Vettes and Lemons on EBay

Transcription

1 Vettes and Lemons on ebay Page 1 Vettes and Lemons on EBay Christopher P. Adams, FTC Laura Hosken, FTC Peter Newberry, FTC PRELIMINARY DRAFT Do not distribution without authors permission. April 11, 2006 ABSTRACT Using bid data from 8,000 new and used Chevrolet Corvettes sold on ebay, this paper empirically tests Akerlof s (1970) hypothesis that the used car market is characterized by low quality and informational problems. The hypothesis states that the used market has a higher proportion of low quality cars than the new market and buyers account for the difference by discounting their value for a used car relative to a new car. This is tested by comparing bids on new and late model used Vettes. The paper finds little evidence of a premium for new Vettes. The paper also considers a natural generalization of Akerlof s (1970) model which allows potential bidders to have different and incomplete private information about the quality of the used car. One implication is that a rational bidder will bid late in the auction in order to reduce the likelihood of other bidders observing his private information. A second implication is that a rational bidder will discount his bid in order to reduce the likelihood of winning the auction because his private information is incorrect (the winner s curse). We test the first implication by comparing bid times on new and used cars and by comparing bid times on newer and older used cars. Akerlof (1970) suggests that the quality and informational problems will be larger with used cars relative to new cars, and other empirical work suggests that quality and informational problems are larger for older used cars relative to newer used cars. Therefore, we expect to find more late bidding on used cars relative to new cars and older used cars relative to newer used cars. If anything, we find that the opposite is true for Vettes. To test the second implication we compare bidding on used Vettes for auctions with different numbers of expected bidders. Recent theory suggests that bidders facing a winner s curse problem will bid less as the number of expected potential bidders increase. Our analysis suggests bidders bid slightly more in auctions with a higher number of expected bidders. Overall, for used Chevrolet Corvettes sold on ebay there is little empirical support for the hypothesis presented in Akerlof (1970). It is not clear, however, whether these results generalize to other cars sold on ebay or cars sold in the off-line used market. The views expressed in this paper do not represent the views of the FTC or any individual Commissioner. The authors would like ebay and staff at ebay Motors for providing the data. We also want to thank Edmunds.com for information they provided us. We want to thank Jorge Roberts and David Yans, for excellent research assistance, Steve Berry, George Deltas, Avi Goldfarb, Debra Holt, Dan Hosken, Jim Lacko, Fiona Scott Morton, Mike Smith, Unjy Song, Steve Tenn, Bill Vogt, Pai-Ling Yin, Robert Zeithammer, participants at the 2005 IIOC meetings in Atlanta, 2005 INFORMS conference, Maryland IO seminar, FRB IO Seminar, DOJ s EAG seminar, and other FTC colleagues for helpful comments in regards to this research project. Any errors are our own. CONTACT: cadams@ftc.gov

2 Vettes and Lemons on ebay Page 2 1. Introduction Akerlof (1970) states the market for used cars is riddled with quality and informational problems. Because only owners can observe the car s quality, the proportion of lemons in the used car market is much higher than the proportion of lemons in the new car market. Akerlof (1970) argues this lemons problem explains why there is such a large price difference between new cars and late model used cars. Akerlof (1970) further argues it is possible for the used car market to collapse because information asymmetries make trade difficult. Given these dire predictions, we may not expect used cars to become very popular in an on-line market like ebay. Yet in 2003 ebay Motors sold an average of one thousand used cars per day. ebay Motors has become the most successful unit of one of the most successful companies of the Internet era. Is Akerlof (1970) correct? Is there a lemons problem on ebay Motors? This paper presents a number of empirical tests of Akerlof s lemons hypothesis using bid data for new and used Chevrolet Corvettes sold on ebay between April 2001 and December Overall, the paper finds little empirical support for the hypothesis, at least in regards to used Corvettes sold on ebay Motors. The paper s first test of Akerlof s hypothesis considers the implication that bidders are willing to pay a considerable premium for a new Vette relative to a late model used Vette. If there is a quality problem and the current owner has more information about the car s quality, then bidders will be wary of buying a used Vette and will discount their bid to account for the increased likelihood that the car is a lemon. First, the paper compares bids on new and used Vettes that are less than a year old. This simple comparison of means and medians suggests bids are higher for the late model used cars than for the new cars. Second, the paper presents results from regression analysis of bids and prices which account for observed characteristics of the cars, the sellers and the bidders. The results suggest there is little evidence of a premium for new cars relative to late model used cars. The paper follows up on this simple test of a new car premium by looking for evidence of informational problems in ebay s used Vette market. In Akerlof (1970) sellers of used cars know the exact quality of the car while buyers know only the population probability that the car is a lemon. A natural generalization allows buyers to observe signals of the car s quality. Such a model allows bidders to correspond with

