Background
Along with China’s rise as a global superpower in recent decades, the Chinese government has expanded its vision to territories beyond their national borders and into the world. Indeed, “since the turn of the century, China has doled out nearly as much aid as the United States, even if it has kept that financing low-key and hard to track.” (Allen-Ebrahimian, 2017) Furthermore, after the current President of China, Jinping Xi, came to power in 2013, he subsequently unrolled the “Belt and Road” initiative that was nominally supposed to help develop global infrastructure, but rumors circulated that these projects were in reality a neo-colonial effort to dominate resources and grow China’s global influence and power. (Ani, 2022)
In my report, I wish to use AidData’s incredibly comprehensive dataset on Chinese global development projects from 2000 to 2017 to get a glimpse of the nature and the intentions behind these “foreign aid” projects. This dataset captures “vast amounts of unstructured, open-source, project-level information” about 13,427 projects that are worth $843 billion across 145 countries, and includes variables related to debt conditions, transactional details, and project implementation. As the scope of this dataset is large, this lab report will only serve as an exploratory study of my final project. Research questions of interest include: the destination of these funds, the length of the projects, and the amount of money spent on these projects.
Materials
Dataset: Global Chinese Development Finance Dataset, Version 2.0 – AidData
Tools: Excel (data analysis), Tableau (data visualization)
Methods
Viz #1: First, I would like to understand which countries received the most amounts of money from China and if there are any continental trends in these countries. As 139 projects only have a continent designation instead of a country one (these projects contains the word “regional”, as in “Africa, regional”), I filtered these out. Then, I aggregated the “Amount (Constant US2017)” field by their sum (since I’m interested in the total value committed by China), which is the inflation-adjusted monetary value of the official commitment issued by the Chinese funding agency. Then I color-coded them by their continents, which is recorded in the “Recipient Region” field.
Viz#2: Second, I would like to understand the average project length and if they have grown longer or shorter with time. In order to do this, I took two fields, “Commitment Year” and “Completion Year”, removed their null values, and added a new calculated field that took the difference of the two called “Project Length”. Then, I plotted the average of these differences against the “Commitment Year” as a time variable.
Viz #3: Lastly, I tried to understand if there are any meaningful relationships between average project length and the amount spent on each project across the years, with the latter being a possible indicator of project size. To do this, I chose a dual line chart and plotted the average of the “Project Length” field and the “Amount (Constant US2017)” variable against the “Commitment Year”.
Results
Viz #1: The top 20 countries that received the most funding are listed in this bar chart. A quick glance of this first visualization shows that Russia received the most amount of project development funds in total from 2000-2017, at ~$183 billion, followed by Venezuela at ~$173 billion. One can also see that among these top 20 countries, 7 are from Asia, 5 are from Africa, 4 are from the Americas, 3 are from Europe (all from Eastern Europe), and only 1 is from the Middle East (Iran).
Viz #2: This plot shows that the average project length has decreased through time, with 2017 being the year with the lowest average project length, at just about half a year per project. Interestingly enough, this downward trend has exacerbated since the unrolling of the Belt and Road initiative, leading one to wonder if this was a reflection of the decreasing quality of the projects instead of its size.
Viz #3: Interestingly enough, the dual line chart shows that as the money spent on global projects increased through the years, the average time spent on each project actually decreased, with 2013 – the unrolling of the “Belt and Road” initiative – as a dividing point.
Reflection
This lab report served to answer some of my fundamental questions about the dataset, including who’s getting the money, the general trend of money CCP spent on foreign investment and how much time was spent on each project in average. The fact that the project length went down was very interesting and should be further explored in the final project: was it because there were more smaller-scaled projects? Or was it because the government was trying to rush the projects along? Furthermore, I would also like to understand the sectors in which the money was invested, as well as any debt conditions that came with such loans.
References
Allen-Ebrahimian, Bethany. (2017, October 11). “Russia is the Biggest Recipient of Chinese Foreign Aid.” Foreign Policy. https://foreignpolicy.com/2017/10/11/russia-is-the-biggest-recipient-of-chinese-foreign-aid-north-korea/
Ani. (2022, March 19). “China Facing Criticism in Africa for ‘Shoddy’ Quality Projects.” The Print. https://theprint.in/world/china-facing-criticism-in-africa-for-shoddy-quality-projects/880046/