I have attached questions and article needed to answer questions
a. When you, as a consumer, buy used goods online (or think about buying online) are you sure that the purchased item will have the quality advertised by the seller? Explain. b. How does Ebay create value? Explain. c. What potential contracting problems exist on Ebay and how does eBay address these problems? d. What is the main principle-agent problem that occurs in used goods online markets that the paper is referring to? Describe the problem in detail. e. What is the main theory (or hypothesis) that the author proposes which helps buyers and sellers transact online? f. How does the author make sure that the differences in observed transaction prices are due to differences in the quality of the cars sold? Explain. American Economic Review 101 (June 2011): 1535–1546 http://www.aeaweb.org/articles.php?doi=10.1257/aer.101.4.1535 1535 The rise of the Internet has seen a huge rise in the volume of used goods traded online. Online auction sites such as eBay and Yahoo! Auctions compete worldwide with specialized listing sites such as usedcomputer.com and cars.com in the retail trade of consumer goods. Meanwhile, business to business transactions totaling bil- lions of dollars take place through online auctions in industries as diverse as aviation and mining. At first glance, this growth is somewhat surprising. Since George A. Akerlof (1970), economists have been aware of the potential for adverse selection in markets with information asymmetries, such as used good markets. Information asymmetries are exacerbated in online transactions, where the buyer typically does not view the good in person. Why then has the volume of trade in these markets proved so robust to adverse selection? In this paper, I argue that it is fundamentally because sellers are able to partially contract on the quality of their goods. By disclosing their private information on the auction Web page in text and photos, the seller offers a contract to potential buy- ers to deliver the item described in the listing. If the disclosures define sufficiently detailed and enforceable contracts, the initial information asymmetry should play no role in determining the performance of the market. Both of these caveats are impor- tant: if contracts are not enforceable, they are meaningless; while if disclosures are costly, the resulting contracts may be coarse and market efficiency may suffer. To test this hypothesis, I examine the role of disclosure and disclosure costs on eBay Motors, the largest used car marketplace in the United States. In this market, despite high stakes for both sides and substantial information asymmetries, there is a high volume of trade with nearly 50,000 cars sold each month in the period from August 2006 to April 2008.1 By analyzing how the market works, I first argue that the institutional framework makes certain kinds of claims relatively easy to enforce. Then, using a large new dataset of over 80,000 car auctions, I show that photos and text posted by the seller on the auction Web page strongly influence prices, suggest- ing that online disclosures are important empirically. Finally, I show that disclosure costs affect how much information the seller decides to post, and therefore the prices 1 Source: eBay Press Releases http://investor.ebay.com/releaseDetail.cfm?releaseID=206868 (accessed May 2, 2011) and also releaseID=306677 (accessed May 2, 1011). Asymmetric Information, Adverse Selection and Online Disclosure: The Case of eBay Motors By Gregory Lewis* * Department of Economics, Harvard University, 125 Littauer Center, 1805 Cambridge St., Cambridge, MA 02138 (e-mail:
[email protected]). This is a heavily revised version of my job market paper, supported by a Rackham Predoctoral Fellowship from the University of Michigan. I would especially like to thank Pat Bajari for his support and advice on this paper. I am also grateful for comments from three anonymous referees, and Dan Ackerberg, Jim Adams, Susan Athey, Matt Backus, Tilman Börgers, Phil Haile, Oliver Hart, Han Hong, Hugo Hopenhayn, Ali Hortaçsu, Guido Imbens, Jakub Kastl, Kai-Uwe Khn, Jim Levinsohn, Julie Mortimer, Serena Ng, Scott Page, Ariel Pakes, Nicola Persico, Rob Porter, Dan Silverman, Jagadeesh Sivadasan, Doug Smith, Lones Smith, and Charles Taragin; and for excellent research assistance from Chris Sullivan. 1536 THE AMERICAN ECONOMIC REVIEW JUNE 2011 he obtains. Taken together, I conclude that disclosure costs—whether caused by technology, bandwidth, or time costs—are an important determinant of the extent to which parties can create well-defined contracts online, and therefore of the success of online goods marketplaces. The theoretical foundations of the paper lie in the work of Sanford J. Grossman and Oliver D. Hart (1980); Grossman (1981); and Paul R. Milgrom (1981); who argued that verifiable disclosure might mitigate the adverse selection problems of Akerlof’s classic paper. Boyan Jovanovic (1982) investigated the welfare implica- tions of disclosure costs. On the empirical side, there is a diverse literature on both mandatory and voluntary disclosure (see, e.g., Alan D. Mathios 2000; Ginger Zhe Jin and Phillip Leslie 2003; Jin 2005; Jin and Andrew Kato 2006). There is also a lit- erature