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

Bibliographic Data

ID22084676
AuthorsMa Flordeliza P Del Castillo (0000-0003-2468-2301, Kyoto University), Toshio Fujimi (0000-0001-7197-0336, Kyoto University, corresponding author), Hirokazu Tatano (0000-0001-7209-4358, Kyoto University)
Year2024
Volume12
Pages1308301-1308301
Publication date2024-02-29
Open AccessYes
TypeARTICLE
VenueFrontiers in Public Health (JOURNAL)
Journal identifiersISSN: 2296-2565 • E-ISSN: 2296-2565
PublisherFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/fpubh.2024.1308301
PMID38487185
OpenAlexW4392289725
LanguageEN
Citations received1
References cited21

Introduction: Economic loss estimation is critical for policymakers to craft policies that balance economic and health concerns during pandemic emergencies. However, this task is time-consuming and resource-intensive, posing challenges during emergencies. Method: To address this, we proposed using electricity consumption (EC) and nighttime lights (NTL) datasets to estimate the total, commercial, and industrial economic losses from COVID-19 lockdowns in the Philippines. Regression models were employed to establish the relationship of GDP with EC and NTL. Then, models using basic statistics and weather data were developed to estimate the counterfactual EC and NTL, from which counterfactual GDP was derived. The difference between the actual and the counterfactual GDP from 2020 to 2021 yielded economic loss. Results: ≥ 0.979). Second, counterfactual EC and NTL could be estimated using models based on statistics and weather data explaining more than 81% of the pre-pandemic values. Last, the estimated total loss amounted to 2.9 trillion PhP in 2020 and 3.2 trillion PhP in 2021. More than two-thirds of the losses were in the commercial sector as it responded to both policies and the COVID-19 case surge. In contrast, the industrial sector was affected primarily by the lockdown implementation. Discussion: This method allowed monitoring of economic losses resulting from long-term and large-scale hazards such as the COVID-19 pandemic. These findings can serve as empirical evidence for advocating targeted strategies that balance public health and the economy during pandemic scenarios

Agricultural economics · Counterfactual thinking · Econometrics · Economic cost · Economic impact analysis · Economic sector · Economics · Economy · Electricity · Estimation · Pandemic · Real gross domestic product · Regression · Statistics · Climate Change and Health Impacts · COVID-19 impact on air quality · Engineering · Impact of Light on Environment and Health · Mathematics · Medicine

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