Animated Map of Coup Attempts Worldwide, 1946-2013

I’m in the throes of updating my data files to prepare for 2014 forecasts of various forms of political change, including coups d’etat. For the past couple of years, I’ve used the coup event list Monty Marshall produces (here) as my primary source on this topic, and I’ve informally cross-referenced Monty’s accounting with the list produced by Jonathan Powell and Clayton Thyne (here).

This year, I decided to quit trying to pick a favorite or adjudicate between the two and just go ahead and mash them up. The two projects use slightly different definitions, but both are basically looking for the same thing: some faction of political insiders (including but not limited to military leaders) seizes executive power at the national level by unconstitutional means that include the use or threat of force.

After stretching the two data sets into country-year format and merging the results, I created separate indicators for successful and failed coups that are scored 1 if either source reports an event of that type and 0 otherwise. For example, Marshall’s data set doesn’t see the removal of Egyptian president Hosni Mubarak from office in 2011 as a coup, but Powell and Thyne’s does, so in my mashed-up version, Egypt gets a 1 for 2011 on the indicator for any successful coups.* The Marshall data set starts in 1946, but Powell and Thyne don’t start until 1950, so my observations for 1946-1949 are based solely on the former. Powell and Thyne update their file on the go, however, whereas Marshall only updates once a year. This means that Powell and Thyne already have most of 2013 covered, so my observations for this year so far are based solely on their reckoning.

The bar plot below shows what the data from the combined version look like over time. The trend is basically the same one we’d see from either of the constituent sources. The frequency of coup attempts grew noticeably in the 1960s and 1970s; continued apace through the 1980s and 1990s, but with fewer successes; and then fell sharply in the past two decades.

coups19462013

We can see those time trends and the geographic distribution of these events in the GIF below (you may need to click on it to get it to play). As the maps show, coup events were pretty well scattered across the world in the 1960s and 1970s, but in the past 20 years, they’ve mostly struck in Africa and Asia.

coups19462013

A .csv with the mashed-up data is on Google Drive (here), and you can find the R script I used to make these plots on Github (here).

Update: For a new-and-improved version that uses daily data and is interactive, see this follow-up post.

* This sentence corrects an error I made in the original version of this post. In that version, I stated that Marshall did not consider the 3 July 2013 events in Egypt to include a coup. That was incorrect, and I apologize to him for my error.

Episodes of Democracy and Autocracy: A New Data Set

To look for patterns in the occurrence of transitions to democracy and democratic breakdowns around the world over time, we need reliable observations of where and when those events have happened. Most statistical analyses of democratic transitions in the past 15 years have used either Polity or the Democracy-Dictatorship (DD) data set to do that. As part of my work for the Political Instability Task Force (PITF), I developed yet another data set on episodes of democratic and authoritarian government in countries worldwide with populations larger than 500,000. The results of that work—I’m calling it the Democracy/Autocracy Data Set (DAD)—are now publicly available on the Dataverse Network, a data-sharing platform operated by Harvard University’s Institute for Quantitative Social Science.*

Like DD, DAD sorts cases annually into two bins: democracies and non-democracies.  Countries are identified as democracies when they satisfy all of several criteria, like items on a checklist. Cases that fail to satisfy one or more of those criteria are identified as non-democracies. Those criteria are meant to be indicative of four broader conditions essential to democracy:

  • Elected officials rule. Representatives chosen by citizens actually make policy, and unelected individuals, bodies, and organizations cannot veto those representatives’ decisions.
  • Elections are fair and competitive. The process by which citizens elect their rulers provides voters with meaningful choice and is free from deliberate fraud or abuse.
  • Politics is inclusive. Adult citizens have equal rights to vote and participate in government and fair opportunity to exercise those rights.
  • Civil liberties are protected. Freedoms of speech, association, and assembly give citizens the chance to deliberate on their interests, to organize in pursuit of those interests, and to monitor the performance of their elected representatives and the bureaucracies on which those officials depend.

Conceptually, these conditions are very similar to the ones used in constructing the DD data set. So why bother doing it all over again? The impetus to re-invent this particular wheel came from concerns I had about the effects of a couple of ancillary rules the makers of the original DD data set used to make decisions about ambiguous cases. As I saw it, those rules systematically skewed the resulting data in ways that are especially problematic for the kind of survival analysis those authors and many others have done with them. I won’t belabor the issue here, but interested readers can find more on the subject in this paper of mine on SSRN.

DAD was designed with survival analysis in mind, so it includes duration of current status, indicators of change from current status, and running counts of past events of both types (transitions to and from democracy). Importantly, those running counts include episodes before 1955, so at least that portion of the data set is not left-censored. Unlike DD, DAD does not differentiate within the two bins among types of democracy and dictatorship. Also unlike DD, however, DAD does track times to first alternations in power within democratic episodes—by individual chief executive and by ruling party/coalition—and it differentiates among democratic breakdowns by their form: executive coup (a.k.a. consolidation of incumbent advantage), military coup, rebellion, or other.

As a kind of bonus, DAD also includes annual data on each countries’ participation in a host of regional and global intergovernmental organizations and treaty regimes—data I used for this paper, which looks at the effects of international integration on prospects for transitions to and from democracy. Those data are also available as a standalone data set through ICPSR (link).

For other published or publicly available research I’ve done with DAD, see here, here, here, here, and here.

Based on my experience working with Polity, DD, and Freedom House’s Freedom in the World data, I can say a little bit about how the various sources compare to one another. In its calls on which regimes are democratic, DAD is closest to Freedom House’s annual list of electoral democracies. DD is generally more cautious than DAD, identifying as dictatorships some cases where DAD sees (usually short-lived) spells of democratic government that ended with a consolidation of incumbent advantage. Polity runs the opposite way, identifying as more democratic than autocratic many cases where DAD sees an autocracy (e.g. Russia and Armenia today).

At present, I am not planning to update DAD. Still, I hope it’s a useful resource and welcome comments and criticisms. Again, you can find the data set and supporting documentation on the Dataverse Network.

* This research was conducted for the Political Instability Task Force (PITF). The PITF is funded by the Central Intelligence Agency (CIA). The views expressed herein are the author’s alone and do not necessarily represent the views of the Task Force or the U.S. Government.

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