vdem: A selection of indexes from the V-Dem dataset, version 6.1

Description Usage Format Variable descriptions References See Also

Description

A selection of indexes from the V-Dem dataset, version 6.1. Described in Coppedge, Michael, John Gerring, Staffan I. Lindberg, Svend-Erik Skaaning, and Jan Teorell, with David Altman, Michael Bernhard, M. Steven Fish, Adam Glynn, Allen Hicken, Carl Henrik Knutsen, Kelly McMann, Pamela Paxton, Daniel Pemstein, Jeffrey Staton, Brigitte Zimmerman, Frida Andersson, Valeriya Mechkova, Farhad Miri. 2016. V-Dem Codebook v6.1. Varieties of Democracy (V-Dem) Project. Original data available at https://v-dem.net/en/data/.

Usage

1

Format

An object of class tbl_df (inherits from tbl, data.frame) with 16485 rows and 52 columns.

Variable descriptions

country_name

Standardized country name. This is the same across all datasets in this package, so you can always join them by country_name and year. Character with 173 distinct values. Most common: Afghanistan (116), Algeria (116), Argentina (116), Benin (116), Bhutan (116), Bolivia (116), Brazil (116), Cambodia (Kampuchea) (116), Colombia (116), Costa Rica (116), East Timor (116), El Salvador (116), Eritrea (116), Ethiopia (116), Fiji (116), Guyana (116), Iran (Persia) (116), Kenya (116), Malawi (116), Maldives (116), Mozambique (116), Myanmar (Burma) (116), Nepal (116), Paraguay (116), Philippines (116), Portugal (116), Qatar (116), Rumania (116), Russia (Soviet Union) (116), Solomon Islands (116), Somalia (116), Sudan (116), Surinam (116), Taiwan (116), Thailand (116), Tunisia (116), Turkey (Ottoman Empire) (116), Uganda (116), United States of America (116), Zimbabwe (Rhodesia) (116). NAs = 0.

GWn

Gleditsch-Ward numeric country code. See Gleditsch and Ward (1999). Numeric. Max = 950, min = 2, distinct = 173, mean = 461.954, sd = 247.337, NAs = 0.

year

Year. Numeric. Max = 2015, min = 1900, distinct = 116, mean = 1959.98, sd = 32.862, NAs = 0.

v2x_polyarchy

Continuous polyarchy index from V-dem version 6.1. Numeric. Max = 0.958, min = 0.008, distinct = 9321, mean = 0.323, sd = 0.282, NAs = 413.

v2x_polyarchy_codehigh

Upper bound of the 95% confidence interval. Numeric. Max = 0.977, min = 0.012, distinct = 9315, mean = 0.351, sd = 0.297, NAs = 413.

v2x_polyarchy_codelow

Lower bound of the 95% confidence interval. Numeric. Max = 0.942, min = 0.004, distinct = 9319, mean = 0.294, sd = 0.268, NAs = 413.

v2x_api

Additive polyarchy index from V-dem version 6.1. Numeric. Max = 0.983, min = 0.017, distinct = 9321, mean = 0.469, sd = 0.309, NAs = 413.

v2x_api_codehigh

Upper bound of the 95% confidence interval. Numeric. Max = 0.991, min = 0.025, distinct = 9316, mean = 0.5, sd = 0.311, NAs = 413.

v2x_api_codelow

Lower bound of the 95% confidence interval. Numeric. Max = 0.976, min = 0.009, distinct = 9320, mean = 0.438, sd = 0.308, NAs = 413.

v2x_mpi

Multiplicative polyarchy index from V-dem version 6.1. Numeric. Max = 0.934, min = 0, distinct = 6115, mean = 0.176, sd = 0.279, NAs = 413.

v2x_mpi_codehigh

Upper bound of the 95% confidence interval. Numeric. Max = 0.963, min = 0, distinct = 6114, mean = 0.202, sd = 0.307, NAs = 413.

v2x_mpi_codelow

Lower bound of the 95% confidence interval. Numeric. Max = 0.907, min = 0, distinct = 5750, mean = 0.151, sd = 0.252, NAs = 413.

v2x_EDcomp_thick

Electoral component index from V-dem version 6.1. To what extent is the electoral principle of democracy achieved? Numeric. Max = 0.967, min = 0.005, distinct = 7781, mean = 0.357, sd = 0.306, NAs = 413.

v2x_EDcomp_thick_codehigh

Upper bound of the 95% confidence interval. Numeric. Max = 0.986, min = 0.008, distinct = 7779, mean = 0.386, sd = 0.323, NAs = 413.

v2x_EDcomp_thick_codelow

Lower bound of the 95% confidence interval. Numeric. Max = 0.952, min = 0.001, distinct = 7780, mean = 0.329, sd = 0.291, NAs = 413.

v2x_libdem

Liberal democracy index from V-dem version 6.1. Numeric. Max = 0.928, min = 0.011, distinct = 10663, mean = 0.261, sd = 0.249, NAs = 413.

