中国沿海地区海洋经济效率时空演化及影响因素分析

doi:10.18402/resci.2018.10.06

摘要/Abstract

摘要：

为展现中国沿海地区海洋经济效率时空演变现状,并根据其具体原因提出针对性对策建议,促进中国海洋经济可持续发展,本文基于考虑非期望产出的三阶段超效率SBM-Global模型、标准差椭圆和重心坐标方法,对中国沿海11个省市2000—2015年海洋经济效率进行测算和时空对比分析。研究发现：①与一阶段相比,三阶段海洋经济效率整体上升,各省市排名出现不同程度变动;②时间演变上,全国各沿海地区海洋经济效率呈上升趋势,绝对差异和相对差异都不断变大;③空间演变上,全国标准差椭圆呈东北-西南格局分布,面积由小变大,效率分布由收缩趋势变为分散趋势,最终呈北、中、南三级格局分布,与三大海洋经济圈分布相吻合;三大海洋经济圈标准差椭圆面积都逐渐缩小,效率分布出现极化现象;④海洋经济区位熵、海洋科研人力资本、海洋环保技术水平与海洋经济效率之间存在非线性关系;陆域经济发展水平、海洋产业结构水平、政府对海洋科技支持力度、海洋经济政策力度对海洋经济效率呈显著正影响;对外开放水平对其影响不显著。

关键词: 海洋经济效率, 三阶段超效率SBM-Global, 标准差椭圆, 重心转移, 面板门槛模型, 沿海地区, 中国

Abstract:

Based on the three stage super-efficient SBM-Global model, standard deviation ellipse and centroid coordinate method, the marine economic efficiency of 11 coastal provinces and cities of China in 2000-2015 years is calculated and analyzed with the time and space. Research discovery: ① Compared with the first stage, the efficiency of marine economy in the third stage has increased overall, and the ranking of provinces and cities has changed differently. ② In the evolution of time: The efficiency of marine economy in all coastal areas of China has been on the rise, and the absolute and relative difference has been increasing and the relative difference changes relatively smooth. ③ In space evolution: The national standard deviation ellipse was distributed in the Northeast-Southwest pattern and its area increased from small to large. The efficiency distribution changes from the contraction trend to the dispersion trend and finally in the three level pattern of North, Middle and South, which is in accordance with the three major marine economic circles. The standard deviation ellipse area of the three major marine economic circles is gradually reduced, and polarization appears in the efficiency distribution. ④ There is a nonlinear relationship between development level of land area economy, marine economic location entropy, human capital of marine scientific research, marine environmental protection technology level and marine economic efficiency; land economic development level, the level of marine industrial structure, the government's support for marine science and technology has a significant positive impact on it, and the level of opening to the outside world has no significant impact on it.

Key words: marine economic efficiency, three stage super efficiency SBM-Global, standard deviation ellipse, center of gravity transfer, panel threshold model, coastal areas, China

盖美, 朱静敏, 孙才志, 孙康. 中国沿海地区海洋经济效率时空演化及影响因素分析[J]. 资源科学, 2018, 40(10): 1966-1979.

Mei GAI, Jingmin ZHU, Caizhi SUN, Kang SUN. Spatio-temporal evolution and influencing factors of marine economic efficiency in coastal areas of China[J]. Resources Science, 2018, 40(10): 1966-1979.

