POPNET Connects with Yuliia Kazmina

POPNET Connects is the seminar series of the Population Scale Network Analysis (POPNET) platform. We invite everyone to join the seminar, connect with others and get involved in discussion. To join our seminars, please sign up for our mailing list.

Recorded: Tuesday 18 May 2021

Uncovering corruption risks in public procurement using big data: the case of Ukraine

Corruption, favoritism and lack of public accountability have long been a central topic in academic research and policy debates. This study focuses on the phenomenon of corruption in a bureaucratic context, in one of the most corruption-prone sectors – public procurement. In their attempts to fight institutionalized grand corruption, governments all over the world improve the regulatory frameworks to ensure transparent and efficient public procurement market. One of the recent developments in the field was a successful launch of the ProZorro public procurement platform in Ukraine that achieved recognition all over the world as one of the best procurement reforms. Despite the enormous effort invested in the development of the transparent and efficient public procurement platform, it is too early to conclude that ProZorro successfully eliminated corruption. Hence, this study sets out to precisely estimate the prevalence and distribution of corruption risks in ProZorro. Overall, we find that ProZorro faces issues related to the lack of competition such as a low number of suppliers and a high share of single bidding contracts in some of the procurement markets. To tackle these issues, we develop a risk assessment tool for policymakers that could signal higher corruption risks in tendering processes.

About Yuliia Kazmina

Yuliia Kazmina is a PhD Candidate at the POPNET project. She obtained a master’s degree in Economic Policy in Global Markets from the Central European University, Hungary.
Yuliia’s research interests concern the domain of computational social science and data-driven policymaking with a focus on network science approach. Previously Yuliia has been a data scientist at a think tank researching and advocating good governance and her policy projects focused on issues of transparency, corruption, and collusion in public funds as well as risks of organized crime.