Add Correlates of War international governmental organizations (IGOs) data to dyad-year or state-year data.
Source:R/add_igos.R
add_igos.Rdadd_igos() allows you to add information from the
Correlates of War International Governmental Organizations data to dyad-year
or state-year data, matching on Correlates of War system codes.
Value
add_igos() takes a dyad-year data frame or state-year data frame and
adds information available from the Correlates of War International
Governmental Organizations data. If the data are dyad-year, the function
returns the original data with just one additional column for the total
number of mutual IGOs for which both members of the dyad are full members. If
the data are state-year, the function returns the original data with four
additional columns. These are the number of IGOs for which the state is a
full member, the number of IGOs for which the state is an associate member,
the number of IGOs for which the state is an observer, and the number of IGOs
for which the state is involved in any way (i.e. the sum of the other three
columns).
Details
The function leans on attributes of the data that are provided by the
create_dyadyear() or create_stateyear() function. Make sure
that function (or data created by that function) appear at the top of the
proverbial pipe.
References
Pevehouse, Jon C.W., Timothy Nordstron, Roseanne W McManus, and Anne Spencer Jamison. 2020. "Tracking Organizations in the World: The Correlates of War IGO Version 3.0 datasets." Journal of Peace Research 57(3): 492-503.
Wallace, Michael, and J. David Singer. 1970. "International Governmental Organization in the Global System, 1815-1964." International Organization 24: 239-87.
Examples
# \donttest{
# just call library(tidyverse) at the top of the pipe
library(magrittr)
cow_ddy %>% add_igos()
#> Joining with `by = join_by(ccode1, ccode2, year)`
#> # A tibble: 2,214,930 × 4
#> ccode1 ccode2 year dyadigos
#> <dbl> <dbl> <dbl> <dbl>
#> 1 2 20 1920 7
#> 2 2 20 1921 8
#> 3 2 20 1922 8
#> 4 2 20 1923 7
#> 5 2 20 1924 7
#> 6 2 20 1925 8
#> 7 2 20 1926 8
#> 8 2 20 1927 8
#> 9 2 20 1928 8
#> 10 2 20 1929 8
#> # ℹ 2,214,920 more rows
create_stateyears() %>% add_igos()
#> Joining with `by = join_by(ccode, year)`
#> # A tibble: 17,511 × 7
#> ccode cw_name year sum_igo_full sum_igo_associate sum_igo_observer
#> <dbl> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 2 United States of… 1816 0 0 0
#> 2 2 United States of… 1817 0 0 0
#> 3 2 United States of… 1818 0 0 0
#> 4 2 United States of… 1819 0 0 0
#> 5 2 United States of… 1820 0 0 0
#> 6 2 United States of… 1821 0 0 0
#> 7 2 United States of… 1822 0 0 0
#> 8 2 United States of… 1823 0 0 0
#> 9 2 United States of… 1824 0 0 0
#> 10 2 United States of… 1825 0 0 0
#> # ℹ 17,501 more rows
#> # ℹ 1 more variable: sum_igo_anytype <dbl>
# }