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add_cow_alliance() allows you to add Correlates of War alliance data to a dyad-year data frame

Usage

add_cow_alliance(data)

Arguments

data

a dyad-year or leader-dyad-year data frame (either "directed" or "non-directed")

Value

add_cow_alliance() takes a dyad-year data frame and adds information about the alliance pledge in that given dyad-year. These include whether there was an alliance with a defense pledge, neutrality pledge, non-aggression pledge, or pledge for consultation in time of crisis (entente).

Details

Duplicates in the original directed dyad-year alliance data were pre-processed. Check cow_alliance in the package's data-raw directory on Github for more information.

This function will also work with leader-dyad-years, though users should be careful with leader-level applications of alliance data. Alliance data are primarily communicated yearly, making it possible---even likely---that at least one leader-dyad in a given year is credited with an alliance that was not active in the particular leader-dyad. The Correlates of War's alliance data are not communicated with time measurements more granular than the year. Apply these data to leader-level analyses with that in mind.

References

Gibler, Douglas M. 2009. International Military Alliances, 1648-2008. Congressional Quarterly Press.

Author

Steven V. Miller

Examples


# just call `library(tidyverse)` at the top of the your script
library(magrittr)

cow_ddy %>% add_cow_alliance()
#> Joining, by = c("ccode1", "ccode2", "year")
#> # A tibble: 2,101,440 × 7
#>    ccode1 ccode2  year cow_defense cow_neutral cow_nonagg cow_entente
#>     <dbl>  <dbl> <dbl>       <dbl>       <dbl>      <dbl>       <dbl>
#>  1      2     20  1920           0           0          0           0
#>  2      2     20  1921           0           0          0           0
#>  3      2     20  1922           0           0          0           0
#>  4      2     20  1923           0           0          0           0
#>  5      2     20  1924           0           0          0           0
#>  6      2     20  1925           0           0          0           0
#>  7      2     20  1926           0           0          0           0
#>  8      2     20  1927           0           0          0           0
#>  9      2     20  1928           0           0          0           0
#> 10      2     20  1929           0           0          0           0
#> # … with 2,101,430 more rows