From China, Another Strike Against Legitimacy

I’ve groused on this blog before (here and here) about the trouble with “legitimacy” as a causal mechanism in theories of political stability and change, and I’ve pointed to Xavier Marquez’s now-published paper as the most cogent expression of this contrarian view to date.

Well, here is a fresh piece of empirical evidence against the utility of this concept: according to a new Global Working Paper from Brookings, the citizens of China who have benefited the most from that country’s remarkable economic growth in recent decades are, on average, its least happy. As one of the paper’s authors describes in a blog post about their research,

We find that the standard determinants of well-being are the same for China as they are for most countries around the world. At the same time, China stands out in that unhappiness and reported mental health problems are highest among the cohorts who either have or are positioned to benefit from the transition and related growth—a clear progress paradox. These are urban residents, the more educated, those who work in the private sector, and those who report to have insufficient leisure time and rest.

These survey results contradict the “performance legitimacy” story that many observers use to explain how the Chinese Communist Party has managed to avoid significant revolutionary threats since 1989 (see here, for example). In that story, Chinese citizens choose not to demand political liberalization because they are satisfied with the government’s economic performance. In effect, they accept material gains in lieu of political voice.

Now, though, we learn that the cohort in which contentious collective action is most likely to emerge—educated urbanites—are also, on average, the country’s least happy people. The authors also report (p. 14) that, in China, “the effect of income increases on life satisfaction are limited.” A legitimacy-based theory predicts that the CCP is surviving because it is making and keeping its citizens happy; instead, we see that it is surviving in spite of deepening unhappiness among key cohorts.

To me, this case further bares the specious logic behind most legitimacy-based explanations for political continuity. We believe that rebellion is an expression of popular dissatisfaction, a kind of referendum in the streets; we observe stability; so, we reason backwards from the absence of rebellion to the absence of dissatisfaction, sprinkle a little normative dust on it, and arrive at a positive concept called legitimacy. Formally, this is a fallacy of affirmative conclusion from a negative premise: happy citizens don’t rebel, no rebellion is occurring, therefore citizens must be happy. Informally, I think it’s a qualitative version of the “story time” process in which statistical modelers often indulge: get a surprising result, then make up a richer explanation for it that feels right.

I don’t mean to suggest that popular attitudes are irrelevant to political stasis and change, or that the durability of specific political regimes has nothing to do with the affinity between their institutional forms and the cultural contexts in which they’re operating. Like Xavier, though, I do believe that the conventional concept of legitimacy is too big and fuzzy to have any real explanatory power, and I think this new evidence from China reminds us of that point. If we want to understand how political regimes persist and when they break down, we need to identify mechanisms that are more specific than this one, and to embed them in theories that allow for more complexity.

About That Apparent Decline in Violent Conflict…

Is violent conflict declining, or isn’t it? I’ve written here and elsewhere about evidence that warfare and mass atrocities have waned significantly in recent decades, at least when measured by the number of people killed in those episodes. Not everyone sees the world the same way, though. Bear Braumoeller asserts that, to understand how war prone the world is, we should look at how likely countries are to use force against politically relevant rivals, and by this measure the rate of warfare has held pretty steady over the past two centuries. Tanisha Fazal argues that wars have become less lethal without becoming less frequent because of medical advances that help keep more people in war zones alive. Where I have emphasized war’s lethal consequences, these two authors emphasize war’s likelihood, but their arguments suggest that violent conflict hasn’t really waned the way I’ve alleged it has.

This week, we got another important contribution to the wider debate in which my shallow contributions are situated. In an updated working paper, Pasquale Cirillo and Nassim Nicholas Taleb claim to show that

Violence is much more severe than it seems from conventional analyses and the prevailing “long peace” theory which claims that violence has declined… Contrary to current discussions…1) the risk of violent conflict has not been decreasing, but is rather underestimated by techniques relying on naive year-on-year changes in the mean, or using sample mean as an estimator of the true mean of an extremely fat-tailed phenomenon; 2) armed conflicts have memoryless inter-arrival times, thus incompatible with the idea of a time trend.

Let me say up front that I only have a weak understanding of the extreme value theory (EVT) models used in Cirillo and Taleb’s paper. I’m a political scientist who uses statistical methods, not a statistician, and I have neither studied nor tried to use the specific techniques they employ.

Bearing that in mind, I think the paper successfully undercuts the most optimistic view about the future of violent conflict—that violent conflict has inexorably and permanently declined—but then I don’t know many people who actually hold that view. Most of the work on this topic distinguishes between the observed fact of a substantial decline in the rate of deaths from political violence and the underlying risk of those deaths and the conflicts that produce them. We can (partly) see the former, but we can’t see the latter; instead, we have to try to infer it from the conflicts that occur. Observed history is, in a sense, a single sample drawn from a distribution of many possible histories, and, like all samples, this one is only a jittery snapshot of the deeper data-generating process in which we’re really interested. What Cirillo and Taleb purport to show is that long sequences of relative peace like the one we have seen in recent history are wholly consistent with a data-generating process in which the risk of war and death from it have not really changed at all.

