One Measure By Which Things Have Recently Gotten Worse

The United Nation’s refugee agency today released its annual report on people displaced by war around the world, and the news is bad:

The number of people forcibly displaced at the end of 2014 had risen to a staggering 59.5 million compared to 51.2 million a year earlier and 37.5 million a decade ago.

The increase represents the biggest leap ever seen in a single year. Moreover, the report said the situation was likely to worsen still further.

The report focuses on raw estimates of displaced persons, but I think it makes more sense to look at this group as a share of world population. The number of people on the planet has increased by more than half a billion in the past decade, so we might expect to see some growth in the number of forcibly displaced persons even if the amount of conflict worldwide had held steady. The chart below plots annual totals from the UNHCR report as a share of mid-year world population, as estimated by the U.S. Census Bureau (here).

unhcr.refugee.trends

The number of observations in this time series is too small to use Bayesian change point detection to estimate the likelihood that the upturn after 2012 marks a change in the underlying data-generating process. I’m not sure we need that kind of firepower, though. After holding more or less steady for at least six years, the share of world population forcibly displaced by war has increased by more than 50 percent in just two years, from about one of every 200 people to 1 of every 133 people. Equally important, reports from field workers indicate that this problem only continues to grow in 2015. I don’t think I would call this upturn a “paradigm change,” as UN High Commissioner for Refugees António Guterres did, but there is little doubt that the problem of displacement by war has worsened significantly since 2012.

In historical terms, just how bad is it? Unfortunately, it’s impossible to say for sure. The time series in the UNHCR report only starts in 2004, and a note warns that methodological changes in 2007 render the data before that year incomparable to the more recent estimates. The UNHCR describes the 2014 figure as “the highest level ever recorded,” and that’s technically true but not very informative when recording started only recently. A longer time series assembled by the Center for Systemic Peace (here) supports the claim that the latest raw estimate is the largest ever, but as a share of world population, it’s probably still a bit lower than the levels seen in the post–Cold War tumult of the early 1990s (see here).

Other relevant data affirm the view that, while clearly worsening, the intensity of armed conflict around the world is not at historically high levels, not even for the past few decades. Here is a plot of annual counts of battle-related deaths (low, high, and best estimates) according to the latest edition of UCDP’s data set on that topic (here), which covers the period 1989–2013. Note that these figures have not been adjusted for changes in world population.

Annual estimates of battle-related deaths worldwide, 1989-2013 (data source: UCDP)

Annual estimates of battle-related deaths worldwide, 1989-2013 (data source: UCDP)

We see similar pattern in the Center for Systemic Peace’s Major Episodes of Political Violence data set (second row here), which covers the whole post-WWII period. For the chart below, I have separately summed the data set’s scalar measure of conflict intensity for two types of conflict, civil and interstate (see the codebook for details). Like the UCDP data, these figures show a local increase in the past few years that nevertheless remains well below the prior peak, which came when the Soviet Union fell apart.

Annual intensity of political violence worldwide, 1946-2014 (data source: CSP)

Annual intensity of political violence worldwide, 1946-2014 (data source: CSP)

And, for longer-term perspective, it always helps to take another look at this one, from an earlier UCDP report:

PRIO battle death trends

I’ll wrap this up by pinning a note in something I see when comparing the shorter-term UCDP estimates to the UNHCR estimates on forcibly displaced persons: adjusting for population, it looks like armed conflicts may be killing fewer but displacing more than they used to. That impression is bolstered by a glance at UCDP data on trends in deaths from “intentional attacks on civilians by governments and formally organized armed groups,” which UCDP calls “one-sided violence” (here).  As the plot below shows, the recent upsurge in warfare has not yet produced a large increase in the incidence of these killings, either. The line is bending upward, but it remains close to historical lows.

Estimated annual deaths from one-sided violence, 1989-2013 (Source: UCDP)

Estimated annual deaths from one-sided violence, 1989-2013 (Source: UCDP)

So, in the tumult of the past few years, it looks like the rate of population displacement has surged while the rate of battle deaths has risen more slowly and the rate of one-sided violence targeting civilians hasn’t risen much at all. If that’s true, then why? Improvements in medical care in conflict zones are probably part of the story, but I wonder if changes in norms and values, and in the international institutions and practices instantiating them, aren’t also shaping these trends. Governments that in the past might have wantonly killed populations they regarded as threats now seem more inclined to press those populations by other means—not always, but more often. Meanwhile, international organizations are readier than ever to assist those groups under pressure by feeding and sheltering them, drawing attention to their miseries, and sometimes even protecting them. The trend may be fragile, and the causality is impossible to untangle with confidence, but it deserves contemplation.

