The Position of European Union Countries According to Poverty Before and After the COVID-19 Crisis
Milan Marković
markovicmilan89@gmail.comUniversity of Niš, Innovation Centre of the University of Niš (Serbia)
Abstract
The purpose of the paper is to evaluate and present the position of the European Union countries according to the poverty level before and after the COVID-19 crisis, combining five individual indicators. The GRA (Grey Relational Analysis) method was used to calculate the composite poverty indicator. To assess poverty, the study uses criteria from the official database of the European Commission and calculates the aggregate index for 2019 and 2022. All criteria in the model have the same relative importance because the method of equal weight coefficients is applied. The paper proved that the Czech Republic and Slovenia had the most favourable indicators of poverty in both periods, while Greece, Romania, Bulgaria, and Latvia occupied a critical position. In general, the countries of Southern Europe and the Baltic countries have poor poverty indicators. Compared to 2019, according to the country rankings, the poverty level is significantly higher in Finland, Germany, and Hungary, while after the pandemic, the following countries made considerable progress in reducing poverty: Poland, Belgium, Luxembourg, and Cyprus. The presented results can be useful to decision-makers at the macro level in the field of economic, social, and sustainable development policy.
Keywords:
poverty, social sustainability, multi-criteria ranking, composite indicator, pandemic, European UnionReferences
ABIFARIN J., OFODU J., 2022, Modelling and grey relational multi-response optimization of chemical additives and engine parameters on performance efficiency of diesel engine, International Journal of Grey Systems, 2(1): 16-26, https://doi.org/10.52812/ijgs.33.
DOI: https://doi.org/10.52812/ijgs.33
Google Scholar
ALSHUWAIKHAT H.M., ADENLE Y.A., ALOTAISHAN T. N., 2023, The development of a grey relational analysis-based composite index for environmental sustainability assessment: Towards a net-zero emissions strategy in Saudi Ara-bia, Heliyon, 9(7): e18192. https://doi.org/10.1016/j.heliyon.2023.e18192.
DOI: https://doi.org/10.1016/j.heliyon.2023.e18192
Google Scholar
BÁRCENA-MARTÍN E., PÉREZ-MORENO S., RODRÍGUEZ-DÍAZ B., 2020, Rethinking multidimensional poverty through a multi-criteria analysis, Economic Modelling, 91: 313-325, https://doi.org/10.1016/j.econmod.2020.06.007.
DOI: https://doi.org/10.1016/j.econmod.2020.06.007
Google Scholar
BUHEJI M., DA COSTA CUNHA K., BEKA G., MAVRIC B., DE SOUZA Y.L., DA COSTA SILVA S.S., HANAFI M., YEIN T.C., 2020, The extent of covid-19 pandemic socio-economic impact on global poverty. a global inte-grative multidisciplinary review, American Journal of Economics, 10(4): 213-224, DOI: 10.5923/j.economics.20201004.02.
DOI: https://doi.org/10.5923/j.economics.20201004.02
Google Scholar
BURLINA C., RODRÍGUEZ-POSE A., 2024, Inequality, poverty, deprivation and the uneven spread of COVID-19 in Europe, Regional Studies, 58(2): 263-284, https://doi.org/10.1080/00343404.2023.2172390.
DOI: https://doi.org/10.1080/00343404.2023.2172390
Google Scholar
ĐOKIĆ M., 2022, World economy in the time of pandemic: Consequences of COVID-19 on world output, trade and employment, Economics of Sustainable Development, 6(1): 57-72, https://doi.org/10.5937/ESD2201057D.
DOI: https://doi.org/10.5937/ESD2201057D
Google Scholar
DRAGO C., 2021, The analysis and the measurement of poverty: An interval-based composite indicator approach, Econ-omies, 9(4): 145, https://doi.org/10.3390/economies9040145.
DOI: https://doi.org/10.3390/economies9040145
Google Scholar
EUROPEAN COMMISSION, 2024, Eurostat database, https://ec.europa.eu/eurostat/data/database (5.5.2024).
Google Scholar
GOEDEMÉ T., DECERF B., VAN DEN BOSCH K., 2022, A new poverty indicator for Europe: The extended head-count ratio, Journal of European social policy, 32(3): 287-301, https://doi.org/10.1177/09589287221080414.
DOI: https://doi.org/10.1177/09589287221080414
Google Scholar
HERMAN E., 2014, Working poverty in the European Union and its main determinants: An empirical analysis, Engineer-ing Economics, 25(4): 427-436, https://doi.org/10.5755/j01.ee.25.4.6339.
DOI: https://doi.org/10.5755/j01.ee.25.4.6339
Google Scholar
JOZIĆ S., BAJIĆ D., CELENT L., 2015, Application of compressed cold air cooling: achieving multiple performance characteristics in end milling process, Journal of Cleaner Production, 100: 325-332, https://doi.org/10.1016/j.jclepro.2015.03.095.
