Identification and Estimation of a Dynamic Multi-Object Auction Model

In this paper I develop an empirical model of bidding and entry behaviour in re- peated simultaneous first-price auctions. The model is motivated by the fact that auctions rarely take place in isolation; they are often repeated over time, and multi- ple heterogeneous lots are regularly auctioned simultaneously. Incorrect modelling of bidders as myopic or as having additive preferences over lots can lead to inaccurate counterfactuals and welfare conclusions. I prove non-parametric identification of primi- tives in this model, and introduce a computationally feasible procedure to estimate this type of game.