Identification in Ascending Auctions, with an Application to Digital Rights Management
Joachim Freyberger and
Brad Larsen ()
No 23569, NBER Working Papers from National Bureau of Economic Research, Inc
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.
JEL-codes: C1 C57 D44 L0 L96 O3 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-com, nep-des, nep-ecm, nep-ict, nep-mkt and nep-pay
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