Coup Forecasts for 2013

Last January, I posted statistical estimates of coup risk for 2012 that drew some wider interest after they correctly identified Mali as a high-risk case. Now that the year’s almost over, I thought it would be a good time to assess more formally how those 2012 forecasts performed and then update them for 2013.

So, first things first: how did the 2012 forecasts fare on the whole? Pretty well, actually.

For purposes of these forecasts, a coup is defined as “as a forceful seizure of executive authority and office by a dissident/opposition faction within the country’s ruling or political elites that results in a substantial change in the executive leadership and the policies of the prior regime.” That language comes from Monty Marshall’s Center for Systemic Peace, whose data set on coup events serves as the basis for one of the two models used to generate the 2012 forecasts. Those forecasts were meant to assess the risk of any coup attempts at some point during the calendar year, whether those attempts succeed or fail. They were not meant to anticipate civil wars, non-violent uprisings, voluntary transfers of executive authority, autogolpes, or interventions by foreign forces, all of which are better thought of (and modeled) as different forms of political crisis.

Okay, so by that definition, I see two countries where coup attempts occurred in 2012: Mali (in March) and Guinea-Bissau (in April). As it happens, both of those countries ranked in the top 10 in January’s forecasts—Guinea-Bissau at no. 2 and Mali at no. 10—so the models seem to be homing in on the right things. We can get a more rigorous take on the forecasts’ accuracy with a couple of statistics commonly used to assess models that try to predict binary outcomes like these (either a coup attempt happens or it doesn’t):

  • AUC Score. The estimated area under the Receiver Operating Characteristic (ROC) curve, used as a measure of the ability of a binary classification model to discriminate between positive and negative cases. Specifically, AUC represents the probability that a randomly selected positive case (here, a country-year with coup activity) will have a higher predicted probability than a randomly selected negative case (e.g., country-year with no coup activity). Ranges from 0.5 to 1, with higher values indicating better discrimination.
  • Brier Score. A general measure of forecast performance, defined as the average squared difference between the predicted and observed values. Ranges from 0 to 1, with lower values indicating more accurate predictions.

Assuming that Mali and Guinea-Bissau were the only countries to see coup activity this year, my 2012 coup forecasts get an AUC score of 0.97 and a Brier score of 0.01. Those are really good numbers. Based on my experience trying to forecast other rare political events around the world, I’m pretty happy with any AUC above the low 0.80s and any Brier score that’s better than an across-the-board base-rate forecast. The 2012 coup forecasts surpass both of those benchmarks.

Of course, with just two events in more than 150 countries, these statistics could be very sensitive to changes in the list of coup attempts. Two possible modifications come from Sudan, where authorities claim to have thwarted coup plots in November and December, and Paraguay, where right-wing legislators pushed leftist President Lugo out of office in June. I didn’t count Sudan because country experts tell me those events were probably just a political ploy President Bashir is using to keep his rivals off balance and not actual coup attempts. I didn’t count Paraguay because President Lugo’s rivals used legal procedures, not force, to oust him in a rushed impeachment. I’m pretty confident that neither of those cases counts as a coup attempt as defined here, but for the sake of argument, it’s worth seeing how the addition of those cases would affect the accuracy assessments.

  • Sudan ranked 11th in the 2012 forecasts, just behind Mali, so the addition of an event there leaves the accuracy stats essentially unchanged at 0.96 and 0.02, respectively.
  • Paraguay would definitely count as a surprise. It ranked in the 80s in the 2012 forecasts, and counting its June events as a coup would drop the AUC to 0.80 and the Brier score to 0.02.
  • If we count both cases as yeses, we get an AUC of 0.84 and a Brier score of 0.02.

All of those are still pretty respectable numbers for true forecasts of rare political events, even if they’re not quite as good as the initial ones. Whatever the exact ground truth, these statistics give me some confidence that the two-model average I’m using here makes a useful forecasting tool.

So, without further ado, what about 2013? The chart below plots estimated coup risk for the coming year for the 30 countries at greatest risk using essentially the same models I used for 2012. (One of the two models differs slightly from last year’s; I cut out a couple of variables that had little effect on the estimates and are especially hard to update.) I picked the top 30 because it’s roughly equivalent to the top quintile, and my experience working with models like these tells me that the top quintile makes a pretty good break point for distinguishing between countries at high and low risk. If a country doesn’t appear in this chart, that means my models think it’s highly unlikely to suffer a coup attempt in the coming year.

2013 Coup Risk Estimates

2013 Coup Risk Estimates

The broad strokes are very similar to 2012, but I’m also seeing a few changes worth noting.

