中国省域工业生态效率及影响因素的空间计量分析

doi:10.18402/resci.2017.07.10

Abstract

Abstract:

The VRS_DEA model was used to estimate industrial ecological efficiency for China's 30 provinces from 2005 to 2014. A spatial econometrics model was also used to test the influencing factors. We found that the industrial ecological efficiency of most provinces shows a trend of increasing fluctuation,and differences between the provinces are obvious. The spatial development pattern was one from western provinces to eastern provinces. Improvement in industrial development levels is beneficial to industrial ecological efficiency,and the capability of scientific and technological innovation have positive effects on industrial ecological efficiency. Environmental regulation,opening to the outside world and fiscal decentralization have significant negative effects on industrial ecological efficiency. Industrial agglomeration and industrial ecological efficiency follow an inverted U type relationship. Because of the co-existence of pollution emissions and economic benefits,the impact of industrial structure on industrial ecological efficiency is not significant,but the environmental pollution caused by change in industrial structure cannot be neglected. In addition,the spatial lag effect of industrial ecological efficiency is positive,indicating that local governments may learn from and imitate each other in environmental governance. The spatial lag effect of quadratic terms of industrial development is positive,while the spatial lag of fiscal decentralization is negative,and the spatial spillover effects of industrial structure are negative. The spatial lag of industrial agglomeration and industrial ecological efficiency follow a positive U type relationship,the effect on industrial ecological efficiency in adjacent areas was first inhibited and then promoted.

Key words: industrial ecological efficiency, VRS_DEA, space effects, spatial econometrics

Yanqun LU, Peng YUAN. Measurement and spatial econometrics analysis of provincial industrial ecological efficiency in China[J].Resources Science, 2017, 39(7): 1326-1337.

Figures/Tables 5

Table 1

Table 2

Industrial ecological efficiency of China's 30 provincial regions from 2005 to 2014"

区域	省（市、区）	2005年	2006年	2007年	2008年	2009年	2010年	2011年	2012年	2013年	2014年	年均值
东北地区	辽宁	0.206	0.193	0.259	0.220	0.334	0.423	0.430	0.499	0.630	0.556	0.375
	吉林	0.412	0.429	0.466	0.494	0.474	0.494	0.451	0.521	0.590	0.653	0.498
	黑龙江	0.647	0.629	0.550	0.580	0.448	0.535	0.583	0.541	0.537	0.461	0.551
东部地区	北京	0.676	0.743	0.840	0.925	0.906	1.000	0.980	1.000	0.952	1.000	0.902
	天津	0.577	0.545	0.635	0.702	0.737	0.685	0.775	0.852	1.000	1.000	0.751
	河北	0.218	0.183	0.180	0.254	0.260	0.325	0.397	0.434	0.541	0.578	0.337
	上海	0.622	0.634	0.675	0.671	0.661	0.672	0.689	0.757	0.825	0.871	0.708
	江苏	0.527	0.514	0.610	0.631	0.646	0.629	0.488	0.557	0.651	0.735	0.599
	浙江	0.636	0.605	0.591	0.628	0.614	0.629	0.630	0.659	0.723	0.294	0.601
	福建	0.568	0.586	0.497	0.561	0.518	0.480	0.479	0.560	0.571	0.556	0.538
	山东	0.488	0.532	0.499	0.526	0.542	0.522	0.642	0.711	0.779	0.830	0.607
	广东	0.907	1.000	0.944	0.888	0.876	0.949	0.837	0.982	0.997	1.000	0.938
	海南	1.000	1.000	1.000	0.972	0.845	1.000	0.855	0.782	0.868	0.732	0.905
西部地区	内蒙古	0.284	0.263	0.315	0.298	0.320	0.297	0.339	0.457	0.462	0.448	0.348
	广西	0.232	0.245	0.201	0.248	0.240	0.263	0.155	0.175	0.245	0.297	0.230
	重庆	0.462	0.283	0.290	0.341	0.303	0.380	0.521	0.602	0.573	0.560	0.432
	四川	0.396	0.357	0.191	0.385	0.440	0.375	0.423	0.515	0.661	0.659	0.440
	贵州	0.430	0.447	0.520	0.546	0.475	0.463	0.331	0.297	0.308	0.231	0.405
	云南	0.340	0.307	0.276	0.290	0.264	0.270	0.179	0.220	0.221	0.227	0.259
	陕西	0.454	0.481	0.461	0.353	0.333	0.329	0.359	0.443	0.469	0.482	0.416
	甘肃	0.380	0.390	0.411	0.406	0.405	0.451	0.342	0.356	0.350	0.360	0.385
	青海	0.798	0.807	0.790	0.818	0.695	0.654	0.690	0.677	0.724	0.739	0.739
	宁夏	0.327	0.343	0.291	0.292	0.279	0.267	0.307	0.360	0.382	0.397	0.325
	新疆	0.375	0.376	0.357	0.363	0.314	0.300	0.275	0.262	0.229	0.239	0.309
中部地区	山西	0.249	0.194	0.218	0.231	0.227	0.202	0.257	0.246	0.251	0.243	0.232
	安徽	0.359	0.328	0.247	0.242	0.286	0.307	0.242	0.287	0.332	0.385	0.301
	江西	0.486	0.468	0.444	0.404	0.419	0.425	0.302	0.354	0.371	0.396	0.407
	河南	0.381	0.426	0.447	0.497	0.484	0.540	0.463	0.524	0.604	0.610	0.498
	湖北	0.333	0.326	0.376	0.388	1.000	0.467	0.342	0.448	0.484	0.474	0.464
	湖南	0.479	0.553	0.433	0.474	0.447	0.415	0.433	0.507	0.512	0.589	0.484
全国平均		0.475	0.473	0.467	0.488	0.493	0.492	0.473	0.520	0.561	0.553	0.499

