Package 'igoR' reference manual

Title:	Intergovernmental Organizations Database
Description:	Tools to extract information from the Intergovernmental Organizations ('IGO') Database , version 3, provided by the Correlates of War Project <https://correlatesofwar.org/>. See also Pevehouse, J. C. et al. (2020). Version 3 includes information from 1815 to 2014.
Authors:	Diego Hernangómez [aut, cre, cph]
Maintainer:	Diego Hernangómez <[email protected]>
License:	GPL (>= 3)
Version:	0.2.1
Built:	2024-12-17 10:23:31 UTC
Source:	https://github.com/dieghernan/igoR

Extract the joint membership of a pair of countries across IGOs

Description

Dyadic version of the data. The unit of observation is a dyad of countries. It provides a summary of the joint memberships of two countries across IGOs over time.

Usage

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

Arguments

`country1`, `country2`	A state of vector of states to be compared. It could be any valid name or code of a state as specified on states2016.
`year`	Year to be assessed, an integer or an array of year.
`ioname`	Optional. `ioname` or vector of `ioname` corresponding to the IGOs to be assessed. If `NULL` (the default), all IGOs would be extracted. See codes on `igo_search()`.

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 containing the common years of the states selected via ⁠country1, country2, year⁠ by rows.

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

For each IGO selected via ioname (or all if the default option has been used) a column (using lowercase ioname as identifier) is provided with the following code system:

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

See 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.

Value

A coded data.frame representing the years and country dyad (rows) and the IGOs selected (columns). See Details.

Differences with the original dataset

There are some differences on the results provided by this function and the original dataset on some IGOs regarding the "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

Source

Codebook Version 3 IGO Data for full reference.

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 datasets. Journal of Peace Research, 57(3), 492–503. doi:10.1177/0022343319881175.

Examples

usa_esp <- igo_dyadic("USA", "Spain")
nrow(usa_esp)
ncol(usa_esp)

dplyr::tibble(usa_esp)

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

dplyr::glimpse(custom)
usa_esp <- igo_dyadic("USA", "Spain")
nrow(usa_esp)
ncol(usa_esp)

dplyr::tibble(usa_esp)

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

dplyr::glimpse(custom)

Extract members of an IGO

Description

Extract all the countries belonging to an IGO on a specific date.

Usage

igo_members(ioname, year = NULL, status = "Full Membership")
igo_members(ioname, year = NULL, status = "Full Membership")

Arguments

`ioname`	Any valid `ioname` of an IGO as specified on igo_year_format3. It could be also a vector of IGOs.
`year`	Year to be assessed, an integer or an array of year. If `NULL` the latest year available of the IGO would be extracted.
`status`	Character or vector with the membership status to be extracted. See Details on state_year_format3.

Value

A data.frame.

Examples

library(dplyr)
igo_members("EU", year = 1993) %>% as_tibble()
igo_members("EU") %>% as_tibble()
igo_members("NAFTA", year = c(1995:1998)) %>% as_tibble()

# Extract different status
igo_members("ACCT", status = c("Associate Membership", "Observer")) %>%
  as_tibble()

# States no members of the UN
igo_members("UN", status = "No Membership") %>%
  as_tibble()

# Vectorized
igo_members(c("NAFTA", "EU"), year = 1993) %>%
  as_tibble() %>%
  arrange(state)

# Use countrycodes package to get additional codes
if (requireNamespace("countrycode", quietly = TRUE)) {
  library(countrycode)
  EU <- igo_members("EU")
  EU$iso3c <- countrycode(EU$ccode, origin = "cown", destination = "iso3c")

  EU$continent <- countrycode(EU$ccode,
    origin = "cown",
    destination = "continent"
  )

  tibble(EU)
}
library(dplyr)
igo_members("EU", year = 1993) %>% as_tibble()
igo_members("EU") %>% as_tibble()
igo_members("NAFTA", year = c(1995:1998)) %>% as_tibble()

