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City Size and PoliticalContentionRobert M. Anthony & Edward M. CrenshawPublished online: 29 Jan 2015.

To cite this article: Robert M. Anthony & Edward M. Crenshaw (2014) City Sizeand Political Contention, International Journal of Sociology, 44:4, 7-33, DOI:10.1080/00207659.2014.979689

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International Journal of Sociology, vol. 44, no. 4, Winter 2014–15, pp. 7–33.Copyright # 2014 Taylor & Francis Group, LLCISSN 0020-7659 (print)/ISSN 1557-9336 (online)DOI: 10.1080/00207659.2014.979689

ROBERT M. ANTHONY AND EDWARD M. CRENSHAW

City Size and Political ContentionThe Role of Primate Cities in Democratization

Abstract: In this research we propose an ironic theory of urban concentration,city size, and democratic reform. Authoritarian regimes tend to concentratetheir countries’ populations in primate cities early in development. While thisallows autocratic regimes to easily monitor and suppress most of their coun-tries’ would-be political entrepreneurs and incipient social movement organiza-tions, over time such primate cities can grow very large, concentratinggrievance (in the form of conspicuous inequalities and ascribed identities) inplaces that may also offer unique mobilization resources (e.g., internationalmedia). We propose that large primary cities can become democratic“pressure cookers” for authoritarian regimes, suggesting that a country’s space-economy may be an integral part of the puzzle of democratic transition. Usinginformation from over eighty developing countries, our fixed-effects pooled time-series analyses of city growth, antistate demonstrations, and democratizationgenerally bear out our theory. We conclude that authoritarian rulers do enjoypolitical and economic advantages by encouraging or dictating urban concen-tration, but also that these advantages probably diminish and perhaps reverseover time. As primary cities swell in population, they form global “theaters” thatamplify contention and encourage other social forces that hasten democraticreform, which can hoist authoritarianism “on its own petard.” We offer thisas a somewhat ironic addendum to current macrosocial theories of political con-tention and change.

Robert M. Anthony is an assistant professor of sociology in the Department ofSociology and Geography at Shepherd University in West Virginia. Edward M.Crenshaw is an associate professor of sociology in the Department of Sociology atOhio State University. Address correspondence to Robert M. Anthony, Departmentof Sociology and Geography, Shepherd University, P.O. Box 5000, Shepherdstown,WV 25443; e-mail: rantho02@shepherd.edu.

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Keywords: cross-national, democratization, urban primacy

Democratization, political mobilization, and contention are central topicsof cross-national research in political sociology and political science.Unfortunately, the broad improvements in representative governancethat characterized the period between the 1970s and the early 2000s (i.e.,Huntington’s [1993] “third wave” of democratization) have suffered somenotable reversals in recent years. In particular, Freedom House reports acontinuous five-year decline in political and civil rights, something neverbefore seen since it began reporting in the early 1970s (Freedom House2011). As Figure 1 demonstrates, aggregate improvements in globaldemocratization ended in 2005, although some individual countries madegains during the same period.

While the social scientific community generally assumes that contentiouspolitics (e.g., street protests) contribute to democratization (e.g., Lipset1959), very little cross-national research has been conducted to confirmthe causal connection. The research that exists is mostly case-study–oriented(e.g., Collier 1999) or regional (e.g., Bratton and van de Walle 1997), withonly a few that are truly global in scope (Celestino and Gleditsch 2013;Jenkins and Schock 2004). As Figure 2 suggests, two forms of contention(riots and protests) began to increase just as the “third wave” of democrati-zation began in the early 1970s, then plateaued in the early 1990s and sub-sequently declined until 2005, when a slight increase was detected. This isjust prior to the decline in aggregate Freedom House democracy scores,

Figure 1. Change in Aggregate Democracy Scores

Source: Freedom House, “Freedom in the World,” 2011; available at www.freedomhouse.org/ (accessed October 2009 and May 2011).

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and the pattern continued with the recent uprisings in the Arab world, wherecivil unrest rapidly spread to core urban areas in the region (e.g., Cairo,Tripoli, Tunis, Damascus). These recent developments as well as the sup-posed correlation between political rights and activism pose questions aboutthe mechanisms underlying these events. That is, is there a significantrelationship between activism and democratization, and if so, is it director indirect via some as-yet unspecified mechanisms?

In this article we offer a theory and an empirical assessment of how majorcities link political contention to democratization in the developing world.As we will demonstrate, an improved theory of democratization emergesonce the role that urban systems play in political modernization is more fullyunderstood. In a nutshell, as a country’s labor force shifts from rural tourban living, economic, social, and political relationships between elitesand the masses are dramatically altered (Lerner 1958; Lipset 1959; Moore1966; Rueschemeyer, Stephens, and Stephens 1992; Weber 1909). To betterunderstand these dynamics, we pose four research questions. First, is itindeed the case that authoritarian systems directly shape their nationalspace-economies (i.e., urban systems)? Second, is there a direct link betweenthe structure of a country’s urban system (i.e., urban primacy, city size) andthe frequency of political contention (i.e., antigovernment demonstrations)?Third, does political protest encourage democracy directly or via some

Figure 2. Number of Protests and Riots, 1960 to 2005

Source: Arthur S. Banks, Cross-National Time-Series Data Archive, DatabanksInternational, Jerusalem; available at www.databanks.sitehosting.net.

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intervening mechanism? Fourth, if urban primacy and city size affectpolitical mobilization, and such mobilization in turn encourages democracy,do urban primacy and city size also directly influence democratization,perhaps even interacting to shape political change?

In order to address these questions, we build upon past research thatlinked modern forms of governance (autocracy and democracy) to the struc-ture of a country’s urban hierarchy (i.e., Ades and Glaeser 1995; Davis andHenderson 2003). Although past research did not consider how urban struc-ture might in turn affect political mobilization and political change, thesestudies provide us with important starting points. By revisiting politicalmodernization theory and conflict=class analysis, we develop a richer, moredetailed macrosocial theory of democratization. We contend that urbanprimacy, a form of urban development whereby the primary city becomesfar larger than other cities in the national urban system, generates emergentpolitical realities that provide the social and economic foundations of mobili-zation, contention, and eventually democracy itself. Thus, while authoritarianrulers may promote urban primacy in order to protect their economic andpolitical interests (Ades and Glaeser 1995; Davis and Henderson 2003), thesocial and political realities=opportunities generated by urban primacy andsubsequent changes in city size concentrate political dissent while concomi-tantly providing the resources needed to make that dissent effective in under-mining authoritarian rule. We explain this theory in more detail below.

