Testing for collusion in asymmetric first-price auctions

This paper proposes a two step procedure to detect collusion in asymmetric first-price procurement (auctions). First, we use a reduced form test to short-list bidders whose bidding behavior is at-odds with competitive bidding. Second, we estimate the (latent) cost for these bidders under both competition and collusion setups. Since for the same bid the recovered cost must be smaller under collusion-as collusion increases the mark-up-than under competition, detecting collusion boils down to testing for first-order stochastic dominance, for which we use the classic Kolmogorov-Smirnov and Wilcoxon-Mann-Whitney tests. Our bootstrap based Monte Carlo experiments for asymmetric bidders confirm that the procedure has good power to detect collusion when there is collusion. We implement the tests for highway procurement data in California and conclude that there is no evidence of collusion even though the reduced form test supports collusion. This highlights potential pitfalls of inferring collusion based only on reduced form tests.

► We model collusion and competition in asymmetric first price procurement (auction). ► We propose a two steps procedure to detect collusion. ► Recovered cost must be smaller under collusion. We use KS and W-MW tests of FOSD. ► We conduct Monte Carlo simulations to asses the power of our tests. ► We apply the method on CalTrans procurement data and find no evidence of collusion.