Demography, Democracy, and Complexity

Five years ago, demographer Richard Cincotta claimed in a piece for Foreign Policy that a country’s age structure is a powerful predictor of its prospects for attempting and sustaining liberal democracy. “A country’s chances for meaningful democracy increase,” he wrote, “as its population ages.” Applying that superficially simple hypothesis to the data at hand, he ventured a forecast:

The first (and perhaps most surprising) region that promises a shift to liberal democracy is a cluster along Africa’s Mediterranean coast: Morocco, Algeria, Tunisia, Libya, and Egypt, none of which has experienced democracy in the recent past. The other area is in South America: Ecuador, Colombia, and Venezuela, each of which attained liberal democracy demographically “early” but was unable to sustain it. Interpreting these forecasts conservatively, we can expect there will be one, maybe two, in each group that will become stable democracies by 2020.

I read that article when it was published, and I recall being irritated by it. At the time, I had been studying democratization for more than 15 years and was building statistical models to forecast transitions to and from democracy as part of my paying job. Seen through those goggles, Cincotta’s construct struck me as simplistic to the point of naiveté. Democratization is a hard theoretical problem. States have arrived at and departed from democracy by many different pathways, so how could what amounts to a one-variable model possibly have anything useful to say about it?

Revisiting Cincotta’s work in 2014, I like it a lot more for a couple of reasons. First, I like the work better now because I have come to see it as an elegant representation of a larger idea. As Cincotta argues in that Foreign Policy article and another piece he published around the same time, demographic structure is one component of a much broader and more complex syndrome in which demography is both effect and cause. Changes in fertility rates, and through them age structure, are strongly shaped by other social changes like education and urbanization, which are correlated with, but hardly determined by, increases in national wealth.

Of course, that syndrome is what we conventionally call “development,” and the pattern Cincotta observes has a strong affinity with modernization theory. Cincotta’s innovation was to move the focus away from wealth, which has turned out to be unreliable as a driver and thus as a proxy for development in a larger sense, to demographic structure, which is arguably a more sensitive indicator of it. As I see it now, what we now call development is part of a “state shift” occurring in human society at the global level that drives and is reinforced by long-term trends in democratization and violent conflict. As in any complex system, though, the visible consequences of that state shift aren’t evenly distributed.

In this sense, Cincotta’s argument is similar to one I often find myself making about the value of using infant mortality rates instead of GDP per capita as a powerful summary measure in models of a country’s susceptibility to insurgency and civil war. The idea isn’t that dead children motivate people to attack their governments, although that may be one part of the story. Instead, the idea is that infant mortality usefully summarizes a number of other things that are all related to conflict risk. Among those things are the national wealth we can observe directly (if imperfectly) with GDP, but also the distribution of that wealth and the state’s will and ability to deliver basic social services to its citizens. Seen through this lens, higher-than-average infant mortality helps us identify states suffering from a broader syndrome that renders them especially susceptible to violent conflict.

Second, I have also come to appreciate more what Cincotta was and is doing because I respect his willingness to apply his model to generate and publish probabilistic forecasts in real time. In professional and practical terms, that’s not always easy for scholars to do, but doing it long enough to generate a real track record can yield valuable scientific dividends.

In this case, it doesn’t hurt that the predictions Cincotta made six years ago are looking pretty good right now, especially in contrast to the conventional wisdom of the late 2000s on the prospects for democratization in North Africa. None of the five states he lists there yet qualifies as a liberal democracy on his terms, a “free” designation from Freedom House). Still, it’s only 2014, one of them (Tunisia) has moved considerably in that direction, and two others (Egypt and Libya) have seen seemingly frozen political regimes crumble and substantial attempts at democratization ensue. Meanwhile, the long-dominant paradigm in comparative democratization would have left us watching for splits among ruling elites that really only happened in those places as their regimes collapsed, and many area experts were telling us in 2008 to expect more of the same in North Africa as far as the mind could see. Not bad for a “one-variable model.”

Whither Organized Violence?

The Human Security Research Group has just published the latest in its series of now-annual reports on “trends in organized violence around the world,” and it’s essential reading for anyone deeply interested in armed conflict and other forms of political violence. You can find the PDF here.

The 2013 edition takes Steven Pinker’s Better Angels as its muse and largely concurs with Pinker’s conclusions. I’ll sheepishly admit that I haven’t read Pinker’s book (yet), so I’m not going to engage directly in that debate. Instead, I’ll call attention to what the report’s authors infer from their research about future trends in political violence. Here’s how that bit starts, on p. 18:

The most encouraging data from the modern era come from the post–World War II years. This period includes the dramatic decline in the number and deadliness of international wars since the end of World War II and the reversal of the decades-long increase in civil war numbers that followed the end of the Cold War in the early 1990s.

What are the chances that these positive changes will be sustained? No one really knows. There are too many future unknowns to make predictions with any degree of confidence.

