Artikel
Predicting the economic impact of the COVID-19 pandemic in the United Kingdom using time-series mining
The COVID-19 pandemic has brought economic activity to a near standstill as many countries imposed very strict restrictions on movement to halt the spread of the virus. This study aims at assessing the economic impacts of COVID-19 in the United Kingdom (UK) using artificial intelligence (AI) and data from previous economic crises to predict future economic impacts. The macroeconomic indicators, gross domestic products (GDP) and GDP growth, and data on the performance of three primary industries in the UK (the construction, production and service industries) were analysed using a comparison with the pattern of previous economic crises. In this research, we experimented with the effectiveness of both continuous and categorical time-series forecasting on predicting future values to generate more accurate and useful results in the economic domain. Continuous value predictions indicate that GDP growth in 2021 will remain steady, but at around −8.5% contraction, compared to the baseline figures before the pandemic. Further, the categorical predictions indicate that there will be no quarterly drop in GDP following the first quarter of 2021. This study provided evidence-based data on the economic effects of COVID-19 that can be used to plan necessary recovery procedures and to take appropriate actions to support the economy.
- Language
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Englisch
- Bibliographic citation
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Journal: Economies ; ISSN: 2227-7099 ; Volume: 9 ; Year: 2021 ; Issue: 4 ; Pages: 1-19 ; Basel: MDPI
- Classification
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Wirtschaft
- Subject
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COVID-19
economic impacts
gross domestic products
industry
- Event
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Geistige Schöpfung
- (who)
-
Rakha, Ahmed
Hettiarachchi, Hansi
Rady, Dina
Gaber, Mohamed Medhat
Rakha, Emad
Abdelsamea, Mohammed M.
- Event
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Veröffentlichung
- (who)
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MDPI
- (where)
-
Basel
- (when)
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2021
- DOI
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doi:10.3390/economies9040137
- Handle
- Last update
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10.03.2025, 11:44 AM CET
Data provider
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Artikel
Associated
- Rakha, Ahmed
- Hettiarachchi, Hansi
- Rady, Dina
- Gaber, Mohamed Medhat
- Rakha, Emad
- Abdelsamea, Mohammed M.
- MDPI
Time of origin
- 2021
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