EVENT:

On October 24th, 2017, the AidData-hosted event, Tyranny of Averages: Are we worsening inequality within countries?, brought together Amanda Glassman (CGD), Caroline Heider (World Bank), Selim Jahan (UNDP), Kevin Croke (World Bank), Bradley C. Parks (AidData) and Samantha Custer (AidData) for an engaging panel discussion on issues of inequality and aid targeting addressed by the report. Watch the recording or read a summary of the remarks.

Methodology

AidData's TUFF Methodology, Version 1.3

Date Published

Oct 9, 2017

Authors

Austin M. Strange, Mengfan Cheng, Brooke Russell, Siddhartha Ghose, and Bradley Parks

Publisher

Citation

Strange, Austin, Mengfan Cheng, Brooke Russell, Siddhartha Ghose, and Bradley Parks. 2017. AidData's Tracking Underreported Financial Flows (TUFF) Methodology, Version 1.3. Williamsburg, VA: AidData.

Update: A revised version of this paper has been published in Health Economics.

Methodology

AidData's TUFF Methodology, Version 1.3

Date Published

Oct 9, 2017

Authors

Austin M. Strange, Mengfan Cheng, Brooke Russell, Siddhartha Ghose, and Bradley Parks

Citation

Strange, Austin, Mengfan Cheng, Brooke Russell, Siddhartha Ghose, and Bradley Parks. 2017. AidData's Tracking Underreported Financial Flows (TUFF) Methodology, Version 1.3. Williamsburg, VA: AidData.

This codebook outlines the set of TUFF procedures that have been developed, tested, refined, and implemented by AidData staff and affiliated faculty at the College of William & Mary. We initially employed these methods to achieve a specific objective: documenting the known universe of officially financed Chinese projects in Africa (Strange et al. 2013, 2017). We have since then employed these methods to track Chinese official finance to five major world regions: Africa, the Middle East, Asia and the Pacific, Latin America and the Caribbean, and Central and Eastern Europe (Dreher et al. 2017). Additionally, other social scientists have adapted and applied the TUFF methodology to identify grants and loans from Gulf Cooperation Council (GCC) members (Minor et al. 2014), under-reported humanitarian assistance flows from traditional and non-traditional sources (Ghose 2017), foreign direct investment from Western and non-Western sources (Bunte et al. 2017), and pre-2000 foreign aid flows from China (Morgan and Zheng 2017). However, this codebook focuses specifically on TUFF data collection and quality assurance procedures to track Chinese official finance between 2000 and 2014.

Tags
Available on GeoQuery
TUFF
Geocoded
SDG Coded
Natural Resource Concessions
Survey Results
Metadata
Publication Date
Oct 2017
Starting Year:
2000
Ending Year:
2014
Number of Entries:
File Size:

AidData's Global Chinese Official Finance Dataset (Version 1.0) tracks the known universe of overseas Chinese official finance between 2000-2014, capturing 4,373 records totaling $354.4 billion. The data includes both Chinese aid and non-concessional official financing.

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