On that point, political scientist Bear Braumoeller would agree. In an interview last year for Popular Science (here), Kelsey Atherton asked Braumoeller about Braumoeller’s assertion in a recent paper (here) that it will take 150 years to know if the downward trend in warfare that Pinker and others have identified is holding. Braumoeller replied:

Some of this literature points to “the long peace” of post-World War II. Obviously we haven’t stopped fighting wars entirely, so what they’re referring to is the absence of really really big wars like World War I and World War II. Those wars would have to be absent for like 70 to 75 more years for us to have confidence that there’s been a change in the baseline rate of really really big wars.

That’s sort of a separate question from how we know whether there are trends in warfare in general. We need to understand that war and peace are both stochastic processes. We need a big enough sample to rule out the historical average, which is about one or two big wars per century. We just haven’t had enough time since World War I and World War II to rule out the possibility that nothing’s changed.

I suspect that the authors of the Human Security Report would not dispute that claim, but after carefully reviewing Pinker’s and their own evidence, they do see causes for cautious optimism. Here I’ll quote at length, because I think it’s important to see the full array of forces taken into consideration to increase our confidence in the validity of the authors’ cautious speculations.

The case for pessimism about the global security future is well rehearsed and has considerable support within the research community. Major sources of concern include the possibility of outbreaks of nuclear terrorism, a massive transnational upsurge of lethal Islamist radicalism, or wars triggered by mass droughts and population movements driven by climate change.

Pinker notes reasons for concern about each of these potential future threats but also skepticism about the more extreme claims of the conflict pessimists. Other possible drivers of global violence include the political crises that could follow the collapse of the international financial system and destabilizing shifts in the global balance of economic and military power—the latter being a major concern of realist scholars worried about the economic and military rise of China.

But focusing exclusively on factors and processes that may increase the risks of large-scale violence around the world, while ignoring those that decrease it, also almost certainly leads to unduly pessimistic conclusions.

In the current era, factors and processes that reduce the risks of violence not only include the enduring impact of the long-term trends identified in Better Angels but also the disappearance of two major drivers of warfare in the post–World War II period—colonialism and the Cold War. Other post–World War II changes that have reduced the risks of war include the entrenchment of the global norm against interstate warfare except in self-defence or with the authority of the UN Security Council; the intensification of economic and financial interdependence that increases the costs and decreases the benefits of cross-border warfare; the spread of stable democracies; and the caution-inducing impact of nuclear weapons on relations between the major powers.

With respect to civil wars, the emergent and still-growing system of global security governance discussed in Chapter 1 has clearly helped reduce the number of intrastate conflicts since the end of the Cold War. And, at what might be called the “structural” level, we have witnessed steady increases in national incomes across the developing world. This is important because one of the strongest findings from econometric research on the causes of war is that the risk of civil wars declines as national incomes—and hence governance and other capacities—increase. Chapter 1 reports on a remarkable recent statistical study by the Peace Research Institute, Oslo (PRIO) that found that if current trends in key structural variables are sustained, the proportion of the world’s countries afflicted by civil wars will halve by 2050.

Such an outcome is far from certain, of course, and for reasons that have yet to be imagined, as well as those canvassed by the conflict pessimists. But, thanks in substantial part to Steven Pinker’s extraordinary research, there are now compelling reasons for believing that the historical decline in violence is both real and remarkably large—and also that the future may well be less violent than the past.

After reading the new Human Security Report, I remain a short-term pessimist and long-term optimist. As I’ve said in a few recent posts (see especially this one), I think we’re currently in the thick of period of systemic instability that will continue to produce mass protests, state collapse, mass killing, and other forms of political instability at higher rates than we’ve seen since the early 1990s for at least the next year or two.

At the same time, I don’t think this local upswing marks a deeper reversal of the long-term trend that Pinker identifies, and that the Human Security Report confirms. Instead, I believe that the global political economy is continuing to evolve in a direction that makes political violence less common and less lethal. This system creep is evident not only in the aforementioned trends in armed violence, but also in concurrent and presumably interconnected trends in democratization, socio-economic development, and global governance. Until we see significant and sustained reversals in most or all of these trends, I will remain optimistic about the directionality of the underlying processes of which these data can give us only glimpses.

The Green Lantern Theory of State-Building

In a recent post on Human Rights Watch’s World Policy Blog, Hanan Salah nicely summarizes the poor state of state-building in post-Qaddafi Libya:

The main problem affecting both justice and security is that armed militias still maintain the upper hand. They have various agendas—financial, territorial, political, religious—and operate with impunity two years after the Qaddafi regime ended. Successive interim governments have failed to assert control over these militias, preferring to contract them as parallel forces to the army and police. Consequently, they retain a stranglehold over key security objectives, such as protecting Libya’s oil fields, making it ever harder for the government to break their financial dependency and hold on these lucrative opportunities. The structure of the militias and related armed groups, their shared interests, political aspirations, and the tribal nature of Libyan society are further complicating factors.

