Identification in Ascending Auctions, with an Application to Digital Rights Management

46 Pages Posted: 17 Jul 2017 Last revised: 26 Nov 2021

See all articles by Joachim Freyberger

Joachim Freyberger

University of Bonn; University of Wisconsin - Madison

Bradley Larsen

Stanford University - Department of Economics; National Bureau of Economic Research (NBER); eBay Research Labs

Date Written: July 2017

Abstract

This study provides new identification and estimation results for ascending (traditional English or online) auctions with unobserved auction-level heterogeneity and an unknown number of bidders. When the seller's reserve price and two order statistics of bids are observed, we derive conditions under which the distributions of buyer valuations, unobserved heterogeneity, and number of participants are point identified. We also derive conditions for point identification in cases where reserve prices are binding (in which case bids may be unobserved in some auctions) and present general conditions for partial identification. We propose a nonparametric maximum likelihood approach for estimation and inference. We apply our approach to the online market for used iPhones and analyze the effects of recent regulatory changes banning consumers from circumventing digital rights management technologies used to lock phones to service providers. We find that buyer valuations for unlocked phones dropped after the unlocking ban took effect.

Suggested Citation

Freyberger, Joachim and Freyberger, Joachim and Larsen, Bradley, Identification in Ascending Auctions, with an Application to Digital Rights Management (July 2017). NBER Working Paper No. w23569, Available at SSRN: https://ssrn.com/abstract=3003667

Joachim Freyberger (Contact Author)

University of Bonn ( email )

Regina-Pacis-Weg 3
Postfach 2220
Bonn, D-53012
Germany

University of Wisconsin - Madison ( email )

716 Langdon Street
Madison, WI 53706-1481
United States

Bradley Larsen

Stanford University - Department of Economics ( email )

Landau Economics Building
579 Serra Mall
Stanford, CA 94305-6072
United States

HOME PAGE: http://www.stanford.edu/~bjlarsen/research.html

National Bureau of Economic Research (NBER) ( email )

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Cambridge, MA 02138
United States

eBay Research Labs ( email )

2065 Hamilton Avenue
San Jose, CA
United States

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