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参考文献 30

[1]	狄乾斌, 刘欣欣, 曹可. 中国海洋经济发展的时空差异及其动态变化研究[J]. 地理科学, 2013, 33(12): 1413-1420.
	[Di Q B, Liu X X, Cao K.Spatial and temporal disparities of marine economic development and dynamic changes in China[J]. Geography Science, 2013, 33(12): 1413-1420. ]
[2]	张耀光, 魏东岚, 王国力, 等. 中国海洋经济省际空间差异与海洋经济强省建设[J]. 地理研究, 2005, 24(1): 46-56.
	[Zhang Y G, Wei D L, Wang G L, et al. Analysis of interprovincial space difference in marine economy and the building of marine economically strong provinces in China[J]. Geographical Studies, 2005, 24(1): 46-56. ]
[3]	国家发展改革委. 全国海洋经济发展“十三五”规划[EB/OL]. (2017-05-04)[2018-08-31]. .
	[National Development and Reform Commission. "13th Five-Year plan" for National Marine Economic Development[EB/OL]. (2017-05-04)[2018-08-31]. ]
[4]	Tingley D, Pascoe S, Coglan L.Factors affecting technical efficiency in fisheries: stochastic production frontier versus data envelopment analysis approaches[J]. Fisheries Research, 2005, 73(3): 363-376.
[5]	卢昆, 郝平. 基于SFA的中国远洋渔业生产效率分析[J]. 农业技术经济, 2016, (9): 84-91.
	[Lu K, Hao P.Production efficiency analysis of SFA Chinese Pelagic Fisheries[J]. Agricultural Technology Economy, 2016, (9): 84-91. ]
[6]	Odeck J, Brathen S.A meta-analysis of DEA and SFA studies of the technical efficiency of seaports: a comparison of fixed and random effects regression models[J]. Transportation Research Part A: Policy and Practice, 2012, 46(10): 1574-1585.
[7]	于谨凯, 潘菁. 基于超效率DEA-Malmquist模型的我国海洋交通运输业效率分析[J]. 海洋经济, 2015, 5(5): 3-12.
	[Yu J K, Pan Q.Efficiency analysis of China's marine transportation industry based on super efficiency DEA-Malmquist model[J]. Marine Economy, 2015, 5(5): 3-12. ]
[8]	李淑娟, 周珊. 滨海城市旅游发展效率时空分异与驱动因素研究-以山东半岛蓝色经济区为例[J]. 中国海洋大学学报(社会科学版), 2015, (4): 8-15.
	[ Li S J, Zhou S.Spatial and temporal differentiation and driving factors of tourism development efficiency in coastal cities-a case study of Shandong Peninsula Blue Economic Zone[J]. Journal of Ocean University of China (Social Science Edition), 2015, (4): 8-15. ]
[9]	钟敬秋, 韩增林. 中国滨海旅游业效率评价及时空演变分析[J]. 海洋开发与管理, 2016, 33(8): 8-16.
	[Zhong J Q, Han Z L.Efficiency evaluation and temporal spatial evolution of coastal tourism in China[J]. Marine Development and Management, 2016, 33(8): 8-16. ]
[10]	DING L L, ZHENG H H, KANG W L.Measuring the green efficiency of ocean economy in China: an improved three-stage model[J]. Romanian journal of economic forecasting, 2017, 20(1): 5–22.
[11]	范斐, 孙才志, 张耀光. 环渤海经济圈沿海城市海洋经济效率的实证研究[J]. 统计与决策, 2011, (6): 119-123.
	[Fan F, Sun C Z, Zhang Y G.Empirical study on marine economic efficiency of coastal cities around Bohai economic circle[J]. Statistics and Decision, 2011, (6): 119-123. ]
[12]	赵林, 张宇硕, 焦新颖, 等. 基于SBM和Malmquist生产率指数的中国海洋经济效率评价研究[J]. 资源科学, 2016, 38(3): 461-475.
	[Zhao L, Zhang Y S, Jiao X Y, et al. An evaluation of Chinese marine economy efficiency based on SBM and Malmquist productivity indexes[J]. Resources Science, 2016, 38(3): 461-475. ]
[13]	Fried H O, Lovell C A K, Schmidt S S, et al. Accounting for environmental effects and statistical noise in data envelopment analysis[J]. Journal of Productivity Analysis, 2002, 17(1): 157-174.
[14]	Kaoru T.A slacks-based measure of efﬁciency in data envelopment analysis[J]. European Journal of Operational Research, 2002, 143(1): 32-41.
