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.”

What a China Corruption Story Says About the Perils of Authoritarian Corruption in the Modern Global Economy

Yesterday, the New York Times dropped a bombshell of investigative journalism on the Chinese Communist Party, reporting that the family of Prime Minister Wen Jiabao has amassed something like $2.7 billion in wealth in recent years, mostly through insider dealings. That a top Party official has profited from his position of authority is hardly surprising—“Man who is shocked at Wen Jiabao family fortune discovered in Chinese village,” the Onion-style China Daily Show headline blared—but the scale of the family’s fortune and the speed of its accumulation is breathtaking.

Unsurprisingly, the Chinese government promptly blocked access to English- and Chinese-language versions of the New York Times web site and mention of the newspaper on Sina Weibo, China’s über-popular micro-blogging service. The article happened to drop in the middle of delicate transition period in China’s political leadership, and what it suggests about the state of that country’s political economy isn’t pretty. As the Times piece dryly noted,

Untangling [the Wen family’s] financial holdings provides an unusually detailed look at how politically connected people have profited from being at the intersection of government and business as state influence and private wealth converge in China’s fast-growing economy.

I’m not a China pro, but I am interested in forces that drive the persistence and collapse of authoritarian regimes. For me, one of the most intriguing aspects of this story is what it suggests about change over time in the difficulty of concealing the patronage and rent-seeking that typically underpin the political economy of authoritarian rule. NYT reporter David Barboza was able to piece together this remarkable picture of the Wen family’s wealth by reviewing corporate and regulatory records in the public domain. I’m sure the trail wasn’t easy to follow, but it was at least possible because the entities involved operate in a global marketplace that demands a certain degree of transparency. These wheelings and dealings are the currency that buys loyalty in many autocracies, but they are rarely laid so bare.

What Barboza’s story underscores for me is the Faustian bargain the Chinese Communist Party has made with the global economy. In exchange for foreign capital and hungry markets and safe harbors for Chinese wealth, China would play by rules that could gradually erode the opacity on which the authority of its political class depends. Among other things, it would produce and file the kinds of records that made the story on the Wen family’s wealth possible.

Importantly, Barboza’s story is not unique. We’ve seen similar stories from other authoritarian regimes in recent years. In May, Radio Free Europe/Radio Liberty’s Khadija Ismayilova described how Azerbaijan’s “first family” had profited handsomely from a $134-million construction project related to the Eurovision contest that country hosted this summer—revelations made possible, in part, because of anti-corruption law Azerbaijan adopted in 2004 to help attract badly needed foreign capital. The 2011 revolution in Tunisia that marked the start of the so-called Arab Spring was apparently sparked, in part, by public furor over U.S. government cables detailing the craven corruption of President Ben Ali’s family—cables that were pushed into the public domain by Wikileaks.

I don’t mean to suggest that globalization and the Internet and all things new and shiny have made it impossible to sustain authoritarian rule. The roster of dictatorships that persist in the face of revelations like these—Azerbaijan, Zimbabwe, and Equatorial Guinea, to name just a few of the most obvious cases—proves otherwise. I do think, however, that these entanglements are marginally increasing pressures on these regimes that can hasten their demise. As Barboza’s story about the Wen family illustrates, this Faustian bargain has worked out quite nicely for many authoritarian elites so far, but Mephistopheles’ powers of concealment do seem to be weakening. And this, among many other things, may help to explain the recent acceleration of the long global trend toward more democratic government.

On the Consequences of Transition Politics for Democratization

In academic work on political development, the term regime transition refers to the period of time between the end of one political regime and the establishment of another. As Guillermo O’Donnell and Philippe Schmitter say on page 6 of their Little Green Book, “It is characteristic of the transition that during it the rules of the political game are not defined. Not only are they in constant flux, but they are usually arduously contested.” Think Tunisia from Ben Ali’s ouster in January 2011 until the convocation of its elected Constituent Assembly in October of that year, or Egypt since Mubarak’s resignation (now 18 months and counting!).

So, we might wonder, does the way that transition unfolds affect the quality and duration of the democracy that ensues? Does it make a difference if, say, this period is characterized by negotiation and compromise instead of tumult and violence? If it’s carefully managed by the remnants of the old regime or driven by outsiders? If democracy is imposed by foreign forces instead of built from within?

