A NONPARAMETRIC TEST FOR COMPARING VALUATION DISTRIBUTIONS IN FIRST-PRICE AUCTIONS.
This article proposes a nonparametric test for comparing valuation distributions in first-price auctions. Our test is motivated by the fact that two valuation distributions are the same if and only if their integrated quantile functions are the same. Our method avoids estimating unobserved valuation...
| Publicado en: | International Economic Review Vol. 58; no. 3; pp. 857 - 889 |
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| Autores principales: | , |
| Formato: | Artículo |
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Wiley-Blackwell
Aug2017
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=124834669&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 124834669 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 00206598 IER jtl: International Economic Review issn: 00206598 maglogo: Y pubinfo: dt: Aug2017 vid: 58 iid: 3 pid: 480 pub: Wiley-Blackwell artinfo: ui: 124834669 10.1111/iere.12238 ppf: 857 ppct: 32 formats: tig: atl: A NONPARAMETRIC TEST FOR COMPARING VALUATION DISTRIBUTIONS IN FIRST-PRICE AUCTIONS. aug: au: Liu, Nianqing Luo, Yao affil: Shanghai University of Finance and Economics, China, Key Laboratory of Mathematical Economics (SUFE), Ministry of Education of China, China University of Toronto, Canada su: United States. Forest Service Auctions Bids Cumulative distribution function Probability density function sug: subj: United States. Forest Service Auctions Bids Cumulative distribution function Probability density function ab: This article proposes a nonparametric test for comparing valuation distributions in first-price auctions. Our test is motivated by the fact that two valuation distributions are the same if and only if their integrated quantile functions are the same. Our method avoids estimating unobserved valuations and does not require smooth estimation of bid density. We show that our test is consistent against all fixed alternatives and has nontrivial power against root-N local alternatives. Monte Carlo experiments show that our test performs well in finite samples. We implement our method on data from U.S. Forest Service timber auctions. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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