中国生态福利绩效空间关联网络演变特征与形成机制

doi:10.31497/zrzyxb.20221211

摘要/Abstract

摘要：

在定量测度生态福利绩效基础上，借助修正的引力模型和社会网络分析方法，研究了中国生态福利绩效空间关联网络演变特征与形成机制。研究发现：（1）中国生态福利绩效空间关联网络呈现“东密西疏”的空间分异规律，关联网络有“扁平化”发展趋势，网络稳定性亟待提升。（2）京津冀、长三角和珠三角处于网络核心位置，具有较强的溢出效应，东北、西北和西南地区处于边缘位置，贵州和甘肃是联系西南和西北省区的关键节点，生态福利绩效在省际间的传输多通过南部省区的中介作用实现。（3）北京、天津和上海构成净溢出板块，珠三角和江浙地区属经纪人板块，长江中下游及西南地区为净溢出板块，东北、黄河中下游及西北地区构成双向溢出板块。（4）资源禀赋差异、市场调节、政府宏观调控和科学技术推动是空间关联网络演变的主要驱动机制。研究成果可为推动生态福利绩效的跨区域协同提升提供参考依据。

关键词: 生态福利绩效, 民生福祉, 空间关联网络, 形成机制, 社会网络分析, 中国

Abstract:

In this article, the ecological well-being performance of provincial-level regions in China from 2000 to 2019 is measured by using the super EBM model considering undesirable output. At the same time, with the help of the modified gravity model and social network analysis method, the evolution characteristics and formation mechanism of China's ecological well-being performance spatial correlation network are analyzed. The results show that: (1) The spatial correlation network of China's ecological well-being performance shows a spatial pattern of "dense in the east but sparse in the west". During the research period, the hierarchical network structure was gradually changed, and the associated network had a "flat" evolution trend. However, the compactness and stability of spatial association networks need to be improved. (2) The Beijing-Tianjin-Hebei region, Yangtze River Delta and Pearl River Delta are at the core of the spatial correlation network, showing obvious spillover effects, while the Northeast, Northwest and Southwest regions are located at the edge of the network. Guizhou and Gansu are the key nodes between the eastern region and the southwest and northwest provinces in the network. The transmission of ecological well-being performance among provinces is mostly realized through the mediating role of southern provinces. On the whole, the eastern coastal provinces are the "overflow highland" in the spatial correlation network, showing a significant "trickling-down effect" on the Northwest, Southwest and Northeast regions, and the benefit effect of the central provinces is not significant. (3) The results of block model analysis show that China's ecological well-being performance has significant spillover effects between provinces and regions, and the spillover effect between regions is the most important. Among them, Beijing, Tianjin and Shanghai play the role of "engine" in the correlation network, forming the net overflow plate. The Pearl River Delta and Jiangsu and Zhejiang belong to the broker plate, the middle and lower reaches of the Yangtze River and Southwest China are net overflow plates, and Northeast region, the middle and lower reaches of the Yellow River and Northwest region constitute two-way overflow plates. (4) Resource endowment difference, market regulation, government macro-control and science and technology progress are the main driving mechanisms for the evolution of spatial correlation network of ecological well-being performance in China. This study can provide an important reference for promoting the regional collaborative improvement of ecological well-being performance.

Key words: ecological well-being performance, people's livelihood and well-being, spatial correlation network, formation mechanism, social network analysis, China

赵林, 曹乃刚, 韩增林, 高晓彤. 中国生态福利绩效空间关联网络演变特征与形成机制[J]. 自然资源学报, 2022, 37(12): 3183-3200.

ZHAO Lin, CAO Nai-gang, HAN Zeng-lin, GAO Xiao-tong. Evolution characteristics and formation mechanism of spatial correlation network of ecological well-being performance in China[J]. JOURNAL OF NATURAL RESOURCES, 2022, 37(12): 3183-3200.

