Analyzing the Failed States Index (with Polity IV)

July 7, 2011
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(This article was first published on Nor Talk Too Wise » R, and kindly contributed to R-bloggers)

So, I decided to sit down and have a little fun with that Failed States Index data I put together. To start, I expect that the dataset will be pretty linearly correlated with the polity IV data. This makes sense–true democracies aren’t failed states, and failed states tend not to be democratic. To test this, I merged the two datasets for 2010. Let’s load them into R…

```FailedStateIndexPolity.Merge <- read.csv("http://nortalktoowise.com/wp-content/uploads/2011/07/FailedStateIndexPolity.Merge_1.csv")
attach(FailedStateIndexPolity.Merge)```

And take a look at a scatterplot of the two variables, Total (which is the sum total of the failed state indicators) and polity2 (which is a country’s democracy score minus its autocracy score):

`plot(polity2, Total)`

Whoa, wasn’t expecting that. It seems that most failed states have polity scores closer to zero than -10, and the more extremely democratic or autocratic a state is, the lower its failed state score will be. On second thought, maybe this does make sense: strong democracies won’t be failed states, and strong autocracies will supplant economic well-being and personal freedoms with strong state control, which failed states should lack the ability to exert. If that’s true, we should look at the relationship between the failed state’s total and the polity’s democ and autoc scores.

```sub <- subset(FailedStateIndexPolity.Merge, democ>-60)
plot(sub\$democ, sub\$Total)```

OK, this makes a little more sense.  More democratic states definitely look a lot less like failed states.  If my hypothesis about strong state control holds, we should see almost the same relationship for the autocracy score.

```sub <- subset(FailedStateIndexPolity.Merge, autoc>-60)
plot(sub\$autoc, sub\$Total)```

Huh, that’s cool.  The trend is similar, but we have a ton of observations at zero.  In other words, of the states without an autocratic bone in their borders, there exists the full array of state failure levels.

Holistically, this supports a conclusion I never really came to in my prior analysis of regime metrics–namely, that state failure isn’t simply the absence of a democracy.  It’s the ineffectiveness of any government structure, democratic or authoritarian.  Of course, paramount in this conclusion is the understanding that democracy and authoritarianism aren’t linearly exclusive.

```sub <- subset(FailedStateIndexPolity.Merge, autoc>-60 & democ>-60)
plot(jitter(sub\$democ), jitter(sub\$autoc)
abline(0,1)```

Because the states whose polity scores are close to zero, and polity is the difference between democ and autoc, the points closest to the line (which represents democ – autoc = 0) are the most failed states.

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