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TRANSCRIPT
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Modernization: Does it have an impact on the survival of different types of
autocracies?
Dr. Daniel Stockemer, Associate Professor, University of Ottawa, [email protected]
Dr. Steffen Kailitz, Researcher, Hannah Arendt Institute, [email protected]
Abstract:
Modernization theory is one of the most influential theories in political science. A near iron law
exists in the discipline – that is, there is an observable close relationship between the level of
economic development and the level of democracy. Up to the present, studies testing the impact
of modernization on political regimes have almost completely focused on democracies. We aim
at broadening the discussion to autocracies and ask the following research question: What
impact has development on the survival of different types of autocracies? Using data covering
the time span from 1945 to 2010, we ascertain – through logistic regression analysis and event
history analysis – that the level of economic development does affect not only the endurance of
democracies but also that of various types of autocracies. In more detail, we find that
modernization accelerates the breakdown of military regimes and communist ideocracies, while
having no to a small positive influence on the longevity of monarchies, personalist autocracies,
one party autocracies, and electoral monarchies.
Keywords: modernization, regime legitimation, regime durability, autocracies, political regime
types
Paper prepared for presentation for the ECPR General Conference, Prague, September 7 to
10.
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Introduction
One of the main questions in comparative politics is: What makes political regimes rise, endure,
and fall? Modernization theory is one of the most important theories to tackle these questions.
However, most of the academic literature measuring the influence of modernization on a
regime’s emergence and longevity has been restricted to democracies (Alemán und Yang 2011;
Boix 2003; Burkhart und Lewis-Beck 1994; Cheibub und Vreeland 2011; Coppedge 1997;
Diamond 1992; Epstein et al. 2006; Foweraker und Landman 2004; Gasiorowski 2000;
Hadenius und Teorell 2005; Huber et al. 1993; Muller 1988; Rao 1984). We shift the focus to
autocracies and test the impact of material affluence on the survival of autocracies. In fact, we
only know of three studies which test the link between economic wealth and the incidence or
survival of autocracies. Sanhueza (1999: 337) reports that “rich autocracies do not show a lower
hazard rate than less developed autocracies”.1 Przeworski et al’s. (2000) conclusions are more
nuanced. They highlight that “dictatorships survive almost invariably in very poor countries”,
are “less stable in countries with incomes between $1,001 and $4,000, and even less so between
$4,001 and 7,000”. However, beyond 7,000 “the trend reverses” and autocracies “become more
likely to survive” (92). Hence, dictatorships are least stable at an intermediate level of per capita
income, while poor and rich autocracies are relatively stable. These results are basically in line
with the finding by Lipset, et al. (1993), who ascertain that the incidence of non-democratic
regimes increases with growing per capita income in a middle range (between $2,346 and
$5,500), but that the likelihood of autocratic regime change decreases in low and high income
countries.
1 Instead of focusing on the potential effect modernization theory could have on the longevity of different types
of autocracy, the recent wave of autocracy research mainly focuses on the stabilizing effect of institutions for
autocracies such as cooptation mechanisms (Blaydes 2011; Brownlee 2007; Cox 2009; Gandhi 2008; Gandhi
und Lust-Okar 2009; Gandhi und Przeworski 2007; Magaloni und Kricheli 2010; Schedler 2009; Svolik 2012).
For example, researchers claim that autocracies with a legislature are more durable because they use this
institution as a forum for policy concessions (Gandhi und Przeworski 2007) and/or as a forum to distribute
patronage and other spoils (Lust-Okar 2009).
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Our quantitative study, which examines the influence of modernization on the survival
of various regime types provides nuanced results. First, we support Przeworski and Limongis
(1997) and Przeworski et al. (2000) seminal findings that material affluence basically reduces
democracies’ risk to revert back to autocracies to zero. With regards to autocracies our results
are more nuanced. We find that modernization decreases the chances of survival of military
regimes and communist autocracies, and has a limited and non-significant influence on the
survival the five remaining regime types, monarchies, one party autocracies, electoral
autocracies, one party autocracies and personalist autocracies.
Our article is structured as follows: first, we condense modernization theory and reflect
on the possible impact of modernization on democracies and autocracies. Second, we outline
our classification of regime types and present alternative hypotheses why the survival of
autocratic regime types should depend or not on modernization. Third and fourth, we discuss
the methodological procedures adopted for this research and the results, respectively. Finally,
we summarize the main findings of this research and provide avenues for future research.
Theory: Modernization theory
Since Seymour Martin Lipset published his seminal article „Some Social Requisites of
Democracy” (1959), modernization theory has become, the „hitherto greatest (in terms of
adherents and research pursued) and most dominant theory of the prerequisites of democracy”
Hadenius (1992: 77). The essence of Lipsets argumentation is: increased education and wealth
lead to a growing middle-class. Because wealth grows and education spreads, extremism in the
lower class declines. Hence, the danger for the upper strata to get violently expropriated by the
lower class declines. With the rise of the middle-class and the decline of extremism in the lower
strata, extremism in the upper strata declines, as well. Modernization theory has been applied
rather extensively to explain the emergence and survival of democracies. The basic argument
for the necessity of a democratic regime (inclusive and competitive) in modernizing or modern
societies from the standpoint of modernization theory „is that, the larger and more complex a
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society becomes, the more important is effective political organization […] and [n]o
institutional form basically different from the democratic association“ (Parsons 1964: 355) can
handle this.