This passage gets at the chicken-and-egg problem that makes state-building so hard, not just in Libya but everywhere. “Justice and security” are the chief public goods a state exists to provide, but the provision of those goods depends on widespread obedience of state authority, and that authority is hard to construct.

What bugged me about Salah’s otherwise excellent post was the use of the verb “prefer” to indicate why this authority isn’t cohering faster in Libya. “Prefer” connotes choice, and I’m not convinced that the officials comprising Libya’s internationally recognized government have very much of that. They face an array of entrenched militias that are probably profiting handsomely from control of their various fiefdoms. Those officials supposedly command an army and police force of their own, but those organizations are still small and under-resourced. Worse, the revenue streams that could make the national army and state police stronger—including oil—are often controlled by the very militias those forces are supposed to be beefing up to defeat. Under these circumstances, how exactly are Libyan officials supposed to persuade these militias to cooperate? Give them a stern talking-to?

To be fair, Salah’s post is hardly the first place I’ve seen this line. Actually, I think it’s fair to say that this is comparative politics’ version of the Green Lantern Theory that Matt Yglesias coined to describe neoconservative U.S. foreign policy and Brendan Nyhan has since extended to the American presidency. In the Green Lantern Theory, political outcomes are mostly a matter of will. If the state doesn’t cohere, it’s because the people tasked with doing it lack the spine to fulfill their charge as duly chosen leaders.

If we reject the Green Lantern Theory of state-building and recognize that power is at least as important as will, it’s tempting to think that outsiders can goose the process with an infusion of armed forces, or at least the money and training an internationally recognized government needs to build up its own. The growth of the state is stunted, so a few costly doses of hormone therapy should do the trick. In fact, as Reuters reported, Libya’s prime minister recently made just this plea at an investment conference in London:

If the international community does not help in the collection of arms and ammunition, if we don’t get help in forming the army and the police, things are going to take very long… The situation is not going to improve unless we get real and practical assistance.

In fact, politics isn’t nearly as mechanical and modular as this idea implies. Before embarking on a new state-boosting mission in Libya, foreign governments would do well to take another look at Somalia, which has been the target of similar treatments for the past two decades. As Alex de Waal describes in a recent post on the LRB Blog,

[President] Hassan’s Western backers have not yet squared the circle of pouring money and guns into a client government to fight a counterinsurgency, and preventing that government from becoming rentierist, militaristic and corrupt. Rent-seeking pervades the whole system: the president or defence minister must bargain separately with each military unit to secure its loyalty for each operation. And even then, he cannot order a Somali unit to enter a ‘liberated’ town where the locals won’t welcome it. It’s no surprise that Somalis hedge their bets against the time when the [Somali Federal Government's] international sponsors tire of a Sisyphean counterinsurgency and sell out their erstwhile proxies. Even if al-Shabab were defeated, it wouldn’t solve Somalia’s problems. The corrupt rentierist system of government, which gave rise to al-Shabab in the first place, would be more entrenched than before.

Much the same could be said of Afghanistan, too.

And this is the Great Frustration of applied social science: prescription doesn’t always follow from explanation. Even if we can understand pretty well why state-building is so hard, we still can’t figure out how to control it. Whether that’s a curse or a blessing will depend on whom you ask, and therein lies the essence of politics.

Watch Locally, Think Globally

In the Central African Republic, an assemblage of rebel groups has toppled the government and installed a new one but now refuses to follow its writ. As those rebels loot and maraud, new armed groups have formed to resist them, and militias loyal to the old government have struck back, too. All of this has happened on the watch of a 2,000-person peacekeeping force from neighboring states. With U.N. backing, those neighbors are now sending more men with guns in hopes that another 1,500 soldiers will finally help restore some sense of order.

This is what full-blown state collapse looks like—as close to Thomas Hobbes’ “war of all against all” as you’re ever likely to see. As I wrote at the start of the year, though, CAR is hardly the only country in such shambles. By my reckoning, Libya, Syria, Yemen, Somalia still, and maybe DRC and South Sudan qualify as collapsed states, too, and if Mali doesn’t anymore, it only just squeaked back over the line.

As the very act of listing implies, we often think of these situations as discrete cases. In our social-scientific imaginations, countries are a bit like petri dishes lined up on a laboratory countertop. Each undergoes a similar set of experiments, and our job is to explain the diversity of their outcomes.

The longer I watch world affairs, though, the less apt that experimental metaphor seems. We can only really understand processes like state collapses—and the civil wars that usually produce them, and the regime transformations that  often precede and succeed them, and virtually everything else we study in international studies—by thinking of these “cases” as local manifestations of system-level dynamics, or at least the product of interactions between local and global processes that are inseparable and mutually causal.

If we think on a systemic scale, it’s easier to see that we are now living through a period of global disorder matched in recent history only by the years surrounding the disintegration of the Soviet Union, and possibly exceeding it. Importantly, it’s not just the spate of state collapses through which this disorder becomes evident, but also the wider wave of protest activity and institutional transformation to which some of those collapses are connected. These streams of change are distinct in some ways, but they also shape each other and share some common causes.

