Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/195547
Authors: 
Hickman, Brent R.
Hubbard, Timothy P.
Paarsch, Harry J.
Year of Publication: 
2017
Citation: 
[Journal:] Quantitative Economics [ISSN:] 1759-7331 [Volume:] 8 [Year:] 2017 [Issue:] 2 [Pages:] 505-551
Abstract: 
Because of discrete bid increments, bidders at electronic auctions engage in shading instead of revealing their valuations, which would occur under the commonly assumed second-price rule. We demonstrate that misspecifying the pricing rule can lead to biased estimates of the latent valuation distribution, and then explore identification and estimation of a model with a correctly specified pricing rule. A further challenge to econometricians is that only a lower bound on the number of participants at each auction is observed. From this bound, however, we establish nonparametric identification of the arrival process of bidders-the process that matches potential buyers to auction listings - which then allows us to identify the latent valuation distribution without imposing functional-form assumptions. We propose a computationally tractable, sieve-type estimator of the latent valua- tion distribution based on B-splines, and then compare two parametric models of bidder participation, finding that a generalized Poisson model cannot be rejected by the empirical distribution of observables. Our structural estimates enable us to explore information rents and optimal reserve prices on eBay.
Subjects: 
eBay
electronic auctions
bid increments
pricing rule
JEL: 
D44
C72
Persistent Identifier of the first edition: 
Creative Commons License: 
https://creativecommons.org/licenses/by-nc/4.0/
Document Type: 
Article
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