Order Statistics Approaches to Unobserved Heterogeneity in Auctions

56 Pages Posted: 6 Jan 2021 Last revised: 22 Oct 2021

See all articles by Yao Luo

Yao Luo

University of Toronto - Department of Economics

Peijun Sang

University of Waterloo - Department of Statistics and Actuarial Science

Ruli Xiao

Indiana University; Indiana University

Date Written: September 8, 2021

Abstract

We establish nonparametric identification of auction models with continuous unobserved heterogeneity using either three consecutive order statistics of bids or two with an instrument. We then propose sieve maximum likelihood estimators for the joint distribution of unobserved heterogeneity and private value, as well as their conditional and marginal distributions. Lastly, we apply our methodology to a novel dataset from judicial auctions in China. Our estimates suggest substantial gains from accounting for unobserved heterogeneity when setting reserve prices. We propose a simple scheme that achieves nearly optimal revenue by using the appraisal value as the reserve price.

Keywords: Sieve Estimation, Nonseparable, Measurement Error, Consecutive Order Statistics

JEL Classification: C14, D44

Suggested Citation

Luo, Yao and Sang, Peijun and Xiao, Ruli and Xiao, Ruli, Order Statistics Approaches to Unobserved Heterogeneity in Auctions (September 8, 2021). Available at SSRN: https://ssrn.com/abstract=3704644 or http://dx.doi.org/10.2139/ssrn.3704644

Yao Luo

University of Toronto - Department of Economics ( email )

150 St. George Street
Toronto, Ontario M5S3G7
Canada

Peijun Sang

University of Waterloo - Department of Statistics and Actuarial Science ( email )

200 University Avenue West
Waterloo, Ontario N2L 3G1
Croatia

Ruli Xiao (Contact Author)

Indiana University ( email )

Wylie Hall
Bloomington, IN 47405-6620
United States

Indiana University ( email )

100 S Woodlawn Ave
Bloomington, IN 47405
United States

HOME PAGE: http://https://sites.google.com/site/iueconomicsrulixiao/

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