3 Vettes and Lemons on ebay Page 3 the seller, observe detailed photographs of the car, obtain a Carfax Report, take the car for a test-drive or get an independent mechanic s assessment of the car s quality. If the car s quality is a characteristic that all bidders consider to be important and bidders have different signals of the car s quality, then the auction is a common value or affiliated value auction. This paper empirically tests whether bidders behave in a way that consistent with rational behavior when bidding in an affiliated values auction. In particular, the paper tests whether bidders bid late in the auction in order to hide their private information from other bidders and whether bidders discount their bids to account for the winner s curse (the probability the winner s private information over values the actual quality of the car). Late bidding or sniping is something of a phenomenon on ebay and numerous explanations have been provided for why such behavior occurs (Bajari and Hortacsu (2003), Roth and Ockenfels (2002)). According to Bajari and Hortacsu (2003) if bidders have private information about the quality of the item then these bidders are made worse off if this private information becomes known to other bidders (Milgrom and Weber (1982)). In equilibrium, bidders will bid late in an ebay-type auction in order to reduce the chance their private information is revealed to other bidders. To distinguish this common values explanation from other explanations, the paper compares the propensity of bidders to bid late on new cars to their propensity to bid late on used cars. Further, the paper compares the propensity to bid late on newer used cars to the propensity to bid late on older used cars. If Bajari and Hortacsu (2003) are correct, the propensity to bid late should increase as quality becomes a more important characteristic of the car and the expected quality of the car decreases. That is, there should be more late bidding on used cars relative to new cars and more late bidding on older used cars relative to newer used cars. The paper s empirical results are not consistent with the common values explanation. The paper finds there is more late bidding on new Vettes relative to used Vettes and more late bidding on younger Vettes relative to older Vettes. The winner s curse refers to the situation where the winner of the auction is the person that over values the item. For example, assume different bidders have different private information about the quality of a used Vette. In this case, some bidders will have information suggesting the car is of high quality and these bidders will over value the car. Some bidders will have information suggesting that the car is of low value and

4 Vettes and Lemons on ebay Page 4 these bidders will under value the car. On average, bidders will be close to the correct valuation of the car, however it is not the average bidder that wins the auction, the highest bidder wins. Rational bidders will realize that there is a winner s curse problem and discount their bid accordingly. These bidders face a trade-off between over paying for the car and losing the auction. According to Haile et al (2003) the larger the number of expected bidders, the greater the amount each bidder will discount his or her bid. The paper tests the hypothesis by regressing bids on used cars on observable characteristics of the cars, sellers and buyers and on the expected number of bidders. As discussed below, it is necessary to use a proxy for the expected number of bidders and for this, the paper uses the number of days of the auction. The paper also presents results from an order statistics regression analysis which accounts for censoring of bids and bidders. The results suggest bids increase very slightly with the number of expected bidders. The paper finds that bidding behavior on used Vettes is not consistent with the winner s curse and the existence of information problems in the market. It is surprising that one of the most famous theoretical results in economics, Akerlof s lemons hypothesis, lacks substantial empirical support. Bond (1982, 1984) and Lacko (1986) use data on the actual repair costs of pickup trucks and cars (respectively) sold in the used market to determine if there is evidence of a lemons problem. Bond (1982, 1984) finds that for used trucks bought on the used car market when these trucks were less than ten years old, there is no difference between the distribution of repair costs of the trucks bought used and the trucks bought new. This result suggests the quality of late model trucks is similar whether or not the truck is sold in the new or the used market. Lacko (1986) analyzes the distribution of repair costs for used cars bought through a variety of channels including friends and family, new car dealers, used car dealers and newspaper classifieds. Lacko (1986) argues that friends and family are unlikely to hide important private information about the quality of the car. Lacko (1986) finds that for cars less than seven years old the distribution of repair costs is similar for all used cars, irrespective of the channel of distribution. Both Bond (1982, 1984) and Lacko (1986) find that the quality of vehicles sold in the used market is lower once those vehicles get older. This result is consistent with a lemons problem in the market for older used cars, but it is not consistent with Akerlof s (1970) explanation for the steep decline in the value of a car in its first year of ownership.

5 Vettes and Lemons on ebay Page 5 More recent work similarly finds evidence of a lemons problem for older used cars but not for newer used cars. Engers et al (2004) analyze ownership durations and argue that the model presented in Akerlof (1970) suggests ownership durations will be positively correlated. Lemons will be hot potatoes quickly passed from one owner to the next. The authors find no evidence that short durations for the first owner are associated with short durations for later owners. A result that is not consistent with Akerlof s lemons hypothesis. However, the authors do find that cars with very long initial ownership durations have subsequent ownership durations that are short and positively correlated. The authors argue this pattern is consistent with neglect by the first owner causing quality problems for later owners. Porter and Sattler (1999) develop upon work by Hendel and Lizzeri (1999) and Bulow (1982) and estimate a general model of the used car market which includes Akerlof s model of information asymmetries with buyer preference for used cars. Porter and Sattler (1999) argue the empirical pattern of trade is consistent with a preference for used cars and not consistent with asymmetric information. Other papers do find some empirical support for Akerlof s hypothesis. 1 This paper presents the most direct empirical test of Akerlof s hypothesis, albeit in a relatively new market. The most straightforward test of Akerlof s hypothesis would be a survey of car buyers in which survey participants are asked to write down their value for a new car and a similar used car. If there is a premium for a new car, then the result would be consistent with Akerlof s lemons hypothesis. In this paper we come close to this test and to some extent we are able to do better because on ebay bidders must put their money where their mouth is. The second price auction mechanism used by ebay suggests rational bidders will bid their expected value for the car, at least by the end of the auction (Vickery (1961), Bajari and Hortacsu (2003), Song (2003)). Below, we assume bidders do in fact bid their value for the car and so we are able to compare bids across new and used Vettes to estimate the new car premium. We are cognizant of various factors that may bias estimates of a car s value using bids on ebay including censoring of later bids, censoring of late entering bidders, discounting to account for 1 Genesove (1993) finds some evidence supporting Akerlof s lemons hypothesis by using data on dealer behavior and preferences. Emons and Sheldon (2002) analyze used car sales in Switzerland and find some support for the lemons problem but state that it is not a widespread problem. Most recently Wolf and Muhanna (2005) argue that faster depreciation of used cars on ebay relative to Kelley Blue Book is evidence of a lemons problem on ebay Motors.