A Note on Trends in Armed Conflict

In a report released earlier this month, the Project for the Study of the 21st Century (PS21) observed that “the body count from the top twenty deadliest wars in 2014 was more than 28% higher than in the previous year.” They counted approximately 163 thousand deaths in 2014, up from 127 thousand in 2013. The report described that increase as “part of a broader multi-year trend” that began in 2007. The project’s executive director, Peter Epps, also appropriately noted that “assessing casualty figures in conflict is notoriously difficult and many of the figures we are looking at here a probably underestimates.”

This is solid work. I do not doubt the existence of the trend it identifies. That said, I would also encourage us to keep it in perspective:

That chart (source) ends in 2005. Uppsala University’s Department of Peace and Conflict (UCDP) hasn’t updated its widely-used data set on battle-related deaths for 2014 yet, but from last year’s edition, we can see the tail end of that longer period, as well as the start of the recent upward trend PS21 identifies. In this chart—R script here—the solid line marks the annual, global sums of their best estimates, and the dotted lines show the sums of the high and low estimates:
Annual, global battle-related deaths, 1989-2013 (source: UCDP)

Annual, global battle-related deaths, 1989-2013 (Data source: UCDP)

If we mentally tack that chart onto the end of the one before it, we can also see that the increase of the past few years has not yet broken the longer spell of relatively low numbers of battle deaths. Not even close. The peak around 2000 in the middle of the nearer chart is a modest bump in the farther one, and the upward trend we’ve seen since 2007 has not yet matched even that local maximum. This chart stops at the end of 2013, but if we used the data assembled by PS21 for the past year to project an increase in 2014, we’d see that we’re still in reasonably familiar territory.

Both of these things can be true. We could be—we are—seeing a short-term increase that does not mark the end of a longer-term ebb. The global economy has grown fantastically since the 1700s, and yet it still suffers serious crises and recessions. The planet has warmed significantly over the past century, but we still see some unusually cool summers and winters.

Lest this sound too sanguine at a time when armed conflict is waxing, let me add two caveats.

First, the picture from the recent past looks decidedly worse if we widen our aperture to include deliberate killings of civilians outside of battle. UCDP keeps a separate data set on that phenomenon—here—which they label “one-sided” violence. If we add the fatalities tallied in that data set to the battle-related ones summarized in the previous plot, here is what we get:

Annual, global battle-related deaths and deaths from one-sided violence, 1989-2013 (Data source: UCDP)

Annual, global battle-related deaths and deaths from one-sided violence, 1989-2013 (Data source: UCDP)

Note the difference in the scale of the y-axis; it is an order of magnitude larger than the one in the previous chart. At this scale, the peaks and valleys in battle-related deaths from the past 25 years get smoothed out, and a single peak—the Rwandan genocide—dominates the landscape. That peak is still much lower than the massifs marking the two World Wars in the first chart, but it is huge nonetheless. Hundreds of thousands of people were killed in a matter of months.

Second, the long persistence of this lower rate does not prove that the risk of violent conflict on the scale of the two World Wars has been reduced permanently. As Bear Braumoeller (here) and Nassim Nicholas Taleb (here; I link reluctantly, because I don’t care for the scornful and condescending tone) have both pointed out, a single war between great powers could end or even reverse this trend, and it is too soon to say with any confidence whether or not the risk of that happening is much lower than it used to be. Like many observers of international relations, I think we need to see how the system processes the (relative) rise of China and declines of Russia and the United States before updating our beliefs about the risk of major wars. As someone who grew up during the Cold War and was morbidly fascinated by the possibility of nuclear conflagration, I think we also need to remember how close we came to nuclear war on some occasions during that long spell, and to ponder how absurdly destructive and terrible that would be.