Of course, the fact that a decades-long decline in violent conflict like the one we’ve seen since World War II could happen by chance doesn’t necessarily mean that it is happening by chance. The situation is not dissimilar to one we see in sports when a batter or shooter seems to go cold for a while. Oftentimes that cold streak will turn out to be part of the normal variation in performance, and the athlete will eventually regress to the mean—but not every time. Sometimes, athletes really do get and stay worse, maybe because of aging or an injury or some other life change, and the cold streak we see is the leading edge of that sustained decline. The hard part is telling in real time which process is happening. To try to do that, we might look for evidence of those plausible causes, but humans are notoriously good at spotting patterns where there are none, and at telling ourselves stories about why those patterns are occurring that turn out to be bunk.

The same logic applies to thinking about trends in violent conflict. Maybe the downward trend in observed death rates is just a chance occurrence in an unchanged system, but maybe it isn’t. And, as Andrew Gelman told Zach Beauchamp, the statistics alone can’t answer this question. Cirillo and Taleb’s analysis, and Braumoeller’s before it, imply that the history we’ve seen in the recent past  is about as likely as any other, but that fact isn’t proof of its randomness. Just as rare events sometimes happen, so do systemic changes.

Claims that “This time really is different” are usually wrong, so I think the onus is on people who believe the underlying risk of war is declining to make a compelling argument about why that’s true. When I say “compelling,” I mean an argument that a) identifies specific causal mechanisms and b) musters evidence of change over time in the presence or prevalence of those mechanisms. That’s what Steven Pinker tries at great length to do in The Better Angels of Our Nature, and what Joshua Goldstein did in Winning the War on War.

My own thinking about this issue connects the observed decline in the the intensity of violent conflict to the rapid increase in the past 100+ years in the size and complexity of the global economy and the changes in political and social institutions that have co-occurred with it. No, globalization is not new, and it certainly didn’t stop the last two world wars. Still, I wonder if the profound changes of the past two centuries are accumulating into a global systemic transformation akin to the one that occurred locally in now-wealthy societies in which organized violent conflict has become exceptionally rare. Proponents of democratic peace theory see a similar pattern in the recent evidence, but I think they are too quick to give credit for that pattern to one particular stream of change that may be as much consequence as cause of the deeper systemic transformation. I also realize that this systemic transformation is producing negative externalities—climate change and heightened risks of global pandemics, to name two—that could offset the positive externalities or even lead to sharp breaks in other directions.

It’s impossible to say which, if any, of these versions is “true,” but the key point is that we can find real-world evidence of mechanisms that could be driving down the underlying risk of violent conflict. That evidence, in turn, might strengthen our confidence in the belief that the observed pattern has meaning, even if it doesn’t and can’t prove that meaning or any of the specific explanations for it.

Finally, without deeply understanding the models Cirillo and Taleb used, I also wondered when I first read their new paper if their findings weren’t partly an artifact of those models, or maybe some assumptions the authors made when specifying them. The next day, David Roodman wrote something that strengthened this source of uncertainty. According to Roodman, the extreme value theory (EVT) models employed by Cirillo and Taleb can be used to test for time trends, but the ones described in this new paper don’t. Instead, Cirillo and Taleb specify their models in a way that assumes there is no time trend and then use them to confirm that there isn’t. “It seems to me,” Roodman writes, “that if Cirillo and Taleb want to rule out a time trend according to their own standard of evidence, then they should introduce one in their EVT models and test whether it is statistically distinguishable from zero.”

If Roodman is correct on this point, and if Cirillo and Taleb were to do what he recommends and still find no evidence of a time trend, I would update my beliefs accordingly. In other words, I would worry a little more than I do now about the risk of much larger and deadlier wars occurring again in my expected lifetime.

Walling Ourselves Off

In the past two weeks, more than a thousand people have died trying to cross the Mediterranean Sea from Africa to Europe on often-overloaded boats. In 2014, more than three thousand perished on this crossing.

Each individual migrant’s motives are unique and unknowable, but this collective surge in deaths clearly stems, in part, from the disorder engulfing parts of North Africa and the Middle East. Civil war and state collapse have expanded the incentives and opportunities to flee, and the increased flow of migrants along dangerous routes has, predictably, led to a surge in accidental deaths.

Of course, those deaths also owe something to the policies of the countries toward which the overloaded boats sail. European governments—many of them presiding over anemic growth and unemployment crises of their own—do not have open borders, and they have responded ambivalently or coolly to this spate of arrivals. Italy, where many of these boats land, had run a widely praised search-and-rescue program for a couple of years, but that effort was replaced in late 2014 by a smaller and so-far less successful EU program. Most observers lament the drownings, but some also worry that a more effective rescue scheme will encourage more people to attempt the crossing, or to get into the sordid business of ferrying others.

