This package archives a large number of datasets measuring democracy in use in the scholarly literature, and it provides functions to access many others. You can use it to access some widely used datasets, including Polity5, Freedom House, Geddes, Wright, and Frantz’ autocratic regimes dataset, the Lexical Index of Electoral Democracy, the DD/ACLP/PACL/CGV dataset, the main indexes of the V-Dem dataset, and many others.

Installation

The package is only available on Github. Install as follows:

remotes::install_github("xmarquez/democracyData")

Basic usage

For the vast majority of use cases, you can just type the name of the dataset you require. For example, here’s the DD/ACLP/PACL/CGV dataset:

$ \text{r} \text{library}(\text{democracyData}) \text{pacl} #> # \text{A} \text{tibble}: 9{,}159 \times 82 #> \text{order} \text{pacl\_country} \text{year} \text{aclpcode} \text{pacl\_cowcode} \text{cowcode2} \text{ccdcodelet} \text{ccdcodenum} #> <\text{dbl}> <\text{chr}> <\text{dbl}> <\text{dbl}> <\text{dbl}> <\text{dbl}> <\text{chr}> <\text{dbl}> #> 1 1 \text{Afghanistan} 1946 142 700 700 \text{AFG} 1 #> 2 2 \text{Afghanistan} 1947 142 700 700 \text{AFG} 1 #> 3 3 \text{Afghanistan} 1948 142 700 700 \text{AFG} 1 #> 4 4 \text{Afghanistan} 1949 142 700 700 \text{AFG} 1 #> 5 5 \text{Afghanistan} 1950 142 700 700 \text{AFG} 1 #> 6 6 \text{Afghanistan} 1951 142 700 700 \text{AFG} 1 #> 7 7 \text{Afghanistan} 1952 142 700 700 \text{AFG} 1 #> 8 8 \text{Afghanistan} 1953 142 700 700 \text{AFG} 1 #> 9 9 \text{Afghanistan} 1954 142 700 700 \text{AFG} 1 #> 10 10 \text{Afghanistan} 1955 142 700 700 \text{AFG} 1 #> # ℹ 9{,}149 \text{more} \text{rows} #> # ℹ 74 \text{more} \text{variables}: \text{aclpyear} <\text{dbl}>, \text{cowcode2year} <\text{dbl}>, \text{cowcodeyear} <\text{dbl}>, #> # \text{chgterr} <\text{dbl}>, \text{ychgterr} <\text{dbl}>, \text{flagc\_cowcode2} <\text{dbl}>, \text{flage\_cowcode2} <\text{dbl}>, #> # \text{entryy} <\text{dbl}>, \text{exity} <\text{dbl}>, \text{cid} <\text{dbl}>, \text{wdicode} <\text{chr}>, \text{imf\_code} <\text{dbl}>, #> # \text{politycode} <\text{dbl}>, \text{bankscode} <\text{dbl}>, \text{dpicode} <\text{chr}>, \text{uncode} <\text{dbl}>, #> # \text{un\_region} <\text{dbl}>, \text{un\_region\_name} <\text{chr}>, \text{un\_continent} <\text{dbl}>, #> # \text{un\_continent\_name} <\text{chr}>, \text{aclp\_region} <\text{dbl}>, \text{bornyear} <\text{dbl}>, … $

``$ \text{r}

\text{You} \text{can} \text{also} \text{use} \text{an} \text{alias}:

\text{dd}() #> # \text{A} \text{tibble}: 9{,}159 \times 82 #> \text{order} \text{pacl_country} \text{year} \text{aclpcode} \text{pacl_cowcode} \text{cowcode2} \text{ccdcodelet} \text{ccdcodenum} #> <\text{dbl}> <\text{chr}> <\text{dbl}> <\text{dbl}> <\text{dbl}> <\text{dbl}> <\text{chr}> <\text{dbl}> #> 1 1 \text{Afghanistan} 1946 142 700 700 \text{AFG} 1 #> 2 2 \text{Afghanistan} 1947 142 700 700 \text{AFG} 1 #> 3 3 \text{Afghanistan} 1948 142 700 700 \text{AFG} 1 #> 4 4 \text{Afghanistan} 1949 142 700 700 \text{AFG} 1 #> 5 5 \text{Afghanistan} 1950 142 700 700 \text{AFG} 1 #> 6 6 \text{Afghanistan} 1951 142 700 700 \text{AFG} 1 #> 7 7 \text{Afghanistan} 1952 142 700 700 \text{AFG} 1 #> 8 8 \text{Afghanistan} 1953 142 700 700 \text{AFG} 1 #> 9 9 \text{Afghanistan} 1954 142 700 700 \text{AFG} 1 #> 10 10 \text{Afghanistan} 1955 142 700 700 \text{AFG} 1 #> # ℹ 9{,}149 \text{more} \text{rows} #> # ℹ 74 \text{more} \text{variables}: \text{aclpyear} <\text{dbl}>, \text{cowcode2year} <\text{dbl}>, \text{cowcodeyear} <\text{dbl}>, #> # \text{chgterr} <\text{dbl}>, \text{ychgterr} <\text{dbl}>, \text{flagc_cowcode2} <\text{dbl}>, \text{flage_cowcode2} <\text{dbl}>, #> # \text{entryy} <\text{dbl}>, \text{exity} <\text{dbl}>, \text{cid} <\text{dbl}>, \text{wdicode} <\text{chr}>, \text{imf_code} <\text{dbl}>, #> # \text{politycode} <\text{dbl}>, \text{bankscode} <\text{dbl}>, \text{dpicode} <\text{chr}>, \text{uncode} <\text{dbl}>, #> # \text{un_region} <\text{dbl}>, \text{un_region_name} <\text{chr}>, \text{un_continent} <\text{dbl}>, #> # \text{un_continent_name} <\text{chr}>, \text{aclp_region} <\text{dbl}>, \text{bornyear} <\text{dbl}>, … $``

Here’s Polity IV:

$ \text{r} \text{polityIV} #> # \text{A} \text{tibble}: 17{,}562 \times 40 #> \text{cyear} \text{polityIV\_ccode} \text{scode} \text{polityIV\_country} \text{year} \text{flag} \text{fragment} \text{democ} \text{autoc} #> <\text{dbl}> <\text{dbl}> <\text{chr}> <\text{chr}> <\text{dbl}> <\text{dbl}> <\text{dbl}> <\text{dbl}> <\text{dbl}> #> 1 21800 2 \text{USA} \text{United} \text{States} 1800 0 \text{NA} 7 3 #> 2 21801 2 \text{USA} \text{United} \text{States} 1801 0 \text{NA} 7 3 #> 3 21802 2 \text{USA} \text{United} \text{States} 1802 0 \text{NA} 7 3 #> 4 21803 2 \text{USA} \text{United} \text{States} 1803 0 \text{NA} 7 3 #> 5 21804 2 \text{USA} \text{United} \text{States} 1804 0 \text{NA} 7 3 #> 6 21805 2 \text{USA} \text{United} \text{States} 1805 0 \text{NA} 7 3 #> 7 21806 2 \text{USA} \text{United} \text{States} 1806 0 \text{NA} 7 3 #> 8 21807 2 \text{USA} \text{United} \text{States} 1807 0 \text{NA} 7 3 #> 9 21808 2 \text{USA} \text{United} \text{States} 1808 0 \text{NA} 7 3 #> 10 21809 2 \text{USA} \text{United} \text{States} 1809 0 \text{NA} 9 0 #> # ℹ 17{,}552 \text{more} \text{rows} #> # ℹ 31 \text{more} \text{variables}: \text{polity} <\text{dbl}>, \text{polity2} <\text{dbl}>, \text{durable} <\text{dbl}>, \text{xrreg} <\text{dbl}>, #> # \text{xrcomp} <\text{dbl}>, \text{xropen} <\text{dbl}>, \text{xconst} <\text{dbl}>, \text{parreg} <\text{dbl}>, \text{parcomp} <\text{dbl}>, #> # \text{exrec} <\text{dbl}>, \text{exconst} <\text{dbl}>, \text{polcomp} <\text{dbl}>, \text{prior} <\text{dbl}>, \text{emonth} <\text{dbl}>, #> # \text{eday} <\text{dbl}>, \text{eyear} <\text{dbl}>, \text{eprec} <\text{dbl}>, \text{interim} <\text{dbl}>, \text{bmonth} <\text{dbl}>, #> # \text{bday} <\text{dbl}>, \text{byear} <\text{dbl}>, \text{bprec} <\text{dbl}>, \text{post} <\text{dbl}>, \text{change} <\text{dbl}>, \text{d4} <\text{dbl}>, #> # \text{sf} <\text{dbl}>, \text{regtrans} <\text{dbl}>, \text{extended\_country\_name} <\text{chr}>, \text{GWn} <\text{dbl}>, … $