An Urban Theory of Political Change: Macrosocial Theories ofPolitical Development

Two grand theories have dominated the literature on democratization andthe politics of contention: conflict=class analysis and political modernizationtheory. Conflict or class analysis stresses gross social inequality and classconflict as direct causes of democracy. This approach follows from Marx(and to some extent Weber) and encompasses notable scholarship such asMoore (1966), Skocpol (1979), and Rueschemeyer, Stephens, and Stephens(1992). It views political systems as epiphenomena of economic-basedstratification systems, suggesting that class conflict is the major impetus inbringing about representative government, typically through some combi-nation of violent (e.g., revolutionary) and nonviolent contention instigatedby either working- or middle-class interests. Primary determinants aresocioeconomic inequality, the degree of contention, the repressive policies=practices of states, and external forces such as multinational corporations,international trade agreements, and political hegemons.

Political modernization theory (PMT) is more nuanced. It differs fromthe agent-driven, activist orientation of class analysis by viewing democracyas more structural and emergent, the final product of pluralist (i.e., inter-dependent) social and economic arrangements that ultimately force the

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compromise of representative government on all parties. Specifically, PMTasserts that industrialization entails urbanization, and such concentration ofeconomic and political capital exposes growing segments of national popu-lations to literacy, mass media, and interest groups (Lerner 1958; Lipset[1960] 1981). This model also assumes that gross social inequalities can hin-der democratization, but that stratification and class structure are stronglydetermined by industrialization (Lipset [1960] 1981: 45–53). In other words,PMT is primarily an interest-group formation theory, asserting that higherlevels of socioeconomic development create diverse interest groups thatinclude but are not restricted to social classes. These groups struggle foreconomic and political power, sometimes using violent or quasi-violentmeans. However, as interdependencies (i.e., cross-cutting affiliations) growin response to economic complexity, the use of violence and other extrainsti-tutional means becomes socially costly for both elites and other interestgroups, and gradually this tempers contention and leads to representativepolitics as a kind of compromise (Dahl and Tufte 1973; Lipset 1959). Main-stream political modernization theorists therefore view democracy as anemergent property stemming from the socioeconomic pluralism attendanton social complexity (Dahl 1989).

PMT therefore explains violence and protest that often accompaniesdemocratization as “growing pains” by stressing how economics and politicsinteract. Rapid development creates social disorganization and strains,thereby encouraging grievance and political conflict while offeringcitizens few opportunities to resolve social problems. Political violenceand protest are thus more likely to occur at intermediate levels of develop-ment because such countries have had neither the time nor the resourcesto normalize their economic and political institutions (Davis and Golden1954; Huntington 1968).

In similar fashion, the political side of PMT argues for a curvilinearrelationship between the degree of popular sovereignty and political conten-tion. Many have argued that quasi-authoritarian and partial democraciesare more likely to generate civil unrest (e.g., Auvinen 1997) as well as moreviolent activities (i.e., terrorism), internal armed conflicts, and full-scale civilwar (Hegre et al. 2001; Schock 1996; Robison, Crenshaw, and Jenkins 2006).Such states are semiopen, thereby creating some limited opportunitiesfor dissident mobilization and yet being neither strong nor rich enoughto dissipate moral outrage over political or economic restrictions (e.g.,Tunisia in 2011).

While these macrotheories are essential springboards in investigatingthe link between contention and democracy, both have failed to fullyintegrate the demographic and geographic factors that shape this relationship.Even classical theorists such as Marx and Tocqueville took the geographicconcentration of political contention as a given. Can we imagine a FrenchRevolution without an economically, politically, and socially dominant

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Paris? How can we explain the many oscillations of Thai democracy withoutreference to Bangkok? In this research, we want to begin filling in thegeographic “black box” that lies at the heart of both the political moderni-zation and class conflict models by empirically demonstrating how theprimacy and size of a country’s primary (i.e., largest) city can shape bothpolitical contention and democratization.

As noted above, it has been documented that authoritarian regimes tendto concentrate their populations and economic activities in one very largecity (usually the country’s capital) (Ades and Glaeser 1995; Davis andHenderson 2003). Ades and Glaeser (1995) found that a country’s largestcity was, on average, 45 percent larger for countries with authoritarian polit-ical systems. Further, there is a heritage effect; countries that have a historyof dictatorship prior to 1970 (but that were no longer dictatorships after1985) have main cities that are, on average, 40 percent larger than countriesthat have always been democratic. Ades and Glaeser’s explanation for thesefindings is simple: dictatorships employ policies that concentrate powerand resources into the areas from which they govern in order to improveeconomic performance and bolster social control. This ultimately leads touneven growth in the areas dominated by government functions, typicallycapital cities. Therefore, we predict that:

H1: Ceteris paribus, autocracies are more likely to promote the rapidgrowth of primary cities, which typically occurs via policies that encourageintense urban concentration (the urban bias=primacy effect).

This of course can be related to Lipton’s (1977) urban bias theory, whichproposes that elites in developing countries institute government policiesthat seriously skew development toward major urban areas. Autocraticelites in particular should favor such policies because they allow economicefficiencies of scale and, perhaps more important, easy monitoring andsuppression of their countries’ would-be political entrepreneurs and incipientsocial movement organizations. Over time, such policies concentrate power,wealth, and grievance (i.e., conspicuous inequalities and ascribed identities)in primate or otherwise very large urban areas. While this concentrationserves the purposes of authoritarian leaders for a time, ultimately it will offerpolitical contenders a unique, concentrated blend of opportunities andresources that facilitate meaningful challenges to the status quo (e.g.,a rapidly growing civil society, superior mobilization potential, the presenceof both the international media and nongovernmental organizations, prox-imity to elites). Therefore, large primary cities have the potential to become“ticking time bombs” for authoritarian regimes. We propose that thegeography of a country’s modern economy, which is reflected in thedistribution of its urban population, is a crucial and ironic part of the puzzlethat explains why authoritarianism yields to democracy over time. Whileother economic and cultural factors are clearly important, our theory

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suggests that a better understanding of democratization requires closerattention to a country’s urban dynamics.

