Digital Empirical Methods for Cartel and Corruption Screening in Procurement

Course Overview

Recent advancements in digital empirical techniques enable us to detect cartels by analyzing market data and bidding patterns for signs of collusion. This method of cartel screening is particularly effective, as collusion directly impacts pricing and the bidding process, allowing for its detection through data analysis.

In this course, we will explore the latest developments in identifying collusion within procurement, where bidding rings are common. Public procurement typically accounts for approximately 12% of the national GDP, making cartel detection crucial. Moreover, with the digitalization of procurement processes, large databases are now readily accessible for analysis.

Competitive tendering, especially through auctions, is the preferred procurement method for many governments. Consequently, the efficiency of public spending is closely linked to the effectiveness of these procurement auctions, and collusion is arguably one of the most important obstacles to achieving efficiency. We focus on tools that help us to shed light on when, where, and for how long collusion is likely to have taken place. Finally, we will also analyze how to detect corruption in procurement processes.

Public procurement processes are vulnerable to corruption which generates sizable costs for public administrations: higher expenses, lower quality of goods, services, and works, inefficient allocations, distortion of competition, etc. In the course, we will review the ways in which corruption can take place in procurement and how we can use data analysis for detecting corruption.

We hope that the material covered in class will be of practical use to economists working in competition agencies, procurement agencies as well as those in auditing and compliance functions within firms.