Humans have always, and often literally, built walls to keep outsiders out. Leslie Chang’s Factory Girls examines China’s current wave of urban migration, but she also dug into her own family’s history in that country and found this:

In 1644, the Manchus, an ethnic group living on China’s northeaster frontier, conquered China and established the Qing Dynasty. Soon thereafter, the Qing rulers declared Manchuria off-limits to the Han Chinese, the majority ethnic group of the rest of the country. Their aim was to monopolize the region’s natural resources and to preserve their homeland: As long as the frontier remained intact, they believed, their people would retain their vitality and forestall the corruption and decadence by which dynasties inevitably fell. To seal off Manchuria, the emperors ordered the construction of a two-hundred-mile mud wall planted with willow trees. It stretched from the Great Wall northeast through most of present-day Liaoning and Jilin provinces, with fortified checkpoints along its length.

The border was called the Willow Palisade, and it was even more porous than the Great Wall. It was completed in 1681, and perhaps twenty years later my ancestor breached it to settle in Liutai, which means “sixth post”—one of the fortified towers that was built expressly to keep out people like him.

An article by Sarah Stillman in this week’s New Yorker describes how, over the past 15 years, the U.S. has adopted tougher measures to keep migrants from crossing illegally into the U.S. from Mexico in spite of the U.S. economy’s continued dependence on more immigrant labor than our government will legally allow to enter. These measures, which include the construction of hundreds of miles of fence, apparently have slowed the rate of illegal crossings. At the same time, they have encouraged the expansion of the human-smuggling business, catalyzed the growth of criminal rackets that extort the families of kidnapped migrants for ransom, and, as in the Mediterranean, contributed to a significant increase in the number of deaths occurring en route.

On the US-Mexico border. Photo by Anthony Suau for TIME.

This impulse is not specific to rich countries. In South Africa, at least seven people have been killed this month in violent attacks on immigrants and their businesses in parts of Durban and Johannesburg. Among the governments publicly condemning these attacks is Nigeria’s. In the early 1980s, the Nigerian government expelled millions of West African migrants from its territory, “blaming them for widespread unemployment and crime” after a slump in oil prices pushed Nigeria’s economy into a downward spiral.

This impulse runs deep. A study published in 1997 found that drivers at a shopping mall left their parking spaces more slowly when another car was waiting near that space than they did when no one was around, even though that delay was costly for both parties. The study’s authors attributed that finding to territorial behavior—”marking or defending a location in order to indicate a presumed right to a particular place.”

This behavior may be instinctual, but that doesn’t mean it’s just. Physical or legal, these walls implicitly assign different values to the lives of the people on either side of them. According to liberalism—and to many other moral philosophies—this gradation of human life is wrong. We should not confuse the accident of our birth on the richer or safer side of those walls with a moral right to exclusively enjoy that relative wealth or safety. The intended and unintended consequences of policy change need to be considered alongside the desired end state, but they should at least be considered. The status quo is shameful.

Some economists also argue that the status quo is unnecessarily costly. In a 2011 paper in the Journal of Economic Perspectives, Michael Clemens estimated that barriers to emigration have a much larger damping effect on the global economy than barriers to capital and trade do.

How large are the economic losses caused by barriers to emigration? Research on this question has been distinguished by its rarity and obscurity, but the few estimates we have should make economists’ jaws hit their desks. When it comes to policies that restrict emigration, there appear to be trillion-dollar bills on the sidewalk.

I hope I live to see that claim tested.

Demography and Democracy Revisited

Last spring on this blog, I used Richard Cincotta’s work on age structure to take another look at the relationship between democracy and “development” (here). In his predictive models of democratization, Rich uses variation in median age as a proxy for a syndrome of socioeconomic changes we sometimes call “modernization” and argues that “a country’s chances for meaningful democracy increase as its population ages.” Rich’s models have produced some unconventional predictions that have turned out well, and if you buy the scientific method, this apparent predictive power implies that the underlying theory holds some water.

Over the weekend, Rich sent me a spreadsheet with his annual estimates of median age for all countries from 1972 to 2015, so I decided to take my own look at the relationship between those estimates and the occurrence of democratic transitions. For the latter, I used a data set I constructed for PITF (here) that covers 1955–2010, giving me a period of observation running from 1972 to 2010. In this initial exploration, I focused specifically on switches from authoritarian rule to democracy, which are observed with a binary variable that covers all country-years where an autocracy was in place on January 1. That variable (rgjtdem) is coded 1 if a democratic regime came into being at some point during that calendar year and 0 otherwise. Between 1972 and 2010, 94 of those switches occurred worldwide. The data set also includes, among other things, a “clock” counting consecutive years of authoritarian rule and an indicator for whether or not the country has ever had a democratic regime before.