Although Ades and Glaeser (1995) do not favor the idea that urban con-centration “causes” political change, they never put it to the test. Logically,however, there are strong reasons to expect urban primacy and subsequentconcentrated population growth to shape political change. After all,authoritarian regimes can neither appease nor oppress their populationsindefinitely, and such massive population redistribution is sure to haveunforeseen economic and political consequences that resist the control ofpolitical elites (e.g., Owen and Witton [1973] found that urban primacy innewly industrializing countries is associated with higher rates of domesticconflict). Thus, while many scholars have indicted both primacy and author-itarianism as impediments to social and political progress, the irony is thatboth may be important stepping-stones to participatory government.

Large Primary Cities as Political Theaters

Causal mechanisms that link urban primacy and city size to political unrestcan be divided into those explained by a grievance model (e.g., Gurr andMoore 1997) and those explained by resources that facilitate politicalmobilization (Jenkins 1983; McAdam 1982). As depicted in Figure 3,primate cities accentuate both real and perceived inequalities, the formervia industrialization and the latter via the spatial proximity of social classes.It has long been known that relative deprivation is more strongly linked togrievance than absolute deprivation (Blau and Blau 1982), and such relativedeprivations will be far more conspicuous within cities where the rich and

Figure 3. Conceptual Model of the Interplay Between Authoritarian Rule,Urbanization, and Democratization

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poor live cheek by jowl. In addition, large primate cities are giant economicengines for their national economies (Kasarda and Crenshaw 1991), and thegeneration of industrial and service occupations creates the social classesthat dominate both PMT’s and the conflict model’s explanation for demo-cratic reform. Many of these new occupational structures force populationsto become literate and politically aware, and as the higher productivity ofmodern economies pulls large segments of the labor force out of poverty,the resultant surplus of time and energy combines with literacy and self-interest to encourage political activism. Finally, primate cities generally drawtheir populations from ethnically (and sometimes religiously) diverse hinter-lands (e.g., Dahl and Tufte 1973). As these diverse groups settle in large cities,their “identities” may harden as invidious distinctions become a matter ofeveryday social life. Indeed, as suggested by social identity=categorizationtheory (Turner et al. 1987), ascribed identities may not even becomepolitically salient in national politics until large-scale urban living createsconspicuous “others” via residential proximity.

Just as importantly, although primate cities offer social resources thatresemble those of any large city, these resources are enormously magnifiedin social importance by the political centrality of such places. The proximity,complexity, and rapid communications offered by large cities make politicalactivism far more likely since dissidents gain greater anonymity as city sizeincreases (Dahl and Tufte 1973). “Urbanism” (i.e., the “modern mindset”that goes with role segmentation and heterogeneity) replaces traditionalsocial psychology fairly quickly in very large cities, one hallmark of whichis belief in political efficacy (as opposed to fatalism) (Inkeles and Smith1974; Lerner 1958). Civil society gradually replaces familialism as family sizefalls, landownership plays a decreasing role in political life, and people areforced to depend increasingly on neighbors and other nonkin to earnand protect social status and wealth. More importantly, very large citiesgenerate local media and attract international media attention, especiallyin a country’s largest (primary) city. These dynamics transform large citiesinto political and social arenas=theaters. Indeed, it has been demonstratedthat very large cities (or “world” cities) by their very nature force whole coun-tries into a global connectivity via telecommunications quite independentlyof their respective levels of development (Crenshaw and Robison 2006).This of course means that states with large cities increasingly come underthe scrutiny of a transnational=supranational “world polity” (Meyer et al.1997). This may create forms of interdependence that force authoritarianand semiauthoritarian governments to attend to the “world’s good opinion”(Keohane 1984). Naturally, such states are most vulnerable to embarrassingconflicts or unrest in their large, primate cities, which may discourage the useof violence to accomplish political repression. This is particularly true, asother organs of local and global civil society begin to converge in a country’sprimary city. Once centrally located, dissidents are naturally drawn to large

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cities where telecommunications, political connections, and material resourcesallow them to operate more efficiently and effectively. It is likely that only themost totalitarian of states avoid the emergence of such dynamics, especiallywhen the primary city is a primate city as well. Following this logic, our initialhypothesis concerning the relationship between urban primacy and politicalmobilization can be stated as follows:

H2: Ceteris paribus, urban primacy promotes political mobilization viathe concentration of national economic and political life (the concen-tration effect).

H3: Ceteris paribus, the size of a country’s primary (i.e., largest) citypositively influences political mobilization via the agglomerationof resources and grievances (the agglomeration effect) as well as theweakening of state repressive power (the global witness effect).

Autocratic Cycles and Democratic Ratchets

Authoritarian and semiauthoritarian systems, by concentrating theirpopulations for command and control purposes, may thus sow the seedsof their own demise. The concentration of grievances and opportunitiesset the stage for effective political mobilization and, in lieu of bargainingand compromise, political contention. For a time, this demographic centra-lization works to maintain authoritarianism: modernization continuesapace, dissent is effectively suppressed, and political centralization is rein-forced by the primate city’s strong gravity. Ultimately, however, the urbancenter generates so much grievance and so many political opportunitiesand mobilization resources that dictatorial governments are forced to either(1) yield to protests and bargain with nascent civil society or (2) use bruteforce to suppress dissent (see Figure 3).

In such cities, with small to medium-size populations, dissents should beeasily suppressed; population size and diversity are still manageable at thispoint, and so economic success helps reduce grievances. Under this scenario,a society may become “stuck” in an autocratic cycle, with any contentionsimply reinforcing the status quo. Yet as both primacy and city size increase,a much larger, more urbane city becomes increasingly connected to globalsociety. Grievances connected to urban disamenities, inequalities, andascribed identities become politicized, and opportunities provided by theincreased media presence and international pressures=resources makepolitical mobilization safer and more effective by tying the hands of therepressive elements of the state (e.g., the recent riots and protests againstthe authoritarian regimes of Tunisia and Egypt, both of which played outin the primate capitals of Tunis and Cairo). Thus, while urban primacymay help autocrats retain power at smaller city sizes, the benefits ofurban primacy should weaken and gradually work against the interests ofauthoritarian rulers as city populations rise.

