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Bootstrap Model Averaging Unit Root Inference

Bruce E. Hansen (Department of Economics, University of Wisconsin, USA)

Jeffrey S. Racine (Department of Economics and Graduate Program in Statistics, McMaster University, Canada; Department of Economics and Finance, La Trobe University, Australia; Info-Metrics Institute, American University, USA; and Rimini Center for Economic Analysis, Italy)

Essays in Honor of Subal Kumbhakar

ISBN: 978-1-83797-874-8, eISBN: 978-1-83797-873-1

Publication date: 5 April 2024

Abstract

Classical unit root tests are known to suffer from potentially crippling size distortions, and a range of procedures have been proposed to attenuate this problem, including the use of bootstrap procedures. It is also known that the estimating equation’s functional form can affect the outcome of the test, and various model selection procedures have been proposed to overcome this limitation. In this chapter, the authors adopt a model averaging procedure to deal with model uncertainty at the testing stage. In addition, the authors leverage an automatic model-free dependent bootstrap procedure where the null is imposed by simple differencing (the block length is automatically determined using recent developments for bootstrapping dependent processes). Monte Carlo simulations indicate that this approach exhibits the lowest size distortions among its peers in settings that confound existing approaches, while it has superior power relative to those peers whose size distortions do not preclude their general use. The proposed approach is fully automatic, and there are no nuisance parameters that have to be set by the user, which ought to appeal to practitioners.

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Acknowledgements

Acknowledgments

Racine would like to gratefully acknowledge support from the Natural Sciences and Engineering Research Council of Canada (NSERC: www.nserc.ca), the Social Sciences and Humanities Research Council of Canada (SSHRC: www.sshrc.ca), and the Shared Hierarchical Academic Research Computing Network (SHARCNET: www.sharcnet.ca). Hansen thanks the National Science Foundation and the Phipps Chair for research support. We would like to thank but not implicate James MacKinnon, Rob Hyndman, and In Choi for their insight and encouragement.

Citation

Hansen, B.E. and Racine, J.S. (2024), "Bootstrap Model Averaging Unit Root Inference", Parmeter, C.F., Tsionas, M.G. and Wang, H.-J. (Ed.) Essays in Honor of Subal Kumbhakar (Advances in Econometrics, Vol. 46), Emerald Publishing Limited, Leeds, pp. 81-98. https://doi.org/10.1108/S0731-905320240000046005

Publisher

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Emerald Publishing Limited