Paper Info
Title
On the convergence and robustness of reserve pricing in keyword auctions
Abstract
Reserve price becomes a critical issue in mechanism design of keyword auctions mostly because of the potential revenue increase brought up by it. In this paper, we focus on a sub-problem in reserve pricing, that is, how to estimate the bids distribution from the truncated samples and further calculate the optimal reserve price in an iterative setting. To the best of our knowledge, this is the first paper to discuss this problem. We propose to use maximum likelihood estimate (MLE) to solve the problem, and we prove that it is an unbiased method for distribution estimation. Moreover, we further simulate the iterative optimal reserve price calculating and updating process based on the estimated distribution. The experimental results are interpreted in terms of the robustness of MLE to truncated sample size and initial reserve price (truncated value), and the convergence of subsequent optimal reserve price in the iterative updating process is also discussed. We conclude that MLE is reliable enough to be applied in real-world optimal reserve pricing in keyword auctions.
Year
DOI
Venue
2012
10.1145/2346536.2346557
ICEC
Keywords
Field
DocType
iterative optimal reserve price,distribution estimation,bids distribution,keyword auction,subsequent optimal reserve price,real-world optimal reserve pricing,reserve price,optimal reserve price,reserve pricing,initial reserve price,maximum likelihood estimate,mechanism design,sample size,electronic commerce,mle
Revenue,Convergence (routing),Econometrics,Mathematical optimization,Reservation price,Computer science,Maximum likelihood,Robustness (computer science),Common value auction,Mechanism design,Truncation (statistics)
Conference
Citations 
PageRank 
References 
1
0.37
3
Authors
4
Name
Order
Citations
PageRank
Yang Sun14615.21
Yunhong Zhou2107076.69
Yin Ming311423.30
Xiaotie Deng43887340.99