[15]	马占新. 数据包络分析模型与方法[M]. 北京: 科学出版社, 2010.
	[Ma Z X.The Models and Methods on Data Envelopment Analysis [M]. Beijing: Science Press, 2010. ]
[16]	陈巍巍, 张雷, 马铁虎, 等. 关于三阶段DEA模型的几点研究[J]. 系统工程, 2014, (9): 144-149.
	[Chen W W, Zhang L, Ma T H, et al. Some research on the three stage DEA model[J]. Systems Engineering, 2014, (9): 144-149. ]
[17]	Lefever D W.Measuring geographic concentration by means of the standard deviational ellipse[J]. The American Journal of Sociology, 1926, 32(1): 88-94.
[18]	Hanse B E.Threshold effects in non-dynamic panels: estimation, testing, and inference[J]. Journal of Econometrics, 1999, 93(2) : 345-368.
[19]	黄建欢, 杨晓光, 胡毅. 资源、环境和经济的协调度和不协调来源-基于CREE-EIE分析框架[J]. 中国工业经济, 2014, (7): 17-30.
	[Huang J H, Yang X G, Hu Y.The coordination and incongruous sources of resources, environment and economy based on CREE-EIE analysis framework[J]. China Industrial Economy, 2014, (7): 17-30. ]
[20]	盖美, 刘丹丹, 曲本亮. 中国沿海地区绿色海洋经济效率时空差异及影响因素分析[J]. 生态经济, 2016, 32(12): 97-103.
	[Gai M, Liu D D, Qu B L.Analysis of spatial and temporal differences and influencing factors of green marine economic efficiency in China's coastal areas[J]. Ecological Economy, 2016, 32(12): 97-103. ]
[21]	张军, 吴桂英, 张吉鹏. 中国省际物质资本存量估计: 1952-2000[J]. 经济研究, 2004, (10): 35-44.
	[Zhang J, Wu G Y, Zhang J P.Estimation of inter provincial material capital stock in China: 1952-2000[J]. Economic Research, 2004, (10): 35-44. ]
[22]	Young A.Gold into Base Metals: Productivity Growth in the People's Republic of China during the Reform Period[R]. Beijing: National Bureau of Economic Research, 2000.
[23]	国家海洋局. 中国海洋统计年鉴[M]. 北京: 海洋出版社, 2000-2015.
	[State Oceanic Administration.China Marine Statistical Yearbook [M]. Beijing: Ocean publishing house, 2000-2015. ]
[24]	中华人民共和国环境保护部. 中国环境统计年鉴[M]. 北京: 中国环境年鉴出版社, 2000-2015.
	[Ministry of Environmental Protection of the People's Republic of China. China Environmental Statistics Yearbook [M]. Beijing: China Environmental Yearbook Press, 2000-2015. ]
[25]	国家统计局. 中国统计年鉴[M]. 北京: 中国统计出版社, 2000-2015.
	[State Statistical Bureau.China Statistical Yearbook [M]. Beijing: China Statistics Publishing House, 2000-2015. ]
[26]	国家统计局. 中国区域统计年鉴[M]. 北京: 中国统计出版社, 2000-2015.
	[ State Statistical Bureau.China Regional Statistical Yearbook [M]. Beijing: China Statistical Publishing House, 2000-2015. ]
[27]	国家统计局城市社会经济调查司. 中国城市统计年鉴[M]. 北京: 中国统计出版社, 2000-2015.
	[Department of Urban Social and Economic Investigation, National Bureau of Statistics. China Urban Statistics Yearbook [M]. Beijing: China Statistics Publishing House, 2000-2015. ]
[28]	[2018-08-31]. [The State Council. Some Opinions on Implementing the Strategy of Revitalizing Old Industrial Bases in Northeast China[EB/OL]. (2016-04-26)[<date-in-citation content-type="access-date">2018-08-31</date-in-citation>]. ]
[29]	天津市海洋局. 天津市科技兴海行动[EB/OL]. (2016-08-10)[2018-08-31]. .
	[Tianjin Ocean Bureau. Tianjin Science and Technology to Promote the Sea Action[EB/OL]. (2016-08-10)[2018-08-31]. ]
[30]	国家发展改革委. 浙江海洋经济发展示范区规划[EB/OL]. (2011-03-12)[2018-08-31].
	[National Development and Reform Commission. Zhejiang Marine Economic Development Demonstration Zone Planning[EB/OL]. (2011-03-12)[2018-08-31].

