Erschienen in:Questioni di Economia e Finanza, Occasional Papers ; No. 544, 2020
Umfang:
1 Online-Ressource (36 p)
Sprache:
Englisch
Entstehung:
Anmerkungen:
In: Questioni di Economia e Finanza, Occasional Papers No. 544, 2020
Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments February 1, 2020 erstellt
Beschreibung:
This paper contributes to the analysis of quantitative indicators (i.e., red flags or screens) to detect corruption in public procurement. Expanding the set of commonly discussed indicators in the literature to new ones derived from the operating practices of police forces and the judiciary, this paper verifies the presence of these red flags in a sample of Italian awarding procedures for roadwork contracts in the period 2009-2015. Then, it validates the efficacy of the indicators through measures of direct corruption risks (judiciary cases and police investigations for corruption-related crimes) and indirect corruption risks (delays and cost overruns). From a policy perspective, our analysis shows that the most effective red flags in detecting corruption risks are those related to discretionary mechanisms for selecting private contractors (such as the most economically advantageous offer or negotiated procedures), compliance with the minimum time limit for the submission of tenders and subcontracting. Moreover, our analysis suggests that greater standardization in the call for tender documents can contribute to reducing corruption risks. From a methodological point of view, the paper highlights the relevance of prediction approaches based on machine learning methods (especially the random forests algorithm) for validating a large set of indicators