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International Journal of Innovation and Research in Educational Sciences

Global Impact Analysis of Green GDP

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Year:
2023
Type of Publication:
Article
Keywords:
Green GDP Accounting, LSTM, Entropy Topsis, Gray Correlation Analysis
Authors:
  • Zhang, Ruitian
  • Xu, Yinan
  • Wu, Yi
  • Huang, Jinghan
  • Lin, Yuxiao
Journal:
IJIRES
Volume:
10
Number:
3
Pages:
138-148
Month:
May
ISSN:
2349-5219
BibTex:
Abstract:
For a long time, ignoring the basic role of resources and environment has become a drawback of the national economic accounting system, the objectivity and authenticity of the accounting values. The lack of integration of resources and environment into the accounting system has made the existing national GDP questioned by academia and the international community, and cannot truly reflect the level of national economic development. Therefore, this paper constructs a green GDP accounting system on the basis of the traditional national accounting system and simulates the global impact of green GDP after replacing the traditional GDP. Taking global data as an example, firstly, we construct a global stagnant growth model with different demographic structures and analyze the future change trend of population size with different age structures under the influence of GDP and GGDP. Subsequently, the changes in the next 30 years are predicted based on LSTM. Then the future changes of temperature and diurnal carbon emissions were solved by constructing multiple regression models under different change trends. Finally, the comprehensive climate score for the next 30 years was solved by the entropy-weighted Topsis integrated evaluation method, which integrates the short-term disadvantages and long-term advantages of GGDP development. Further, we investigate the model in depth, using improved gray correlation analysis, adding data dimensions, time dimensions, and considering the impact of economic, technological, medical, and educational factors on the development of green GDP and the impact caused by the use or conservation of natural resources.

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