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H4: Ceteris paribus, urban primacy should be negatively related todemocracy, an effect that should attenuate as a city’s population rises(the critical mass effect).

In addition to the above, we should also expect political protest thatoccurs in very large cities to have an enhanced effect on democratization(i.e., city size and protest interact to boost democratic pressures). Thisis because protests and general civil strife are far more likely to beobserved if they occur on the “world stage;” in this case, a large primatecapital city. Thus, any democratic outcomes owing to protest activityshould be amplified in countries with very large primary cities becausesalient protest is far and away more likely to elicit reaction from the“world polity” and “global civil society,” thereby constraining elitesand forcing compromise.

H5: Ceteris paribus, antistate demonstrations contribute to democrati-zation, and this relationship between protest and democracy growsstronger as the size of a country’s largest (primary) cities increase(the world polity effect).

Methods, Data, and Measures

Statistical Methodology

We analyze data for eighty-five developing countries between 1960 and2005.1 When modeling urban primacy and democratization, we use ordinaryleast squares (OLS) with panel-corrected standard errors (PCSE) with coun-try fixed-effects. OLS with PCSE produces less-biased standard errorscaused by panel heteroskedasticity and contemporaneous correlation, twoproblems that are known to plague time-series cross-section (TSCS) dataanalyses (Beck and Katz 1995, 1996, 2004). We lead our dependent variableby one year, and we control for autocorrelation by assuming that theresiduals exhibit panel-specific autocorrelation.2

In order to model antigovernment demonstrations, we use zero-inflatednegative binomial regression. This methodological choice follows from thefact that our protest variable is an event count. Count data are typicallyunsuited to standard OLS regression and are better examined using anevent-count technique. We use negative binomial regression, which modifiesPoisson regression by correcting for overdispersion in the data (Cameronand Tivendi 1998; Land, McCall, and Nagin 1996). Overdispersion isa common condition that occurs when the variance of the count is greaterthan its mean. Negative binomial regression controls for this by addinga stochastic component to the model (Land, McCall, and Nagin 1996).

Moreover, given that antistate protests are generally rare events (75percent of the country-years in our sample experience no event, see Banks

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[2009]), this variable contains excessive zeros (i.e., nonevents) that areprobably driven by causes different from those driving single or multipleevents. To correct for possible bias in our estimates, we use a zero-inflatedcount model technique that provides a way to model the excessive zeros(Greene 2000; Lambert 1992). Zero-inflation techniques allow us to performa logit regression for cases that have zero events while simultaneouslyrunning a negative binomial regression for case-years that do reportprotests. The zero-inflation logit effectively cleanses the negative binomialregressions of the influence of zero-driving factors, thus making for moreaccurate estimation as well as identifying factors that drive nonevents.

There is another important reason for using zero-inflation techniques in theinvestigation of protests. Essentially, our counts have been derived from newsstories. As Drakos and Gofas (2006) and others have noted, news reportageis selective about events that are reported. Many factors enter into newsselection, such as “newsworthiness,” the number of current events, andlocal=regional bias. More fundamental than any of these considerations, how-ever, are political and civil liberties (e.g., press freedom). Our data for protests(detailed below) were derived from media sources, and it is thus logical toassume that countries with fewer civil liberties might report “zero” events,even when they actually occurred, and particularly if those events were of anantistate nature (i.e., suppression-worthy). Just as importantly, populationsize should matter for event counts of any kind. Thus, it might be reasonableto assume that very small countries do not generate as many protest eventsas large ones, and even when they do, the global media might take no notice.

Urban Population and Urban Primacy

The UN’sWorld Urbanization Prospects: The 2009 Revision provides measuresfor each country’s largest city=urban agglomeration and total urbanpopulation that were logged. The urban primacy measure we use is based onEl-Shakhs’s (1972) urban primacy index. This index calculates the “averageratio of the differences in population size between [the largest city] and eachsmaller city” within the urban system. We used the first five elements (i.e.,cities) to calculate the measure.3 Thus, the index uses the same informationas 1–4 urban primacy ratio (the largest city divided by the sum of the next fourlargest). However, unlike the 1–4 ratio, El Shakhs’s measure takes the sizeof the largest urban area in the system as a point of reference, thus allowingfor greater insight into the degree of balance within the city system.

Antistate Protest=Demonstrations

We measure antigovernmental protests using Arthur Banks’s Cross-NationalTime-Series Data Archive. The variable is operationalized as “any peaceful

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public gathering of at least 100 people for the primary purpose of displayingor voicing their opposition to government policies or authority, excludingdemonstrations of a distinctly anti-foreign nature” (Banks 2009) and isderived from multiple publicly available news sources from around theglobe. In terms of evaluating our thesis that certain urban configurationsindirectly contribute to political reforms over time, this variable offersa more exact estimate since the variable excludes protests against foreignstates, corporations, and other institutions that may not be linked to thedomestic government.4

Political Systems

Measuring change within political systems, and in particular demo-cratization, has been somewhat controversial. Various studies have useddifferent proxies in an attempt to capture “democracy” (e.g., Alvarezet al. 1996; Arat 1988; Bollen 1979, 1980; Bowman, Lehoucq, andMahoney 2005; Cheibub, Gandhi, and Vreeland 2010; Cutright 1963;Jackman 1973; Lipset 1959; Neubauer 1967; Przeworski 2000; Treierand Jackman 2008). According to Munck and Verkuilen (2002), a majorityof measures are highly correlated due to a reliance on common datasources (e.g., Arthur Banks), and all fail in some way to conceptualize,estimate, and aggregate the concept of democracy and=or autocracy intoa scale.

Despite the recent criticisms of the Polity database (e.g., Bowman,Lehoucq, and Mahoney 2005; Cheibub, Gandhi, and Vreeland, 2010; Treierand Jackman 2008), we use the revised combined polity score as a dependentvariable in Table 4 since it provides us with a way to model “movement”to and away from democracy=autocracy, which is more inline with ourtheoretical statements than is predicting transition to or from democracy.The revised combined polity score is a measure that estimates degreesof democracy and autocracy (see Marshall, Gurr, and Jaggers [2009], PolityIV Project Dataset Users’ Manual for complete details on this index andits components). This measure ranges from �10 (most autocratic) to þ10(most democratic); we add a constant so that our variable runs from 0 to21. For the revised combined polity score, cases of interregnum=anarchy(originally coded �77) and cases of transition (originally coded �88) areinterpolated (where possible), while periods of foreign interruption (orig-inally coded �66) are removed.

