Add Correlates of War major power information to a data frame
Source:R/add_cow_majors.R
add_cow_majors.Rdadd_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.
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/
Examples
# just call `library(tidyverse)` at the top of the your script
library(magrittr)
cow_ddy %>% add_cow_majors()
#> # A tibble: 2,139,270 × 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
#> # ℹ 2,139,260 more rows