Deciding Between Competition and Collusion

TLDR

The authors develop a method to identify and test for bid rigging in procurement auctions, focusing on the identification problem within a general auction model with asymmetric bidders. They construct a general auction model, derive necessary and sufficient conditions for competitive bidding, elicit prior cost distributions from experts, apply Bayesian comparison of competitive versus collusive models, and test the approach on Midwest construction firm bidding data. The resulting techniques are computationally efficient, flexible, and can be implemented in standard statistical software.

Abstract

We develop an approach to identify and test for bid rigging in procurement auctions. First, we introduce a general auction model with asymmetric bidders. Second, we study the problem of identification in our model. We state a set of conditions that are both necessary and sufficient for a distribution of bids to be generated by a model with competitive bidding. Third, we discuss how to elicit a prior distribution over a firm's structural cost parameters from industry experts. Given this prior distribution, we use Bayes's theorem to compare competitive and collusive models of industry equilibrium. Finally, we apply our methodology to a data set of bidding by construction firms in the Midwest. The techniques we propose are not computationally demanding, use flexible functional forms, and can be programmed using most standard statistical packages.