Therefore, the main premise behind modernization theory is that socio-economic
developments foster the pressure and the need for a political development (Huntington und
Dominguez 1975) that “involves the creation of political institutions sufficiently adaptable,
complex, autonomous, and coherent to absorb and direct the participation of [the new social
groups] and to promote social and economic change in the society” (Huntington 1968: 264; see
also Lapalombora und Weiner 1966: 3). The modern political institutions – parties and
especially parliaments – then serve “as the channel[s] through which rents can be distributed,
and more importantly, as the forum in which policy compromises can be organized“ (Gandhi
2008: 100). A revised version of modernization theory by Christian Welzel and Ronald
Inglehart implies that changing mass attitudes are the decisive link between modernization and
democracy (Inglehart und Welzel 2010; Welzel 2007, 2013; Welzel und Inglehart 2005; Welzel
et al. 2003).
However, modernization is not without its opponents. Critics of modernization theory
like Guillermo O’Donnell (1973: 3) challenge the theory in the following way: „if other
countries become as rich as the economically advanced nations, it is highly probable that they
will become political democracies”. Hence, non-democracies should become democracies
when they pass a certain threshold of modernization. A brief look at the distribution of countries
suffices to acknowledge that many countries including the Gulf monarchies or Singapore have
become rich, but not democratic.
To resolve this predicament Adam Przeworski has amended modernization theory
(Przeworski et al. 2000; 1997) and presented a survival story why rich countries are
predominantly democratic. According to them the likelihood of transitions from non-
democracy to democracy is not effected by increasing wealth. However, the survival chances
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of democracy increase with wealth. In this article, we take Przeworski as a starting point and
test whether the survival of different types of autocracies is also impacted by development, and
if so, how strongly. We will formulate our hypotheses below, but before doing so we will
introduce our 7 regime types.
Definition of regime types
To determine modernization theory’s influence on the longevity of various types of autocracies,
it is important to classify various types of autocracies and to distinguish them from a
democracy. We code various political regimes based on their basic pattern of legitimation
(Kailitz 2013). To classify six types of autocracies (i.e. monarchy, ideocracy, electoral
autocracy, military regime, one party autocracy, personalist autocracy) we employ a two step
coding process. First, we sort out all non-regime phases like civil war or the occupation of a
country. Second we try to verify who actually rules an autocratic country.
The defining feature of a monarchy is the ruler’s title, which normally is „King“ or
„Emir.“ In most cases, the monarchic title and privileges are passed on through family lineage.
This simple criterion excludes two types of regimes: (1) regimes, which are governed by a
former king, who was chosen as a non-monarchic elected ruler. Cases of this first type of elected
former monarchs are Khama in Botswana or Mutesa in Uganda. (2) Parliamentary monarchies,
in which the monarch is the country’s figure head, but does not constitute the executive. Many
of the West and North European parliamentary monarchies including the UK or Sweden fit this
second categorization. Because the monarch in these countries has no or very limited political
power we do not include parliamentary monarchies in the party family of monarchies. The Gulf
dynasties including Saudi Arabia or the United Arab Emirates are examples of contemporary
monarchies.
Communist Ideocracy is the second regime type in our classification. The ideological
basis of a ideocracy is totalitarian, which promises its followers an ideal/ or utopian future
(Friedrich und Brzezinski 1965; Linz 2000). Three different types with a totalitarian ideology
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have existed so far: communist, national-socialist/fascist and Islamist regimes. Except for two
cases, the post WWII period has been characterized by one type of ideocratic regime, a
communist regime.2 Two features characterize a communist regime: (1) the self-denomination
as a socialist/ communist (2) the ruling by a Socialist- Leninist party that eliminates opposition
parties and controls society. The former countries of the Soviet Bloc as well as the PR of China
are examples of communist/ socialist regimes.
Military regimes are next in our categorization of autocracies. To code a country as a
military regime we have one inclusion and two exclusion criteria. The inclusion criterion is the
rule of the junta – either a military general or a group of high ranking military officers, who are
chosen by the military. The two exclusion criteria are that the country is neither a monarchy
nor an ideocracy, and that there are no multiparty election for the executive. Argentina under
Perron (1976-1983) and Chile under Pinochet (1973-1988) are two examples of military
dictatorships.
The fourth autocratic regime type is personalist autocracy, which is defined as an
(almost) “institutionless polity” where there are no succession rules of the ruler. (Brooker 2008:
139; Jackson und Rosberg 1982: 8). Two characteristics help us code a regime as a personalist
autocracy. The first rule is an exclusion rule; that is the regime under consideration cannot be
coded as any of the three regime types listed above. Second, we only coded a personalist
autocracy as such if the country lacks popular (direct or indirect) multiparty elections. This
implies that the personalist rules has (almost) absolute power. No opposition can topple the
leader through institutional means. Prominent cases of personalist autocracies are cases where
the ruler becomes president for life (e.g. Hastings Banda in Malawi (1971) or Jean-Bédel
Bokassa in the Central African Republic (1972).
2 The only two examples of Islamist Ideocracies in our period of investigation were Afghanistan 97-00 and Iran
82-09. We excluded these two cases from the analysis
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The second to last autocratic regime type which we distinguish is a one party autocracy
of non-ideocratic nature. The first coding criterion is again an exclusion criterion. We code a
one party autocracy as such if the regime does not fulfill the conditions of an ideocracy,
monarchy, military autocracy or personalist autocracy. The second criterion is the absence of
any type of popular elections. The third criterion, is that power is exercised by a single party
rather than a monarch or personal dictator. Belarus (since 1991) and, Kenya (82-91) are
prominent examples of this type of regime.
