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Grey Relational Analysis of the Land- Sea Economy in China

Grey Relational Analysis of the Land- Sea Economy in China

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Grey Relational Analysis of the Land- Sea Economy in China

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  1. 2016 International Conference on Grey Systems and Uncertainty Analysis Grey Relational Analysis of the Land- Sea Economy in China Reporter:Xue Jin Supervisor:Professor Kedong Yin 2016-08-09

  2. 1 3 Conclusions and Future Work 2 4 Grey correlation degree analysis Relational schema analysis Backgroud 5 Causality test of land-sea economy Catalogua I Backgroud II Causality test of land-sea economy III Grey correlation degree analysis IV Relational schema analysis V Conclusions and Future Work

  3. I Backgroud II Causality test of land-sea economy 1Backgroud III Grey correlation degree analysis IV Relational schema analysis V Conclusions and Future Work

  4. I Backgroud 01 02 03 II Causality test of land-sea economy Blue economy Energy consumption power Fully effective use of all kinds of Marine resources and energy III Grey correlation degree analysis IV Relational schema analysis Practice and develope the strategy of "sea power" V Conclusions and Future Work

  5. I Backgroud IICausality test of land-sea economy 2Causality test of land-sea economy III Grey correlation degree analysis IV Relational schema analysis V Conclusions and Future Work

  6. Data: select the value of ocean gross domestic product and regional GDP from 1996-2013 Table 1Related indexs of land-sea economy I Backgroud IICausality test of land-sea economy III Grey correlation degree analysis IV Relational schema analysis V Conclusions and Future Work

  7. 2.1 Time series data processing I Backgroud IICausality test of land-sea economy Table 2 Processed data of land-sea economy III Grey correlation degree analysis IV Relational schema analysis V Conclusions and Future Work

  8. 2.2 ADF test of time series With the time sequence in table 1 and table 2, do a unit roots test and analysis using Eviews. The results are shown as follows. I Backgroud IICausality test of land-sea economy III Grey correlation degree analysis IV Relational schema analysis V Conclusions and Future Work After the Logarithmic yield processing, all series have good stability. Thus Granger causality test can be done.

  9. 2.3 Granger causality test of land-sea economy I Backgroud IICausality test of land-sea economy III Grey correlation degree analysis IV Relational schema analysis V Conclusions and Future Work

  10. I Backgroud II Causality test of land-sea economy • Grey correlation degree analysis III Grey correlation degree analysis IV Relational schema analysis V Conclusions and Future Work

  11. 3.1 Indicators selection I Backgroud II Causality test of land-sea economy III Grey correlation degree analysis IV Relational schema analysis V Conclusions and Future Work

  12. 3.2 Dimensionless processing I Backgroud II Causality test of land-sea economy III Grey correlation degree analysis IV Relational schema analysis V Conclusions and Future Work

  13. 3.3 Difference sequence, maximum and minimum difference I Backgroud II Causality test of land-sea economy III Grey correlation degree analysis IV Relational schema analysis V Conclusions and Future Work

  14. 3.4 Calculation of grey correlation I Backgroud II Causality test of land-sea economy III Grey correlation degree analysis IV Relational schema analysis V Conclusions and Future Work

  15. measure the grey correlation degree I Backgroud IICausality test of land-sea economy III Grey correlation degree analysis IV Relational schema analysis The relevance between marine economy and the tertiary industry is strongest followed is the second industry finally is the first industry V Conclusions and Future Work

  16. I Backgroud II Causality test of land-sea economy 4Relational schema analysis III Grey correlation degree analysis IV Relational schema analysis V Conclusions and Future Work

  17. There are certain differences between the development of national economy and marine economy in China’s 11 coastal provinces and cities. I Backgroud Table 10 GDP and ocean gross domestic product of China’s 11 coastal provinces and cities in 2013 II Causality test of land-sea economy III Grey correlation degree analysis IV Relational schema analysis V Conclusions and Future Work

  18. I Backgroud II Causality test of land-sea economy III Grey correlation degree analysis IV Relational schema analysis V Conclusions and Future Work

  19. Three kinds of patterns I Backgroud Guangxi Hebei II Causality test of land-sea economy b a c Land-sea weak type land-sea asymmetrical type Land-sea strong type III Grey correlation degree analysis Tianjin Shandong Zhejiang Liaoning IV Relational schema analysis Hainan Jiangsu V Conclusions and Future Work

  20. I Backgroud II Causality test of land-sea economy 5Conclusions and Future Work III Grey correlation degree analysis IV Relational schema analysis V Conclusions and Future Work

  21. The article uses methods such as ADF test, Granger causality test and grey correlation degree analysis to preliminary demonstrate the relationship of land-sea economy. I Backgroud II Causality test of land-sea economy ① There is a certain correlation between marine economy and land area economy. III Grey correlation degree analysis ② Three kinds of patterns sum up the relationship between the sea and land of 11coastal provinces and cities in our country,. IV Relational schema analysis V Conclusions and Future Work Planning economic layout of the land and sea, better promote the integration development of sea and land

  22. I Backgroud II Causality test of land-sea economy Thanks for the invitation of Prof. Yang! THANK YOU! III Grey correlation degree analysis IV Relational schema analysis V Conclusions and Future Work