6 Vettes and Lemons on ebay Page 6 future auctions and discounting to account for informational problems. 2 Overall, these issues lead us to caution the reader when interpreting sizes or dollar amounts of the coefficients. 3 As there is no more or less bias for new cars relative to used cars the reader should not be suspect of the sign of the coefficients or the paper s failure to find evidence of a new car premium for Vettes. The paper s test of common values using late bidding on new and used cars is based on theoretical work presented in Bajari and Hortacsu (2003) and Milgrom and Weber (1982). While many papers have discussed reasons for late bidding, to our knowledge our paper presents the first empirical tests of the common values explanation. 4 The paper s test of bid discounting to account for the winner s curse is based on Haile et al (2003) and Yin (2005). Haile et al (2003) present a test of common values in first price auctions. The authors argue that in a simple sealed bid auction exogenous variation in the number of expected bidders will cause bidders to discount their bids by different amounts. In particular, discounting will increase as the number of expected bidders increase. The authors also point out that bidders may increase their bids as the number of observed bidders increase if those bidders are observed bidding above a minimum requirement. In addition, Song (2004) and Adams (2004) argue that late entering bidders will be censored in ebay-type auctions causing the number of bidders to be under counted. To account for these issues, this paper follows Yin (2005) and uses the length of the auction to proxy for the number of expected bidders. The paper also presents some results from an order statistics approach based on Song (2003) and Zeithammer (2005). This order statistics approach is meant to account for bias caused by the censoring of bids and bidders on ebay (Adams (2004), Song (2003)). One explanation for the paper s failure to find evidence of a lemons problem for Vettes sold on ebay is ebay s reputation system. Akerlof (1970) suggests mechanisms such a branding or reputation may help to solve the lemons problem in the used market. Lacko (1986) finds evidence that sellers who care more about their reputation such as friends and family and new car dealers sell higher quality cars than other sellers. Beyond the lemons problem, there may be straight out fraud on ebay (Jin and Kato (2005)). In fact, at least one person has been charged with fraud in regards to car sales which 2 See discussions of these various issues in Athey and Haile (2002), Adams (2004), Song (2003), Zeithammer (2005), Haile et al (2003), and Yin (2005). 3 Results presented in Adams et al (2004) suggest that the approach used in this paper may lead to over valuations of the cars and may also lead to biased estimates of coefficients. 4 See Roth and Ockenfels (2002) and Bajari and Hortacsu (2004).

7 Vettes and Lemons on ebay Page 7 occurred during the period corresponding to the data used in this paper. 5 According to the FTC, fraud in Internet auctions is consistently the Commission s second largest consumer complaint. 6 The reputation system used by ebay may help to solve both the lemons problem and reduce concerns about fraud. ebay records comments and scores (positive, neutral and negative) for participants in each transaction. The score of the seller is presented as a percentage (percent positive) on the item s web page with more detailed information one click away. The empirical evidence of the impact of these scores is mixed (Bajari and Hortacsu (2004)). Resnick et al (2004) perform a controlled experiment in which they set up two sellers, one real seller with a high reputation score and one new seller with a different name and a low score. In reality the sellers are identical and the items are similar. The authors find evidence of a significant premium for an established reputation on ebay. This paper includes a measure of the seller s reputation in its regression analysis, but finds little effect of the seller s reputation score on observed bids. The results presented in this paper suggest that ebay s reputation system has little effect in the used Vette market. The paper proceeds as follows. Section 2 presents data and background on ebay, ebay Motors and Chevrolet Corvettes. Section 3 empirically tests the hypothesis that there is a premium for new cars relative to similar used cars. Section 4 empirically tests the hypothesis that used Vette auctions are common value auctions. Section 5 presents a discussion of the results and the extent to which the results generalize to other car auctions and off-line sales. Section 6 concludes. 2. Data and Background 2.1 Auctions EBay uses an auction mechanism called a proxy bidding system. This system emulates a common English auction. Each bidder has the opportunity to bid her maximum amount. The system then takes that amount and sets the price equal to the second highest maximum amount plus a bid increment. Given this framework, it is 5 According to the Associated Press (August ), a man pled guilty to defrauding ebay customers of $40,000 by listing cars and failing to deliver them. 6 See

