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Procedia Computer Science
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Covid-19 Economic Vulnerability Index: EU Evidence

Authors: Joanna Brzyska; Izabela Szamrej-Baran;

Covid-19 Economic Vulnerability Index: EU Evidence

Abstract

The COVID-19 pandemic outbreak caused many negative effects on both the global and national economies. To implement effective policies to mitigate the negative impact of a pandemic, it is necessary to identify particularly vulnerable areas. The objective of this paper is to rank the EU countries in terms of the level of vulnerability of their economies to the impact of the pandemic. For this purpose, the COVID-19 Economic Vulnerability Index (CEVI) was constructed. It replaces the 15-dimensional set of characteristics of the countries with one aggregate, synthetic indicator estimated for 27 EU member states. In the study multivariate statistical methods, including agglomerative clustering and multi-attribute methods of object assessment were used to analyse the effects of the pandemic. The research shows that EU countries have different levels of economic vulnerability to the impact of the COVID-19 pandemic. The southern European countries (Spain, Croatia, Greece and Italy), where the tourism sector plays an important role in GDP composition, are the most fragile. Germany and the Scandinavian countries proved to be the least sensitive to the negative impact of the pandemic. The CEVI can be an important part of the decision support system. It enables the identification of countries that show greater vulnerability to the economic impact of the COVID-19 pandemic and may help support countries that need help the most. The proposed index also indicates certain areas in the country's economy that make it more vulnerable. The CEVI in combination with other instruments can be a very useful tool to improve the economy's resilience and help it recover faster in the event of a pandemic shock.

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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Top 10%
Average
Average
Green
gold