According to an interesting paper upon which I recently stumbled—and, I gather, a forthcoming book based on the same research—authors Gary Stradiotto and Sujian Guo conclude the answer to that question is a resounding “yes”:

 The literature offers competing claims among scholars concerning the role the mode of transition plays in influencing post-transitional democracy. The authors reconcile these claims. First, they classify democratic transitions into four transitional modes, and hypothesize that cooperative transitions result in higher levels of democracy that last longer than other transition types. A method to quantitatively test the mode of transition (the independent variable) against democratic quality and longevity (the dependent variables) is developed. The results provide strong confirmation that states that transition through cooperative pacts are associated with higher levels of democracy and a lower risk of reversion compared to other transition types.

The question this paper is trying to answer is a really important one for participants in these transitions, who have to think strategically about how to try to push developments in a particular direction, and for policymakers and activists in other countries, who might wish to influence those trajectories as well.

As careful as the authors are in their analysis, though, and as plausible as their story is, I don’t think their research design succeeds in solving the vexing problems that make it so hard to answer this question with confidence. I’m thinking of two problems in particular.

The first is the problem of confounding factors. The conjecture that modes of transition might have lasting effects on the democracies they produce is rooted in the idea of path dependency, which is just a fancy way of referring to the persistent influence of events or conditions deeper in the past than the moment or period we’re studying. Using this language, the hypothesis Stradiotto and Guo are exploring could be restated as the idea that the survival and quality of democracy after a transition depends, in part, on the form of the politics that occur during the transition process itself.

That statement seems obviously true, and yet it’s devilishly hard to prove. The problem is that transitions don’t occur on blank slates, and the history that preceded the breakdown of the old regime might—really, must—also have some effect on both a) what form the transition takes and b) what happens afterwards. For example, numerous scholars of comparative democratization have argued that the structural features of an authoritarian regime affect the likelihood that the regime will break down, and if it breaks down, that democracy will follow (see here, here, and here). Others emphasize the effects of even deeper forces—things like Jared Diamond’s argument about the persistent influences of climate and geography on political and economic development, or Daron Acemoglu, Simon Johnson, and James Robinson’s claim that institutions imposed at the time of initial colonization have powerfully shaped developmental trajectories right up to the present.

When confounding factors are present, it’s really hard to be sure that the patterns we see are causal and not just coincidental. An analogy might help here. The trajectory of a golf ball, for example, is highly path dependent. Changes in wind speed and direction after the ball is struck will have some effect on where it lands, but, under most conditions, the ball’s flight path is largely predetermined by the way it was struck. If we wanted to explain why balls land where they do, we could analyze the relationship between distinct flight paths–hooks, slices, worm-burners, and such–and landing spots, and we would find a strong association between the two. But, of course, it’s not really the flight path that caused that outcome. Instead, it’s the club selection and swing mechanics that caused that flight path to occur, and it’s the training and experience that caused those swing mechanics and club selection, and so on. If our analysis began the moment the ball left the ground, we would find strong patterns in our data, but we would misunderstand the causes of those patterns.

To look for independent effects of transition modes in the face of this problem, we can’t just pile measures of likely confounding factors into a statistical model and expect to have “controlled” for them. Instead, we have to think more like experimenters. One way to do this is to focus on variation within sets of cases that have similar values on potential confounding factors. Matching before modeling and conditional regression are two ways to do this. Mixed-effects models with cases clustered by likely confounders might work, too, although this could get quite messy if those confounding factors aren’t nested. I suspect the causal-inference pros could suggest many others, and in any case, my point is that, without some more careful structuring of the comparisons, we really can’t tell if variation in the mode of transition is causing variation in outcomes, or if that variation in modes is just symptomatic of deeper differences that would likely have doomed or blessed the ensuing democracy anyway.

The second big problem is selection bias. Stradiotto and Guo limit their study to cases where democracy happened and exclude ones where a transition led to something else. “Excluding cases that never reach a democratic threshold is not problematic,” they argue, “as we are only concerned with understanding how the mode of transition influences the resultant democracy.”

