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Stage: Phase 3
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Public procurement corruption risks: Harnessing Big Data for better fiscal governance and growth
(D323)
8
Vote Score
Submitted:
12/17/2019
Status: 
Top 4

The goal of the submission is to create a policy-oriented global intelligence tool by measuring public procurement corruption risks and their financial costs. Such an innovation can be achieved on the back of state-of-the-art research which has already gathered data on 40 million contracts from 47 countries, defined and validated corruption risk indicators, and estimated costs of corruption. The proposed project would bring all these results together and put them onto a dashboard and standardized dataset relevant for policy decisions in the IMF, the World Bank and other organisations.

The proposed dashboard and dataset would enable policy makers, first, to explore corruption risks in public procurement both on the macro and micro levels, for example looking at the risks of individual ministries over time. This analysis could identify hotspots of corruption risk where policy change is likely to achieve the biggest impact. Second, the project would allow policy makers to track the financial impacts and growth costs of corruption risks on the micro and macro levels. For example, overpricing in public infrastructure projects could be traced back to identified corruption risks. Third, policy scenario modelling could be done on the basis of the identified links between corruption risks and costs. For example, the financial benefits of decreasing single bidding could be predicted informing policy choice on how best to reduce budget deficits without compromising public service quality.

Expertise Required
We are seeking an IMF staff member who would champion our Big Data-driven global anticorruption analytical tool. We seek individuals as intellectual partners who have expertise in anticorruption and good governance. In addition, skills related to public procurement, government contracting, and public investment projects would be a great asset. Finally, a staff member who has in depth insights about IMF data systems and analytical tools would be a further great asset. 

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