Our measure of autocracy also comes from the Polity IV index. It codesall cases of democracy, years of anarchy, cases of transition, and foreigninterruptions as zero, but retains the negative ten-point scale for degree ofautocracy. Thus, 10 equates to the most autocratic countries, with 1 beingthe least, and 0 being not autocratic. A complete description of the variablecan be found in Marshal, Gurr, and Jaggers (2009: 14).

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Other Measures

To measure the level of economic development, we use data on real grossdomestic product per capita (RGDP=c) in constant prices (chain index)from the Penn World Tables 6.3 (PWT). World Development Indicators(2009) provides the percentage of GDP attributed to trade (imports plusexports), the percentage of GDP consumed by government, age dependency(i.e., working-age population as a percentage of the population), and (thelog of) total population. For our measure of university students per capitain Tables 3 and 4, we use the Cross-National Time-Series Data Archive(Banks [2009]—note that the statistics reported for this variable are in theoriginal database metric, which we multiplied by 1,000). For easy reference,Table 1 provides a summary of the simple statistics of all measures used inour analyses as well as their sources.

Results

Table 2 displays the tests of our first hypothesis—that autocratic govern-ments encourage the rapid growth of their countries’ largest cities, and thatthis typically results from urban primacy (the primacy=urban bias effect).Model 1 reports the results of a straightforward demographic model (netof country fixed-effects). As one might suspect, large populations tend toproduce very large primary cities (b¼ .922, p� .01). Moreover, the greaterthe number of potential rural-to-urban migrants in a country, the largerthe primary city tends to grow (i.e., age dependency=working-agepopulation is positively related to primary city size, b¼ .0038,� .01). Thematuration of the urban system also matters; as a country becomes increas-ingly urban, urban population growth is more evenly spread between thevarious cities in the space-economy. This explains why, when the proportionof the population living in cities reaches about 70 percent, the relationshipbetween urbanization and the size of the primary city begins to abate (hence,our fitting of the quadratic for percent urban).

These demographic effects persist once economic variables are entered inModel 2. Our initial economic model demonstrates a weak curvilinear influ-ence of real gross domestic product per capita on primary city size, althoughthe effect drops to statistical nonsignificance in later models. Likewise, tradeas a percentage of GDP has little to no impact on primary city size, althoughsome research links urban primacy to international trade (Armstrong andMcGee 1985). We conclude that demographic effects dominate economicforces in the process of primary city growth.

Turning to the political variables that constitute the tests of our hypo-thesis, Model 3 demonstrates that, while government spending apparentlyplays no role in primary city size, autocracy is positively and significantlyrelated to size (b¼ .001, p< .05). Per annum and on average, every

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additional unit of autocracy (ranging from 0 to 10) increases the size ofa country’s primary city by about a tenth of 1 percent. Given that the aver-age primary city size in our sample is about 1.5 million people, this suggeststhat a unit increase in autocracy adds an annual average of about 1,500people. While apparently a small effect, the maximal effect (multiplied byforty-five years and up to a factor of ten) can be quite substantial—a uniquely political influence that can add many thousands of peopleto a typical primary city.

Regardless, Model 4 supports our first hypothesis—the influence of auto-cracy on primary city population is mediated by urban primacy. A robusteffect of urban primacy replaces autocracy, which suggests primacy as anintervening variable. Model 5 demonstrates that urban policies and

Table 1

Sample Statistics by Source

Source and variable N Mean Std. dev. Min Max

Polity IV (2011)

Polity IV Score 2,826 8.7187 6.7919 0 20

Autocracy 2,826 4.1943 3.4394 0 10

World Development Indicators (2009)

RGDP/C 2,826 8.0763 0.9268 6.2059 11.4908

RGDP/C Squared 2,826 66.0852 15.5056 38.5133 132.0388

Trade (% of GDP) 2,826 58.0866 31.2821 5.3142 220.4068

Age Dependency Ratio 2,826 81.7271 16.0752 26.0911 112.7530

Government Consumption (logged) 2,826 2.5524 0.4247 1.0904 4.2419

Penn World Tables (v6.3)

Total Population (logged) 2,826 9.3969 1.3684 5.9696 14.0827

Cross-National Time Series (Banks 2009)

Antigovernment Demonstrations 2,826 0.6476 1.7038 0 26

Antigovernment DemonstrationsSquared 2,826 3.3213 21.4002 0 676

University Students per Capita 2,826 91.5449 105.2441 0 653

WUP (2009)

Largest City Population (logged) 2,826 14.1267 1.1681 9.0094 16.7814

Percent Urban 2,826 43.2 22.0 4.8 98.3

Percent Urban Squared 2,826 2351.4 2192.5 23.0 9662.9

Anthony (2014a & 2014b)

Primacy Index 2,826 0.8044 0.1370 0.2221 0.9797

Primacy Index Squared 2,826 0.6658 0.1930 0.0493 0.9598

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Tab

le2

PooledTim

e-SeriesReg

ress

ions(P

CSE)oftheLogofPrimaryCitySizeReg

ress

edonSelec

tedVariables,

1960

–20

05(Fixed

-Effec

tsModels)

Mod

el1

Mod

el2

Mod

el3

Mod

el4

Mod

el5

Logof

Total

Pop

ulation

0.92

2���

0.92

8���

0.92

9���

0.91

3���

0.91

3���

(0.022

8)(0.021

0)(0.020

1)(0.018

2)(0.018

2)

Age

Dep

ende

ncy

0.00

381�

��0.00

379�

��0.00

387�

��0.00

198�

��0.00

195�

��

(0.000

441)

(0.000

438)

(0.000

414)

(0.000

327)

(0.000

321)

Perce

ntUrban

0.07

15��

�0.07

16��

�0.07

13��

�0.06

21��

�0.06

21��

�

(0.002

47)

(0.002

30)

(0.002

13)

(0.001

87)

(0.001

81)

Perce

ntUrban

Squ

ared

�0.000

458�

���0

.000

455�

���0

.000

454�

���0

.000

389�

���0

.000

387�

��

(1.72e

�05)