目标层	准则层	指标层（第一、三阶段）	指标层（第二阶段）
投入	资源系统	年末涉海从业总人数/万人、固定资本存量/亿元海洋机动渔船年末拥有量/艘、星级饭店数量/家港口码头泊位数/个	海洋科研人力资本/人政府科教支持力度/%
产出	经济系统	海洋GDP/亿元	陆域经济发展水平/（万元/人）、地区对外开放水平/%、海洋经济发展水平/（万元/人）、海洋产业结构水平/%
产出	环境系统	废水直排入海量/万t、SO₂排放量/t	单位海洋GDP能耗/（万元/t）

省份	天津	河北	辽宁	上海	江苏	浙江	福建	山东	广东	广西	海南	全国
一阶段	0.874	0.422	0.428	0.776	0.352	0.424	0.620	0.500	0.581	0.263	0.734	0.543
三阶段	0.799	0.438	0.511	0.885	0.464	0.537	0.549	0.688	0.736	0.282	0.567	0.587
一阶段排名	1	9	7	2	10	8	4	6	5	11	3
三阶段排名	2	10	8	1	9	7	6	4	3	11	5

	涉海从业总人数		固定资本存量		资源投入
	系数	T值	系数	T值	系数	T值
常数项	56.00	2.40**	2.00	2.10***	-430.00	-5.60***
海洋科研人力资本	110.00	1.50	-0.55	-1.90*	-0.30E+04	-10.00***
海洋经济发展水平	-30.00	-3.40***	0.09	2.20**	2.50E+04	21.00***
陆域经济发展水平	120.00	4.80***	-0.32	-2.90***	-6.00E+04	-20.00***
单位海洋GDP能耗	-0.70E-04	-0.87	-0.63E-04	-2.10**	6.90	4.60***
sigma-squared	4.00E+04	600.00***	0.98	5.20***	3.30E+08	3.30E+08***
γ	0.92	100.00***	0.95	100.00***	0.52	9.80***
log likelihood	-990.00		-39.00		-0.20E+04

门槛变量	门槛数	F值	1%	5%	10%	门槛值	置信区间
海洋经济区位熵X1	单一	40.05**	65.29	31.91	20.67	0.90	[0.82,0.93]
	双重	5.15	35.78	16.57	11.56	6.31	[4.92,6.71]
	三重	6.52*	11.71	7.07	5.07	4.95	[0.73,7.93]
海洋产业结构X2	单一	22.41	54.00	34.40	27.04	0.61	[0.26,0.65]
	双重	4.22	17.13	10.99	8.72	0.65	[0.61,0.68]
	三重	10.16	24.46	13.10	10.82	0.29	[0.26,0.56]
海洋科研人力资本X3	单一	7.23*	21.15	11.03	7.27	1.42	[0.00,2.70]
	双重	2.94	17.90	11.76	6.27	8.43	[0.03,10.16]
	三重	12.01***	14.17	9.20	7.39	2.42	[0.03,2.70]
单位海洋GDP能耗X4	单一	12.63*	25.39	17.20	12.66	0.46	[0.05,0.58]
	双重	11.46	23.04	15.46	12.02	0.56	[0.05,0.78]
	三重	5.52	23.15	16.50	10.29	0.05	[0.05,0.38]
海洋经济政策X5	单一	6.82	20.94	11.74	7.55	196.15	[34.66,801.78]
	双重	15.87*	34.95	20.98	9.92	1 178.78	[1 128.39,1 188.60]
	三重	1.71	13.81	8.07	6.22	540.85	[34.66,619.47]

	Y(Z1门槛变量)		Y(X2门槛变量)		Y(X3门槛变量)
	系数	置信区间	系数	置信区间	系数	置信区间
Z1	0.023***	[0.011, 0.035]	0.018***	[0.005, 0.031]	0.022***	[0.008, 0.035]
Z2	-0.039	[-0.094, 0.017]	-0.070*	[-0.128, -0.012]	-0.068**	[-0.128, -0.008]
Z3	0.040***	[0.029, 0.052]	0.041***	[0.030, 0.053]	0.051***	[0.038, 0.063]
X1-1·I	-0.522***	[-0.673, -0.371]
X1-2·I	0.064**	[0.012, 0.124]
X2			0.320***	[0.171, 0.470]
X3-1·I					0.016***	[0.004, 0.028]
X3-2·I					0.003	[-0.001, 0.007]
	Y(X4门槛变量)		Y(X5门槛变量)
	系数	置信区间	系数	置信区间
Z1	0.011	[-0.002, 0.025]	0.022***	[0.014, 0.042]
Z2	-0.062**	[-0.121, -0.003]	-0.073**	[-0.131, -0.014]
Z3	0.058***	[0.044, 0.071]	0.045***	[0.032, 0.054]
X4-1·I	0.531***	[0.129, 0.932]
X4-2·I	0.145	[-0.094, 0.383]
X5			0.243***	[0.012, 0.383]