Data update of World Bank, IADB, and EuropeAid datasets on development aid funded contracts and projects

The DFID-funded project “Curbing Corruption in Government Contracting” is releasing an update on the datasets collected on development projects, public tenders, and contracts for three major donor agencies: the World Bank, the Inter-American Development Bank (IADB), and EuropeAid. The datasets not only republish structured data gathered from official source websites, but also contain corruption risk red flags developed by the research team.

About the project

The project entitled “Curbing Corruption in Government Contracting” analyses how procurement can be manipulated for corrupt ends using a prize-winning ‘red flags’ methodology developed by Mihály Fazekas. We collect datasets of procurement tenders and contracts, with a range of variables that indicate corruption risk, and analyse the data to identify suspicious patterns and trends, by procuring entity, supplier, and over time.

Regarding procurement that uses funds from development aid donors, pressure to ensure accountability and transparency in the allocation of funds has been growing. Yet, donors have only blunt tools available to monitor whether recipient governments use aid for agreed purposes. To address this problem, we developed an innovative methodology for analysing big data from major aid agencies to calculate more accurate and targeted indicators of corruption in aid-funded procurement. We employed these indicators to explore how the risks of corruption in aid allocation are affected by (1) different institutional control mechanisms and (2) the socio-political context in recipient-countries. Our findings hopefully contribute to guiding donor agencies in the future development of more efficient delivery and monitoring mechanisms, while our data analysis tools can be incorporated into donors’ evaluation frameworks on a real-time basis.

Data and documentation

Find the first iteration of these datasets and accompanying source data and documentation here.

All data and codes on this page are licensed under Creative Commons BY-NC-SA 4.0.