Events

Economics Seminar

Author:

• Emmanuel Guerre
  Queen Mary University of London

• Nathalie Gimenes
  Queen Mary University of London

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. This allows to estimate the optimal bidding strategy and all bidder’s private values near the boundaries with a fast rate. Extensions to binding reservation price and the case where only the winning bid is observed are considered. The choice of the smoothing parameters is also discussed. The framework also extends to a specification with interdependent values depending on a bidder specific covariate. In this model where dependence is parametrized through the signal copula function, a linear value quantile specification generates a linear bid quantile one with varying quantile slopes depending on all the bidder specific covariates. Averaging still allows to estimate the quantile function of the values with a fast rate.