Identifying common patterns via country clustering based on key macroeconomic indicators after banking crises
Banking crises have posed recurring global challenges over the past decades. The purpose of the article is to identify common patterns among countries after banking crises by clustering them based on the trajectories of key macroeconomic indicators and underlying dynamics during critical post-crisis...
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LLC "CPC "Business Perspectives"
2025-06-01
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| Series: | Banks and Bank Systems |
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| Online Access: | https://www.businessperspectives.org/images/pdf/applications/publishing/templates/article/assets/22380/BBS_2025_02_Ashurbayli-Huseynova.pdf |
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| author | Nigar Ashurbayli-Huseynova Nigar Guliyeva |
| author_facet | Nigar Ashurbayli-Huseynova Nigar Guliyeva |
| author_sort | Nigar Ashurbayli-Huseynova |
| collection | DOAJ |
| description | Banking crises have posed recurring global challenges over the past decades. The purpose of the article is to identify common patterns among countries after banking crises by clustering them based on the trajectories of key macroeconomic indicators and underlying dynamics during critical post-crisis periods. The study analyzes 50 selected countries based on historical banking crises, data availability, and balanced regional representation. Six crisis peaks are identified: 1990, 1998, 2008, 2015, 2020, and 2023. Recovery is assessed through 12 macroeconomic indicators – GDP growth, investment, government debt, unemployment, poverty, and banking sector health – sourced from World Bank data. Z-score standardization was applied in STATA 19.5. Using Sturges’ rule and Ward’s method in STATGRAPHICS 19, the clustering revealed country groups sharing similar crisis and post-crisis recovery patterns. The analysis of these 7 formed clusters and countries belonging to each allows us to determine common patterns explained through explicit and implicit common features. Explicit characteristics cover geography, development level, crisis timing, and implicit factors are financial market exposure, banking structures, commodity dependence, policy frameworks, etc. Key findings include persistent groupings (e.g., Albania remaining in the same cluster), countries in prolonged crisis (e.g., Ukraine, Venezuela), stable pairings (e.g., Argentina-Uruguay; Azerbaijan-Iraq-Qatar), and cluster shifts (e.g., Sweden, USA, Malaysia transitioning across crises). Positive recovery cases such as Iceland, Sweden, the USA, Norway, Malaysia, and Argentina demonstrate effective resolution strategies. These insights may inform future crisis response frameworks by identifying successful policy approaches and vulnerabilities tied to institutional and structural dynamics. |
| format | Article |
| id | doaj-art-57f2a63deca3420282ec0aea14ff6446 |
| institution | Kabale University |
| issn | 1816-7403 1991-7074 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | LLC "CPC "Business Perspectives" |
| record_format | Article |
| series | Banks and Bank Systems |
| spelling | doaj-art-57f2a63deca3420282ec0aea14ff64462025-08-20T03:33:14ZengLLC "CPC "Business Perspectives"Banks and Bank Systems1816-74031991-70742025-06-01202628210.21511/bbs.20(2).2025.0622380Identifying common patterns via country clustering based on key macroeconomic indicators after banking crisesNigar Ashurbayli-Huseynova0https://orcid.org/0000-0002-2641-7520Nigar Guliyeva1https://orcid.org/0000-0002-1495-0686Ph.D. in Economics, Associate Professor, Department of Applied Economics, Azerbaijan State University of Economics (UNEC), AzerbaijanPostgraduate Student, Department of Applied Economics, Azerbaijan State University of Economics (UNEC), AzerbaijanBanking crises have posed recurring global challenges over the past decades. The purpose of the article is to identify common patterns among countries after banking crises by clustering them based on the trajectories of key macroeconomic indicators and underlying dynamics during critical post-crisis periods. The study analyzes 50 selected countries based on historical banking crises, data availability, and balanced regional representation. Six crisis peaks are identified: 1990, 1998, 2008, 2015, 2020, and 2023. Recovery is assessed through 12 macroeconomic indicators – GDP growth, investment, government debt, unemployment, poverty, and banking sector health – sourced from World Bank data. Z-score standardization was applied in STATA 19.5. Using Sturges’ rule and Ward’s method in STATGRAPHICS 19, the clustering revealed country groups sharing similar crisis and post-crisis recovery patterns. The analysis of these 7 formed clusters and countries belonging to each allows us to determine common patterns explained through explicit and implicit common features. Explicit characteristics cover geography, development level, crisis timing, and implicit factors are financial market exposure, banking structures, commodity dependence, policy frameworks, etc. Key findings include persistent groupings (e.g., Albania remaining in the same cluster), countries in prolonged crisis (e.g., Ukraine, Venezuela), stable pairings (e.g., Argentina-Uruguay; Azerbaijan-Iraq-Qatar), and cluster shifts (e.g., Sweden, USA, Malaysia transitioning across crises). Positive recovery cases such as Iceland, Sweden, the USA, Norway, Malaysia, and Argentina demonstrate effective resolution strategies. These insights may inform future crisis response frameworks by identifying successful policy approaches and vulnerabilities tied to institutional and structural dynamics.https://www.businessperspectives.org/images/pdf/applications/publishing/templates/article/assets/22380/BBS_2025_02_Ashurbayli-Huseynova.pdfbankCOVID-19creditdebtfinancial crisisGDP |
| spellingShingle | Nigar Ashurbayli-Huseynova Nigar Guliyeva Identifying common patterns via country clustering based on key macroeconomic indicators after banking crises Banks and Bank Systems bank COVID-19 credit debt financial crisis GDP |
| title | Identifying common patterns via country clustering based on key macroeconomic indicators after banking crises |
| title_full | Identifying common patterns via country clustering based on key macroeconomic indicators after banking crises |
| title_fullStr | Identifying common patterns via country clustering based on key macroeconomic indicators after banking crises |
| title_full_unstemmed | Identifying common patterns via country clustering based on key macroeconomic indicators after banking crises |
| title_short | Identifying common patterns via country clustering based on key macroeconomic indicators after banking crises |
| title_sort | identifying common patterns via country clustering based on key macroeconomic indicators after banking crises |
| topic | bank COVID-19 credit debt financial crisis GDP |
| url | https://www.businessperspectives.org/images/pdf/applications/publishing/templates/article/assets/22380/BBS_2025_02_Ashurbayli-Huseynova.pdf |
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