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Modelling volatility in job loss during the COVID-19 pandemic: the Malaysian case

This study employs a suitable volatility model that examines the impact of COVID-19 new cases and deaths on the volatility of daily job loss in Malaysia. Autoregressive Distributed Lag (ARDL) and Generalized Autoregressive Conditional Heteroscedasticity (GARCH) were employed as the modelling strateg...

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Main Authors: Habibullah, Muzafar Shah, Saari, Mohd Yusof, Maji, Ibrahim Kabiru, Haji Din, Badariah, Mohd Saudi, Nur Surayya
Format: Article
Language:English
Published: Taylor & Francis 2024
Online Access:http://psasir.upm.edu.my/id/eprint/105756/1/Modelling%20volatility%20in%20job%20loss%20during%20the%20COVID-19%20pandemic%20%20The%20Malaysian%20case.pdf
http://psasir.upm.edu.my/id/eprint/105756/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85181872386&doi=10.1080%2f23322039.2023.2291886&partnerID=40&md5=680052130e55f454fec9132f965f6788
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spelling my.upm.eprints.1057562024-08-20T06:40:47Z http://psasir.upm.edu.my/id/eprint/105756/ Modelling volatility in job loss during the COVID-19 pandemic: the Malaysian case Habibullah, Muzafar Shah Saari, Mohd Yusof Maji, Ibrahim Kabiru Haji Din, Badariah Mohd Saudi, Nur Surayya This study employs a suitable volatility model that examines the impact of COVID-19 new cases and deaths on the volatility of daily job loss in Malaysia. Autoregressive Distributed Lag (ARDL) and Generalized Autoregressive Conditional Heteroscedasticity (GARCH) were employed as the modelling strategy to estimate daily data from January to December 2020. In addition, the asymmetric GARCH-M (EGARCH-M, TGARCH-M, and PGARCH-M) were further applied. The findings from different versions of the ARDL(p,q1,q2)-(E,T,P)GARCH(1,1)-M model show that the ARDL-EGARCH-M model can capture the volatility and clustering of variability in job loss. The findings revealed asymmetry effects, suggesting that negative shocks (bad news) in a pandemic period increased volatility in job loss compared to positive shocks (good news). Policy implications relating to lockdown measures and news signals were provided. Taylor & Francis 2024-01 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/105756/1/Modelling%20volatility%20in%20job%20loss%20during%20the%20COVID-19%20pandemic%20%20The%20Malaysian%20case.pdf Habibullah, Muzafar Shah and Saari, Mohd Yusof and Maji, Ibrahim Kabiru and Haji Din, Badariah and Mohd Saudi, Nur Surayya (2024) Modelling volatility in job loss during the COVID-19 pandemic: the Malaysian case. Cogent Economics and Finance, 12 (1). pp. 1-26. ISSN 2332-2039 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85181872386&doi=10.1080%2f23322039.2023.2291886&partnerID=40&md5=680052130e55f454fec9132f965f6788 10.1080/23322039.2023.2291886
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description This study employs a suitable volatility model that examines the impact of COVID-19 new cases and deaths on the volatility of daily job loss in Malaysia. Autoregressive Distributed Lag (ARDL) and Generalized Autoregressive Conditional Heteroscedasticity (GARCH) were employed as the modelling strategy to estimate daily data from January to December 2020. In addition, the asymmetric GARCH-M (EGARCH-M, TGARCH-M, and PGARCH-M) were further applied. The findings from different versions of the ARDL(p,q1,q2)-(E,T,P)GARCH(1,1)-M model show that the ARDL-EGARCH-M model can capture the volatility and clustering of variability in job loss. The findings revealed asymmetry effects, suggesting that negative shocks (bad news) in a pandemic period increased volatility in job loss compared to positive shocks (good news). Policy implications relating to lockdown measures and news signals were provided.
format Article
author Habibullah, Muzafar Shah
Saari, Mohd Yusof
Maji, Ibrahim Kabiru
Haji Din, Badariah
Mohd Saudi, Nur Surayya
spellingShingle Habibullah, Muzafar Shah
Saari, Mohd Yusof
Maji, Ibrahim Kabiru
Haji Din, Badariah
Mohd Saudi, Nur Surayya
Modelling volatility in job loss during the COVID-19 pandemic: the Malaysian case
author_facet Habibullah, Muzafar Shah
Saari, Mohd Yusof
Maji, Ibrahim Kabiru
Haji Din, Badariah
Mohd Saudi, Nur Surayya
author_sort Habibullah, Muzafar Shah
title Modelling volatility in job loss during the COVID-19 pandemic: the Malaysian case
title_short Modelling volatility in job loss during the COVID-19 pandemic: the Malaysian case
title_full Modelling volatility in job loss during the COVID-19 pandemic: the Malaysian case
title_fullStr Modelling volatility in job loss during the COVID-19 pandemic: the Malaysian case
title_full_unstemmed Modelling volatility in job loss during the COVID-19 pandemic: the Malaysian case
title_sort modelling volatility in job loss during the covid-19 pandemic: the malaysian case
publisher Taylor & Francis
publishDate 2024
url http://psasir.upm.edu.my/id/eprint/105756/1/Modelling%20volatility%20in%20job%20loss%20during%20the%20COVID-19%20pandemic%20%20The%20Malaysian%20case.pdf
http://psasir.upm.edu.my/id/eprint/105756/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85181872386&doi=10.1080%2f23322039.2023.2291886&partnerID=40&md5=680052130e55f454fec9132f965f6788
_version_ 1809142947902390272
score 13.211869

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