European Journal on Criminal Policy and Research

, Volume 22, Issue 3, pp 369–397 | Cite as

An Objective Corruption Risk Index Using Public Procurement Data

  • Mihály FazekasEmail author
  • István János Tóth
  • Lawrence Peter King


In order to address the lack of reliable indicators of corruption, this article develops a composite indicator of high-level institutionalised corruption through a novel ‘Big Data’ approach. Using publicly available electronic public procurement records in Hungary, we identify “red flags” in the public procurement process and link them to restricted competition and recurrent contract award to the same company. We use this method to create a corruption indicator at contract level that can be aggregated to the level of individual organisations, sectors, regions and countries. Because electronic public procurement data is available in virtually all developed countries from about the mid-2000s, this method can generate a corruption index based on objective data that is consistent over time and across countries. We demonstrate the validity of the corruption risk index by showing that firms with higher corruption risk score had relatively higher profitability, higher ratio of contract value to initial estimated price, greater likelihood of politicians managing or owning them and greater likelihood of registration in tax havens, than firms with lower scores on the index. In the conclusion we discuss the uses of this data for academic research, investigative journalists, civil society groups and small and medium business.


Grand corruption Hungary Indicator Public procurement 



The authors would like to express their gratitude for two EU funded projects at the Budapest Corvinus University (TAMOP 4.2.2.B and ANTICORRP (Grant agreement no: 290529)) even though they relied extensively on their voluntary contributions for realising this project. They would also like to express special thanks to colleagues at the Corruption Research Center Budapest working on the Hungarian public procurement database (MakAB), especially Kinga Csizmás, Ágnes Czibik, Zoltán Kelemen and Tamás Uhrin. Furthermore, we would like to thank the colleagues at the University of Cambridge, Hungarian Economic Association, and U4 Anti-Corruption Resource Center for their insightful comments on earlier drafts of this paper.

Supplementary material

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Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  1. 1.Department of SociologyUniversity of CambridgeCambridgeUK
  2. 2.Government Transparency InstituteBudapestHungary
  3. 3.Institute of EconomicsHungarian Academy of SciencesBudapestHungary

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