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Testing Corruption Indicators: Statistical Analysis of a Hungarian Cartel

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The study analyzes the reliability of corruption risk indicators using Hungarian public procurement data, specifically focusing on EU-funded contracts associated with a cartel case revealed by the Hungarian Competition Authority (HCA) in 2016. The investigation aims to determine whether corruption risk indicators for public procurement contracts related to the identified cartel case (214 contracts) are significantly higher than those for similar contracts in different submarkets. The analysis utilizes data from the Corruption Research Center Budapest database, encompassing Hungarian public procurement information from January 1998 to July 2023, totaling around 340,000 contracts or contract lots. Since the cartel case detected by the HCA was part of the EU-funded KEOP program, covering contracts from 2015 to 2016 in the manufacturing sector, our analysis is limited to EU-subsidized contracts in the manufacturing sector awarded in 2015 and 2016.

Our findings highlight that the corruption risk indicator (single bid), endorsed by the EU Single Market Scoreboard, provides valuable insights for identifying anomalies in public procurement. For the identified cartel contracts, the likelihood of a contract being awarded to a single bidder (without competition) was significantly higher compared to contracts not associated with a cartel case. A similarly robust outcome was observed for the indicator measuring contracts concluded with more than three bids. The probability of contracts with more than three bids was significantly lower for cartel contracts than for others.

The indicator assessing the occurrence of rounded winner prices yielded a significant result for one of the three subsamples, and in another, it was significant only at the 10% level. These results affirm the significance of conducting statistical analyses on contracts and the calculation, as well as in-depth examination, of corruption indicators (single bid, more than three bids, and rounded winner price) to identify anomalies in public procurement.

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2024

Feb

21

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