Geolocated dataset of Chinese overseas development finance

Abstract

China is now the world’s largest source of bilateral development finance and will likely continue to play a prominent role in sovereign lending through its multi-billion-dollar Belt and Road Initiative. This paper introduces major methodological enhancements in tracking this finance: the use of an original application programming interface (API) to gathers news in multiple languages; double-verification of every record to ensure every finance commitment has been formalized; and visual geo-location to trace the precise footprint of every project. The resulting dataset enables economic, environmental, and social analyses with high-precision spatial accuracy, as well as spatiotemporal monitoring by project stakeholders and enhanced planning by project managers. It covers the years 2008–2019 to enable analysis before and after the announcement of the Belt and Road Initiative. It includes 862 finance commitments, 669 of which have geographic location, to 94 countries across the world.

Mapping the risks of China’s global coastal development to marine socio-ecological systems

“…The 114 Chinese DFI projects assessed in this study (those within 1 km of the coastline or a river within 100 km of the coastline) constitute one-fourth of the projects financed by the China Development Bank and Export-Import Bank of China between 2008-2019 that have been geolocated with high spatial precision 14 . However, it is likely that more coastal development projects have been financed that have yet to be mapped, as there are an additional 209 (31%) Chinese DFI loans where the location(s) of the projects have a spatial uncertainty of 25 km or more.…”

“…We obtained geolocated data for projects financed by China’s development finance institutions (DFIs)—the China Development Bank (CDB) and Export-Import Bank of China (CHEXIM)—from 2008 to 2019 from the Chinese Overseas Development Finance (CODF) database 47 . The CODF dataset contains 669 loans for projects represented as points (e.g.…”

“…structural complexes, reservoirs, extraction areas) of varying levels of spatial precision. We included projects where the exact location is known (precision = 1), as the remaining projects have a location uncertainty of 25 km or greater 14 . For each project included in the analysis, we expanded upon the existing sector classification to distinguish and group the most similar types of projects according to their potential impacts on marine systems.…”

“…The last decade has brought a boom in overseas financing for large-scale development, with Chinese development finance institutions (DFIs) emerging as the largest bilateral creditor of these development projects 12, 13 . The China Development Bank (CDB) and Export-Import Bank of China (CHEXIM), alone, have lent more than US$460 billion to low- and middle-income countries since 2008 for the development of roads, power plants, ports, and other infrastructure 14 . It is estimated that China is also the largest bilateral funder of coastal infrastructure overseas, surpassing Japan and multilateral DFIs, such as the Asian Development Bank and Inter-American Development Bank 15 .…”

“…We identified 114 DFI projects in 39 countries financed between 2008 and 2019 that may negatively impact marine socio-ecological systems, including ports, power plants, roads, and other facilities (Fig. 1a), representing one-fourth of all Chinese DFI projects that have been geolocated with the highest precision, and worth nearly $65 billion in finance commitments (7% of all commitments) since 2008 14 . For each different type of project, we estimated the distribution of exposure risks ( R E )—the likelihood that a given ocean cell may be exposed to a particular stressor—up to 100 km from the project site for 15 stressors, such as habitat loss, invasive species, and pollution from light, noise, and organic and inorganic chemicals.…”