Quantile-Based Nonparametric Inference for First-Price Auctions

Marmer, Vadim and Shneyerov, Artyom (2006): Quantile-Based Nonparametric Inference for First-Price Auctions.

Abstract

We propose a quantile-based nonparametric approach to inference on the probability density function (PDF) of the private values in first-price sealed-bid auctions with independent private values. Our method of inference is based on a fully nonparametric kernel-based estimator of the quantiles and PDF of observable bids. Our estimator attains the optimal rate of Guerre, Perrigne, and Vuong (2000), and is also asymptotically normal with the appropriate choice of the bandwidth. As an application, we consider the problem of inference on the optimal reserve price.

• Item Type: MPRA Paper
• Institution: University of British Columbia
• Language: English
• Keywords: First-price auctions; independent private values; nonparametric estimation; kernel estimation; quantiles; optimal reserve price
• Subjects: C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C14 - Semiparametric and Nonparametric Methods: General; D - Microeconomics > D4 - Market Structure, Pricing, and Design > D44 - Auctions