Dear Workshop participants:

This paper, which I co-authored with Dwayne Woods of Purdue University, grew out of our attempt to understand the effects that travel liberalization will have on Cuba’s political future. The Cuban government last year announced a set of changes to its travel regulations that are the most sweeping in over five decades. As you will see, there is a connection in this story to political protest through the Exit, Voice, and Loyalty paradigm of Albert O. Hirschman. As always, I (and also my co-author) thank you for the opportunity to present at the Workshop and for any feedback you provide.

1

NO WAY OUT: TRAVEL RESTRICTIONS AND AUTHORITARIAN

STABILITY

2

Why do autocrats differ in their propensity to allow their citizens to travel abroad? This article posits that there is an inverse relationship between the freedom of foreign movement and authoritarian stability. Authoritarian leaders recognize this and hence try to control foreign travel by their citizens. The result is that autocracies that impose restrictions on travel last significantly longer than those that do not, for two reasons. First, travel restrictions decrease the costs of repression for regimes. Secondly, countries that allow international travel integrate themselves significantly more in the global society than regimes that restrict it. There is an authoritarian dilemma inherent in this choice then, since the very human capital that governments desire to develop economically is based on openness to and integration with the outside world.

Keywords: migration, democracy, globalization, travel restrictions.

Word count: 8,510

3

The relationship between international migration and domestic politics has drawn

increased interest in comparative politics in recent years.1 Despite this extensive

treatment, scholars have not explicitly addressed why autocrats differ in their propensity

to allow their citizens to travel and move to other countries, and what effects these

restrictions have on the stability of their governments.2 This article posits that there is an

inverse relationship between the freedom of foreign movement and authoritarian stability.

Authoritarian leaders recognize this and hence try to control the foreign movement of

their populations, fearing that exit will result in increased internationalization of domestic

dissent and less domestic control.

There is, moreover, an authoritarian dilemma inherent in this choice. The very

human capital that governments desire to develop economically is based on openness to

1 Lodigiani and Salomone (2012) have shown, for example, that total international

migration to countries with higher female political empowerment significantly increases

the female parliamentary shares in sending countries. Spilimbergo (2009) demonstrates

that foreign-educated individuals promote democracy in their home country, but only if

the education is acquired in democratic countries. A growing literature demonstrates the

effect of remittances on government in the source country (O'Mahony 2013; Pfutze,

forthcoming).

2 Most of the migration literature in Political Science and Sociology focuses on migration

flows from South to North, that is, economic migration from developing countries to

advanced industrialized democracies. In the words of Laurie A. Brand (2006, 2), “one

cannot really talk about a developed literature on sending-state emigration or practices in

the way one can cite myriad works on receiving-state immigration policy [original

emphasis]”.

4

and integration with the outside world. The deeper an authoritarian regime pursues global

integration through travel, monetary transfers, and communication flows, however, the

more difficult and costly it is for that regime to impose restrictions on travel. 3

Our findings reveal that regimes that impose restrictions are significantly more

durable than those that do not, for two related reasons. First, travel restrictions decrease

the costs of repression for regimes because the freedom of movement, like other human

rights, is a public good that allows citizens to coordinate their information, resources, and

activities (Bueno de Mesquita and Smith 2009, 2010). In addition, countries where

foreign travel is permitted integrate themselves significantly more in the global society

than regimes that have restrictive travel policies. This suggests the social linkages and

networks that develop between émigrés and foreigners on the one hand and local citizens

on the other significantly increase the democratic prospects of less democratic nations.

The findings in this study highlight then the need to move beyond simplified

accounts of the relationship between migration and democratic political reforms

(Hirschman 1970, 1993). In these accounts, the two ways to express dissatisfaction with

an authoritarian government – foreign travel and anti-government protest – are mutually

at odds, that is, the use of one impedes the other. Hirschman rightly anticipated that in the

presence of politically motivated emigration, it would be difficult for anti-government

dissent to develop. But he did not envision how social globalization, motivated to some

3 Fargues (2011, 5) captured the dilemma authoritarian regimes face in this

observation:“North African governments long distrusted their migrant communities in

Europe, suspecting them of being centers of political opposition, before coming to court

them for their remittances.”

5

extent by emigration, could increase citizen political involvement at a later stage.4 As

countries become more socially integrated with the outside, particularly through ties that

bind émigrés with their compatriots back home, citizens are able to pressure their

governments more effectively and elites are in a better position to identify with and

benefit from democratic reforms.

The following two sections point to gaps in our understanding of the relationship

between emigration and democratic reforms and articulate an alternative approach that

factors globalization into the behavior of both masses and elites in authoritarian regimes.

The third section details the empirical approach we have developed for testing these

relationships. A fourth section presents the results of our analysis. We conclude by

drawing implications and policy lessons from our findings.

Exit and Voice: An Inverse Relationship?

In an award-winning article on the collapse of the German Democratic Republic,

Albert O. Hirschman (1993) tried to understand why the GDR had been a stable

authoritarian regime for so long but had collapsed so suddenly.5 In the original

formulation of his exit, voice, and loyalty approach (hereafter EVL), Hirschman (1970)

implied that the blocking or limiting of exit should have a seesaw effect on voice. More

specifically, if citizens cannot express their grievances with the regime in power by

4 Some have even claimed that widespread emigration from the Arab world in the last

half of the 20th century directly contributed to the Arab Spring of 2011. This is indeed

what is suggested (albeit not demonstrated) in Fargues (2011).

5 Foreign travel began to destabilize the country in the summer of 1989. The GDR was

dissolved on October 3, 1990.

6

leaving, they may be more likely to speak up, making protest the dominant means of

redressing grievances in the political arena. In what amounted to a modification of his

earlier EVL framework, Hirschman claimed that the sudden collapse of the GDR could

be explained by a change in the relationship between emigration and protest: where a

regime is widely unpopular and authorities attempt to block exit, exit may actually go

along with belief in the efficacy of voice.6

Two decades have passed since the publication of Hirschman’s account, and his

interpretation of East Germany’s collapse has been challenged, among others for

underestimating the role mass migration can play in failing to produce collective voice

(Pfaff 2006; Pfaff and Kim 2003). But while these works have continued to refine the

EVL framework initially introduced by Hirschman more than four decades ago, an

increasingly accumulating literature has called into the question the utility of the model

for understanding broader trends in the relationship between globalization, in particular

the movement of people across national borders, and domestic democratic reforms (e.g.,

Hoffmann 2008; Koslowski 2005).7

6 Hirschman based his argument on Hungary’s opening up of its Western border in the

summer of 1989, which allowed East German tourists vacationing there to ask for entry

into West Germany, forcing the East German regime to allow them safe passage to the

West (Brubaker 1990, 13). The GDR government subsequently refused to consider any

more liberalization in its travel regulations.

7 There is also evidence that some autocracies have recently reconsidered their approach

to the regulation of foreign travel despite the absence of compelling reasons to change

them. On January 14th, 2013, for example, the Cuban government enacted the most

comprehensive changes in its travel policies in over five decades. See

7

Hirschman intended his approach to be useful in explaining the likelihood of

democratic political reforms in authoritarian regimes. He did so by trying to understand

the relationship between emigration and protest. While the EVL framework provides

some good intuitive insights, however, it raises a number of important questions that it

cannot satisfactorily answer. This failure stems from its inability to fully take

conditioning factors into account and to travel to cases outside those for which it was

originally conceived, namely, state-socialist regimes that simultaneously restrict the

exercise of exit and voice.