And here’s a basic version of the V-Dem dataset, including only the 7 main indexes of democracy:

$ \text{r} \text{vdem\_simple} #> # \text{A} \text{tibble}: 28{,}092 \times 54 #> \text{vdem\_country\_name} \text{country\_text\_id} \text{country\_id} \text{year} \text{historical\_date} \text{project} #> <\text{chr}> <\text{chr}> <\text{dbl}> <\text{dbl}> <\text{date}> <\text{dbl}> #> 1 \text{Mexico} \text{MEX} 3 1789 1789-12-31 1 #> 2 \text{Mexico} \text{MEX} 3 1790 1790-12-31 1 #> 3 \text{Mexico} \text{MEX} 3 1791 1791-12-31 1 #> 4 \text{Mexico} \text{MEX} 3 1792 1792-12-31 1 #> 5 \text{Mexico} \text{MEX} 3 1793 1793-12-31 1 #> 6 \text{Mexico} \text{MEX} 3 1794 1794-12-31 1 #> 7 \text{Mexico} \text{MEX} 3 1795 1795-12-31 1 #> 8 \text{Mexico} \text{MEX} 3 1796 1796-12-31 1 #> 9 \text{Mexico} \text{MEX} 3 1797 1797-12-31 1 #> 10 \text{Mexico} \text{MEX} 3 1798 1798-12-31 1 #> # ℹ 28{,}082 \text{more} \text{rows} #> # ℹ 48 \text{more} \text{variables}: \text{historical} <\text{dbl}>, \text{histname} <\text{chr}>, \text{codingstart} <\text{dbl}>, #> # \text{codingend} <\text{dbl}>, \text{codingstart\_contemp} <\text{dbl}>, \text{codingend\_contemp} <\text{dbl}>, #> # \text{codingstart\_hist} <\text{dbl}>, \text{codingend\_hist} <\text{dbl}>, \text{gapstart1} <\text{dbl}>, #> # \text{gapstart2} <\text{dbl}>, \text{gapstart3} <\text{dbl}>, \text{gapend1} <\text{dbl}>, \text{gapend2} <\text{dbl}>, #> # \text{gapend3} <\text{dbl}>, \text{gap\_index} <\text{dbl}>, \text{vdem\_cowcode} <\text{dbl}>, \text{v2x\_polyarchy} <\text{dbl}>, #> # \text{v2x\_polyarchy\_codelow} <\text{dbl}>, \text{v2x\_polyarchy\_codehigh} <\text{dbl}>, … $

All datasets in this package are fully documented; type ?pacl for example to see the documentation for the PACL dataset.

Downloading democracy data

Though all datasets can be accessed directly from this package, most datasets can also be downloaded directly from elsewhere. For example, to download the full V-Dem dataset, use the vdemdata package. The package does include the main indexes of version 16.0 of V-Dem (see vdem_simple), so you don’t need to use the vdemdata package if you are only interested in the higher-level indexes of democracy. You can also download directly the latest versions of the World Bank’s Voice and Accountability Index from the World Governance Indicators and Polity5, though there are also archived versions of these two in the package.

For example, we can download and process the Freedom House “Freedom in the World” dataset as follows:

``$ \text{r} \text{fh_downloaded} <- \text{download_fh}(\text{verbose} = \text{FALSE})

\text{fh_downloaded} #> # \text{A} \text{tibble}: 9{,}435 \times 11 #> \text{fh_country} \text{year} \text{pr} \text{cl} \text{status} \text{fh_total} \text{fh_total_reversed} #> <\text{chr}> <\text{dbl}> <\text{dbl}> <\text{dbl}> <\text{fct}> <\text{dbl}> <\text{dbl}> #> 1 \text{Afghanistan} 1972 4 5 \text{PF} 9 5 #> 2 \text{Afghanistan} 1973 7 6 \text{NF} 13 1 #> 3 \text{Afghanistan} 1974 7 6 \text{NF} 13 1 #> 4 \text{Afghanistan} 1975 7 6 \text{NF} 13 1 #> 5 \text{Afghanistan} 1976 7 6 \text{NF} 13 1 #> 6 \text{Afghanistan} 1977 6 6 \text{NF} 12 2 #> 7 \text{Afghanistan} 1978 7 7 \text{NF} 14 0 #> 8 \text{Afghanistan} 1979 7 7 \text{NF} 14 0 #> 9 \text{Afghanistan} 1980 7 7 \text{NF} 14 0 #> 10 \text{Afghanistan} 1982 7 7 \text{NF} 14 0 #> # ℹ 9{,}425 \text{more} \text{rows} #> # ℹ 4 \text{more} \text{variables}: \text{extended_country_name} <\text{chr}>, \text{GWn} <\text{dbl}>, \text{cown} <\text{dbl}>, #> # \text{in_GW_system} <\text{lgl}> $``

This downloads the latest archived update of the “Freedom in the World” dataset (1972-2024, corresponding to the 2025 report), puts it in country-year format (extracting the relevant info from the awful Excel table that Freedom House makes available), calculates the variables fh_total and fh_total_reversed, and adds state system information, including a standardized country name, the Gleditsch-Ward country code and the Correlates of War country code. You can also, however, use the packaged version (fh), which tracks the newer 2026 workbook:

``$ \text{r} \text{identical}(\text{fh_downloaded}, \text{fh}) #> [1] \text{FALSE}

\text{fh} #> # \text{A} \text{tibble}: 12{,}108 \times 11 #> \text{fh_country} \text{year} \text{pr} \text{cl} \text{status} \text{fh_total} \text{fh_total_reversed} #> <\text{chr}> <\text{dbl}> <\text{dbl}> <\text{dbl}> <\text{fct}> <\text{dbl}> <\text{dbl}> #> 1 \text{Afghanistan} 1972 4 5 \text{PF} 9 5 #> 2 \text{Afghanistan} 1973 7 6 \text{NF} 13 1 #> 3 \text{Afghanistan} 1974 7 6 \text{NF} 13 1 #> 4 \text{Afghanistan} 1975 7 6 \text{NF} 13 1 #> 5 \text{Afghanistan} 1976 7 6 \text{NF} 13 1 #> 6 \text{Afghanistan} 1977 6 6 \text{NF} 12 2 #> 7 \text{Afghanistan} 1978 7 7 \text{NF} 14 0 #> 8 \text{Afghanistan} 1979 7 7 \text{NF} 14 0 #> 9 \text{Afghanistan} 1980 7 7 \text{NF} 14 0 #> 10 \text{Afghanistan} 1982 7 7 \text{NF} 14 0 #> # ℹ 12{,}098 \text{more} \text{rows} #> # ℹ 4 \text{more} \text{variables}: \text{extended_country_name} <\text{chr}>, \text{GWn} <\text{dbl}>, \text{cown} <\text{dbl}>, #> # \text{in_GW_system} <\text{lgl}> $``

(In fact, since Freedom House no longer offers freely available versions of their latest updated data, it is usually best to use the packaged data if you need the most recent Freedom House snapshot, and the archived downloader if you specifically want the last public release). Other democracy datasets can often also be “re-downloaded” from the websites of their creators or maintainers if required. For example, one can either access PACL directly by typing

$ \text{r} \text{pacl} #> # \text{A} \text{tibble}: 9{,}159 \times 82 #> \text{order} \text{pacl\_country} \text{year} \text{aclpcode} \text{pacl\_cowcode} \text{cowcode2} \text{ccdcodelet} \text{ccdcodenum} #> <\text{dbl}> <\text{chr}> <\text{dbl}> <\text{dbl}> <\text{dbl}> <\text{dbl}> <\text{chr}> <\text{dbl}> #> 1 1 \text{Afghanistan} 1946 142 700 700 \text{AFG} 1 #> 2 2 \text{Afghanistan} 1947 142 700 700 \text{AFG} 1 #> 3 3 \text{Afghanistan} 1948 142 700 700 \text{AFG} 1 #> 4 4 \text{Afghanistan} 1949 142 700 700 \text{AFG} 1 #> 5 5 \text{Afghanistan} 1950 142 700 700 \text{AFG} 1 #> 6 6 \text{Afghanistan} 1951 142 700 700 \text{AFG} 1 #> 7 7 \text{Afghanistan} 1952 142 700 700 \text{AFG} 1 #> 8 8 \text{Afghanistan} 1953 142 700 700 \text{AFG} 1 #> 9 9 \text{Afghanistan} 1954 142 700 700 \text{AFG} 1 #> 10 10 \text{Afghanistan} 1955 142 700 700 \text{AFG} 1 #> # ℹ 9{,}149 \text{more} \text{rows} #> # ℹ 74 \text{more} \text{variables}: \text{aclpyear} <\text{dbl}>, \text{cowcode2year} <\text{dbl}>, \text{cowcodeyear} <\text{dbl}>, #> # \text{chgterr} <\text{dbl}>, \text{ychgterr} <\text{dbl}>, \text{flagc\_cowcode2} <\text{dbl}>, \text{flage\_cowcode2} <\text{dbl}>, #> # \text{entryy} <\text{dbl}>, \text{exity} <\text{dbl}>, \text{cid} <\text{dbl}>, \text{wdicode} <\text{chr}>, \text{imf\_code} <\text{dbl}>, #> # \text{politycode} <\text{dbl}>, \text{bankscode} <\text{dbl}>, \text{dpicode} <\text{chr}>, \text{uncode} <\text{dbl}>, #> # \text{un\_region} <\text{dbl}>, \text{un\_region\_name} <\text{chr}>, \text{un\_continent} <\text{dbl}>, #> # \text{un\_continent\_name} <\text{chr}>, \text{aclp\_region} <\text{dbl}>, \text{bornyear} <\text{dbl}>, … $

