Identifying Demand from Online Auction Data

Download or read book Identifying Demand from Online Auction Data written by Christopher Adams and published by . This book was released on 2009 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The paper presents a framework for estimating a demand system from price data generated by a large scale auction platform such as eBay. Auction prices are used to identify characteristics of the joint distribution using an order statistics like approach where the bidder's "revealed preference" in equilibrium enables inference of valuations. Two approaches are presented for identifying the full joint distribution. Sklar's Theorem is used to show the complete joint distribution can be inferred from combining information from the first step with information on the marginal distributions inferred from prices of auctions with no competition. A multiple market model is used to show variation in the number of auctions for the same product can be used to provide bounds on the joint distribution. The paper presents additional results for when the number of participants is unobserved, when the number of competing auctions is unobserved and when there is observed bidder heterogeneity.