Consequently, we set out not to test a more refined theory of exit, voice and

loyalty dynamics. Instead, we use the original model to ask three relatively open-ended

questions. First, is the exit-voice dynamic conditioned by globalization? In other words,

is the calculus on travel shaped by the degree to which a regime is integrated into the

global society? A second and related question is whether regimes that restrict travel more

also integrate themselves less with the outside world. Finally, is it possible to identify a

causal relationship between travel restrictions and regime stability? That is, do travel

restrictions, directly or indirectly, increase the ability of autocracies to hang on to power?

The extent to which exit results in voice, and the ability of loyalists nationals to

rely on voice to demand political reforms, varies greatly. North Korea, for example, has

one of the most restrictive exit policies in the world, going as far as executing anyone

caught trying to flee the country. The regime rightly views exit as a signal to others of the

existence of domestic dissent. In Cuba, on the other hand, exit has been used as a valve to

http://www.ibtimes.com/cuba-travel-restrictions-lifted-us-wet-foot-dry-foot-policies-

remain-same-1013514#.

8

diffuse domestic grievances by ridding the country of those who might be more propense

to engage in protest (Pedraza 2007).

In China, exit is now to some extent a function of global economic integration.

The communist party permits its citizens to travel abroad for study, business, and

tourism, but carefully controls travel visas for dissident intellectuals, academics, and

members of ethnic and religious minorities.8 Moreover, China attempts through various

channels to control the way that Chinese citizens experience travel abroad. China’s

Approved Destination Status (ADS) policy, for example, allows Chinese citizens to travel

in organized group tours to countries the government has approved (Arita at al. 2011).

The objective of the policy, adopted in 1995, is to accommodate the growing demand by

Chinese to visit other countries and at the same time allow the government to have some

control over which countries they visit and the duration and nature of those visits. The

Chinese case suggests that the context in which autocracies respond to the threat of voice

has changed in last four decades: a significant number of governments have become more

democratic (Doorenspleet 2005). The demise of superpower rivalry in particular created a

world that is lot less hospitable to the policies of regimes that suppress human rights and

restrict political competition (Boix 2011; Jansson, Lindenfors, and Sandberg 2013, 2).

Figure 1 presents two plots of travel restrictions from 1981, the first year for

which data is available, to the most recent year for which we have data, 2011. The source

of this information is the CIRI Human Rights Data Project (Cingranelli and Richards

8 See the article appearing in the New York Times on February 22, 2003 titled “No Exit:

China Uses Passports as Political Cudgel”, available at

http://www.nytimes.com/2013/02/23/world/asia/chinese-passports-seen-as-political-

statement.html?pagewanted=all&_r=0.

9

2008), the only repository of standardized comparative data on the freedom of travel.

The plot displays both the distribution of values as well as the average for a particular

year, allowing a trend over time to be discerned. The plots thus capture global trends in

the regulation of foreign travel, first for all regimes, and then for countries where

authoritarian tendencies prevail over democratic ones judging by the polity scores of

country-year observations. We have used a polity score of 0 as our threshold dividing

autocratic observations from democratic ones. 9

Figure 1. Travel Restrictions in the Era of Globalization, 1981-2011

9 The polity score is a combination of an autocracy and a democracy score, both taking a

value from 0 to 10. The autocracy score is subtracted from the democracy one, thus

yielding the overall polity score. This provides a convenient yardstick allowing us to

characterize the authority characteristics of a country with a score of or below 0 as

primarily authoritarian. See the Polity IV user’s manual at

http://www.systemicpeace.org/inscr/p4manualv2010.pdf. If Cheibub et al.’s (2010, 3)

dichotomous classification of countries is used, the results differ by just 49 observations,

or 2.4%. Cheibub, Gandhi, and Vreeland define a democracy as a country where the chief

executive is be chosen “by popular election or by a body that was itself popularly

elected”, the legislature is popularly elected, there is more than one party competing in

elections, and “an alternation in power under electoral rules identical to the ones that

brought the incumbent to office must have taken place”.

10

0.5

11.

52

1980 1990 2000 2010YEAR

all countries

0.5

11.

52

1980 1990 2000 2010YEAR

autocraciesFr

eedo

m o

f for

eign

mov

emen

t

Travel restrictions over time

Note: A score of 0 indicates that this freedom was severely restricted, a score of 1 indicates the freedom was somewhat restricted, and a score of 2 indicates unrestricted freedom of foreign movement.

Figure 1 very clearly establishes that whereas no global trend exists in travel

regulation for the last three decades, a more restrictive trend over time is evident when

the comparison is limited to autocracies – despite the reality that the world has become

increasingly more democratic since the onset of the Third Wave of democratization in

1974.10 Similar to the displays in Figure 1, Figure 2 plots correlograms of economic,

social and political globalization for all countries over time for which there is data. The

information comes from the KOF Globalization project (Dreher 2006; Dreher, Gaston,

10 Although the number changes every year, there are more than 115 out of 196 countries

that meet the minimal criteria for being considered democratic according to Freedom

House (Puddington 2012).

11

and Martens 2008), a quite extensive collection of standardized cross-national time-series

data on globalization in its various manifestations.

12

Figure 2. Global Progress in Economic, Social, and Political Globalization, 1981-2010

020

4060

8010

0

1980 1990 2000 2010YEAR

economic globalization

020

4060

1980 1990 2000 2010YEAR

social globalization

020

4060

8010

0

1980 1990 2000 2010YEAR

political globalization

Progress in Globalization, All Countries

Note: Economic globalization refers to data on flows of trade, stocks of foreign direct investment, portfolio investment, and income payments to foreign nationals, all as a percentage of GDP. Social globalization refers to data on telephone, letters, and information flows into and out of countries, flows of “goods, services, income, or financial items without a quid pro quo”, international tourist arrivals and departures, and the foreign or foreign-born population in a country. Political globalization refers to embassies in a country, membership in international organization, participation in U.N. Security Council Missions, and international treaties ratified.

As Figure 2 indicates, the world is becoming more integrated whether the measure of

globalization used is economic, social or political.

Figure 2 raises the possibility that autocratic elites, while attracted to the

opportunities presented by globalization, also see increasing contact with and dependence

on the outside as a threat to their power and legitimacy. If this is so, a secular trend

towards more interdependence may be specific to democracies, not the world as a whole.

Figure 3 reveals however that autocracies are also partaking in the challenges and

13

opportunities presented by globalization.

14

Figure 3. Progress in Economic, Social, and Political Globalization for Autocracies, 1981-2010.

020

4060

8010

0

1980 1990 2000 2010YEAR

economic globalization

020

4060

1980 1990 2000 2010YEAR

social globalization

020

4060

8010

0

1980 1990 2000 2010YEAR

political globalization

Progress in Globalization, Autocracies

If autocracies tend to restrict travel compared to democracies (Breunig, Cao, and

Luedtke 2012), they seem to be doing so because, not despite globalization. The question

then is whether these restrictions are having their intended effect on the stability of

authoritarian regimes. A positive correlation exists between restrictions on foreign travel

and authoritarian stability: autocracies that impose restrictions on outbound travel last

significantly longer than those that do not. This relationship is present whether

authoritarian stability is understood in terms of how many days a regime is in existence

(r=0.19; p<0.000)11 or in relation to movement (or lack thereof) along a continuous one-

11 We adopted the Polity IV definition of a regime transition as a change in the polity

score of 3 points or more in either direction over a period of 3 years of less. Accordingly,

increases of 3 points or more are classified as liberalizing events.

15

dimensional indicator of the extent of ‘democrativeness’ of a political system (r=-0.14;

p<0.000).12 The following section explains the reason why this relationship is present.

