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Thematic Sessions<br />
ST4: Econometrics<br />
Chair: Marcelo Fernandes<br />
Thursday, September 5th<br />
10:30<br />
Semiparametric Quantile Models for Ascending<br />
Auctions with Asymmetric Bidders<br />
Nathalie Gimenes<br />
PUC/Rio<br />
Asymmetry is a relevant question when bidders of different sizes and technological capability are<br />
competing at the same auction. This issue is especially important if the econometrician provides<br />
the seller with a policy recommendation (auction optimal design) based on a misspecified symmetric<br />
setup, which may bring a significant expected loss to the seller, depending on the degree of<br />
asymmetry. Therefore, a parsimonious and easy estimation approach that accounts for bidders<br />
asymmetry can be very useful for policy analysis. In this paper, we suggest an identification and<br />
estimation approach to recover the latent private value conditional quantile function when bidders<br />
are asymmetric. The estimation strategy is done in two steps: in the first-step, the asymmetric<br />
parameters are estimated via maximum likelihood method; and then used in the second-step to<br />
estimate the type private value conditional quantile functions. The methodology is illustrated using<br />
USFS timber ascending auctions. According to our estimates, Loggers (firms lacking technological<br />
capability to process the timber) provides the US Government with an expected revenue on average<br />
14% lower than Mills.<br />
Keywords: Private values; Asymmetry; Ascending auctions; Seller expected revenue; Quantile<br />
regression identification; Quantile regression estimation<br />
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