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Erschienen in: Review of Industrial Organization 3/2023

18.08.2023

Big Bids and Bidder Behavior in Uniform Price Auctions: Evidence from Peer-to-Peer Loan Markets

verfasst von: Garrett T. Senney, Jonathan R. Lhost

Erschienen in: Review of Industrial Organization | Ausgabe 3/2023

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Abstract

We investigate the effect of big bids on uniform price auctions with the use of data from peer-to-peer loan auctions. Following a big bid by a prospective lender, subsequent bidders are less likely to enter the auction, and those that do enter tend to bid higher interest rates. We show that bidders are not reacting to the identity of the big bidder—just to the bigness of the bid. Additionally, we find that auctions with a big bid receive fewer bids overall, but these loan requests are still more likely to get funded and to have higher interest rates. These results have strong implications for maximizing a seller’s revenue (or minimizing a buyer’s cost in a procurement auction) and the allocative efficiency in uniform price auctions.

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Fußnoten
1
For context, the mean and median bid are $78 and $50, respectively.
 
2
This assumption is reasonable given the fact that correlation and Durbin-Wu-Hausman tests cannot reject the null of exogeneity. We discuss this more in Sect. 4.4.
 
3
To protect the members’ privacy, their true identity is never revealed.
 
4
Prosper deemphasized groups starting in 2011, but this feature still exists on the platform.
 
5
This format is similar to what is commonly used in Treasury auctions and multi-unit procurement auctions.
 
6
Lenders cannot cancel a bid after it has been submitted.
 
7
Recall, loan requests are between $1000 and $25,000.
 
8
While the duration can be between 3 and 14 days, 81% of listings are set for one week.
 
9
The loan is fully amortized in monthly payments.
 
10
Credit grades are constructed as 40-point bands of the borrower’s Experian credit score.
 
11
Outcome data were collected on September 21, 2011. 9,099 of the loans had reached maturity, while the 515 remaining loans were still active in good standing.
 
12
Being delinquent ranges from being a single day late on a payment to being so incurable that the loan is charged off.
 
13
Delinquency rates are substantially higher than default rates. See Federal Reserve Bank of Richmond (2012), which is available via the “Residential Mortgage Delinquency and Foreclosure Rates” link courtesy of the Internet Archive Way Back Machine: http://​web.​archive.​org/​web/​20121019072734/​http://​www.​richmondfed.​org/​banking/​markets_​trends_​and_​statistics/​trends.
 
14
Previous research has found that most lenders tend to diversify across listings by pledging small amounts in multiple listings.
 
15
The final interest rate is an upper bound on what lenders actually bid.
 
16
The p-values for all four of the distributional tests are basically zero.
 
17
On average, these lenders have made 54 bids, so the vast majority of their bidding is not with the big bidder.
 
18
A Lagrange Multiplier test does not reject the null of homoskedasticity at the 5% level, a Hausman test of the normality of the Tobit does not reject the null at the 5% level, and Wald and Chi-squared tests fail to reject that pooling before and after is appropriate.
 
19
We also perform a U-test and a K-S test to examine the equality of the before and after interest rate distributions. The after big bid distribution stochastically dominates the before distribution.
 
20
A Lagrange Multiplier test does not reject the null of homoskedasticity at the 5% level; a Hausman test of the normality of the Tobit does not reject the null at the 5% level; and Wald and Chi-squared tests fail to reject that pooling before and after is appropriate.
 
21
The exception is for the 100% definition of a big bid, which funds the loan itself.
 
22
E listings have a mean request amount of $3295, while AA listings have a mean of $14,770.
 
23
These results are available from the authors upon request. Note that for the 100% definition, the Big Bid Pct variable must be removed.
 
24
The mean and median differences in the number of other active auctions are 42 and 35, respectively.
 
Literatur
Zurück zum Zitat Bonaldi, P., Hortaçsu, A., & Song, Z. (2015). An empirical test of auction efficiency: Evidence from MBS auctions of the federal reserve (Tech. Rep. No. Finance and Economic Discussion Series: 2015-085). Washington, DC: Board of Governors of the Federal Reserve Board. Bonaldi, P., Hortaçsu, A., & Song, Z. (2015). An empirical test of auction efficiency: Evidence from MBS auctions of the federal reserve (Tech. Rep. No. Finance and Economic Discussion Series: 2015-085). Washington, DC: Board of Governors of the Federal Reserve Board.
Zurück zum Zitat Davidson, R., & MacKinnon. (1993). Estimation and inference in econometrics. Oxford University Press. Davidson, R., & MacKinnon. (1993). Estimation and inference in econometrics. Oxford University Press.
Zurück zum Zitat Klafft, M. (2008). Peer to peer lending: Auctioning microcredits over the internet. In A. Agarwal & R. Khurana (Eds.), International conference on information systems, technology and management. Dubai. Klafft, M. (2008). Peer to peer lending: Auctioning microcredits over the internet. In A. Agarwal & R. Khurana (Eds.), International conference on information systems, technology and management. Dubai.
Zurück zum Zitat Nekipelov, D. (2007). Entry deterrence and learning prevention on eBay. Duke University Working Paper Series. Nekipelov, D. (2007). Entry deterrence and learning prevention on eBay. Duke University Working Paper Series.
Metadaten
Titel
Big Bids and Bidder Behavior in Uniform Price Auctions: Evidence from Peer-to-Peer Loan Markets
verfasst von
Garrett T. Senney
Jonathan R. Lhost
Publikationsdatum
18.08.2023
Verlag
Springer US
Erschienen in
Review of Industrial Organization / Ausgabe 3/2023
Print ISSN: 0889-938X
Elektronische ISSN: 1573-7160
DOI
https://doi.org/10.1007/s11151-023-09912-2

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