(1.63e

�05)

(1.39e

�05)

(1.47e

�05)

(1.38e

�05)

Logof

RGDP=c

0.12

3�0.11

00.07

720.07

53

(0.065

8)(0.067

1)(0.061

5)(0.061

2)

Logof

RGDP=cSqu

ared

�0.008

47��

�0.007

89�

�0.005

75�0

.005

78

(0.004

08)

(0.004

15)

(0.003

75)

(0.003

74)

Trade

as%

ofGDP

1.42

e�05

3.94

e�06

�7.40e

�06

�1.52e

�05

(7.17e

�05)

(7.24e

�05)

(6.05e

�05)

(6.00e

�05)

Logof

Gov

ernm

ent

Con

sumption

6.79

e�06

�0.004

37�0

.085

3��

(0.004

32)

(0.003

90)

(0.038

0)

(Con

tinu

ed)

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Tab

le2

Continued

Mod

el1

Mod

el2

Mod

el3

Mod

el4

Mod

el5

Autoc

racy

0.00

0994

��0.00

0411

0.00

0385

(0.000

443)

(0.000

402)

(0.000

406)

Urban

Prim

acy

2.23

2���

1.98

5���

(0.145

)(0.147

)

Urban

Prim

acy�Gov

ernm

ent

Con

sumption

0.09

92��

(0.045

3)

Con

stan

t2.59

0���

2.08

2���

2.13

6���

1.08

8���

1.31

0���

(0.176

)(0.309

)(0.315

)(0.318

)(0.299

)

Cou

ntry-yea

rs2,74

72,74

72,74

72,74

72,74

7

R2

0.99

970.99

980.99

980.99

980.99

98

Num

berof

coun

tries

8585

8585

85

Note:

Stan

dard

errors

inpa

rentheses.

��� p

<.01;

��p<.05;

� p<.10.

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concentration interact to boost primary city size, as we anticipated; themultiplicative term combining primacy and government spending is positiveand statistically significant (b¼ .099, p� .05), suggesting that higher govern-ment spending boosts the impact of urban primacy on primary city size.We conclude from this that our first hypothesis is supported: autocraticpolitical systems are somewhat more likely to select policies and practicesthat lead to urban primacy, and primacy in turn accelerates the populationgrowth of primary cities. A definitive urban bias effect, particularly on thepart of nondemocratic regimes, is discernible in the data, confirming Adesand Glaeser’s (1995) findings.

In Table 3 we report our tests of Hypotheses 3 and 4—both urbanprimacy and the size of primary cities offer social movements, domesticand international civil society, and other local and transnational actorssocial contexts that may be ripe for mobilization (i.e., the concentrationeffect) while also providing a kind of “global stage” upon which to leveragesocial change (i.e., the global witness effect). To reiterate, given that ourprotest measure is a count variable generated by the vagaries of inter-national media reportage, we use zero-inflated negative binomial regressionto predict antistate protests. As can be seen in all the inflate models ofTable 3, the larger and more democratic a country is, the less likely thata “0” has been reported for antigovernment demonstrations=protests ina given country-year, primarily because large countries and protests withincountries that allow a modicum of civil liberties are much less likely to bemissed or ignored by the international media (and thus by data clearing-houses). Controlling for this potential bias in media coverage necessarilyimproves the precision of our more substantive findings (i.e., the negativebinomial models).

Model 6 of Table 3 reports the results of our theoretically relevant vari-ables on antistate protests. We see evidence for both hypotheses in Model 6,although the primacy effect turns out to be curvilinear. The second-degreepolynomial for urban primacy suggests that, when El-Shakhs’s (1972) urbanprimacy index reaches .76 (at around the thirtieth percentile in this sample),primacy’s negative influence on protests begins to abate; thereafter, therelationship attenuates until it actually turns positive. Apparently, urbanprimacy does serve to “hold the lid on” social protest for much of its range,but ultimately, intense urban primacy promotes rather than prevents anti-state protest, in keeping with our second hypothesis (and confirming Owenand Witton 1973). The effect of the log of primary city size (Log of LargestCity) is more straightforward: the larger that city, the more antistate pro-tests. To interpret the coefficient, every additional log of primary city sizeadds approximately .5 additional protests per annum. The range of the pro-test variable belies the apparent smallness of the effect. The mean for protestis .64 in this sample (and the median is 0), so adding an additionalprotest every two years as city size rises is actually a very powerful effect.

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Table 3

Zero-Inflated Negative Binomial Regressions of AntigovernmentDemonstrations (Banks), 1960–2005

Model 6 Model 7 Model 8 Model 9

Urban Primacy �7.891�� �8.135�� �7.707�� �10.00���

(3.231) (3.166) (3.310) (2.910)

Urban Primacy Squared 5.189�� 5.348�� 4.986� 4.979��

(2.537) (2.459) (2.604) (2.320)

Log of Largest City 0.492��� 0.336��� 0.304��� 1.140���

(0.0881) (0.0786) (0.0873) (0.365)

Autocracy 0.0174 �0.787�� �0.661�� �0.783���

(0.0239) (0.306) (0.302) (0.267)

Log of Largest City�Autocracy 0.0538��� 0.0457�� 0.0547���

(0.0205) (0.0201) (0.0177)

Log of RGDP=c 1.589 4.887���

(2.158) (1.767)

Log of RGDP=c Squared �0.0851 �0.292���

(0.134) (0.109)

Trade as % of GDP �0.00133 �1.23e�05

(0.00264) (0.00268)

Age Dependency �0.000165

(0.00729)

Percent Urban �0.0806��

(0.0318)

Percent Urban Squared 0.000626���

(0.000240)

Log of Total Population �0.737��

(0.302)

Constant �4.380��� �1.903 �8.753 �22.80���

(1.625) (1.606) (9.086) (7.264)

Inflate

Log of Total Population �0.584��� �0.410��� �0.454��� �0.421���

(0.189) (0.133) (0.167) (0.131)

Polity IV Score �0.192��� �0.132��� �0.138��� �0.124���

(0.0502) (0.0347) (0.0494) (0.0363)

Constant 6.311��� 4.466��� 4.872��� 4.612���

(1.702) (1.311) (1.631) (1.259)

(Continued )

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And while our control for autocracy in this model fails to attain statisticalsignificance, the interaction term between city size and autocracy in Model7 suggests something interesting: autocracy might significantly decreaseprotest (via repression, we assume) were it not for very large cities. Indeed,the log of primary city size has to reach about 14 (around the mean of thevariable) before autocracy begins to promote protest. We conclude thatboth the concentration effect and the global witness effect (H2 and H3) findbroad support in these initial models.

