Identification in Auctions With Selective Entry

S-Tier
Journal: Econometrica
Year: 2014
Volume: 82
Issue: 1
Pages: 315-344

Authors (2)

Matthew Gentry (not in RePEc) Tong Li (Vanderbilt University)

Score contribution per author:

4.022 = (α=2.01 / 2 authors) × 4.0x S-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

This paper considers nonparametric identification of a two‐stage entry and bidding game we call the Affiliated‐Signal (AS) model. This model assumes that potential bidders have private values, observe signals of their values prior to entry, and then choose whether to undertake a costly entry process, but imposes only minimal structure on the relationship between signals and values. It thereby nests a wide range of entry processes, including in particular the Samuelson (1985) and Levin and Smith (1994) models as special cases. Working within the AS model, we map variation in factors affecting entry behavior (potential competition or entry costs) into identified bounds on model fundamentals. These bounds are constructive, collapse to point identification when available entry variation is continuous, and can readily be refined to produce the pointwise sharp identified set. We then extend our core results to accommodate nonseparable unobserved auction‐level heterogeneity and potential endogeneity of entry shifters, thereby establishing a formal identification framework for structural analysis of auctions with selective entry.

Technical Details

RePEc Handle
repec:wly:emetrp:v:82:y:2014:i:1:p:315-344
Journal Field
General
Author Count
2
Added to Database
2026-01-25