Strictly speaking, I’m not an academic, but I do a pretty good impersonation of one, so I’ll conclude with a footnote to that second caveat: I did not attribute the idea that the risk of major war is a thing of the past to Steven Pinker, as some do, because as Pinker points out in a written response to Taleb (here), he does not make precisely that claim, and his wider point about a long-term decline in human violence does not depend entirely on an ebb in warfare persisting. It’s hard to see how Pinker’s larger argument could survive a major war between nuclear powers, but then if that happened, who would care one way or another if it had?

States Aren’t the Only Mass Killers

We tend to think of mass killing as something that states do, but states do not have a monopoly on this use of force. Many groups employ violence in an attempt to further their political and economic agendas; civilians often suffer the consequences of that violence, and sometimes that suffering reaches breathtaking scale.

This point occurred to me again as I thought about the stunning acts of mass violence that Boko Haram has carried out in northern Nigeria in the past few weeks. The chart below comes from the Council on Foreign Relations’ Nigeria Security Tracker, an online interface for a data set that counts deaths from “violent incidents directed at government property, places of worship, and suicide bombings.” The sharp upward bend at the far right of that red line represents the sudden and brutal end of several hundred lives in the past two months in various towns and villages in a part of the world that surely isn’t as alien to Americans as many of us assume. In Nigeria, too, parents wake up and set about the business of providing for themselves and their families, and many kids toddle off to school to learn and fidget and chatter with friends. Over the past few years, Boko Haram has repeatedly interrupted those daily routines with scores of attacks resulting in thousands of murders.

boko.haram.killings.chart.20140307

I suspect the tendency to see mass killing as the purview of states is driven by the extraordinary salience of two archetypal cases—the Holocaust, of course, but also the Rwandan genocide. From those examples, we infer that violence on this scale requires resources, organization, and opportunity on a scale that in “modern” times only states are supposed to possess. The Holocaust took this bureaucratic logic to unique extremes, but many accounts of the Rwandan genocide also emphasize state planning and propaganda as necessary conditions for that episode of mass murder in extremis.

It’s true that resources, organization, and opportunity facilitate mass violence, and that states are much more likely to have them. In some contexts, though, rebel groups and other non-state actors can accumulate enough resources and become well enough organized to kill on a comparable scale. This is especially likely in the same contexts in which states usually perpetrate mass killing, namely, in civil wars. In some wars, rebels manage to establish governance systems of their own, and the apparent logic of the atrocities committed by these quasi-states looks very similar to the logic behind the atrocities perpetrated by their foes: destroy your rival’s base of support, and scare civilians into compliance or complicity.

Rebels don’t need to govern to carry out mass killings, though, a point driven home by groups like the RUF in Sierra Leone, the Seleka and anti-balaka militias in the Central African Republic, and, of course, Boko Haram. Sometimes the states we now expect to protect civilians against such violence are so weak or absent or uncaring that those non-state groups don’t need deep pockets and sprawling organizations to accomplish mass murder. On Boko Haram, CFR’s John Campbell observes that, “Several of the most recent incidents involve government security forces unaccountably not at their posts, allowing Boko Haram freedom of movement. The governor of Borno state publicly said that Boko Haram fighters outgun government forces.” Campbell also notes that those security forces might be shirking their duty because they are poorly paid and equipped, and because they simply fear a group that “has a long tradition of killing any person in the security services that it can.” With a state like that, the resources and organization required to accomplish mass murder are, unfortunately, not so vast. What is required is a degree of ruthlessness that most of us find hard to understand, but that incomprehensibility should not be confused with impossibility.

Acts we conventionally describe as “terrorism” nowadays are also atrocities by another name, and so-called terrorist groups occasionally succeed in their lethal business on an extraordinary scale. Al Qaeda’s attacks on September 11, 2001, certainly qualify as a mass killing as we conventionally define it. Nearly 3,000 noncombatant civilians from a discrete group (Americans) were deliberately killed as part of a wider political conflict, and all in a single day. The torrent of car bombings and other indiscriminate attacks in Iraq in recent months has surely crossed that arbitrary 1,000-death threshold by now, too.

For analytical purposes, it would be useful to have a catalog of episodes in which non-state organizations committed atrocities on such a large scale. That catalog would allow us to try to glean patterns and develop predictive models from their comparison to each other and, more important, to situations in which those episodes did not occur. Even more useful would be a reliable assemblage of data on the incidents comprising those episodes, so we could carefully study how and where they arise and accumulate over time, perhaps with some hope of halting or at least mitigating future episodes as they develop.

