Identification and Inference in First-Price Auctions with Risk Averse Bidders and Selective Entry

75 Pages Posted: 15 Oct 2020 Last revised: 7 Jun 2023

See all articles by Xiaohong Chen

Xiaohong Chen

Yale University - Cowles Foundation

Matthew L. Gentry

Florida State University

Tong Li

Vanderbilt University

Jingfeng Lu

National University of Singapore (NUS) - Department of Economics

Multiple version iconThere are 2 versions of this paper

Date Written: May 28, 2023

Abstract

We study identification and inference in first-price auctions with risk averse bidders and selective entry, building on a flexible framework we call the Affiliated Signal with Risk Aversion (AS-RA) model with potentially non-binding reserve prices. Assuming either exogenous variation in the number of potential bidders (N) or a continuous instrument (z) shifting opportunity costs of entry, we provide a sharp characterization of the nonparametric restrictions implied by equilibrium bidding. This characterization implies that risk neutrality is nonparametrically testable. In addition, with sufficient variation in both N and z, the AS-RA model primitives are nonparametrically identified (up to a bounded constant) on their equilibrium domains. Finally, we explore new methods for inference in set-identified auction models based on Chen, Christensen, and Tamer (2018), as well as novel computational strategies to implement these. Simulation studies reveal good finite-sample performance of our inference methods, which can readily be adapted to other set-identified auction models.

Keywords: Auctions, entry, risk aversion, identification, set inference, MPEC, profile likelihood ratio, nonregular models.

JEL Classification: D44, C57

Suggested Citation

Chen, Xiaohong and Gentry, Matthew L. and Li, Tong and Lu, Jingfeng, Identification and Inference in First-Price Auctions with Risk Averse Bidders and Selective Entry (May 28, 2023). Available at SSRN: https://ssrn.com/abstract=3681530 or http://dx.doi.org/10.2139/ssrn.3681530

Xiaohong Chen

Yale University - Cowles Foundation ( email )

Box 208281
New Haven, CT 06520-8281
United States

Matthew L. Gentry (Contact Author)

Florida State University ( email )

Tallahassee, FL 30306-2180
United States

HOME PAGE: http://www.matthewgentry.net

Tong Li

Vanderbilt University ( email )

2301 Vanderbilt Place
Nashville, TN 37240
United States

Jingfeng Lu

National University of Singapore (NUS) - Department of Economics ( email )

1 Arts Link, AS2 #06-02
Singapore 117570, Singapore 119077
Singapore

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