Corruption in Public Procurement: Finding the Right Indicators

被引:0
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作者
Joras Ferwerda
Ioana Deleanu
Brigitte Unger
机构
[1] Utrecht University School of Economics,
[2] VU University Amsterdam,undefined
关键词
Corruption; Public procurement; Selection bias and econometrics; C31 (cross-sectional econometric model); K42 (illegal behaviour);
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摘要
Red flags are widely used to minimize the risk of various forms of economic misconduct, among which corruption in public procurement. Drawing on criminal investigations, the literature has developed several indicators of corruption in public procurements and has put them forward as viable risk indicators. But are they genuinely viable, if only corrupt procurements are analysed? Using a dataset of 192 public procurements — with 96 cases where corruption was detected and 96 cases where corruption was not detected — this paper addresses the identification of significant risk indicators of corruption. We find that only some indicators significantly relate to corruption and that eight of them (e.g. large tenders, lack of transparency and collusion of bidders) can best predict the occurrence of corruption in public procurements. With this paper we successfully tap into one of the most vulnerable areas of criminological research — selecting the right sample — and consequently, our results can help increase the detection of corruption, increase investigation effectiveness and minimize corruption opportunities.
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页码:245 / 267
页数:22
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