In:
PLOS ONE, Public Library of Science (PLoS), Vol. 17, No. 2 ( 2022-2-14), p. e0263898-
Abstract:
Usually, official and survey-based statistics guide policymakers in their choice of response instruments to economic crises. However, in an early phase, after a sudden and unforeseen shock has caused unexpected and fast-changing dynamics, data from traditional statistics are only available with non-negligible time delays. This leaves policymakers uncertain about how to most effectively manage their economic countermeasures to support businesses, especially when they need to respond quickly, as in the COVID-19 pandemic. Given this information deficit, we propose a framework that guided policymakers throughout all stages of this unforeseen economic shock by providing timely and reliable sources of firm-level data as a basis to make informed policy decisions. We do so by combining early stage ‘ad hoc’ web analyses, ‘follow-up’ business surveys, and ‘retrospective’ analyses of firm outcomes. A particular focus of our framework is on assessing the early effects of the pandemic, using highly dynamic and large-scale data from corporate websites. Most notably, we show that textual references to the coronavirus pandemic published on a large sample of company websites and state-of-the-art text analysis methods allowed to capture the heterogeneity of the pandemic’s effects at a very early stage and entailed a leading indication on later movements in firm credit ratings. While the proposed framework is specific to the COVID-19 pandemic, the integration of results obtained from real-time online sources in the design of subsequent surveys and their value in forecasting firm-level outcomes typically targeted by policy measures, is a first step towards a more timely and holistic approach for policy guidance in times of economic shocks.
Type of Medium:
Online Resource
ISSN:
1932-6203
DOI:
10.1371/journal.pone.0263898
DOI:
10.1371/journal.pone.0263898.g001
DOI:
10.1371/journal.pone.0263898.g002
DOI:
10.1371/journal.pone.0263898.g003
DOI:
10.1371/journal.pone.0263898.g004
DOI:
10.1371/journal.pone.0263898.g005
DOI:
10.1371/journal.pone.0263898.g006
DOI:
10.1371/journal.pone.0263898.t001
DOI:
10.1371/journal.pone.0263898.t002
DOI:
10.1371/journal.pone.0263898.t003
DOI:
10.1371/journal.pone.0263898.t004
DOI:
10.1371/journal.pone.0263898.t005
DOI:
10.1371/journal.pone.0263898.t006
DOI:
10.1371/journal.pone.0263898.t007
DOI:
10.1371/journal.pone.0263898.s001
DOI:
10.1371/journal.pone.0263898.s002
DOI:
10.1371/journal.pone.0263898.s003
DOI:
10.1371/journal.pone.0263898.s004
DOI:
10.1371/journal.pone.0263898.s005
DOI:
10.1371/journal.pone.0263898.s006
DOI:
10.1371/journal.pone.0263898.s007
DOI:
10.1371/journal.pone.0263898.s008
DOI:
10.1371/journal.pone.0263898.s009
DOI:
10.1371/journal.pone.0263898.s010
DOI:
10.1371/journal.pone.0263898.r001
DOI:
10.1371/journal.pone.0263898.r002
DOI:
10.1371/journal.pone.0263898.r003
DOI:
10.1371/journal.pone.0263898.r004
Language:
English
Publisher:
Public Library of Science (PLoS)
Publication Date:
2022
detail.hit.zdb_id:
2267670-3
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