The Conceptual Model

Hirschman claimed that in the presence of politically motivated emigration, it

would be difficult for anti-government dissent to develop. But he did not envision how

social globalization, motivated to some extent by exit, could increase voice at a later

stage. His conceptualization of exit as an individual act and voice as a collective one

involving significant risks, moreover, can severely circumscribe the domain of cases to

which the terms may apply (e. g., communist one-party autocracies). We argue instead

that democratization and social globalization require us to relax the scope conditions of

these two terms and define exit and voice as not simply politically motivated exile and

costly anti-government opposition, respectively. Instead, exit can take the form of

temporary exile and even economically motivated emigration since the latter, by

responding to the government’s inability to meet the economic needs of its population, is

an expression of disapproval. Voice, moreover, can take less demanding forms such as

voting for the opposition party in party-dominated autocracies (Pfutze 2012).

Travel restrictions are likely to affect the type and extent of integration an

autocracy pursues with the outside world. Contrary to the EVL model, however, we are

not interested in the relationship between exit and voice per se, but in how the two

produce (or fail to lead to) democratic reforms. We also subsume the category of loyalty 12 An example is the unified democracy scores (Pemstein, Meserve, and Melton 2010).

Country-year observations where state authority has collapsed due to civil conflict,

foreign intervention, or a protracted regime transition are excluded.

16

into the realm of voice (as hinted by Hirschman in his distinction between insurgent voice

and reformist voice) and ask instead how the regulation of exit affects the probability that

a country will engage in reforms that increase its level of democracy. In so doing, we

adapt the classical Dahlsian (1971) argument about democratization as a function of the

costs of tolerating or suppressing a political opposition to the relationship between travel

restrictions and authoritarian stability.

In our view, restricting travel limits the capacity of citizens not only to emigrate,

but also to return, and this explains why travel restrictions lower repression costs for

governments: by preventing citizens from expressing their dissent in the first place, or

severing the link between dissenters (those who have already left) and their societies,

governments that severely restrict travel make it difficult for citizens to organize and

mobilize around oppositional grievances. The variable we employ to measure this right,

the CIRI Human Rights Data Project’s “freedom of foreign movement and travel”

indicator, embodies the notion that the freedom to leave one’s country of origin and to

return to that country whenever one pleases are fundamental human rights enshrined in

the United Nations’ Universal Declaration of these rights. As a result, the Project codes

this right as severely restricted when countries restrict all or nearly all the foreign travel

of its citizens (as in most communist countries), and when they “do not respect the right

of citizen refugees outside of the country’s international borders to return to their homes.”

(Cingranelli and Richards 2008, 47).13

13 In addition, the freedom to move and travel is severely restricted when governments

have policies making it impossible or very difficult for married women to travel abroad

alone or without their husband’s consent (as in the Middle East), and when countries

limit the travel of sizable minority groups.

17

A country may be more socially globalized because of its own policies, those of

its neighbors, or both. For our purposes, what matters is the extent to which social

integration helps countries promote democratic reforms, controlling for other factors that

may affect this integration such as travel policies and the level of development.14

We believe that democracies pursue policies that are more amenable to global

integration along societal dimensions, but we are not claiming we can isolate the precise

mechanisms in the external environment that influence a country’s political system

(Brinks and Coppedge 2006, 467). Indeed, external forces can influence a country’s level

of democracy through at last five different channels (Levitsky and Way 2010, 38-39).15

The indicator of social globalization we use captures some of those channels – such as

income or financial transfers a country receives without a quid pro quo, namely

remittances and foreign aid. Other variables we employ such as the average level of

democracy in a country’s immediate neighborhood help control for other important

channels of diffusion.

Diffusion variables in previous studies have not explicitly captured processes that

reflect how a nation’s citizens respond to the external environment. Many of the variables

used, even those that proxy for spatial diffusion, mostly reflect the effect of external

14 It is well known for example that less developed countries (LDCs) are much less

socially globalized than their developed counterparts because potential host countries,

fearing the economic effects of immigration, make it very difficult for LDC citizens to

obtain travel permits.

15 These mechanisms are diffusion, direct democracy promotion, multilateral

conditionality, democracy assistance, and transnational advocacy networks.

18

factors on a country’s elite.16 Our study is the first to include a variable that primarily

reflects how the external environment affects citizens in the recipient nation, in addition

to more commonly used indicators of political and economic diffusion.

The Empirical Model

We rely on a panel of 112 countries from 1985 to 2007 to test the effects of travel

restrictions on authoritarian stability (see Appendix A). This time frame creates an ideal

sample for our empirical analysis since it encompasses a period of time beginning

roughly after travel regulations in some ex-communist countries were relaxed following

the East-West détente of the 1970s. Our dependent variable is a country’s Unified

Democracy Score (hereafter UDS) and the main independent variable is the “freedom of

foreign movement and travel” indicator from the CIRI Human Rights Data Project. UDSs

combine scores from 10 different regime indicators (Pemstein, Meserve, and Melton

2010). In so doing, they provide information on a range of political characteristics –

whether institutional, or behavioral. As such, we consider democratization any positive

16 One example would be how liberalization abroad induces home elites to liberalize, or

how backsliding abroad makes repression at home more attractive, which is the process

Brinks and Coppedge (2006) seem to model when including in their analysis a variable

capturing the average change in Freedom House scores for a country’s contiguous

neighbors. Other variables such as the proportion of countries in the world or in the

neighborhood that are democratic (Gleditsch and Ward 2006) do not clearly distinguish

between the effect of external factors on elites and on mass actors. An exception is

Wejnert (2005), who included in her study measures of media exposure.

19

change in a country’s UDS, whether the change occurs as a result of less repression,

greater inclusiveness, more political competition, or something else.

Our theoretical discussion has already established the expectation that social

globalization leads to higher levels of democracy.17 Before proceeding, it is important to

note that we transform the original index of social globalization including subcategories

for personal contact, information flows, and cultural proximity into a new index that

excludes the third subcategory. In our view, two of the proxies used to represent this

subcategory, the number of McDonald’s restaurants and Ikea stores located in a country,

lack validity because the number of such outlets could be more a function of that

country’s openness to and ability to attract foreign direct investment than the cultural

predispositions of its citizens.18 We note though that the pairwise correlation between our

index and the UDS is high (r=0.63; p<0.000). This raises the possibility that regimes may

systematically explain variation in social globalization. We account empirically for this

17 Social globalization has been found in particular to lead to less political repression in

the form of fewer violations of physical integrity rights (Flaten and de Soysa 2012).

18 A better approach in our view would have been to use public opinion data from sources

such as the World Values Survey to establish empirically the existence of this proximity.

We, however, chose not to pursue this approach for two reasons: first, personal contacts

and information flows are much closer to what we think of as social globalization (Flaten

and de Soysa 2012, 631), leading to some extent to the cultural proximity among some

nations that we observe. National cultures and any similarity among them, moreover, is

also a function of important variables such as socio-economic development. To retain the

first two subcategories while excluding the third, we thus rescaled the original index by

multiplying it by their weights, 69%, or 0.69.

20

possibility by finding proxies for social globalization that can then be used to model the

reciprocal effects between social globalization and democracy. This amounts to an

instrumental variables analysis in which social globalization is first modeled as a function

of these proxies and other exogenous covariates, and then predicted values from this

regression along with the exogenous covariates are used to explain the level of

democracy in the second stage.

