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

Joost R. Santos (), John Frederick D. Tapia, Albert Lamberte, Christine Alyssa Solis, Raymond R. Tan, Kathleen B. Aviso and Krista Danielle S. Yu
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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

Economies, 2022, vol. 10, issue 8, 1-18

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.

Keywords: Leontief model; Dirichlet distribution; uncertainty analysis; workforce; disaster; pandemic (search for similar items in EconPapers)
JEL-codes: E F I J O Q (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

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