The final type of autocracy, which we distinguish is an electoral autocracy. Two
conditions guide us in our choice to code a regime as such. First, the country must allow (direct
or indirect) popular multi-party/multi-candidate executive elections and direct popular
legislative elections. However, and contrary to a democracy electoral autocracies are
characterized by low levels of electoral integrity. This implies that basic democratic rights such
as the freedom of assembly or of free access of all candidates to the ballot box might be
seriously circumscribed. In addition, the powers of the legislature are limited, indicating the
government’s prerogatives are not really circumscribed. Mexico (1945-87) and currently
Russia (since 2000) are examples of electoral autocracies.
The last and seventh type of political regime is a liberal democracy. In contrast to all
forms of autocracy, citizens in a liberal democracy are asked to recognize the right of public
authority to issue commands, because they have “participated in the process wherein those
commands originated” (Barker 1990: 69). Free and fair elections are, in this sense, not only an
institutional feature of liberal democracy, but they are the procedural legitimation of the rulers
to rule and the legislators to legislate (Luhmann 1972).
Hypotheses
Theoretically, there are several sound arguments in favor of the proposition that modernization
should have a varying influence on the longevity of different regime types. To formulate our
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hypotheses, we use some classics of modernization theory such as Huntington and Almond.
We complement these classics with our own reflections.
H(1): Modernization should have a strong positive influence on the survival of
democracies and communist autocracies.
We use Huntington to build our first hypothesis: For Huntington (1968) “Communist
totalitarian states and Western liberal states” are the most suitable for the survival of democracy,
because they both have “effective bureaucracies, well-organized political parties, a high degree
of popular participation in public affairs, and working systems of civilian control over the
military” (1) Huntington further points out that Communist totalitarian regimes like in the
Soviet Union could weather modernizing processes due to their high degree of modernity just
like Western democracies, while in countries with traditional political systems, like countries
of Asia, Latin America and Africa, socio-economic modernization often leads to violence and
instability, as these social and economic changes “undermine[d] traditional sources of political
authority and traditional political institutions” (Huntington 1968: 5).
H(2): Modernization should have a negative influence on the survival of monarchies and
personlist autocracies.
Pertaining to the survival of monarchies and personalist autocracies, Huntington is also very
vocal. He advances the argument that “relatively primitive and simple traditional political
systems are usually overwhelmed and destroyed in the modernization process” (18). According
to him the future of traditional non-democracies, namely traditional monarchies, facing
modernization is “bleak” (Huntington 1966; Huntington 1968: 191). Rather, the “logical result”
of the “centralization of power and the failure to expand political participation” is “revolt or
revolution” (191). Similarly, Almond und Powell (1966: 40) affirm that a traditional personalist
regime that is less differentiated, is less capable to “accommodate demands for new regulations
and services” and thus less able to cater to the demands of the people than a modern populist
regime with a “developed and differentiated bureaucracy”
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We concur with Huntington, Almond and Powell that monarchies and personalist
autocracies in their pure form are to be seen as the least modern autocratic regimes. They are
characterized by a traditional personalist legitimation without modern political institutions
(parliaments and parties). They do not exhibit an ideology and require a political culture where
the vast majority of people is uninterested in political participation (subject culture). So they
lack channels for the citizens’ feedback or platforms for the solution of conflicts within the
elites. In addition, mass mobilization or ideologization of the ruled people would be
counterproductive for this regime type as this would necessarily challenge the pre-modern
legitimation.
Nevertheless there is an inherent contradiction in this argument in particular when it
comes to monarchies. The Gulf dynasties are examples of contemporary monarchies that seem
to last forever. The simple reason is that the personalist rulers can use the increasing wealth to
invest more money in repression and cooptation. Seen from this lens, these two regime types
might be able to counterbalance the growing instability triggered by modernization, and survive
for a long time.
(H3) Modernization should have a negative influence on the longevity of one party
autocracies
While one-party autocracies are more inclusive than monarchies or personal autocracies, we
still deem them incompatible with modernization (e.g. Huntington und Moore 1970). For sure,
one party autocracies normally hold non-competitive elections and the pure existence of a party
gives citizens an opportunity to take part in the political process. Yet, this political participation
is not real, but rather directed participation in the framework of a society with almost no civil
liberties. One-party autocracies exclude competition of political alternatives and participation
is confined to those who agree with the core of the regime. Hence, we argue that one-party
autocracies are clearly less “modern” than, for example, democracies. Modernization should
rather inhibit than push their survival.
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(H4) Modernization should have a positive influence on the survival of electoral
autocracies
In his seminal work “Modernization and Bureaucratic-Authoritarianism” Guillermo O’Donnell
(1973) was the first political scientist, who argues that what he labels bureaucratic
authoritarianism is very compatible with modernization. Despite the fact that the government’s
prerogatives are not really circumscribed, electoral autocracies such as Singapore have
succeeded to build modern state institutions that can channel the demands pushed by
modernization. Electoral authoritarian regimes also give citizens limited possibilities to
participate in the political realm. Hence demands for regime change should not be as quickly
and as strongly voiced as in one party or personalist autocracies, for example, and electoral
autocracies should rather benefit than suffer from economic modernization.
(H5) Modernization should have a negative influence on the survival of military regimes
Our final hypothesis contracts Huntington (1968). He puts forward the argument that the
military is the most advanced unified “modern” institution in developing countries and in these
countries usually a force of societal modernization. We disagree with this statement and see
relatively long lasting military regimes such as Argentina under Perón (1976-1983) and Chile
under Pinochet (1973-1988) rather as the exception than the rule. Instead for us military
autocracies are like absolutist monarchies and personalist autocracies; they are not only non-
inclusive and non-competitive, but also unable to accommodate demands for societal change.