And what are those common causes? The 2007 financial crisis surely played a significant role. The resulting recessions in the U.S. and Europe rippled outward, shrinking trade flows and remittances to smaller and poorer countries and pulling down demand for commodities on which some of their economies heavily depend.

Those recessions also seem to have accelerated shifts in relative power among larger countries, or at least perceptions of them. Those perceptions—see here and here, for example—may matter even more than the underlying reality because they shape governments’ propensity to intervene abroad, the forms those interventions take, and, crucially, other governments’ beliefs about what kinds of intervention might occur in the future. In this instance, those perceptions have only been reinforced by popular concerns about the cost and wisdom of foreign intervention when so many are suffering through hard times at home. This amalgamation of forces seems to have found its sharpest expression yet in the muddled and then withdrawn American threat to punish the Syrian regime for its use of chemical weapons, but the trends that crystallized in that moment have been evident for a while.

The financial crisis also coincided with, and contributed to, a global run-up in food prices that still hasn’t abated by much (see the chart below, from the FAO). As I mentioned in another recent post, a growing body of evidence supports the claim that high food prices help produce waves of civil unrest. This link is evident at the level of the global system and in specific cases, from the countries involved in the Arab Spring to South Africa. Because food prices are so influential, I think it’s likely that climate change is contributing to the current disorder, too, as another force putting upward pressure on those prices and sometimes dislodging large numbers of people who have to pay them.

As Peter Turchin and others have argued, it’s possible that generic oscillations in human social order—perhaps the political analogue of the business cycle—are also part of the story. I’m not confident that these patterns are distinct from the forces I’ve already mentioned, but they could be, at least in part. In any case, those patterns seem sufficiently robust that they deserve more attention than most of us give them now.

Last but not least, the systemic character of these processes is also evident in the forms of negative and positive feedback that arise to try to reverse or accelerate the slide into entropy. Powerful players with a stake in extant structures—mostly states, but also private corporations and even transnational NGOs—work to restore local forms of order that reinforce rather than challenge those structures. At the same time, other actors try to leverage the entropy to their own advantage. Governments less invested in the prior order may see new opportunities to weaken rivals or husband allies. Transnational criminal enterprises often find ways to expand revenue streams and develop new ones by smuggling arms and other contraband to and through societies that have fallen apart. Since the late 2000s, for example, “there has been a significant increase in the number of attacks on vessels by pirates,” Interpol claims, and I don’t think this concurrence of this trend with the spikes in popular unrest and state collapse is purely coincidental.

This system-level view finds linkages between a host of recent trends that we usually only consider in isolation from each other. It also suggests that this, too, shall pass—and then occur again. If Turchin & co. are correct, the current wave of disorder won’t peak for another several years, and we can expect the next iteration to arrive in the latter half of the current century. I’m not convinced the cycles are as tidy as that, and I wonder if the nature of the system itself is now changing in ways that will produce new patterns in the future. Either way, though, I hope it’s now clear that the miseries besetting CAR aren’t as disconnected from the collapses of Libya, Syria, and Yemen or the eruptions of mass protest in a host of countries over the past several years as our compartmentalized reading and theorizing usually entices us to think.

How Social Science Is Like Microbiology

I’m almost finished reading Michael Pollan’s latest, Cooked. It’s a terrific book about food, but it’s also steeped in science, and I wanted to share a passage from the part of the book on fermentation that really resonated with me. Pollan is writing about microbiology, but the developments he identifies in that field could (or should) apply just as well to the social sciences. The passage starts like this:

In the decades since Louis Pasteur founded microbiology, medical research has focused mainly on bacteria’s role in causing disease. The bacteria that reside in and on our bodies were generally regarded as either harmless “commensals”—freeloaders, basically—or pathogens to be defended against. Scientists tended to study these bugs one at a time, rather than as communities. This was partly a deeply ingrained habit of reductive science, and partly a function of the available tools. Scientists naturally focused their attention on the bacteria they see, which meant the handful of individual bugs that could be cultivated in a petri dish. There, they found some good guys and some bad guys. But the general stance toward bacteria we had discovered all around us was shaped by metaphors of war, and in that war, antibiotics became the weapon of choice.

Cholera_bacteria_SEMThe “habit of reductive science” Pollan describes should be familiar to social scientists, too. We often sort the objects of our analysis into binary categories of helpful and hurtful, assume the objects we see are all there really is, and then design interventions to try to kill the bad without harming the good. Where microbiology has traditionally drawn a sharp line between pathogens and cells that belong, social science has neatly distinguished rebel groups and criminal gangs and patronage networks from bureaucracies and political parties and civil society. Where medicine has antibiotics, development practitioners have aid.