  • Consistent with 2012, countries from sub-Saharan Africa continue to dominate the high-risk group. Nine of the top 10 and 22 of the top 30 countries come from that part of the world. One of those 22 is South Sudan, which didn’t get a forecast in early 2012 because I didn’t have the requisite data but now makes an ignominious debut at no. 20. Another is Sudan, which, as Armin Rosen discusses, certainly isn’t getting any more stable. Mali and Guinea-Bissau also both stay near the top of the list, thanks in part to the “coup trap” I discussed in another recent post. Meanwhile, I suspect the models are overestimating the risk of a new coup attempt in Niger, which seems to have landed on firmer footing after its “democratizing” coup in February 2010, but that recent history will leave Niger in the statistical high-risk group until at least 2015.
  • More surprising to me, Timor-Leste now lands in the top 10. That’s a change from 2012, but only because the data used to generate the 2012 forecasts did not count the assassination attempts of 2008 as a coup try. The latest version of CSP’s coup list does consider those events to be failed coup attempt. Layered on top of Timor-Leste’s high poverty and hybrid political authority patterns, that recent coup activity greatly increases the country’s estimated risk. If Timor-Leste makes it through 2013 without another coup attempt, though, its estimated risk should drop sharply next year.
  • In Latin America, Haiti and Ecuador both make it into the Top 20. As with Timor-Leste, the changes from 2012 are artifacts of adjustments to the historical data—adding a coup attempt in Ecuador in 2010 and counting Haiti as a partial democracy instead of a state under foreign occupation. Those artifacts mean the change from 2012 isn’t informative, but the presence of those two countries in the top 20 most certainly is.
  • Syria also pops into the high-risk group at no. 25. That’s not an artifact of data revisions; it’s a reflection of the effects of that country’s devastating state collapse and civil war on several of the risk factors for coups.
  • Finally, notable for its absence is Egypt, which ranks 48th on the 2013 list and has been a source of coup rumors throughout its seemingly interminable transitional period. It’s worth noting though, that if you consider SCAF’s ouster of Mubarak in 2011 to be a successful coup (CSP doesn’t), Egypt would make its way into the top 30.

As always, if you’re interested in the details of the modeling, please drop me a line at and I’ll try to answer your questions as soon as I can.

Update: After a Washington Post blog mapped my Top 30, I produced a map of my own.

Has Africa Gone Coup-Crazy in 2012?

Guinea-Bissau’s armed forces violently seized control of the country’s capital yesterday in an apparent coup d’etat. This is the second successful coup in West Africa in the past month–the other happened in Mali in mid-March–and, if my Twitter feed is any indication, this pair of events has a lot of people wondering if 2012 is going to be an unusually “hot” year for coups in that part of the world.

Statistically speaking, the answer seems to be “no”–or “not yet,” anyway, and it still has a ways to go to get there.

To see if 2012 is shaping up to be a weird year for coup activity in Africa, I used the ‘bcp’ package in R to apply a technique called Bayesian change point detection (BCP) to annual counts of successful and failed coup attempts in the region from 1946 through 2012 (so far). BCP treats time-series data as a collection of independent and identically distributed partitions and looks for points in that series where the data’s generative parameters appear to change. My data on coup events come from the Center for Systemic Peace.

The results are shown below. The top half of the chart plots the observed annual counts (the dots) and the posterior means for those annual counts (the line). The real action, though, is in the bottom half, which plots the posterior probabilities of a change point. The higher that number, the more confident we are that a particular year marks a sudden change. In this series, we see evidence of three change points: one in the mid-1960s, a few years after the start of decolonization; another in the early 1990s, after the end of the Cold War; and a third in the late 1990s, when the rate of coups in the region takes a sharp dip. Meanwhile, the pair of events observed so far in 2012 looks perfectly normal, just about average for the past decade and still well below the recent peak of six events in 2008.

If two coup bids in 2012 does not an aberration make, how many would we need to see this year to call it a significant change? I reran the BCP analysis several times using ever-larger counts for 2012, and it took a big jump to start moving the posterior probability of a change point in any appreciable way. At five events, the posterior probability still hadn’t moved much. At six, it finally moved appreciably, but only to around 0.2. In the end, it took eight events to push the posterior probability over 0.5.

In other words, it would take a lot more than two coup bids in 2012 to mark a significant change from the recent past, and what we’ve seen this year so far looks like normal variation in a stochastic process. Event counts are often noisy, but our pattern-seeking brains still try to find meaning in those small variations. It’s also harder to remember less recent events, and our brains tend to confuse that difficulty with infrequency. It helps to remember those biases whenever a new event starts you thinking about a trend.

NOTE: This version of the plot and the scenario analysis corrects an error in the data used in the original post. For the first run, I forgot that my analysis file ended in 2010, so the 0 events shown for 2011 was a mistake. There were actually two failed coups in Africa last year, one in the DRC in February and another in Guinea in July. With those two events added to the data set, the first third of 2012 looks even more typical than it did before.


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