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dc.contributor.authorJiacheng, G.
dc.contributor.authorZhalezka, B. A.
dc.date.accessioned2026-01-13T10:14:42Z-
dc.date.available2026-01-13T10:14:42Z-
dc.date.issued2025
dc.identifier.citationComputer Data Analysis and Modeling: Stochastics and Data Science : Proc. of the XIV Intern. Conf., Minsk, Sept. 24–27, 2025 / Belarusian State Univ. ; eds.: Yu. Kharin (ed.-in-chief) [et al.]. – Minsk : BSU, 2025. – Pp. 95-98.
dc.identifier.isbn978-985-881-830-2
dc.identifier.urihttps://elib.bsu.by/handle/123456789/339957-
dc.description.abstractBased on China’s provincial panel data, this study uses entropy weight model and vector autoregressive model to measure the economic growth quality of high-tech industries in China and test the interaction effect among regions. It is found that the quality of economic growth of high-tech industries in China has shown a steady growth trend during the study period, but there are obvious differences in the growth level among regions. The economic growth quality of high-tech industries in the eastern region is obviously stronger than that in the central region and the western region. In addition, the economic growth quality of high-tech industries in the eastern region is likely to have a siphon effect on the central region and the western region, while the central region is likely to have a radiation effect on the western region
dc.language.isoen
dc.publisherMinsk : BSU
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.subjectЭБ БГУ::ОБЩЕСТВЕННЫЕ НАУКИ::Экономика и экономические науки
dc.subjectЭБ БГУ::ЕСТЕСТВЕННЫЕ И ТОЧНЫЕ НАУКИ::Математика
dc.titleA method to evaluate the economic growth quality of high-tech industry in China and its regional linkage
dc.typeconference paper
Располагается в коллекциях:2025. Computer Data Analysis and Modeling: Stochastics and Data Science

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