Reference : The Empirical Saddlepoint Estimator
Scientific congresses, symposiums and conference proceedings : Unpublished conference
Business & economic sciences : Quantitative methods in economics & management
http://hdl.handle.net/10993/35091
The Empirical Saddlepoint Estimator
English
Holcblat, Benjamin mailto [University of Luxembourg > Faculty of Law, Economics and Finance (FDEF) > Luxembourg School of Finance (LSF) >]
Sowell, Fallaw mailto [Carnegie Mellon University > Tepper Business School]
17-Dec-2017
Previous studies have shown that existing moment-based estimation approaches have poor small-sample performance in some applications. We propose an alternative that is based on the ESP (empirical saddlepoint) approximation of the solutions to the empirical moment conditions. Saddlepoint approximations are known to perform well in small sample. The novel estimator proposed, which we call the ESP estimator, is the mode of the ESP approximation. We show that it is consistent and asymptotically normal, and we study its higher-order bias. We propose novel test statistics based on the ESP estimator. Finally, we also investigate the finite-sample properties of the ESP estimator and related test statistics through Monte-Carlo simulations.
No
International
2017 Computational Financial Econometrics Conference
16-18 December 2017
CFEnetwork, Birkbeck University of London and King's College London
London
UK
[en] Empirical saddlepoint approximation ; Moment-based estimation ; Small-sample asymptotic;
[en] Previous studies have shown that existing moment-based estimation approaches have poor small-sample performance in some applications. We propose an alternative that is based on the ESP (empirical saddlepoint) approximation of the solutions to the empirical moment conditions. Saddlepoint approximations are known to perform well in small sample. The novel estimator proposed, which we call the ESP estimator, is the mode of the ESP approximation. We show that it is consistent and asymptotically normal, and we study its higher-order bias. We propose novel test statistics based on the ESP estimator. Finally, we also investigate the finite-sample properties of the ESP estimator and related test statistics through Monte-Carlo simulations.
Researchers
http://hdl.handle.net/10993/35091

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