Chinese Infrastructure in Africa
They are all first authors.
- DOI
- 10.2991/assehr.k.220401.083How to use a DOI?
- Keywords
- Chinese infrastructure; Africa
- Abstract
In the data analysis part, we first divide the data into transportation project variables, such as transportation services and space transportation, and post and telecommunications project variables, such as computers, communications, and other services. When conducting principal component analysis on the two types of variables by wind, we selected two principal components with 80% characteristics of the original variables, namely, aviation and port transportation project variables and transportation service import ratio variables. New variables replace transportation project variables. In addition, for post and telecommunications variables, we selected two principal components with 96.8% characteristics of the original variables as new variables, namely: Post and telecommunications variables as the proportion of computer communications in commercial services and the proportion of computer communications in the import and export volume of services. The variable in this way is used to replace the post and telecommunications variables. As part of building the model, we built a linear regression model based on the standardized GDP data and the four principal components. We chose to use the linear regression model because of the strong linear correlation between the variables, and the correlation coefficient R reached 0.827. In addition, from the ANOVA results, it can be found that the F value of the fitted linear model is 7.582, indicating that the linear regression model should be used to fit the variables because the test result is significant. We can know that the four variables have a significant impact on GDP through the regression parameters of the linear regression model. At this time, we constructed a linear regression model. Other variables also have a stimulating effect on GDP, and transportation projects composed of aviation and ports have the strongest stimulating effect on GDP. With the increase in infrastructure, South Africa’s GDP also means an improvement in living standards.
- Copyright
- © 2022 The Authors. Published by Atlantis Press SARL.
- Open Access
- This is an open access article distributed under the CC BY-NC 4.0 license.
Cite this article
TY - CONF AU - Haixuan Yu AU - Hui Yuan AU - Yi Wang PY - 2022 DA - 2022/04/08 TI - Chinese Infrastructure in Africa BT - Proceedings of the 2022 International Conference on Social Sciences and Humanities and Arts (SSHA 2022) PB - Atlantis Press SP - 439 EP - 448 SN - 2352-5398 UR - https://doi.org/10.2991/assehr.k.220401.083 DO - 10.2991/assehr.k.220401.083 ID - Yu2022 ER -