The econometrics of auctions with asymmetric anonymous bidders

Abstract

We consider standard auction models when bidders' identities are not observed by the econometrician. First, we adapt the definition of identifiability to a framework with anonymous bids and we explore the extent to which anonymity reduces the possibility to identify private value auction models. Second, in the asymmetric independent private value model which is nonparametrically identified, we generalize Guerre, Perrigne and Vuong's estimation procedure [Optimal Nonparametric Estimation of First-Price Auctions, Econometrica 68 (2000) 525-574] and study the asymptotic properties of our multi-step kernel-based estimator. Third a test for symmetry is proposed. Monte Carlo simulations illustrate the practical relevance of our estimation and testing procedures for small data sets.auctions ; nonparametric identification ; nonparametric estimation ; tests for symmetry ; unobserved heterogeneity ; anonymous bids ; uniform convergence rate