Inference in Auctions with Many Bidders Using Transaction Prices

Fuente: arXiv
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Hauptverfasser: Bugni, Federico A., Wang, Yulong
Format: Preprint
Veröffentlicht: 2023
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author Bugni, Federico A.
Wang, Yulong
author_facet Bugni, Federico A.
Wang, Yulong
contents This paper studies inference in first-price and second-price sealed-bid auctions with many bidders, using an asymptotic framework where the number of bidders increases while the number of auctions remains fixed. Our approach enables asymptotically exact inference on key features, such as the winner's expected utility, the seller's expected revenue, and the tail of the valuation distribution, using only transaction price data. Our simulations demonstrate the accuracy of the methods in finite samples. We apply our methods to Hong Kong vehicle license auctions, focusing on high-priced, single-letter plates. Other relevant applications include online and art auctions.
format Preprint
id arxiv_https___arxiv_org_abs_2311_09972
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Inference in Auctions with Many Bidders Using Transaction Prices
Bugni, Federico A.
Wang, Yulong
Econometrics
This paper studies inference in first-price and second-price sealed-bid auctions with many bidders, using an asymptotic framework where the number of bidders increases while the number of auctions remains fixed. Our approach enables asymptotically exact inference on key features, such as the winner's expected utility, the seller's expected revenue, and the tail of the valuation distribution, using only transaction price data. Our simulations demonstrate the accuracy of the methods in finite samples. We apply our methods to Hong Kong vehicle license auctions, focusing on high-priced, single-letter plates. Other relevant applications include online and art auctions.
title Inference in Auctions with Many Bidders Using Transaction Prices
topic Econometrics
url https://arxiv.org/abs/2311.09972