Econometrics of Ascending Auctions by Quantile Regression

Nathalie Gimenes ()

No 2014_25, Working Papers, Department of Economics from University of São Paulo (FEA-USP)

Abstract: This paper suggests an identification and estimation approach based on quantile regression to recover the underlying distribution of bidders' private values in ascending auctions under the IPV paradigm. The quantile regression approach provides a flexible and convenient parametrization of the private values distribution, with an estimation methodology easy to implement and with several specification tests. The quantile framework provides a new focus on the quantile level of the private values distribution and on the seller's optimal screening level, which can be both useful for bidders and seller. The empirical application on timber auctions suggests that using policy recommendations from seller's expected payoff may be sometimes inappropriate from a seller's point of view due to the low probability of selling the good. This seems to be an important issue specially in auctions with strong heterogeneity among the bidders, since the seller has incentive to screen bidders' participation by setting a high reservation price, which in turn leads to a low probability of selling the good.

Keywords: Private values; timber auctions; ascending auctions; seller expected revenue; quantile regression identification; quantile regression estimation; quantile regression specification testing. (search for similar items in EconPapers)
JEL-codes: C14 D44 L70 (search for similar items in EconPapers)
Date: 2014-10-30
New Economics Papers: this item is included in nep-ecm
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Citations: View citations in EconPapers (3)

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