Identification of auction models using order statistics

Auction data often contain information on only the most competitive bids as opposed to all bids. The usual measurement error approaches unobserved heterogeneity are inapplicable due dependence among order statistics. We bridge this gap by providing a set of positive identification results. First, we show that symmetric auctions with discrete identifiable using two consecutive statistics and an instrument. Second, extend results ascending unknown competition heterogeneity.