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指标类型	一级指标	二级指标	指标参考文献
投入指标	水资源投入	人均用水总量/m³	龙亮军等^[23]；方时姣等^[42]
	土地资源投入	人均建成区面积/m²
	能源资源投入	人均能源消费量/tce
产出指标	人类发展指数	人均地区生产总值/元	肖黎明等^[20]；徐维祥等^[21]
		平均受教育年限/年
		万人均卫生技术人员数/人
	环境污染物	人均废水排放量/t	方时姣等^[42]
		人均二氧化硫排放量/t
		人均烟（粉）尘排放量/t
		人均工业固体废物产生量/t

省（市、自治区）	EWP指数					省（市、自治区）	EWP指数
省（市、自治区）	2000年	2006年	2012年	2019年	增长率	省（市、自治区）	2000年	2006年	2012年	2019年	增长率
北京	0.690	0.456	0.743	1.002	1.983	湖南	0.529	0.458	0.636	0.969	3.241
天津	0.467	0.454	0.660	0.602	1.337	广东	0.381	0.314	0.460	0.620	2.597
河北	0.428	0.399	0.587	0.748	2.986	广西	0.341	0.411	0.577	0.714	3.968
山西	0.491	0.518	0.651	0.749	2.251	海南	0.658	0.461	0.603	0.685	0.217
内蒙古	0.387	0.322	0.482	0.565	2.010	重庆	0.384	0.265	0.439	0.627	2.609
辽宁	0.347	0.343	0.457	0.446	1.322	四川	0.339	0.338	0.602	0.702	3.904
吉林	0.396	0.356	0.414	0.470	0.907	贵州	0.132	0.200	0.536	0.704	9.188
黑龙江	0.328	0.295	0.404	0.469	1.899	云南	0.339	0.285	0.489	0.837	4.874
上海	0.616	0.583	0.721	0.956	2.339	陕西	0.561	0.571	0.804	0.941	2.761
江苏	0.442	0.374	0.518	0.698	2.435	甘肃	0.295	0.319	0.460	0.602	3.831
浙江	0.361	0.405	0.593	0.744	3.872	青海	0.413	0.375	0.667	0.635	2.296
安徽	0.252	0.352	0.497	0.667	5.249	宁夏	0.308	0.203	0.253	0.352	0.708
福建	0.441	0.393	0.558	0.779	3.045	新疆	0.410	0.356	0.408	0.415	0.068
江西	0.406	0.347	0.587	0.666	2.635	东部	0.479	0.412	0.583	0.713	2.121
山东	0.435	0.349	0.517	0.567	1.403	中部	0.408	0.403	0.544	0.686	2.774
河南	0.459	0.445	0.602	0.816	3.076	西部	0.355	0.331	0.520	0.645	3.187
湖北	0.404	0.452	0.562	0.685	2.814	全国	0.415	0.380	0.550	0.681	2.646

省（市、自治区）	网络中心性指标			省（市、自治区）	网络中心性指标
省（市、自治区）	度数中心度	接近中心度	中介中心度	省（市、自治区）	度数中心度	接近中心度	中介中心度
北京	89.655/89.655	87.879/90.625	9.113/7.681	湖北	20.690/31.034	3.448/37.662	0.000/0.252
天津	82.759/34.483	80.556/56.863	7.202/0.431	湖南	20.690/27.586	4.715/53.704	0.369/9.892
河北	13.793/17.241	49.153/50.877	0.059/3.038	广东	37.931/31.034	4.754/42.029	5.111/15.237
山西	17.241/24.138	49.153/50.877	0.100/1.790	广西	24.138/27.586	4.700/37.179	0.544/9.190
内蒙古	10.345/17.241	48.333/3.333	0.059/0.000	海南	17.241/24.138	4.708/32.955	0.062/0.059
辽宁	20.690/24.138	3.571/3.571	0.082/0.123	重庆	24.138/31.034	4.700/31.183	0.092/14.26
吉林	17.241/24.138	3.571/3.567	0.000/0.883	四川	20.690/24.138	3.333/23.967	0.000/0.038
黑龙江	17.241/24.138	3.333/3.333	0.000/0.000	贵州	44.828/27.586	3.333/32.955	0.000/2.704
上海	96.552/93.103	96.667/93.548	7.628/14.361	云南	27.586/24.138	3.448/32.955	0.000/2.509
江苏	34.483/79.310	60.417/76.316	0.510/8.291	陕西	13.793/24.138	4.915/21.014	0.021/0.185
浙江	34.483/62.069	59.184/69.048	0.000/1.901	甘肃	20.690/41.379	3.448/25.893	0.123/8.987
安徽	17.241/20.690	50.877/52.727	2.648/0.679	青海	13.793/24.138	3.448/20.714	0.000/0.000
福建	24.138/58.621	4.700/52.727	0.369/8.807	宁夏	10.345/27.586	3.333/3.333	0.000/0.000
江西	24.138/24.138	4.708/53.704	0.811/12.469	新疆	10.345/27.586	3.333/3.333	0.000/0.000
山东	13.793/20.690	49.153/3.333	0.059/0.000	均值	27.816/34.253	25.173/37.170	1.174/4.138
河南	13.793/20.690	48.333/51.786	0.261/0.372	—	—	—	—