Research Design
To test whether development or wealth influences the survival of various types of autocracies,
we did not only collect data on our dependent variable, the survival of regimes, and on our main
independent variables (regime type and level of development), but also for two control
variables: economic growth and the presence of natural resources. We add the first control
variable “economic growth” to account for the fact that rapidly declining economic conditions
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could lead to political instability and/ or the breakdown of political regimes (Gasiorowski,
1995; Svolik, 2013). Consequently, we expect that fast economic decline in the form of low or
negative growth might trigger the end of a regime (Przeworski, Alvarez, Cheibub et al., 2000;
Przeworski and Limongi, 1997). Second, we control for non-taxable revenues in the form of
natural resources such as oil or copper. We hypothesize that leaders and regimes with high
amounts of non-taxable income at their disposal can raise enough money for themselves, their
allies and important institutions such as the military or police (Morrison, 2009; Ross, 2001;
Smith, 2004). This renders a leader and regime more independent from the population, which
in turn should increase the regime’s longevity (Crespo Cuaresma, Oberhofer and Raschky,
2011).
Our five variables are operationalized as follows: the dependent variable, regime
survival, measures the years a regime has persisted without interruption based on the
classification described above (for a list of regime types, please see appendix 3). For the first
of our independent variables, we use the natural logarithm of GDP per capita as an indicator of
development. The source of the data for GDP per capita is the recently updated data set of the
Maddison Project (Bolt und Van Zanden 2013). Our second independent variable regime type
follows the classification described above. The first control variable is operationalized by the
yearly growth in a country’s GDP per capita. The data source is the same as for the GDP per
capita data (Bolt und Van Zanden 2013). To code the second and final control variable, we use
a dummy variable, labelled resource intensive based on the coding of Haber and Menaldo
(2011).
For all variables, we collected data for a 65 year period from 1945 to 2010. Our dataset
is as comprehensive as possible. It includes more than 7,000 cases from 162 countries. We only
had to exclude tiny countries such as Monaco and Andorra, for which we could not get data for.
The few larger countries (e.g. East Germany) for which we could not get data for are spread
throughout the world; hence they should not systematically bias our results.
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We propose a three step research process to measure the moderating link between
regime type and development on the survival of various regime types. First, we present some
descriptive statistics of all our variables to give the reader an idea of the spread of these
indicators. Second, we fit three logistic regression analyses to our data (Jenkins 1995). The first
model (i.e. Model 1) includes the binary variable “end of regime” as the dependent variable.
Years during which a regime falls and is replaced by another regime (excluding civil war and
occupation) are coded 1, country years with no regime change 0. On the right-hand side is the
log GDP per capita data as well as six dummy variables for various regimes. These six dummy
variables are democracy, monarchy, communism military regime, personalist autocracy and
one-party autocracy. Electoral autocracies serve as the reference category. We also add an
interaction term between any of the 6 regime type dummies and the log GDP per capita. This
interaction term measures if any of the regime categories’ survival benefits from high
development. A positive and significant interaction term would indicate that this is the case.
The second and third model add the control variables and the time dummies for the various
decades covered, respectively (see Models 2 and 3). These time dummies control for temporal
variation in the breakdown of regimes. Because of the difficulty to directly interpret the
regression weights in logistic regression analysis, we use ‘Clarify‘ a program developed by
Michael Tomz, Jason Wittenberg and Gary King, which allows us to transform the coefficients,
which are represented in log odds into probabilities (Tomz et al. 2003).
Third, and serving as robustness checks of our main models, we use time series logistic
regressions (see models 4 to 6 in appendix 1) and discrete time survival models (models 7 to 9
in appendix 2) (Rabe-Hesketh and Skrondal 2012: 749-796), an approach which was coined by
Beck et al. (1998) “binary time series cross section analysis”. On the left hand side of models
7 to 9 is years elapsed until the breakdown of a regime. The variable is right-censored as some
countries have not experienced regime breakdown in the 65 years covered in this study. The
independent variables are identical to the logistic models; that is the first set of models include
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the log GDP data, the regime type dummies, and the interaction terms (see Model 4 and 7). The
second and the third set of models add the control variables and time dummies, respectively
(see Models 5, 6 and 8, 9).
Results
The descriptive statistics reveal that the average regime falls roughly every 16 years. We also
learn that the regime type democracy was the most frequent regime type. Democracies covered
more than 40 percent of the regimes in the aftermath of the WWII until 2010. The most frequent
autocratic regime type was electoral autocracy, which made up a fifth of all regimes. All other
regimes roughly covered between 5 and 10 percent of all regime types. Models 1 to 9 indicate
how modernization affects any of the 7 regime types covered in this study.
Table 1: Descriptive Statistics3
Mean Standard Dev. Min Max
Average Regime Duration 15.91 15.21 1 65
Liberal Democracy .41 .49 0 1
Electoral Autocracy .21 .41 0 1
Military Autocracy .08 .27 0 1
Monarchy .09 .29 0 1
Communist ideocracy .09 .29 0 1
Personalist Autocracy .06 .23 0 1
One-party autocracy .06 .24 0 1
Log GDP per capita 7.96 1.06 5.83 10.67
Economic Growth .02 .06 -.69 .57
Resource Resilience .30 .46 0 1
3 The descriptive stastistics for the dummy variables are to be interpreted as follows: for example, the value .41
indicates that during the observation period, 41 percent of the countries are democracies, the value .21 for
autocracies implies that 21 percent of the countries were autocracies.
