Covid-19 Economic vulnerability index : EU evidence

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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.

Tytuł
Covid-19 Economic vulnerability index : EU evidence
Twórca
Brzyska Joanna ORCID 0000-0003-3589-6313
Słowa kluczowe
economic vulnerability; COVID-19 pandemic; multivariate statistical methods; synthetic measure; wrażliwość ekonomiczna; pandemia COVID-19; wielowymiarowa analiza statystyczna; zmienna syntetyczna
Współtwórca
Szamrej-Baran Izabela ORCID 0000-0002-9824-362X
Data
2021
Typ zasobu
artykuł
Identyfikator zasobu
DOI 10.1016/j.procs.2021.09.128
Źródło
Procedia Computer Science, 2021, vol.192, pp. 3551-3559
Język
angielski
Prawa autorskie
CC BY-NC-ND CC BY-NC-ND
Kategorie
Publikacje pracowników US
Data udostępnienia11 paź 2021, 13:55:09
Data mod.11 paź 2021, 13:55:09
DostępPubliczny
Aktywnych wyświetleń0