Proceedings of the 2020 International Conference on Social Sciences and Big Data Application (ICSSBDA 2020)

Analysis of the Import and Export Trade of Chinese Herbal Medicine in China

Authors
Zengping Shi, Lu Zhang
Corresponding Author
Lu Zhang
Available Online 2 November 2020.
DOI
10.2991/assehr.k.201030.066How to use a DOI?
Keywords
Chinese herbal medicine, trade competitiveness index, international competitiveness, empirical analysis
Abstract

This paper analyzes the import and export data of Chinese herbal medicine from 1994 to 2018, analyzes the current situation of Chinese herbal medicine international trade, analyzes its international competitiveness by using the trade competition index, and uses the multi-linear regression model to analyze the data gradually. This paper explores the factors affecting the international competitiveness of Chinese herbal medicine. The research shows that the main factors affecting the international trade of Chinese herbal medicine are the sowing area of herbs and the World commodity price index, which is not Gross domestic product (Percent change, market exchange rates).

Copyright
© 2020, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2020 International Conference on Social Sciences and Big Data Application (ICSSBDA 2020)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
2 November 2020
ISBN
978-94-6239-266-3
ISSN
2352-5398
DOI
10.2991/assehr.k.201030.066How to use a DOI?
Copyright
© 2020, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Zengping Shi
AU  - Lu Zhang
PY  - 2020
DA  - 2020/11/02
TI  - Analysis of the Import and Export Trade of Chinese Herbal Medicine in China
BT  - Proceedings of the 2020 International Conference on Social Sciences and Big Data Application (ICSSBDA 2020)
PB  - Atlantis Press
SP  - 325
EP  - 331
SN  - 2352-5398
UR  - https://doi.org/10.2991/assehr.k.201030.066
DO  - 10.2991/assehr.k.201030.066
ID  - Shi2020
ER  -