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Discussion of “The Asymmetric Impact of COVID-19: A Novel Approach to Quantifying Financial Distress across Industries”

The COVID-19 pandemic crisis and the associated lockdown measures have exerted significantly adverse effects on corporate sectors globally. Archanskaia et al. (2023) provide a novel empirical strategy to timely assess corporate financial distress in the EU. The contribution is two-fold. First, this...

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Autor principal: Wang, Xuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Published by Elsevier B.V. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10240910/
https://www.ncbi.nlm.nih.gov/pubmed/37346244
http://dx.doi.org/10.1016/j.euroecorev.2023.104501
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author Wang, Xuan
author_facet Wang, Xuan
author_sort Wang, Xuan
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description The COVID-19 pandemic crisis and the associated lockdown measures have exerted significantly adverse effects on corporate sectors globally. Archanskaia et al. (2023) provide a novel empirical strategy to timely assess corporate financial distress in the EU. The contribution is two-fold. First, this paper’s notion of financial distress considers both the equity position and corporate indebtedness. Second, the methodology proposed in this paper allows the authors to estimate corporate financial distress in the EU at a highly granular level and link micro-level simulations to sectoral macroeconomic outcomes. The methodology employed by Archanskaia et al. (2023) consists of three steps. First, the authors apply a nowcasting model to acquire monthly industrial turnover data. Second, they feed the obtained monthly industrial turnover into a profit-generating process via an accounting identity to estimate monthly firm profits at the firm level. Third, the authors use the estimated firm profits with a snapshot of information on pre-existing liquid assets to deduce the firm-level liquidity needs and the depletion of equity through the focus period during COVID-19. These estimated results on firm equity position and indebtedness enable the authors to quantity corporate financial distress in the EU via various angles (e.g., country-level heterogeneity, industry heterogeneity, and the targeting of COVID support policies). The primary advantage of this approach is that it deals with large datasets at the granular level and produces firm-level results almost in real-time. Therefore, it can help policymaking track the effects of crises over time. However, one can quickly critique this three-step approach for its susceptibility to the usual Lucas critique. That said, since the objective here is to estimate firm-level financial distress, a large structural model being more or less aggregate in nature, though able to mitigate the Lucas critique concern, will encounter significant challenges in estimating firm-level results with the requisite level of granularity offered by the available data. Therefore, I broadly concur with the authors’ position that ‘the specific contribution of this paper consists in striking a better balance between the need to carry out a multi-country evaluation of the pandemic’s effects on industrial activity in a strongly integrated region like the EU and the difficulty of capturing time, industry, and country variation in turnover with sufficient granularity.’
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spelling pubmed-102409102023-06-05 Discussion of “The Asymmetric Impact of COVID-19: A Novel Approach to Quantifying Financial Distress across Industries” Wang, Xuan Eur Econ Rev Article The COVID-19 pandemic crisis and the associated lockdown measures have exerted significantly adverse effects on corporate sectors globally. Archanskaia et al. (2023) provide a novel empirical strategy to timely assess corporate financial distress in the EU. The contribution is two-fold. First, this paper’s notion of financial distress considers both the equity position and corporate indebtedness. Second, the methodology proposed in this paper allows the authors to estimate corporate financial distress in the EU at a highly granular level and link micro-level simulations to sectoral macroeconomic outcomes. The methodology employed by Archanskaia et al. (2023) consists of three steps. First, the authors apply a nowcasting model to acquire monthly industrial turnover data. Second, they feed the obtained monthly industrial turnover into a profit-generating process via an accounting identity to estimate monthly firm profits at the firm level. Third, the authors use the estimated firm profits with a snapshot of information on pre-existing liquid assets to deduce the firm-level liquidity needs and the depletion of equity through the focus period during COVID-19. These estimated results on firm equity position and indebtedness enable the authors to quantity corporate financial distress in the EU via various angles (e.g., country-level heterogeneity, industry heterogeneity, and the targeting of COVID support policies). The primary advantage of this approach is that it deals with large datasets at the granular level and produces firm-level results almost in real-time. Therefore, it can help policymaking track the effects of crises over time. However, one can quickly critique this three-step approach for its susceptibility to the usual Lucas critique. That said, since the objective here is to estimate firm-level financial distress, a large structural model being more or less aggregate in nature, though able to mitigate the Lucas critique concern, will encounter significant challenges in estimating firm-level results with the requisite level of granularity offered by the available data. Therefore, I broadly concur with the authors’ position that ‘the specific contribution of this paper consists in striking a better balance between the need to carry out a multi-country evaluation of the pandemic’s effects on industrial activity in a strongly integrated region like the EU and the difficulty of capturing time, industry, and country variation in turnover with sufficient granularity.’ Published by Elsevier B.V. 2023-08 2023-06-05 /pmc/articles/PMC10240910/ /pubmed/37346244 http://dx.doi.org/10.1016/j.euroecorev.2023.104501 Text en © 2023 Published by Elsevier B.V. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Wang, Xuan
Discussion of “The Asymmetric Impact of COVID-19: A Novel Approach to Quantifying Financial Distress across Industries”
title Discussion of “The Asymmetric Impact of COVID-19: A Novel Approach to Quantifying Financial Distress across Industries”
title_full Discussion of “The Asymmetric Impact of COVID-19: A Novel Approach to Quantifying Financial Distress across Industries”
title_fullStr Discussion of “The Asymmetric Impact of COVID-19: A Novel Approach to Quantifying Financial Distress across Industries”
title_full_unstemmed Discussion of “The Asymmetric Impact of COVID-19: A Novel Approach to Quantifying Financial Distress across Industries”
title_short Discussion of “The Asymmetric Impact of COVID-19: A Novel Approach to Quantifying Financial Distress across Industries”
title_sort discussion of “the asymmetric impact of covid-19: a novel approach to quantifying financial distress across industries”
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10240910/
https://www.ncbi.nlm.nih.gov/pubmed/37346244
http://dx.doi.org/10.1016/j.euroecorev.2023.104501
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