Paper
16 June 2023 Simulation research on vector dynamic equilibrium model of international trade based on big data algorithm
Lihua Yang
Author Affiliations +
Proceedings Volume 12703, Sixth International Conference on Intelligent Computing, Communication, and Devices (ICCD 2023); 127030O (2023) https://doi.org/10.1117/12.2683007
Event: Sixth International Conference on Intelligent Computing, Communication, and Devices (ICCD 2023), 2023, Hong Kong, China
Abstract
The drastic changes in the environment will cause a series of humanitarian disasters, lead to political violence, and make the already fragile country crumble. China's dependence on foreign trade remains high all the year round, and the development of international trade business is of great significance to China's economic development and the increase of economic aggregate.We should link the balance of international trade with the balance of international payments from the perspective of comparative advantage and economies of scale and rethink the dynamic balance of international trade. In this paper, the simulation research of international trade vector dynamic equilibrium model based on big data algorithm is carried out. We extend the estimation and inference method based on the dynamic equilibrium model of international trade vector to the uncertain region in the parameter space. Bayesian statistical inference method is used, and probability weights are constructed for deterministic and uncertain regions in parameter space based on observation data. The results show that the vector dynamic equilibrium model of international trade constructed in this paper can provide a reliable analytical framework and a powerful tool for policy makers to predict and judge the effect of monetary policy system changes.
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Lihua Yang "Simulation research on vector dynamic equilibrium model of international trade based on big data algorithm", Proc. SPIE 12703, Sixth International Conference on Intelligent Computing, Communication, and Devices (ICCD 2023), 127030O (16 June 2023); https://doi.org/10.1117/12.2683007
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KEYWORDS
Data modeling

Statistical analysis

Computer simulations

Statistical inference

Autocorrelation

Reflection

Error analysis

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