The variables chosen as proxies are the number of direct borders (sea and land) a

country shares with its neighbors (Correlates of War 2013; Stinnett et al. 2002), and the

average yearly level of democracy in the world. Scholars have recently claimed that

autocracies tend to bloc exit while allowing entry, with democracies following the

opposite policy (Breunig, Cao, and Luedtke 2012). Since social globalization is to some

extent a function of the policies on entry and exit of other countries, the global level of

democracy provides some idea of how the distribution of regimes affects opportunities

for inbound and outbound travel.19

To be valid, the proxies can only be associated with democracy through their

effect on social globalization. That means they have to be correlated with the endogenous

19 In constructing our matrix of instruments, we also experimented with several alternative

proxy variables but ultimately settled on the two we present since the results were

invariably very similar and the estimator performed as well or worse with the alternative

constructions. Instrumental variables estimation in general and the Hausman endogeneity

test in particular are sensitive to the quality of instruments and model specification

(Paxton, Hipp, and Marquart-Pyatt 2011, 80). Although we opted for parsimony in our

analysis, results with different combinations of alternative proxies are available upon

request (See Appendix B).

21

variable (i.e., instruments should be relevant) but uncorrelated with the dependent

variable (exclusion condition). As a result, proxy variables cannot be correlated with the

errors in the second stage of the model. Consequently, we provide diagnostics that assess

whether our matrix of instruments is correlated with the endogenous regressor

(Underidentification Test) but uncorrelated with the error term in the second stage

(Overidentification Test). Finally, we examine whether social globalization is indeed

exogenous to democracy or if the two affect one another (Endogeneity Test).

Our pooled two-stage least squares analysis models both how levels of the

independent variables produce differences in levels of the dependent variable, and how

changes over time in the independent variables produce changes within countries in the

dependent variable in both stages of the analysis. We opted not to model changes only

since there may be a considerable lag between chances in exit policies and the effects of

these changes on a country’s political system. As a result, we provide random effect

estimates of the effect of travel restrictions and other covariates on democracy and social

globalization, controlling for country-specific, unobserved factors that may be difficult to

model.20 Since we are interested in comparing the magnitude of the effect for particular

variables, all our coefficients have been standardized. As such, they represent the number

of standard deviations the dependent variable increases or decreases in response to a one

standard deviation increase in the independent variable.

20 An example would be the hostile relationship between the United States and Cuba in

which the United States has consistently lowered the cost of exit (compared to other

countries) for those disaffected with Cuba’s one-party state socialist government

(Colomer 2000).

22

It is also important to emphasize that our two main independent variables,

“freedom of foreign movement and travel” and “social globalization”, should be

associated with a range of both state and societal behaviors that affect the performance of

democracy such as the presence of free and fair elections, state repressive behavior, and

contentious activity on the part of members of society. The following section provides a

description of the remaining independent and control variables as well as our

expectations regarding their effects.

Inequality in the distribution of pre-tax, pre-transfer income has long been

considered detrimental to democratic politics (Acemoglu and Robinson 2006; Boix

2003). Great gaps in the income different classes receive may create grievances that make

the poor prone to revolution and the wealthy less likely to tolerate competitive politics.

As a result, market inequality could lead to more repression, less political competition,

and/or less electoral inclusiveness. The measure of inequality used is the pre-tax, pre-

transfer Gini coefficient from the Standardized World Income Inequality Database (Solt

2009).

GDP per capita: The most economically developed countries also tend to be the

most democratic, although it is not clear if this is because economic development directly

causes democratization, or because democracies, once installed, survive in more

developed countries (Kennedy 2010). What is clear, however, is that more socioeconomic

development should be associated with greater social globalization. We rely on a measure

of GDP per capita in constant purchasing power parity (PPP) international dollars from

the World Development Indicators.21 Because of its right skew, we use its natural log

transformation instead.

21 http://data.worldbank.org/data-catalog/world-development-indicators.

23

Oil rents: Countries that depend on natural resource wealth have long been

considered inauspicious for democratic rule (Ross 2012). The unusually large rents oil

generates reduce the need to tax the population, thereby depriving it of collective

representation. Oil rents also reduce accountability since the recipients of these rents tend

to be state owned enterprises (with the exception of oil companies in the United States,

which are in private hands). We use an indicator of oil rents from the World

Development Indicators that measures the difference between the value of crude oil

production at world prices and total costs of production (as a percentage of GDP).

Economic globalization: There is no scholarly consensus on the effect of trade

and capital flows on democracy (Coppedge 2012, 301-302). Tariff and other revenue

from financial transactions could lower repression costs for governments. Trade in goods

and services, however, can also generate wealth and goods that empower citizens

economically and make them less dependent on their government for their survival.

While our expectations with respect to the effect of this variable on democracy are clearly

mixed, we expect economic globalization to be positively associated with social

globalization. As already indicated, we use the index of economic globalization

developed by Axel Dreher.22

Political globalization: This variable, as indicated in Figure 2, refers to the extent

of formal penetration by other governments, international organizations, and the United

Nations in the affairs of a particular country. It is expected to result in more social

globalization and greater democracy scores if a majority of states in the international

system are democracies.

22 http://globalization.kof.ethz.ch/.

24

GDP growth: It is important to control for adverse economic conditions that may

affect inbound and outbound travel or create adverse conditions for the stable functioning

of democratic politics (Gasiorowski 1995; Haggard and Kaufman 1995). We also include

an interaction between the freedom of movement variable and GDP growth because some

(e.g. Wright 2009) have suggested that dictators use emigration as a safety valve when

poor economic performance causes their legitimacy to fall. The interaction term would

thus help decide whether travel policies primarily help entrench authoritarian rule by

allowing governing elites to maintain control, or by opening a safety valve for the

disaffected to leave. The inflation-adjusted rate of economic growth, taken from the

World Development Indicators, is expressed in annual percentage points.

Military personnel: The size of the military matters to our analysis for two

reasons: a large and influential military may intervene directly or indirectly in politics,

and/or involve itself in domestic coercion (Svolik 2012). Following Albertus and

Menaldo (2012), we operationalize this variable as military personnel in thousands, based

on figures from the Correlates of War project. We select this measure over military

spending figures since personnel figures are considered more reliable (e.g., Bowman,

1996, 293).23 Because this variable is considerably right-skewed, we also employ its

logarithmic transformation.

Population density: It is important to control for population as larger countries

may be more propense to emigration. In addition, one of the most solid findings from the

literature on state repression is that more populous countries have governments that are

23 Albertus and Menaldo (2012, 154) use military size per 100 inhabitants but we believe

it is best to rely on the original variable as we also include population density in our

analysis.

25

more repressive because there are more people whose behaviors have to be controlled

(Bueno de Mesquita et al. 2003; Davenport 2007). But as important as the total number

of people is their concentration, since high densities facilitate collective action.

Consequently, we rely on densities rather than absolute counts. Population density refers

to people per square kilometer. Information on this variable comes from the World

Development Indicators.

There are several international factors that should affect both a state’s social

integration and its democratic performance. Among these we choose the character of a

country’s neighborhood because it has been used in several previous studies (Brinks and

Coppedge 2006; Gleditsch 2002; Gleditsch and Ward 2006). We account for other

relevant international factors such as regional and global influences (e.g., Pevehouse

2005; Thomas 2001) through the model specification.

Neighborhood level of democracy: According to diffusion theorists,

demonstration effects in neighboring countries and/or imitation by the home country

should increase the home country’s level of democracy. But one could just as easily

envision the opposite effect, that is, that the more the political distance between North

and South Korea grows – to take a particularly poignant example – the more strongly

North Korean elites seek to block the diffusion of democratic norms and practices from

their Southern neighbor (Gunitsky 2013). We follow Brinks and Coppedge’s (2006)

classification of contiguous neighbors and like them, also average regime scores for a

country’s neighbors in a given year. We, however, average over UDS instead of Freedom

House indexes.