What we’re now learning, though, is that these lines are really much blurrier than we’ve assumed. Pollan goes on:

But it turns out that the overwhelming majority of bacteria residing in the gut simply refuse to grow on a petri dish—a phenomenon known among researchers as “the great plate anomaly.” Without realizing it, they were practicing what is sometimes called parking-lot science—named for the human tendency to search for lost keys under the streetlights not because that’s where we lost them but because that is where we can best see. The petri dish was a streetlight. But when, in the early 2000s, researchers developed genetic “batch” sequencing techniques allowing them to catalog all the DNA in a sample of soil, say, or seawater or feces, science suddenly acquired a broad and powerful beam light that could illuminate the entire parking lot. When it did, we discovered hundreds of new species in the human gut doing all sorts of unexpected things.

This, to me, is the promise of what Gary King calls the “social science data revolution.” Exponential growth in the production and distribution of information to and from all parts of the world, and in our collective capacity to store and process and analyze that information, are to the social sciences what genetic batch sequencing is to microbiology. Our libraries and limited professional networks were our petri dishes, and now they’ve been shattered—in a good way.

Pollan then describes where microbiology’s version of the data revolution has led:

To their surprise, microbiologists discovered that nine of every ten cells in our bodies do not belong to us, but to these microbial species (most of them residents of our gut), and that 99 percent of the DNA we’re carrying around belongs to those microbes. Some scientists, trained in evolutionary biology, began looking at the human individual in a humbling new light: as a kind of superorganism, a community of several hundred coevolved and interdependent species. War metaphors no longer made sense. So the microbiologists began borrowing new metaphors from the ecologists.

I’d say a comparable gestalt shift is occurring in some corners of social science, with similarly dramatic implications. For decades, we’ve cranked out snapshots and diagrams and typologies of objects—states, parties, militaries, ethnic groups—that we’ve assumed to be more or less static and distinct and told just-so stories about how one thing changes into another. Now, we’re shedding those functionalist assumptions and getting better at seeing those objects as permeable superorganisms embedded in ecosystems, all of them continually coevolving in ways that may elude our capacity to narrate, or even to understand at all. The implications are simultaneously thrilling and overwhelming.

A Cautionary Note on Increased Aid to Syrian Rebels

According to today’s Washington Post, the U.S. government is starting to supply food and medicine directly to selected Syrian rebel groups. Meanwhile, “Britain and other nations working in concert with the United States are expected to go further to help the rebel Free Syrian Army by providing battlefield equipment such as armored vehicles, night-vision devices or body armor.”

The point of all this assistance, of course, is to hasten the fall of Syrian President Bashir al-Assad. According to newly minted Secretary of State John Kerry, Assad is “out of time and must be out of power.”

220px-Ford_assembly_line_-_1913

Best I can tell, the logic behind this stepped-up support for the Syrian rebels Western governments “like” follows the logic of an assembly line. To increase desired outputs, increase relevant inputs.

But civil wars aren’t like factories. They’re more like ecosystems, and if there’s one thing we’ve learned from our attempts to manage ecosystems, it’s that they often have unintended consequences. Consider this 2009 story from the New York Times:

With its craggy green cliffs and mist-laden skies, Macquarie Island — halfway between Australia and Antarctica — looks like a nature lover’s Mecca. But the island has recently become a sobering illustration of what can happen when efforts to eliminate an invasive species end up causing unforeseen collateral damage.

In 1985, Australian scientists kicked off an ambitious plan: to kill off non-native cats that had been prowling the island’s slopes since the early 19th century. The program began out of apparent necessity — the cats were preying on native burrowing birds. Twenty-four years later, a team of scientists from the Australian Antarctic Division and the University of Tasmania reports that the cat removal unexpectedly wreaked havoc on the island ecosystem.

With the cats gone, the island’s rabbits (also non-native) began to breed out of control, ravaging native plants and sending ripple effects throughout the ecosystem. The findings were published in the Journal of Applied Ecology online in January.

“Our findings show that it’s important for scientists to study the whole ecosystem before doing eradication programs,” said Arko Lucieer, a University of Tasmania remote-sensing expert and a co-author of the paper. “There haven’t been a lot of programs that take the entire system into account. You need to go into scenario mode: ‘If we kill this animal, what other consequences are there going to be?’”

I don’t mean to suggest a moral equivalence between the human beings fighting and being murdered in Syria and the rabbits and cats and birds on Macquarie Island. I do mean to suggest that attempts to manipulate systems like these almost always underestimate the complexity of the problem. What scientist Barry Rice said to the New York Times for that 2009 article on the difficulty of managing invasive species applies just as well to attempts by outside powers to manufacture desired outcomes in civil wars:

When you’re doing a removal effort, you don’t know exactly what the outcome will be. You can’t just go in and make a single surgical strike. Every kind of management you do is going to cause some damage.

I hope Syria gets to a better place soon. Like Dan Trombly and Ahsan Butt, however, I am not confident that increased support for selected rebel factions will help that happen, and I am worried about the unintended consequences it will bring.

