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Evaluating the impact of COVID-19 on ex-vessel prices using time-series analysis

The spread of coronavirus disease 2019 (COVID-19) and subsequent lockdown measures have impacted economies and industries worldwide. The fisheries industry witnessed a sharp decline in demand and a slump in fish prices due to its dependence on the food service industry. It is important to quantitati...

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Autores principales: Abe, Keita, Ishimura, Gakushi, Baba, Shinya, Yasui, Shota, Nakamura, Kosuke
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Japan 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8784210/
https://www.ncbi.nlm.nih.gov/pubmed/35095191
http://dx.doi.org/10.1007/s12562-021-01574-x
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author Abe, Keita
Ishimura, Gakushi
Baba, Shinya
Yasui, Shota
Nakamura, Kosuke
author_facet Abe, Keita
Ishimura, Gakushi
Baba, Shinya
Yasui, Shota
Nakamura, Kosuke
author_sort Abe, Keita
collection PubMed
description The spread of coronavirus disease 2019 (COVID-19) and subsequent lockdown measures have impacted economies and industries worldwide. The fisheries industry witnessed a sharp decline in demand and a slump in fish prices due to its dependence on the food service industry. It is important to quantitatively assess those fish species affected most and the extent of the pandemic’s impact on them, to take specific countermeasures. We propose a time-series analysis as an alternative to the current practice of using ad hoc year-on-year comparisons. Although the pandemic makes it difficult to construct a counterfactual approach due to the lack of an appropriate control group, we use time-series forecasting to simulate normal conditions using pre-pandemic data. In Tokyo, the unit price of fish species that were negatively impacted by the food services industry dropped by 12.65% to 14.64%, and by 26.08% to 28.22% after the declaration of a state of emergency. Seasonality, short weekly cycles, and short-term market trends are factors that affect the price of fish. Species-specific impact estimates related to the COVID-19 pandemic can allow policymakers to implement recovery measures in a more targeted and effective manner. The results of our analysis can increase fishers’ and policymakers’ awareness of the usefulness of economic analyses and incentivize them to release data to establish a system to accumulate and analyze data strategically for urgent and appropriate interventions in the fisheries industry.
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spelling pubmed-87842102022-01-24 Evaluating the impact of COVID-19 on ex-vessel prices using time-series analysis Abe, Keita Ishimura, Gakushi Baba, Shinya Yasui, Shota Nakamura, Kosuke Fish Sci Original Article The spread of coronavirus disease 2019 (COVID-19) and subsequent lockdown measures have impacted economies and industries worldwide. The fisheries industry witnessed a sharp decline in demand and a slump in fish prices due to its dependence on the food service industry. It is important to quantitatively assess those fish species affected most and the extent of the pandemic’s impact on them, to take specific countermeasures. We propose a time-series analysis as an alternative to the current practice of using ad hoc year-on-year comparisons. Although the pandemic makes it difficult to construct a counterfactual approach due to the lack of an appropriate control group, we use time-series forecasting to simulate normal conditions using pre-pandemic data. In Tokyo, the unit price of fish species that were negatively impacted by the food services industry dropped by 12.65% to 14.64%, and by 26.08% to 28.22% after the declaration of a state of emergency. Seasonality, short weekly cycles, and short-term market trends are factors that affect the price of fish. Species-specific impact estimates related to the COVID-19 pandemic can allow policymakers to implement recovery measures in a more targeted and effective manner. The results of our analysis can increase fishers’ and policymakers’ awareness of the usefulness of economic analyses and incentivize them to release data to establish a system to accumulate and analyze data strategically for urgent and appropriate interventions in the fisheries industry. Springer Japan 2022-01-24 2022 /pmc/articles/PMC8784210/ /pubmed/35095191 http://dx.doi.org/10.1007/s12562-021-01574-x Text en © The Author(s) 2021, corrected publication 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Original Article
Abe, Keita
Ishimura, Gakushi
Baba, Shinya
Yasui, Shota
Nakamura, Kosuke
Evaluating the impact of COVID-19 on ex-vessel prices using time-series analysis
title Evaluating the impact of COVID-19 on ex-vessel prices using time-series analysis
title_full Evaluating the impact of COVID-19 on ex-vessel prices using time-series analysis
title_fullStr Evaluating the impact of COVID-19 on ex-vessel prices using time-series analysis
title_full_unstemmed Evaluating the impact of COVID-19 on ex-vessel prices using time-series analysis
title_short Evaluating the impact of COVID-19 on ex-vessel prices using time-series analysis
title_sort evaluating the impact of covid-19 on ex-vessel prices using time-series analysis
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8784210/
https://www.ncbi.nlm.nih.gov/pubmed/35095191
http://dx.doi.org/10.1007/s12562-021-01574-x
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