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Table 2: Time series logistic regressions
Model 1 Model 2 Model 3
Liberal Democracy 4.54***
(1.61)
4.74***
(1.62)
4.82**
(1.63)
Military Autocracy -2.50*
(1.51)
-2.60*
(1.62)
-2.56*
(1.53)
Monarchy 1.98
(2.26)
2.46
(2.27)
2.40
(2.30)
Communist ideocracy -6.58**
(2.90)
-6.34**
(2.92)
-6.38**
(2.95)
Personalist Autocracy 2.10
(2.44)
2.39
(2.45)
2.27
(2.45)
One-party autocracy -.30
(1.95)
-.05
(1.97)
-.29
(1.99)
Log GDP per capita -.30**
(.13)
-.28**
(.13)
-.27**
(.13)
Economic Growth -2.61***
(.93)
-2.45**
(.95)
Resource Resilience .02
(.13)
.02
(.13)
Interaction Log GDP-Democracy -.76***
(.21)
-.79***
(.21)
-.80***
(.22)
Interaction Log GDP-Military Regime .42**
(.20)
.43**
(.20)
.43**
(.20)
Interaction Log GDP-Monarchy -.42
(.31)
-.48
(.31)
-.47
(.31)
Interaction Log GDP-Communism .71*
(.37)
.68*
(.37)
.69*
(.37)
Interaction Log GDP-Personalist Autocracy -.35
(.35)
-.40
(.35)
-.38
(.35)
Interaction Log GDP-One-party autocracy .04
(.27)
.004
(.28)
.04
(.28)
1950s -.49
(.45)
1960s -.24
(.43)
1970s -.35
(.43)
1980s -.48
(.43)
1990s -.19
(.42)
2000s -.62
(.44)
Constant -.26
(.96)
-.38
(.98)
-.02
(1.07)
Log Likelihood -1175.26 -1162.05 -1158.69
N 7107 6962 6962
Standard errors in parentheses, *p<.1, **p<.05, ***p<.01
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The results from of our three main regression analyses provide nuanced, but interesting
results. They confirm the first part of H (1); they highlight that wealth prevents democracies
from falling. However, they disconfirm the second part of H (1); that is communism’s
likelihood to fall increases with development. In addition, we find support for H (5); that is
military regimes are more susceptible to fall the richer they are. For the three remaining
hypotheses, the regression coefficients highlight non-statistically significant relationships.
To highlight and explain these findings, models 1 to 3 illustrate that democracy has a
positive sign and is statistically significant. The Log GDP per capita indicator has the expected
statistically significant negative sign and the interaction term the expected statistically
significant negative sign, as well. This implies that poor democracies have a higher probability
to break down, but this probability decreases the richer the democratic country becomes. In
contrast, the dummy variable for communism has a negative sign, highlighting that communist
countries are less likely to fall, the log GDP per capita variable is still negative, but the
interaction term between the two is positive. This combination indicates that rich communist
countries have a higher likelihood to break down than poorer communist ideocracies. For
military regimes, the interpretation is as follows. The regression weight for military regimes is
statistically significant and positive highlighting that military regimes have a higher chance to
fall than other regime types. The positive sign of GDP per capita would indicate that material
affluence moderates this influence. However, the interaction term is again positive and
statistically significant illustrating that for affluent countries the negative influence of military
regimes on regime survival is reinforced.
Table 3, which displays the probability transformations of the log odds from model 3
(i.e. the full model with all control variables) highlights the substantive influence of these
relationships. For example, these probability transformations predict that a liberal democracy
in a country with a log GDP of 6.9, which roughly corresponds to a per capita GDP of $ 1,000
has a 3.7 percent chance to fall. This likelihood becomes basically 0 at a log GDP per capita of
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8.5 or a GDP of roughly $ 5,000. This result strongly confirms Prezworski’s various
publications on the “impossibility” of rich democracies to fall. For the other two significant
relationships, model 3 predicts that the likelihood of a communist regime to fall increases from
a mere 1.5 percent for a very poor country with an average material wealth of $1,000 to 6
percent for a relatively wealth country with an average GDP per capita of $20,000. For a
military regime, the probability of its annual breakdown increases from 10 percent for a poor
country to 16 percent for a relatively wealthy country. For three other regime types (e.g.
monarchies, electoral autocracies, and one party autocracies), the probability transformations
reveal that the likelihood of these regime types to fall seems to moderately decrease with
material affluence. However, neither of these differences/ changes is statistically different from
zero. Finally, table 3 highlights that the fall of one party autocracies do not seem to be
influenced at all by the developmental level of a country.
Table 3: Predicted probability of regime end
Log per capita
GDP = 6.9
(per capita GDP
1000)
Log per capita
GDP = 8.5
(per capita GDP
5000)
Log per capita
GDP = 9.9
(per capita GDP
10000)
Log per capita
GDP = 9.9
(per capita GDP
20000)
Electoral
Autocracy
7.1% 4.8% 4.1% 3.5%
Liberal
Democracy
3.7% .7% .3% .2%
Military
Autocracy
10.2% 13.0% 14.6% 16.4%
Monarchy 3.3% 1.1% .7% .5%
Communist
ideocracy
1.5% 2.9% 4.1% 6.0%
Personalist
Autocracy
7.1% 5.2% 4.7% 4.4%
One-party
autocracy
14.5% 13.8% 13.5% 13.3%
The regression models and the corresponding probability transformation in table 3
further provide very interesting results pertaining to the longevity of various regime types. For
example, the models show that the existing monarchies, in particularly, the wealthy Gulf
17
dynasties are very unlikely to fall. In the 21st century it is probably impossible that new
monarchies are installed, but our analysis predicts that the existing monarchies might still
survive for the next decades and possibly even centuries. More nuanced the future of the
existing communist regimes (e.g. China and Laos) might not look as promising as the leaders
there might assume. In particular, our analyses hints that the more a communist regimes
becomes developed, the higher its chances of falling. This implies that the years of long lasting
communist regimes such as China might be counted. Equally nuanced, our study highlights that
the prospects of two remaining regime types – personalist and electoral autocracies might not
look as bad, as our theory of legitimation predicts; their likelihood of falling fluctuates between
7 and 4 percent, which still indicates relative stability.