Or re-download the dataset from Jose Antonio Cheibub’s website as follows:

``$ \text{r}

\text{pacl_redownloaded} <- \text{redownload_pacl}(\text{verbose} = \text{FALSE})

\text{pacl_redownloaded} #> # \text{A} \text{tibble}: 9{,}159 \times 82 #> \text{order} \text{pacl_country} \text{year} \text{aclpcode} \text{pacl_cowcode} \text{cowcode2} \text{ccdcodelet} \text{ccdcodenum} #> <\text{dbl}> <\text{chr}> <\text{dbl}> <\text{dbl}> <\text{dbl}> <\text{dbl}> <\text{chr}> <\text{dbl}> #> 1 1 \text{Afghanistan} 1946 142 700 700 \text{AFG} 1 #> 2 2 \text{Afghanistan} 1947 142 700 700 \text{AFG} 1 #> 3 3 \text{Afghanistan} 1948 142 700 700 \text{AFG} 1 #> 4 4 \text{Afghanistan} 1949 142 700 700 \text{AFG} 1 #> 5 5 \text{Afghanistan} 1950 142 700 700 \text{AFG} 1 #> 6 6 \text{Afghanistan} 1951 142 700 700 \text{AFG} 1 #> 7 7 \text{Afghanistan} 1952 142 700 700 \text{AFG} 1 #> 8 8 \text{Afghanistan} 1953 142 700 700 \text{AFG} 1 #> 9 9 \text{Afghanistan} 1954 142 700 700 \text{AFG} 1 #> 10 10 \text{Afghanistan} 1955 142 700 700 \text{AFG} 1 #> # ℹ 9{,}149 \text{more} \text{rows} #> # ℹ 74 \text{more} \text{variables}: \text{aclpyear} <\text{dbl}>, \text{cowcode2year} <\text{dbl}>, \text{cowcodeyear} <\text{dbl}>, #> # \text{chgterr} <\text{dbl}>, \text{ychgterr} <\text{dbl}>, \text{flagc_cowcode2} <\text{dbl}>, \text{flage_cowcode2} <\text{dbl}>, #> # \text{entryy} <\text{dbl}>, \text{exity} <\text{dbl}>, \text{cid} <\text{dbl}>, \text{wdicode} <\text{chr}>, \text{imf_code} <\text{dbl}>, #> # \text{politycode} <\text{dbl}>, \text{bankscode} <\text{dbl}>, \text{dpicode} <\text{chr}>, \text{uncode} <\text{dbl}>, #> # \text{un_region} <\text{dbl}>, \text{un_region_name} <\text{chr}>, \text{un_continent} <\text{dbl}>, #> # \text{un_continent_name} <\text{chr}>, \text{aclp_region} <\text{dbl}>, \text{bornyear} <\text{dbl}>, … $``

These two data frames should be identical:

identical(pacl, pacl_redownloaded)
#> [1] TRUE

You should thus normally use the “archived” versions of these datasets, unless you want to manipulate the raw data yourself (using the redownload_* functions with the option return_raw = TRUE), or think they might have been updated since you installed this package.

Included democracy datasets

For a list of all the democracy datasets available through this package, type democracy_info:

library(dplyr)
#> 
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union

democracy_info |>
  knitr::kable()