8 Vettes and Lemons on ebay Page 8 optimal for the bidder to bid her expected value for the item, at least by the end of the auction (Vickery (1961), Bajari and Hortacsu (2003), Song (2003)). In fact, this paper s interpretation of the results presented below assumes bidders do bid their value by end of the auction. In the analysis, a bid is set equal to the highest bid that a particular individual makes in a particular auction. Table 1 presents the mean bid for Vettes and for all cars sold on ebay Motors. The table shows that the average bid on a new Vette is $32,000, while the average bid on a used Vette is $12,000 and for ebay Motors it is just over $6,000. Sellers can determine various characteristics of the auction. All auctions start out at a minimum bid set by the seller. The seller can also choose the option of a secret reserve price. The secret reserve is unknown to the bidder although the bidder does know whether the reserve has been met. In the case of the minimum bid, no bid is allowed to be made below that amount. When there is only one bid above the minimum, the price is set equal to the minimum bid plus an increment. In the case of the secret reserve, once there is one bid above the secret reserve the price is set equal to the secret reserve plus an increment. In this way, both the minimum bid and the secret reserve affect the expected price received by the seller and both affect the cost of the listing (although in the case of cars, the listing costs are a fairly small proportion of the end price). ebay also gives some sellers the opportunity to offer a Buy It Now price (BIN). If a bidder selects the Buy It Now, the bidder wins the auction at the Buy It Now price. This option goes away once the first bid is made, or in the case of a secret reserve, once the first bid above the secret reserve is made. Sellers can choose other options such as the length of the auction (3, 5, 7 and 10 days), the end date and end time of the auction. Table 1 presents summary statistics for the use of secret reserves, BINs, and the different auction lengths available for both Vettes and all cars. The table also presents the average amount for the minimum bids, secret reserve and BIN. The table suggests that about half of the auctions last seven days with one fifth lasting ten days. About a third of the Vettes have the Buy It Now option, while the proportion of all cars with the BIN option is a little less than 30%. The median BIN offer on a new Vettes is just $45,500 while the median offer for a used Vette is $15,600, with the median BIN equal to $7,000 for all cars. Secret reserves are used about half the time, with relatively greater use in Vette auctions. When the reserve is used it is set at around

9 Vettes and Lemons on ebay Page 9 $18,000, while the starting price is set around $7,000. Both of these are lower for the general ebay Motors market. Table 1: Auction Characteristics Mean New Vettes Used Vettes All Cars Three day auctions a Five day auctions a Seven day auctions a Ten day auctions a Auctions with BIN Items sold with BIN BIN price (Median c ) $ 45, $ 15, $ 6, Reserve used Reserve Price $ 34, $ 17, $ 8, Starting Price $ 18, $ 6, $ 2, Bid b $ 32, $ 12, $ 6, Final Price a $ 30, $ 16, $ 7, Number of Bidders per auction b Total Number of Auctions 314 8, ,259 Total Number of Auctions, excluding items sold with BIN 250 6, ,736 Total Number of Auctions in bidder data 268 6, ,291 a Of auctions not sold with "Buy It Now" feature b Bidder data does not include auctions before December 1, c There is a BIN price of $10 billion 2.2 Buyers and Sellers To what extent can the results in this paper be generalized to ebay Motors as a whole and to the off-line used car market? One way to answer this question is to compare bidders of Vettes to other bidders and to the population in general. Table 2 presents summary statistics for observable characteristics of bidders on ebay Motors, observable characteristics Vette bidders, and demographic information for the general U.S. population. Our data shows that ebay Motors has over one million bidders with 27,000 bidders on Vettes. The demographic data includes the median income of the zip code of the bidder, the percentage of the zip code that is African American, and the percent of zip code living in an urban area. The demographic data is based upon publicly available information from the 2000 U.S. Census available from the Census Bureau. The table shows that the median household income in the zip code of the average bidder on ebay Motors is around $48,000 which is substantially higher than the median income for

10 Vettes and Lemons on ebay Page 10 the U.S. population. The average bidder on ebay Motors and Vettes are more likely to come from zip codes with fewer African Americans than the U.S. average. The average zip code is about 80% urban for ebay Motors bidders and little less for Vette bidders. This is about the same as the U.S. population of which about 80% live in an urban area. Table 2 also presents information on the average distance from bidder to seller, the average number of auctions each bidder bids in, and the average feedback score of the bidder. 7 The table shows that ebay users are willing to shop for cars that are over 700 miles from their house and Vette bidders are willing to go even further a field. Chart A3 presents the distribution of distances between bidders and sellers. The chart shows that 18% of bidders live within 200 miles of the seller. Note that the feedback score is for the user as of April 2004 and it is provided as an aggregate number rather than as a percentage. 8 One way to interpret the feedback score is as a measure of experience on ebay. The table shows that bidders on Motors and Vettes are quite experienced with Vette bidders more experienced than other Motors bidders. Table 2: Bidder Characteristics Mean New Vettes Used Vettes All Cars USA Percentage Population Black Median HH Income $ 50, $ 49, $ 48, $ 41, Percent Zip Urban Number of Auctions Bid on by Bidder Feedback Score Distance from Bidder to Seller Number of Bidders 1,273 26,418 1,308,343 Notes: The census classfies people as either urban or rural. Distance from Bidder to Seller is a weighted average. Number of Bidders is unique to the bidder id number. The other variables are unique to bidder's zip code. Who sells Corvettes on ebay? Are sellers usually new or used car dealers or are they ordinary citizens? Table 3 presents summary statistics for observable characteristics of Vette sellers and ebay Motors sellers more generally. The table shows that Motor s sellers are quite experienced. It seems that most sellers on the site are 7 Distance is calculated using zip code centriods on MapInfo. 8 The average score is calculated by assuming positives are equal to +1, neutrals are equal to 0 and negatives are equal to -1.

