Research on Chinese Import Trade Based on Mulitiple Linear Regression Model

DOI

10.2991/wartia-16.2016.180How to use a DOI?

Keywords

Import, multiple linear regression model, OLS, econometric test.

Abstract

This paper uses OLS parameter estimation method and GDP, per capita disposable income, export, foreign investment and exchange rate fluctuations as the five factors for our multiple linear regression analysis, and the economic significance, statistical significance and econometric test are made. The conclusions are that: (1) the main factors that affect the import trade are GDP, urban residents per capita disposable income, total exports, influence of foreign investment on import trade, and fluctuations in the exchange rate, which has a negative influence on import trade. The two factors: GDP and the impact of foreign investment, have a serious overlap relationship and causes the col-linearity problem. The influence of exchange rate on import trade, can display by urban residents per capita disposable income. (2) According to the results of the test for heteroscedasticity can be concluded that the effect of 2007-2014 data of the model don’t have heteroscedasticity. (3) The autocorrelation test shows that, the import trade by a year ago has majorly impact on the nowadays, total imports often with national fundamentals associated closely. First three quarter of imported trade resulted in an increase in the import trade increased. In front of the fourth quarter of imports often have a negative impact.

Copyright

© 2016, 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/).

Download article (PDF)

TY  - CONF
AU  - Biao Xu
PY  - 2016/05
DA  - 2016/05
TI  - Research on Chinese Import Trade Based on Mulitiple Linear Regression Model
BT  - Proceedings of the 2016 2nd Workshop on Advanced Research and Technology in Industry Applications
PB  - Atlantis Press
SP  - 852
EP  - 856
SN  - 2352-5401
UR  - https://doi.org/10.2991/wartia-16.2016.180
DO  - 10.2991/wartia-16.2016.180
ID  - Xu2016/05
ER  -