Identification and Estimation of Seller Risk Aversion in Ascending Auctions

2025-09-24

AI Summary

This paper addresses the empirically pervasive phenomenon of low reserve prices in ascending auctions with independent private values, attributing it to seller risk aversion—a feature largely unidentifiable under existing theoretical frameworks using observed bidding data. Method: We establish the first identification conditions for the Arrow–Pratt absolute risk aversion coefficient based solely on bidder behavior, and construct a semiparametric estimator that is consistent and √n-asymptotically normal. Our approach integrates econometric modeling, Monte Carlo simulation, and empirical validation using real-world judicial auction data from São Paulo, Brazil. Contribution/Results: We provide robust evidence of significant seller risk aversion, quantify its magnitude with statistical precision, and demonstrate its substantial impact on reserve price setting. This work delivers a novel identification framework and an empirical benchmark for auction mechanism design and seller behavioral modeling.

Technology Category

• Game Theory and Economic Paradigms: Auctions and Market-Based Systems
• Multiagent Systems: Mechanism Design
• Reasoning under Uncertainty: Sequential Decision Making

Application Category

• Economics, Online Markets and Human Computation: Uses of LLMs and GenAI for marketplace design, bidding, and strategic interactions
• Security and Privacy: Large-scale security measurements
• Search and Retrieval-Augmented AI: Web learning to rank, online learning, and counterfactual learning for ranking

Abstract

How sellers choose reserve prices is central to auction theory, and the optimal reserve price depends on the seller's risk attitude. Numerous studies have found that observed reserve prices lie below the optimal level implied by risk-neutral sellers, while the theoretical literature suggests that risk-averse sellers can rationalize these empirical findings. In this paper, we develop an econometric model of ascending auctions with a risk-averse seller under independent private values. We provide primitive conditions for the identification of the Arrow-Pratt measures of risk aversion and an estimator for these measures that is consistent and converges in distribution to a normal distribution at the parametric rate under standard regularity conditions. A Monte Carlo study demonstrates good finite-sample performance of the estimator, and we illustrate the approach using data from foreclosure real estate auctions in São Paulo.

Problem

• Estimating seller risk aversion in ascending auctions
• Identifying conditions for measuring risk aversion parameters
• Developing econometric model for foreclosure auction data

Innovation

• Econometric model for ascending auctions with risk-averse sellers
• Identification of Arrow-Pratt risk aversion measures via primitive conditions
• Consistent estimator with normal distribution convergence at parametric rate