Findings

26

Table 1 presents the results of our instrumental variables analysis of social

globalization and democracy. The overall coefficient of codetermination (or R2) is high,

indicating the model explains a significant amount of variation in the data. Tellingly,

more of the variation explained is cross-sectional than time-series, reflecting the

distribution of our dependent variables. Diagnostic tests indicate the model is properly

specified, with proxy variables or instruments being correlated with the endogenous

regressor but uncorrelated with the errors in the second stage of the regression.

27

Table 1. Instrumental Variables Analysis of Social Globalization and Democracy, 1985-2007

Independent variables Social globalization UDSSocial globalization 0.347***

(0.131)Freedom of movement 0.006 0.110***

(0.008) (0.012)Inequality 0.020** -0.040***

(0.010) (0.015)GDP per capita 0.581*** 0.082

(0.023) (0.086)Oil rents -0.078*** -0.081***

(0.012) (0.020)Economic globalization 0.131*** -0.032

(0.012) (0.027)Political globalization 0.100*** 0.064**

(0.013) (0.028)GDP growth 0.008 -0.001

(0.005) (0.008)Freedom of movement*GDP growth -0.003 0.011

(0.004) (0.007)Military population -0.065*** -0.096***

(0.021) (0.032)Population density -0.008 -0.136***

(0.021) (0.032)Neighborhood 0.157*** 0.213***

(0.018) (0.039)Global democracy 0.071***

(0.007)Total number of borders 0.055***

(0.021)Constant 0.006 -0.041

(0.026) (0.040)Underidentification Test: χ² (p-value)H 0: Instruments are uncorrelated with endogenous regressors

19.445(0.000)

Overidentification Test: χ² (p-value)H 0: Instruments are uncorrelated with the error term

0.713(0.399)

Endogeneity Test: χ² (p-value)H 0: Regressors are exogenous

0.249(0.618)

R2 within 0.195R2 between 0.764R2 overall 0.713N 1937

28

* p≤0.1; ** p≤0.05; *** p≤0.01, two-tailed tests. Standardized coefficients reported with standard errors in parentheses.

The results largely confirm our expectations, since social globalization and

freedom of movement are both positively and significantly associated with higher levels

of democracy. Freedom of movement is insignificantly associated with social

globalization, but this is in all likelihood due to the reality that the index accounts for

outbound tourists but not migrants moving to another country. We do not consider this a

serious problem however, since countries that severely restrict outbound migration also

tend to restrict international tourism and return trips for their compatriots, as our

discussion of the freedom of movement variable made clear. Travel policies, moreover,

affect only a subset of indicators used to construct the index of social globalization.

Nevertheless, the bivariate correlation between the freedom of movement and social

globalization is positive and very significant (r=0.33; p<0.000).

As hypothesized, countries that are more politically and economically globalized

are also more socially globalized, but not those who rely on oil rents. Oil dominated

economies are less pluralistic and diversified than would be expected based on their

levels of development (Boix 2003). Also expected is the finding that more borders and a

higher proportion of democracies in the neighborhood and the world significantly

increase social globalization. Not surprisingly, GDP per capita emerges as the variable

with the largest positive effect on a country’s index of social globalization.

Tellingly, the interaction term between freedom of movement and GDP growth is

insignificant. This indicates that travel regulations do not relate to autocratic rule

primarily by serving as safety valves. This is not simply a matter of travel regulations

varying mostly between as opposed to within countries, since the within variation in this

29

variable accounts for 60% of the between variation. We do not deny that poor economic

performance may have contributed to massive exoduses in some autocracies (e.g., Cuba

in 1980 and 1994, East Germany in 1961 and 1989). But a poorly performing economy is

seldom the sole or main mass grievance against authoritarian states. Most likely, there is

variation in economic performance from one exodus to another (the East German

economy was performing better in the early 1960s than in the late 1980s, for example). In

the final analysis, GDP growth does not significantly explain variation in UDS scores

even in the absence of an interaction term.

A crucial finding to emerge from this exercise, however, is that social

globalization is not endogenous to democracy, that is, social globalization affects

democracy significantly, but it does not in turn vary significantly by political regime.

This lack of a reciprocal relationship is confirmed by a Durbin-Wu-Hausman test of

endogeneity (Paxton et al. 2011, 78-80), the null hypothesis of which is that the

coefficient of social globalization from the instrumental variables estimation does not

differ significantly from that of an ordinary random effects (panel data) model. The null

hypothesis is accepted, suggesting that while autocracies are not significantly more

globalized than democracies, they should worry that the benefits they gain while they

seek to expand their integration with the outside world could come at a price.

The lack of endogeneity of social globalization to democracy indicates that an

instrumental variables approach is not only unnecessary, but may not be ideal. Two-stage

least squares regression is not as efficient as OLS, having only large sample properties

(consistency). In addition, our estimation so far has not properly accounted for

autocorrelation and other disturbances that could pose a threat to efficient and consistent

30

parameter estimation. A Wooldridge test for serial correlation in panel data indicates the

presence of such correlation. We may indeed generate more accurate results if we treat

social globalization as exogenous and properly account for the possibility of serial

correlation and other violations of classical assumptions. We thus adjust the errors using

a first order autoregressive process.

Fortunately, mixed or hierarchical models lend themselves well to the task. We

thus estimate a three-level linear model with random intercepts for countries, regions and

years, with countries nested within regions and crossed effects for years.24 The model

presents several unique advantages. Similar to the previous approach, country effects

capture unit heterogeneity, that is, country-specific, unobserved factors, but allowing the

error variance for the group effects to be estimated separately for each group provides an

additional safeguard against heteroskedasticity (Shor et al. 2007). Secondly, adding

random effects for regions controls for International Governmental Organizations (IGOs),

the unique role of the European Union in democracy promotion (Levitsky and Way

24 “Crossed” means that years are not nested within regions or countries, that is, that for

every realization of year there are multiple realizations of country and region and vice-

versa. The suitability of this parameterization was assessed using the Akaike information

criterion (AIC) and the Bayesian information criterion (BIC). In both cases, a model with

countries nested within regions and years crossed with countries and regions yielded

smaller AIC and BIC values than a model with nested random effects but no crossed

effects for years, a model with years crossed with countries but no random effects for

regions, and a model with years crossed with regions but no random effects for countries.

31

2010), and any number of other geographical influences not captured by the level of

democracy in a country’s immediate neighborhood (Wejnert 2005).25

Third, contrary to the complete pooling that ignores clustering or un-pooled

techniques that treat every unit as unique (fixed effects), units in a hierarchical set up are

neither assumed to be unique nor are their differences ignored (Beck 2001, 124–25).

Instead, by employing varying intercepts for units, country and regional effects are

assumed to vary and this variance is estimated conditional on the data and parameters of

the model. Fourthly, year effects capture differences over time that are common to all

groups. Statistically, this has the added benefit that it directly models time intercepts,

removing contemporaneous correlation. Theoretically, it does justice to arguments

claiming that the global balance of democracy exerts an independent effect (via

demonstration) on the autocracies that remain (Gleditsch and Ward 2006).26

Finally, the partial pooling inherent in mixed or hierarchal modeling is

particularly desirable for unbalanced panels since it allows more accurate estimates of

25 Brinks and Coppedge (2006) code seventeen regions in their analysis. This compares to

the sixteen in Wejnert (2005, 59). In addition, several of their country classifications

appeared to be typos, so we corrected them using Wikipedia. The changes are as follows:

Turkey from "Southern Europe" to “Middle East”, Solomon Islands from "Sub-Saharan

Africa" to “Pacific”, Sao Tome and Principe from "Caribbean” to “Sub-Saharan Africa”,

Singapore from “East Asia” to “Southeast Asia”, Maldives from “Sub-Saharan Africa” to

“South Asia”, Lesotho from “Sub-Saharan Africa” to “Southern Africa” and Chad from

“Northern Africa” to “Sub-Saharan Africa”.