# Extract different status
igo_members("ACCT", status = c("Associate Membership", "Observer")) %>%
  as_tibble()

# States no members of the UN
igo_members("UN", status = "No Membership") %>%
  as_tibble()

# Vectorized
igo_members(c("NAFTA", "EU"), year = 1993) %>%
  as_tibble() %>%
  arrange(state)

# Use countrycodes package to get additional codes
if (requireNamespace("countrycode", quietly = TRUE)) {
  library(countrycode)
  EU <- igo_members("EU")
  EU$iso3c <- countrycode(EU$ccode, origin = "cown", destination = "iso3c")

  EU$continent <- countrycode(EU$ccode,
    origin = "cown",
    destination = "continent"
  )

  tibble(EU)
}

Helper functions to recode categories

Description

These functions convert the numerical code of igo_year_format3 and state_year_format3 into factors.

igo_recode_igoyear() is intended to work with values on igo_year_format3.
igo_recode_stateyear() is intended to work with values on state_year_format3.
igo_recode_dyadic() is intended to work with values on igo_dyadic().

Usage

igo_recode_igoyear(x)

igo_recode_stateyear(x)

igo_recode_dyadic(x)
igo_recode_igoyear(x)

igo_recode_stateyear(x)

igo_recode_dyadic(x)

Arguments

`x`	Numerical value (or vector of values) to recode.

Value

The recoded values as factors.

Examples

data("igo_year_format3")

# Recode memberships for some countries

library(dplyr)

samp <- igo_year_format3 %>%
  select(ioname:year, spain, france) %>%
  filter(year > 2000) %>%
  as_tibble()

glimpse(samp)

# Recode
samp %>%
  mutate(
    spain = igo_recode_igoyear(spain),
    france = igo_recode_igoyear(france)
  ) %>%
  glimpse()

data("igo_year_format3")

# Recode memberships for some countries

library(dplyr)

samp <- igo_year_format3 %>%
  select(ioname:year, spain, france) %>%
  filter(year > 2000) %>%
  as_tibble()

glimpse(samp)

# Recode
samp %>%
  mutate(
    spain = igo_recode_igoyear(spain),
    france = igo_recode_igoyear(france)
  ) %>%
  glimpse()

Search and find an IGO

Description

Search any IGO by name or string pattern.

Usage

igo_search(pattern = NULL, exact = FALSE)
igo_search(pattern = NULL, exact = FALSE)

Arguments

`pattern`	regex pattern. If `NULL` the function returns a dataset with all the IGOs on igo_year_format3. Integer values are accepted.
`exact`	Logical. When `TRUE` only exact matches are returned.

Details

The information of each IGO is retrieved based on the last year available on igo_year_format3.

An additional column label is provided. This column is a clean version of longorgname

Value

A data.frame.

Examples

# All values
library(dplyr)
all <- igo_search()

all %>% tibble()

# Search by pattern
igo_search("EU") %>%
  select(ionum:orgname) %>%
  tibble()

igo_search("EU", exact = TRUE) %>%
  select(ionum:orgname) %>%
  tibble()

# With integers
igo_search(10) %>%
  select(ionum:orgname) %>%
  tibble()

igo_search(10, exact = TRUE) %>%
  select(ionum:orgname) %>%
  tibble()

# Several patterns (regex style)
igo_search("NAFTA|UN|EU") %>%
  select(ionum:orgname) %>%
  tibble()

# Several patterns Exact (regex style)
igo_search("^NAFTA$|^UN$|^EU$") %>%
  select(ionum:orgname) %>%
  tibble()

# All values
library(dplyr)
all <- igo_search()

all %>% tibble()

# Search by pattern
igo_search("EU") %>%
  select(ionum:orgname) %>%
  tibble()

igo_search("EU", exact = TRUE) %>%
  select(ionum:orgname) %>%
  tibble()

# With integers
igo_search(10) %>%
  select(ionum:orgname) %>%
  tibble()

igo_search(10, exact = TRUE) %>%
  select(ionum:orgname) %>%
  tibble()

# Several patterns (regex style)
igo_search("NAFTA|UN|EU") %>%
  select(ionum:orgname) %>%
  tibble()

# Several patterns Exact (regex style)
igo_search("^NAFTA$|^UN$|^EU$") %>%
  select(ionum:orgname) %>%
  tibble()

Finds codes and names of a state

Description

Extract all the memberships of a state on a specific date.

Usage

igo_search_states(state)
igo_search_states(state)

Arguments

state

Any valid name or code of a state as specified on states2016(). It could be also an array of states.

