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http://bura.brunel.ac.uk/handle/2438/27292| Title: | Improved Tests for Granger Non-Causality in Panel Data |
| Authors: | Xiao, J Karavias, Y Juodis, A Sarafidis, V Ditzen, J |
| Keywords: | st0706;xtgrangert;xtgrangert postestimation;panel data;Granger causality;Nickell bias;heterogeneous panels;half-panel jackknife;cross-section dependence |
| Issue Date: | 5-Apr-2023 |
| Publisher: | SAGE Publications |
| Citation: | Xiao, J. et al. (2023) 'Improved Tests for Granger Non-Causality in Panel Data', Stata Journal, 23, pp. 230 - 242. doi: 10.1177/1536867X231162034. |
| Abstract: | Copyright © Stata Corp LLC 2023. In this article, we introduce the xtgrangert command, which implements the panel Granger noncausality testing approach developed by Juodis, Karavias, and Sarafidis (2021, Empirical Economics 60: 93–112). This test offers superior size and power performance to existing tests, which stem from the use of a pooled estimator that has a faster √NT convergence rate. The test has several other useful properties: it can be used in multivariate systems; it has power against both homogeneous and heterogeneous alternatives; and it allows for cross-section dependence and cross-section heteroskedasticity. |
| Description: | Supplementary is available online at https://journals.sagepub.com/doi/10.1177/1536867X231162034#supplementary-materials . |
| URI: | https://bura.brunel.ac.uk/handle/2438/27292 |
| ISSN: | 1536-867X |
| Other Identifiers: | ORCID iDs: Yiannis Karavias https://orcid.org/0000-0002-1208-5537; Vasilis Sarafidis https://orcid.org/0000-0001-6808-3947. |
| Appears in Collections: | Dept of Economics and Finance Research Papers |
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| FullText.pdf | Copyright © Stata Corp LLC 2023. Rights and permissions: Creative Commons License (CC BY 4.0). This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). | 357.59 kB | Adobe PDF | View/Open |
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