Skip to contents

add_cow_majors() allows you to add Correlates of War major power variables to a dyad-year, leader-year, leader dyad-year, or state-year data frame.

Usage

add_cow_majors(data)

Arguments

data

a data frame with appropriate peacesciencer attributes

Value

add_cow_majors() takes a data frame and adds information about major power status for the given state or dyad in that year. If the data are dyad-year (or leader dyad-year), the function returns two columns for whether the first state (i.e. ccode1) or the second state (i.e. ccode2) are major powers in the given year, according to the Correlates of War. 1 = is a major power. 0 = is not a major power. If the data are state-year (or leader-year), the functions returns just one column (cowmaj) for whether the state was a major power in a given state-year.

Details

Be mindful that the data are fundamentally state-year and that extensions to leader-level data should be understood as approximations for leaders in a given state-year.

References

Correlates of War Project. 2017. "State System Membership List, v2016." Online, https://correlatesofwar.org/data-sets/state-system-membership

Author

Steven V. Miller

Examples


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

cow_ddy %>% add_cow_majors()
#> # A tibble: 2,101,440 × 5
#>    ccode1 ccode2  year cowmaj1 cowmaj2
#>     <dbl>  <dbl> <int>   <dbl>   <dbl>
#>  1      2     20  1920       1       0
#>  2      2     20  1921       1       0
#>  3      2     20  1922       1       0
#>  4      2     20  1923       1       0
#>  5      2     20  1924       1       0
#>  6      2     20  1925       1       0
#>  7      2     20  1926       1       0
#>  8      2     20  1927       1       0
#>  9      2     20  1928       1       0
#> 10      2     20  1929       1       0
#> # … with 2,101,430 more rows