On February 20, Johannes Wachs gave us a fascinating talk about his main research focus: detecting corruption patterns in public auction data. His research has already gained some well-deserved attention and was presented on some of the great conferences contributing to network science (like NetSciX and ICCSS). Johannes’s lead question is the following: Can we identify patterns of corruption, cartel behavior and collusion on public auction markets, by looking at the bipartite networks of firms and contract issuers? Can we uncover universal patterns that are less case-specific and could help policy makers and anti-corruption agencies?
In his presentation Johannes discussed the difficulties of coming up with non-context-specific measures, and some of the indicators he uses, to detect suspicious market interactions (like the Corruption Risk index or CRI). He presented case studies from Hungary and the Czech Republic, with promising results. More specifically, one take-away was that high-risk edges are usually clustered: where you find corruption, it is likely to find more around it. We were introduced to the concept of nestedness which is a fascinating way of looking at networks, coming from ecology, and indeed it might prove to be useful in detecting corruption as well.
Towards the end of the presentation Johannes shifted his focus onto collusion and ways to design network measures that can potentially detect cartel behavior.
His current activity is gathering data from real ground-truth case studies from economics articles and working out which network features indicate/predict corruption and cartel behavior. We are looking forward to future updates on this captivating topic.
Written by Dávid Deritei