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

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.

Estimating sectoral COVID-19 economic losses in the Philippines using nighttime light and electricity consumption data

“…In the Philippines, economic losses due to COVID-19 in 2020 and 2021 amounted to 2.9 and 3.2 trillion PhP, respectively. This study's 2020 estimate falls within the range of economic losses reported in previous studies (12,13,29). A study reported 2.1 trillion PhP losses covering 2 years under the assumption of uninterrupted recovery from October 31, 2020 (13).…”

“…In the context of the Philippines, several studies have assessed economic losses due to COVID-19 through various methods, such as ratio analysis ( 10 ), linear probability model ( 11 ), input–output analysis ( 12 , 13 ), and compartmentalized dynamic transmission ( 14 ). These studies successfully estimated a rough snapshot of the immediate economic losses due to COVID-19.…”

A humanistic model of corporate social responsibility in e-commerce with high-tech support in the artificial intelligence economy

“…In contrast to Santos et al ( 2022 ), Asokan et al ( 2022 ), Bianchet et al ( 2021 ), El Khoury et al ( 2022 ), Jasielska et al ( 2022 ), and Miller et al ( 2022 ), it is indicated that corporate social responsibility increases business profitability in the COVID-19 pandemic and crisis not so much by increasing customer loyalty as by increasing employee loyalty. Improving the internal quality characteristics of workers and business operations contributes to the growth of revenues in e-commerce.…”

“…When a lockdown is imposed under the combined effect of the social and economic factors noted, there is a decrease in production and a reduction in effective demand. Against a general macroeconomic downturn, society places greater demands on the corporate social responsibility of business (Santos et al, 2022 ). Multiple studies, for example, studies by Asokan et al ( 2022 ), El Khoury et al ( 2022 ), and Miller et al ( 2022 ) show that consumers are favoring responsible business products over irresponsible business products during the COVID-19 pandemic and crisis.…”

The Impact of COVID-19 on Financial Markets and the Real Economy

“…This book comprises 17 papers published in the Special Issue entitled "The Impact of COVID-19 on Financial Markets and the Real Economy", centered on exploring variations in the structure of socioeconomic models due to the pandemic (Vasin 2022); the impact of the COVID-19 pandemic on the economy or industries of various nations such as Canada (Singh et al 2022), China (Habibi et al 2022), Slovakia (Svabova et al 2022), United States (Rodousakis and Soklis 2022), or Vietnam (Huynh et al 2021;Nguyen et al 2022); workforce disruptions caused by the pandemic in the Philippines (Santos et al 2022) or on the Russian labor market (Rodionov et al 2022); examining the tourism and recreational potential of the cross-border regions of Russia and Kazakhstan, and the risks these regions faced during the COVID-19 phase (Tanina et al 2022); analyzing the factors affecting young Vietnamese people's intentions to use financial technology (Khuong et al 2022) or the factors affecting Vietnamese informal laborers' credit access in the context of the pandemic (Vu and Ho 2022); predicting Jordanian insurance companies and their performance examination (Altarawneh et al 2022) or developing an early warning of solvency risk in the banking industry in Indonesia during the COVID-19 outbreak (Hidayat et al 2022); stock market responses during the COVID-19 s several phases (Keliuotyte-Staniuleniene and Kviklis 2022); the drivers of cross-border mergers and acquisitions during the pandemic (Lee et al 2021); and the financial and fiscal variables of the Ecuadorian economic groups (Tulcanaza-Prieto and Morocho-Cayamcela 2021).…”