Value

A data.frame.

Examples

library(dplyr)

igo_search_states("Spain") %>% as_tibble()

igo_search_states(c(20, 150)) %>% as_tibble()

igo_search_states("congo") %>% as_tibble()

igo_search_states(c("Germany", "papal states")) %>% as_tibble()

igo_search_states(c("FRN", "United Kingdom", 240, "italy")) %>% as_tibble()
library(dplyr)

igo_search_states("Spain") %>% as_tibble()

igo_search_states(c(20, 150)) %>% as_tibble()

igo_search_states("congo") %>% as_tibble()

igo_search_states(c("Germany", "papal states")) %>% as_tibble()

igo_search_states(c("FRN", "United Kingdom", 240, "italy")) %>% as_tibble()

Extract memberships of a state

Description

Extract all the memberships of a state on a specific date.

Usage

igo_state_membership(state, year = NULL, status = "Full Membership")
igo_state_membership(state, year = NULL, status = "Full Membership")

Arguments

`state`	Any valid name or code of a state as specified on `states2016()`. It could be also an array of states.
`year`	Year to be assessed, an integer or an array of year. If `NULL` the latest year available of the state would be extracted.
`status`	Character or vector with the membership status to be extracted. See Details on igo_year_format3.

Value

A data.frame.

Examples

# Memberships on two different dates
igo_state_membership("Spain", year = 1850)
igo_state_membership("Spain", year = 1870)
igo_state_membership("Spain", year = 1880:1882)

# Last year
igo_state_membership("ZAN")[, 1:7]

# Use codes to get countries
igo_state_membership("2", year = 1865)

# Extract different status
igo_state_membership("kosovo", status = c(
  "Associate Membership", "Observer",
  "Full Membership"
))

# Vectorized
igo_state_membership(c("usa", "spain"), year = 1870:1871)

# Use countrycodes package to get additional codes
if (requireNamespace("countrycode", quietly = TRUE)) {
  library(countrycode)
  IT <- igo_state_membership("Italy", year = 1880)
  IT$iso3c <- countrycode(IT$ccode, origin = "cown", destination = "iso3c")
  head(IT)
}
# Memberships on two different dates
igo_state_membership("Spain", year = 1850)
igo_state_membership("Spain", year = 1870)
igo_state_membership("Spain", year = 1880:1882)

# Last year
igo_state_membership("ZAN")[, 1:7]

# Use codes to get countries
igo_state_membership("2", year = 1865)

# Extract different status
igo_state_membership("kosovo", status = c(
  "Associate Membership", "Observer",
  "Full Membership"
))

# Vectorized
igo_state_membership(c("usa", "spain"), year = 1870:1871)

# Use countrycodes package to get additional codes
if (requireNamespace("countrycode", quietly = TRUE)) {
  library(countrycode)
  IT <- igo_state_membership("Italy", year = 1880)
  IT$iso3c <- countrycode(IT$ccode, origin = "cown", destination = "iso3c")
  head(IT)
}

Intergovernmental Organizations (IGO) by year

Description

Data on IGOs from 1815-2014, at the IGO-year level. Contains one record per IGO-year (with years listed at 5 year intervals through 1965, and annually thereafter).

Format

data.frame with 19,335 rows. Relevant fields:

ioname: Short abbreviation of the IGO name.
orgname: Full IGO name.
year: Calendar Year.
afghanistan...zimbabwe: status of that state in the IGO. See Details.
sdate: start date (year) that the IGO started.
deaddate: dead date (year) that the IGO dead.
longorgname: a longer version of the IGOs name (including previous names)
ionum: IGO id number in v2.1 and v3.0 of the data.
version: COW version number.

See Codebook Version 3 IGO Data for full reference.

Details

Possible value of the status of that 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

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

Note

Raw data used internally by igoR.

Source

Intergovernmental Organizations (v3), The Correlates of War Project (IGO Data Stata Files).

