  We use methods from network science to analyze corruption risk in a large
administrative dataset of over 4 million public procurement contracts from
European Union member states covering the years 2008-2016. By mapping
procurement markets as bipartite networks of issuers and winners of contracts
we can visualize and describe the distribution of corruption risk. We study the
structure of these networks in each member state, identify their cores and find
that highly centralized markets tend to have higher corruption risk. In all EU
countries we analyze, corruption risk is significantly clustered. However,
these risks are sometimes more prevalent in the core and sometimes in the
periphery of the market, depending on the country. This suggests that the same
level of corruption risk may have entirely different distributions. Our
framework is both diagnostic and prescriptive: it roots out where corruption is
likely to be prevalent in different markets and suggests that different
anti-corruption policies are needed in different countries.
