Quantile methods for first-price auction: A signal approach

Nathalie Gimenes () and Emmanuel Guerre

No 2016_23, Working Papers, Department of Economics from University of São Paulo (FEA-USP)

Abstract: This paper considers a quantile signal framework for first-price auction. Under the independent private value paradigm, a key stability property is that a linear specification for the private value conditional quantile function generates a linear specification for the bids one, from which it can be easily identified. This applies in particular for standard quantile regression models but also to more flexible additive sieve specification which are not affected by the curse of dimensionality. A combination of local polynomial and sieve methods allows to estimate the private value quantile function with a fast optimal rate and for all quantile levels in [0; 1] without boundary effects. The choice of the smoothing parameters is also discussed. Extensions to interdependent values including bidder specific variables are also possible under some functional restrictions, which tie up the signal to the bidder covariate. The identification of this new model is established and some estimation methods are suggested.

Keywords: First-price auction; independent private value; quantile regression; local polynomial estimation; sieve estimation; dimension reduction; boundary correction; interdependent values (search for similar items in EconPapers)
JEL-codes: C14 L70 (search for similar items in EconPapers)
Date: 2016-10-21
New Economics Papers: this item is included in nep-ecm
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Citations: View citations in EconPapers (10)

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