References

Examples

data("state_year_format3")

# Show a glimpse
library(dplyr)

state_year_format3 %>%
  select(ccode:afgec) %>%
  filter(year > 1990) %>%
  glimpse()

# Recode numerical to factors: with a sample
sample_state_year <- state_year_format3 %>%
  as_tibble() %>%
  select(ccode:afgec) %>%
  filter(year == 1990)

sample_state_year %>% glimpse()

# Recode
sample_state_year_recoded <- sample_state_year %>%
  mutate(across(-c(ccode:state), igo_recode_stateyear))

sample_state_year_recoded %>% glimpse()
data("state_year_format3")

# Show a glimpse
library(dplyr)

state_year_format3 %>%
  select(ccode:afgec) %>%
  filter(year > 1990) %>%
  glimpse()

# Recode numerical to factors: with a sample
sample_state_year <- state_year_format3 %>%
  as_tibble() %>%
  select(ccode:afgec) %>%
  filter(year == 1990)

sample_state_year %>% glimpse()

# Recode
sample_state_year_recoded <- sample_state_year %>%
  mutate(across(-c(ccode:state), igo_recode_stateyear))

sample_state_year_recoded %>% glimpse()

Country membership to IGO by year

Description

Data on IGOs from 1815-2014, at the country-year level. Contains one record per country-year (with years listed at 5 year intervals through 1965, and annually thereafter).

Format

data.frame with 15,557 rows. Relevant fields:

ccode: COW country number, see states2016.
year: Calendar Year.
state: Abbreviated state name, identical to variable names in igo_year_format3.
aaaid...wassen: IGO variables containing information on state membership status. See Details.

See Codebook Version 3 IGO Data

Details

Possible value of the status of that state in the IGO are:

Category	Numerical Value
No Membership	0
Full Membership	1
Associate Membership	2
Observer	3
Missing data	-9
IGO Not In Existence	-1

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

Note

Raw data used internally by igoR.

Source

Intergovernmental Organizations (v3), The Correlates of War Project (IGO Data Stata Files)

References

Examples

data("state_year_format3")
dplyr::tibble(state_year_format3)

data("state_year_format3")
dplyr::tibble(state_year_format3)

State System Membership (v2016)

Description

The list of states with COW abbreviations and ID numbers, plus the field state from state_year_format3.

Format

data.frame with 243 rows. Relevant fields:

ccode: COW country number.
stateabb: COW state abbreviation (3 characters).
statenme: COW state name.
styear...endday: Fields to identify the beginning and the end of each tenure.
version: Data file version number.
state: Abbreviated state name as appear in state_year_format3.

Details

This data set contains the list of states in the international system as updated and distributed by the Correlates of War Project.

These data sets identify states, their standard Correlates of War "country code" or state number (used throughout the Correlates of War project data sets), state abbreviations, and dates of membership as states and major powers in the international system.

The Correlates of War project includes a state in the international system from 1816-2016 for the following criteria:

Prior to 1920 the entity must have had a population greater than 500,000 and have had diplomatic missions at or above the rank of charge d'affaires with Britain and France.
After 1920 the entity must be a member of the League of Nations or the United Nations, or have a population greater than 500,000 and receive diplomatic missions from two major powers.

Note

state variable added to original data to help comparison across datasets on this package.

Source

State System Membership (v2016), The Correlates of War Project.

References

Correlates of War Project. 2017 "State System Membership List, v2016." Online, https://correlatesofwar.org/.

Examples

# example code
data("states2016")
dplyr::glimpse(states2016)
# example code
data("states2016")
dplyr::glimpse(states2016)

Package 'igoR'

Help Index

Extract the joint membership of a pair of countries across IGOs

Description

Usage

Arguments

Details

Value

Differences with the original dataset

Source

References

See Also

Examples

Extract members of an IGO

Description

Usage

Arguments

Value

See Also

Examples

Helper functions to recode categories

Description

Usage

Arguments

Value

See Also

Examples

Search and find an IGO

Description

Usage

Arguments

Details

Value

See Also

Examples

Finds codes and names of a state

Description

Usage

Arguments

Value

See Also

Examples

Extract memberships of a state

Description

Usage

Arguments

Value

See Also

Examples

Intergovernmental Organizations (IGO) by year

Description

Format

Details

Note

Source

References

See Also

Examples

Country membership to IGO by year

Description

Format

Details

Note

Source

References

See Also

Examples

State System Membership (v2016)

Description

Format

Details

Note

Source

References

See Also

Examples