Chapters, articles

Using Beneficial Ownership Data for Systematic Risk Assessment in Public procurement. The Example of 6 European Countries.

Tello Arista, I., Fazekas, M. & Volkotrub, A. Using Beneficial Ownership Data for Systematic Risk Assessment in Public procurement. The Example of 6 European Countries. Eur J Crim Policy Res (2026). https://doi.org/10.1007/s10610-025-09654-9

Despite the considerable interest, there is little evidence on the suitability of beneficial ownership data for systematic corruption risk assessment. This paper aims to validate common beneficial ownership risk indicators for proxying public procurement corruption. By implication, it offers practical insights for research, policy, and investigations. It also …

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Revisiting the Link between Politicians’ Salaries and Corruption.

Klasnja, Marko; Fazekas, Mihály & Al-Shaibani, Ahmed (2026) Revisiting the Link between Politicians’ Salaries and Corruption. British Journal of Political Science. 56:e20. doi:10.1017/S0007123426101392

It has long been argued that paying politicians higher salaries should help decrease corruption. However, the empirical evidence is mixed, partly due to the large variation in contexts, research designs, conceptual definitions and measures of corruption, and the predominance of case studies with potentially limited generalizability. To alleviate these challenges, we evaluate uniformly defined and validated corruption …

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Public procurement cartels: A large-sample testing of screens using machine learning

Fazekas, Mihály; Tóth, Bence; Wachs, Johannes & Abdou, Aly (2026). Public procurement cartels: A large-sample testing of screens using machine learning. International Journal of Industrial Organization. 104.

Due to the high budgetary costs of public procurement cartels, it is crucial to measure and understand them. The literature developed screens that work well for selected cartel types and with high quality data, but it didn’t produce generalisable knowledge supporting policy and law enforcement on typically available datasets. We simultaneously measure multiple …

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Data Science Meets Political Economy: Applications to Legislative Favouritism around the World

Benoit, Cyril; Brenner, Dominik & Fazekas, Mihály (2025) Data Science Meets Political Economy: Applications to Legislative Favouritism around the World. In Sarah Giest, Bram Klievink, Alex Ingrams, and Matt Young (eds.): Handbook of Governance and Data Science. Edward Elgar, Cheltenham, UK. Chapter 3.

Merging governance studies and data science, this Handbook provides a comprehensive overview of how these fields interact with each other, driving a greater understanding of and guidance for the data-driven transformation of government.

Bringing together contributions from …

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The impact of emergencies on corruption risks: Italian natural disasters and public procurement

Fazekas, Mihály; Nishchal, Shrey & Soreide, Tina (2025) The impact of emergencies on corruption risks: Italian natural disasters and public procurement. Regulation & Governance.

 

Theory and case studies suggest that emergencies and disasters increase corruption, especially in public procurement, hampering relief and reconstruction efforts. Despite a growing interest in the topic, including in research, there is still little systematic evidence about these effects, their structure and trajectories. We set out to investigate the medium-term impact of disasters on corruption …

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The political economy of open contracting reforms in low‐ and middle‐income countries

Adam, I., Dávid‐Barrett, E., & Fazekas, M. (2024). The political economy of open contracting reforms in low‐ and middle‐income countries. Governance, 1–20. https://doi.org/10.1111/gove.12897

Transparency reforms make government contracting more open and amenable to public scrutiny, helping to improve public spending efficiency. But they are also politically sensitive, complex and highly technical, which makes them especially difficult to implement if state capacity is weak. Our research on nine low- and middle-income countries in Africa and Asia systematically assesses progress in improving …

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Predicting pharmaceutical prices. Advances based on purchase-level data and machine learning

Mihály Fazekas, Zdravko Veljanov and Alexandre Borges de Oliveira (2024) Predicting pharmaceutical prices. Advances based on purchase-level data and machine learning. BMC Public Health 24. Article 1888. 

Background

Increased costs in the health sector have put considerable strain on the public budgets allocated to pharmaceutical purchases. Faced with such pressures amplified by financial crises and pandemics, national purchasing authorities are presented with a puzzle: how to procure pharmaceuticals of the highest quality for the lowest price. The literature explored a …

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Global Contract-level Public Procurement Dataset

Mihály Fazekas, Bence Toth, Aly Abdou and Ahmed Al-Shaibani (2024) Global Contract-level Public Procurement Dataset. Data in Brief. 2024. april.

One-third of total government spending across the globe goes to public procurement, amounting to about 10 trillion dollars a year. Despite its vast size and crucial importance for economic and political developments, there is a lack of globally comparable data on contract awards and tenders run. To fill this gap, this article introduces the Global Public Procurement Dataset (GPPD). Using …

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Collusion Risk in Corporate Networks

Isabela Villamil, János Kertész, and Mihály Fazekas (2024) Collusion Risk in Corporate Networks. Scientific Reports, 14.

Collusion among economic operators increases prices, reduces product quality, and hinders innovation. Structural links can affect the incentive and ability of firms to behave competitively by facilitating collusion. We use a network-based approach to study the relationship between ownership links and bidding behavior in procurement markets. We build temporal multiplex networks based on firms’ ownership and co-bidding ties to find network measures that may …

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Data Analytics for Anti-Corruption in Public Procurement

Poltoratskaia, Viktoriia & Fazekas, Mihály (2024) Data Analytics for Anti-Corruption in Public Procurement. In Sope Williams and Jessica Tillipman (eds.) Routledge Handbook of Public Procurement Corruption. Chapter 4. Routledge.

This chapter describes and analyses the ways in which data analytics can be used for countering corruption in public procurement. It also discusses the main challenges for effective data-driven anti corruption in public procurement. We propose a simple conceptual framework, which distinguishes petty and grand corruption. Depending on the type of …

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