Robust Inference in First-Price Auctions: Experimental Findings as Identifying Restrictions

51 Pages Posted: 11 Feb 2019 Last revised: 21 Feb 2019

See all articles by Serafin Grundl

Serafin Grundl

Board of Governors of the Federal Reserve System

Yu Zhu

Government of Canada - Bank of Canada

Date Written: 2019-02-07

Abstract

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 reserve price. These bounds are consistent with RNBNE and all models of overbidding and remain valid if different bidders employ different bidding strategies. We propose simple estimators and evaluate the validity of the bounds numerically and in experimental data.

Keywords: Experimental findings, First-price auction, Partial identification, Robust inference, Structural estimation

JEL Classification: C14, D44, C57

Suggested Citation

Grundl, Serafin and Zhu, Yu, Robust Inference in First-Price Auctions: Experimental Findings as Identifying Restrictions (2019-02-07). FEDS Working Paper No. 2019-006. Available at SSRN: https://ssrn.com/abstract=3331458 or http://dx.doi.org/10.17016/FEDS.2019.006

Serafin Grundl (Contact Author)

Board of Governors of the Federal Reserve System ( email )

20th Street and Constitution Avenue NW
Washington, DC 20551
United States

Yu Zhu

Government of Canada - Bank of Canada ( email )

234 Wellington Street
Ontario, Ottawa K1A 0G9
Canada

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