In my view, this isn’t quite right. To fully understand how modes relate to outcomes, we also have to consider transitions that failed to produce democracy. Freek Vermuelen nicely illustrates why in an old post on the Harvard Business Review Blog Network called “Beware the Dangers of Selection Bias”:

Consider, for example, the popular notion that innovation projects require diverse, cross-functional teams. This notion exists because if we analyze some path-breaking innovation projects, we see they were often staffed by such teams. However, it has also been suggested (see for instance the work of Professor Jerker Denrell from Stanford Business School) that diverse, cross-functional teams also often created the biggest failures of all. However, such failures never resulted in any products… Therefore, if we (only) examine the projects which actually resulted in successful innovations, it seems the diverse cross-functional teams did much better. Yet, on average, the homogeneous teams—although not responsible for the few really big inventions—might have done better; always producing a reliable, good set of results.

What Stradiotto and Guo are analyzing is the outcome, conditional on the successful conclusion of the transition. If we’re interested in how the dynamics of the transition process shapes prospects for democratization, though, I think it’s pretty clear that we’ll also want to consider how those dynamics affect whether or not democracy even arises in the first place. Indeed, in an earlier stab at this problem, Gerardo Munck argues that modes of transition have strong effects on both of those stages:

All too often the literature on modes of transition has failed to distinguish between transitions from established regimes and transitions to new regimes and thus reduced the assessment of modes of transition to their impact on the consolidation of democracy. The mode of transition not only affects the consolidation of new regimes but also helps to determine whether the transition is to democracy or some other regime type.

In sum, confounding factors and selection effects make it very hard for us to identify the marginal effects of transition modes on prospects for democratization, and I don’t think Stradiotto and Guo succeed in overcoming these problems in their recent contribution to the literature on this timely question. Perhaps the authors have addressed these issues in their forthcoming book, which I look forward to reading. In the meantime, it’s frustrating that we don’t have much of an answer to this very important question, especially at a moment when so many countries are experiencing these kinds of transitions. Unfortunately, though, I think that’s still where we are.

Economic Growth and the Survival of New Democracies

Last week, a senior official in Egypt’s Muslim Brotherhood warned the U.S. against cutting aid to his country at a time when Egypt is, he suggested, on the brink of economic collapse. In an interview with the Washington Post, Khairat Al-Shater said that reductions in Western aid would exacerbate an economic crisis that could “transform a peaceful revolution into a hunger revolution.”

Al-Shater’s warning reflects a widely held view that new democracies can be made or broken by their economic performance. “It is a cardinal principle of empirical democratic theory,” democratization scholar Larry Diamond writes, “that hard economic times are supposed to mean hard times for democracy.” This principle has been confirmed by a few statistical studies on the survival of democratic regimes: other things being equal, the risk of democratic breakdown does seem to be higher when GDP growth rates are slower. (See here, here, here, and here for affirmative findings and here for a negative one.)

After reading Al-Shater’s warning, I decided to revisit this question with an emphasis on the real-world concerns of the moment. Instead of looking at the entire life course of all democracies, as previous studies generally do, I wondered what economic performance around the time of a democratic transition–like we saw in Tunisia in 2011 and like we might be seeing right now in Egypt and Libya–would tell us about the prospects that a democratic regime will survive well beyond its founding elections. Perhaps these earliest years create impressions and encourage strategies that enable or afflict the ensuing regime during this formative period in ways we can’t see when we lump entire episodes of democracy together.

To test this conjecture, I used a global data set to identify all transitions to democracy that occurred during the period 1955-2008. With that case list in hand, I built a logistic regression model of the relationships between the conditions under which those transitions occurred and the odds that the ensuing regimes would survive for at least five years. (As it happens, surviving for just five years is actually a pretty big deal. Of the 103 transitions to democracy that occurred during that period, only 62 produced regimes that lasted longer.)

From prior research, we know that higher levels of economic development, the absence of political polarization, prior democracy, and the end of the Cold War are all associated with improved prospects for democratic consolidation, so all of those factors were included in the model. To capture the marginal effects of economic performance on prospects for democratic survival–the original point of this exercise–I added measures of annual percent change in GDP per capita for the three years bracketing the transition: the one before, the year of the transition, and the year after. (See the end of the post for more details on the modeling.)

