Reproducibility package for Rigging The Scores: Corruption Through Scoring Rule Manipulation In Public Procurement Auctions

Public procurement is highly susceptible to corruption, especially in developing countries. Although open auctions are widely adopted to curb it, I document that corruption remains prevalent even within this procurement format. Procurement officers can collaborate with firms to manipulate scoring rules, ensuring predetermined winners, while corrupt firms submit non-competitive bids to meet minimum bidder requirements. Using extensive data from Chinese public procurement auctions, I introduce model-driven statistical tools to detect such corruption, identifying a corruption rate of 65%. A procurement expert audit survey confirms the tools’ reliability, with a 91% probability that experts recognize suspicious scoring rules when flagged. Firm-level analysis reveals that local, state-owned, and less productive firms are favored in corrupt auctions. Lastly, I explore policy implications. Analysis of the national anti-corruption campaign since 2012 suggests that general investigations may be insufficient to address deeply ingrained corrupt practices. Using counterfactuals based on an estimated structural model, I find that implementing anonymous call-for-tender evaluations could improve social welfare by 10% by eliminating suspicious rues and encouraging broader participation.