海洋产业影响省域经济增长估计及其分异动因判识

doi:10.13249/j.cnki.sgs.2018.02.003

地理科学 ›› 2018, Vol. 38 ›› Issue (2): 177-185.doi: 10.13249/j.cnki.sgs.2018.02.003

海洋产业影响省域经济增长估计及其分异动因判识

马仁锋^1,²(), 候勃¹, 张文忠², 袁海红¹, 窦思敏¹

1.宁波大学地理与空间信息技术系, 浙江宁波315211
2.中国科学院地理科学与资源研究所区域可持续发展分析与模拟院重点实验室, 北京100101

收稿日期:2017-05-08 修回日期:2017-09-02 出版日期:2018-04-10 发布日期:2018-04-10
作者简介:
作者简介：马仁锋（1979-）,男,湖北枣阳人,博士,副教授,主要从事经济地理、区域规划与城市研究。E-mail: marfxf@126.com
基金资助:
浙江省自然科学基金项目(LY17D010002)、宁波大学研究生科研创新基金项目(G17098)资助

Estimates of Marine Industry Impact on Provincial Economic Growth and Its Identification of Differentiation Dynamics in 2006-2015

Renfeng Ma^1,²(), Bo Hou¹, Wenzhong Zhang², Haihong Yuan¹, Simin Dou¹

1. Department of Geography & Spatial Information Techniques, Ningbo University, Ningbo 315211, Zhejiang, China;
2. Key Laboratory of Regional Sustainable Development Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China

Received:2017-05-08 Revised:2017-09-02 Online:2018-04-10 Published:2018-04-10
Supported by:
Zhejiang Provincial Natural Science Foundation ( LY17D010002), Graduate Research Innovation Foundation of Ningbo University (G17098)

摘要/Abstract

摘要：

采用静态和动态计量方法分析2006~2015年海洋经济对沿海省（市、区）经济发展的影响程度并通过空间计量方法识别差异动因。研究发现：① 海洋经济对中国省域经济发展具有显著地影响,其中天津、上海、福建、山东、广东、海南海洋经济总量贡献率高于全国平均水平;② 省域海洋产业对区域经济影响度分异呈现省际绝对差异不断扩大、相对差异不断缩小,且具有显著的空间相关性;③ 引起省域经济增长差异的海洋经济相关因素中,海洋第二产业、海洋进出口贸易额等起到正向促进作用（即拉大差异）,且海洋第二产业结构具有显著的溢出效应。相关发现有助于中国沿海省（市、区）经济的协调发展和科学决策。

关键词: 海洋产业, 省域经济, 空间相关性, 增长动因, 空间计量经济模型

Abstract:

By analyzing the economic impact of marine industry on coastal provinces, the arcitle examines the spatial correlation of per capita GDP, establishes a spatial econometric model, and then analyzes the spatial and temporal differentiation of the marine industry and the causes of the regional economic growth (2006-2015). Choosing the coastal provinces (cities) as the research unit. This study found that: 1) Comprehensive portrayal of the contribution rate of the marine economy to the provincial economy and the static and dynamic measurement results of marine economy promoting regional economic growth. We found that the marine economy in coastal provinces (cities) has a significant impact on provincial economic growth, and the degree of promotion is different. In addition, the contribution rate of marine economy to provincial economy in Tianjin, Shanghai, Fujian, Shandong, Guangdong and Hainan is higher than the national average rate. Further, the differences in the influence degree of the marine industry on the regional economy shows that the absolute difference between the provinces is expanding and the relative difference is shrinking, and there is significant spatial correlation. 2) The related factors of the Marine economy may give rise to the difference of provincial economic growth, we have found that the second marine industry, marine import and export trade volume both play a positive role in promoting regional economy. While the first and tertiary industries of marine economy have a hindrance to the differences in provincial economic growth. And the secondary industry of marine economy has obvious positive spillover effect on the surrounding areas, while the estimated parameters of the employment situation, the fiscal revenue and the education basic situation in the coastal areas are not significant in the spatial measurement model. 3) The results of the four spatial econometric models show that most of the explanatory variables pass the significance testing and they are in line with the actual situation. Durbin space error model estimation results overall is superior to the other models, the error of spatial Durbin model identify the Marine economy factors influencing the regional economic growth differences includes not only the neighboring regions of the economy themselves, but also the surrounding provinces of the relevant explanatory variables. Basing on the analysis of the economic growth difference and the contribution rate of the marine economy in the coastal provinces, the article draws the focus of narrowing the development gap of marine industry in the coastal provinces and cities to promote the coordinated development of China's coastal zone. That is, to cultivate the marine economic potential of provincial economic growth. Related findings are helpful for understanding the balanced development and making scientific decision-making of Marine economy in coastal cities and provinces in China.