dataset	long_name	main_democracy_measure_col	measure_type	based_on	in_pmm_replication	categorical_regime_types	user_extendable	downloadable	included_in_package	first_published_use	source_link	licensing_info	notes
anckar	The Anckar-Fredriksson dataset of political regimes	democracy	dichotomous	bmr	FALSE	TRUE	FALSE	TRUE	TRUE	2018	https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/AK8NVX&version=2.0	CC0 1.0	Version 3.0 covers 1800-2024. The democracy measure follows BMR democracy_omitteddata (dataset version 4.0) over the overlap and is supplemented or revised by Anckar and Fredriksson for 2021-2024 and selected microstate and case-specific country-years.
anrr	The Acemoglu, Naidu, Restrepo, and Robinson dataset	dem	dichotomous	FH,Polity	FALSE	FALSE	TRUE	FALSE	TRUE	2019	https://www.journals.uchicago.edu/doi/full/10.1086/700936	Unknown. Assumed CC0 1.0	The measure can be extended by using the latest FH, Polity, and PACL Data, but the rules are not entirely transparent, and some cases in the original dataset have been hand-coded.
arat_pmm	The Arat measure of democracy	pmm_arat	continuous	NA	TRUE	FALSE	FALSE	FALSE	TRUE	1991	NA	Unknown. Assumed CC0 1.0	Only available via the Pemstein, Meserve, and Melton (2013) replication data. I have not been able to access the original data.
blm	The Bowman, Lehoucq, and Mahoney index of democracy for Central America	blm	trichotomous	NA	TRUE	FALSE	FALSE	FALSE	TRUE	2005	NA	Unknown. Assumed CC0 1.0	This used to be downloadable; the website hosting it is down, however.
bmr	The Boix-Miller-Rosato dichotomous coding of democracy, 1800-2015, version 4.0	democracy,democracy_omitteddata,democracy_femalesuffrage	dichotomous	PACL	FALSE	FALSE	FALSE	TRUE	TRUE	2010	https://sites.google.com/site/mkmtwo/data	Unknown. Assumed CC0 1.0	NA
bnr	The Bernhard, Nordstrom & Reenock Event History Coding of Democratic Breakdowns	event,bnr	dichotomous	NA	FALSE	FALSE	TRUE	FALSE	TRUE	2001	NA	Unknown. Assumed CC0 1.0	Can be extended using a full panel of sovereign countries (COW). Extended version included in this package. This used to be downloadable; the website hosting it is down, however.
bti	The Berteslmann Index of Political transformation	SI_Democracy_Status	continuous	NA	FALSE	FALSE	FALSE	TRUE	TRUE	2006	https://bti-project.org/fileadmin/api/content/en/downloads/data/BTI_2006-2022_Scores.xlsx	Unknown.	NA
bollen_pmm	The Bollen measure of democracy	pmm_bollen	continuous	NA	TRUE	FALSE	FALSE	FALSE	TRUE	1978	NA	Unknown. Assumed CC0 1.0	The original data was compiled in 1978, for Bollen’s dissertation; existing data seems to be from the 2000 update. I do not know how much it changed over time. Only available via the Pemstein, Meserve, and Melton (2013) replication data. I have not been able to access the original data.
doorenspleet	Renske Doorenspleet’s Democracy Dataset	doorenspleet,regime	dichotomous	Polity	FALSE	FALSE	FALSE	FALSE	TRUE	2000	https://www.cambridge.org/core/journals/world-politics/article/abs/reassessing-the-three-waves-of-democratization/25A6CB38E6746F98D882DFC43A54D211	Unknown. Assumed CC0 1.0	NA
eiu	The Economist Intelligence Unit’s Democracy Index	eiu	continuous	NA	FALSE	FALSE	FALSE	FALSE	TRUE	2006	https://www.eiu.com/n/global-themes/democracy-index/	Unknown.	The original data has to be manually extracted from the tables in the EIU’s pdf report on the index.
fh	Freedom House “Freedom in the World” data	status,fh_total,fh_total_reversed	ordinal	FH	TRUE	FALSE	FALSE	TRUE	FALSE	1973	https://freedomhouse.org/reports/freedom-world/freedom-world-research-methodology	Unknown.	Updated to the Freedom in the World 2026 workbook, with coverage through 2025.
fh_full	Freedom House “Freedom in the World” data	total	continuous	FH	FALSE	FALSE	FALSE	TRUE	FALSE	2003	https://freedomhouse.org/reports/freedom-world/freedom-world-research-methodology	Unknown.	This is the 0-100 score Freedom House uses for its more aggregated ratings. The package now combines the detailed 2013-2026 workbook (calendar years 2012-2025) with the aggregate 2003-2026 workbook (calendar years 2002-2025), preserving the existing schema by filling unavailable item-level questions with missing values.
fh_electoral	Freedom House “Electoral Democracies” List	electoral	dichotomous	FH	FALSE	FALSE	FALSE	TRUE	FALSE	1990	https://freedomhouse.org/report/freedom-world	Unknown.	The package now preserves both the direct official electoral-democracy lists (electoral) and the recalculated series from full scores (electoral_calc). Direct official lists still have known gaps, including 2020 and 2024.
gwf	The Geddes Wright and Frantz Autocratic Regimes dataset	gwf_regimetype,gwf_nonautocracy	dichotomous	PACL	FALSE	TRUE	TRUE	TRUE	TRUE	2014	https://sites.psu.edu/dictators/	Unknown. Assumed CC0 1.0	Can be extended using the gwf_duration variable. Extended version included in this package.
hadenius_pmm	Axel Hadenius’ Index of Democracy	pmm_hadenius	continuous	NA	TRUE	FALSE	FALSE	FALSE	TRUE	1992	NA	Unknown. Assumed CC0 1.0	Only available via the Pemstein, Meserve, and Melton (2013) replication data. I have not been able to access the original data.
kailitz	The Steffen Kailitz Dataset of Authoritarian Regime Types	combined_regime,kailitz_binary,kailitz_tri	dichotomous	NA	FALSE	TRUE	FALSE	FALSE	TRUE	2013	https://journals.sagepub.com/doi/full/10.1177/0192512115616830	Unknown.	NA
LIED	The Lexical Index of Electoral Democracy, v. 6.9	lexical_index	ordinal	PIPE	FALSE	FALSE	FALSE	TRUE	TRUE	2015	https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/WPKNIT	CC0 1.0	Updated to version 6.9 with coverage through 2025.
magaloni	Autocracies of the World, 1950-2012 (Version 1.0).	demo_nr,demo_r,regime_r,regime_nr	dichotomous	PACL	FALSE	TRUE	TRUE	TRUE	TRUE	2013	https://cddrl.fsi.stanford.edu/research/autocracies_of_the_world_dataset	Unknown. Assumed CC0 1.0	Can be extended using the duration_nr variable. Extended version included in this package.
mainwaring	Mainwaring, Brinks, and Perez Linan’s democracy measure for Latin America	mainwaring,Regime	trichotomous	NA	TRUE	FALSE	FALSE	FALSE	TRUE	2001	https://web.archive.org/web/20120119050029/http://kellogg.nd.edu/scottmainwaring/Political_Regimes.pdf	Unknown. Assumed CC0 1.0	NA
munck_pmm	Munck Index of Democracy	pmm_munck	continuous	NA	TRUE	FALSE	FALSE	FALSE	TRUE	2009	NA	Unknown. Assumed CC0 1.0	Only available via the Pemstein, Meserve, and Melton (2013) replication data. I have not been able to access the original data.
pacl, pacl_update	The Democracy and Dictatorship Dataset (DD/PACL/ACLP/CGV)	democracy,regime,Democracy,DD_regime,DD_category	dichotomous	PACL	TRUE	TRUE	FALSE	TRUE	TRUE	1996	https://sites.google.com/site/joseantoniocheibub/datasets/dd, http://www.christianbjoernskov.com/bjoernskovrodedata/	Unknown. Assumed CC0 1.0	The original data was first compiled, as far as I know, for the famous ACLP study “Modernization: Theories and Facts” study of 1996. It was extended and changed by Cheibub, Gandhi, and Vreeland in 2010 (pacl dataset) and further updated by Bjornskov and Rode (2020; pacl_update dataset), who added new institutional variables.
peps	Participation-Enhanced Polity Score	PEPS1i,PEPS2i,PEPS1q,PEPS2q,PEPS1v,PEPS2v,polity1raw,Polity1,Polity2,Polity3	continuous	Polity	FALSE	FALSE	FALSE	TRUE	TRUE	2006	https://www.lehigh.edu/~bm05/democracy/PEPS1pub.dta	Unknown. Assumed CC0 1.0	NA
PIPE	The Political Institutions and Political Events (PIPE) dataset	democracy,democracy2,regime	dichotomous	PIPE	FALSE	FALSE	FALSE	FALSE	TRUE	2010	https://sites.google.com/a/nyu.edu/adam-przeworski/home/data	Unknown. Assumed CC0 1.0	Democracy measures in PIPE are calculated in this package on the basis of imperfect instructions in the codebook. Use with care. This used to be downloadable; the link no longer works, however.
pitf	Political Instability Task Force democracy indicator	pitf_binary	dichotomous	Polity	FALSE	FALSE	FALSE	FALSE	TRUE	2010	https://www.systemicpeace.org/inscr/	Unknown. Assumed CC0 1.0	Constructed score on the basis of Polity data.
pitf	Political Instability Task Force democracy indicator	pitf	ordinal	Polity	FALSE	FALSE	FALSE	FALSE	TRUE	2010	https://www.systemicpeace.org/inscr/	Unknown. Assumed CC0 1.0	Constructed score on the basis of Polity data.
polityIV	The Polity IV dataset	polity,polity2	ordinal	Polity	TRUE	FALSE	FALSE	TRUE	TRUE	1975	https://www.systemicpeace.org/inscr/	Unknown. Assumed CC0 1.0	The first compilation of this dataset (POLITY I) was probably first used in a 1975 study by Eckstein and Gurr, but had been collected by Gurr since the late 1960s. The current form of the data is very different from the original Polity I data. The Polity II codebook survives, but I find no record of the Polity I codebook.
polity_annual	The Polity5 dataset	polity,polity2	ordinal	Polity	TRUE	FALSE	FALSE	TRUE	FALSE	1975	https://www.systemicpeace.org/inscr/	Unknown. Assumed CC0 1.0	The first compilation of this dataset (POLITY I) was probably first used in a 1975 study by Eckstein and Gurr, but had been collected by Gurr since the late 1960s. The current form of the data is very different from the original Polity I data. The Polity II codebook survives, but I find no record of the Polity I codebook.
polyarchy	The Polyarchy Scale and the Contestation Scale	cont,poly	ordinal	NA	TRUE	FALSE	FALSE	TRUE	TRUE	1990	https://web.archive.org/web/20160309180905/http://www3.nd.edu/~mcoppedg/crd/datacrd.htm	Unknown. Assumed CC0 1.0	NA
polyarchy_dimensions	Latent Dimensions of Contestation and Inclusiveness by Michael Coppedge, Angel Alvarez, and Claudia Maldonado	CONTEST,INCLUS	continuous	latent variable	FALSE	FALSE	FALSE	TRUE	TRUE	2008	https://web.archive.org/web/20160309180905/http://www3.nd.edu/~mcoppedg/crd/datacrd.htm	Unknown. Assumed CC0 1.0	NA
prc_gasiorowski	The Political Regime Change (PRC) dataset.	regime,prc,prc_at_end_year,prc_at_beginning_year	trichotomous	NA	TRUE	FALSE	FALSE	FALSE	TRUE	1996	NA	Unknown. Assumed CC0 1.0	NA
reign	The Rulers, Elections, and Irregular Governance (REIGN) dataset, regime characteristics worksheet.	gwf_regimetype	dichotomous	GWF	FALSE	TRUE	FALSE	TRUE	TRUE	2016	https://github.com/OEFDataScience/REIGN.github.io	Unknown. Assumed CC0 1.0	Archived here now, since collection has stopped.
svmdi	Suport Vector Machine Democracy Index by Grundler and Krieger	svmdi, csvmdi	continuous	latent variable	FALSE	FALSE	FALSE	TRUE	TRUE	2016	https://ml-democracy-index.net/	Unknown. Assumed CC0 1.0	NA
svmdi	Suport Vector Machine Democracy Index by Grundler and Krieger	dsvmdi	dichotomous	latent variable	FALSE	FALSE	FALSE	TRUE	TRUE	2016	https://ml-democracy-index.net/	Unknown. Assumed CC0 1.0	NA
svolik_regime	Milan Svolik’s Regime Dataset	regime,regime_numeric	dichotomous	PACL	FALSE	FALSE	FALSE	FALSE	TRUE	2012	https://campuspress.yale.edu/svolik/the-politics-of-authoritarian-rule/	Unknown. Assumed CC0 1.0	NA
uds	The Unified Democracy Scores	mean,median	continuous	latent variable	FALSE	FALSE	TRUE	FALSE	TRUE	2010	NA	Unknown. Assumed CC0 1.0	Can be extended using the methods described in this package’s “Replicating and Extending the UD scores of Pemstein, Meserve, and Melton” article (https://xmarquez.github.io/democracyData/articles/Replicating_and_extending_the_UD_scores.html)
ulfelder	The Democracy/Autocracy Dataset by Jay Ulfelder	rgjtype	dichotomous	Polity	FALSE	FALSE	TRUE	TRUE	TRUE	2007	https://dataverse.harvard.edu/dataset.xhtml?persistentId=hdl:1902.1/18836	CC0 1.0	Can be extended using the rgjdurd and rgjdura variables. Extended version included in this package.
utip	The University of Texas Inequality Project Categorical Dataset of Political Regimes	utip_trichotomous	trichotomous	NA	FALSE	TRUE	FALSE	TRUE	TRUE	2008	https://utip.gov.utexas.edu/datasets.html	Unknown. Assumed CC0 1.0	Both the dichotomous and trichotomous versions of these measures are calculated by this package. The original dataset distinguishes several different types of democracy.
utip	The University of Texas Inequality Project Categorical Dataset of Political Regimes	utip_dichotomous,utip_dichotomous_strict	dichotomous	NA	FALSE	TRUE	FALSE	TRUE	TRUE	2008	https://utip.gov.utexas.edu/datasets.html	Unknown. Assumed CC0 1.0	Both the dichotomous and trichotomous versions of these measures are calculated by this package. The original dataset distinguishes several different types of democracy.
vanhanen	Vanhanen measures of democracy, 1800-2018	vanhanen_democratization	continuous	NA	TRUE	FALSE	FALSE	FALSE	TRUE	1968	https://services.fsd.tuni.fi/catalogue/FSD1289?lang=en&study_language=en	CC-BY 4.0	Vanhanen first collected democracy data on 12 countries for his 1968 dissertation. Current data is different from the original data, though it still uses a similar conceptual scheme.
vaporeg	The Varieties of Political Regimes dataset by Kailitz	vaporeg_dem	dichotomous	NA	FALSE	TRUE	FALSE	FALSE	TRUE	2025	https://www.va-poreg.de/	Unknown. Assumed CC0 1.0	This revises and extends the Kailitz dataset of political regimes.
vdem	The Varieties of Democracy Dataset, version 16	v2x_polyarchy,v2x_api,v2x_mpi,v2x_libdem,v2x_partipdem,v2x_delibdem,v2x_egaldem	continuous	NA	FALSE	FALSE	FALSE	FALSE	TRUE	2015	https://www.v-dem.net/data/the-v-dem-dataset/	CC-BY-SA 4.0	The full dataset be accessed using the package vdemdata. (Use “remotes::install_github(”vdeminstitute/vdemdata”)“; the package is not on CRAN)
wahman_teorell_hadenius	Authoritarian Regimes Data Set, version 5.0, by Axel Hadenius, Jan Teorell, & Michael Wahman	regime1ny,regime1nyrobust, regimeny, regimenyrobust	dichotomous	FH,Polity	FALSE	TRUE	FALSE	TRUE	TRUE	2007	https://sites.google.com/site/authoritarianregimedataset/data	Unknown. Assumed CC0 1.0	NA
wgi_democracy	The World Governance Indicators “Voice and Accountability” Index	Estimate	continuous	FH	FALSE	FALSE	FALSE	TRUE	TRUE	2010	https://www.worldbank.org/en/publication/worldwide-governance-indicators	Unknown.	NA

