中国区域投入产出效率的综合测度与时空格局

doi:10.11821/dlyj020170979

摘要/Abstract

摘要：

改革开放40多年来,中国经济发展与资源环境之间的矛盾日益突出,资源环境安全面临严峻的挑战。在此背景下,基于要素投入和经济、环境总产出的综合视角,构建区域投入产出效率评价指标体系,应用数据包络分析方法,采用CCR模型、Super-CCR模型,测算1995-2015年间不同时期中国各省区市的投入产出效率,并对其变化趋势及空间分异进行分析。结果表明,全国投入产出效率在波动中呈上升态势,特别是2010年之后投入产出效率提升较明显;2015年,中国区域投入产出效率呈较明显的由东向西、由北向南逐渐降低的空间格局分异。分区域看,东部地区投入产出效率相对最高,其中北京、天津、广东等省市的上升态势明显;东北地区投入产出效率整体偏低,特别是黑龙江的投入产出效率表现为持续下降;中部各省投入产出效率普遍不高,但河南相对较高且2010年较之前提升明显;西部地区投入产出效率的省际差异明显,其中西南各省投入产出效率下降态势较明显。

关键词: 投入产出效率, DEA模型, 时空格局, 省际, 中国

Abstract:

With rapid economic growth, the problem of resources depletion and environmental pollution has become increasingly prominent in China. According to the CO₂ emission reduction target, by 2020 the amount of CO₂ emission per output unit (GDP) will drop by 40%-45% compared to 2005, and China is facing a severe challenge in national sustainable development. It is against such background that this paper will make a comprehensive examination of regional input and output efficiency, aiming to discover a green and compatible way. From the perspective of the integrated view of factor input and economic-environmental output, this paper establishes provincial input and output efficiency indicator system, and then measures the changing trend and spatial differences of provincial input and output efficiency in China comprehensively, using CCR model and super-CCR mode. The major findings were summarized as follows. First, the input and output efficiency in China is rising, although there are fluctuations; especially after 2010, the efficiency in China has increased significantly, due to the government's efforts of development of green economy. In 2015, the input and output efficiency in China is 1.667, compared to 1.354 in 1995. Second, in 2015, provincial efficiency decreases gradually from eastern to central and western region, from north to south; while the provincial differences have been more significiant, compared to 1995. Third, the input and output efficiency of eastern region is higher than that of other regions, due to obvious location advantages, large economic volume and relatively high resource allocation efficiency. And the efficiency of Beijing, Tianjin and Guangdong has been increasing in the last two decades. The input and output efficiency in the western and northeastern regions are much lower, while Heilongjiang's efficiency has been decreasing since 1995. The input and output efficiency in central region with heavy industrial structure is at the middle level. Among the provinces, Shanxi, Anhui and Hubei have decreased the efficiency, while Henan has increased significantly after financial crisis. There exist clear differences of input and output efficiency in the western region, where the efficiency of most provinces is lower due to the weakness of natural background, too large proportion of energy and raw materials industry. But the efficiency of Qinghai is always the forfront, while that of southwest provinces has an obvious decreasing trend.

Key words: input and output efficiency, DEA model, spatio-temporal pattern, province, China

宋周莺, 康蕾, 刘毅. 中国区域投入产出效率的综合测度与时空格局[J]. 地理研究, 2019, 38(2): 326-336.

Zhouying SONG, Lei KANG, Yi LIU. Spatio-temporal analysis of provincial input-output efficiency in China[J]. GEOGRAPHICAL RESEARCH, 2019, 38(2): 326-336.

图/表 4

表1

表2

基于Super-CCR模型的1995-2015年中国投入产出效率评价结果"

DMU	1995年		2000年		2005年		2010年		2015年
DMU	Score	Rank	Score	Rank	Score	Rank	Score	Rank	Score	Rank
北京	1.8996	4	1.6290	5	1.7783	4	2.1187	3	2.2354	3
天津	1.1805	12	2.1003	3	1.8765	3	2.6745	2	2.6102	2
河北	1.1131	15	1.1051	13	1.0473	11	1.1227	10	1.0271	16
山西	0.9354	22	0.8840	24	0.9969	13	0.9630	15	0.7515	27
内蒙古	0.8566	27	1.0261	16	0.8079	21	1.2056	8	1.1021	12
辽宁	1.0513	19	1.1845	10	0.9021	17	0.9927	14	1.0861	13
吉林	0.9808	21	1.0163	17	0.8301	19	0.8182	21	0.8867	21
黑龙江	1.2809	8	1.2846	7	0.9934	14	0.6442	29	0.7601	26
上海	2.1383	3	1.8469	4	1.5113	7	1.6870	5	1.4638	6
江苏	1.2089	10	1.0726	14	1.0536	10	1.1072	12	1.2170	9
浙江	1.2202	9	1.1561	11	1.0614	9	1.1207	11	1.2136	10
安徽	0.9102	24	0.8977	23	0.6558	29	0.7523	24	0.8119	25
福建	1.1874	11	1.2592	8	1.2525	8	1.0690	13	1.0690	15
江西	1.0583	18	0.9967	18	0.7866	23	0.9110	16	0.9424	19
山东	1.1652	13	1.2071	9	1.5888	5	1.4173	7	1.3969	7
河南	1.1266	14	1.0383	15	0.9863	16	1.1404	9	1.1361	11
湖北	0.8347	28	0.9285	21	0.9872	15	0.7777	22	0.9651	18
湖南	1.0358	20	0.9638	19	0.8506	18	0.8686	19	1.0814	14
广东	1.3497	6	1.5800	6	1.5814	6	1.4863	6	1.5186	5
广西	1.1044	16	0.9475	20	0.7541	24	0.8444	20	1.2868	8
海南	5.4019	1	20.7961	1	21.6711	1	15.8943	1	16.7966	1
重庆	-	-	0.9024	22	0.8226	20	0.7445	25	0.8653	23
四川	1.8328	5	0.8246	25	0.8032	22	0.8701	18	0.8732	22
贵州	0.9338	23	0.7446	28	0.6834	28	0.7748	23	0.8885	20
云南	1.2860	7	1.1271	12	1.0437	12	0.7150	27	0.8406	24
陕西	0.8728	26	0.7604	27	0.7507	25	0.9054	17	1.0176	17
甘肃	0.7555	29	0.6644	30	0.7320	27	0.6554	28	0.5365	30
青海	2.5956	2	2.3932	2	2.9437	2	1.8926	4	2.2157	4
宁夏	0.8867	25	0.7151	29	0.5733	30	0.5689	30	0.6959	29
新疆	1.0751	17	0.7684	26	0.7434	26	0.7272	26	0.7036	28
平均值	1.3544	-	1.7940		1.7690	-	1.5823	-	1.6665	-

表2

图1

图2

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指标类型	类别	具体指标
投入指标	自然资源要素	用水总量
		建设用地面积
		能源消耗总量
	社会经济要素	从业人员数量
		固定资产投资额
		R&D经费支出占比
产出指标	经济产出	GDP
		工业增加值
		社会消费品零售总额
	污染排放	工业固体废物产生量
		工业废气排放总量
		工业废水排放量