Table 2

Figure 1

Table 3

Table 4

Estimated results of traditional panel models and SDM"

变量	传统混合回归模型	传统个体固定模型	传统时间固定模型	个体固定SDM模型
ln（IS）	-0.028 （-0.107）	0.913**** （2.924）	0.131 （0.348）	0.693* （1.519）
ln²（IS）	0.023 （0.707）	-0.001 （-0.043）	0.012 （0.231）	-0.035 （-0.871）
REGUL	-10.386**** （-3.302）	-6.069**** （-2.914）	-12.178**** （-3.695）	-4.873*** （-2.357）
FDI	4.649**** （3.842）	0.002 （0.002）	4.294**** （3.343）	-0.194 （-0.176）
R&D	3.602**** （2.735）	14.552**** （5.051）	2.111* （1.490）	11.433**** （2.900）
FP	0.598*** （2.453）	-2.562**** （-8.678）	0.496** （1.883）	-1.897**** （-5.158）
AGG	-0.720**** （-4.880）	-0.017 -（0.180）	-1.082**** （-5.895）	0.488**** （2.647）
AGG²	0.190**** （4.025）	-0.020 （-0.686）	0.291**** （5.116）	-0.115*** （-2.596）
HP	-0.260** （-1.768）	-0.089 （-0.480）	-0.197* （-1.332）	0.060 （0.342）
W $×$ ln（IS）	-	-	-	-0.540 （-0.760）
W $×$ ln²（IS）	-	-	-	0.113** （1.764）
W $×$ REGUL	-	-	-	1.517 （0.325）
W $×$ FDI	-	-	-	8.514 （1.279）
W $×$ R & D	-	-	-	3.264 （1.084）
W $×$ FP	-	-	-	-1.085** （-1.648）
W $×$ AGG	-	-	-	-0.672**** （-3.332）
W $×$ AGG²	-	-	-	0.160**** （3.134）
W $×$ HP	-	-	-	-0.453* （-1.476）
W $×$ EP	-	-	-	0.189*** （2.483）
R²	0.439	0.883	0.474	0.894
Log likelihood	122.207	357.062	131.830	369.560
固定效应F检验	-	34.727***	0.607	-
LM_spatial lag test	12.633**** （p=0.000）	12.335**** （p=0.000）	1.677* （p=0.195）	-
LM_spatial error test	30.507 （p=0.868）	6.589**** （p=0.010）	3.232** （p=0.072）	-
Wald test spatial lag	-	-	-	20.377*** （p=0.016）
Wald test spatial error	-	-	-	23.038**** （p=0.006）

Table 4

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变量	最大值	最小值	均值	标准差
工业增加值/亿元	79 121	860	16 734	13 464
工业废水排放量/万t	296 318	5 782	76 744	65 374
工业废气排放量/亿m³	45 625	127	8 047	7 528
固体废弃物产生量/万t	24 224	156	5 108	4 793

变量	符号	最大值	最小值	均值	标准差
工业生态效率	EP	1.000	0.155	0.500	0.215
工业规模	IS	4.603	3.276	3.967	0.278
规制强度	GRGUL	0.028	0.000	0.004	0.004
研发投入	R&D	0.061	0.002	0.014	0.010
对外开放程度	FDI	0.064	0.000	0.010	0.009
财政分权	FP	0.936	0.635	0.815	0.069
工业集聚	AGG	2.512	0.404	1.613	0.414
工业结构	HP	0.482	0.003	0.259	0.075

Measurement and spatial econometrics analysis of provincial industrial ecological efficiency in China

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