inst/doc/igoR.R

In igoR: Intergovernmental Organizations Database

## ----knitropts, include=FALSE-------------------------------------------------
start_time <- Sys.time()

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  warning = FALSE,
  message = FALSE,
  fig.width = 6,
  fig.height = 4,
  out.width = "100%",
  out.height = "60%"
)

## ----setup--------------------------------------------------------------------
library(igoR)

# Additional libraries
library(ggplot2)
library(dplyr)

## ----custom_theme-------------------------------------------------------------
theme_igoR <- theme(
  axis.title = element_blank(),
  axis.line.x.bottom = element_line("black"),
  axis.line.y.left = element_line("black"),
  axis.text = element_text(color = "black", family = "sans"),
  axis.text.y.left = element_text(angle = 90),
  legend.position = "bottom",
  legend.title = element_blank(),
  legend.key = element_blank(),
  legend.key.width = unit(2, "cm"),
  legend.text = element_text(family = "sans", size = 13),
  legend.box.background = element_rect(color = "black", linewidth = 1),
  legend.spacing = unit(1.2 / 100, "npc"),
  plot.background = element_rect("grey90"),
  plot.margin = unit(rep(0.5, 4), "cm"),
  panel.background = element_rect("white"),
  panel.grid = element_blank(),
  panel.border = element_rect(fill = NA, colour = "grey90"),
  panel.grid.major.y = element_line("grey90")
)

## ----Fig1, message=FALSE, warning=FALSE, fig.cap="Figure 1. IGOs and states in the world system, 1816-2014"----
# Summarize
igos_by_year <- igo_year_format3 %>%
  group_by(year) %>%
  summarise(value = n(), .groups = "keep") %>%
  mutate(variable = "Total IGOs")

countries_by_year <- state_year_format3 %>%
  group_by(year) %>%
  summarise(value = n(), .groups = "keep") %>%
  mutate(variable = "Number of COW states")

all_by_year <- rbind(igos_by_year, countries_by_year) %>%
  mutate(variable = factor(variable))

# Reverse values
all_by_year$variable <- factor(all_by_year$variable,
  levels = rev(levels(all_by_year$variable))
)

# Plot
ggplot(all_by_year, aes(x = year, y = value)) +
  geom_line(color = "black", aes(linetype = variable)) +
  scale_linetype_manual(values = c("solid", "dashed")) +
  geom_vline(xintercept = c(1945, 1989)) +
  ylim(0, 400) +
  theme_igoR

## ----Fig2, message=FALSE, warning=FALSE, fig.cap="Figure 2. Birth and death rates of IGOs, 1816-2014"----
# Births and deads by year

df <- igo_search()

births <- df %>%
  mutate(year = sdate) %>%
  group_by(year) %>%
  summarise(value = n(), .groups = "keep") %>%
  mutate(variable = "IGO Births")

deads <- df %>%
  mutate(year = deaddate) %>%
  group_by(year) %>%
  summarise(value = n(), .groups = "keep") %>%
  mutate(variable = "IGO Deaths")


births_and_deads <- rbind(births, deads) %>% filter(!is.na(year))


# Plot
ggplot(births_and_deads, aes(x = year, y = value)) +
  geom_line(color = "black", aes(linetype = variable)) +
  scale_linetype_manual(values = c("solid", "dashed")) +
  ylim(0, 15) +
  theme_igoR

## ----regions_code-------------------------------------------------------------
# Extracted from analysis-jpr.do - See https://www.prio.org/JPR/Datasets/

# crossreg and universal codes not included

Asia <- c(
  550, 560, 570, 580, 590, 600, 610, 640, 650, 660,
  670, 725, 750, 825, 1030, 1345, 1400, 1530, 1532, 2300,
  2770, 3185, 3330, 3560, 3930, 4115, 4150, 4160, 4170,
  4190, 4200, 4220, 4265, 4440
)

MiddleEast <- c(
  370, 380, 390, 400, 410, 420, 430, 440, 450, 460,
  470, 490, 500, 510, 520, 1110, 1410, 1990, 2000,
  2220, 3450, 3800, 4140, 4270, 4380
)

Europe <- c(
  20, 300, 780, 800, 832, 840, 860, 1020, 1050, 1070, 1080,
  1125, 1140, 1390, 1420, 1440, 1563, 1565, 1580, 1585, 1590,
  1600, 1610, 1620, 1630, 1640, 1645, 1653, 1660, 1670, 1675,
  1680, 1690, 1700, 1710, 1715, 1720, 1730, 1740, 1750, 1760,
  1770, 1780, 1790, 1800, 1810, 1820, 1830, 1930, 1970, 1980,
  2310, 2325, 2345, 2440, 2450, 2550, 2575, 2610, 2650, 2705,
  2890, 2972, 3010, 3095, 3230, 3290, 3360, 3485, 3505, 3585,
  3590, 3600, 3610, 3620, 3630, 3640, 3650, 3655, 3660, 3665,
  3762, 3810, 3855, 3860, 3910, 4000, 4350, 4450, 4460, 4510,
  4520, 4540
)

Africa <- c(
  30, 40, 50, 60, 80, 90, 100, 110, 115, 120, 125, 130, 140,
  150, 155, 160, 170, 180, 190, 200, 210, 225, 240, 250, 260, 280,
  290, 690, 700, 710, 940, 1060, 1150, 1170, 1260, 1290, 1310,
  1320, 1330, 1340, 1355, 1430, 1450, 1460, 1470, 1475, 1480,
  1500, 1510, 1520, 1870, 2080, 2090, 2230, 2330, 2795, 3300,
  3310, 3470, 3480, 3510, 3520, 3570, 3740, 3760, 3761, 3790,
  3820, 3875, 3905, 3970, 4010, 4030, 4050, 4055, 4080, 4110,
  4120, 4130, 4230, 4240, 4250, 4251, 4340, 4365, 4480, 4485,
  4490, 4500, 4501, 4503
)