Unfortunately, the data we want usually aren’t the data we have, and that’s true here, too. The Uppsala Conflict Data Program (UCDP) has compiled a data set on “one-sided violence,” defined as “intentional attacks on civilians by governments and formally organized armed groups,” that includes low, high, and best estimates of deaths attributed to each perpetrator group in cases where that annual estimate is 25 deaths or more (here). These data are an excellent start, but they only cover years since 1989, so the number of episodes involving non-state groups as perpetrators is still very small. The Armed Conflict Location & Event Data Project (ACLED) compiles detailed data (here) on attacks by non-state groups, among others, but it only covers Africa since 1997. New developments in the automated production of political event data hint at the possibility of analyzing deliberate violence against civilians around the world at a much higher resolution in the not-too-distant future. As I’ve discovered in an ongoing efforts to adapt one of these data sets to this purpose, however, we’re not quite there yet (see here).

In the meantime, we’ll keep seeing accounts of murderous sprees by groups like Boko Haram (here and here, to pick just two) and CAR’s Seleka (here) and anti-balaka (here) alongside the thrum of reporting on atrocities from places like Syria and Sudan. And as we read, we would do well to remember that people, not states, are the the common denominator.

PS. In the discussion of relevant data sets, I somehow forgot to mention that the Political Instability Task Force also funds the continuing collection of data on “atrocities” around the world involving five or more civilian fatalities (here). These data, which run all the way back to January 1995, are carefully compiled under the direction of a master of the craft, but they also suffer from the inevitable problems of reporting bias that plague all such efforts and so must be handled with care (see Will Moore here and here on this subject).

Do Elections Trigger Mass Atrocities?

Kenya plans to hold general elections in early March this year, and many observers fear those contests will spur a reprisal of the mass violence that swept parts of that country after balloting in December 2007.  The Sentinel Project for Genocide Prevention says Kenya is at “high risk” of genocide in 2013, and a recent contingency-planning memo from Joel Barkan the Council on Foreign Relations asserts that “there will almost certainly be further incidents of violence in the run-up to the 2013 elections.” As a recent Africa Initiative backgrounder points out, this violence has roots that stretch much deeper than the 2007 elections, but the fear that mass violence will flare again around this year’s balloting seems well founded.

All of which got me wondering: is this a generic problem? We know that election-related violence is a real and multifaceted thing. We also have works by Jack Snyder and Amy Chua, among others, arguing that democratization actually makes some countries more susceptible to ethnic and nationalist conflict rather than less, as democracy promoters often claim. What I’m wondering, though—as someone who has long studied democratization and is currently working on tools to forecast genocide and other forms of mass killing—is whether or not elections substantially increase the risk of mass atrocities in particular, where “mass atrocities” means the deliberate killing of large numbers of unarmed civilians for apparently political ends.

Best I can tell, the short answer is no. After applying a few different statistical-modeling strategies to a few measures of atrocities, I see little evidence that elections commonly trigger the onset or intensification of this type of political violence. The absence of evidence isn’t the same thing as evidence of absence, but these results convince me that national elections aren’t a major risk factor for mass killing.

If you’re interested in the technical details, here’s what I did and what I found:

My first cut at the problem looked for a connection between national elections and the onset of state-sponsored mass killings, defined as “a period of sustained violence” in which ” the actions of state agents result in the intentional death of at least 1,000 noncombatants from a discrete group.” That latter definition comes from work Ben Valentino and I did for my old research program, the Political Instability Task Force, and it restricts the analysis to episodes of large-scale killing by states or other groups acting at their behest. Defined as such, mass killings are akin to genocide in their scale, and there have only been about 110 of them since 1945.

So, do national elections help trigger this type of mass killing? To try to answer this question, I thought of elections as a kind of experimental “treatment” that some country-years get and others don’t. I used the National Elections Across Democracy and Autocracy (NELDA) data set to identify country-years since 1945 with national elections for chief executive or legislature or both, regardless of how competitive those elections were. I then used the MatchIt package in R to set up a comparison of country-years with and without elections within 107 groups that matched exactly on several other variables identified by prior research as risk factors for mass-killing onset: autocracy vs. democracy, exclusionary elite ideology (yes/no), salient elite ethnicity (yes/no), ongoing armed conflict (yes/no), any mass killing since 1945 (yes/no), and Cold War vs. post-Cold War period. Finally, I used conditional logistic regression to estimate the difference in risk between election and non-election years within those groups.