11 Vettes and Lemons on ebay Page 11 individuals rather than dealers. For the Vettes we were able determine that at least 33% of the new car sellers were new car dealers. 9 Of the sellers of used Vettes about 7% have three or more Vette sales, for the rest of Motors a similar percentage is 10%. Table 3: Sellers of 'Vettes on ebay New Vettes Used Vettes All Cars Mean Seller Feedback Median Household Income in Seller's Zip $ 43, $ 50, $ 49, Percent Urban Population in Seller's Zip Pecent of sellers who are new car dealers Percent of sellers with 3 auctions or more Total Number of Sellers 183 4, , Corvettes This paper uses bid data on Corvettes because Vettes are one of the most popular models sold on ebay. The model has consistently been in the top few most popular models sold on the site. The other feature of the Vette is that there has been relatively little variation in car characteristics both across cars of the same model year as well as across model years. One concern about using Vettes is that used Vette market may not be representative ebay Motors or the off-line used car market. Due to this concern the present results for Chevrolet Cavaliers. The paper uses bids on Corvettes and Cavaliers from model years 1981 to This restriction is made because we need to use the Vehicle Identification Number (VIN) to determine some of the observable characteristics of the car. 10 For example, we use the VIN to determine whether the Vette is a convertible or a coupe. General Motors began producing Corvettes in June of 1953 as a means to show the world that they could create a sports car to compete with European name plates. The first generation Corvettes (C1) lasted until 1963, when the all new Sting-Ray body design was introduced. The second generation (C2) was produced until 1968, when Chevrolet began to model the Corvette s body after the Mako Shark II concept vehicle. This third generation (C3) Corvette is where our data set begins. While both 1981 and 1982 Corvettes were part of the third generation, Carfax data indicates that their engines differ slightly, so a separate engine dummy for each year is included. Table 4 shows that 9 As discussed below, this number should be equal to 100% as only dealers can sell new cars. 10 Information on car characteristics is provided in the VIN. We used carfax.com to decode the Corvette VINs and we had Edmunds.com decode the Cavalier VINs.

12 Vettes and Lemons on ebay Page 12 the 1981 and 1982 models make up only 3% and 4% of the auctions, respectively. A 1983 model was not produced, so 1984 Corvettes marked the beginning of the fourth generation (C4). These Corvettes were powered by a 5.7 liter engine, called the L-83 and it produced 205 horsepower. An engine dummy is also created for the 1984 Corvettes, as change in the fuel injection system was introduced in The TPI engine dummy equals 1 for all models with this new fuel injection system called the tuned port injection system. This engine type accounts for 26% of the auctions in our data. In 1990, GM began making Corvettes with the new ZR-1 engine that produced 375 horsepower. Shortly thereafter, a new generation of LT-1 engines was released with 300 horsepower. These Corvettes make up 21 percent of the total auctions in the data set. In 1996, a special LT-4 engine was offered as an option in the Grand Sport model and it produced 330 horsepower. In 1997 the fifth generation of Corvettes began production. The C5s were produced until the 2004 model where our data set ends. 37% of the Corvettes in our data set are part of the C5 generation. 11 Table 4: Engine and Model Variables 12 Variable Percent Years Description eightyone model year 'Vettes eightytwo model year 'Vettes Eightyfour model year 'Vettes- C4 without TPI Tpi 'Vettes with Tuned Port Injection System zr 'Vettes with ZR-1 engine lt 'Vettes with LT-1 eninge lt Grand Sport 1996 'Vettes c Fifth generation 'Vettes The data is a sample of cars sold at auction on ebay between April of 2001 and December During this period there were more than 700,000 new and used car sold on ebay Motors. The sample includes all Chevrolet Corvettes sold during this period for which we have a valid Vehicle Identification Number (VIN). VINs and car characteristics like make, model, model year, mileage and color are entered into the ebay 11 Information on Corvette styles and engines comes from 12 The data in this table is based on 8,332 auctions.

