Identification and Inference in First-Price Auctions with Risk-Averse Bidders and Selective Entry.
We study identification and inference in first-price auctions with risk-averse bidders and selective entry, building on a flexible framework we call the Affiliated Signal with Risk Aversion (AS-RA) model. Assuming exogenous variation in either the number of potential bidders (N) or a continuous inst...
| Publicado en: | Review of Economic Studies Vol. 93; no. 1; pp. 366 - 404 |
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| Autores principales: | , , , |
| Formato: | Artículo |
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Oxford University Press / USA
Jan2026
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| Materias: | |
| 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=191113077&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 191113077 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 00346527 REM jtl: Review of Economic Studies issn: 00346527 maglogo: N pubinfo: dt: Jan2026 vid: 93 iid: 1 pid: 622 pub: Oxford University Press / USA artinfo: ui: 191113077 10.1093/restud/rdaf016 ppf: 366 ppct: 38 formats: tig: atl: Identification and Inference in First-Price Auctions with Risk-Averse Bidders and Selective Entry. aug: au: Chen, Xiaohong Gentry, Matthew Li, Tong Lu, Jingfeng affil: Department of Economics, Yale University, USA Department of Economics, Florida State University, USA Department of Economics, Vanderbilt University, USA Department of Economics, National University of Singapore, Singapore su: Inference (Logic) Auctions Bidders Mathematical programming Nonparametric estimation Bidding strategies sug: subj: Inference (Logic) Auctions Bidders Mathematical programming Nonparametric estimation Bidding strategies keyword: Approximate profile likelihood-ratio Bayes credible sets Boundary condition Entry Flexible parametric form Frequentist confidence sets Identification MPEC Parameter-dependent support Risk aversion Set inference Approximate profile likelihood-ratio Bayes credible sets Boundary condition Entry Flexible parametric form Frequentist confidence sets Identification MPEC Parameter-dependent support Risk aversion Set inference ab: We study identification and inference in first-price auctions with risk-averse bidders and selective entry, building on a flexible framework we call the Affiliated Signal with Risk Aversion (AS-RA) model. Assuming exogenous variation in either the number of potential bidders (N) or a continuous instrument (z) shifting opportunity costs of entry, we provide a sharp characterization of the nonparametric restrictions implied by equilibrium bidding. This characterization implies that risk neutrality is nonparametrically testable. In addition, with sufficient variation in both N and z , the AS-RA model primitives are nonparametrically identified (up to a bounded constant) on their equilibrium domains. Finally, we explore new methods for inference in set-identified auction models based on Chen et al. (2018, Econometrica , vol. 86, 1965–2018), as well as novel and fast computational strategies using Mathematical Programming with Equilibrium Constraints. Simulation studies reveal the good finite-sample performance of our inference methods, which can readily be adapted to other set-identified flexible equilibrium models with parameter-dependent support. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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