Comparative Politics, Meet Complex Interdependence

On the IPE@UNC blog a few days ago, Kindred Winecoff compellingly argued that much of the theory-testing done in international relations (IR) and international political economy (IPE) in recent years rests on the false assumption that outcomes across cases are independent of each other. Paraphrasing here, he points out that “almost all” of the big theoretical traditions in IR and IPE—neorealism, liberal institutionalism, and Marxism among them—identify ways in which outcomes across cases are strongly interdependent, but the research designs we usually adopt to test those theories implicitly assume they are not. In other words, “in the typical case, our empirical design does not match our theoretical structure.”

I think he’s right, and I think the same can be said of theories of political development, which is really most of what comparative politics is about. Two cases of current interest illuminate how it’s really impossible to understand persistence and change in national political institutions without thinking about how those institutions are embedded in a larger global context.

Let’s start with Myanmar. Conventional theories meant to apply to the reforms occurring there focus our attention on domestic processes, like socioeconomic modernization or economic inequality, as the likely impetus behind these changes. At best, though, these processes are structural conditions that have shifted little in Myanmar in recent years, and at worst they’re close to irrelevant. Myanmar is currently experiencing a rush of “modernization,” but much of it’s happening as a consequence, not a cause, of the regime-initiated liberalization. Any effort to understand why this liberalization is occurring now has to consider the growing fears of Burmese elites about their dependency on China, the bite of U.S. sanctions, and the opportunity costs of remaining isolated in a global economy that sees the country as an untapped trove and under-served market. If you try to estimate the effects of income or education or inequality on these trends in a model that ignores these wider forces, you’re probably going to get a misleading result.

Or take Bahrain. It’s impossible to explain the start of the popular uprising in Manama in the spring of 2011 without talking about diffusion, and it’s impossible to understand the outcome (so far) without looking at the material and diplomatic support the monarchy receives from powerful patrons—support that is itself rooted in those patrons’ regional geopolitical (counterbalancing Iran) and global economic (oil) concerns.

If you want to get really silly, imagine trying to infer the effects of income or oil wealth or inequality on the propensity for democratization from a data set composed only of Panama and Iraq. Talk about omitted-variable bias…

I don’t mean to imply that of scholars of comparative politics are oblivious to these issues. Interpretive studies of political development often reference international forces, and over the past 20 years, we’ve increasingly tried to incorporate these ideas into our statistical models as well. Steven Levitsky and Lucan Way’s thoughts on linkage and leverage are an example of the former. Other studies have nibbled at the problem by looking for evidence of diffusion in patterns of democratization, or at the marginal effects from participation in international organizations and other treaty regimes. Studies on the relationship between oil wealth and the survival of authoritarian regimes also lean in this direction, although it’s telling that newer research suggests that these effects really aren’t about oil per se so much as the specific role that commodity has played in a particular (and likely fleeting) realization of the global political economy. Dependency theory also operated at this level, although the results were a bit cartoonish and the long-term predictions have now been proved flat wrong.

What’s still missing from comparative politics, I think, is the one-two punch of theories that are more explicitly systemic combined with methods that suit those theories. Right now, we’ve got little bits of each, but nothing that really brings the two together. We’re stuck in a complex adaptive system that doesn’t really distinguish between national and international, political and economic, human and natural, and our theories of stability and change in political institutions should take that whole more seriously.

Instead of thinking of the international environment as something we incorporate into our models by tacking one or two covariates onto the tail ends of our country-level equations, we should think more carefully about country-level institutions as middle-range manifestations of processes occurring in a global system. The simplifying assumption that states are separable units certainly has its uses, but we shouldn’t conflate that utility with causal relevance. Like maps, all models are simplifications, but those simplifications aren’t useful if they ignore the very causes they’re meant to locate. That’s true in a metaphorical sense, but as Winecoff calls out in the blog post that sparked this ramble, it’s also true in the more literal sense that badly misspecified models produce unreliable results.

I’ll wrap this ramble up by noting that the “development” metaphor itself helps illuminate the problem, and might even contribute to it by reinforcing a certain frame of mind. In many fields of study, “development” is a process that happens to individuals and follows a certain arc. It connotes directional growth and maturation, and it has a beginning, middle, and end. When we apply this metaphor to politics—comparing “fledgling” and “mature” democracies, for example, or talking about the “international community” as if it were something like a gathering of people in a room—we get stuck in a rut from which it’s hard to see the other, arguably richer, aspects of that world.

What Darwin Teaches Us about Political Regime Types

Here’s a paragraph, from a 2011 paper by Ian Lustick, that I really wish I’d written. It’s long, yes, but it rewards careful reading.