13 Vettes and Lemons on ebay Page 13 Motors database by the seller. EBay Motors displays this information in the top part of the web page advertising the auction. The data is not always accurately entered and VINs are not always provided. 13 A valid VIN gives information about the car including make, model, year, engine type, and model style. By using only observations with a valid VIN we can corroborate information about the car that the seller includes on the ebay site, and eliminate those observations with conflicting information. The total number of Corvette auctions that occurred during this period was 15,351, with 9,293 for model years 1981 or later. In a couple of cases there were obvious transcription errors with the VINs, and in those cases the VIN was adjusted and the model information was checked against other seller entered information. 14 Table 5 presents summary statistics of the Vettes in the sample. Most of the Vettes in the sample are used, some 96%. Used Corvettes sold on ebay are on average about ten years old with an average mileage of just under 64,000. It is 4,600 miles for new Vettes. The average car on ebay Motors is older, but this may have something to do with the fact we cut off the Vette data at Only 1% of the cars sold on ebay are listed by the seller as new. Note that the mileage information is seller entered and in some cases we drop observations above 306,000 miles all of which have nonsensical entries such as % of new Vettes and 73% of used Vettes are automatic, 52% of new Vettes and 24% of used Vettes are convertibles and around 25% are red. Graphs A1 and A2 in the appendix present the distribution of mileage and model years respectively. Graph A1 shows there is a large group (12%) of cars with mileage at less than 10,000 miles. Graph A2 shows that model years are centered around 1999 with the C5 making up the largest single version of the Corvette in the data. 13 ebay now requires an accurate VIN to be provided. 14 Transcription errors were detected by entering a VIN into Carfax. If incorrect, Carfax would then suggest an alternate, or correct, VIN. Thus we could clean the data in this manner.

14 Vettes and Lemons on ebay Page 14 Table 5: Car Characteristics New Vettes Used Vettes All Cars Age of the Car Mileage* 4,658 64,689 84,841 Model Year Percent Automatic Percent Convertible Percent Coupe Percent Hardtop Percent Hatchback Percent Red Percent Black Total Number of Cars 314 8, ,259 *Restricted to mileage between 0 and 306, New Car Premium Akerlof (1970) argues there is a discontinuous decrease in the value of the car from the new car showroom to the used market. In the model this discontinuity occurs because only owners of used cars are able to observe the actual quality of the car. In equilibrium, the expected quality of used cars is much lower than the expected quality of new cars. This section tests Akerlof s lemons hypothesis by measuring the difference in a bidder s willingness to pay for a new car and a bidder s willingness to pay for an almost new used car. The difference, if it exists, is equal to the new car premium. This premium may measure the extent a bidder discounts the value of a used car to account for expected quality problems. The first test compares bids on new and used Vettes which are less than a year old at the time of the sale. Because of the small number of auctions this analysis is not able to account for other factors such as style, color, the year of the sale, etc. The paper uses four different definitions of new. To test Akerlof s hypothesis we would like to know whether or not the car has left the showroom. The legal definition of a new car is a car which has never had an owner. 15 On ebay Motors sellers enter the condition of the car, where the only choices are new or used. This means, that an almost new car which has recently left the showroom could be listed as new because the seller 15 Note that a car can change owners without leaving the showroom.

15 Vettes and Lemons on ebay Page 15 believes that it is as if it is new or the seller could follow the strict letter of the law and defines the car as used. Because of possible misspecification of new cars, our test of Akerlof s hypothesis may be biased to zero. Still, we believe there is enough correlation between our measure of new and actual new cars to give the test power. In order to reduce the number of new cars that are actually used, we use a number of more restrictive definitions. In each case, observations which do not meet the more restrictive criteria are dropped. We define New1" as cars for which the seller states the car is new. Our first restriction, called New2, defines a new car as one for which the seller says it is new and the car is less than one year old at the time of sale. Our second restriction, called New3, defines new as a car for which the seller says the car is new, the car is less than one year old at the time of sale and we know the seller to be a new car dealer. Note, the only people that can sell an actual new car are new car dealers. A new car dealer must have a new car franchise agreement with the manufacture, have a state new car dealer license, and have passed various other state requirements. We use information provided by ebay and information from public websites such as Yahoo! to determine whether a seller is a new car dealer. The final definition, called New4, requires the seller state the car is new, requires the car be less than one year old and requires the car have less than 100 miles. Table 6 presents the mean, median and standard deviation of bids on new and used Vettes that are less than a year old. If Akerlof s hypothesis is correct then we would expect bids to be substantially higher on new cars relative to used cars. The table shows that in general this is not true. The table shows that the average bid and the median bid are both higher on used cars than on new cars. Moreover, it matters little exactly which definition of new is used. It does show, however, that the standard deviation is higher for new cars relative to used cars and therefore some proportion of bids may be higher on new cars relative to used cars.

