ACM Home Page
Please provide us with feedback. Feedback
Efficiency of (revenue-)optimal mechanisms
Full text PdfPdf (391 KB)
Source
Electronic Commerce archive
Proceedings of the tenth ACM conference on Electronic commerce table of contents
Stanford, California, USA
SESSION: Session 7 table of contents
Pages 235-242  
Year of Publication: 2009
ISBN:978-1-60558-458-4
Authors
Gagan Aggarwal  Google Inc., Mountain View, CA, USA
Gagan Goel  Georgia Tech, Atlanta, GA, USA
Aranyak Mehta  Google Inc., Mountain View, CA, USA
Sponsors
ACM: Association for Computing Machinery
SIGEcom: ACM Special Interest Group on Electronic Commerce
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 10,   Downloads (12 Months): 34,   Citation Count: 0
Additional Information:

abstract   references   index terms   collaborative colleagues  

Tools and Actions: Request Permissions Request Permissions    Review this Article  
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/1566374.1566408
What is a DOI?

ABSTRACT

We compare the expected efficiency of revenue maximizing (or optimal) mechanisms with that of efficiency maximizing ones. We show that the efficiency of the revenue maximizing mechanism for selling a single item with (k + logeovere-1 k + 1) bidders is at least as much as the efficiency of the efficiency-maximizing mechanism with k bidders, when bidder valuations are drawn i.i.d. from a Monotone Hazard Rate distribution. Surprisingly, we also show that this bound is tight within a small additive constant of 4.7. In other words, Θ(log k) extra bidders suffice for the revenue-maximizing mechanism to match the efficiency of the efficiency-maximizing mechanism, while o(log k) do not. This is in contrast to the result of Bulow and Klemperer comparing the revenue of the two mechanisms, where only one extra bidder suffices. More precisely, they show that the revenue of the efficiency-maximizing mechanism with k + 1 bidders is no less than the revenue of the revenue-maximizing mechanism with k bidders.

We extend our result for the case of selling t identical items and show that Θ(log k) + t Θ(log log k) extra bidders suffice for the revenue-maximizing mechanism to match the efficiency of the efficiency-maximizing mechanism.

In order to prove our results, we do a classification of Monotone Hazard Rate (MHR) distributions and identify a family of MHR distributions, such that for each class in our classification, there is a member of this family that is pointwise lower than every distribution in that class. This lets us prove interesting structural theorems about distributions with Monotone Hazard Rate.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
J. Bulow and P. Klemperer. Auctions Versus Negotiations. AMERICAN ECONOMIC REVIEW. 86:180--194, 1996.
 
2
E. Clarke. Multipart pricing of public goods. Public Choice. 11(1):17--33, 1971.
 
3
T. Groves. Incentives in teams. Econometrica. 41(4):617--631, 1973.
4
 
5
R. Myerson. Optimal Auction Design. MATH. OPER. RES. 6(1):58--73, 1981.
 
6
Z. Neeman. The effectiveness of English auctions. Games and Economic Behavior. 43(2):214--238, 2003.
 
7
T. Roughgarden and M. Sundararaj. Is efficiency expensive. In Third Workshop on Sponsored Search Auctions, 2007.
 
8
W. Vickrey. Counterspeculation, auctions, and competitive sealed tenders. Journal of Finance. 16(1):8--37, 1961.
 
9
R. Zhan. Optimality and Efficiency in Auctions Design: A Survey.

Collaborative Colleagues:
Gagan Aggarwal: colleagues
Gagan Goel: colleagues
Aranyak Mehta: colleagues