Our control variables behave as follows. First, we find high economic growth to be a
stabilizing factor for regime survival. In contrast, the presence of natural resources in the form
of a rentier state does not influence the longevity of autocracies. Both with regards to our
variables of interest, as well as our control variables, the robustness checks (see models 4 to
9appendix 1 and 2) confirm models 1 to 3. This gives us confidence that the relationships
described here are solid and in line with reality.
Conclusion
This article has made two contributions to the literature on modernization theory, one small
contribution and one more significant contribution. First, and this is the small contribution, it
has confirmed Prezeworki’s seminal findings, made 20 years ago, that affluent democracies do
not fall. This finding is probably now one of the “iron laws” in the discipline of political science.
Second, and this is the larger contribution, this article is one of the first studies to
comprehensively unpack modernization theory’s impact on the survival of various types of
autocracies. We find that except for two cases, communist autocracies and military systems,
modernization does not necessarily hurt the survival of these not democratic regimes. Rather,
contrary monarchies, electoral autocracies, and personal autocracies see their chances of
18
survival rather increase than decrease, even if this relationship is not statistically significant in
the models. Yet, communist regimes and military regimes see their chances of survival
significantly decrease. As totalitarian regimes, these types of governments appear to lack the
legitimation necessary to cope with the demands of modernity.
There are several practical repercussions to take away from this study. First,
modernization is no panacea for the establishment of democracy. Rather most types of
autocracies are amenable enough to repress, coopt or amend the demands triggered by
modernization.. Second, and relatedly this implies for theory that modernization is much less
deterministic than (early) proponents of the theory including Lipset or Almond suggested. It is
neither a prerequisite for the installation of democracy nor does it trigger an “automatic” shift
in values away from materialistic and transitional values and towards post-modern values in
the way Inglehart and co-authors assume. Rather modernization processes might be complex,
dynamic and non-linear. Future research might look into more detail into this complex nature;
both in relation to the emergence and survival of various regime types. .
19
Appendix 1: Table 3: Time series logistic regressions
Model 1 Model 2 Model 3
Liberal Democracy 4.75***
(1.70)
4.92***
(1.70)
4.99**
(1.71)
Military Autocracy -2.07
(1.61)
-2.25
(1.61)
-2.23
(1.63)
Monarchy 1.96
(2.39)
2.43
(2.40)
2.43
(2.43)
Communist ideocracy -6.53**
(3.09)
-6.29**
(3.10)
-6.30*
(3.12)
Personalist Autocracy 1.74
(2.62)
1.97
(2.62)
1.84
(2.62)
One-party autocracy -.25
(2.09)
-.05
(2.11)
-.27
(2.12)
Log GDP per capita -.29**
(.14)
-.27*
(.14)
-.27*
(.14)
Economic Growth -2.55***
(.96)
-2.38**
(.97)
Resource Resilience .01
(.16)
.01
(.16)
Interaction Log GDP-Democracy -.80***
(.22)
-.82***
(.22)
-.84***
(.23)
Interaction Log GDP-Military Regime .36**
(.21)
.38*
(.21)
.38*
(.22)
Interaction Log GDP-Monarchy -.41
(.32)
-.47
(.32)
-.47
(.33)
Interaction Log GDP-Communism .70*
(.39)
.67*
(.39)
.67
(.40)
Interaction Log GDP-Personalist Autocracy -.31
(.37)
-.35
(.37)
-.33
(.37)
Interaction Log GDP-One-party
autocracyOne-party autocracy
.04
(.29)
.01
(.29)
.04
(.30)
1950s -.45
(.45)
1960s -.19
(.43)
1970s -.30
(.43)
1980s -.42
(.44)
1990s -.11***
(.43)
2000s -.54
(.45)
Constant -.39
(1.05)
-.45
(1.06)
-.19
(1.15)
Log Likelihood -1171.00 -1158.42 -1155.20
N 7107 6962 6962
Standard errors in parentheses, *p<.1, **p<.05, ***p<.01
