Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/27291
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dc.contributor.authorKaravias, Y-
dc.contributor.authorNarayan, PK-
dc.contributor.authorWesterlund, J-
dc.date.accessioned2023-10-02T12:47:58Z-
dc.date.available2023-10-02T12:47:58Z-
dc.date.issued2022-04-08-
dc.identifierORCID iDs: Yiannis Karavias https://orcid.org/0000-0002-1208-5537; Paresh Kumar Narayan https://orcid.org/0000-0001-7934-8146-
dc.identifier.citationKaravias, Y., Narayan, P.Y. and Westerlund, J. (2022) 'Structural Breaks in Interactive Effects Panels and the Stock Market Reaction to COVID-19', Journal of Business & Economic Statistics, 41 (3), pp. 653 - 666. doi: 10.1080/07350015.2022.2053690.en_US
dc.identifier.issn0735-0015-
dc.identifier.urihttps://bura.brunel.ac.uk/handle/2438/27291-
dc.descriptionSupplementary materials are available online at https://www.tandfonline.com/doi/full/10.1080/07350015.2022.2053690#supplemental-material-section .en_US
dc.description.abstractCopyright © 2022 The Authors. Dealing with structural breaks is an essential step in most empirical economic research. This is particularly true in panel data comprised of many cross-sectional units, which are all affected by major events. The COVID-19 pandemic has affected most sectors of the global economy; however, its impact on stock markets is still unclear. Most markets seem to have recovered while the pandemic is ongoing, suggesting that the relationship between stock returns and COVID-19 has been subject to structural break. It is therefore important to know if a structural break has occurred and, if it has, to infer the date of the break. Motivated by this last observation, the present article develops a new break detection toolbox that is applicable to different sized panels, easy to implement and robust to general forms of unobserved heterogeneity. The toolbox, which is the first of its kind, includes a structural change test, a break date estimator, and a break date confidence interval. Application to a panel covering 61 countries from January 3 to September 25, 2020, leads to the detection of a structural break that is dated to the first week of April. The effect of COVID-19 is negative before the break and zero thereafter, implying that while markets did react, the reaction was short-lived. A possible explanation is the quantitative easing programs announced by central banks all over the world in the second half of March.en_US
dc.description.sponsorshipKnut and Alice Wallenberg Foundation for financial support through a Wallenberg Academy Fellowship.en_US
dc.format.extent653 - 666-
dc.format.mediumPrint-Electronic-
dc.languageEnglish-
dc.language.isoen_USen_US
dc.publisherRoutledge (Taylor & Francis Group)en_US
dc.rightsCopyright © 2022 The Authors. Published with license by Taylor & Francis Group, LLC. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.-
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/-
dc.subjectchange-pointen_US
dc.subjectcommon correlated effectsen_US
dc.subjectCOVID-19en_US
dc.subjectcross-section dependenceen_US
dc.subjectpanel dataen_US
dc.subjectstructural changeen_US
dc.titleStructural Breaks in Interactive Effects Panels and the Stock Market Reaction to COVID-19en_US
dc.typeArticleen_US
dc.identifier.doihttps://doi.org/10.1080/07350015.2022.2053690-
dc.relation.isPartOfJournal of Business & Economic Statistics-
pubs.issue3-
pubs.publication-statusPublished-
pubs.volume41-
dc.identifier.eissn1537-2707-
dc.rights.holderThe Authors-
Appears in Collections:Dept of Economics and Finance Research Papers

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