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Uncertainty Analysis of Business Interruption Losses in the Philippines Due to the COVID-19 Pandemic

Author

Listed:
  • Joost R. Santos

    (Department of Engineering Management and Systems Engineering, George Washington University, Washington, DC 20052, USA)

  • John Frederick D. Tapia

    (Department of Chemical Engineering, De La Salle University, Manila 0922, Philippines)

  • Albert Lamberte

    (School of Economics, De La Salle University, Manila 0922, Philippines)

  • Christine Alyssa Solis

    (School of Economics, De La Salle University, Manila 0922, Philippines)

  • Raymond R. Tan

    (Department of Chemical Engineering, De La Salle University, Manila 0922, Philippines)

  • Kathleen B. Aviso

    (Department of Chemical Engineering, De La Salle University, Manila 0922, Philippines)

  • Krista Danielle S. Yu

    (School of Economics, De La Salle University, Manila 0922, Philippines)

Abstract

In this study, we utilize an input–output (I–O) model to perform an ex-post analysis of the COVID-19 pandemic workforce disruptions in the Philippines. Unlike most disasters that debilitate physical infrastructure systems, the impact of disease pandemics like COVID-19 is mostly concentrated on the workforce. Workforce availability was adversely affected by lockdowns as well as by actual illness. The approach in this paper is to use Philippine I–O data for multiple years and generate Dirichlet probability distributions for the Leontief requirements matrix (i.e., the normalized sectoral transactions matrix) to address uncertainties in the parameters. Then, we estimated the workforce dependency ratio based on a literature survey and then computed the resilience index in each economic sector. For example, sectors that depend heavily on the physical presence of their workforce (e.g., construction, agriculture, manufacturing) incur more opportunity losses compared to sectors where workforce can telework (e.g., online retail, education, business process outsourcing). Our study estimated the 50th percentile economic losses in the range of PhP 3.3 trillion (with telework) to PhP 4.8 trillion (without telework), which is consistent with independently published reports. The study provides insights into the direct and indirect economic impacts of workforce disruptions in emerging economies and will contribute to the general domain of disaster risk management.

Suggested Citation

  • Joost R. Santos & John Frederick D. Tapia & Albert Lamberte & Christine Alyssa Solis & Raymond R. Tan & Kathleen B. Aviso & Krista Danielle S. Yu, 2022. "Uncertainty Analysis of Business Interruption Losses in the Philippines Due to the COVID-19 Pandemic," Economies, MDPI, vol. 10(8), pages 1-18, August.
    • Handle: RePEc:gam:jecomi:v:10:y:2022:i:8:p:202-:d:892378
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    References listed on IDEAS

    as
    1. Krista Danielle S. Yu & Kathleen B. Aviso & Joost R. Santos & Raymond R. Tan, 2020. "The Economic Impact of Lockdowns: A Persistent Inoperability Input-Output Approach," Economies, MDPI, vol. 8(4), pages 1-14, December.
    2. Neil M. Ferguson & Derek A. T. Cummings & Christophe Fraser & James C. Cajka & Philip C. Cooley & Donald S. Burke, 2006. "Strategies for mitigating an influenza pandemic," Nature, Nature, vol. 442(7101), pages 448-452, July.
    3. Albala-Bertrand, J. M., 1993. "Political Economy of Large Natural Disasters: With Special Reference to Developing Countries," OUP Catalogue, Oxford University Press, number 9780198287650.
    4. Yasuhide Okuyama & Joost R. Santos, 2014. "Disaster Impact And Input--Output Analysis," Economic Systems Research, Taylor & Francis Journals, vol. 26(1), pages 1-12, March.
    5. Jalal Ali & Joost R. Santos, 2015. "Modeling the Ripple Effects of IT‐Based Incidents on Interdependent Economic Systems," Systems Engineering, John Wiley & Sons, vol. 18(2), pages 146-161, March.
    6. Yasuhide Okuyama & Krista D. Yu, 2019. "Return of the inoperability," Economic Systems Research, Taylor & Francis Journals, vol. 31(4), pages 467-480, October.
    7. Jeremy Ginsberg & Matthew H. Mohebbi & Rajan S. Patel & Lynnette Brammer & Mark S. Smolinski & Larry Brilliant, 2009. "Detecting influenza epidemics using search engine query data," Nature, Nature, vol. 457(7232), pages 1012-1014, February.
    8. Jansen, Pieter S. M. Kop, 1994. "Analysis of multipliers in stochastic input-output models," Regional Science and Urban Economics, Elsevier, vol. 24(1), pages 55-74, February.
    9. Adam Rose, 2004. "Economic Principles, Issues, and Research Priorities in Hazard Loss Estimation," Advances in Spatial Science, in: Yasuhide Okuyama & Stephanie E. Chang (ed.), Modeling Spatial and Economic Impacts of Disasters, chapter 2, pages 13-36, Springer.
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    1. Elena B. Zavyalova & Vera A. Volokhina & Marija A. Troyanskaya & Yulia I. Dubova, 2023. "A humanistic model of corporate social responsibility in e-commerce with high-tech support in the artificial intelligence economy," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-10, December.

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