Issue |
SHS Web of Conferences
Volume 17, 2015
ICMETM 2015 - International Conference on Modern Economic Technology and Management
|
|
---|---|---|
Article Number | 01008 | |
Number of page(s) | 7 | |
Section | Economic and Industry | |
DOI | https://doi.org/10.1051/shsconf/20151701008 | |
Published online | 25 March 2015 |
Analysis of Factors on the US Soybean Pricing in China’s Import Market – Based on principal component analysis
College of Economics in Yangtze University, Jingzhou, Hubei, China
a Corresponding author: mjg56@sina.com
Using quarterly data from 2002 to 2014, based on principal component analysis, this paper studies the factors affecting the US soybean pricing in China’s import market, and results show that China’s soybean import quantity from the US has positive impact on the US soybean pricing in China’s import market, but its impact is very weak. China’s gross domestic product, China’s domestic soybean production price index, the yuan-dollar exchange rate, the yuan-Argentine peso exchange rate and the yuan-Brazilian real exchange rate have negative impact on the US soybean pricing in China’s import market. According to this, there are some recommendations: maintain the growth of gross domestic product; improve soybean TFP to reduce soybean producer price index reasonably; take advantage of the exchange rate mechanism effectively to adjust the cost of soybean imports.
Key words: soybean imports / principal component regression / soybean pricing
© Owned by the authors, published by EDP Sciences, 2015
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 2.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.