26 One example of this type of argument is the claim that regime changes cluster in waves

that affect many countries simultaneously (Huntington 1991).

32

country effects, alleviating the problem of slow-moving or completely time-invariant

predictors (Shor et al. 2007, 168). The mixed or hierarchical structure of the model comes

from employing varying intercept parameters for regions, countries and years. This

makes it unnecessary to use one of the indicator dummies as the baseline category (as

would have been necessary had we introduced fixed effects for regions, countries, or

years).27

To allow for the possibility that the effect of travel restrictions on democracy is

contingent on a country’s level of engagement with the outside world, we present two

models of democracy, one using the same variables as in the previous analysis, and a

second that adds an interaction term between freedom of movement and social

globalization. Table 2 presents the results of our three-level model of democracy. Q-Q

plots of the best linear unbiased predictions for all three random effects indicate no

deviations from normality. The random effect parameters also indicate that the largest

variance in democracy is among regions, followed by countries. The estimates then

confirm the importance of properly correcting for serial correlation and accounting for

hard to model factors such as regional diffusion and demonstration effects.

27 Multiple intercepts are usually interpreted as offsets from a dropped group intercept. A

more efficient method, however, is to model these intercepts directly by placing a

common distribution around them.

33

Table 2. Mixed-Effects Analysis of Democratization, 1985-2007

Independent Variables UDS UDS UDS

Social globalization 0.180*** 0.180***(0.038) (0.038)

Freedom of movement 0.027*** 0.012 0.012(0.008) (0.008) (0.008)

Social globalization*freedom of movement

-0.040***(0.008)

Economic globalization 0.022 0.026(0.020) (0.019)

Political Globalization 0.019 0.021(0.018) (0.018)

Overall globalization 0.182***(0.033)

Overall globalization*freedom of movement

-0.045***(0.009)

Market inequality -0.010 -0.012 -0.016(0.018) (0.018) (0.018)

GDP per capita 0.253*** 0.250*** 0.280***(0.058) (0.058) (0.056)

Oil rents -0.041*** -0.043*** -0.047***(0.014) (0.014) (0.014)

GDP growth 0.005 0.004 0.003(0.005) (0.005) (0.005)

Military population -0.101*** -0.102*** -0.104***(0.031) (0.031) (0.031)

Population density -0.125*** -0.134*** -0.130***(0.046) (0.046) (0.044)

Neighborhood 0.159*** 0.156*** 0.153***(0.036) (0.036) (0.036)

constant -0.119 -0.106 -0.103(0.097) (0.098) (0.098)

N 1937 1937 1937* p<0.1; ** p<0.05; *** p<0.01, two-tailed tests. Standardized coefficients reported with standard errors in parentheses.

34

Substantively speaking, the results from the hierarchical model are somewhat

similar to the second stage of the instrumental variables estimation. But some important

differences emerge, both in terms of the magnitude of coefficients as well as their

significance. Regarding differences in magnitude, the coefficient for social globalization,

which was the largest in the second stage of the instrumental variables analysis, is now

smaller once it has been estimated more precisely. In addition, freedom of movement,

while maintaining its significance, has become smaller in size. This is nevertheless

expected since the latter is a policy variable while all other covariates reference structural

characteristics of countries. In the model where these two variables are interacted,

however, freedom of movement is itself insignificant while the interactive term is

negative and very statistically significant. Individual coefficients in interaction terms

refer to the effect of that variable when the other is zero. Hence, the regulation of travel

when social globalization is zero captures a scenario that is absent in our data – countries

with no social globalization. The interaction term, however, contains more information

than the coefficient can display and we thus explore it using marginal effects simulations.

Our simulations demonstrate that the marginal effect of social globalization is

always positive, albeit with a declining slope, indicating that at higher levels of travel

openness, each additional 1-unit increase in social globalization yields smaller increases

in democracy. Each standard deviation increase in social globalization increases

democracy by 0.18 points, or 4.38%. This might seem like a small amount considering

how long it can take countries to increase their levels of social globalization, but the

marginal effect is belied by the pairwise correlation between this variable and democracy

35

in our sample (r=0.727; p<0.000), almost identical to the pairwise correlation between

the natural log of GDP and democracy (r=0.730; p<0.000).

Higher levels of the freedom of movement variable increase democracy at low

levels of social globalization. This offers support for our claim that autocracies most at

risk when they liberalize travel are those that are least socially globalized, although the

substantive effects of this variable are smaller than those of social globalization.

Conversely, the marginal effect of travel openness is negative at the highest levels of

social globalization. Most countries with high levels of social globalization are advanced

industrialized democracies. A few outlying autocracies (Belarus, Croatia, Jordan and

Singapore) receive high amounts of remittances or foreign aid and hence have high levels

of social globalization. Since they also restrict travel, they are responsible for the

negative marginal effects of freedom of movement. Freedom of movement, however, also

has important substantive effects on democracy considering its pairwise correlation with

UDS (r=0.533; p<0.000). This is much higher than the correlation between income

inequality and UDS (r=0.086; p<0.002), another variable much discussed in the literature

on democratization (Acemoglu and Robinson 2006; Boix 2003).

As expected, the largest positive influence on a country’s political system is the

level of development, while in the negative direction it is population density. But the

effects of social globalization are larger than those of other prominent candidates such as

economic globalization. Oil rents and military population also exert powerful negative

influences on democracy, as hypothesized.

Regarding statistical significance, political globalization, which had a positive and

significant effect on democracy in the instrumental variables analysis, now has an

36

insignificant effect. In addition, inequality, which was statistically significant in the

instrumental variables analysis, has now lost its significance, while the opposite has

occurred to GDP per capita. The findings are in line with recent work on the determinants

of democratization and democratic stability indicating that the level of economic

development has a stronger effect on regime transitions and consolidation than income

inequality (Kennedy 2010). Overall then, hierarchical modeling has reaffirmed the

importance of variables previously thought to affect the prospects for democracy such as

socio-economic development, military influence, and population pressures, while

establishing the importance of globalization and policies regarding the freedom of

movement.

As a check on the robustness of the results, we also estimated a model in which

all our diffusion variables are combined into an overall index of globalization (also

available from the KOF dataset). This model is reported to the right of the first two

models in Table 3. The results are largely consistent with those in columns 1 and 2. The

models all reveal that the economic component of globalization much emphasized in the

literature on regime transitions has a smaller and less significant effect on democracy

than its social component. Indeed, of all the globalization-induced diffusion effects,

social globalization is by far the most important.

Conclusion

Scholars studying migration and democracy have long sought to establish a

connection between emigration – in particular regime policies surrounding foreign travel

– and democratic political reforms. The question is particularly relevant as autocracies in

37

the Middle East grapple with popular revolts motivated to some extent by societal

influences emanating beyond their borders. Our article is motivated by these concerns, in

particular the need to understand to what extent globalization affects the way in which

less democratic regimes formulate policies on foreign travel, and what effect such

policies have on these regimes.

We incorporated the core of Hirschman’s exit and voice model into our

conceptual framework, but also went beyond its rather simplistic mechanisms. While

Hirschman rightly anticipated that emigration would serve as a safety valve for

governments in authoritarian regimes, he did not entertain the possibility that social ties

that straddle national borders act in ways that can significantly affect a nation’s

democratic prospects. Hirschman’s conceptualization of exit and voice was limited to the

nation-state. We argued that globalization conditions the effects of migration and voice

on democratic political reforms. As countries become more socially integrated with the

outside, citizens are able to pressure their governments more effectively and elites are in

a better position to identify with and benefit from democratic reforms.  

