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http://bura.brunel.ac.uk/handle/2438/32193| Title: | Generalized fixed-T panel unit root tests |
| Authors: | Karavias, Y Tzavalis, E |
| Keywords: | fixed T;nonlinear trends;panel data;serial correlation;structural breaks;unit root |
| Issue Date: | 12-Mar-2019 |
| Publisher: | Wiley on behalf of Board of the Foundation of the Scandinavian Journal of Statistics |
| Citation: | Karavias, Y. and Tzavalis, E. (2019) 'Generalized fixed-T panel unit root tests', Scandinavian Journal of Statistics, 46 (4), pp. 1227 - 1251. doi: 10.1111/sjos.12392. |
| Abstract: | Panel data unit root tests, which can be applied to data that do not have many time series observations, are based on very restrictive error and deterministic component specification assumptions. In this paper, we develop a new, doubly modified estimator, based on which we propose a panel unit root test that allows for multiple structural breaks, linear and nonlinear trends, heteroscedasticity, serial correlation, and error cross-section heterogeneity, when the number of time series observations is finite. The test has the additional perk that it is invariant to the initial condition. |
| URI: | https://bura.brunel.ac.uk/handle/2438/32193 |
| DOI: | https://doi.org/10.1111/sjos.12392 |
| ISSN: | 0303-6898 |
| Other Identifiers: | ORCiD: Yiannis Karavias https://orcid.org/0000-0002-1208-5537 |
| Appears in Collections: | Dept of Economics and Finance Research Papers |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| FullText.pdf | Copyright © 2019 Board of the Foundation of the Scandinavian Journal of Statistics. This is the peer reviewed version of the following article: Karavias Y, Tzavalis E. Generalized fixed-T panel unit root tests. Scand J Statist. 2019; 46: 1227–1251, which has been published in final form at https://doi.org/10.1111/sjos.12392. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions (see: https://authorservices.wiley.com/author-resources/Journal-Authors/licensing/self-archiving.html ). | 387.25 kB | Adobe PDF | View/Open |
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