Nonparametric inference on counterfactuals in first-price auctions

Fuente: arXiv
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Autores principales: Andreyanov, Pasha, Franguridi, Grigory
Formato: Preprint
Publicado: 2021
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author Andreyanov, Pasha
Franguridi, Grigory
author_facet Andreyanov, Pasha
Franguridi, Grigory
contents In a classical model of the first-price sealed-bid auction with independent private values, we develop nonparametric estimators for several policy-relevant targets, such as the bidder's surplus and auctioneer's revenue under counterfactual reserve prices. Motivated by the linearity of these targets in the quantile function of bidders' values, we propose an estimator of the latter and derive its Bahadur-Kiefer expansion. This makes it possible to construct uniform confidence bands and test complex hypotheses about the auction design. Using the data on U.S. Forest Service timber auctions, we test whether setting zero reserve prices in these auctions was revenue maximizing.
format Preprint
id arxiv_https___arxiv_org_abs_2106_13856
institution arXiv
publishDate 2021
record_format arxiv
spellingShingle Nonparametric inference on counterfactuals in first-price auctions
Andreyanov, Pasha
Franguridi, Grigory
Econometrics
In a classical model of the first-price sealed-bid auction with independent private values, we develop nonparametric estimators for several policy-relevant targets, such as the bidder's surplus and auctioneer's revenue under counterfactual reserve prices. Motivated by the linearity of these targets in the quantile function of bidders' values, we propose an estimator of the latter and derive its Bahadur-Kiefer expansion. This makes it possible to construct uniform confidence bands and test complex hypotheses about the auction design. Using the data on U.S. Forest Service timber auctions, we test whether setting zero reserve prices in these auctions was revenue maximizing.
title Nonparametric inference on counterfactuals in first-price auctions
topic Econometrics
url https://arxiv.org/abs/2106.13856