Geocoded China Data

AidData's Geocoded Global Chinese Official Finance Dataset, Version 1.1.1

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Summary

This dataset geolocates Chinese Government-financed projects that were implemented between 2000-2014. It captures 3,485 projects worth $273.6 billion in total official financing. The dataset includes both Chinese aid and non-concessional official financing.

To access the pre-merged version of this data used in AidData Working Paper #64, please click here (download starts immediately). This data is also available in our spatial data extraction tool, GeoQuery, for users to make custom merges with other social, economic and environmental datasets at subnational scales.

Official Citation

Bluhm, R., Dreher, A., Fuchs, A., Parks, B. C., Strange, A., & Tierney, M.J. (2018). Connective Financing: Chinese Infrastructure Projects and the Diffusion of Economic Activity in Developing Countries. ​AidData Working Paper #64. Williamsburg, VA: AidData at William & Mary.

Dreher, A., Fuchs, A., Parks, B. C., Strange, A., & Tierney, M.J. (Forthcoming). Banking on Beijing: The Aims and Impacts of China’s Overseas Development Program. Cambridge, UK: Cambridge University Press.

AidData Research and Evaluation Unit. (2017). Geocoding Methodology, Version 2.0. Williamsburg, VA: AidData at William & Mary. https://www.aiddata.org/publications/geocoding-methodology-version-2-0

*Please note: All three works count as the official citation for this dataset.

Date Published

September 11, 2018

Full Description

After releasing the first-ever global dataset of Chinese development projects in October of 2017, AidData embarked on a far-reaching effort to assign precise geographic coordinates to those projects. The result of thousands of hours of geocoding by dozens of research assistants is a first-of-its-kind geocoded dataset that pinpoints 3,485 Chinese development projects worth USD $273.6 billion that were implemented in 6,190 locations in 138 countries over a fifteen-year period (2000-2014). This dataset only includes projects that were both recommended for research in the original dataset and projects whose status was completed or implemented.

The data package available for download at the link above includes the following files:  

  • all_flow_classes.csv
  • oda-like_flows.csv
  • oof-like_flows.csv
  • vague_flows.csv
  • project_descriptions_and_sources.csv

Each row in these datasets contain a project location. To make it easier for users to distinguish between projects that do or do not meet the strict definition of “aid,” these files provide project location records that have been pre-filtered according to the “flow_class” variable (ODA-like, OOF-like, or Vague OF). Descriptions of these flow classes and their meanings are included in the accompanying ReadMe.

Funding: This research was made possible with generous financial support from the John D. and Catherine T. MacArthur Foundation, Humanity United, the William and Flora Hewlett Foundation, the Academic Research Fund of Singapore’s Ministry of Education, the United Nations University World Institute for Development Economics Research (UNU-WIDER), the German Research Foundation (DFG), and the College of William and Mary.