Extract joint membership for a pair of countries across IGOs

Create a dyadic version of the data. The unit of observation is a country dyad. The result summarizes joint memberships across IGOs over time.

Usage

igo_dyadic(country1, country2, year = 1816:2014, ioname = NULL)

Source

Codebook Version 3 IGO Data for full reference.

Arguments

country1, country2: State or vector of states to compare. Values can be any valid state name or code as specified in states2016.
year: Year to assess, as an integer or vector of years.
ioname: Optional. ioname or vector of ioname corresponding to the IGOs to assess. If NULL (the default), all IGOs will be extracted. See codes in igo_search().

Value

A coded data.frame with years and country dyads as rows and selected IGOs as columns. See Details.

Details

This function tries to replicate the information contained in the original file distributed by The Correlates of War Project (dyadic_format3.dta). That file is not included in this package due to its size.

The result is a data.frame with one row for each common year selected via country1, country2 and year.

An additional column, dyadid, computed as (1000 * ccode1) + ccode2, is provided to identify relationships.

For each IGO selected via ioname, or all IGOs if the default option is used, a column using lowercase ioname as an identifier is provided with the following coding system:

Category	Numerical Value
No Joint Membership	0
Joint Full Membership	1
Missing data	-9
State Not System Member	-1

See the igo_recode_dyadic() section for an easy way to recode the numerical values into factors.

If one state in an IGO is a full member but the other is an associate member or observer, that IGO is not coded as a joint membership.

Differences from the original data set

Some results from this function differ from the original data set for some IGOs regarding "Missing data" (-9) and "State Not System Member" (-1). However, it is not clear how to fully replicate those values.

See Codebook Version 3 IGO Data.

References

Pevehouse, J. C., Nordstrom, T., McManus, R. W., & Jamison, A. S. (2020). Tracking organizations in the world: The Correlates of War IGO Version 3.0 data sets. Journal of Peace Research, 57(3), 492–503. doi:10.1177/0022343319881175 .

Examples

usa_esp <- igo_dyadic("USA", "Spain")
nrow(usa_esp)
#> [1] 199
ncol(usa_esp)
#> [1] 546

dplyr::tibble(usa_esp)
#> # A tibble: 199 × 546
#>    dyadid ccode1 stateabb1 statenme1    state1 ccode2 stateabb2 statenme2 state2
#>     <dbl>  <int> <chr>     <chr>        <chr>   <int> <chr>     <chr>     <chr> 
#>  1   2002      2 USA       United Stat… usa       230 SPN       Spain     spain 
#>  2   2002      2 USA       United Stat… usa       230 SPN       Spain     spain 
#>  3   2002      2 USA       United Stat… usa       230 SPN       Spain     spain 
#>  4   2002      2 USA       United Stat… usa       230 SPN       Spain     spain 
#>  5   2002      2 USA       United Stat… usa       230 SPN       Spain     spain 
#>  6   2002      2 USA       United Stat… usa       230 SPN       Spain     spain 
#>  7   2002      2 USA       United Stat… usa       230 SPN       Spain     spain 
#>  8   2002      2 USA       United Stat… usa       230 SPN       Spain     spain 
#>  9   2002      2 USA       United Stat… usa       230 SPN       Spain     spain 
#> 10   2002      2 USA       United Stat… usa       230 SPN       Spain     spain 
#> # ℹ 189 more rows
#> # ℹ 537 more variables: year <dbl>, ccode <dbl>, state <dbl>, aaaid <dbl>,
#> #   aacb <dbl>, aalco <dbl>, aaro <dbl>, aata <dbl>, aatpo <dbl>, abeda <dbl>,
#> #   abepseac <dbl>, acc <dbl>, acct <dbl>, acdt <dbl>, aci <dbl>, acml <dbl>,
#> #   acp <dbl>, acpeu <dbl>, acs <dbl>, acso <dbl>, acssrb <dbl>, acu <dbl>,
#> #   acwl <dbl>, afesd <dbl>, afeximb <dbl>, afgec <dbl>, afpu <dbl>,
#> #   afrand <dbl>, afristat <dbl>, afspc <dbl>, afte <dbl>, agc <dbl>, …

# Use custom arguments.
custom <- igo_dyadic(
  country1 = c("France", "Germany"), country2 = c("Sweden", "Austria"),
  year = 1992:1993, ioname = "EU"
)

dplyr::glimpse(custom)
#> Rows: 8
#> Columns: 11
#> $ dyadid    <dbl> 220220, 220220, 255255, 255255, 220220, 220220, 255255, 2552…
#> $ ccode1    <int> 220, 220, 255, 255, 220, 220, 255, 255
#> $ stateabb1 <chr> "FRN", "FRN", "GMY", "GMY", "FRN", "FRN", "GMY", "GMY"
#> $ statenme1 <chr> "France", "France", "Germany", "Germany", "France", "France"…
#> $ state1    <chr> "france", "france", "germany", "germany", "france", "france"…
#> $ ccode2    <int> 380, 380, 380, 380, 305, 305, 305, 305
#> $ stateabb2 <chr> "SWD", "SWD", "SWD", "SWD", "AUS", "AUS", "AUS", "AUS"
#> $ statenme2 <chr> "Sweden", "Sweden", "Sweden", "Sweden", "Austria", "Austria"…
#> $ state2    <chr> "sweden", "sweden", "sweden", "sweden", "austria", "austria"…
#> $ year      <dbl> 1992, 1993, 1992, 1993, 1992, 1993, 1992, 1993
#> $ eu        <dbl> -1, 0, -1, 0, -1, 0, -1, 0