We believe we make an important contribution to work on the diffusion of norms,

technology, and institutions as well by presenting the most detailed picture of the effects

of international diffusion on democracy to date. Overall, our objective has been to extend

rather than to challenge previous research. Perhaps the most important paradox we have

uncovered is that although travel restrictions increase popular grievances against

autocracies, they also deprive citizens of resources to organize and mobilize collectively.

We have also uncovered a dilemma most likely pressing on the minds of authoritarian

38

elites: that as they integrate their countries ever more deeply with the outside world, it

becomes increasingly more difficult to maintain control over their restive populations.

Our research thus yields some important policy implications that democratic

governments, opposition activists in less democratic countries, and civil-society

democracy promoters would be well advised to follow. This is a well-trodden area and by

no means do we seek to supplant the knowledge and expertise that practitioners have

accumulated. Democracy promotion can also be quite challenging in the least democratic

settings. But our findings are clear that if the goal is ultimately to increase the prospects

for democracy in the least democratic nations of the world, one way to do it would be by

trying to increase the social globalization of the target country, which may not be

something outside actors can do directly, but through their economic and political

engagement, since both are associated with higher levels of social globalization.

39

Appendix A. Countries Included in the Analysis, 1985-2007

Albania Georgia NorwayAlgeria Germany West PakistanAngola Ghana PanamaArgentina Greece Papua New GuineaArmenia Guatemala ParaguayAustralia Haiti PeruAustria Honduras PhilippinesAzerbaijan Hungary PolandBangladesh India PortugalBelarus Indonesia RomaniaBelgium Iran RussiaBenin Ireland SenegalBolivia Israel SingaporeBotswana Italy SlovakiaBrazil Ivory Coast SloveniaBulgaria Jamaica South AfricaCambodia Japan SpainCameroon Jordan Sri LankaCanada Kazakhstan SwedenChad Kenya SwitzerlandChile Korea South SyriaChina Kyrgyzstan TajikistanColombia Latvia TanzaniaCongo, Republic of Lebanon ThailandCosta Rica Lithuania TogoCroatia Macedonia Trinidad and TobagoCyprus Malaysia TunisiaCzech Republic Mexico TurkeyDenmark Moldova TurkmenistanDominican Republic Mongolia UkraineEcuador Morocco United KingdomEgypt Mozambique United StatesEl Salvador Namibia UruguayEstonia Nepal VenezuelaFinland Netherlands VietnamFrance New Zealand YemenGabon Nicaragua Zambia

NigeriaNote: For publication along with the paper.

40

Appendix B. Alternative Proxy Variables for Instrumental Variables Analysis

-A country’s location in the world according to the regional classification in Brinks and

Coppedge (2006).

-The mean of all dyadic minimum, capital, and centroid distances, averaged over all

dyads for every country in the world. The more remote a country, the less globalized it

will be (Breunig, Cao, and Luedtke 2012). Data on distances comes from the CShapes

dataset, which includes information on three types of distances: minimum, centroid, and

capital. A centroid can be defined as the mean geographic position of all the points in the

coordinate space for a particular country (Weidmann, Kuse, and Gleditsch 2010, 99).

-The log of exports to advanced OECD democracies derived from the Correlates of War

Project Trade Data Set (Barbieri and Keshk 2012; Barbieri, Keshk, and Pollins 2009).

-Indexes of ethnic, linguistic and religious fractionalization. Data on social diversity,

which is expected to increase social globalization through cultural ties between a

country’s residents and those abroad, is derived from the QoG Standard Dataset (Teorell

et al. 2013).

- Time since independence expressed in years, and time since the last regime change, also

in years. Both are expected to increase social globalization by fomenting stability and

predictability. Instability and conflict, however, can also lead to strife that pushes

refugees and other migrants out of their homeland, making a country more socially

globalized. Data on the timing of independence comes from the Issue Correlates of War

(ICOW) Colonial History Data Set (Hensel 2009). Information on regime durability can

be downloaded from the Polity IV project website.

41

References

Acemoglu, Daron, and James A. Robinson. 2006. Economic Origins of Dictatorship and Democracy. Cambridge, New York: Cambridge University Press.

Albertus, Michael, and Victor A. Menaldo. 2012. "Coercive Capacity and the Prospects for Democratization." Comparative Politics 44 (2):151-69.

Arita, Shawn, Christopher Edmonds, Sumner La Croix, and James Mak. 2011. "Impact of Approved Destination Status on Chinese Travel Abroad: An Econometric Analysis." Tourism Economics 17 (5):983-96.

Barbieri, Katherine, and Omar Keshk. 2012. "Correlates of War Project Trade Data Set Codebook, Version 3.0." http://correlatesofwar.org (July 28, 2013).

Barbieri, Katherine, Omar M. G. Keshk, and Brian Pollins. 2009. "Trading Data: Evaluating our Assumptions and Coding Rules." Conflict Management and Peace Science 26 (5):471-91.

Barry, Brian. 1974. "Review Article: Exit, Voice and Loyalty." British Journal of Political Science 4 (1):79-107.

Beck, Nathaniel. 2001. "Time-Series-Cross-Section Data." Statistica Neerlandica 55 (2):111-33.

Boix, Carles. 2003. Democracy and Redistribution. Cambridge; New York: Cambridge University Press.

———. 2011. "Democracy, Development and the International System." American Political Science Review 105 (4):809-28.

Bowman, Kirk. 1996. "Taming the Tiger: Militarization and Democracy in Latin America." Journal of Peace Research 33 (3):289-308.

Brand, Laurie A. 2006. Citizens Abroad: Emigration and the State in the Middle East and North Africa. New York: Cambridge University Press.

Breunig, Christian, Xun Cao, and Adam Luedtke. 2012. "Global Migration and Political Regime Type: A Democratic Disadvantage." British Journal of Political Science 42 (4):825-54.

Brinks, Daniel, and Michael Coppedge. 2006. "Diffusion is no Illusion: Neighbor Emulation in the Third Wave of Democracy." Comparative Political Studies 39 (4):463-89.

Brubaker, Rogers. 1990. "Frontier Theses: Exit, Voice, and Loyalty in East Germany." Migration World XVIII (3/4):12-7.

42

Bueno de Mesquita, Bruce, and Alastair Smith. 2009. "Political Survival and Endogenous Institutional Change." Comparative Political Studies 42 (2):167-97.

———. 2010. "Leader Survival, Revolutions, and the Nature of Government Finance." American Journal of Political Science 54 (4):936-50.

Bueno de Mesquita, Bruce, Alastair Smith, Randolph M. Siverson, and James D. Morrow. 2003. The Logic of Political Survival. Cambridge: MIT Press.

Cheibub, José Antonio, Jennifer Gandhi Gandhi, and James Raymond Vreeland. 2010. "Democracy and Dictatorship Revisited." Public Choice 143 (1-2):67-101.

Cingranelli, David L., and David L. Richards. 2008. "The Cingranelli-Richards (CIRI) Human Rights Data Project Coding Manual Version 2008.3.13." http://ciri.binghamton.edu/documentation/ciri_coding_guide.pdf (October 8, 2013).

Colomer, Josep M. 2000. "Exit, Voice, and Hostility in Cuba." The International Migration Review 34 (2):423-42.

Coppedge, Michael. 2012. Democratization and Research Methods: The Methodology of Comparative Politics. New York: Cambridge University Press.

Correlates of War Project. "Direct Contiguity Data, 1816-2006. Version 3.1." http://correlatesofwar.org (June 26, 2013).

