中国海洋资源消耗强度因素分解与时空差异分析
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摘要
基于海洋资源消耗强度内涵,测度中国沿海省区1996—2015年海洋资源消耗强度,揭示其时空演化特征,运用改进的对数均值迪式指数分解法(LMDI)建立因素分解模型,分析中国海洋资源消耗强度变动的因素贡献并进行差异比较。结果表明:(1)1996—2015年,中国海洋资源消耗强度总体呈先上升后稳步下降的态势,第一产业资源消耗强度平稳下降,第二、三产业资源消耗强度与中国海洋资源消耗强度变动趋势基本同步;空间格局演化上,海洋资源消耗中高强度省区逐渐减少,低强度省区逐渐增多,区域差异逐步缩小;(2)技术进步效应、产业结构效应和区域规模效应对我国海洋资源消耗强度下降的贡献率分别为78.224%、18.334%和3.442%;沿海各省区的因素分解效应差异显著,其中福建以技术进步效应为主,浙江、山东和海南以技术进步效应和区域规模效应为主,天津、河北和江苏以技术进步效应和产业结构效应为主,辽宁、上海、广东和广西则是技术进步效应、产业结构效应和区域规模效应共同推动海洋资源消耗强度下降;(3)从海洋三次产业来看,技术进步效应在第二产业内部贡献最大,累计占比为77.118%;产业结构效应在第一产业内部贡献最大,累计占比为314.547%;区域规模效应在三次产业内部无明显差异。各省区推行海洋三次产业资源集约利用技术或措施时应有所区别和侧重。
Based on the connotation of marine resources consumption intensity, this study evaluated the marine resources consumption intensity in China's coastal provinces from 1996 to2015, revealing its temporal and spatial evolution characteristics. It implemented an improved LMDI to establish a factor decomposition model to analyze the contribution of factors in the change of marine resources consumption intensity and compare the differences. The results showed the following:(1) From 1996 to 2015, the intensity of China's marine resources consumption demonstrated an overall increasing trend, followed by a gradual decline. For the primary industry,resources consumption intensity exhibited a stable decline, while its fluctuations for the secondary and tertiary industries followed those of China's marine resources consumption intensity.Regarding the spatial evolutions. Moderately high-intensity provinces gradually declined in number, while low-intensity provinces gradually increased. Further, the variation between regions gradually declined.(2) The technological progress, industrial structure, and regional scale effects had contributed to 78.224%, 18.334%, and 3.442% of the total decline in marine resources consumption intensity. The factor decompostion effects varied significantly across provinces. The technological progress effect influenced marine resources consumption intensity in Fujian, while the technological progress and regional scale effects effected Zhejiang, Shandong, and Hainan. The technological progress and industrial structure effects influenced Tianjin, Hebei, and Jiangsu, while the technological progress, industrial structure, and regional scale effects drove decreasing marine resources consumption intensity in Liaoning, Shanghai, Guangdong, and Guangxi.(3) Among the three marine industries, the secondary industry illustrated the largest contribution with the technological progress effect, accounting for 77.118%; the primary industry did show the largest contribution with the industrial structure effect, accounting for 314.547%. The regional scale effect was not significant within the three industries. Technologies and the measures aim at promoting the intensive use of marine resources should be regionally targeted and differentiated according to each province.
Based on the connotation of marine resources consumption intensity, this study evaluated the marine resources consumption intensity in China's coastal provinces from 1996 to2015, revealing its temporal and spatial evolution characteristics. It implemented an improved LMDI to establish a factor decomposition model to analyze the contribution of factors in the change of marine resources consumption intensity and compare the differences. The results showed the following:(1) From 1996 to 2015, the intensity of China's marine resources consumption demonstrated an overall increasing trend, followed by a gradual decline. For the primary industry,resources consumption intensity exhibited a stable decline, while its fluctuations for the secondary and tertiary industries followed those of China's marine resources consumption intensity.Regarding the spatial evolutions. Moderately high-intensity provinces gradually declined in number, while low-intensity provinces gradually increased. Further, the variation between regions gradually declined.(2) The technological progress, industrial structure, and regional scale effects had contributed to 78.224%, 18.334%, and 3.442% of the total decline in marine resources consumption intensity. The factor decompostion effects varied significantly across provinces. The technological progress effect influenced marine resources consumption intensity in Fujian, while the technological progress and regional scale effects effected Zhejiang, Shandong, and Hainan. The technological progress and industrial structure effects influenced Tianjin, Hebei, and Jiangsu, while the technological progress, industrial structure, and regional scale effects drove decreasing marine resources consumption intensity in Liaoning, Shanghai, Guangdong, and Guangxi.(3) Among the three marine industries, the secondary industry illustrated the largest contribution with the technological progress effect, accounting for 77.118%; the primary industry did show the largest contribution with the industrial structure effect, accounting for 314.547%. The regional scale effect was not significant within the three industries. Technologies and the measures aim at promoting the intensive use of marine resources should be regionally targeted and differentiated according to each province.
