Sample Spacings for Identification: The Case of English Auctions With Absentee Bidding

Abstract

This paper presents new nonparametric identification results for ascending auctions with independent private values. The standard identification approach is infeasible in the motivating setting, because absentee bidding conceals the number of bidders. I exploit insights from the statistics literature about the stochastic ordering of adjacent sample spacings. I show how to use such sample spacings to set-identify structural features, using an incomplete model and without knowing all highest bids or the number of bidders. Applying the sample spacing method to a small sample of wine auctions, I show that it identifies informative bounds on policy-relevant counterfactuals. It turns out that Sotheby's restricts full exploitation of the exclusion principle of optimal reserve prices. As a result, sellers set sub-optimally low reserve prices. They benefit up to 13% from adopting a common reserve price rule equal to 120% of the Wine Department's pre-auction value estimate.

Keywords: Nonparametric set-identification, English auctions, Order statistics, Shape restrictions

JEL Classification: D44, C01, C46, C57