Dahl, Robert Alan. 1971. Polyarchy: Participation and Opposition. New Haven, CT: Yale University Press.

Davenport, Christian. 2007. State Repression and the Domestic Democratic Peace. New York: Cambridge University Press.

Doorenspleet, Renske. 2005. Democratic Transitions: Exploring the Structural Sources of the Fourth Wave. Boulder: Lynne Rienner Publishers.

Dreher, Axel. 2006. "Does Globalization Affect Growth? Evidence from a New Index of Globalization." Applied Economics 38 (10):1091-110.

Dreher, Axel, Noel Gaston, and Pim Martens. 2008. Measuring Globalisation: Gauging its Consequences. New York: Springer.

Fargues, Philippe. 2011. “Voice after Exit: Revolution and Migration in the Arab World.” http://www.migrationinformation.org/feature/display.cfm?ID=839 (January 20, 2013).

Flaten, Ranveig Drolsum, and Indra de Soysa. 2012. "Globalization and Political Violence, 1970–2008." International Interactions 38 (5):622-46.

Gasiorowski, Mark J. 1995. "Economic Crisis and Political Regime Change: An Event History Analysis." American Political Science Review 89 (4):882-97.

43

Gleditsch, Kristian Skrede. 2002. All International Politics is Local: The Diffusion of Conflict, Integration, and Democratization. Ann Arbor, MI: University of Michigan Press.

Gleditsch, Kristian Skrede, and Michael D. Ward. 2006. "Diffusion and the International Context of Democratization." International Organization 60 (4):911-33.

Gunitsky, Seva. 2013. "Complexity and Theories of Change in International Politics." International Theory 5 (10):35-63.

Haggard, Stephan, and Robert R. Kaufman. 1995. The Political Economy of Democratic Transitions. Princeton: Princeton University Press.

Hensel, Paul R. 2009. "ICOW Colonial History Data Set, Version 0.4." http://www.icow.org/colhist.html (June 27, 2013).

Hirschman, Albert O. 1970. Exit, Voice and Loyalty: Responses to Decline in Firms, Organizations and States. Cambridge: Harvard University Press.

———. 1993. "Exit, Voice, and the Fate of the German Democratic Republic: An Essay in Conceptual History." World Politics 45 (2):173-202.

Hoffmann, Bert. 2008. "Bringing Hirschman Back In: Conceptualizing Transnational Migration as a Reconfiguration of “Exit”, “Voice”, and “Loyalty”." http://ideas.repec.org/p/gig/wpaper/91.html (January 20, 2013).

Huntington, Samuel P. 1991. The Third Wave: Democratization in the Late Twentieth Century. Norman: University of Oklahoma Press.

Jansson, Fredrik, Patrik Lindenfors, and Mikael Sandberg. 2013. "Democratic Revolutions as Institutional Innovation Diffusion: Rapid Adoption and Survival of Democracy." Technological Forecasting and Social Change 80 (8):1546-56.

Kennedy, Ryan. 2010. "The Contradiction of Modernization: A Conditional Model of Endogenous Democratization." Journal of Politics 72 (3):785-98.

Koslowski, Rey, ed. 2005. International Migration and Globalization of Domestic Politics. New York: Routledge.

Levitsky, Steven, and Luncan A. Way. 2010. Competitive Authoritarianism: Hybrid Regimes After the Cold War. New York: Cambridge University Press.

Elisabetta Lodigiani and Sara Salomone. 2012. "Migration-Induced Transfers of Norms. The Case of Female Political Empowerment." Centro Studi Luca D'Agliano. http://www.dagliano.unimi.it/media/GC_Paper_Lodigiani.pdf (October 8, 2013).

Marshall, Monty G., Keith Jaggers and Ted Robert Gurr. 2011. Polity IV Project: Political Regime Characteristics and Transitions, 1800-2010, Dataset Users' Manual.

44

College Park: Center for International Development and Conflict Management, University of Maryland.

O'Mahony, Angela. 2013. "Political Investment: Remittances and Elections." British Journal of Political Science 43 (4):799-820.

Paxton, Pamela, John R. Hipp, and Sandra Marquart-Pyatt. 2011. Nonrecursive Models: Endogeneity, Reciprocal Relationships, and Feedback Loops. Quantitative Applications in the Social Sciences Vol. 168. Thousand Oaks, CA: Sage Publications, Inc.

Pedraza, Silvia. 2007. Political Disaffection in Cuba’s Revolution and Exodus. New York: Cambridge University Press.

Pemstein, Daniel, Stephen A. Meserve, and James Melton. 2010. "Democratic Compromise: A Latent Variable Analysis of Ten Measures of Regime Type." Political Analysis 18 (4):426-49.

Pevehouse, Jon C. 2005. Democracy from Above: Regional Organizations and Democratization. New York: Cambridge University Press.

Pfaff, Steven. 2006. Exit-Voice Dynamics and the Collapse of East Germany: The Crisis of Leninism and the Revolution of 1989. Durham, NC: Duke University Press.

Pfaff, Steven, and Hyojoung Kim. 2003. "Exit-Voice Dynamics in Collective Action: An Analysis of Emigration and Protest in the East German Revolution." American Journal of Sociology 109 (2):401-44.

Pfutze, Tobias. 2012. "Does Migration Promote Democratization? Evidence from the Mexican Transition." Journal of Comparative Economics 40 (2):159-75.

———. forthcoming. "Do Remittances Promote Democratization? How International Migration Helps to Overcome Political Clientelism." Journal of Development Economics.

Puddington, Arch. 2012. Freedom in the World 2012: The Arab Uprisings and their Global Repercussions. Washington, D.C.: Freedom House.

Ross, Michael L. 2012. The Oil Curse: How Petroleum Wealth Shapes the Development of Nations. Princeton: Princeton University Press.

Shor, Boris, Joseph Bafumi, Luke Keele, and David Park. 2007. "A Bayesian Multilevel Modeling Approach to Time-Series Cross-Sectional Data." Political Analysis 15 (2):165-81.

Solt, Frederick. 2009. "Standardizing the World Income Inequality Database." Social Science Quarterly 90 (2):231-42. SWIID Version 4.0, September 2013.

Spilimbergo, Antonio. 2009. "Democracy and Foreign Education." American Economic Review 99 (1):528-43.

45

Stinnett, Douglas M., Jaroslav Tir, Philip Schafer, Paul F. Diehl, and Charles Gochman. 2002. "The Correlates of War Project Direct Contiguity Data, Version 3." Conflict Management and Peace Science 19 (2):58-66.

Svolik, Milan. 2012. The Politics of Authoritarian Rule. New York: Cambridge University Press.

Teorell, Jan, Nicholas Charron, Stefan Dahlber, Sören Holmberg, Bo Rothstein, Petrus Sundin, and Richard Svensson. 2013. "The Quality of Government Dataset, version 15." http://www.qog.pol.gu.se (May 6, 2013).

Thomas, Daniel C. 2001. The Helsinki Effect: International Norms, Human rights, and the Demise of Communism. Princeton: Princeton University Press.

Weidmann, Nils B., Doreen Kuse, and Kristian Skrede Gleditsch. 2010. "The Geography of the International System: The CShapes Dataset." International Interactions 36 (1):86-106.

Wejnert, Barbara. 2005. "Diffusion, Development, and Democracy, 1800-1999." American Sociological Review 70 (1):53-81.

Wright, Joseph. 2009. "Exit During Crisis: How Openness, Migration, and Economic Crisis Affect Democratization." http://www.personal.psu.edu/jgw12/blogs/josephwright/Wright_KelloggWPdraft.pdf (September 10, 2013).

46