引文
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[9]杨正先,张志锋,韩建波,等.海洋资源环境承载能力超载阈值确定方法探讨[J].地理科学进展,2017,36(3):313-319.[Yang Z X,Zhang Z F,Han J B,et al.Thresholds determination of marine resource and environmental carrying capacity[J].Progress in Geography,2007,36(3):313-319.]
[10]孙才志,于广华,王泽宇,等.环渤海地区海域承载力测度与时空分异分析[J].地理科学,2014,34(5):513-521.[Sun C Z,Yu GH,Wang Z Y,et al.Marine carrying capacity assessment and spatio-temporal analysis in the Bohai sea ring area[J].Scientia Geographica Sinica,2014,34(5):513-521.]
[11]孙才志,覃雄合,李博,等.基于WSBM模型的环渤海地区海洋经济脆弱性研究[J].地理科学,2016,36(5):705-714.[Sun C Z,Qin X H,Li B,et al.Assessment of marine economy vulnerability of coastal cities in Bohai sea ring area based on WSBM model[J].Scientia Geographica Sinica,2016,36(5):705-714.]
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[14]王泽宇,卢雪凤,韩增林,等.中国海洋经济增长与资源消耗的脱钩分析及回弹效应研究[J].资源科学,2017,39(9):1658-1669.[Wang Z Y,Lu X F,Han Z L,et al.Decoupling analysis and rebound effect between China's marine economic growth and resource consumption[J].Resources Science,2017,39(9):1658-1669.]
[15]邹玮,孙才志,覃雄合.基于Bootstrap-DEA模型环渤海地区海洋经济效率空间演化与影响因素分析[J].地理科学,2017,37(6):859-867.[Zou W,Sun C Z,Qin X H.Spatial evolution of marine economic efficiency and its influential factors in Bohai sea ring area based on Bootstrap-DEA model[J].Scientia Geographica Sinica,2017,37(6):859-867.]
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[17]Sun J W.Changes in energy consumption and energy intensity:Acomplete decomposition model[J].Energy Economics,1998,20(1):85-100.
[18]孔婷,孙林岩,何哲.中国工业能源消耗强度的区域差异-基于省(市)面板数据模型的实证分析[J].资源科学,2010,32(7):1222-1229.[Kong T,Sun L Y,He Z.A study on regional industrial energy intensity:An empirical analysis based on panel data model of different provinces in China[J].Resources Science,2010,32(7):1222-1229.]
[19]Cornillie J,Fankhauser S.The energy intensity of transition countries[J].Energy Economics,2004,26(3):283-295.
[20]臧正,邹欣庆.中国大陆水资源强度的收敛特征检验:基于省际面板数据的实证[J].自然资源学报,2016,31(6):920-935.[Zang Z,Zou X Q.Test on convergence trait of water resource intensity in mainland China:An empirical research based on panel data at provincial Level[J].Journal of Natural Resources,2016,31(6):920-935.]
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[22]楼东,谷树忠,钟赛香.中国海洋资源现状及海洋产业发展趋势分析[J].资源科学,2005,27(5):20-26.[Lou D,Gu S Z,Zhong SX.Current situation and development trend of marine industry in China[J].Resources Science,2005,27(5):20-26.]
[23]吴姗姗,张凤成,曹可.基于集对分析和主成分分析的中国沿海省海洋产业竞争力评价[J].资源科学,2014,36(11):2386-2391.[Wu S S,Zhang F C,Cao K.Marine industry competitiveness of coastal provinces in China based on set pair analysis and principal component analysis[J].Resources Science,2014,36(11):2386-2391.]
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