One might naively imagine that Darwin’s theory of the “origin of species” to be “only” about animals and plants, not human affairs, and therefore presume its irrelevance for politics. But what are species? The reason Darwin’s classic is entitled Origin of Species and not Origin of the Species is because his argument contradicted the essentialist belief that a specific, finite, and unchanging set of categories of kinds had been primordially established. Instead, the theory contends, “species” are analytic categories invented by observers to correspond with stabilized patterns of exhibited characteristics. They are no different in ontological status than “varieties” within them, which are always candidates for being reclassified as species. These categories are, in essence, institutionalized ways of imagining the world. They are institutionalizations of difference that, although neither primordial nor permanent, exert influence on the futures the world can take—both the world of science and the world science seeks to understand. In other words, “species” are “institutions”: crystallized boundaries among “kinds”, constructed as boundaries that interrupt fields of vast and complex patterns of variation. These institutionalized distinctions then operate with consequences beyond the arbitrariness of their location and history to shape, via rules (constraints on interactions), prospects for future kinds of change.

This is one of the big ideas to which I was trying to allude in a post I wrote a couple of months ago on “complexity politics”, and in an ensuing post that used animated heat maps to trace gross variations in forms of government over the past 211 years. Political regime types are the species of comparative politics. They are “analytic categories invented by observers to correspond with stabilized patterns of exhibited characteristics.” In short, they are institutionalized ways of thinking about political institutions. The patterns they describe may be real, but they are not essential. They’re not the natural contours of the moon’s surface; they’re the faces we sometimes see in them.

video game taxonomy

Mary Goodden’s Taxonomy of Video Games

If we could just twist our mental kaleidoscopes a bit, we might find different things in the same landscape. One way to do that would be to use a different set of measures. For the past 20 years or so, political scientists have relied almost exclusively on the same two data sets—Polity and Freedom House’s Freedom in the World—to describe and compare national political regimes in anything other than prose. These data sets are very useful, but they are also profoundly conventional. Polity offers a bit more detail than Freedom House on specific features of national politics, but the two are essentially operationalizing the same assumptions about the underlying taxonomy of forms of government.

Given that fact, it’s hard to see how further distillations of those data sets might surprise us in any deep way. A new project called Varieties of Democracy (V-Dem) promises to bring fresh grist to the mill by greatly expanding the number of institutional elements we can track, but it is still inherently orthodox. Its creators aren’t trying to reinvent the taxonomy; they’re looking to do a better job locating individuals in the prevailing one. That’s a worthy and important endeavor, but it’s not going to produce the kind of gestalt shift I’m talking about here.

New methods of automated text analysis just might. My knowledge of this field is quite limited, but I’m intrigued by the possibilities of applying unsupervised learning techniques, such as latent Dirichlet allocation (LDA), to the problem of identifying political forms and associating specific cases with them. In contrast to conventional measurement strategies, LDA doesn’t oblige us to specify a taxonomy ahead of time and then look for instances of the things in it. Instead, LDA assumes there is an infinite mixture of overlapping but latent categories out there, and these latent categories are partially revealed by characteristic patterns in the ways we talk and write about the world.

Unsupervised learning is still constrained by the documents we choose to include and the language we use in them, but it should still help us find patterns in the practice of politics that our conventional taxonomies overlook. I hope to be getting some funding to try this approach in the near future, and if that happens, I’m genuinely excited to see what we find.

211 Years of Political Evolution in 60 Seconds — New and Improved!!

The heat maps used in the animation I posted yesterday plotted change over time in counts of countries in each cell of a two-dimensional space representing different kinds of politcal institutions. Over the 211 years in question, however, the number of countries in the world has grown dramatically, from about 50 in 1800 to well over 150 in 2011. For that reason, a couple of commenters wondered whether we would see something different if we plotted proportions instead of counts, using the size of the total population as a denominator in each cell. Proportions better fit the ideas behind a fitness landscape, so I added a line to my code and gave it a whirl. Here’s what I got:

To my eye, there aren’t any big differences in the patterns we see here compared with the ones based on counts. Re-watching the animation today, though, here are a few other things that caught my attention:

  • The predominance in the mid-1800s of intermediate forms combining authoritarian selection with highly polarized political participation—what Polity calls “factionalism.” This peak in the middle left of the heat maps shows how popular mobilization generally led to competitive elections, and not the other way around. As historian Sean Wilenz wrote, “Democracy is never a gift bestowed…It must always be fought for.” It also reminds us that popular mobilization was initially quite polarized in the “developed” world (ha!), just as it often is poorer countries today.
  • The wide variety of intermediate forms present in the early 1900s. Here we see a bunch of cases in the upper left-hand quadrant, combining authoritarian selection procedures with open and well-regulated participation. This is a combination we almost never see nowadays. It looks like there were some interesting experiments occurring in the wake of the industrial explosion that occurred in richer countries in the latter half of the nineteenth century.
  • The sharp bifurcation of the fitness landscape after World War II. Before the war, the peak in the lower left-hand corner representing closed dictatorships had shrunken, and there seemed to be more action in the upper left and lower right quadrants. After the war, the peak in the lower left rose again and remained there until around 1990. This pattern makes clearer that the evolution of the past two centuries has not been a steady march toward democracy. It’s interesting—and potentially chilling—to contemplate how much the fitness landscape of the past 70 years might have differed had World War II taken different turns.

