What are the conservation impacts of Chinese development activities in ecological hotspots? We generate and sub-nationally geo-reference a dataset of official Chinese development activities implemented between 2000 and 2014 in the Tropical Andes, the Great Lakes region of Africa, and the Mekong Delta. We then merge these project data with a long series of high-resolution satellite data in order to evaluate their impacts on forest cover. A difference-in-differences estimation strategy is used to identify changes in tree cover that have resulted from exposure to Chinese-funded infrastructure projects in Cambodia and Tanzania. We find that in Cambodia, these projects slowed forest loss, while Tanzania saw faster rates of forest loss in areas near active projects. However, these average results mask heterogeneous treatment effects across different types of forest governance regimes. In Cambodia, where large tracts of forested land – including concessions and plantations – have been granted to natural resource sector investors and the enforcement of environmental laws and regulations is exceptionally weak, we find that standing forests in plantation areas were negatively impacted by nearby Chinese-funded infrastructure projects. In Tanzania, where there is a minimally viable protected areas network, we find that areas under formal protection experienced little or no deforestation from these Chinese-funded projects. These effects hold even after we account for economic development patterns, as proxied by nighttime lights. We conclude that Chinese-funded infrastructure projects need not lead to widespread environmental damage when nearby ecosystems are appropriately protected, and domestic environmental governance plays a crucial role in shaping forest cover outcomes.
Funding: The authors thank the John D. and Catherine T. MacArthur Foundation for the generous funding that made this study possible. This study was also indirectly made possible through a cooperative agreement (AID-OAA-A-12-00096) between USAID’s Global Development Lab and AidData at the College of William & Mary under the Higher Education Solutions Network (HESN) Program, as it supported the creation of a spatial data repository and extraction tool which we used to execute our data analysis.