Models 8 and 9 of Table 3 add economic and demographic controlvariables to see if our initial findings are robust. Model 9 (the morecomprehensive of the two) suggests that the level of development is alsoimportant to protest, and is in fact curvilinear as the modernization modelsuggests (cf. Davis and Golden 1954; Huntington 1968). Also, there isan urban maturation effect: the second-order polynomial for urbanizationsuggests that when city living reaches about 66 percent of the population,urbanization gradually begins to promote protest, probably owing to thesuperior mobilization potential of general urban living (again, in keepingwith modernization theory). Finally, controlling for everything else(most notably urbanization), larger populations experience fewer antistateprotests (b¼�.737, b� .01).

We investigate the determinants of representative government (i.e., thePolity Index) in Table 4, with special emphasis on how urban primacyand the size of the primary city interact with one another and with antistateprotest to influence democratization. In Model 10 we see that, net of fixedeffects, primacy first encourages democracy and then apparently impedes it,although it must be kept in mind that this is net of primary city size andantistate demonstrations. The second-order polynomial suggests that urbansystems above .32 on El-Shakhs’s index strongly discourage representativegovernment (in keeping with authoritarian logic). Nonetheless, as those

Table 3 Continued

Model 6 Model 7 Model 8 Model 9

Test statistics

Log of Alpha 0.670��� 0.528�� 0.548�� 0.402

(0.222) (0.267) (0.278) (0.267)

Alpha 1.954 1.695 1.73 1.495

Number of nonzeros 712 712 712 712

Number of zeros 2,113 2,113 2,113 2,113

Country-years 2,825 2,825 2,825 2,825

Note: Robust standard errors in parentheses.���p< .01; ��p< .05; �p< .10.

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Table 4

Pooled Time-Series Regressions (PCSE) of Political Democratization (Polity IV)on Selected Variables, 1960–2005 (Fixed-Effects Models)

Model 10 Model 11 Model 12 Model 13

Urban Primacy 28.58��� 22.96�� �42.81��� 17.41��

(10.56) (9.554) (11.31) (8.016)

Urban Primacy Squared �44.83��� �24.94��� �20.30��

(9.730) (9.329) (8.267)

Log of Largest City 4.761��� 0.177 �2.697�� 0.256

(0.423) (1.204) (1.166) (1.117)

Demonstrations �0.0781� �0.0808�� �0.0816� �0.849��

(0.0413) (0.0410) (0.0421) (0.395)

Demonstrations Squared 0.00527�� 0.00537��� 0.00509��

(0.00206) (0.00205) (0.00213)

Log of Total Population 4.844��� 4.009��� 3.926���

(1.701) (1.392) (1.395)

Age Dependency �0.0451�� �0.0266 �0.0243

(0.0190) (0.0198) (0.0197)

Percent Urban 0.0903 0.129��� 0.117��

(0.0549) (0.0465) (0.0469)

Log of RGDP=c �5.272� �6.561��

(3.067) (3.054)

Log of RGDP=c Squared 0.242 0.323�

(0.180) (0.178)

Trade % of GDP 0.0121��� 0.0116���

(0.00439) (0.00434)

University Students=c 0.00624� 0.00522

(0.00346) (0.00339)

Urban Primacy� Log of Largest City 3.150���

(0.806)

Log of Largest City�Demonstrations 0.0546��

(0.0263)

Constant �59.48��� �49.93��� 22.78 �12.30

(6.621) (10.35) (15.75) (14.98)

Number of country-years 2,740 2,740 2,740 2,740

R2 0.473 0.461 0.490 0.456

Number of countries 85 85 85 85

Note: Standard errors in parentheses.�p< .10; ��p< .05; ���p< .01.

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primate cities grow in size, intense urban concentration gradually creates theconditions for successful democratization; the coefficient for the logof primary city size is 4.76 (p� .001), with the substantive interpretation thatevery 10 percent increase in primary city size produces a .476 increase in thePolity scale (a fairly strong effect). As mentioned before, cross-nationalinvestigations of protest’s influence on actual democratization have beensparse. Here, we see that such demonstrations=protests are curvilinearlyrelated to democratization; on average, whenever a country reaches a thresh-old of approximately seven protests per annum then such demonstrationsbegin to encourage representative government. Given that this numberof protests is above the ninetieth percentile for the protest variable, the modelindicates that intensive cycles=campaigns of protest are probably necessaryto “move the dial” in the direction of representative government.

Adding demographic control variables (Model 11) does not change thisverdict much, with the exceptions that (1) it shifts the curve of the primacyvariable (the quadratic’s magnitude is nearly halved, although it remainsrobust), and (2) it washes out the log of primary city size, essentially becausethe log of total population assumes its variance with the dependent variable.We also see something of a reverse “youth bulge” effect here—as theworking-age population share rises, democracy decreases. This finding isnot robust, however (see Models 12 and 13).

In Model 12 we add our economic controls and test our fourthhypothesis. In this model, only trade as a percentage of GDP is strongand positive. While the dependency=world-systems school typically expectsglobalization and international capitalism to discourage democratization,this is apparently not true . . .quite the opposite, in fact. More importantly,net of demographic and economic controls, an interaction exists betweenurban primacy and the log of primary city size (b¼ 3.15, p< .01), whichvalidates our fourth hypothesis (the critical mass effect). To interpret, themultiplicative term indicates that urban primacy is strongly and negativelyinfluential in democratization (with a �42.81 anchor point), but thisattenuates as primary city size rises. By the time the log of primary city sizereaches 13.5 (or about 750,000 people), the power of urban primacy toretard democratization vanishes and grows ever more positive.

