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Analyzing the Impact of COVID-19 on Economic Sustainability: A Clustering Approach

Author

Listed:
  • Orietta Nicolis

    (Engineering Faculty, Universidad Andres Bello, Quillota 980, Viña del Mar 2520000, Chile
    Research Center for Integrated Disaster Risk Management (CIGIDEN), Santiago 8331150, Chile
    These authors contributed equally to this work.)

  • Jean Paul Maidana

    (Engineering Faculty, Universidad Andres Bello, Quillota 980, Viña del Mar 2520000, Chile
    These authors contributed equally to this work.)

  • Fabian Contreras

    (School of Engineering in Expedition Management and Ecotourism, Faculty of Natural Sciences, Universidad San Sebastián, Santiago 7510157, Chile
    These authors contributed equally to this work.)

  • Danilo Leal

    (Engineering Faculty, Universidad Andres Bello, Quillota 980, Viña del Mar 2520000, Chile
    Statistical Institute, Universidad de Valparaíso, Valparaíso 2340000, Chile
    These authors contributed equally to this work.)

Abstract
This work presents a comprehensive analysis of the economic impact of the COVID-19 pandemic, with a focus on OECD countries and the Chilean case. Utilizing a clustering approach, the research aims to investigate how countries can be categorized based on their pandemic mitigation strategies, economic responses, and infection rates. The methodology incorporates k-means and hierarchical clustering techniques, along with dynamic time warping, to account for the temporal variations in the pandemic’s progression across different nations. The study integrates the GDP into the analysis, thereby offering a perspective on the relationship between this economic indicator and health measures. Special attention is given to the case of Chile, thus providing a detailed examination of its economic and financial indicators during the pandemic. In particular, the work addresses the following main research questions: How can the OECD countries be clustered according to some health and economical indicators? What are the impacts of mitigation measures and the pension fund withdrawals on the Chilean economy? The study identifies significant differences ( p -value < 0.05%) in the GDPs and infection rates between the two identified clusters that are influenced by government measures, particularly in the banking sector (55% and 60% in clusters 1 and 2, respectively). In Chile, a rebound in the IMACEC index is noted after increased liquidity, especially following partial pension fund withdrawals, thereby aligning with discrepancies between model forecasts and actual data. This study provides important insights for evidence-based public policies, thus aiding decision makers in mitigating the socioeconomic impact of global health crises and offering strategic advice for a sustainable economy.

Suggested Citation

  • Orietta Nicolis & Jean Paul Maidana & Fabian Contreras & Danilo Leal, 2024. "Analyzing the Impact of COVID-19 on Economic Sustainability: A Clustering Approach," Sustainability, MDPI, vol. 16(4), pages 1-30, February.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:4:p:1525-:d:1337284
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    References listed on IDEAS

    as
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    4. Jena, Pradyot Ranjan & Majhi, Ritanjali & Kalli, Rajesh & Managi, Shunsuke & Majhi, Babita, 2021. "Impact of COVID-19 on GDP of major economies: Application of the artificial neural network forecaster," Economic Analysis and Policy, Elsevier, vol. 69(C), pages 324-339.
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