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.

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 Inequality, Democracy, and Inferential Sand Castles

One of the most important and influential research programs in comparative politics in my professional lifetime depends on data that are, in my view, far too flimsy to support the inferential edifices we keep trying to build with them.

I’m talking about research on the relationship between economic inequality and democracy. This topic is hardly new–Karl Marx had some important things to say about it in the mid-1800s–but interest in the subject was renewed in the early 2000s with the publication of books by comparativist Carles Boix (2003) and economists Daron Acemoglu and James Robinson (2006).  Drawing intellectual inspiration from Marxist political sociology, both books casts politics as, at its roots, a struggle between rich and poor over the distribution (or redistribution) of wealth. The poor want more of it, but they have a hard time getting and staying organized enough to take it from the rich, who can usually use their wealth and power to dispel or repel any challenges. When the poor finally do manage to organize a credible and formidable threat, however, wealthy elites may offer democratic government as a form of compromise, allowing them to concede the redistribution of some wealth without having their assets seized or suffering the costs of a long fight.

Boix and Acemoglu & Robinson identify several factors that contribute to the relevant actors’ strategies, but the one around which a major research program has emerged is economic inequality. According to Boix, democratic transitions are most likely to occur when inequality is low. In Acemoglu & Robinson’s model, democratic transitions are most likely when inequality is either very low or very high. Whichever model we use, though, the implication is that democracy emerges as a strategic concession to pressures on the haves from the have-nots under conditions that are specific enough to test, provided we have the requisite data.

These authors’ theoretical models are explicitly intended to explain hundreds of years’ worth of institutional stability and change in all parts of the world, and their work has inspired many new and interesting research projects in comparative politics. When I started attending academic conferences in the mid-2000s, this topic seemed to be gulping down most of the intellectual oxygen in the field of comparative democratization. Whole panels were devoted to the topic, usually more than one per conference, and I was often told that my statistical analyses which excluded inequality (see here and here for examples) were incomplete. Some of the projects spawned by this burst of activity have produced articles that have appeared in the discipline’s most influential journals, including one in the most recent issue of the American Political Science Review.

Here’s the problem, though: Democratic transitions are rare events. So, to test the broad historical claims these authors make, we need reliable measures of economic inequality from a large number of countries for long periods of time. Coarse measures would suffice if the relevant theories were only concerned with gross and static variations in inequality, but they’re not. These theories are meant to be dynamic, and they posit that modest differences or changes in the degree of inequality can have significant effects.

The measures of economic inequality we actually have, however, are nowhere near that good. To accurately measure economic inequality, we need to observe variation in assets, income, or consumption at the individual or household level. (See this paper for a careful discussion of different ways to measure inequality.) That kind of observation can only happen through well-designed surveys or carefully kept tax records. Everything else is guesstimation, often with very wide confidence intervals. Of course, household-level surveys rarely happen in poor countries, and they hardly happened anywhere until fairly recently in human history. Poor countries also tend to have poor tax records, and even the records in wealthy countries are sometimes suspect.  We also know that some dictatorships simply don’t share this kind of data with the outside world–Cuba and North Korea are still black holes in major cross-national economic data sets–and when they do, the validity of the reported values is often suspect.

These problems are all clearly reflected in the gaps and confidence measures in the leading source of data on this topic, the World Bank’s Measuring Income Inequality Database (a.k.a. Deininger & Squire). Browsing the data in country-year format, it’s easy to see that many countries (e.g., Afghanistan) have few or no observations; countries generally come online as they get richer (e.g., Latin America in the latter half of the 20th century); and where poor countries are included, the data are often marked as unreliable. In one paper on the topic, Christian Houle notes that the Deininger & Squire dataset includes observations for just 10% of all country-years during the period 1950-2001. Ten percent! And that’s just for the most recent half-century. Other scholars have attempted to improve on those data–see here for one prominent effort–but no alchemy can spin reliable measures from thin air.

In short, there’s a systematic relationship between the existence and quality of our observations of inequality and the very outcomes we’re trying to explain. For statistical analysis that’s meant to generate causal inferences, this is the worst kind of problem to have.

Given that problem, it’s hard for me to understand how the field of comparative politics has come to take the results of these studies so seriously. If we want to stick to cases where we have reliable measures of inequality, we have to limit our analysis to recent decades in richer countries, where there’s little or no variation on the dependent variable. What we can’t and never will be able to do with confidence–because no one can go back in time or reconstruct surveys or records that never existed–is a global analysis of the relationship between income inequality and political instability in the 19th and 20th centuries. Maybe the requisite data will become available to study this relationship in poorer societies of the future, but the past is mostly lost to us.

This hasn’t stopped many from trying, but the flimsy data on which those studies are usually based makes me wonder how we’ve come to consider the results to be much more than intriguing curiosities. I understand and agree that this is a really interesting and important question. One of the frustrating things about being a social scientist, though, is that there are often important questions to which we simply can’t provide clear answers. I believe this is one of those questions, and I hope this post has convinced a few of you of that, too.

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