Predicting the economic impact of the COVID-19 pandemic in the United Kingdom using time-series mining

Ahmed Rakha; Hansi Hettiarachchi; Dina Rady; Mohamed Medhat Gaber; Emad Rakha; Mohammed M. Abdelsamea

doi:10.3390/economies9040137

Predicting the economic impact of the COVID-19 pandemic in the United Kingdom using time-series mining

Ahmed Rakha
, Hansi Hettiarachchi
, Dina Rady
, Mohamed Medhat Gaber
, Emad Rakha
, Mohammed M. Abdelsamea^*

^*Corresponding author for this work

University of Nottingham
Birmingham City University
George Washington University
Galala University
Assiut University

Research output: Contribution to journal › Article › peer-review

18 Citations (SciVal)

Original language	English
Article number	137
Journal	Economies
Volume	9
Issue number	4
DOIs	https://doi.org/10.3390/economies9040137
Publication status	Published (VoR) - Dec 2021

Funding

We would like to thank Isabelle Bülthoff and Lewis Chuang for helpful discussions on earlier drafts of the manuscript. We gratefully acknowledge the support of the Humboldt Foundation (Feodor-Lynen Stipend to KSP), the Max Planck Society and the WCU (World Class University) program through the National Research Foundation of Korea funded by the Ministry of Education, Science and Technology (R31-2008-000-10008-0).

Keywords

COVID-19
Economic impacts
Gross domestic products
Industry
UK

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10.3390/economies9040137

Cite this

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title = "Predicting the economic impact of the COVID-19 pandemic in the United Kingdom using time-series mining",

keywords = "COVID-19, Economic impacts, Gross domestic products, Industry, UK",

author = "Ahmed Rakha and Hansi Hettiarachchi and Dina Rady and Gaber, \{Mohamed Medhat\} and Emad Rakha and Abdelsamea, \{Mohammed M.\}",

note = "Funding Information: We would like to thank Isabelle B{\"u}lthoff and Lewis Chuang for helpful discussions on earlier drafts of the manuscript. We gratefully acknowledge the support of the Humboldt Foundation (Feodor-Lynen Stipend to KSP), the Max Planck Society and the WCU (World Class University) program through the National Research Foundation of Korea funded by the Ministry of Education, Science and Technology (R31-2008-000-10008-0). Publisher Copyright: {\textcopyright} 2021 by the authors. Licensee MDPI, Basel, Switzerland.",

year = "2021",

month = dec,

doi = "10.3390/economies9040137",

language = "English",

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AU - Rakha, Ahmed

AU - Hettiarachchi, Hansi

AU - Rady, Dina

AU - Gaber, Mohamed Medhat

AU - Rakha, Emad

AU - Abdelsamea, Mohammed M.

N1 - Funding Information: We would like to thank Isabelle Bülthoff and Lewis Chuang for helpful discussions on earlier drafts of the manuscript. We gratefully acknowledge the support of the Humboldt Foundation (Feodor-Lynen Stipend to KSP), the Max Planck Society and the WCU (World Class University) program through the National Research Foundation of Korea funded by the Ministry of Education, Science and Technology (R31-2008-000-10008-0). Publisher Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

PY - 2021/12

Y1 - 2021/12

KW - COVID-19

KW - Economic impacts

KW - Gross domestic products

KW - Industry

KW - UK

UR - https://www.scopus.com/pages/publications/85117233782

UR - https://www.scopus.com/pages/publications/85117233782#tab=citedBy

U2 - 10.3390/economies9040137

DO - 10.3390/economies9040137

M3 - Article

AN - SCOPUS:85117233782

SN - 2227-7099

VL - 9

JO - Economies

JF - Economies

IS - 4

M1 - 137

ER -

Predicting the economic impact of the COVID-19 pandemic in the United Kingdom using time-series mining

Funding

Keywords

Access to Document

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