v2x_libdem_codehigh

Upper bound of the 95% confidence interval. Numeric. Max = 0.952, min = 0.018, distinct = 10663, mean = 0.29, sd = 0.262, NAs = 413.

v2x_libdem_codelow

Lower bound of the 95% confidence interval. Numeric. Max = 0.904, min = 0.004, distinct = 10661, mean = 0.231, sd = 0.237, NAs = 413.

v2x_partipdem

Participatory democracy index from V-dem version 6.1. Numeric. Max = 0.84, min = 0, distinct = 9950, mean = 0.2, sd = 0.205, NAs = 422.

v2x_partipdem_codehigh

Upper bound of the 95% confidence interval. Numeric. Max = 0.87, min = 0.001, distinct = 9949, mean = 0.226, sd = 0.216, NAs = 422.

v2x_partipdem_codelow

Lower bound of the 95% confidence interval. Numeric. Max = 0.811, min = 0, distinct = 9945, mean = 0.174, sd = 0.194, NAs = 422.

v2x_delibdem

Deliberative democracy index from V-dem version 6.1. Numeric. Max = 0.929, min = 0, distinct = 9885, mean = 0.213, sd = 0.267, NAs = 521.

v2x_delibdem_codehigh

Upper bound of the 95% confidence interval. Numeric. Max = 0.958, min = 0.001, distinct = 9884, mean = 0.247, sd = 0.291, NAs = 521.

v2x_delibdem_codelow

Lower bound of the 95% confidence interval. Numeric. Max = 0.9, min = 0, distinct = 9809, mean = 0.179, sd = 0.245, NAs = 521.

v2x_egaldem

Egalitarian democracy index from V-dem version 6.1. Numeric. Max = 0.925, min = 0.007, distinct = 10213, mean = 0.246, sd = 0.246, NAs = 413.

v2x_egaldem_codehigh

Upper bound of the 95% confidence interval. Numeric. Max = 0.949, min = 0.013, distinct = 10213, mean = 0.281, sd = 0.26, NAs = 413.

v2x_egaldem_codelow

Lower bound of the 95% confidence interval. Numeric. Max = 0.901, min = 0.001, distinct = 10212, mean = 0.212, sd = 0.233, NAs = 413.

v2xcs_ccsi

Civil society index from V-dem version 6.1. How robust is civil society? Higher values mean civil society is more robust. Numeric. Max = 0.984, min = 0.009, distinct = 3848, mean = 0.472, sd = 0.311, NAs = 55.

v2xcs_ccsi_codelow

Upper bound of the 95% confidence interval. Numeric. Max = 0.961, min = 0.002, distinct = 3847, mean = 0.365, sd = 0.299, NAs = 55.

v2xcs_ccsi_codehigh

Lower bound of the 95% confidence interval. Numeric. Max = 0.995, min = 0.031, distinct = 3847, mean = 0.583, sd = 0.296, NAs = 55.

v2xlg_legcon

Legislative constraints on the executive index from V-dem version 6.1. To what extent is the legislature and government agencies (e.g., comptroller general, general prosecutor, or ombudsman) capable of questioning, investigating, and exercising oversight over the executive? Higher values mean more constraints. Numeric. Max = 0.987, min = 0.023, distinct = 2443, mean = 0.467, sd = 0.305, NAs = 3197.

v2xlg_legcon_codehigh

Upper bound of the 95% confidence interval. Numeric. Max = 0.996, min = 0.064, distinct = 2443, mean = 0.581, sd = 0.297, NAs = 3197.

v2xlg_legcon_codelow

Lower bound of the 95% confidence interval. Numeric. Max = 0.96, min = 0.006, distinct = 2443, mean = 0.358, sd = 0.289, NAs = 3197.

v2x_jucon

Judicial constraints on the executive index from V-dem version 6.1. To what extent does the executive respect the constitution and comply with court rulings, and to what extent is the judiciary able to act in an independent fashion? Higher values mean more constraints. Numeric. Max = 0.992, min = 0.005, distinct = 3071, mean = 0.517, sd = 0.291, NAs = 156.

v2x_jucon_codehigh

Upper bound of the 95% confidence interval. Numeric. Max = 0.998, min = 0.018, distinct = 3072, mean = 0.635, sd = 0.273, NAs = 156.

v2x_jucon_codelow

Lower bound of the 95% confidence interval. Numeric. Max = 0.974, min = 0.001, distinct = 3071, mean = 0.399, sd = 0.288, NAs = 156.

v2x_execorr

Executive corruption index from V-dem version 6.1. How routinely do members of the executive, or their agents grant favors in exchange for bribes, kickbacks, or other material inducements, and how often do they steal, embezzle, or misappropriate public funds or other state resources for personal or family use? Higher values mean more corruption. Numeric. Max = 0.979, min = 0.011, distinct = 2068, mean = 0.453, sd = 0.3, NAs = 156.

