Essays on applied economics



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6. Conclusion


This paper has provided the first related pieces of evidence in the literature that together lend strong support to competing auctions theory. First, in the presence of competing auctions, bidders use a very different strategy than they would with independent auctions. Bidders tend to bid across competing auctions and bid on the auction with the lowest standing bid. We further demonstrate that when homogenous auctions end at almost the same time, more bidders are likely to bid across competing auctions than when auctions end at different times. We also find that winners who bid across competing auctions pay a lower price than those winners who do not bid across competing auctions. Therefore, since there are many homogenous auctions competing against each other in on-line auctions, it is inappropriate to consider on-line auctions as independent, ignoring the existence of other competing auctions.

In this paper, we do not consider whether the auction prices are uniform with the existence of competing auctions. According to the theory, competing auctions tend to make prices more uniform. We will study such price effect of the existence of competing auction on eBay in a separate paper. In the current paper, we also take the behavior of sellers as exogenous. It will be interesting to see what the equilibrium behavior of sellers is given the existence of competing auctions. This will be especially useful for those sellers who want to sell many identical items one by one in a short time.



Reference
Bajari, Patrick and Ali Hortacsu. (2000) “Winner’s curse, Reserve Prices and Endogenous Entry: Empirical Insights from eBay auctions”, Working paper, Stanford University.
Hooser, Daniel and Daniel Wooders. (2001) Reputation in Auctions: Theory and Evidence from eBay, working paper, University of Arizona.
Lucking-Reiley, David. (1999) “Auctions on the Internet: What’s being auctioned, and How?” Working paper, Vanderbilt University.
Myerson, R. B. (1981) Optimal Auction Design. Mathematical of Operations Research, 6, 58-73.
McAfee, P. (1993) “Mechanism Design by Competing Sellers,” Econometrica 61 (1993) no.6, 1281-1312.
Peters, Michael and Sergei Severinov. (1997) “Competition among sellers who offer auctions instead of prices,” Journal of Economic Theory, 75, 141-197.
Peters, Michael and Sergei Severinov. (2001) “Internet Auctions with Many Traders,” Working paper, University of Toronto.
Forsythe, Robert et al. (1992) “Anatomy of an Experimental Political Stock Market,” American Economic Review, vol. 5, 1142-1161.
Roth, Alvin and Axel Ockenfels. (2000) “Last Minute Bidding and the Rules for Ending Second Price Auctions: Theory and Evidence from a Natural Experiment in eBay,” Tech. Report, Harvard University
Wilson, R. (1985) “Incentive efficiency of double auctions,” Econometrica 53, 1101-1117.
Zheng, Mingli (2001) Real time simulations of eBay auctions with competing auctions, working paper, University of Toronto.

Figure 1.1


A bidding History Page from ebay


EBay Bid History for
Intel Pentium II Xeon 450MHz 512k - Used (Item # 1292121814)




Currently

$24.49




First bid

$10.00




Quantity

1




# of bids

10




Time left

Auction has ended.




Started

Oct-31-01 22:51:27 PST




Ends

Nov-03-01 22:51:27 PST




Seller (Rating)

nhahmad (11)







View page with email addresses (Accessible by Seller only)   Learn more.







Bidding History (Highest bids first)




User ID

Bid Amount

Date of Bid

planetorb (9)

$24.49

Nov-03-01 22:30:37 PST

ibgeek (4)

$23.99

Nov-03-01 22:18:01 PST

raheem112 (0)

$21.00

Nov-03-01 22:03:35 PST

iteachcomputers (1)

$20.00

Nov-03-01 22:06:49 PST

raheem112 (0)

$20.00

Nov-03-01 18:33:27 PST

planetorb (9)

$17.50

Nov-01-01 21:11:05 PST

raheem112 (0)

$15.00

Nov-03-01 18:33:16 PST

raheem112 (0)

$14.00

Nov-03-01 18:32:50 PST

raheem112 (0)

$13.00

Nov-03-01 18:32:39 PST

raheem112 (0)

$11.00

Nov-03-01 18:31:52 PST

Remember that earlier bids of the same amount take precedence.

Bid Retraction and Cancellation History

There are no bid retractions or cancellations.



Table 1.1
Sample Statistics For CPU Auctions (Number of auction=7910)


Variable

Mean

Std Dev

Minimum

Maximum

Number of bids

6.66

6.91

0

49

Last bid (unit: $)

60.60

82.34

0.01

981

Starting Bid (unit: $)

29.25

61.60

0.01

899

1452 auction receive no bids

899 auctions have secret reserve price

515 auctions have met reserve prices



Table 1.2
Sample Statistics for Samples of Competing Auctions





Daily sample

Hourly sample

Minute sample

Number of auctions

1247

748

346

Number of groups

550

321

139

Number of auction with reserve met

66

36

5

Number of auctions with reserve not met

40

30

19

Number of auctions not receiving bids

305

196

115

Number of bidders winning more than one item in a group

24

18

10

Figure 1.2
Histogram of Bidders’ Feedback

Figure 1.3


Histogram of Bids Submission Time for Daily Sample

Table 1.3


Statistics of Cross Bidding in the Whole Process





Groups

Auctions per group

Cross bidder per group

Bidder per group

Proportion







Mean

Std

Min

Max

Mean

Std

Min

Max

Mean

Std

Max

Min

Mean

Daily

458

2.28

0.87

2

9

1.53

1.78

0

10

6.56

5.14

32

1

0.23

Hourly

258

2.36

0.98

2

8

1.41

1.90

0

10

6.59

5.32

32

1

0.22

Minute

101

2.60

1.29

2

8

1.48

1.96

0

10

4.86

4.34

20

1

0.27

(For groups with positive bids only.)



Proportion: proportion of cross bidders.

T-statistics for the proportion of hourly sample and minute sample is:

T-statistics for the proportion of dailyly sample and minute sample is:

T-statistics for the proportion of hourly sample and daily sample is:
Table 1.3 B
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