Combining all democracy datasets

You can create one huge data frame including all democracy measures with one call:

``$ \text{r}

\text{democracy_data} <- \text{generate_democracy_scores_dataset}(\text{output_format} = "\text{wide}", \text{verbose} = \text{FALSE})

\text{democracy_data} #> # \text{A} \text{tibble}: 42{,}377 \times 81 #> \text{extended_country_name} \text{GWn} \text{cown} \text{in_GW_system} \text{year} \text{anckar_democracy} #> <\text{chr}> <\text{dbl}> <\text{dbl}> <\text{lgl}> <\text{dbl}> <\text{dbl}> #> 1 \text{Abkhazia} 396 \text{NA} \text{FALSE} 1997 \text{NA} #> 2 \text{Abkhazia} 396 \text{NA} \text{FALSE} 1998 \text{NA} #> 3 \text{Abkhazia} 396 \text{NA} \text{FALSE} 1999 \text{NA} #> 4 \text{Abkhazia} 396 \text{NA} \text{FALSE} 2000 \text{NA} #> 5 \text{Abkhazia} 396 \text{NA} \text{FALSE} 2001 \text{NA} #> 6 \text{Abkhazia} 396 \text{NA} \text{FALSE} 2002 \text{NA} #> 7 \text{Abkhazia} 396 \text{NA} \text{FALSE} 2003 \text{NA} #> 8 \text{Abkhazia} 396 \text{NA} \text{FALSE} 2004 \text{NA} #> 9 \text{Abkhazia} 396 \text{NA} \text{FALSE} 2005 \text{NA} #> 10 \text{Abkhazia} 396 \text{NA} \text{FALSE} 2006 \text{NA} #> # ℹ 42{,}367 \text{more} \text{rows} #> # ℹ 75 \text{more} \text{variables}: \text{anrr_democracy} <\text{dbl}>, \text{arat} <\text{dbl}>, \text{blm} <\text{dbl}>, #> # \text{bmr_democracy} <\text{dbl}>, \text{bmr_democracy_femalesuffrage} <\text{dbl}>, #> # \text{bmr_democracy_omitteddata} <\text{dbl}>, \text{bnr_extended} <\text{dbl}>, \text{pmm_bollen} <\text{dbl}>, #> # \text{bti} <\text{dbl}>, \text{doorenspleet} <\text{dbl}>, \text{eiu} <\text{dbl}>, \text{fh_total_reversed} <\text{dbl}>, #> # \text{fh_electoral} <\text{dbl}>, \text{gwf_democracy_extended} <\text{dbl}>, #> # \text{gwf_democracy_extended_strict} <\text{dbl}>, \text{pmm_hadenius} <\text{dbl}>, … $``

You can select exactly which datasets to include in your big data frame. See ?generate_democracy_scores_dataset for further options to customize the output.

Latent Variable Indexes of Democracy

The package also offers a series of convenience functions to calculate latent variable indexes of democracy (following Pemstein, Meserve, and Melton’s 2010 article “Democratic Compromise: A Latent Variable Analysis of Ten Measures of Regime Type”); see the vignette on Replicating and Extending the UD scores of Pemstein, Meserve, and Melton. It also contains a pre-calculated extended version of these scores, available as extended_uds:

extended_uds
#> # A tibble: 41,986 × 20
#>    extended_country_name   GWn  cown in_GW_system  year     z1 se_z1 z1_pct975
#>    <chr>                 <dbl> <dbl> <lgl>        <dbl>  <dbl> <dbl>     <dbl>
#>  1 Abkhazia                396    NA FALSE         1997 0.0419 0.320     0.670
#>  2 Abkhazia                396    NA FALSE         1998 0.0419 0.320     0.670
#>  3 Abkhazia                396    NA FALSE         1999 0.0419 0.320     0.670
#>  4 Abkhazia                396    NA FALSE         2000 0.0419 0.320     0.670
#>  5 Abkhazia                396    NA FALSE         2001 0.0419 0.320     0.670
#>  6 Abkhazia                396    NA FALSE         2002 0.0419 0.320     0.670
#>  7 Abkhazia                396    NA FALSE         2003 0.0419 0.320     0.670
#>  8 Abkhazia                396    NA FALSE         2004 0.0419 0.320     0.670
#>  9 Abkhazia                396    NA FALSE         2005 0.245  0.319     0.870
#> 10 Abkhazia                396    NA FALSE         2006 0.245  0.319     0.870
#> # ℹ 41,976 more rows
#> # ℹ 12 more variables: z1_pct025 <dbl>, z1_adj <dbl>, z1_pct975_adj <dbl>,
#> #   z1_pct025_adj <dbl>, z1_as_prob <dbl>, z1_pct975_as_prob <dbl>,
#> #   z1_pct025_as_prob <dbl>, z1_adj_as_prob <dbl>, z1_pct975_adj_as_prob <dbl>,
#> #   z1_pct025_adj_as_prob <dbl>, num_measures <int>, measures <list>