As expected, I found that a new democracy’s survival prospects are indeed better when its economy grows faster around the time of its birth. In contrast to al-Shater’s gloomy prognostication, however, the effects I observed were not large. The marginal effects from GDP growth in the year of the transition are illustrated in the line plot below. As the chart shows, a difference of several percentage points in GDP growth–a large swing in most real-world situations–would produce only a very modest difference in the estimated likelihood of surviving past five years, other things being equal. (I don’t think p-values are as informative as estimates of marginal effects, but for those of you wondering, the p-value in this instance is 0.28; the coefficient is 0.046.) The association with growth on either side of the transition are not captured in that chart, in part because they were even weaker (coefficients of 0.027 and 0.018 and p-values of 0.54 and 0.70, respectively).

We can also see the weakness of this effect in the modest contribution of those growth rates to the statistical model’s ability to accurately assess risk in the historical cases. The figure below plots Receiver Operating Characteristic (ROC) curves for versions of my model with and without the measures of initial GDP growth. ROC curves summarize a model’s ability to discriminate between cases with and without some feature of interest–in this instance, surviving past five years. The better the model does, the farther the line pushes toward the upper left-hand corner, and the larger the area under the curve (AUC). As you can see, adding measures of GDP growth to the model doesn’t improve the accuracy by a whole lot, producing just about a 2% bump in AUC.

On the whole, I’d say these results run counter to the spirit, if not the letter, of prevailing expectations. The marginal effects of economic performance flow in the anticipated direction, but they don’t have anything close to the kind of “make or break” impact that Al-Shater and Diamond’s statements imply. A new democracy’s level of economic development and the occurrence of acute political polarization tell us the most about its survival prospects, and variations in economic performance around the transition don’t seem to move the needle a whole lot beyond that.

I wonder if the prevailing wisdom about the dire consequences of poor economic performance for democratic consolidation isn’t at least in part a case of the availability heuristic at work. Historical cases of economic crisis followed by democratic collapse easily spring to mind (Weimar Germany, anyone?), and it’s not hard to generate a plausible story linking those two events. What those plausible stories seem to overlook, though, is that many of those attempts at democracy probably would have failed anyway, even in the absence of economic crisis, because that’s the fate of most democracies across a wide range of conditions. Meanwhile, there are plenty of countervailing examples of young democracies that survived sharp economic contractions (say, Greece after military rule, or much of post-Communist Europe), but these null cases seem to be more forgettable.

Even if economic growth had a stronger impact on prospects for democratic survival than my analysis indicates it does, I’m skeptical that this information would be as useful to policy-makers seeking to promote democracy as I suspect they think it is. Assume for a moment that a bump of a few percentage points in GDP growth in the transition year would double the odds in favor of democratic survival. Can anyone tell me what policy interventions will reliably pump growth rates that far, that fast? If foreign aid or economic policy could work that kind of magic, wouldn’t the “developing” world already be a lot richer?

I’ll wrap this post up by going back to where we started, namely, the Middle East after the “Arab awakening.” Even though GDP growth doesn’t contribute much to it, the model’s overall performance isn’t bad. After looking at those ROC curves, I wondered what the model would say about the prospects for the survival of new democracies in three Arab countries on the cusp of new tries at democracy: Tunisia, Egypt, and Libya. Of the three, only Tunisia would already qualify as democratic by my definition, but Egypt and Libya are both in the midst of transitions from authoritarian rule that could put them over the threshold soon. So I took the IMF’s latest projections of their growth rates and plugged them into the model, along with recent data on their levels of economic development and my best guess as to whether or not they would qualify as acutely polarized according to the data set I used for that indicator. Here’s what came back as estimates of the  probability that each of those new democracies would make it to their sixth birthday, assuming that, of the three, only Tunisia would not qualify as acutely polarized:

  • Tunisia: 82%
  • Egypt: 48%
  • Libya:  89%

The contrast between Tunisia and Egypt’s survival prospects did not surprise me, but the high estimate for Libya did. Interestingly, expected economic growth seems to be contributing to this result. According to the IMF, Libya’s economy contracted by more than 60% in 2011, but it’s expected to recoup some of those losses in 2012 with an astonishing annual growth rate of nearly 70%. That value is so unusually large that it packs a lot of wallop, even though the weight for GDP growth in the equation is small. Whether that anomalous leap translates into a tremendous boost for democratic consolidation in the real world is another matter. Color me dubious.