DOI: https://doi.org/10.1016/j.jclepro.2015.03.095
Google Scholar
KOVÁŘOVÁ E., 2023, The EU Countries’ Assessment with Respect to the Prevalence of Severe Material Deprivation and Determinants of Poverty: Application of Non-parametric DEA Approach, Revija za socijalnu politiku, 30(3): 271-291, https://doi.org/10.3935/rsp.v30i3.1840.
DOI: https://doi.org/10.3935/rsp.v30i3.1840
Google Scholar
KUO Y., YANG T., HUANG G.W., 2008, The use of grey relational analysis in solving multiple attribute decision-making problems, Computers & Industrial Engineering, 55(1): 80-93, https://doi.org/10.1016/j.cie.2007.12.002.
DOI: https://doi.org/10.1016/j.cie.2007.12.002
Google Scholar
ŁUCZAK A., KALINOWSKI S., 2020, Assessing the level of the material deprivation of European Union countries, Plos one, 15(9): e0238376, https://doi.org/10.1371/journal.pone.0238376.
DOI: https://doi.org/10.1371/journal.pone.0238376
Google Scholar
MARKOVIĆ M., POPOVIĆ Z., MARJANOVIĆ I., 2023, Towards a circular economy: evaluation of waste management performance in European Union countries, Serbian Journal of Management, 18(1): 45-57, https://doi.org/10.5937/sjm18-40073.
DOI: https://doi.org/10.5937/sjm18-40073
Google Scholar
MARKOVIĆ M., STANKOVIĆ J.J., DIGKOGLOU P., MARJANOVIĆ I., 2022, Evaluation of Social Protection Per-formance in EU Countries: Multiple-criteria Decision Analysis (MCDA), Problemy Ekorozwoju – Problems of Sustaina-ble Development, 17(2): 124-132, https://doi.org/10.35784/pe.2022.2.13.
DOI: https://doi.org/10.35784/pe.2022.2.13
Google Scholar
MENSHIKOV V., KOKINA I., KOMAROVA V., RUZA O., DANILEVIČA A., 2020, Measuring multidimensional poverty within the resource-based approach: a case study of Latgale region, Latvia, Entrepreneurship and Sustainability Issues, 8(2): 1211-1227, https://nbn-resolving.org/urn:nbn:de:0168-ssoar-88139-3.
DOI: https://doi.org/10.9770/jesi.2020.8.2(72)
Google Scholar
MICHÁLEK A., 2023, Changes in the social situation in EU countries during COVID‐19 (an alternative approach to the assessment of social indicators), Regional Science Policy & Practice, 15(8): 1841-1863, https://doi.org/10.1111/rsp3.12683.
DOI: https://doi.org/10.1111/rsp3.12683
Google Scholar
MISHRA N.P., DAS S.S., YADAV S., KHAN W., AFZAL M., ALARIFI A., KENAWY E.R., ANSARI M.T., HASNAIN M.S., NAYAK A.K., 2020, Global impacts of pre-and post-COVID-19 pandemic: Focus on socio-economic consequences, Sensors International, 1: 100042, https://doi.org/10.1016/j.sintl.2020.100042.
DOI: https://doi.org/10.1016/j.sintl.2020.100042
Google Scholar
ROCCHI L., RICCIOLINI E., MASSEI G., PAOLOTTI L., BOGGIA A., 2022, Towards the 2030 Agenda: measuring the progress of the European Union countries through the SDGs achievement index, Sustainability, 14(6): 3563, https://doi.org/10.3390/su14063563.
DOI: https://doi.org/10.3390/su14063563
Google Scholar
STANKOVIĆ J.J., DŽUNIĆ M., MARJANOVIĆ I., 2022, Towards an Inclusive Europe: Ranking European Countries Based on Social Sustainability Indicators, In International Conference on Decision Support System Technology, Cham, Springer International Publishing: 84-96.
DOI: https://doi.org/10.1007/978-3-031-06530-9_7
Google Scholar
WORLD HEALTH ORGANIZATION, 2023, https://www.who.int/director-general/speeches/detail/who-director-general-dr-tedros-end-of-2023-message--keeping-the-hope-for-health-alive (10.5.2024).
Google Scholar
UNITED NATIONS DEVELOPMENT PROGRAMME, 2024, Goal 1 – No poverty, https://www.undp.org/sustainable-development-goals/no-poverty (10.5.2024).
Google Scholar
YAMAOKA Y., ISUMI A., DOI S., OCHI M., FUJIWARA T., 2021, Differential effects of multiple dimensions of poverty on child behavioral problems: results from the A-CHILD study, International Journal of Environmental Research and Public Health, 18(22): 11821, https://doi.org/10.3390/ijerph182211821.
DOI: https://doi.org/10.3390/ijerph182211821
Google Scholar
ZINS S., 2020, Variance Estimation by Linearisation for the At Risk of Poverty or Social Exclusion (AROPE) Rate, Aus-trian Journal of Statistics, 49(1): 33-44, http://dx.doi.org/10.17713/ajs.v49i1.882.
DOI: https://doi.org/10.17713/ajs.v49i1.882
Google Scholar
Authors
Milan Markovićmarkovicmilan89@gmail.com
University of Niš, Innovation Centre of the University of Niš Serbia
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