State system functions

The package also includes a couple of other convenience functions to work with historical democracy data and determine state system membership. The first is country_year_coder, which works like the countrycode package, except that it is able to determine state system information for country-year pairs. Suppose you have this dataset:

my_weird_democracy_data <- tibble(
  country = c("Germany", "Germany", "Germany",
              "Germany", "East Germany",
              "Federal Republic of Germany",
              "Somaliland", "Somalia",
              "Palestine", "Russia",
              "Russia", "USSR",
              "Republic of Vietnam",
              "Yugoslavia", 'Yugoslavia',
              "Vietnam, South"),
  year = c( 2015, 1930, 1970, 1945, 1949,
            1992, 1990, 1990, 1940, 1917, 
            1912, 1922, 1975, 1990, 1991, 1954),
  my_measure = rnorm(16))


my_weird_democracy_data
#> # A tibble: 16 × 3
#>    country                      year my_measure
#>    <chr>                       <dbl>      <dbl>
#>  1 Germany                      2015    -0.0464
#>  2 Germany                      1930    -0.180 
#>  3 Germany                      1970    -2.26  
#>  4 Germany                      1945     0.645 
#>  5 East Germany                 1949    -0.356 
#>  6 Federal Republic of Germany  1992    -1.31  
#>  7 Somaliland                   1990     1.47  
#>  8 Somalia                      1990     1.16  
#>  9 Palestine                    1940     0.736 
#> 10 Russia                       1917    -0.547 
#> 11 Russia                       1912     0.571 
#> 12 USSR                         1922     1.88  
#> 13 Republic of Vietnam          1975    -1.59  
#> 14 Yugoslavia                   1990    -1.71  
#> 15 Yugoslavia                   1991    -0.974 
#> 16 Vietnam, South               1954    -0.535

and you then want to add state system information. country_year_coder does that for you!

my_weird_democracy_data <- my_weird_democracy_data |>
  country_year_coder(country,
                     year,
                     match_type = "country",
                     verbose = FALSE,
                     include_in_output = c("extended_country_name", 
                                           "GWn", "cown", 
                                           "polity_ccode", 
                                           "in_GW_system", 
                                           "in_cow_system", 
                                           "in_polity_system",
                                           "polity_startdate",
                                           "polity_enddate"))

my_weird_democracy_data |>
  knitr::kable()

country	year	my_measure	extended_country_name	GWn	cown	polity_ccode	in_GW_system	in_cow_system	in_polity_system	polity_startdate	polity_enddate
Germany	2015	-0.0464479	German Federal Republic	260	255	255	TRUE	TRUE	TRUE	1990-10-02	NA
Germany	1930	-0.1801533	Germany (Prussia)	255	255	255	TRUE	TRUE	TRUE	1871-01-19	1945-05-07
Germany	1970	-2.2629547	German Federal Republic	260	260	260	TRUE	TRUE	TRUE	1945-05-08	1990-10-02
Germany	1945	0.6454211	German Federal Republic	260	260	260	FALSE	FALSE	TRUE	1945-05-08	1990-10-02
East Germany	1949	-0.3560058	German Democratic Republic	265	265	265	TRUE	FALSE	TRUE	1945-05-08	1990-10-02
Federal Republic of Germany	1992	-1.3052748	German Federal Republic	260	255	255	TRUE	TRUE	TRUE	1990-10-02	NA
Somaliland	1990	1.4664221	Somaliland	NA	NA	NA	FALSE	FALSE	FALSE	NA	NA
Somalia	1990	1.1580588	Somalia	520	520	520	TRUE	TRUE	TRUE	1960-07-01	NA
Palestine	1940	0.7356530	Palestine, State of	NA	NA	NA	FALSE	FALSE	FALSE	NA	NA
Russia	1917	-0.5469135	Russia (Soviet Union)	365	365	365	TRUE	TRUE	TRUE	1800-01-01	1922-12-29
Russia	1912	0.5709414	Russia (Soviet Union)	365	365	365	TRUE	TRUE	TRUE	1800-01-01	1922-12-29
USSR	1922	1.8826326	Russia (Soviet Union)	365	365	364	TRUE	TRUE	TRUE	1922-12-30	1991-12-31
Republic of Vietnam	1975	-1.5934750	Vietnam, Republic of	817	817	817	FALSE	FALSE	TRUE	1955-10-26	1975-12-31
Yugoslavia	1990	-1.7109352	Yugoslavia	345	345	345	TRUE	TRUE	TRUE	1921-01-01	1991-07-01
Yugoslavia	1991	-0.9740215	Yugoslavia	345	345	347	TRUE	TRUE	TRUE	1991-07-01	2003-03-11
Vietnam, South	1954	-0.5349674	Vietnam, Republic of	817	817	817	TRUE	TRUE	FALSE	1955-10-26	1975-12-31

country_year_coder tries to match not just the country name or the country code (as countrycode does), but also to figure out the appropriate state system code given the year. (Above, for example, the function figures out that Germany 1970 should get a COW code of 260, but Germany 1992 should get 255 - though it should retain the 260 code in the Gleditsch and Ward system of states. This is, incidentally, how download_fh adds the correct COW and GW country codes to Freedom House’s Excel data). It also tries to figure out whether a given country-year is in the specific state system list. (In the example above, Germany in 1945 is not listed as a member of the state system in either COW or Gleditsch and Ward, since it was occupied by the Allies as of 31 December 1945, but is listed as a member of the state system in Polity IV as the Federal Republic, though with a polity score of -66, “interregnum”).

One nice thing about country_year_coder (in my humble opinion!) is that it can sometimes correct country coding errors; I’ve run across more than one dataset with the supposed COW code 255 for the Federal Republic of Germany for the period 1955-1990, which would prevent a clean join to a dataset with the correct COW code, but would be caught by country_year_coder.

There is also a function that allows you to create a blank state system panel for any of the three main state systems:

``$ \text{r} \text{create_panel}(\text{system} = "\text{cow}") #> # \text{A} \text{tibble}: 17{,}816 \times 5 #> \text{cown} \text{cow_country_name} \text{cow_startdate} \text{cow_enddate} \text{year} #> <\text{dbl}> <\text{chr}> <\text{date}> <\text{date}> <\text{dbl}> #> 1 700 \text{Afghanistan} 1919-08-08 \text{NA} 1919 #> 2 700 \text{Afghanistan} 1919-08-08 \text{NA} 1920 #> 3 700 \text{Afghanistan} 1919-08-08 \text{NA} 1921 #> 4 700 \text{Afghanistan} 1919-08-08 \text{NA} 1922 #> 5 700 \text{Afghanistan} 1919-08-08 \text{NA} 1923 #> 6 700 \text{Afghanistan} 1919-08-08 \text{NA} 1924 #> 7 700 \text{Afghanistan} 1919-08-08 \text{NA} 1925 #> 8 700 \text{Afghanistan} 1919-08-08 \text{NA} 1926 #> 9 700 \text{Afghanistan} 1919-08-08 \text{NA} 1927 #> 10 700 \text{Afghanistan} 1919-08-08 \text{NA} 1928 #> # ℹ 17{,}806 \text{more} \text{rows}

\text{create_panel}(\text{system} = "\text{GW}") #> # \text{A} \text{tibble}: 20{,}726 \times 5 #> \text{GWn} \text{GW_country_name} \text{GW_startdate} \text{GW_enddate} \text{year} #> <\text{dbl}> <\text{chr}> <\text{date}> <\text{date}> <\text{dbl}> #> 1 700 \text{Afghanistan} 1919-05-01 \text{NA} 1919 #> 2 700 \text{Afghanistan} 1919-05-01 \text{NA} 1920 #> 3 700 \text{Afghanistan} 1919-05-01 \text{NA} 1921 #> 4 700 \text{Afghanistan} 1919-05-01 \text{NA} 1922 #> 5 700 \text{Afghanistan} 1919-05-01 \text{NA} 1923 #> 6 700 \text{Afghanistan} 1919-05-01 \text{NA} 1924 #> 7 700 \text{Afghanistan} 1919-05-01 \text{NA} 1925 #> 8 700 \text{Afghanistan} 1919-05-01 \text{NA} 1926 #> 9 700 \text{Afghanistan} 1919-05-01 \text{NA} 1927 #> 10 700 \text{Afghanistan} 1919-05-01 \text{NA} 1928 #> # ℹ 20{,}716 \text{more} \text{rows} $``

Citation

The standard citation function from base R will produce a list of citations for all the datasets included in this package:

citation(package = "democracyData")

To cite any of the datasets included in this package use:

Acemoglu D, Naidu S, Restrepo P, Robinson JA (2019). “Democracy Does Cause Growth.” Journal of Political Economy, 127(1), 47-100. doi:10.1086/700936 https://doi.org/10.1086/700936.

Anckar C, Fredriksson C (2018). “Classifying Political Regimes 1800–2016: A Typology and a New Dataset.” European Political Science, 18(1), 84-96. doi:10.1057/s41304-018-0149-8 https://doi.org/10.1057/s41304-018-0149-8.

Arat ZF (1991). Democracy and Human Rights in Developing Countries. Lynne Rienner Publishers, Boulder.

Bell C (2016). “The Rulers, Elections, and Irregular Governance Dataset (REIGN).” https://oefdatascience.github.io/REIGN.github.io/.

Bernhard M, Nordstrom T, Reenock C (2001). “Economic Performance, Institutional Intermediation, and Democratic Survival.” Journal of Politics, 63(3), 775-803. doi:10.1111/0022-3816.00087 https://doi.org/10.1111/0022-3816.00087.

