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Insights from the Field

Why measuring high-level corruption is tough — and this study might help.


corruption proxy
public procurement
Europe dataset
composite score
European Politics
BJPS
2 Stata files
2 datasets
Dataverse
Uncovering High-Level Corruption: Cross-national objective corruption risk indicators using public procurement data was authored by Mihaly Fazekas and Gabor Kocsis. It was published by Cambridge in BJPS in 2020.

Scholars and policymakers have long struggled with accurately gauging high-level corruption, despite some recent progress. This research introduces two novel objective indicators—single bidding in competitive markets—and a composite score of procurement 'red flags'—based on official government data from 2.8 million contracts across twenty-eight European countries between 2009 and 2014—to directly operationalize the concept that favors specific bidders without justification.

Data & Methods: Analyzing records from Europe-wide public tenders during a six-year period (2009-2014).

* Corruption Proxy #1: Single Bidding in Competitive Markets — Identifying contracts awarded via single bidding despite competition being available or expected.

* Corruption Proxy #2: Tender 'Red Flags' Composite Score — Systematically flagging indicators of potential corruption from tender documents and processes.

The findings demonstrate how these objective measures can capture country-level corruption trends while avoiding subjectivity. Using a news-style heading for clarity:

Key Findings & Validation:

* These indicators align well with established macro corruption assessments.

* They effectively identify micro-level instances of preferment without justification, providing strong empirical support.

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