Please note that while we make every effort to clean this data, the speed and scale with which it was collected means that we cannot validate all of it. If you find an error in the data, please file an issue on this Github page.

  1. CoronaNet Database Version 1.0 (core)

This file contains variables from the CoronaNet government response project, representing national and sub-national policy event data from more than 190 countries since January 1st, 2020. The data include source links, descriptions, targets (i.e. other countries), the type and level of enforcement, and a comprehensive set of policy types. For more detail on this data, you can see our codebook here.


  1. CoronaNet Database Version 1.0 (extended)

This file contains the government response information from the core data along with the following datasets:


coronanet_release.csv Dictionary

  1. record_id Unique identifier for each policy record
  2. entry_type Whether the record is new, meaning no restriction had been in place before, or an update (restriction was in place but changed). Corrections are corrections to previous entries.
  3. event_description A short description of the policy change
  4. type The category of the policy
  5. country The country initiating the policy
  6. init_country_level Whether the policy came from the national level or a sub-national unit
  7. index_prov The ID of the sub-national unit
  8. target_country Which foreign country a policy is targeted at (i.e. travel policies)
  9. target_geog_level Whether the target of the policy is a country as a whole or a sub-national unit of that country
  10. target_who_what Who the policy is targeted at
  11. recorded_date When the record was entered into our data
  12. target_direction Whether a travel-related policy affects people coming in (Inbound) or leaving (Outbound)
  13. travel_mechanism If a travel policy, what kind of transportation it affects
  14. compliance Whether the policy is voluntary or mandatory
  15. enforcer What unit in the country is responsible for enforcement
  16. date_announced When the policy goes into effect
  17. link A link to at least one source for the policy
  18. ISO_A3 3-digit ISO country codes
  19. ISO_A2 2-digit ISO country codes
  20. severity_index_5perc 5% posterior low estimate (i.e. lower bound of uncertainty interval) for severity index
  21. severity_index_median posterior median estimate (point estimate) for severity index, which comes from a Bayesian latent variable model aggregating across policy types to measure country-level policy severity (see paper on our website)
  22. severity_index_5perc 95% posterior high estimate (i.e. upper bound of uncertainty interval) for severity index

coronanet_release_allvars.csv Dictionary

  1. All of the fields listed above, plus

  2. tests_daily_or_total Whether a country reports the daily count of tests a cumulative total

  3. tests_raw The number of reported tests collected from host country websites or media reports

  4. deaths The number of COVID-19 deaths, aggregated to the country-day level (JHU CSSE data)

  5. confirmed_cases The number of confirmed cases of COVID-19, aggregated to the country-day level (JHU CSSE data)

  6. recovered The number of recoveries from COVID-19, aggregated to the country-day level (JHU CSSE data)

  7. ccode The Correlates of War country code

  8. ifs IMF IFS country code

  9. Rank_FP (most recent year available from Niehaus dataset) Reporters without Borders Press Freedom Annual Ranking

  10. Score_FP (most recent year available from Niehaus dataset) Reporters with Borders Press Freedom Score

  11. state_IDC (most recent year available from Niehaus dataset) State/Provincial Governments Locally Elected

  12. muni_IDC (most recent year available from Niehaus dataset) Municipal Governments Locally Elected

  13. dispersive_IDC (most recent year available from Niehaus dataset) Dispersive Powersharing

  14. constraining_IDC (most recent year available from Niehaus dataset) Constraining Powersharing

  15. inclusive_IDC (most recent year available from Niehaus dataset) Inclusive powersharing

  16. sfi_SFI (most recent year available from Niehaus dataset) State fragility index

  17. ti_cpi_TI (most recent year available from Niehaus dataset) Corruption perceptions index

  18. pop_WDI_PW (most recent year available from Niehaus dataset) World Bank population

  19. gdp_WDI_PW (most recent year available from Niehaus dataset) World Bank GDP (total)

  20. gdppc_WDI_PW (most recent year available from Niehaus dataset) World Bank GDP per capita

  21. growth_WDI_PW (most recent year available from Niehaus dataset) World Bank GDP growth percent

  22. lnpop_WDI_PW (most recent year available from Niehaus dataset) Log of World Bank population

  23. lngdp_WDI_PW (most recent year available from Niehaus dataset) Log of World Bank GDP

  24. lngdppc_WDI_PW (most recent year available from Niehaus dataset) Log of World Bank GDP per capita

  25. disap_FA (most recent year available from Niehaus dataset) 3 category, ordered variable for disappearances index

  26. polpris_FA (most recent year available from Niehaus dataset) 3 category, ordered variable for political imprisonment index

  27. latentmean_FA (most recent year available from Niehaus dataset) the posterior mean of the latent variable index for human rights protection)

  28. transparencyindex_HR (most recent year available from Niehaus dataset) Transparency Index

  29. EmigrantStock_EMS (most recent year available from Niehaus dataset) Total emmigrant stock from

  30. v2x_polyarchy_VDEM (most recent year available from Niehaus dataset) Electoral democracy index

  31. news_WB (most recent year available from Niehaus dataset) Daily newspapers (per 1,000 people)

License

CC-By Attribution 4.0 International

Please cite the project and dataset as:

Cheng, Cindy, Joan Barceló, Allison Hartnett, Robert Kubinec, and Luca Messerschmidt. 2020. COVID-19 Government Response Event Dataset (CoronaNet v1.0). https://www.coronanet-project.org