To assess the predictive power of median age and compare it to other measures of socioeconomic development, I used the base and caret packages in R to run 10 iterations of five-fold cross-validation on the following series of discrete-time hazard (logistic regression) models:

  • Base model. Any prior democracy (0/1), duration of autocracy (logged), and the product of the two.
  • GDP per capita. Base model plus the Maddison Project’s estimates of GDP per capita in 1990 Geary-Khamis dollars (here), logged.
  • Infant mortality. Base model plus the U.S. Census Bureau’s estimates of deaths under age 1 per 1,000 live births (here), logged.
  • Median age. Base model plus Cincotta’s estimates of median age, untransformed.

The chart below shows density plots and averages of the AUC scores (computed with ‘roc.area’ from the verification package) for each of those models across the 10 iterations of five-fold CV. Contrary to the conventional assumption that GDP per capita is a useful predictor of democratic transitions—How many papers have you read that tossed this measure into the model as a matter of course?—I find that the model with the Maddison Project measure actually makes slightly less accurate predictions than the one with duration and prior democracy alone. More relevant to this post, though, the two demographic measures clearly improve the predictions of democratic transitions relative to the base model, and median age adds a smidgen more predictive signal than infant mortality.

Of course, all of these things—national wealth, infant mortality rates, and age structures—have also been changing pretty steadily in a single direction for decades, so it’s hard to untangle the effects of the covariates from other features of the world system that are also trending over time. To try to address that issue and to check for nonlinearity in the relationship, I used Simon Wood’s mgcv package in R to estimate a semiparametric logistic regression model with smoothing splines for year and median age alongside the indicator of prior democracy and regime duration. Plots of the marginal effects of year and median age estimated from that model are shown below. As the left-hand plot shows, the time effect is really a hump in risk that started in the late 1980s and peaked sharply in the early 1990s; it is not the across-the-board post–Cold War increase that we often see covered in models with a dummy variable for years after 1991. More germane to this post, though, we still see a marginal effect from median age, even when accounting for those generic effects of time. Consistent with Cincotta’s argument and other things being equal, countries with higher median age are more likely to transition to democracy than countries with younger populations.


I read these results as a partial affirmation of modernization theory—not the whole teleological and normative package, but the narrower empirical conjecture about a bundle of socioeconomic transformations that often co-occur and are associated with a higher likelihood of attempting and sustaining democratic government. Statistical studies of this idea (including my own) have produced varied results, but the analysis I’m describing here suggests that some of the null results may stem from the authors’ choice of measures. GDP per capita is actually a poor proxy for modernization; there are a number of ways countries can get richer, and not all of them foster (or are fostered by) the socioeconomic transformations that form the kernel of modernization theory (cf. Equatorial Guinea). By contrast, demographic measures like infant mortality rates and median age are more tightly coupled to those broader changes about which Seymour Martin Lipset originally wrote. And, according to my analysis, those demographic measures are also associated with a country’s propensity for democratic transition.

Shifting to the applied forecasting side, I think these results confirm that median age is a useful addition to models of regime transitions, and it seems capture more information about those propensities than GDP (by a lot) and infant mortality (by a little). Like all slow-changing structural indicators, though, median age is a blunt instrument. Annual forecasts based on it alone would be pretty clunky, and longer-term forecasts would do well to consider other domestic and international forces that also shape (and are shaped by) these changes.

PS. If you aren’t already familiar with modernization theory and want more background, this ungated piece by Sheri Berman for Foreign Affairs is pretty good: “What to Read on Modernization Theory.”

PPS. The code I used for this analysis is now on GitHub, here. It includes a link to the folder on my Google Drive with all of the required data sets.

Two Guys on Bikes Talk International Development

A couple of weeks ago, on the tail end of a lunchtime group bike ride, I complained to the one guy still headed my way—let’s call him Bob, because I didn’t ask him if I could share our conversation—about the lousy state of the roads in our area. We were heading south on Beach Drive through the northern neck of Rock Creek Park in Washington, DC, crunching through fallen leaves and dodging or bouncing off cracks and holes in the asphalt. Like a coarse file, I said. Before winter even starts, he said.

That got us to wondering why the roads weren’t in better shape, and that got us to lamenting the failure of local, state, and national governments to spend more on infrastructure in the past few years, when borrowing was cheap and the economy was dragging. Bob applauded the Obama administration’s first stimulus package but complained that it mostly just dumped money into the economy, a lot of which ended up “going to China.” That remark about China segued into a short but thoughtful complaint about the federal government’s focus on free trade.

I said I didn’t have a problem with freer trade and was actually glad to see living standards improve so much in some of the poorest parts of the world in the last couple of decades. I know there are some losers, I said, but I’m okay with the American middle class getting a little worse off if it means billions of really poor people in other countries are now much better off. After all, they’re all people, right?

I would call Bob a strong liberal, so his response came as a surprise. “I am not okay with that,” he told me. He didn’t say anything about Americans as such, or clang any other patriotic bells. Instead, he said that people he knows personally were having trouble feeding their kids or getting divorced or otherwise struggling in the past several years. I said something like, “Right, but people who were dying before age five are now doing a little better,” I argued. “Nope, still not okay,” he responded.