Details of the Modeling

The sample for the statistical analysis described here comprises 103 democratic transitions that occurred in countries worldwide during the period 1955-2008.  These transitions were identified using the same data set on episodes of democracy that was summarized in my book. To focus on transitions most like the ones occurring in the Middle East today, cases where new countries were “born” with democratic regimes were excluded from the analysis. I did not use the well-known and widely-used Democracy and Dictatorship Data Set because, as elaborated in this working paper, I have serious concerns about its utility for survival analysis. (That said, I would be very interested to see how sensitive the results reported here are to the choice of measures of democratic transitions and breakdowns. I’d do it myself if this were an academic paper, but, hey, it’s just a blog post.)

Once I’d assembled a roster of relevant cases, I used the ‘glm’ command in R to estimate a logistic regression model that included the covariates listed below (with sources in parentheses). The analysis file includes one record per transition. The dependent variable in this model was a binary one indicating whether or not a democratic episode lasted more than five years beyond its transition year. As noted above, 62 of the 103 cases did.

  • Annual percent change in GDP per capita in years t-1, t, and t+1, where t is the year in which the democratic transition occurred (World Development Indicators)
  • Infant mortality rate, relative to annual global median and logged (U.S. Bureau of the Census)
  • Political polarization (a.k.a. “factionalism,” indicated by a score of 3 on Polity’s PARCOMP variable)
  • Any prior episodes of democracy
  • Post-Cold War period

The ROC curves were created using ROCR.

If you’d like to replicate and tinker with this analysis, please email me to ask for the data set and R script. My address is ulfelder <at> gmail <dot> com.

Update: The code I used for this analysis is now on Github, here. The data set in .csv form can be downloaded from my Google Drive, here.

Why Didn’t Gaddafi Just Retire?

Close on the heels of his capture and apparent execution by Libyan rebels, we are learning that longtime dictator Moammar Gaddafi amassed an astonishing personal fortune over his 40+ years in power. According to a story in today’s Washington Post (emphasis added),

Gaddafi secretly salted away more than $200 billion in bank accounts, real estate and corporate investments around the world before he was killed — about $30,000 for every Libyan citizen and double the amount that Western governments previously had suspected, according to senior Libyan officials…If the values are accurate, Gaddafi will go down in history as one of the most rapacious as well as one of the most bizarre world leaders.

That’s billion with a B, folks. If it’s even close to accurate, that fortune would have made Gaddafi the richest person in the world.

Gaddafi’s mind-boggling wealth poses a puzzle for political scientists who study authoritarian rule. With all that money stuffed under his mattress, why didn’t Gaddafi just walk away early in the course of the rebellion to enjoy a fat retirement? When you’ve already got $200 billion to work with, the marginal benefits of additional accumulation are going to be pretty thin. Instead, Gaddafi chose to stick it out, and look where that decision got him (warning: graphic).

Most theories of authoritarian rule solve this problem by fiat. Rulers are simply assumed to value staying in office over everything else, and at virtually any cost. If we start with that assumption, Gaddafi’s behavior is not puzzling at all–but recently “retired” Tunisian president Ben Ali‘s is. Recall that Ben Ali fled his country just a few weeks after Tunisia’s popular uprising started to gain steam, before it was apparent whether or not the challenge could be sustained. Clearly, retirement is an option for some dictators.

In short, I think we still have a pretty poor understanding of what motivates authoritarian rulers to cling to power (or not). This matters, because the better we understand rulers’ motivations, the better equipped we are as policy-makers or activists to design strategies that might drive those rulers from office and allow for democratization. Among the many things the Arab uprisings of 2011 will give the world, perhaps one of them will be a better grasp of how dictators decide when enough is enough.

PS. On October 23, The New York Times ran this story describing Gaddafi’s last days, based mostly on the account of one member of his inner circle. The story suggests that Gaddafi may have been willing to cede power and trying to flee the country toward the end, but it’s hard to put a lot of stock in the words of one man whose own fate was so closely tied to the colonel’s.

PPS. Over at the Monkey Cage, eminent political scientist Barbara Walter sees Gaddafi’s decision to stick it out as an unfortunate side effect of a strengthened International Criminal Court.

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