Bertelsmann Stiftung (2026). “Transformation Index BTI 2026: Governance in International Comparison.” Bertelsmann Stiftung, Gütersloh. https://www.bertelsmann-stiftung.de/en/publications/publication/did/transformation-index-bti-2026.

Bertelsmann Stiftung (2024). “Transformation Index of the Bertelsmann Stiftung 2024.” Bertelsmann Stiftung.

Bjørnskov C, Rode M (2025). “Bjørnskov-Rode Integrated Dataset v6.2.” http://www.christianbjoernskov.com/bjoernskovrodedata/.

Bjørnskov C, Rode M (2020). “Regime Types and Regime Change: A New Dataset on Democracy, Coups, and Political Institutions.” The Review of International Organizations, 15(2), 531-551. doi:10.1007/s11558-019-09345-1 https://doi.org/10.1007/s11558-019-09345-1.

Boix C, Miller M, Rosato S (2012). “A Complete Data Set of Political Regimes, 1800–2007.” Comparative Political Studies, 46(12), 1523-1554. doi:10.1177/0010414012463905 https://doi.org/10.1177/0010414012463905.

Bollen KA (2001). “Cross-National Indicators of Liberal Democracy, 1950-1990.” doi:10.3886/ICPSR02532.v2 https://doi.org/10.3886/ICPSR02532.v2.

Bollen K, Paxton P (2000). “Subjective Measures of Liberal Democracy.” Comparative Political Studies, 33(1), 58-86. doi:10.1177/0010414000033001003 https://doi.org/10.1177/0010414000033001003.

Bowman K, Lehoucq F, Mahoney J (2005). “Measuring Political Democracy: Case Expertise, Data Adequacy, and Central America.” Comparative Political Studies, 38(8), 939-970. doi:10.1177/0010414005277083 https://doi.org/10.1177/0010414005277083.

Chalmers RP (2012). “mirt: A Multidimensional Item Response Theory Package for the R Environment.” Journal of Statistical Software, 48(6), 1-29. doi:10.18637/jss.v048.i06 https://doi.org/10.18637/jss.v048.i06.

Cheibub JA, Gandhi J, Vreeland JR (2009). “Democracy and Dictatorship Revisited.” Public Choice, 143(1-2), 67-101. doi:10.1007/s11127-009-9491-2 https://doi.org/10.1007/s11127-009-9491-2.

Coppedge M, Alvarez A, Maldonado C (2008). “Two Persistent Dimensions of Democracy: Contestation and Inclusiveness.” The journal of politics, 70(03), 632-647. doi:10.1017/S0022381608080663 https://doi.org/10.1017/S0022381608080663.

Coppedge M, Gerring J, Knutsen CH, Lindberg SI, Teorell J, Altman D, Angiolillo F, Bernhard M, Borella C, Cornell A, Fish MS, Fox L, Gastaldi L, Gjerløw H, Glynn A, Good God A, Grahn S, Hicken A, Kinzelbach K, Marquardt KL, McMann K, Mechkova V, Neundorf A, Paxton P, Pemstein D, Rydén O, von Römer J, Seim B, Sigman R, Skaaning S, Staton J, Sundström A, Tzelgov E, Uberti L, Wang Y, Wig T, Ziblatt D (2024). “V-Dem Codebook V14.” Varieties of Democracy (V-Dem) Project. https://www.v-dem.net/data/the-v-dem-dataset/.

Coppedge M, Gerring J, Knutsen CH, Lindberg SI, Teorell J, Altman D, Angiolillo F, Bernhard M, Cornell A, Fish MS, Fox L, Gastaldi L, Gjerløw H, Glynn A, God AG, Grahn S, Hicken A, Kinzelbach K, Marquardt KL, McMann K, Mechkova V, Neundorf A, Paxton P, Pemstein D, von Römer J, Seim B, Sigman R, Skaaning S, Staton J, Sundström A, Tannenberg M, Tzelgov E, Wang Y, Wiebrecht F, Wig T, Ziblatt D (2025). “V-Dem Codebook V15.” Varieties of Democracy (V-Dem) Project. https://www.v-dem.net/.

Coppedge M, Gerring J, Knutsen CH, Lindberg SI, Teorell J, Altman D, Angiolillo F, Bernhard M, Cornell A, Fish MS, Fox L, Gastaldi L, Gjerløw H, Glynn A, God AG, Hicken A, Kinzelbach K, Krusell J, Marquardt KL, McMann K, Mechkova V, Medzihorsky J, Neundorf A, Paxton P, Pemstein D, Pernes J, von Römer J, Seim B, Sigman R, Skaaning S, Staton J, Sundström A, Tannenberg M, Tzelgov E, Wang Y, Wig T, Wilson S, Ziblatt D (2026). “V-Dem [Country-Year/Country-Date] Dataset V16.” Varieties of Democracy (V-Dem) Project. https://www.v-dem.net/data/the-v-dem-dataset/.

Coppedge M, Gerring J, Knutsen CH, Lindberg SI, Teorell J, Altman D, Angiolillo F, Bernhard M, Cornell A, Fish MS, Fox L, Gastaldi L, Gjerløw H, Glynn A, God AG, Hicken A, Kinzelbach K, Marquardt KL, McMann K, Mechkova V, Neundorf A, Paxton P, Pemstein D, Pernes J, von Römer J, Seim B, Sigman R, Skaaning S, Staton J, Sundström A, Tannenberg M, Tzelgov E, Wang Y, Wig T, Ziblatt D (2026). “V-Dem Codebook V16.” Varieties of Democracy (V-Dem) Project. https://www.v-dem.net/documents/70/codebook_v16.pdf.

Coppedge M, Gerring J, Knutsen CH, Lindberg SI, Teorell J, Altman D, Bernhard M, Cornell A, Fish MS, Gastaldi L, Gjerløw H, Glynn A, Grahn S, Hicken A, Kinzelbach K, Marquardt KL, McMann K, Mechkova V, Neundorf A, Paxton P, Pemstein D, Rydén O, von Römer J, Seim B, Sigman R, Skaaning S, Staton J, Sundström A, Tzelgov E, Uberti L, Wang Y, Wig T, Ziblatt D (????). “V-Dem Codebook V13.”

Coppedge M, Reinicke WH (1990). “Measuring Polyarchy.” Studies in Comparative International Development, 25(1), 51-72.

Correlates of War Project (2017). “State System Membership List, V2016.” https://correlatesofwar.org.

Doorenspleet R (2000). “Reassessing the Three Waves of Democratization.” World Politics, 52(03), 384-406. doi:10.1017/S0043887100016580 https://doi.org/10.1017/S0043887100016580.

Freedom House (2024). “Freedom in the World 2024: The Mounting Damage of Flawed Elections and Armed Conflict.” Freedom House. https://freedomhouse.org/report/freedom-world/2024/mounting-damage-flawed-elections-and-armed-conflict.

Freedom House (2025). “Freedom in the World 2025: The Uphill Battle to Safeguard Rights.” Freedom House.

Freedom House (2026). “Freedom in the World 2026: The Growing Shadow of Autocracy.” Freedom House.

Gasiorowski M (1996). “An Overview of the Political Regime Change Dataset.” Comparative Political Studies, 29(4), 469-483. doi:10.1177/0010414096029004004 https://doi.org/10.1177/0010414096029004004.

Geddes B, Wright J, Frantz E (2014). “Autocratic Breakdown and Regime Transitions: A New Data Set.” Perspectives on Politics, 12(1), 313-331. doi:10.1017/S1537592714000851 https://doi.org/10.1017/S1537592714000851.

Gleditsch KS, Ward MD (1999). “Interstate System Membership: A Revised List of Independent States since the Congress of Vienna.” International Interactions, 25(4), 393-413. doi:10.1080/03050629908434958 https://doi.org/10.1080/03050629908434958.

Goldstone J, Bates R, Epstein D, Gurr T, Lustik M, Marshall M, Ulfelder J, Woodward M (2010). “A Global Model for Forecasting Political Instability.” American Journal of Political Science, 54(1), 190-208. doi:10.1111/j.1540-5907.2009.00426.x https://doi.org/10.1111/j.1540-5907.2009.00426.x.

Gründler K, Krieger T (2016). “Democracy and Growth: Evidence from a Machine Learning Indicator.” European Journal of Political Economy, 45, 85-107. doi:10.1016/j.ejpoleco.2016.05.005 https://doi.org/10.1016/j.ejpoleco.2016.05.005.

Gründler K, Krieger T (2018). “Machine Learning Indices, Political Institutions, and Economic Development.” CESifo Group Munich. https://dx.doi.org/10.2139/ssrn.3171982.