211 Years of Political Evolution in 60 Seconds

The GIF below—click on it to make it play—animates a series of 211 heat maps summarizing annual data on national political regimes around the world from 1800 to 2010. The space in the heat maps represents two of the “concept” variables from the Polity IV data set—executive recruitment and political competition—that roughly correspond to the dimensions of contestation and participation Robert Dahl uses to define modern regime types. In the animated maps, the lower left is least democratic, and the upper right is most democratic. The darker the grey, the higher the number of cases in that cell. [NB. For a version that uses proportions instead of raw counts and some additional thoughts on patterns over time, see this short follow-up post.]

[Fellow propeller-heads: I built this in R with helpful suggestions from Trey Causey and Tom Parris along the way. The heat maps were made with a function appropriately called 'heatmap', and I used the 'animation' package to compile those images into a .gif. Ping me if you'd like to see the script.]

I made this animation because I think it supports the idea, discussed briefly in my last post, that political development is an evolutionary process. Evolutionary processes feed on diversity and mutation, but the results of evolution are not randomly distributed. Borrowing from Daniel Dennett, we can imagine evolution occurring in a multidimensional design space that contains all possible combinations of a particular set of building blocks. In biology, those building blocks are genes; in politics, they might be simple rules.

For present purposes, let’s imagine that there are only two dimensions in this design space. Those two dimensions suggest a map of the design space that evolutionary biologists call a fitness landscape. The topography of this landscape is determined by the fitness of specific combinations, as indicated by sizes of the relevant populations. That’s what the heat maps in the animation above are showing.

The existence of the system is a matter of chance, but once an evolutionary system emerges, we can expect to see certain patterns. The selection pressures present in any particular environment mean that some combinations will be fitter than others, producing visible and often durable peaks in that fitness landscape. Mutation—and, in the case, of social technologies like government, deliberate tinkering—will keep producing new varieties, but most won’t be fit enough for the environment of the day to survive and spread. As a result, most of the variation will cluster around the existing peaks, because small differences in design will often (but not always!) produce small differences in fitness.

When selection pressures change, however, the designs embodied in the previous peaks will often become less fit, and new designs will emerge as stronger competitors. Importantly, though, that transition from the old peaks to new ones usually won’t be smooth and direct. Instead, as Niles Eldredge and Stephen Jay Gould describe in their model of punctuated equlibrium, we can expect to see bursts of diversity as the evolutionary engine “searches” for new forms that better fit the changing environment. As the selection pressures settle into a new normal, the fitness landscape should also settle back into the familiar pattern of clearer peaks and valleys.

The two Polity variables used here are, of course, gross and conceptually biased simplifications of complex phenomena. Underlying each of these dimensions are a few component variables that are themselves simplifications of complex sets of written and unwritten rules. Still, the Polity data are the best we’ve got right now for observing change in over a long period of time, and it’s pretty hard for us humans to visualize four- or seven- or thirty-dimensional space. So, for now, I’m using these two summary indices to get a very rough map of the design space for modern political institutions.

Maybe it’s confirmation bias at work, but when I watch the animation above, I see the patterns evolutionary theorists tell me I should see. In 1800, the fitness landscape is dominated by a single peak representing highly undemocratic regimes—mostly monarchies with virtually no popular participation. If we could extend the movie back several more centuries, we would see the same pattern holding through the entirety of human civilization since our hunter-gatherer days.

Pretty soon after we drop in to watch, however, things start to move. In the early 1800s, a couple of new lumps rise as popular participation expands in some regimes. Most countries still select their rulers by hereditary lineage or other closed means (the peak in the middle left), but some start using competitive elections to pick their governments. By the late nineteenth century, a second peak has clearly emerged in the upper right-hand corner, where rulers are chosen through competitive elections with broad participation. [NB: I think Polity rushes things a bit here by ignoring the disenfranchisement of women, but we go to publish with the data we've got, not the data we'd like.]

Through most of the twentieth century, the same general pattern holds. There’s a fair amount of variation, but most regimes are concentrated in the same few patches of the design space. At the end of the twentieth and start of the twenty-first centuries, however, we see a burst of diversity. The authoritarian peak shrinks, the democratic peak holds, and large swathes of the design space that have rarely been occupied bubble with activity.

To my eye, this very recent phase looks like one of Eldredge and Gould’s punctuation marks, that is, an episode of heightened diversity caused by a significant shift in selection pressures. Most observers of international politics won’t be surprised to see this pattern, and many of them would probably attribute it to the end of the Cold War. I’m not so sure. I’m more inclined to see the collapse of the Soviet Union and the expansion in the diversity of political forms as twin consequences of deeper changes in the global system that seem to be favoring democratic forms over authoritarian ones. What new peaks we’ll see when the system settles down again—and on what heretofore hidden dimensions of political design space they might draw—is impossible to know, but it sure is fascinating to watch.

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