20
Appendix 2: Table 4: Survival analysis
Model 1 Model 2 Model 3
Liberal Democracy 3.79**
(1.58)
4.02**
(1.59)
3.85**
(1.63)
Military Autocracy -4.63***
(1.48)
-4.76***
(148)
-4.59***
(1.55)
Monarchy .19
(2.30)
.87
(2.30)
-.42
(2.33)
Communist ideocracy -8.46**
(2.95)
-8.59**
(2.97)
-9.33**
(3.02)
Personalist Autocracy 2.04
(2.49)
2.60
(2.50)
2.42
(2.55)
One-party autocracy -3.64*
(1.86)
-3.33*
(1.86)
-4.11**
(1.92)
Log GDP per capita -.76***
(.13)
-.73***
(.14)
-.75***
(.14)
Economic Growth -3.38***
(.94)
-3.46***
(.95)
Resource Resilience .15
(.12)
.18
(.13)
Interaction Log GDP-Democracy -.67***
(.21)
-.70***
(.21)
-.67***
(.22)
Interaction Log GDP-Military Regime .72***
(.20)
.74***
(.20)
.71**
(.21)
Interaction Log GDP-Monarchy -.26
(.31)
-.35
(.31)
-.19
(.32)
Interaction Log GDP-Ideocracy .88**
(.37)
.90**
(.38)
1.00***
(.38)
Interaction Log GDP-Personalistic Autocracy -.38
(.35)
-.46
(.36)
-.42
(.36)
Interaction Log GDP-One-party
autocracyOne-party autocracy
.50*
(.26)
.45*
(.26)
.56**
(.27)
1950s -1.43***
(.42)
1960s -1.41***
(.40)
1970s -1.79***
(.40)
1980s -2.12***
(.41)
1990s -1.69***
(.40)
2000s -2.30***
(.42)
Constant .85
(.97)
.61
(.98)
2.54**
(1.12)
Log Likelihood -1315.12 -1302.81 -1281.74
N 7107 6962 6962
Standard errors in parentheses, *p<.05, **p<.01, ***p<.001
21
Appendix 3: The coding of regimes
Monarchy: Afghanistan 46-72, Bahrain 71-10, Bhutan 49-10, Brunei Darussalam 84-10,
Burundi 62-64, Cambodia 55-69, 93-96, Central African Rep. 76-78, Egypt 46-51, Ethiopia
46-73, Iran 47-52, 55-78, Iraq 46-57, Jordan 46-10, Kuwait 61-09, Libya 51-68, Liechtenstein
46-10, Maldives 65-67, Monaco 46-10, Morocco 56-60, 63-10, Nepal 46-05, 02-2005, Oman
46-10, Qatar 71-10, Samoa 62-06, Saudi Arabia 46-10, Swaziland 68-10, Tonga 70-10,
United Arab Emirates 71-10, Yemen 48-61, Yemen, North 46-61
Ideocracy
Subtype Communist Ideocracy: Albania 46-89, Angola 75-90, Benin 75-89, Bulgaria 47-89,
Cambodia 77-78, 81-90, China 50-10, Congo-Brazzaville 70-89, Cuba 61-10, Czechoslovakia
48-67, 69-88, Ethiopia, 87-90, GDR 49-88, Grenada, 79-82, Hungary 48-55, 57-88, Korea,
North 48-10, Laos 75-10, Mongolia 46-88, Mozambique 75-90, Nicaragua 80-89, Poland 47-
88, Romania, 48-88, Soviet Union 46-90, Vietnam 77-10, Vietnam, North 54-75, Yemen, South
67-89, Yugoslavia 46-89
Subtype Islamist Ideocracy: Afghanistan 97-00, Iran 82-10
Military Autocracy: Algeria 65-75, 92-94, Argentina, 57, 66-72, 76-82, Bangladesh 77, 82-85,
Benin 65-69, 72-74, Bolivia 46, 51, 64-65, 69-78, 80-81, Brazil 65-84, Burkina Faso 66-76, 80-
82, Burundi 87-91, 97, Central African Republic 81-86, Chad 75-77, Chile 73-88, Colombia
53-57, Comoros 99-2001, Congo-Brazzaville 68-69, Ecuador 63-65, 72-78, El Salvador 46-47,
50-51, 60-61, Ethiopia 76-86, Fiji 87-91, 06-10, Ghana 67-68, 72-77, Greece 67-73, Guatemala
54-57, 82-84, Guinea 84-90, Guinea-Bissau 80-83, 04, Haiti 91-93, Honduras, 63-70, 72-79,
Indonesia 68-97, Iraq 58-78, Korea, South 61-62, 72-79, Lesotho 86-92, Liberia 80-86,
Madagascar 72-74, Mali 68-78, Mauritania 78-91, 05-06, 08-09, Myanmar (Burma) 62-10,
Nicaragua 73, Niger 74-88, Nigeria 66-77, 83-97, Pakistan 58-61, 69-70, 77-87, 99-2007,
Panama 68-72, 74-78, Paraguay 46-47, Peru 48-50, 62, 68-77, Portugal 74-75, Rwanda 73-77,
Sierra Leone 67, 92-95, Somalia 69-91, Spain 46-74, Sudan 58-63, Suriname 81-86, Syria 51-
53, Taiwan 49-74, Thailand 46-67, 71-72, 76, 91, 06, Turkey 60, 71-72, 80-82, Uruguay 73-83,
Venezuela 48-57, Vietnam, South 63-64, Yemen, North 62-78
Personalist Autocracy: Afghanistan 73-77, 10, Benin, 67-74, 66-58, Burkina Faso 83-90,
Burundi 66-83, Central African Republic 66-78, 03-04, Chad 85-90, 92-95, Comoros 80-89,
Congo-Brazzaville 97-01, Congo-Zaire 66-91, Ecuador 70-71, Equatorial Guinea 71-92,
Eritrea 93-10, Ghana 81-90, Guinea-Bissau 80-83, Haiti 64-85, Indonesia 52-54, 59-67, Iraq