Gründler K, Krieger T (2021/05/17/). “Using Machine Learning for Measuring Democracy: A Practitioners Guide and a New Updated Dataset for 186 Countries from 1919 to 2019.” European Journal of Political Economy, 102047. doi:10.1016/j.ejpoleco.2021.102047 https://doi.org/10.1016/j.ejpoleco.2021.102047.

Hadenius A (1992). Democracy and Development. Cambridge University Press, New York.

Hadenius A, Teorell J (2007). “Pathways from Authoritarianism.” Journal of Democracy, 18(1), 143-157. doi:10.1353/jod.2007.0009 https://doi.org/10.1353/jod.2007.0009.

Hsu S (2008). “The Effect of Political Regimes on Inequality, 1963-2002.” UTIP Working Paper.

Kailitz S (2013). “Classifying Political Regimes Revisited: Legitimation and Durability.” Democratization, 20(1), 39-60.

Kailitz S (2024). “Varieties of Political Regimes (va-PoReg). Codebook. Version 1.7.” Hannah Arendt Institute for Totalitarianism Studies, Dresden.

Kailitz S (2026). “Varieties of Political Regimes (va-PoReg). Codebook. Version 3.2.” Hannah Arendt Institute for Totalitarianism Studies, Dresden.

Kailitz S (2024). “Varieties of Political Regimes (va-PoReg). Dataset.”

Kailitz S (2026). “Varieties of Political Regimes (va-PoReg). Dataset. Version 3.2.” Hannah Arendt Institute for Totalitarianism Studies.

Kaufmann D, Kraay A (2020). “Worldwide Governance Indicators.” http://www.govindicators.org.

Kaufmann D, Kraay AC (2024). “The Worldwide Governance Indicators: Methodology and 2024 Update.” Policy Research Working Paper 10952, World Bank Group, Washington, DC. https://openknowledge.worldbank.org/entities/publication/4649907e-8902-4e74-a7ed-0e205e5e7919.

Magaloni B, Chu J, Min E (2013). “Autocracies of the World, 1950-2012 (Version 1.0).” https://dx.doi.org/10.2139/ssrn.4346003.

Mainwaring S, Brinks D, Pérez-Liñán A (2001). “Classifying Political Regimes in Latin America.” Studies in Comparative International Development, 36(1), 37-65. doi:10.1007/bf02687584 https://doi.org/10.1007/bf02687584.

Mainwaring S, Pérez-Liñán A, Brinks D (2014). “Political Regimes in Latin America, 1900-2007 (with Daniel Brinks).” In Democracies and Dictatorships in Latin America: Emergence, Survival, and Fall. Cambridge University Press, New York. https://web.archive.org/web/20120119050029/http://kellogg.nd.edu/scottmainwaring/Political_Regimes.pdf.

Márquez X (2020). “democracyData: A Package for Accessing and Manipulating Existing Measures of Democracy.” https://github.com/xmarquez/democracyData.

Márquez X (2016). “A Quick Method for Extending the Unified Democracy Scores.” Available at SSRN 2753830. doi:10.2139/ssrn.2753830 https://doi.org/10.2139/ssrn.2753830.

Marshall MG, Gurr TR (2020). Polity 5: Political Regime Characteristics and Transitions, 1800-2018. Dataset Users’ Manual..

Marshall MG, Gurr TR, Jaggers K (2019). Polity IV Project: Political Regime Characteristics and Transitions, 1800-2018. Dataset Users’ Manual..

Moon BE, Birdsall JH, Ciesluk S, Garlett LM, Hermias JJ, Mendenhall E, Schmid PD, Wong WH (2006). “Voting Counts: Participation in the Measurement of Democracy.” Studies in Comparative International Development, 41(2), 3-32. doi:10.1007/BF02686309 https://doi.org/10.1007/BF02686309.

Munck G (2009). Measuring Democracy: A Bridge between Scholarship and Politics. The Johns Hopkins University Press, Baltimore.

Pemstein D, Marquardt KL, Tzelgov E, Wang Y, Medzihorsky J, Krusell J, Miri F, von Römer J (2022). “The V-dem Measurement Model: Latent Variable Analysis for Cross-national and Cross-temporal Expert-coded Data.” Report 21, Varieties of Democracy Institute, University of Gothenburg. https://www.v-dem.net/media/publications/Working_Paper_21.pdf.

Pemstein D, Meserve SA, Melton J (2013). “Replication Data for: Democratic Compromise: A Latent Variable Analysis of Ten Measures of Regime Type.” doi:10.7910/DVN/WWYOHU https://doi.org/10.7910/DVN/WWYOHU, 1902.1/PMM.

Pemstein D, Meserve S, Melton J (2010). “Democratic Compromise: A Latent Variable Analysis of Ten Measures of Regime Type.” Political Analysis, 18(4), 426-449. doi:10.1093/pan/mpq020 https://doi.org/10.1093/pan/mpq020.

Przeworski A (2013). “Political Institutions and Political Events (PIPE) Data Set.” https://sites.google.com/a/nyu.edu/adam-przeworski/home/data.

Reich G (2002). “Categorizing Political Regimes: New Data for Old Problems.” Democratization, 9(4), 1-24. doi:10.1080/714000289 https://doi.org/10.1080/714000289.

Skaaning S, Gerring J, Bartusevičius H (2015). “A Lexical Index of Electoral Democracy.” Comparative Political Studies, 48(12), 1491-1525. doi:10.1177/0010414015581050 https://doi.org/10.1177/0010414015581050.

Svolik M (2012). The Politics of Authoritarian Rule. Cambridge University Press, Cambridge and New York.

Taylor SJ, Ulfelder J (2015). “A Measurement Error Model of Dichotomous Democracy Status.” Available at SSRN. doi:10.2139/ssrn.2726962 https://doi.org/10.2139/ssrn.2726962.

The Economist Intelligence Unit (2025). “Democracy Index 2024: What’s Wrong with Representative Democracy?” The Economist Intelligence Unit Limited, London, UK. https://www.eiu.com/n/global-themes/democracy-index/.

The Economist Intelligence Unit (2026). “Democracy Index 2025: Democracy Stabilises after Eight Years of Decline.” Economist Intelligence Unit, London. https://www.eiu.com/n/campaigns/democracy-index-2025/.

The Economist Intelligence Unit (2023). “Democracy Index 2022: Frontline Democracy and the Battle for Ukraine.” The Economist Intelligence Unit.

The Economist Intelligence Unit (2024). “Democracy Index 2023: Age of Conflict.” Economist Intelligence Unit, London, United Kingdom.

Ulfelder J (2012). “Democracy/Autocracy Data Set.” doi:10.7910/DVN/M11WFC https://doi.org/10.7910/DVN/M11WFC, 1902.1/18836.

Ulfelder J, Lustik M (2007). “Modelling Transitions to and from Democracy.” Democratization, 14(3), 351-387. doi:10.1080/13510340701303196 https://doi.org/10.1080/13510340701303196.

Vanhanen T (2019). “Measures of Democracy 1810-2018 (Dataset). Version 8.0 (2019-06-17).” https://urn.fi/urn:nbn:fi:fsd:T-FSD1289.

Wahman M, Teorell J, Hadenius A (2013). “Authoritarian Regime Types Revisited: Updated Data in Comparative Perspective.” Contemporary Politics, 19(1), 19-34. doi:10.1080/13569775.2013.773200 https://doi.org/10.1080/13569775.2013.773200.

World Bank (2025). “The Worldwide Governance Indicators: Revised Methodology for Measuring Governance Using Perception Data.” World Bank Group, Washington, DC. https://www.worldbank.org/content/dam/sites/govindicators/doc/The%20Worldwide%20Governance%20Indicators%202025%20Methodology%20Revision.pdf.

World Bank (2025). “Worldwide Governance Indicators, 2025 Revision.” www.govindicators.org. http://www.govindicators.org.

To see these entries in BibTeX format, use ‘print(, bibtex=TRUE)’, ‘toBibtex(.)’, or set ‘options(citation.bibtex.max=999)’.

You can also find the citation for a specific dataset using the wrapper cite_dataset with the name of the dataset in this package:

cite_dataset("gwf")

[1] B. Geddes, J. Wright, and E. Frantz. “Autocratic Breakdown and Regime Transitions: A New Data Set”. In: Perspectives on Politics 12.1 (2014), pp. 313-331. DOI: 10.1017/S1537592714000851.

Feedback and Caveats

Feedback welcome!

Note that some functions in this package can be quite slow: generating a full democracy dataset (including downloading Freedom House, Polity, and WGI) or applying country_year_coder to a large data frame both can take some time. Suggestions to accelerate the code are welcome.

country_year_coder fails to give correct answers in some weird edge cases mostly involving Yugoslavia, Germany, or Vietnam. If you run across any of these cases, let me know.