	-0.013 [-1.43]	0.028** [2.04]	0.271*** [4.55]	0.013 [0.28]	0.088* [1.77]	0.646 0.471

Measurement and influencing factors of the growth drag of energy in China

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