The results? In my data, mass-killing episodes were 80% as likely to begin in election years as non-election years, other things being equal. The 95% confidence interval for this association was wide (45% to 145%), but the result suggests that, if anything, countries are actually somewhat less prone to suffer onsets of mass killing in election years as non-election years.

I wondered if the risk might differ by regime type, so I reran the analysis on the subset of cases that were plausibly democratic. The estimate was effectively unchanged (80%, CI of 35% to 185%). Then I thought it might be a post-Cold War thing and reran the analysis using only country-years from 1991 forward. The estimate moved, but in the opposite of the anticipated direction. Now it was down to 60%, with a CI of 17% to 215%.

These estimates got me worried that something had gone wacky in my data, so I reran the matching and conditional logistic regression using coup attempts (successful or failed) instead of elections as the “treatment” of interest. Several theorists have identified threats to incumbents’ power as a cause of mass atrocities, and coups are a visible and discrete manifestation of such threats. My analysis strongly confirmed this view, indicating that mass-killing episodes were nearly five times as likely to start in years with coup attempts as years without, other things being equal. More important for present purposes, this result increased my confidence in the reliability of my earlier finding on elections, as did the similar estimates I got from models with country fixed effects, country-specific intercepts (a.k.a. random effects), and interaction terms that allowed the effects of elections to vary across regime types and historical eras.

Then I wondered if this negative finding wasn’t an artifact of the measure I was using for mass atrocities. The 1,000-death threshold for “mass killing” is quite high, and the restriction to killings by states or their agents ignores situations of grave concern in which rebel groups or other non-state actors are the ones doing the murdering. Maybe the danger of election years would be clearer if I looked at atrocities on a smaller scale and ones perpetrated by non-state actors.

To do this, I took the UCDP One-Sided Violence Dataset v1.4 and wrote an R script that aggregated its values for specific conflicts into annual death counts by country and perpetrator (government or non-government). Then I used R’s ‘pscl’ package to estimate zero-inflated negative binomial regression (ZINB) models that treat the death counts as the observable results of a two-stage process: one that determines whether or not a country has any one-sided killing in a particular year, and then another that determines how many deaths occur, conditional on there being any. In addition to my indicator for election years, these models included all the risk factors used in the earlier matching exercise, plus population size and the logged counts of deaths from one-sided violence by government and non-government actors (separately) in the previous year. All of these variables were included in the logistic regression “hurdle” model; only elections, population size, and the lagged death counts were included in the conditional count models.

To my surprise once again, the results suggested that, if anything, atrocities the risk of mass atrocities is actually lower in years with national elections. In the model of government-perpetrated violence, the coefficient for the election indicator in the hurdle model was barely distinguishable from zero (0.04), and the association in the count portion was modestly negative (-0.20, s.e. of 0.20). In the model of violence perpetrated by other groups, the effect in the hurdle portion was modestly negative (-0.25, s.e. of 0.20), and the effect in the count portion was decidedly negative (-0.82, s.e. of 0.19). When I reran the models with separate indicators for executive and legislative elections, the results bounced around a little bit, but the basic patterns remained unchanged. None of the models showed a substantial, positive association between either type of election and the occurrence or scale of one-sided violence against civilians.

In light of the weakness of the observed effects, the noisiness of the measures employed, and my prior beliefs about the effects of elections on risks of mass killing—shaped in part by the Kenyan case I discussed at the start of this post—I’m not quite ready to assert that election years actually reduce the risk of mass atrocities. What I am more comfortable doing, however, is ignoring elections in statistical models meant to forecast mass atrocities across large numbers of countries.

If you’re interested in replicating or tweaking this analysis, please email me at ulfelder@gmail.com, and I’ll be happy to send you the data and R scripts (one to get country-year summaries of the UCDP data, another to run the matching and modeling) I used to do it. [UPDATE: I’ve put the scripts and data in a publicly accessible folder on Google Drive. If you try that link and it doesn’t work, please let me know.] Ideally, I would cut out the middleman by putting them in a Github repository, but I haven’t quite figured out how to do that yet. If you’re in the DC area and interested in getting paid to walk me me through that process, please let me know.

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