Create country-year/month/day panels consistent with the COW or Gleditsch & Ward lists of independent states. I mainly use this for merging different data sources:
- Create a master template that reflects one of the independent states lists.
- For each data source, normalize to a copy of the master template. Doing this by source makes it easier to identify and address issues like missing values or observation for non-independent states.
- In the end, merge everything together. Since all the inputs are already normalized to a proper state panel list, there should be no issues.
What the package does:
- It contains the Gleditsch and Ward (G&W) as well as the Correlates of War (COW) state system membership lists.
library("states")
data(gwstates)
data(cowstates)- Search them with
sfind, this can be helpful for manual coding:
sfind(260)[, 1:6]
#> list ccode code3c country_name start end
#> 45 GW 260 GFR German Federal Republic 1949-09-21 9999-12-31
#> 299 COW 260 GFR German Federal Republic 1955-05-05 1990-10-02
sfind("German")[, 1:6]
#> list ccode code3c country_name start end
#> 44 GW 255 GMY Germany (Prussia) 1816-01-01 1945-05-07
#> 45 GW 260 GFR German Federal Republic 1949-09-21 9999-12-31
#> 46 GW 265 GDR German Democratic Republic 1949-10-05 1990-10-02
#> 297 COW 255 GMY Germany 1816-01-01 1945-05-08
#> 298 COW 255 GMY Germany 1990-10-03 9999-12-31
#> 299 COW 260 GFR German Federal Republic 1955-05-05 1990-10-02
#> 300 COW 265 GDR German Democratic Republic 1954-03-25 1990-10-02- You can use it to build a country-year template that matches either the COW or G&W state lists.
countries <- state_panel(1991, 2001)
str(countries)
#> 'data.frame': 2091 obs. of 2 variables:
#> $ gwcode: int 2 2 2 2 2 2 2 2 2 2 ...
#> $ year : int 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 ...- Visualize missing/non-independent cases in your data. See this related blog post for more details.
data("polity")
str(polity)
#> 'data.frame': 17228 obs. of 3 variables:
#> $ ccode : num 700 700 700 700 700 700 700 700 700 700 ...
#> $ year : num 1800 1801 1802 1803 1804 ...
#> $ polity: num -6 -6 -6 -6 -6 -6 -6 -6 -6 -6 ...
plot_missing(polity, x = "polity", ccode = "ccode", statelist = "COW")
For the underlying data (missing info requires date input):
polity$date <- as.Date(paste0(polity$year, "-01-01"))
mm <- missing_info(polity, x = "polity", ccode = "ccode",
time = "date", period = "year",
statelist = "COW")
head(mm)
#> ccode date independent missing_value status
#> 18671 2 1800-01-01 0 FALSE Complete, non-independent
#> 18672 2 1801-01-01 0 FALSE Complete, non-independent
#> 18673 2 1802-01-01 0 FALSE Complete, non-independent
#> 18674 2 1803-01-01 0 FALSE Complete, non-independent
#> 18675 2 1804-01-01 0 FALSE Complete, non-independent
#> 18676 2 1805-01-01 0 FALSE Complete, non-independentThe package is on CRAN and can be installed with:
install.packages("states")Or to install from GitHub:
library("remotes")
remotes::install_github("andybega/states")For the Gleditsch and Ward (G&W) state data:
Gleditsch, Kristian S. & Michael D. Ward. 1999. “Interstate System Membership: A Revised List of the Independent States since 1816.” International Interactions 25: 393-413.
For the Correlates of War (COW) state data:
Correlates of War Project. 2017. “State System Membership List, v2016.” Online, https://correlatesofwar.org