Entry Deterrence and Learning Prevention on eBay Export

@unpublished{Nekipelov_2007_eBayEntryDeterrence, abstract = {nternet auctions (such as eBay) differ from the traditional auction format in that participants 1) typically face a choice over several simultaneous auctions and 2) often have limited information about rival bidders. Since existing economic models do not account for these features of the bidding environment, it should not be surprising that even casual empiricism reveals a sharp discrepancy between the predictions of existing theory and the actual behavior of bidders. In particular, despite the second-price structure of eBay auctions (which, along with private values, implies that bidders submit a single bid), eBay bidders frequently bid multiple times over the course of a single auction and cluster their bids at the very end. In this paper, I show that the presence of multiple, contempo- raneous auctions for similar items coupled with uncertainty regarding rival entry can explain both features. The multi-auction structure of eBay induces two types of aggressive bidding behavior: entry deterrence and learning prevention. While the incentive to deter entry leads to aggressive early bidding, the incentive to prevent rivals from learning the unobserved features of the auction by observing the price process can lead to late bidding. I analyze these features in a continuous- time stochastic auction model with endogenous entry, in which bidder types are differentiated by their initial information regarding the entry process. I establish non-parametric identification of the structural model and develop a computationally attractive method for estimating its parame- ters. Empirical estimates using eBay auctions of pop-music CDs confirm my theoretical prediction that the rate of entry depends on price. I then test my model against alternative explanations of observed bidding behavior using a detailed field experiment.}, author = {Nekipelov, Denis}, citeulike-article-id = {2970401}, keywords = {auctions, empirical, internet\_auctions, multi\_unit, paper\_01\_internet\_auctions, sniping}, posted-at = {2008-07-07 16:31:08}, priority = {5}, title = {Entry Deterrence and Learning Prevention on eBay}, year = {2007} }

TY - UNPB ID - Nekipelov_2007_eBayEntryDeterrence L3 - citeulike-article-id:2970401 N2 - nternet auctions (such as eBay) differ from the traditional auction format in that participants 1) typically face a choice over several simultaneous auctions and 2) often have limited information about rival bidders. Since existing economic models do not account for these features of the bidding environment, it should not be surprising that even casual empiricism reveals a sharp discrepancy between the predictions of existing theory and the actual behavior of bidders. In particular, despite the second-price structure of eBay auctions (which, along with private values, implies that bidders submit a single bid), eBay bidders frequently bid multiple times over the course of a single auction and cluster their bids at the very end. In this paper, I show that the presence of multiple, contempo- raneous auctions for similar items coupled with uncertainty regarding rival entry can explain both features. The multi-auction structure of eBay induces two types of aggressive bidding behavior: entry deterrence and learning prevention. While the incentive to deter entry leads to aggressive early bidding, the incentive to prevent rivals from learning the unobserved features of the auction by observing the price process can lead to late bidding. I analyze these features in a continuous- time stochastic auction model with endogenous entry, in which bidder types are differentiated by their initial information regarding the entry process. I establish non-parametric identification of the structural model and develop a computationally attractive method for estimating its parame- ters. Empirical estimates using eBay auctions of pop-music CDs confirm my theoretical prediction that the rate of entry depends on price. I then test my model against alternative explanations of observed bidding behavior using a detailed field experiment. TI - Entry Deterrence and Learning Prevention on eBay KW - auctions KW - empirical KW - internet_auctions KW - multi_unit KW - paper_01_internet_auctions KW - sniping AU - Nekipelov, Denis PY - 2007/// ER -