Key words: marine industry, provincial economy, spatial correlation, growth motivation, spatial econometric model

中图分类号:

F062.9

马仁锋, 候勃, 张文忠, 袁海红, 窦思敏. 海洋产业影响省域经济增长估计及其分异动因判识[J]. 地理科学, 2018, 38(2): 177-185.

Renfeng Ma, Bo Hou, Wenzhong Zhang, Haihong Yuan, Simin Dou. Estimates of Marine Industry Impact on Provincial Economic Growth and Its Identification of Differentiation Dynamics in 2006-2015[J]. SCIENTIA GEOGRAPHICA SINICA, 2018, 38(2): 177-185.

图/表 6

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表2

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表6

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变量分类	变量名称		变量解释
被解释变量	Y	区域经济差异	人均 GDP（元）
解释变量	H	主要海洋产业活动	沿海地区海洋货物运输量（万t）
	C	财政收入	沿海地区财政收入（万元）
	J	涉海就业	涉海就业人员情况（万人）
	E	教育基本情况	本、专科毕（结）业生数（万人）
	O	海洋产业结构	海洋第一产业产值（万元）
	T		海洋第二产业产值（万元）
	S		海洋第三产业产值（万元）

地区	2006年	2007年	2008年	2009年	2010年	2011年	2012年	2013年	2014年	2015年
辽宁	15.99	15.96	15.41	15.00	14.19	15.05	13.65	13.82	15.00	15.43
天津	31.41	31.70	29.72	28.69	32.76	31.12	30.55	31.69	31.97	33.10
河北	9.37	8.99	8.63	5.35	5.65	5.92	6.10	6.15	6.30	6.90
山东	16.67	17.24	17.21	17.17	18.06	17.70	17.94	17.73	17.60	17.46
江苏	5.95	7.28	6.98	7.89	8.57	8.66	8.74	8.32	8.99	9.10
上海	38.47	35.45	34.99	27.94	30.44	29.27	29.46	29.19	26.40	26.57
浙江	11.79	11.95	12.46	14.76	14.01	14.04	14.27	14.00	14.33	14.41
福建	22.89	24.76	24.84	26.17	24.99	24.40	22.75	23.11	27.00	26.90
广东	15.70	14.58	16.32	16.87	17.94	17.27	18.41	18.15	21.28	21.88
广西	6.23	5.77	5.56	5.72	5.73	5.24	5.84	6.26	5.90	6.00
海南	29.60	30.34	29.44	28.61	27.13	25.91	26.37	28.08	26.94	28.00
全国	15.74	15.67	15.80	15.56	16.09	15.74	15.84	15.78	16.07	16.36

地区	回归模型	R²	AdjR²	DW	F
天津	y=3.1347x+244.87	0.992	0.991	2.497	778.967
河北	y=17.277x-3096.3	0.608	0.542	0.852	9.299
辽宁	y=19293lnx-132993.1483	0.971	0.967	2.983	203.537
上海	y=22326lnx-173917.0365	0.905	0.889	2.07	56.882
江苏	y=9.866x+8115	0.989	0.988	1.651	557.862
浙江	y=10596e^0.00024^x	0.984	0.982	1.932	379.960
福建	y=4399.5e^0.00032^x	0.983	0.980	1.034	339.515
山东	y=5.3612x+2198.5	0.998	0.998	2.746	3448.532
广东	y=4.7766x+7820.8	0.992	0.991	3.001	765.189
广西	y=8942.2lnx-46353	0.970	0.965	1.398	195.120
海南	y=2154.7lnx-11496	0.987	0.985	1.315	471.619

