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Robust Inference in First-Price Auctions : Experimental Findings as Identifying Restrictions
In laboratory experiments bidding in first-price auctions is more aggressive than predicted by the risk-neutral Bayesian Nash Equilibrium (RNBNE) - a finding known as the overbidding puzzle. Several models have been proposed to explain the overbidding puzzle, but no canonical alternative to RNBNE has emerged, and RNBNE remains the basis of the structural auction literature. Instead of estimating a particular model of overbidding, we use the overbidding restriction itself for identification, which allows us to bound the valuation distribution, the seller's payoff function, and the optimal ...
Identification of First-Price Auctions With Biased Beliefs
This paper exploits variation in the number of bidders to separately identify the valuation distribution and the bidders' belief about the valuation distribution in first-price auctions with independent private values. Exploiting variation in auction volume the result is extended to environments with risk averse bidders. In an illustrative application we fail to reject the null hypothesis of correct beliefs.
Identification and Estimation of Risk Aversion in First Price Auctions With Unobserved Auction Heterogeneity
We extent the point-identification result in Guerre, Perrigne, and Vuong (2009) to environments with one-dimensional unobserved auction heterogeneity. In addition, we also show a robustness result for the case where the exclusion restriction used for point identification is violated: We provide conditions to ensure that the primitives recovered under the violated exclusion restriction still bound the true primitives in this case. We propose a new Sieve Maximum Likelihood Estimator, show its consistency and illustrate its finite sample performance in a Monte Carlo experiment. We investigate ...