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Asymptotic Moments of Autoregressive Estimators with a Near Unit Root and Minimax Risk

Essays in Honor of Peter C. B. Phillips

ISBN: 978-1-78441-183-1

ISSN: 0731-9053

Publication date: 21 November 2014

Abstract

These moments of the asymptotic distribution of the least-squares estimator of the local-to-unity autoregressive model are computed using computationally simple integration. These calculations show that conventional simulation estimation of moments can be substantially inaccurate unless the simulation sample size is very large. We also explore the minimax efficiency of autoregressive coefficient estimation, and numerically show that a simple Stein shrinkage estimator has minimax risk which is uniformly better than least squares, even though the estimation dimension is just one.

Keywords

Acknowledgements

Acknowledgement

Research supported by the National Science Foundation. I thank a referee for helpful comments.

Citation

Hansen, B.E. (2014), "Asymptotic Moments of Autoregressive Estimators with a Near Unit Root and Minimax Risk", Essays in Honor of Peter C. B. Phillips (Advances in Econometrics, Vol. 33), Emerald Group Publishing Limited, Bingley, pp. 3-21. https://doi.org/10.1108/S0731-905320140000033001

Publisher

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Emerald Group Publishing Limited

Copyright © 2014 Emerald Group Publishing Limited