地区	回归模型	R（Kendall’s ) Tau-b相关系数	R²	F
天津	y=-207.37x³+139.54x²-26.157x+1.6359	0.524	0.509	1.286
河北	y=-19.196x³+1.0969x²+2.1056x-0.09637	1.000	0.818	4.496
辽宁	y=-53.281x³+22.445x²-1.8977x+0.13773	0.429	0.786	3.675
上海	y=-45.604x³+9.3626x²+1.0051x-0.00386	0.619	0.497	0.990
江苏	y= 0.25393x^0.30375	0.714	0.590	7.209
浙江	y=-45.389x³+12.404x²+0.08291x+0.02794	0.048	0.760	3.174
福建	y=7.7647x³-4.2736x²+1.004x+0.07884	0.333	0.421	0.726
山东	y=-231.2x³+94.61x²-11.199x+0.50071	0.619	0.937	11.074
广东	y=6.5954x³-2.375x²+0.30598x+0.11158	0.048	0.090	0.099
广西	y=1114.6x³-586.81x²+98.977x-5.1774	0.048	0.363	0.022
海南	y=-880.75x³+394.99x²-56.758x+2.747	0.238	0.159	0.300

		卡方统计	卡方自由度	P值
		966.217356	7	0.0000
变量	固定效应	随机效应	方差	P值
H	0.198796	0.253289	0.000050	0.0000
C	0.029424	-0.576559	0.001879	0.0000
J	-0.172104	0.460696	0.002985	0.0000
E	0.012960	0.716520	0.002125	0.0000
O	-0.040608	-0.265288	0.000322	0.0000
T	0.156970	-0.083384	0.000237	0.0000
S	0.044353	-0.001629	0.000175	0.0005

海洋产业影响省域经济增长估计及其分异动因判识

Estimates of Marine Industry Impact on Provincial Economic Growth and Its Identification of Differentiation Dynamics in 2006-2015

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变量	SLM系数	SEM系数	SDM系数	SDEM系数
H	0.9584^***(3.103746)	0.489461^***(2.648149)	1.166775^***(2.37734)	1.051553^***(3.789919)
J	-2.341585(-0.106089)	-9.435456(-0.780028)	-24.077058(-0.668345)	29.337306^*(1.481309)
C	-7.761522^**(-1.902011)	-0.439478(-0.199542)	-6.691618(-1.024232)	-2.545109(-0.561547)
E	640.653006^*(1.698864)	-205.513042^*(-1.089912)	347.633515(0.782879)	145.52079(0.462581)
O	-33.228169^*(-1.596233)	-19.664495^**(-1.788737)	-1.524914^*(-0.054038)	-4.406687^* (-0.160597)
T	11.537193^*(1.843374)	10.515812^***(3.305701)	5.279244^**(0.717254)	7.941851^**(1.322155)
S	-7.145898^*(-0.946012)	-4.931319^*(-1.565384)	3.189366^*(0.221914)	-4.607707^*(-0.415416)
W×H	-	-	-0.10783(-0.191012)	0.065832(0.10073)
W×J	-	-	-6.225627(-0.113743)	93.928872^*(1.795482)
W×C	-	-	-35.154602^**(-2.271724)	-12.134548(-1.113041)
W×E	-	-	1937.788188^***(3.133376)	990.949808(1.296434)
W×O	-	-	66.110194(0.75398)	36.886462(0.471991)
W×T	-	-	16.63193^**(1.964318)	37.328556^**(2.040601)
W×S	-	-	13.190625(0.664135)	-24.674653(-1.013791)
Ρ（λ）	-0.236068^***(-2.625756)	0.768493^***(13.929742)	-0.236068^***(-2.614974)	0.798501^***(16.366526)
R²	0.1485 556795057.5	0.1592	0.0061	0.0061
Sig.²	0.1485 556795057.5	144874119.1	481838304.8	481838304.8
对数似然估计函数值	-943.54625	-961.45765	-951.5286	-951.5286

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