What started out as a boilerplate cyclists’ lament on road conditions had turned into a debate of sorts on the ethics of international development. As often happens, we’d found our way to a version of the Trolley Problem. Growth is coming down the track, but it will be distributed unevenly, and some people might even get run over. If you could guide that trolley’s path, how should you choose? Proximity? Familiarity? Nationality? At random? Should we worry most about maximizing overall welfare, or should the people close to us count more? On what grounds?

I won’t try to resolve that debate here, and you already know what I think from the anecdote. Instead, I wanted to share the story because it reminded me of something important in the politics of global development. Equality sounds good in the abstract, but we do not sit comfortably with it in practice. Most of us care more about some people than others, and those feelings shape our politics. We can—and, I think, should—aspire to global fairness, but we can also expect to keep tripping over our own feelings when we walk in that direction.

The Ghosts of Wu Chunming’s Past, Present, and Future

On a blogged recommendation from Chris Blattman, I’m now reading Factory Girls. Written by Leslie T. Chang and published in 2008, it’s a non-fiction book about the young migrant women whose labor has stoked the furnaces of China’s economic growth over the past 30 years.

One of the book’s implicit “findings” is that this migration, and the larger socioeconomic transformation of which it is a part, is a difficult but ultimately rewarding process for many. Chang writes (p. 13, emphasis in the original):

Migration is emptying villages of young people. Across the Chinese countryside, those plowing and harvesting in the fields are elderly men and women, charged with running the farm and caring for the younger children who are still in school. Money sent home by migrants is already the biggest source of wealth accumulation in rural China. Yet earning money isn’t the only reason people migrate. In surveys, migrants rank ‘seeing the world,’ ‘developing myself,’ and ‘learning new skills’ as important as increasing their incomes. In many cases, it is not crippling poverty that drives migrants out from home, but idleness. Plots of land are small and easily farmed by parents; nearby towns offer few job opportunities. There was nothing to do at home, so I went out.

That idea fits my priors, and I think there is plenty of system-level evidence to support it. Economic development carries many individual and collective costs, but the available alternatives are generally worse.

Still, as I read, I can’t help but wonder how much the impressions I take away from the book are shaped by selection bias. Like most non-fiction books written for a wide audience, Factory Girls blends reporting on specific cases—here, the experiences of certain women who have made the jump from small towns to big cities in search of paid work—with macro-level data on the systemic trends in which those cases are situated. The cases are carefully carefully and artfully reported, and it’s clear that Chang worked on and cared deeply about this project for many years.

No matter how hard the author tried, though, there’s a hitch in her research design that’s virtually impossible to overcome. Chang can only tell the stories of migrants who shared their stories with her, and these sources are not a random sample of all migrants. Even worse for attempts to generalize from those sources, there may be a correlation between the ability and desire to tell your story to a foreign reporter and the traits that make some migrants more successful than others. We don’t hear from young women who are too ashamed or humble or disinterested to tell their stories to a stranger who wants to share them with the world. We certainly can’t hear from women who have died or been successfully hidden from the reporter’s view for one reason or another. If the few sources who open up to Chang aren’t representative of the pool of young women whose lives she aims to portray, then their stories won’t be, either.

An anecdote from Wu Chunming, one of the two young women on whom the book focuses, stuck in my mind as a metaphor for the selection process that might skew our view of the process Chang means to describe. On pp. 46-47, Chang writes:

Guangdong in 1993 was even more chaotic than it is today. Migrants from the countryside flooded the streets looking for work, sleeping in bus stations and under bridges. The only way to find a job was to knock on factory doors, and Chunming and her friends were turned away from many doors before they were hired at the Guotong toy factory. Ordinary workers there made one hundred yuan a month, or about twelve dollars; to stave off hunger, they bought giant bags of instant noodles and added salt and boiling water. ‘We thought if we ever made two hundred yuan a month,’ Chunming said later, ‘we would be perfectly happy.’

After four months, Chunming jumped to another factory, but left soon after a fellow worker said her cousin knew of better jobs in Shenzhen. Chunming and a few friends traveled there, spent the night under a highway overpass, and met the girl’s cousin the next morning. He brought them to a hair salon and took them upstairs, where a heavily made-up young woman sat on a massage bed waiting for customers. Chunming was terrified at the sight. ‘I was raised very traditionally,’ she said. ‘I thought everyone in that place was bad and wanted me to be a prostitute. I thought that once I went in there, I would turn bad too.’

The girls were told that they should stay and take showers in a communal stall, but Chunming refused. She walked back down the stairs, looked out the front door, and ran, abandoning her friends and the suitcase that contained here money, a government-issued identity card, and a photograph of her mother…

‘Did you ever find out what happened to the friends you left behind in the hair salon?’ I asked.