16 Vettes and Lemons on ebay Page 16 Table 6: Bids on New and Used 'Vettes (less than a year old) Mean Median Standard Deviation Number of Bids Used $ 29, $ 35, $ 15, New2 $ 22, $ 14, $ 26, ,998 New3 $ 24, $ 19, $ 31, New4 $ 21, $ 12, $ 27, ,094 Note: Bids higher than $500,000 were dropped. See note on Table 7. One concern with the simple test presented above is that it does not account for observable differences in the cars, the bidders or the sellers. To account for these observable characteristics, the paper presents results from a series of median regressions. Median regression analysis is used because results from mean regressions are sensitive to the removal of a few outlier observations (see the footnote of Table 7). Results for the different versions of new and for bids with and without demographic variables are included in Table 7. The regressors account for car characteristics such as mileage, age, engine type (see Table 4), style, transmission, and color, the seller s feedback, as well as bidder demographic characteristics such as the median income of the bidder s zip code, the proportion African American in the bidder s zip code and distance from seller. 16 The median regression coefficients are presented along with the standard errors, which are in parenthesis. With few exceptions the coefficients are statistically significant at traditional levels. If Akerlof s hypothesis is correct then we would expect the coefficient on the dummy variable New to be positive, large and statistically significant. The results presented in Table 7 show the coefficient on the various New dummy variables are all negative, large (in absolute values terms) and statistically significant. There is some variation in the magnitude of the coefficient depending on the definition of new and whether demographic characteristics are included. It is not clear why there seems to be a discount for new cars (at least for the median bid), but the result is certainly not consistent with Akerlof s lemons hypothesis. A concern with the raw bid data is that there may be substantial censoring. Table 8 presents prices and shows that the new car premium is around -$400 and not statistically different from zero when engine dummies are included and the new car is sold be a new car dealer. 16 An indicator of race is included because race is correlated with other characteristics that may affect demand such as income, access to the internet, and population density (Scott Morton et al (2003)). There may also be differential preferences for Vettes across racial groups.

17 Vettes and Lemons on ebay Page 17 Most of the other coefficient estimates are as one would expect. Age and mileage lead to lower prices with the value of the car falling by between $1,600 and $800 for every year. Convertibles are worth about $3,000 more and automatics are worth between $3,000 and $800 less than manuals. The older cars, the model year 1981, 1982 and 1984, have positive coefficients suggesting that the value of the Corvette falls for a number of years and then starts to increase at about twenty years of age. The value of the car falls the further it is from the bidder, the lower the income of the bidder, and if the bidder is from a zip code with a larger African American population. The only counter intuitive result is that the coefficient on seller feedback is negative. That is, sellers with a higher net feedback number receive lower bids at a rate of about $1 per feedback rating. 17 This section presents results from a straightforward test of Akerlof s lemons hypothesis. An implication of the model presented in Akerlof (1970) is that bidders are willing to pay a significant premium for a new car because the expected quality of a new car is greater than the expected quality of the used cars for sale on the market. What we find is that the median bid on a new car is actually less than the median bid on a used car, all else equal. There is no evidence of a new car premium. The appendix presents results from an identical analysis of Chevrolet Cavaliers. The tables show that there is a new car premium of about 20% of the value of a new car. That is bidders are willing to pay $1,000 to $2,000 more for a new Chevrolet Cavalier relative to an identical, but used, Cavalier This seems to contradict other evidence on the relationship between prices and seller feedback (Resnick et al (2004)). 18 Of course it is difficult to determine if this premium is due to lemons or to a substantial decline in observed quality.

18 Vettes and Lemons on ebay Page 18 Table 7: New vs Used Dummy Variable Median Quantile Regressions Variable New - Seller Entered -2, , (148.81) (157.14) New Seller Entered, 0 Years Old. -10, , (169.59) (169.90) New Seller Entered, 0 Years Old, Chevy -7, , Dealer (233.37) (223.90) Mileage/10, (0.01) (0.01) (0.01) (0.01) (0.01) (0.01) Convertible 2, , , , , , (51.57) (52.14) (55.05) (54.97) (52.80) (53.51) Automatic (51.90) (52.50) (55.46) (55.37) (53.22) (53.95) Car Color Dummies Included Included Included Included Included Included Engine Dummies Included Included Included Included Included Included Age (13.68) (13.88) (14.57) (14.57) (14.04) (14.14) Seller Feedback (0.04) (0.04) (0.04) (0.04) (0.04) (0.04) Time Dummies Included Included Included Included Included Included Distance (0.04) (0.03) (0.03) Median Income (0.00) (0.00) (0.00) Percent Black (199.38) (191.39) (193.75) Constant 23, , , , , , (111.44) (112.75) (118.79) (143.18) (137.62) (139.20) Observations Pseudo R-Squared note: There are 21 bids over $500,000 in the data set, and we considered these to be extreme bids. Although there are only 3 bids in this subset in which the car is new (according the new1 definition), these 3 bids have a dramatic impact on the data set. If these 21 bids are removed from the data set, the average bid for a "new" car drops by 30%, where the average bid for a "used" car drops by only 6.5%. Furthermore, the results from a mean regression were not robust to dropping these observations. In order to account for this we ran 3 quantile regressions: median,.25, and.75. The median regression is shown, the.25 quanitle regressions indicate a negative relationship between the new variables and bid, while the.75 quantile regressions indicate a positive relationship. This further suggests that these "extreme" bids have a significant effect on the results.

