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Uncovering High-Level Corruption: Cross-National Objective Corruption Risk Indicators Using Public Procurement Data

Published online by Cambridge University Press:  24 August 2017

Mihály Fazekas  and
Gábor Kocsis
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Abstract

Measuring high-level corruption is subject to extensive scholarly and policy interest, which has achieved moderate progress in the last decade. This article develops two objective proxy measures of high-level corruption in public procurement: single bidding in competitive markets and a composite score of tendering ‘red flags’. Using official government data on 2.8 million contracts in twenty-eight European countries in 2009–14, we directly operationalize a common definition of corruption: unjustified restriction of access to public contracts to favour a selected bidder. Corruption indicators are calculated at the contract level, but produce aggregate indices consistent with well-established country-level indicators, and are also validated by micro-level tests. Data are published at http://digiwhist.eu/resources/data/.

Keywords

European Unioncorruptionmeasurementpublic procurementCRI
Type
Articles
Information
British Journal of Political Science , Volume 50 , Issue 1 , January 2020 , pp. 155 - 164
Copyright
© Cambridge University Press 2017 

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Footnotes

*

Department of Sociology, University of Cambridge (email: [email protected]); Government Transparency Institute (email: [email protected]). The authors would like to express their gratitude to generous funding from the European Union 7th Framework program (grant title: ANTICORRP; grant agreement no: 290529) and the Dutch Presidency of the European Union (project title: Public Integrity and Trust in Europe). They also thank the anonymous reviewers and numerous people commenting on earlier drafts of this article and database, in particular, Alina Mungiu-Pippidi, István János Tóth, Carl Dahström, Johannes Wachs, Luciana Cingolani, Nicholas Charron and Viktor Lapuente. Replication data sets are available in Harvard Dataverse at: https://dx.doi.org/doi:10.7910/DVN/6XYZOD and online appendices are available at https://doi.org/10.1017/S0007123417000461.

References

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Supplementary material: Link

Fazekas and Kocsis Dataset

Dataset

https://dx.doi.org/10.7910/DVN/6XYZOD
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Supplementary material: PDF

Fazekas and Kocsis supplementary material

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