‘No,’ she said. ‘I don’t know if it was a truly bad place or just a place where you could work as a massage girl if you wanted. But it was frightening that they would not let us leave.’

In that example, we hear Wu’s side of this story and the success that followed. What we don’t hear are the stories of the other young women who didn’t run away that day. Maybe the courage or just impulsiveness Chunming showed in that moment is something that helped her become more successful afterwards, and that also made her more likely to encounter and open up to a reporter.

Chang implicitly flags this issue for us at the end of that excerpt, and she explicitly addresses it in a “conversation” with the author that follows the text in my paperback edition. Still, Chang can’t tell us the versions of the story that she doesn’t hear. In social-scientific jargon, those other young women left behind at the hair salon are the unobserved counterfactuals to the optimistic narrative we get from Chunming. A more literary soul might describe those other girls as the ghosts of Wu Chunming’s past, present, and future. Unlike Dickens’ phantoms, though, these other lives actually happened, and yet we still can’t see them.

In a recent blog post, sociologist Zeynep Tufekci wrote about the relationship between a project’s research design and the inferences we can draw from it:

Research methods, a topic that is seemingly so dry, are the heart and soul of knowledge. Most data supports more than one theory. This does NOT mean all data supports all theories: rather, multiple explanations can fit one set of findings. Choosing the right underlying theory, an iterative process that always builds upon itself, requires thinking hard on how data selection impacts findings, and how presentation of findings lends itself to multiple theories, and how theories fit with existing worldviews, and how better research design can help us distinguish between competing explanation.

A good research project consciously grapples with these.

Like the video Tufekci critiques in her essay, Chang’s book is a research project. Factory Girls is a terrific piece of work and writing, but those of us who read it with an eye toward understanding the wider processes its stories are meant to represent should do so with caution, especially if it confirms our prior beliefs. I hope that economic development is mostly improving the lives of young women and men in China, and there is ample macro-level evidence that it is. The stories Chang relates seem to confirm that view, but a little thinking about selection effects suggests that we should expect them to do that. To really test those beliefs, we would need to trace the life courses of a wider sample of young women. As is often happens in social science, though, the cases most important to testing our mental models are also the hardest to see.

Meanwhile, In the Lives of Hundreds of Millions of Asians…

While our social-media feeds and cable-news crawls were inundating us with news of the latest bombing, beheading, armed clash, plane crash, and viral epidemic, this was happening, too:

Rural wages are rising across much of Asia, and in some cases have accelerated since the mid 2000s. And they are doing so fast (and getting faster)… Doubling in China in the last decade, tripling or quadrupling in Vietnam. A bit slower in Bangladesh, but still up by half. This really matters because landless rural people are bottom of the heap (72% of Asia’s extreme poor are rural—some 687m people in 2008), so what they can pick up from their casual labour is a key determinant of poverty, or the lack of it. Steve argues that if the trend continues (and it looks like it will) this spells ‘the end of mass (extreme) poverty in Asia’.

That quote comes from a recent post by Duncan Green for his From Poverty to Power blog. The emphasis is mine. The Steve referenced in the last line is economist Steve Wiggins, co-author with Sharada Keats of a new report, on rural wages in Asia, from which those findings flow.

The good news from this report doesn’t stop in Asia. As Green also summarizes, higher rural wages in many Asian countries are driving up wages from manufacturing and increasing the costs of food production. Those trends should help tilt comparative advantage in food production and low-wage manufacturing toward Africa and lower-income parts of Asia. As that happens, the prospects for similar transformations occurring in those areas should improve, too.

There is no shortage of catastrophes in the world right now, and climate change runs under the whole thing like a fault line that’s started trembling with peak intensity and consequences still unknown. Meanwhile, though, most people in most parts of the world are quietly going about the business of trying to make their own lives a little bit better. And, apparently, many of them are succeeding. We shouldn’t let the incessant flow of bad news obscure our view of the larger system. This report is yet another indication that, at that level, some important things are still trending positive in spite of all the terrible things we more easily observe.

How Democracy Actually Developed

How did democracy become a good thing? This might sound like a silly question to (most) contemporary American ears, but the coupling of a belief in the propriety of popular sovereignty with an inclusive definition of who qualifies as “the people” didn’t dominate the idea space until pretty recently. In a post on The Junto (here, H/T Adam Elkus), Tom Cutterham offers this explanation:

The story of modern democracy is one in which democracy lost its social and economic content at the very moment it gained political ascendancy.

What happened was the separation of the “economic” and the “political” into separate spheres. It was only under the conditions of this separation that a widely dispersed political power, through the universal suffrage, began to appear possible. Power relations, which had hitherto been fundamentally political issues, of lordship and so on—like who owed what to whom, and who could do what to whom, and who could make whom do what they wanted—were transformed into fundamentally economic issues, having to to do with ownership and contract. So if you want to know why democracy—defined basically as a diffusion of formal political power among the people—went from being bad to good, from being not only impossible but undesirable to not only desirable but possible, one way of answering the question is actually extremely straightforward: the real power wasn’t in politics any more; it was somewhere else, in the newly separate sphere of the economy.