Model 13 tests our final hypothesis or question: are antistate demonstra-tions augmented by large primary city size (the world polity effect)? Ourmultiplicative term (b¼ .0546, p le; .05) suggests that the answer is yes. Tointerpret, while antistate demonstrations are mostly ineffective at promotingdemocracy (with a�.849 anchor point), this is completely reversed andbegins to positively contribute to democratization once the log of primarycity size reaches about 15 (i.e., 3.3 million people). In essence, protests havetheir greatest prodemocratic outcomes when they occur in megacities, andthis is probably due to the unique combination of resources such large placesoffer to social movements (e.g., international media and thus the scrutiny of

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the international community). We conclude that this establishes a primafacie case for our fifth hypothesis, establishing strong cross-nationalevidence of the globalization of political contention and democratization(e.g., Keck and Sikkink 1998) as well as the essential relevance of our urbantheory of political change.

Discussion

Our results demonstrate that large primary cities can be “pressure cookers”that become increasingly difficult for authoritarian regimes to manage.While we cannot claim that our urban theory of protest and democratizationprovides the essential missing element in the black boxes lying at the heartof macrosocial theories of democratization, our analyses strongly point tothe mechanisms proposed here as an important corrective for those theoriesas well as a constructive synthesis of them (in that our theory combineselements of structural modernization, social movements, and conflicttheories that are mutually compatible and coherent).

Moreover, this urban theory of political change is ironic on two levels.Most fundamentally, while dictators and oligarchs centralize their space-economies to intensify political control, they may actually be sowing theseeds of their own destruction. First in response to political manipulationand then later to the “natural gravity” of agglomeration, the populationsof primary cities rise, and with them unique grievances involving social class,ethnic propinquity=rivalry, and urban social problems=disamenities.Unfortunately for authoritarian rulers, such massive, politically centralplaces also generate=attract unique mobilization resources such as literacy,urbanism, the international mass media, and elements of local and transna-tional civil society (e.g., nongovernmental organizations). These resourcesgradually allow mobilization for political change while concomitantly “tyingthe hands” of authoritarian elites via the transparency induced by mass mediaand subsequent pressures from global civil society and the world polity(Egypt’s Mubarak is a good recent example of this dynamic). Of course,democratic outcomes are never assured. Having centralized mobilization,critical mass, and a global stage may not be enough to secure representativegovernment, nor is there any guarantee that protest=repression=bargainingcycles will have happy endings. Yet our statistical analyses demonstrate that,on average, countries that have large primary cities will have a better chanceof leveraging political change as time goes on.

The second irony involves how the academic community has appro-ached urban primacy over the years. While academics have sometimesviewed urban primacy as a temporary (and thus relatively benign) stageof urban development (Alonso 1980; Henderson 2003), more frequentlyscholars have taken a much more critical perspective that considers

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primacy economically parasitic (London 1977), deleterious to humanwelfare (Brockerhoff and Brennan 1998), and an instrument of politicaldespotism (Ades and Glaeser 1995). Our research suggests that even thisdarker view may have an unexpected silver lining. While it seems likely thaturban primacy is neither a necessary nor sufficient structural preconditionof democracy, this pattern of city building does appear to be a majorstepping-stone toward more representative government, particularlyamong relatively undeveloped countries where a “jump-start” may berequired to foster democratization. Thus, far from viewing urban primacyas an impediment to economic and political advancement (Armstrong andMcGee 1985), our analysis should encourage the scholarly community toreconsider the longer-term benefits of urban concentration. While primatecities (and particularly those that are also megacities) are burdened bya plethora of social and economic problems, it may also prove truethat they are cradles of political modernity. We do not doubt that somepart of the puzzle linking modernization to democracy lies in the urbanmechanisms we have proposed here.

Future research should examine (1) different measures of urban form,(2) a broader range of political contention, (3) the many interveningmechanisms that create the “world stage=theater” effect (e.g., internationalmass media), and (4) different measures of democratization. Moreover, anexamination of so-called overurbanization (i.e., countries that have largerurban populations than they “ought to” given their level of development)and how it may influence political development is needed. While someevidence points to overurbanization=hyperurbanization as a way to “jump-start” modern economic production in extremely poor countries (Crenshawand Oakey 1998), how hyperurbanization influences political evolutionis an open question.

Above all, it is time for social scientists to take the demography andgeography of contention and political change more seriously. While elites,social movement activists, and other actors surely shape political develop-ment, broader social structures and contexts often act as selection agentsthat determine when, if, and how political change occurs. As the so-calledArab Spring suggests, understanding how “stages” influence “actors”should prove useful in explaining how social pressures actually translate intodemocratic outcomes.

Notes

1. We exclude countries whose RGDP=c was more than $8,000 in 1965. Thiscut-off reflects a “natural” gap between countries above and below $8,000 (Irelandhad $8,218 while Jamaica had $6,787). We restrict the sample to developing countriesbecause most of the dynamics tested here (e.g., urbanization, democratization)have already played out in the developed world. The following countries wereexcluded from the sample: Ireland, Japan, Greece, Spain, Israel, Argentina, Italy,

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Finland, Venezuela, Austria, France, Belgium, United Kingdom, Iceland, Australia,Denmark, Netherlands, Norway, Canada, New Zealand, Sweden, United States,Luxembourg, Switzerland, and Germany (including East and West).

2. A Lagrange multiplier test of the residuals led to the rejection of the nullhypotheses of no autocorrelation in all of our models, which is not surprising. Thus,further specification was required, in this case, by assuming panel-specific auto-correlation and calculating rho using the time-series autocorrelation calculation(i.e., rhotype (tscorr) option for xtpcse in STATA 12). For a discussion of auto-correlation, see Keele and Kelly (2006).

3. Estimates for each country’s five largest cities from 1960 to 2005, which wereused to calculate the index, were taken from the urban primacy data used in the workof Anthony (2014a and 2014b).

4. We experimented with the Non-Violent and Violent Campaigns and OutcomesDatabase (NAVCO) developed by Chenoweth and Stephans (2008, 2011), butits coding scheme for protest does not lend itself to the zero-inflated regressiontechnique that we strongly prefer in light of the controversy over media bias inpolitical event samples. Given our topic (how protest influences democracy),avoiding spurious findings (i.e., media bias creating a false relationship betweenprotest and democratization) requires us to be diligent in this regard. The zero-inflateprocedure, which is novel when used for this purpose, is nearly ideal for correctingevent selectivity bias, but using it constrains us to event-count analysis (and thusour use of Banks).

Funding

This research was made possible by a grant from the National ScienceFoundation (SES – 1125307).

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