Data on intergovernmental organizations (IGOs) from 1816 to 2014 at the IGO-year level. Each row represents one IGO in one year. Years are recorded at five-year intervals through 1965 and annually thereafter.
Format
A data.frame with
19,335 rows. Relevant
fields:
ioname: Short abbreviation for the IGO name.orgname: Full IGO name.year: Calendar year.afghanistan...zimbabwe: Membership status of each state in the IGO. See the Details section.sdate: Start year for the IGO.deaddate: End year for the IGO.longorgname: Longer IGO name, including previous names.ionum: IGO identifier in versions 2.1 and 3.0 of the data.version: Correlates of War version number.
Source
Intergovernmental Organizations (version 3), IGO Data Stata Files from the Correlates of War Project.
See the Codebook Version 3 IGO Data for the full reference.
Details
Possible values for the status of a state in the IGO are:
| Category | Numerical value |
| No Membership | 0 |
| Full Membership | 1 |
| Associate Membership | 2 |
| Observer | 3 |
| Missing data | -9 |
| State Not System Member | -1 |
Use igo_recode_igoyear() to recode the numerical values as
factors.
Note
Data distributed with igoR.
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 .
See also
Other data sets:
state_year_format3,
states2016
Examples
data("igo_year_format3")
# Show a glimpse.
library(dplyr)
igo_year_format3 %>%
select(ioname:year, spain, france) %>%
filter(year > 1990) %>%
glimpse()
#> Rows: 8,019
#> Columns: 5
#> $ ioname <chr> "ACPEU", "ACPEU", "ACPEU", "ACPEU", "ACPEU", "ACPEU", "ACPEU",…
#> $ orgname <chr> "ACP/EU Joint Assembly", "ACP/EU Joint Assembly", "ACP/EU Join…
#> $ year <dbl> 1991, 1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000, 20…
#> $ spain <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,…
#> $ france <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,…
# Prepare a sample of numerical membership values.
sample_igo_year <- igo_year_format3 %>%
as_tibble() %>%
select(ioname:year, spain, france) %>%
filter(year == 1990)
sample_igo_year %>% glimpse()
#> Rows: 314
#> Columns: 5
#> $ ioname <chr> "ACPEU", "ACSSRB", "CAMES", "ACI", "AfDB", "AFGEC", "AIPO", "A…
#> $ orgname <chr> "ACP/EU Joint Assembly", "Administrative Center for Soc Securi…
#> $ year <dbl> 1990, 1990, 1990, 1990, 1990, 1990, 1990, 1990, 1990, 1990, 19…
#> $ spain <dbl> 1, 0, -9, 0, 1, 0, 0, 0, -9, 0, 0, 0, 0, 1, -9, -9, 0, 0, 0, 0…
#> $ france <dbl> 1, 1, -9, 0, 1, 0, 0, 0, -9, 0, 0, 0, 0, 1, -9, -9, 0, 0, 0, 0…
# Recode the membership columns.
sample_igo_year_recoded <- sample_igo_year %>%
mutate(across(c(spain, france), igo_recode_igoyear))
sample_igo_year_recoded %>% glimpse()
#> Rows: 314
#> Columns: 5
#> $ ioname <chr> "ACPEU", "ACSSRB", "CAMES", "ACI", "AfDB", "AFGEC", "AIPO", "A…
#> $ orgname <chr> "ACP/EU Joint Assembly", "Administrative Center for Soc Securi…
#> $ year <dbl> 1990, 1990, 1990, 1990, 1990, 1990, 1990, 1990, 1990, 1990, 19…
#> $ spain <fct> Full Membership, No Membership, Missing data, No Membership, F…
#> $ france <fct> Full Membership, Full Membership, Missing data, No Membership,…