Anti-corruption in Aid-funded Procurement: Whacking the Mole is Not Enough
GI-ACE researchers Liz Dávid-Barrett and Mihály Fazekas use big data analysis from…
Building on Phase 1 findings, this project digs deeper into the impact of changes in sociopolitical contexts by focusing on recipient-country regulatory frameworks and their interactions with donor regulations.
To learn more about this project, contact Principal Investigator Liz Dávid-Barrett.
This project is a continuation of one in which an innovative methodology was developed for analysing big data from major aid agencies to calculate indicators of corruption risk in aid-funded procurement. This methodology was employed to explore how the type and structure of corruption risks were affected by the institutional control mechanisms employed by donors and the sociopolitical context in recipient countries. Results showed that both factors affect corruption risks and that they interact.
This project extends the large-scale database developed in the initial project to national procurement data from 10 countries. This new database covers developing countries, such as Chile, India, Indonesia, and Mexico, while also including developed economies as comparators, such as Spain and the United Kingdom. The dataset contains more than 6 million contracts, during the period from 2010 to 2018. For some countries where data is of poorer quality, the focus will be more on qualitative and impacts aspects, promoting the improvement of data infrastructure and empowering local users to collect and analyse data through a software tool. In this way, the potential for methodological innovation is maximised by continuing to work with advanced datasets while also promoting the benefits of such analysis as far as possible to other countries that would benefit from using these methods in the medium term.
Public procurement accounts for around 50 percent of public spending in developing countries (World Bank 2015), and is the spending channel for a significant share of international development aid. Yet it is an area that is highly prone to corruption. Better understanding of how procurement procedures are manipulated and which interventions are most effective in curbing corruption in procurement is critical to combating corruption, as well as to saving public money, ensuring better provision of public goods, and building confidence in markets.
This project takes a two-tiered approach to extending the existing database:
A user-friendly interface for analysing the freely available data resulting from this project will be rolled out to a wide range of users, including in-country civil society activists, law enforcement officials, and anticorruption agencies.
International Donors
The research team engaged heavily with donors throughout the research, e.g., presenting the methods and findings at internal workshops with the Foreign, Commonwealth, and Development Office (FCDO) (formerly the Department of International Development (DFID)), the World Bank, and the Inter-American Development Bank (IDB), to inform their practices and rules about disbursing aid and monitoring procurement and to provide evidence to support their advocacy work with national governments, so they could collect and publish better quality procurement data and introduce better monitoring systems.
The work fundamentally changed the approach of the World Bank, particularly its Solutions and Innovations in Procurement (SIP) team, which works to identify risks in Bank-financed contracts and to assist governments in improving their own risk management. The team also worked with some World Bank country offices to build awareness of the potential of big data analytics, eg, in August 2017, Sussex research team co-organised an event with the Bank’s country office in Dar es Salaam, the Tanzanian Public Procurement Regulatory Authority (PPRA), and the Tanzanian Prevention and Combatting of Corruption Board.
National Governments
The research team also worked directly with public procurement regulators in two countries, Jamaica and Uganda, to develop online tools to assist their work. These interactive portals allow the regulators (Integrity Commission of Jamaica (ICJ) and Ugandan Public Procurement and Disposal of Assets Authority (PPDA)) to analyse their own procurement data, helping them to spot systemic corruption risks as well as high-risk individual transactions, hence informing policy change and investigation of cases.
Civil Society
The team also worked with the African Maths Initiative (AMI), a Kenya-based non-governmental organisation that works on improving maths education in Africa, to incorporate the red flags methodology into their open-source, user-friendly software package, R-Instat (a front-end to R). The team also worked with AMI to organise workshops for maths students, civil society activists, and researchers in Tanzania (March 2017), Ghana (May 2018), and Uganda (October 2018).
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