Americas <- c(
  310, 320, 330, 340, 720, 760, 815, 875, 880, 890, 900,
  910, 912, 913, 920, 950, 970, 980, 990, 1000, 1010, 1095,
  1130, 1486, 1489, 1490, 1860, 1890, 1920, 1950, 2070, 2110,
  2120, 2130, 2140, 2150, 2160, 2170, 2175, 2180, 2190, 2200,
  2203, 2206, 2210, 2260, 2340, 2490, 2560, 2980, 3060,
  3340, 3370, 3380, 3390, 3400, 3410, 3420, 3428, 3430, 3670,
  3680, 3812, 3830, 3880, 3890, 3900, 3925, 3980, 4070, 4100,
  4260, 4280, 4370
)

regions <- igo_search()

regions$region <- NA

regions <- regions %>% select(region, ionum)

regions$region <-
  ifelse(regions$ionum %in% Africa, "Africa", regions$region)

regions$region <-
  ifelse(regions$ionum %in% Americas, "Americas", regions$region)

regions$region <-
  ifelse(regions$ionum %in% Asia, "Asia", regions$region)

regions$region <-
  ifelse(regions$ionum %in% Europe, "Europe", regions$region)

regions$region <-
  ifelse(regions$ionum %in% MiddleEast, "Middle East", regions$region)

## ----Fig3, message=FALSE, warning=FALSE, fig.cap="Figure 3. IGO counts across regions, 1816-2014"----
# regions dataset created on previous chunk

# All IGOs
alligos <- igo_year_format3[, c("year", "ionum")]

regionsum <- merge(alligos, regions) %>%
  group_by(year, region) %>%
  summarise(value = n(), .groups = "keep") %>%
  filter(!is.na(region))

# Order
regionsum$region <- factor(regionsum$region,
  levels = c(
    "Asia", "Europe",
    "Africa", "Americas",
    "Middle East"
  )
)

# Plot
ggplot(regionsum, aes(x = year, y = value)) +
  geom_line(color = "black", aes(linetype = region)) +
  scale_linetype_manual(values = c(
    "solid", "dashed",
    "dotted", "dotdash", "longdash"
  )) +
  guides(linetype = guide_legend(ncol = 2, byrow = TRUE)) +
  ylim(0, 80) +
  theme_igoR

## ----Fig4, message=FALSE, warning=FALSE, fig.cap="Figure 4. IGO membership: five states in Asia, 1865-2014"----
asia5_cntries <- c(
  "China", "India",
  "Pakistan", "Indonesia",
  "Bangladesh"
)

# Five countries of Asia
asia5_igos <- igo_state_membership(
  state = asia5_cntries,
  year = 1865:2014,
  status = c("Full Membership")
)

asia5 <- asia5_igos %>%
  group_by(statenme, year) %>%
  summarise(values = n(), .groups = "keep")


# Reorder
asia5$statenme <- factor(asia5$statenme,
  levels = asia5_cntries
)



# Plot
ggplot(asia5, aes(x = year, y = values)) +
  geom_line(color = "black", aes(linetype = statenme)) +
  scale_linetype_manual(values = c(
    "solid", "dashed",
    "dotted", "dotdash",
    "longdash"
  )) +
  guides(linetype = guide_legend(ncol = 3, byrow = TRUE)) +
  theme(axis.title.y.left = element_text(
    family = "sans",
    size = 12,
    margin = margin(r = 6)
  )) +
  scale_y_continuous(
    "Number of memberships",
    breaks = c(0, 20, 40, 60, 80, 100),
    limits = c(0, 95),
    labels = as.character(c(0, 20, 40, 60, 80, 100))
  ) +
  theme_igoR

## ----Fig5, message=FALSE, warning=FALSE, fig.cap="Figure 5. Number of IGOs with full shared memberships with Spain (selected countries), 1816-2014"----
selected_countries <- c(
  "France",
  "Morocco",
  "China",
  "USA"
)

Spain_Selected <- igo_dyadic("Spain", selected_countries)

# Compute number of shared memberships

Spain_Selected$values <- rowSums(Spain_Selected == 1)

# Plot
ggplot(Spain_Selected, aes(x = year, y = values)) +
  geom_line(color = "black", aes(linetype = statenme2)) +
  scale_linetype_manual(values = c(
    "solid", "dashed",
    "dotted", "dotdash"
  )) +
  guides(linetype = guide_legend(ncol = 2, byrow = TRUE)) +
  theme(axis.title.y.left = element_text(
    family = "sans",
    size = 10,
    margin = margin(r = 6)
  )) +
  scale_y_continuous(
    "Shared memberships w\ Spain",
    breaks = c(0, 20, 40, 60, 80, 100),
    limits = c(0, 110),
    labels = as.character(c(0, 20, 40, 60, 80, 100))
  ) +
  theme_igoR +
  geom_vline(xintercept = 1939, alpha = 0.2) +
  annotate(
    "label",
    x = 1938,
    y = 60,
    size = 3,
    label = "Spanish \nCivil War"
  ) +
  geom_vline(xintercept = 1978, alpha = 0.2) +
  annotate(
    "label",
    x = 1970,
    y = 100,
    size = 3,
    label = "Constitution\nof Spain"
  )