Empirical Implementation of Nonparametric First-Price Auction Models

Monotonicity of the equilibrium bidding strategy is a key property of structural auction models. Traditional nonparametric estimators provide a flexible means of uncovering salient features of auction data, but do not formally impose the monotonicity assumption that is inherent in the models during estimation. Here, we develop a nonparametric estimator which imposes monotonicity. We accomplish this by employing the constrained weighted bootstrapping theory developed in the statistics literature.We further develop methods for automatic bandwidth selection. Finally, we discuss how to impose monotonicity in auctions with differing numbers of bidders, reserve prices, and auction-specific characteristics. Finite sample performance is examined using simulated data as well as experimental auction data.