Cookies?
Library Header Image
LSE Research Online LSE Library Services

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

Komarova, Tatiana ORCID: 0000-0002-6581-5097 (2009) Nonparametric identification in asymmetric second-price auctions: a new approach. In: Econ 370 Econometrics Seminar Series, 2009-09-23, California, United States. (Submitted)

Full text not available from this repository.

Abstract

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 (Other)
Official URL: http://economics.stanford.edu/seminars/
Additional Information: © 2009 The Author
Divisions: Economics
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
Date Deposited: 20 Feb 2012 12:34
Last Modified: 15 Sep 2023 08:26
URI: http://eprints.lse.ac.uk/id/eprint/41947

Actions (login required)

View Item View Item