19 Vettes and Lemons on ebay Page 19 Table 8: New vs Used Dummy Variable Regressions- Price Variable Equation 1 Equation 2 Equation 3 Equation 4 Equation 5 Equation 6 New - Seller Entered 1, , New Seller Entered, 0 Years Old. (412.83) (356.45) , (465.55) (400.89) 3, New Seller Entered, 0 Years Old, Chevy Dealer (580.65) (470.89) Mileage/10, (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) Convertible 2, , , , , , (176.31) (175.51) (165.46) (147.96) (146.46) (132.57) Automatic -2, , , , , , (172.77) (171.91) (162.03) (150.18) (148.66) (134.63) Car Color Dummies included Included Included Included Included Included Engine Dummies Included Included Included Age -1, , , , , , (12.85) (12.77) (11.94) (39.58) (39.29) (35.24) Seller Feedback Time Dummies (0.13) (0.13) (0.12) (0.11) (0.11) (0.10) Included Included Included Included Included Included Constant 32, , , , , , (341.71) (339.70) (319.54) (319.86) (317.00) (285.92) Observations R-Squared Information Dispersion in the Used Market The previous section presents results from a direct test of a natural implication of Akerlof s (1970) model. This section presents results of two indirect tests of a generalization of Akerlof s (1970) original model. A reasonable generalization of the model allows potential buyers to observe signals of the car s quality. In the context of an ebay auction these signals may be from pictures posted by the seller, communications between the seller and the bidder, inspections arranged by the seller or the bidder, etc. If quality is an important attribute of the car and bidders observe different signals of the car s quality then a used Vette auction will have features of a common value or affiliated value auction. Theoretical work on such auctions suggests rational bidders will behave in certain ways when bidding in such auctions. This section presents results

20 Vettes and Lemons on ebay Page 20 from observing bidding behavior and tests whether bidder behavior in Vette auctions on ebay is consistent with common or affiliated value auctions. The section tests whether bidders bid later on used Vettes relative to new Vettes. Milgrom and Weber (1982) show a bidder in an affiliated value auction will reduce his expected value of entering an auction to zero if he provides his private information to other bidders. This result implies that bidders in common value auctions on ebay will bid late (Bajari and Hortacsu (2003)). In general, ebay is an open call auction, meaning that the price (and to some extent) the bids are observed by other bidders prior to the end of the auction. As the price increases, other bidders will adjust their expected value of the item upwards because these bidders know other bidders have signals suggesting the item has a value above the current price. These bidders may react to these higher prices by bidding more than they had originally planned. 19 In this way, high bids may lead to more high bids and even higher prices. In contrast, late bids are less likely to be observed by other bidders and even if these bids are observed, other bidders may not have the time to react with a higher bid of their own. By bidding late in the auction, bidders can keep their private information private and keep the price of the item down. The empirical test assumes quality and informational issues are a problem for used Vettes sold on ebay but they are not a problem for new Vettes auctions. That is, the test is whether there is more late bidding on used Vette auctions than on new Vette auctions. The paper also compares the timing of bids for newer used cars and bids for older used cars. Empirical evidence presented in Bond (1982, 1984), Lacko (1986) and Engers et al (2004) suggests even though newer used cars auctions may not have a common values component older used cars auctions may. Tables 9 and 10 present the empirical results for late bidding in Vette auctions. Charts A4 to A7 present additional information on the timing of bids in used Vette auctions. Table 9 presents the frequency of bids in the last minute, the last five minutes and the last hour for new Vettes, used Vettes and various subcategories of used Vettes. Table 9 presents the results for all bidders. 20 Table 10 presents results from a probit regression on the frequency of the top two bidders to bid in the last minute, the last five 19 It is not that these bidders get caught up in the excitement of the auction, rather these bidders bid more because their expected value of the item has increased. 20 We also analyzed late bidding for the top two bidders only. We did this because bidders who enter the auction late or plan to bid late in the auction may be censored by the price when they choose to make their last bid. The only bidders that are not censored in these auctions are the two top bidders. While the frequency of late bidding is much higher the relative results between new and used and newer and older are similar.

21 Vettes and Lemons on ebay Page 21 minutes and the last hour. We present the percentage point change in the probability due to a change in the variable measured at the sample averages for the non-changing variables (x-bar). The standard deviations and the sample averages are in parenthesis. None of the coefficients in the Last 5 minute or Last Hour regressions are statistically significant. The only coefficients that are statistically significant at conventional levels are the coefficients on Age and Seller Feedback for the Last Minute regression. If bidders behave as if there are important quality and information problems in the used market and not in the new market, we would expect a negative coefficient on New1. The results show that bidders have the same propensity to bid late for new cars as they do for used cars, or if there is a difference it is that bidders bid later on new cars. For used cars the results show bidders are somewhat more likely to bid later on newer used cars relative to older used cars. The graphs indicate that there is a large spike in high bids in the last 10% of Vette auctions. Amongst all bidders around 25% of high bidders come in the last 10% of the auction duration, while for the top two bidders it is around 70% of high bids. However, the pattern seems to be similar for both new and used Vettes. These results are not consistent with bidders behaving as if there is an important quality and information problems in used Vette auctions and not in new Vette auctions. Once again, seller feedback has an effect which is opposite to what we would expect if there was a lemons problem that the feedback was helping to solve. Table 9: Propensity to bid late Last 1 Minute Last 5 Minutes Last Hour Total Bids Overall ,698 New and 0 Age Used ,129 2 years old or less ,710 5 years old or less , years old or less ,370 Older than 10 years ,328 1,000 miles or less ,144 10,000 miles or less , ,000 miles or less ,383 More than 100,000 miles ,315