README

CoronaNet Project Team July, 2021

About This Repository

This repository contains the raw data from the CoronaNet data collection project. This data is in a policy record format, in which one row equals one specific policy with end and beginning dates. While it is a very compact format, it is not necessarily ideal for data analysis projects. We also have 6 indices (social distancing, business restrictions, school restrictions, health monitoring, health resources and masks), and a wide data format with 156 of our indicators for January 1st to January 15th, 2021. Both the indices and the wide data format have one row per policy type per day per country, which is much easier to merge with our data sources. For more info, please see this Github repository.

If you do want to see the data in policy record format, which includes more information than what is released in our wide data, please see below for more information about what is in this repository. More information about the fields are available in our PDF Codebook and Online Codebook.

CoronaNet Raw Data

When using our raw data, we recommend checking the CoronaNet Update Tracker, so you can track our policy updates by country and subnational unit. We have hundreds of RAs working to keep the data up to date, but there will inevitably be issues in the data in terms of being up to date.

First, CoronaNet data releases:

Please note that while we make every effort to validate 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.

The format of the data is in country-day-record_id format. Some record_id values have letters appended to indicate that the general policy category type also has a value for type_sub_cat, which contains more detail about the policy, such as whether health resources refers to masks, ventilators, or hospitals. Some entries are marked as new_entry in the entry_type field for when a policy of that type was first implemented in the country. Later updates to those policies are marked as updates in entry_type. To see how policies are connected, look at the policy_id field for all policies from the first entry through updates for a given country/province/city. If an entry was corrected after initial data collection, it will read corrected in the entry_type field (the original incorrect data has already been replaced with the corrected data).

1. data/CoronaNet/data_bulk/coronanet_release[.rds/csv.gz] These files contain variables from the CoronaNet government response project, representing national and sub-national policy event data from more than 140 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.

2. data/CoronaNet/data_bulk/coronanet_release_allvars[.rds/csv.gz] These files contains the government response information from coronanet_release.csv along with the following datasets:

   1. Tests from the CoronaNet testing database (see http://coronanet-project.org for more info);
   2. Cases/deaths/recovered from the JHU data repository (https://github.com/CSSEGISandData/COVID-19);
   3. Country-level covariates including GDP, V-DEM democracy scores, human rights indices, power-sharing indices, and press freedom indices from the Niehaus World Economics and Politics Dataverse (https://niehaus.princeton.edu/news/world-economics-and-politics-dataverse)

3. data/CoronaNet/data_country/coronanet_release_[country].csv For each country in coronanet_release, we have generated a separate data file in a .csv format.

4. data/CoronaNet/data_country/coronanet_release_allvars_[country].csv For each country in coronanet_release_allvars, we have generated a separate data file in a .csv format.

coronanet_release.csv Field Dictionary

1. record_id Unique identifier for each unique policy record

2. policy_id Identifier linking new policies with subsequent updates to policies

3. 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.

4. update_type Whether an update as recorded as ongoing ("Change of Policy") or ending ("End of Policy")

5. update_level_var: What dimension of a policy is being updated (e.g. timing, compliance) and how (i.e., strengthening or relaxing)

6. description A short textual description of the policy change

7. date_announced When the policy is announced

8. date_start When the policy goes into effect

9. date_end_spec Qualtiative information on a policy's end date

10. date_end When the policy ends (if it has an explicit end date)

11. country The country where a policy was initiated

12. ISO_A3 3-digit ISO country codes for the country where a policy was initiated

13. ISO_A2 2-digit ISO country codes for the country where a policy was initiated

14. init_country_level The level of government that initiated a policy (e.g. national, provincial)

15. domestic_policy Indicates where policy targets an area within the initiating country (i.e. is domestic in nature)

16. province The province where a policy was initiated, if applicable

17. ISO_L2 ISO province codes for the province where a policy was initiated, if applicable

18. city The city where a policy was initiated, if applicable

19. type The category of the policy

20. type_sub_cat The sub-category of the policy (if one exists)

21. type_new_admin_coop The type of cooperation governments undertake, if applicable

22. type_vac_cat The particular vaccine (e.g. Pfizer) for which a policy is being made

23. type_vac_mix Whether mixing of different vaccines is allowed

24. type_vac_reg Regulatory status of a vaccine

25. type_vac_purchase Conditions under which a vaccine is purchased

26. type_vac_group Criteria for deciding how to administer vaccinations

27. type_vac_group_rank The number of groups given preferential treatment for vaccine access, if applicable

28. type_vac_who_pays The financial responisbility for paying for a vaccine

29. type_vac_dist_admin Entity in charge of distributing vaccines

30. type_vac_loc Where vaccination is taking place

31. type_vac_cost_num Monetary resources devoted for a given vaccine policy (number)

32. type_vac_cost_scale Monetary resources devoted for a given vaccine policy (scale, e.g. millions, billions)

33. type_vac_cost_unit Monetary resources devoted for a given vaccine policy (unit, e.g. currency type)

34. type_vac_cost_gov_perc Monetary resources devoted for a given vaccine policy (gov perc: contribution covered by the government)

35. type_vac_amt_num Material resources devoted for a given vaccine policy (number)

36. type_vac_amt_scale Material resources devoted for a given vaccine policy (scale, e.g. milions, billions)

37. type_vac_amt_unit Material resources devoted for a given vaccine policy (unit, e.g. doses)

38. type_vac_amt_gov_perc Material resources devoted for a given vaccine policy (gov perc: contribution covered by the government)

39. type_text Any additional information about the policy type (such as the number of ventilators/days of quarantine/etc.)

40. institution_cat Whether the business or government service is deemed as essential, non-essential or no information is provided

41. institution_status Whether a school, business or government service is open, open with conditions or closed

42. institution_conditions If a school, business or government service are open with conditions, records the conditions

43. target_init_same Whether the policy initiator is the same as the policy target

44. target_country Which foreign country a policy is targeted at (i.e. travel policies)

45. target_geog_level Whether the target of the policy is a country as a whole or a sub-national unit of that country

46. target_region The name of a regional grouping (like ASEAN) that is a target of the policy (if any)

47. target_province The name of a province targeted by the policy (if any)

48. target_city The name of a city targeted by the policy (if any)

49. target_intl_org The international org targeted by the policy (if any)

50. target_other Any geographical entity that does not fit into the targeted categories mentioned above

51. target_who_what The travel or residency status of who the policy is targeted at

52. target_who_gen Special populations the policy is targeted at (e.g. asylum seekers/refugees)

53. target_direction Whether a travel-related policy affects people coming in (Inbound) or leaving (Outbound)

54. travel_mechanism If a travel policy, what kind of transportation it affects

55. compliance Whether the policy is voluntary or mandatory

56. enforcer What unit in the country is responsible for enforcement

57. dist_index_high_est The high (95% posterior density) estimate of the country social distancing score (0-100)

58. dist_index_med_est The median (most likely) estimate of the country social distancing score (0-100)

59. dist_index_low_est The low (95% posterior density) estimate of the country social distancing score (0-100)

60. dist_index_country_rank The relative rank by each day for each country on the social distancing score

61. pdf_link Permanent pdf link for at least one source for the policy

62. link A link to at least one source for the policy

63. date_updated When we can confirm the country - policy type was

64. recorded_date When the record was entered into our data

    last checked/updated (we can only confirm policy type for a given country is up to date as of this date)

coronanet_release_allvars.csv Field 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)