This more jaundiced view of democracy’s ascendancy reminded me of a recent Monkey Cage guest post by Corrine McConnaughy about the path to women’s suffrage in the United States (here). Summarizing evidence from her recent book, McConnaughy argues that the suffrage movement had less influence on the expansion of women’s right to vote than the prevailing narrative implies. Instead,

Women’s voting rights were not a direct response to [suffrage] movement activism.  They were political concessions to the already enfranchised allies of the movement, delivered under partisan duress.

Put the two posts together, and you get a rather different take on American “progress” than the one we encounter in most social-studies curricula. What we call democracy today is not the product of a slow but steady awakening of virtue. Instead, it is the accumulation of many cynical ploys in the endless struggle over wealth and power, and the form that less virtuous process has produced is, in some crucial ways, a hollow one. In their influential 2006 book, Acemoglu and Robinson argued (p. xiii) that

Democracy then arises as a credible commitment to pro-citizen policies (e.g., high taxation) by transferring political power between groups (from the elite to the citizens)… The elite must democratize—create a credible commitment to future majoritarian policies—if it wishes to avoid more radical outcomes.

Cutterham’s and McConnaughy’s posts imply that this isn’t quite right. Expansions of democracy aren’t always motivated by threats of revolution, and they don’t automatically commit societies to majoritarian policies. By working to limit the scope of politics with one hand while conceding some formal political power with the other, incumbent elites and their descendants have often managed to retain a remarkable amount of their wealth and influence in spite of those concessions and the “people power” they supposedly produce.

This other understanding of democratic development will already be familiar to anyone who’s read Sean Wilentz’s The Rise of American Democracy (or, for that matter, watched the last season of Deadwood), but it bears repeating, in part because it helps explain how we got here.

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.”

Today’s China Is Communist and Modern, Not High Modernist

This rebuttal to my recent post on China is a cross-post from Jeremy Wallace’s blog, Science of Politics, with his permission. You can see the original here. Thanks to a shout-out from Marginal Revolution, my post got a lot of views, and I hope Jeremy’s response will get the same. He’s the expert on China, so his argument has me reconsidering my views.

The Chinese government released its long-awaited urbanization plan (国家新型城镇化规划) on 16 March. Ian Johnson, who has written extensively about China’s urbanization for the New York Times, begins his piece on the announcement of the plan in grand terms:

China has announced a sweeping plan to manage the flow of rural residents into cities, promising to promote urbanization but also to solve some of the drastic side effects of this great uprooting.

These descriptions of nondemocratic regime’s releasing “sweeping” plans to reshape their economic geography made Jay Ulfelder think of High Modernism, largely from Jim Scott’sSeeing Like a State. Scott describes significant disasters that have emerged out of failed social engineering projects. Ulfelder quotes from a review of Scott’s excellent book by Cass Sunstein:

Scott does not deny that some designs are well-motivated, and he acknowledges that plans can sometimes do a lot of good. He is concerned to show that when a government, with its “thin simplifications” of complicated systems, fails to understand how human beings organize (and disorganize) themselves, its plans are doomed from the start. Scott calls some governments practitioners of “high modernism,” a recipe for many natural and social disasters, including tyranny… Left to itself, this ideology is overconfident but benign. [High modernism] becomes authoritarian when it is conjoined to “an authoritarian state that is willing and able to use the full weight of its coercive power to bring these high-modernist designs into being.” This is especially dangerous when it is linked to “a prostrate civil society that lacks the capacity to resist these plans.” Thus the greatest calamities in Scott’s book involve a weak society that cannot adapt to a government’s plans.

In some ways, then, the summary of the plan in the NYT looks like a classical example of High Modernism. As Ulfelder writes,

China’s sweeping plans for controlled urbanization strike me as high modernism par excellence. This scheme is arguably the twenty-first century version of agricultural collectivization—the kind of “revolution from above” that Stalin promised, only now the goal is to put people into cities instead of farms, and to harness market forces instead of refuting them. ”We are here on the path to modernity,” the thinking seems to go, “and we want to be there. We are a smart and powerful state, so we will meticulously plan this transformation, and then use our might to induce it.”

Such a characterization leads Ulfelder to two predictions.

If Scott is right about these “certain schemes,” though, then two things are liable to happen. First, China’s new plan for managed urbanization will probably fail on its own terms. It will fail because human planners don’t really understand how these processes work, and even if those planners did understand, they still couldn’t control them. This prediction doesn’t imply that China won’t continue to urbanize, or even that city-dwellers’ quality of life won’t continue to improve on average. It just means that those trends will continue in spite of these grand plans instead of because of them. If the American experience in Afghanistan—or, heck, in its own urban centers—is any guide, we should expect many of the housing developments, schools, and transportation infrastructure born of this plan to go underused and eventually to decay. Or, as an economist might put it, the return on investment will probably be poor.

