The CoRisk Index is the first[according to whom?] economic indicator of industry risk assessments related to COVID-19. In contrast to conventional economic climate indexes, e.g. the Ifo Business Climate Index or Purchasing Managers' Index, the CoRisk Index relies on automatically retrieved company filings.[1] The index has been developed by a team of researchers at the Oxford Internet Institute, University of Oxford, and the Hertie School of Governance in March 2020. It gained international media attention[2][3][4][5] as an up-to-date empirical source for policy makers and researchers[6][7][8][9][10][11] investigating the economic repercussions of the Coronavirus Recession.

Methodology

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The index is calculated with the use of company 10-k risk reports filed to the U.S. Securities and Exchange Commission (SEC). The CoRisk Index is calculated industry-specific as a geometric mean of three measures:  ,[1] where k refers to the average industry count of Corona-related keywords used in each report and n represents the average industry share of negative keywords in Corona-related sentences.

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References

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  1. ^ a b Stephany, Fabian; Neuhäuser, Leonie; Stoehr, Niklas; Darius, Philipp; Teutloff, Ole; Braesemann, Fabian (2022-02-02). "The CoRisk-Index: a data-mining approach to identify industry-specific risk perceptions related to Covid-19". Humanities and Social Sciences Communications. 9 (1): 1–15. doi:10.1057/s41599-022-01039-1. hdl:20.500.11850/532071. ISSN 2662-9992.
  2. ^ "Analysis | Crisis begins to hit professional and public-sector jobs once considered safe". Washington Post. ISSN 0190-8286. Retrieved 2022-08-29.
  3. ^ Guldner, Jan. "Rezession und Instabilität: So steht der Pegel der Corona-Angst". www.wiwo.de (in German). Retrieved 2022-08-29.
  4. ^ smartlighting (2020-05-06). "Nuevo índice online analiza preocupaciones comerciales ante COVID-19". smartlighting (in Spanish). Retrieved 2022-08-29.
  5. ^ "New online index shows business concerns over COVID-19 | University of Oxford". www.ox.ac.uk. Retrieved 2022-08-29.
  6. ^ Latif, Siddique; Usman, Muhammad; Manzoor, Sanaullah; Iqbal, Waleed; Qadir, Junaid; Tyson, Gareth; Castro, Ignacio; Razi, Adeel; Boulos, Maged N. Kamel; Weller, Adrian; Crowcroft, Jon (2020-09-04). "Leveraging Data Science To Combat COVID-19: A Comprehensive Review". doi:10.36227/techrxiv.12212516.v2. {{cite journal}}: Cite journal requires |journal= (help)
  7. ^ Béland, Louis-Philippe; Brodeur, Abel; Wright, Taylor (2020-04-27). "The Short-Term Economic Consequences of Covid-19: Exposure to Disease, Remote Work and Government Response". Rochester, NY. {{cite journal}}: Cite journal requires |journal= (help)
  8. ^ "DATA in the time of COVID-19". Open Data Watch. 2020-11-13. Retrieved 2022-08-29.
  9. ^ Brodeur, Abel; Clark, Andrew E.; Fleche, Sarah; Powdthavee, Nattavudh (2021-01-01). "COVID-19, lockdowns and well-being: Evidence from Google Trends" (PDF). Journal of Public Economics. 193: 104346. doi:10.1016/j.jpubeco.2020.104346. ISSN 0047-2727.
  10. ^ Brodeur, Abel; Cook, Nikolai; Wright, Taylor (2021-03-01). "On the effects of COVID-19 safer-at-home policies on social distancing, car crashes and pollution". Journal of Environmental Economics and Management. 106: 102427. doi:10.1016/j.jeem.2021.102427. ISSN 0095-0696. PMC 7864793.
  11. ^ Davis, Steven J.; Hansen, Stephen; Seminario-Amez, Cristhian (September 2020). "Firm-Level Risk Exposures and Stock Returns in the Wake of COVID-19". {{cite journal}}: Cite journal requires |journal= (help)