Skip to contents

create_dyadyears() allows you to dyad-year data from either the Correlates of War (CoW) state system membership data or the Gleditsch-Ward (gw) system membership data. The function leans on internal data provided in the package.

Usage

create_dyadyears(system = "cow", mry = TRUE, directed = TRUE, subset_years)

Arguments

system

a character specifying whether the user wants Correlates of War state-years ("cow") or Gleditsch-Ward ("gw") state-years. Correlates of War is the default.

mry

optional, defaults to TRUE. If TRUE, the function extends the script beyond the most recent system membership updates to include observation to the most recently concluded calendar year. For example, the Gleditsch-Ward data extend to the end of 2017. When mry == TRUE, the function returns more recent years (e.g. 2018, 2019) under the assumption that states alive at the end of 2017 are still alive today. Use with some care.

directed

optional, defaults to TRUE. If TRUE, the function returns so-called "directed" dyad-year data. In directed dyad-year data, France-Germany (220-255) and Germany-France (255-220) are observationally different. If FALSE, the function returns non-directed data. In non-directed data, France-Germany and Germany-France in the same year are the same observation. The standard here is to drop cases where the country code for the second observation is less than the country code for the first observation.

subset_years

and optional character vector for subsetting the years returned to just some temporal domain of interest to the user. For example, c(1816:1820) would subset the data to just all dyad-years in 1816, 1817, 1818, 1819, and 1820. Be advised that it's easiest to subset the data after the full universe of dyad-year data have been created. This means you could, if you choose, effectively overwrite mry = TRUE with this argument since the mry argument is applied at the expansion of the state system data, which occurs at the start of the function.

Value

create_dyadyears() takes state system membership data provided by either Correlates of War or Gleditsch-Ward and returns a dyad-year data frame.

References

Miller, Steven V. 2019. ``Create Country-Year and (Non)-Directed Dyad-Year Data With Just a Few Lines in R'' http://svmiller.com/blog/2019/01/create-country-year-dyad-year-from-country-data/

Author

Steven V. Miller

Examples

# \donttest{
# CoW is default, will include years beyond 2016 (most recent CoW update)
create_dyadyears()
#> Joining, by = c("ccode1", "ccode2", "year")
#> # A tibble: 2,101,440 × 3
#>    ccode1 ccode2  year
#>     <dbl>  <dbl> <int>
#>  1      2     20  1920
#>  2      2     20  1921
#>  3      2     20  1922
#>  4      2     20  1923
#>  5      2     20  1924
#>  6      2     20  1925
#>  7      2     20  1926
#>  8      2     20  1927
#>  9      2     20  1928
#> 10      2     20  1929
#> # … with 2,101,430 more rows

# Gleditsch-Ward, include most recent years
create_dyadyears(system="gw")
#> Joining, by = c("gwcode1", "gwcode2", "year")
#> # A tibble: 2,059,724 × 3
#>    gwcode1 gwcode2  year
#>      <dbl>   <dbl> <int>
#>  1       2      20  1867
#>  2       2      20  1868
#>  3       2      20  1869
#>  4       2      20  1870
#>  5       2      20  1871
#>  6       2      20  1872
#>  7       2      20  1873
#>  8       2      20  1874
#>  9       2      20  1875
#> 10       2      20  1876
#> # … with 2,059,714 more rows

# Gleditsch-Ward, don't include most recent years
create_dyadyears(system="gw", mry=FALSE)
#> Joining, by = c("gwcode1", "gwcode2", "year")
#> # A tibble: 1,939,316 × 3
#>    gwcode1 gwcode2  year
#>      <dbl>   <dbl> <int>
#>  1       2      20  1867
#>  2       2      20  1868
#>  3       2      20  1869
#>  4       2      20  1870
#>  5       2      20  1871
#>  6       2      20  1872
#>  7       2      20  1873
#>  8       2      20  1874
#>  9       2      20  1875
#> 10       2      20  1876
#> # … with 1,939,306 more rows

# Gleditsch-Ward, don't include most recent years, directed = FALSE
create_dyadyears(system="gw", mry=FALSE, directed = FALSE)
#> Joining, by = c("gwcode1", "gwcode2", "year")
#> # A tibble: 969,658 × 3
#>    gwcode1 gwcode2  year
#>      <dbl>   <dbl> <int>
#>  1       2      20  1867
#>  2       2      20  1868
#>  3       2      20  1869
#>  4       2      20  1870
#>  5       2      20  1871
#>  6       2      20  1872
#>  7       2      20  1873
#>  8       2      20  1874
#>  9       2      20  1875
#> 10       2      20  1876
#> # … with 969,648 more rows
# }