The second prediction of sorts I take from Scott’s book is that the Chinese Communist Party’s plans for socially engineered urbanization will probably produce a lot of conflict and suffering on their way to failure.

I disagree with the assessment of the plan as high modernism and with the causal mechanisms underlying the predictions that arise from it. It isn’t high modernist because China doesn’t “plan” like it used to and the described policies incrementally adjust the status quo. The predictions themselves are not wrong so much as they are already correct.

First, the nature of planning in China has gradually moved away from the intense micro-managing of the eponymous Planned Economy to something much more akin to policies that shape the incentive structure of local governments and individuals by allocating marginal resources more to one locale rather than another. That is, China governs like a modern state, not a high modern one. Even the words used in plans have changed, as pointed out by Philipp C.C. Huang:

If one looks to the evolution in the Chinese terms for planning, we can see that the words have changed first from jihua 计划 and zhilingxing jihua 指令性计划 or “commandist planning” to zhidaoxing jihua 指导性计划 or “guidance planning,” and, more recently, to abandoning the old term jihua completely in favor of guihua 规划, now the commonly used term for what the new National Development and Reform Commission (国家发展和改革委员会), which replaced the old National Planning Commission (国家计划委员会), undertakes.

This semantic change reflects a real reduction in the Party’s control of the day-to-day operations of the economy. This can be seen in the fact that this document is often described as “long-awaited.” It is long-awaited because it was supposed to be announced last year. As Jamil Anderlini of the FT put it,

The urbanisation plan was originally expected to be published more than a year ago, but deep divisions between government departments and dissatisfaction from Li Keqiang, the Chinese premier, who has been a strong champion of the scheme, delayed the plan’s publication until now.

I would argue that this slowly rolled out plans like this one are less likely to be sweeping than those that emerge out of nowhere. Additionally, this dissatisfaction implies that, unlike in China under Mao, local implementation of the plan is unlikely to be anything but grudging. There is a growing literature on local resistance to implementing central dictates in China (e.g., Margaret Pearson and Mei Ciqi have a nice forthcoming paper in China Journal entitled “Killing the Chicken to Scare the Monkey: Sanctions, Shared Beliefs and Local Defiance in China” that I can’t find online).

Second, the document is not a radical departure from prior policy. Johnson’s statement “the plan [is] the country’s first attempt at broadly coordinating one of the greatest migrations in history” fits awkwardly with a history of policies regulating and restricting migration that have existed since 1950s (I might have just finished writing a book about China’s management of urbanization).

The household registration (hukou) system was established when Soviet-style industrialization was initiated to control that true high modernist policy’s unintended consequences, namely blind flows of farmers into cities looking for work and escaping rural taxation. This system of effective migration restrictions has been tinkered with at the national and subnational level countless times during China’s post-Mao Reform Era (1978–). Over the past ten years, such reforms have been constantly trumpeted but implemented reality rarely measures up to the hype of policy announcement. Yet reforms have certainly taken place; Tom Miller’s great China’s Urban Billion summarizes many recent changes well.

The newly released document describes policies that are broadly similar to what we have seen time after time in recent years: continued “strict control” of population growth in the largest cities and encouragement of development of small and medium-sized cities, particularly in the country’s central and western regions. What is different here is a central commitment to assist local government’s fund the infrastructure of their cities and efforts to contain “land urbanization,” where local governments claim rural land from village collectives, pay farmers a pittance, and sell it at a huge profit to developers. The urbanization of land causes the “forced urbanization” of individuals that Ian Johnson’s reporting decries, so attempts to reduce its prevalence going forward should be welcomed.

Why does this plan sound high modernist then? Because it emanates from a Communist Party-led regime that still tends to use language more appropriate to the grand pronouncements of Marxism. It is a Communist state. The regime retains the power to manage the economy and guides it towards in desired directions but in general refrains from stating desired ends.

As for the predictions coming from classifying China as high modernist, the country already is dealing with serious problems of ghost cities where any return on investment is questionable. It is certainly possible that aiding the development of small and medium cities will turn out being wasteful economically, even if it might be savvy politically. In terms of urban instability and violence, I’m sanguine. I see this plan as continuing in a long line of policies that the regime has put forward to try to avoid urban unrest–incorporating slums, expanding access to urban social services, and slowing down land confiscations–are all reasonable levers for the center to use to tamp down the possibilities of protest in cities.

In the end, the Chinese regime speaks with archaic language–that is indeed, occasionally frightening–but acts like a modern state. Today’s CCP leadership certainly prefers to depoliticize and to quantify, to argue that it is pursuing “development,” “progress,” and “modernization” without giving the Chinese people much of a voice to prevent them from doing so. But so do other modern states. China today is far from the catastrophes of its high modern era, namely the Great Leap Forward. Let us all be thankful that this is so.

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