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Nonparametric identification in asymmetric second-price auctions: a new approach

Komarova, Tatiana (2009) Nonparametric identification in asymmetric second-price auctions: a new approach. In: Econ 370 Econometrics Seminar Series, 23 September 2009, Department of Economics, Stanford University, California, USA. (Unpublished)

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This paper proposes an approach to proving nonparametric identification in gen- eralized competing risks models. I focus on second-price auctions, which constitute a special case of these models, and analyze the identification of asymmetric distri- butions of bidders' values. I consider the situation where bidders have independent private values, and the only available data pertain to the winner's identity and to the winning price. I provide conditions on observable data sufficient to guarantee point identification. My identification proof is constructive and based on establishing the existence and uniqueness of a solution to the system of non-linear differential equa- tions that describes the relationships between unknown distribution functions and observable functions. I demonstrate how this approach can be extended to obtain identification in any generalized competing risks model. Moreover, contrary to classi- cal competing risks (Roy model) results, I describe how generalized models can yield implications that can help check for model misspecification.

Item Type: Conference or Workshop Item (Lecture)
Official URL:
Additional Information: © 2009 The Author
Subjects: H Social Sciences > HB Economic Theory
Q Science > QA Mathematics
JEL classification: C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods: General > C14 - Semiparametric and Nonparametric Methods
Sets: Departments > Economics
Collections > Economists Online
Date Deposited: 20 Feb 2012 12:34
Last Modified: 15 Jun 2017 11:26

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