Causal inference for the impact of economic policy on financial and labour markets amid the COVID-19 pandemic

Vo, NNY; Xu, G; Le, DA

Causal inference for the impact of economic policy on financial and labour markets amid the COVID-19 pandemic

Vo, NNY Xu, G

Le, DA

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Publisher:: IOS Press
Publication Type:: Journal Article
Citation:: Web Intelligence, 2022, 20, (1), pp. 1-19
Issue Date:: 2022-01-01

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Field	Value	Language
dc.contributor.author	Vo, NNY
dc.contributor.author	Xu, G https://orcid.org/0000-0003-4493-6663
dc.contributor.author	Le, DA
dc.date.accessioned	2022-08-25T10:48:47Z
dc.date.available	2022-08-25T10:48:47Z
dc.date.issued	2022-01-01
dc.identifier.citation	Web Intelligence, 2022, 20, (1), pp. 1-19
dc.identifier.issn	2405-6456
dc.identifier.issn	2405-6464
dc.identifier.uri	http://hdl.handle.net/10453/160865
dc.description.abstract	The COVID-19 pandemic has turned the world upside down since the beginning of 2020, leaving most nations worldwide in both health crises and economic recession. Governments have been continually responding with multiple support policies to help people and businesses overcoming the current situation, from 'Containment', 'Health' to 'Economic' policies, and from local and national supports to international aids. Although the pandemic damage is still not under control, it is essential to have an early investigation to analyze whether these measures have taken effects on the early economic recovery in each nation, and which kinds of measures have made bigger impacts on reducing such negative downturn. Therefore, we conducted a time series based causal inference analysis to measure the effectiveness of these policies, specifically focusing on the 'Economic support' policy on the financial markets for 80 countries and on the United States and Australia labour markets. Our results identified initial positive causal relationships between these policies and the market, providing a perspective for policymakers and other stakeholders.
dc.language	en
dc.publisher	IOS Press
dc.relation.ispartof	Web Intelligence
dc.relation.isbasedon	10.3233/WEB-210477
dc.rights	© Vo, Nhi N.Y., Xu, Guandong, and Le, Dat Anh 2022. The definitive, peer reviewed and edited version of this article is published in Web Intelligence, vol. 20, no. 1, 1-19, 2022, 10.3233/WEB-210477. 2.3. Any other use is subject to a permission from IOS Press B.V. 2.4.
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	0801 Artificial Intelligence and Image Processing, 0899 Other Information and Computing Sciences, 1702 Cognitive Sciences
dc.subject.classification	Artificial Intelligence & Image Processing
dc.title	Causal inference for the impact of economic policy on financial and labour markets amid the COVID-19 pandemic
dc.type	Journal Article
utslib.citation.volume	20
utslib.for	0801 Artificial Intelligence and Image Processing
utslib.for	0899 Other Information and Computing Sciences
utslib.for	1702 Cognitive Sciences
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - AAI - Advanced Analytics Institute Research Centre
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
utslib.copyright.status	open_access	*
dc.date.updated	2022-08-25T10:48:45Z
pubs.issue	1
pubs.publication-status	Published
pubs.volume	20
utslib.citation.issue	1

Abstract:

The COVID-19 pandemic has turned the world upside down since the beginning of 2020, leaving most nations worldwide in both health crises and economic recession. Governments have been continually responding with multiple support policies to help people and businesses overcoming the current situation, from 'Containment', 'Health' to 'Economic' policies, and from local and national supports to international aids. Although the pandemic damage is still not under control, it is essential to have an early investigation to analyze whether these measures have taken effects on the early economic recovery in each nation, and which kinds of measures have made bigger impacts on reducing such negative downturn. Therefore, we conducted a time series based causal inference analysis to measure the effectiveness of these policies, specifically focusing on the 'Economic support' policy on the financial markets for 80 countries and on the United States and Australia labour markets. Our results identified initial positive causal relationships between these policies and the market, providing a perspective for policymakers and other stakeholders.

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http://hdl.handle.net/10453/160865