v2x_execorr_codehigh

Upper bound of the 95% confidence interval. Numeric. Max = 0.995, min = 0.039, distinct = 2066, mean = 0.581, sd = 0.297, NAs = 156.

v2x_execorr_codelow

Lower bound of the 95% confidence interval. Numeric. Max = 0.935, min = 0.002, distinct = 2068, mean = 0.329, sd = 0.273, NAs = 156.

vdem_country

Country name in the original dataset. Character with 170 distinct values. Most common: Afghanistan (116), Algeria (116), Argentina (116), Benin (116), Bhutan (116), Bolivia (116), Brazil (116), Burma_Myanmar (116), Cambodia (116), Colombia (116), Costa Rica (116), East Timor (116), El Salvador (116), Eritrea (116), Ethiopia (116), Fiji (116), Guyana (116), Iran (116), Kenya (116), Malawi (116), Maldives (116), Mozambique (116), Nepal (116), Paraguay (116), Philippines (116), Portugal (116), Qatar (116), Romania (116), Russia (116), Solomon Islands (116), Somalia (116), Sudan (116), Suriname (116), Taiwan (116), Thailand (116), Tunisia (116), Turkey (116), Uganda (116), United States (116), Zimbabwe (116). NAs = 0.

GWc

Gleditsch-Ward alphabetic country code. See Gleditsch and Ward (1999). Character with 173 distinct values. Most common: AFG (116), ALG (116), ARG (116), BEN (116), BHU (116), BOL (116), BRA (116), CAM (116), COL (116), COS (116), ERI (116), ETH (116), ETM (116), FJI (116), GUY (116), IRN (116), KEN (116), MAD (116), MAW (116), MYA (116), MZM (116), NEP (116), PAR (116), PHI (116), POR (116), QAT (116), RUM (116), RUS (116), SAL (116), SOL (116), SOM (116), SUD (116), SUR (116), TAW (116), THI (116), TUN (116), TUR (116), UGA (116), USA (116), ZIM (116). NAs = 0.

cown

Correlates of War numeric country code. Differs from GWn for a few country-years. See Gleditsch and Ward (1999). Numeric. Max = 950, min = 2, distinct = 170, mean = 461.952, sd = 247.358, NAs = 0.

polity_ccode

Country code in Polity datasets. Differs from GWn for a few country-years. See Gleditsch and Ward (1999). Numeric. Max = 950, min = 2, distinct = 177, mean = 461.928, sd = 247.352, NAs = 0.

region

Region. Character with 20 distinct values. Most common: Eastern Africa (1866), South America (1383), Western Africa (1725). NAs = 0.

continent

Continent. Character with 5 distinct values. Most common: Africa (5598), Asia (3932), Europe (3173). NAs = 0.

GW_startdate

Date at which the state entered the system of states according to Gleditsch and Ward, or NA if it has never been a member. Date. Max = 2011-07-09, min = 1816-01-01, distinct = 141, NAs = 0.

GW_enddate

Date at which the state ceased to be a member of the system of states according to Gleditsch and Ward, or NA if it still exists. Date. Max = 2006-06-04, min = 1830-07-05, distinct = 20, NAs = 15659.

microstate

Indicator of whether the state is a microstate, according to Gleditsch's list of microstates. Logical. TRUE = 338, FALSE = 16147, NAs = 0.

lat

Latitude. Numeric. Max = 64.963, min = -40.901, distinct = 172, mean = 16.459, sd = 24.65, NAs = 0.

lon

Longitude. Numeric. Max = 178.065, min = -106.347, distinct = 172, mean = 21.033, sd = 62.768, NAs = 0.

in_cow

Whether the country-year is in the Correlates of War system of states. Logical. TRUE = 11448, FALSE = 5037, NAs = 0.

in_system

Whether the country-year is in the Gleditsch-Ward system of states. See Gleditsch and Ward (1999). Logical. TRUE = 11747, FALSE = 4738, NAs = 0.

References

Coppedge, Michael, John Gerring, Staffan I. Lindberg, Svend-Erik Skaaning, and Jan Teorell, with David Altman, Michael Bernhard, M. Steven Fish, Adam Glynn, Allen Hicken, Carl Henrik Knutsen, Kelly McMann, Pamela Paxton, Daniel Pemstein, Jeffrey Staton, Brigitte Zimmerman, Frida Andersson, Valeriya Mechkova, Farhad Miri. 2016. V-Dem Codebook v6.1. Varieties of Democracy (V-Dem) Project.

Gleditsch, Kristian S. & Michael D. Ward. 1999. "Interstate System Membership: A Revised List of the Independent States since 1816." International Interactions 25: 393-413. The list can be found at http://privatewww.essex.ac.uk/~ksg/statelist.html

See Also

Other democracy: all_gwf_extended_yearly, democracy, extended_uds, kailitz_yearly, lied, magaloni, polity_annual, wahman_teorell


xmarquez/AuthoritarianismBook documentation built on May 4, 2019, 1:24 p.m.