We develop a fully nonparametric identification framework and a test of collusion in ascending bid auctions. Assuming efficient collusion, we show that the underlying distributions of values can be identified despite collusive behaviour when there is at least one bidder outside the cartel. We propose a nonparametric estimation procedure for the distributions of values and a bootstrap stochastic dominance test of the null hypothesis of competitive behaviour against the alternative of collusion. Our framework allows for asymmetric bidders, and the test can be performed on individual bidders. The test is applied to the Guaranteed Investment Certificate auctions conducted over the Internet. There have been allegations of collusion in this market. Our test, however, does not uncover collusion for the auctions conducted over the Internet. A plausible explanation of this is that the auction design involved very limited information disclosure.