To save content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about saving content to .
To save content items to your Kindle, first ensure firstname.lastname@example.org
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about saving to your Kindle.
Note you can select to save to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
Social science research on the aims and impacts of Chinese development finance remains in its infancy because Beijing shrouds its overseas portfolio of grants and loans in secrecy. This chapter introduces the Tracking Underreported Financial Flows (TUFF) methodology that the authors have developed to assemble a comprehensive dataset of Chinese aid and debt-financed development projects around the globe. It also provides an overview of previous attempts to quantify Chinese development finance, and explains how the authors’ methods and data are different from those of others. This chapter also tests whether an alternative approach—field-based data collection—might yield more useful and reliable re- sults. Drawing upon evidence from a “ground-truthing” exercise in Uganda and South Africa, the authors demonstrate that field-based and TUFF-based data collection methods produce similar results. However, the TUFF methodology is less vulnerable to detection bias and more readily scalable than field-based data collection.
Email your librarian or administrator to recommend adding this to your organisation's collection.