板块类型		2000年				2019年
板块类型		板块Ⅰ	板块Ⅱ	板块Ⅲ	板块Ⅳ	板块Ⅰ	板块Ⅱ	板块Ⅲ	板块Ⅳ
接收关系	板块内	3	0	6	7	2	0	14	9
接收关系	板块外	13	15	38	63	8	23	55	73
溢出关系	板块内	3	0	6	7	2	0	14	9
溢出关系	板块外	74	32	13	10	61	60	11	27
期望内部关系比例/%		6.897	10.345	37.931	34.483	6.897	10.345	34.483	37.931
实际内部关系比例/%		3.900	0	31.579	41.176	3.175	0	56.000	25.000

变量	2000年	2002年	2004年	2006年	2008年	2010年	2012年	2014年	2016年	2019年
dis	0.189^*** （0.000）	0.187^*** （0.000）	0.192^*** （0.000）	0.248^*** （0.000）	0.259^*** （0.000）	0.279^*** （0.000）	0.274^*** （0.000）	0.242^*** （0.000）	0.255^*** （0.000）	0.246^*** （0.000）
pgdp	0.393^*** （0.000）	0.390^*** （0.000）	0.419^*** （0.000）	0.526^*** （0.000）	0.527^*** （0.000）	0.537^*** （0.000）	0.510^*** （0.000）	0.484^*** （0.000）	0.522^*** （0.000）	0.573^*** （0.000）
inds	0.144^** （0.016）	0.123^** （0.029）	0.103^** （0.041）	0.011 （0.363）	0.008 （0.420）	-0.014 （0.265）	0.015 （0.304）	0.026 （0.159）	-0.017 （0.306）	-0.122^*** （0.005）
open	0.048^* （0.084）	0.098^** （0.017）	0.079^** （0.044）	0.042 （0.136）	0.013 （0.265）	0.010 （0.378）	0.026 （0.206）	0.039^* （0.096）	0.056^* （0.070）	0.042^* （0.090）
env	0.009 （0.348）	-0.002 （0.510）	-0.013 （0.373）	-0.008 （0.429）	0.001 （0.476）	-0.019 （0.175）	-0.046^** （0.020）	-0.036^** （0.022）	-0.011 （0.340）	-0.080^*** （0.002）
gov	-0.014 （0.365）	-0.001 （0.542）	0.030 （0.179）	0.038^* （0.088）	0.022 （0.196）	-0.016 （0.214）	-0.031^* （0.085）	-0.017 （0.229）	0.011 （0.369）	-0.008 （0.421）
tech	0.074^** （0.046）	0.026 （0.191）	0.058^* （0.066）	0.066^** （0.034）	0.086^*** （0.002）	0.084^*** （0.000）	0.047^** （0.027）	0.051^** （0.021）	0.059^*** （0.007）	0.012 （0.374）
R²	0.289	0.311	0.321	0.357	0.340	0.347	0.335	0.319	0.345	0.313
Adj-R²	0.285	0.306	0.317	0.352	0.336	0.343	0.330	0.317	0.340	0.309