The seeds of Global Governance

Author: Xavier Fernández-i-Marín
January 20, 2012 - 5 minutes
COW Data visualization ggplot IGOs Governance

International Governmental Organizations (IGOs) can be thought of as the seeds for a new mechanisms of Global Governance. They represent deals between countries to try to solve diverse issues. Some of them are formed by few countries, and others by most of them. Some IGOs are general, and others focused on very specific topics. Some of them only accept regional members, while others are open to all the international community. But giving all those differences, they serve a purpose individually. And if we consider them together, we can think about them as the seeds of a kind of new “international government”.

How to measure an IGO

The classical approximation which dates back to the 1970’s on a seminal article by Michael Wallace and David Singer titled “International Governmental Organization in the Global System, 1815-1964” is to consider an organization to be an International Governmental Organization if it has the following three characteristics:

This excludes treaties between states and legal agreements, and all the , but it also excludes “objects” such as the G20, which is usually regarded as a leading institution in the international arena.

The evolution of IGO

The following figure shows the number of IGOs that were formed by many members (high values in the x-axis) or few (low values in the x-axis). And it does so for 4 different points in time: in 1870, in 1930, in 1970 and in 2005. The data is based on the “full members” of IGO according to the latest version (2.3) of the International Governmental Organizations database maintained by Timothy Nordstrom (University of Mississippi), Jon Pevehouse (University of Wisconsin) and Megan Shannon (University of Mississippi) and hosted at the Correlates of War Program and described at an article on “Conflict Management and Peace Science”

Few points are important from this figure:

Read data

d <- read.table(“IGO_stateunit_v2.3.csv”, head=TRUE, sep=“,”) igo <- d[,-c(1, 3)]

Generate status factors

migo <- melt(igo, id=c(“country”, “year”)) names(migo)[3:4] <- c(“igo”, “status”) table(migo$status) migo$status <- factor(migo$status, levels=c(0, 1, 2, 3, -9, -1), labels=c(“no membership”, “full membership”, “associate membership”, “observer”, “NA”, “IGO not in existence”)) migo <- cbind(migo, fm=ifelse(migo$status==“full membership”, 1, 0))

Full membership

migo.fm <- tapply(migo$fm, list(migo$year, migo$igo), sum) migo.fm <- melt(migo.fm) names(migo.fm) <- c(“year”, “igo”, “fm”) migo.fm <- subset(migo.fm, fm>0) # only when IGOs have at least some members

Do the plot

t <- subset(migo.fm, year==“1880”) p1 <- ggplot(t, aes(x=fm)) + xlim(0, 200) + ylim(0, 70) + geom_histogram(binwidth=5) + xlab(“Number of full membership countries”) + ylab(“Number of IGO”) + opts(title=“1880”) t <- subset(migo.fm, year==“1930”) p2 <- ggplot(t, aes(x=fm)) + xlim(0, 200) + ylim(0, 70) + geom_histogram(binwidth=5) + xlab(“Number of full membership countries”) + ylab(“Number of IGO”) + opts(title=“1930”) t <- subset(migo.fm, year==“1970”) p3 <- ggplot(t, aes(x=fm)) + xlim(0, 200) + ylim(0, 70) + geom_histogram(binwidth=5) + xlab(“Number of full membership countries”) + ylab(“Number of IGO”) + opts(title=“1970”) t <- subset(migo.fm, year==“2005”) p4 <- ggplot(t, aes(x=fm)) + xlim(0, 200) + ylim(0, 70) + geom_histogram(binwidth=5) + xlab(“Number of full membership countries”) + ylab(“Number of IGO”) + opts(title=“2005”) grid.arrange(p1, p2, p3, p4, ncol=2, nrow=2)

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