on adverse selection in used vehicle markets (e.g., Eric W. Bond 1982, David Genesove 1993). The contribution of the paper to the online auctions literature (e.g., Paul Resnick and Richard Zeckhauser 2002; Daniel Houser and John Wooders 2006) is to provide a different perspective, shifting the focus from the seller feedback mechanism, and the implicit contract it helps enforce, to the role of disclosure and the explicit contracts thus defined. In a similar vein, Pai-Ling Yin (2008) shows that when the webpage leaves bidders uncertain as to the value of the object sold, prices are lower. The later part of the paper examines how software availability changes what information is disclosed. George P. Baker and Tomas N. Hubbard (2004) also examine the impact of technology on contracting, looking at how the introduction of on-board computers impacted asset ownership in the trucking industry. The paper proceeds as follows. Section II describes the market; Section III introduces the data- set and the empirical analysis; and Section IV concludes. I. eBay Motors In the period from 2006 –2008 eBay Motors, the automobile arm of online auc- tions giant eBay, is thriving. In an average month, nearly 50,000 vehicles were sold, a sales rate of almost one vehicle every two minutes. This trading volume dwarfs those of its online competitors, the classified services cars.com, autobytel.com and Autotrader.com. In contrast to these sites, most of the sellers on eBay Motors are private individuals, although dealers still account for around 30 percent of the list- ings. Another big difference is that a large proportion (75 percent) of vehicles are sold to out-of-state buyers. Because of this, bidders can typically neither examine the car in person nor rely entirely on the seller’s reputation; they must rely on the information on the auction Web page to evaluate potential purchases.2 Some information is standardized and mandatory, such as car make, model, mile- age, etc. But most of the details are voluntarily disclosed by the seller in the item description, which can include text, photos, graphics and video. eBay charges little for posting information, as text and graphics are free, while each additional photo costs $0.15. Yet the opportunity costs are higher, as it is time consuming to take, select and upload photos, write the description, generate graphics, etc. While these opportunity costs may seem small, the fact that professional car dealers typically 2 Source: Auction123. http://www.auction123.com/ebayadvantages.aspx (accessed January 9, 2009). 1537lEWIs: AdVERsE sElECTION ANd ONlINE dIsClOsUREVOl. 101 NO. 4 invest in advanced listing management software to limit these costs suggests that they are not insignificant. Such software allows easier photo uploading and main- tenance, graphics production and listing management, and is offered by companies such as CARad, eBizAutos and Auction123 at costs ranging from $10 a listing to a flat $300 a month fee. It is typical in most eBay car auctions for sellers to post many photos, a full text description of the car’s history and features, and sometimes graph- ics and videos showing the car’s condition. The Web page created by the seller defines the contract between the buyer and the seller, in accordance with whose terms the buyer agrees to purchase the vehicle described by the seller at the final closing price of the auction.3 Rich media such as photos and videos may define the contract terms more precisely than text. Two fea- tures of the market make these contracts practically enforceable. First, “most buyers opt to pick up the vehicle in person.”4 Even when the seller ships the vehicle to the buyer, payment is often held in escrow (e.g., through PayPal) until the buyer has had a chance to examine the vehicle. The result is that much of the information provided by the seller is often verifiable before payment is made. Second, material misrepre- sentations by the seller constitute fraud. In contrast to private car sales offline where it may be difficult to establish exactly what the seller did or did not promise, the Web page is stored by eBay for at least 20 days after the sale. As a result, these online transactions have a clearly defined contract in the event of a dispute. Because of these institutional features, sellers have little incentive to lie, and buyers can take much of the Web page information at face value. Conversely, sellers have the incentive to cre- ate detailed Web pages, knowing that buyers will rely on the information presented. We examine how buyers respond to disclosures in the analysis that follows. II. Analysis To fix ideas, it is useful to have the disclosure model of Grossman and Hart (1980); Grossman (1981); and Milgrom (1981) in mind. A seller knows a number of pieces of information about the car he is selling. On some dimensions, the infor- mation known may not be verifiable ex post or enforced as a contractual claim by the buyer. Then the buyer should not update based on seller statements about these dimensions. For example, the buyer may not be able to judge the mechanical condi- tion of the car upon pick-up. In this case, statements along the lines of “this car has no mechanical problems whatsoever” should be treated as cheap talk. On other dimensions,