79-02, Lesotho 70-85, Liberia 90, Libya 69-10, Madagascar 72-75, Malawi 71-93, Maldives
69-04, Mozambique 91-93, Nicaragua 46-50, 72-73, Panama 73 Philippines 94-2002, Rwanda
78-80, Somalia 69-90, Sudan 89-10, Suriname 75, Syria, 63-10, Togo 67-90, Tunisia 56-86,
Turkmenistan 99-2005, Uganda 71-78, 87-95, Venezuela 48-57, Yemen, North 79-89
One-party Autocracy: Algeria 63-64, 77-91, Bangladesh 79-81, Burkina Faso 60-65, Burundi
82-86, Cameroon 66-81, 83-90, 09, Cape Verde, 75-89, Central African Republic 62-65, 87-
92, Chad 62-74, 09-10, China 46-47, Congo-Brazzaville 63-67, 09-10, Cote d’Ivoire 60-89,
Djibouti 77-91, Dominican Republic 48-60, Egypt 53-75, 09-10, Equatorial Guinea 70, 09-10,
Gabon 68-89, 09-10,Gambia 09-10, Ghana 64, Guinea 59-83, 09-10, Guinea-Bissau 74-79, 84-
90, Haiti 57-63, Kenya 82-91, Malawi 64-70, Mali 79-90, Mauritania 64-77, Niger 60-73, 89,
Rwanda 65-72, 81-93, Sao Tome 75-89, Seychelles 79-90, Sierra Leone 78-90, Sudan 72-83,
22
Syria 00-10, Taiwan 75-88, Tanzania 65-94, Tunisia 75-78, Turkmenistan 91-98, 06-10,
Uganda 69-70, Uzbekistan 91-10, Zambia 72-89
Electoral Autocracy: Afghanistan 08-10, Albania 96-01, Algeria 89-91, 97-10, Angola 10-10,
Argentina 48-54, 58-61, 63-65, Armenia 95-10, Azerbaijan 92-10, Bangladesh 86-90, Belarus
91-10, Benin 60-62, Bolivia 47-50, 56-63, 66-68, Bulgaria 46, Burkina Faso 91-10, Burundi
93-95, 08-10, Cambodia 72-74, 98-10, Cameroon 61-65, 91-08, 10, Central African Republic
60-61, 91-92,05-10, Chad 60-61, 97-08, Colombia, 46-47, Comoros 90-94, Congo-Brazzaville
60-62, 92-96, 03-08, Congo-Zaire 06-10, Cote d´Ivoire 90-98, 00-01, 08-10, Croatia 91-98,
Cuba 46-51, 55-58, Djibouti 92-10, Dominican Republic 46-47, 67-77, Ecuador 48-62, 68-71,
00-01, Egypt 76-08, El Salvador 52-59, 62-78, Equatorial-Guinea 69, 93-08, Ethiopia 95-10,
Gabon 60-66, 91-08, Gambia 97-08, Georgia 91-03, Ghana 60-63, 70-71, 93-00, Guatemala
46-53, 58-62, 66-81, 86-92, Guinea 95-08, Guinea-Bissau 91-97, Guyana 66--91, Haiti 45-47,
51-55, 94-98, 00-03, 07-10, Honduras 45-55, 57-62, Indonesia 55-56, 99-03, Kazakhstan 91-
10, Kenya 63-81, 92-2001, Korea, South 48-51, 52-59, 63-71, 81-86, 88-97, Kyrgyzstan 91-10,
Lebanon 46-74, 05-10, Lesotho 98-01, Liberia 46-79, 87-89, 97-02, Madagascar 60-71, 76-90,
Malaysia 72-07, Maldives 05-07, Mali 60-67, Mauritania 60-63, 92-04, 08, Mexico 45-96,
Mozambique 94-10, Nicaragua 51-72, 74-78, 84-89, Niger 90, 96-98,00-10, Nigeria 60-65, 79-
82, 99-07, Pakistan 48-55, 62-68, Panama 46-48, 55-67, 79-87, Paraguay 48-88, Peru 46-47,
51-55, 63-67, 93-99, Philippines 46-71, 78-85, Portugal 46-73, Russia 00-10, Rwanda 62-64,
03-10, Senegal 60-61, 63-99, Serbia and Montenegro 93-99, Seychelles 91-10, Sierra Leone
68-70, 73-76, 91, Singapore 65-10, South Africa 46-91, Sri Lanka 48-10, Sudan 65-68, 84, 86-
88, Tajikistan 92-10, Tanzania 61-64, 95-10, Thailand 75, 79-90, Togo 60-66, 04-10, Turkey
54-59, Uganda 67-68, 80-84, 96-10, Uruguay 46-51, Venezuela 46-47, 59-68, 06-10, Vietnam,
South 56-62, Yemen 93-10, Zambia 64-71, 90, 93-2000, Zimbabwe 80-10
Liberal Democracy: Albania 92-95, 02-10, Andorra 93-10, Antigua and Barbuda 81-10,
Argentina 73-75, 83-10, Australia 46-10, Austria 46-10, Bahamas 73-10, Bangladesh 91-06,
09-10, Barbados 66-10, Belgium 46-10, Belize 81-10, Benin 91-10, Bolivia 82-10, Botswana
66-10, Brazil 47-63, 88-10, Bulgaria 90-10, Canada 46-10, Cape Verde 91-10, Central African
Republic 93-02, Chile 46-72, 90-10, Colombia 46-47, 58-10, Comoros 04-10, Costa Rica, 46-
47, 49-10, Croatia 00-10, Cuba 46-51, Cyprus 60-62, 69-10, Czech Republic 93-10,
Czechoslovakia 46, 90-92, Denmark 46-10, Dominica 78-10, Dominican Republic 78-10, East
Timor 06-10, Ecuador 79-99, 02-10, El Salvador 84-10, Estonia 91-10, Fiji 70-86, 92-99, 2001-
2005, Finland 46-10, France 45-10, Gambia 65-93, Georgia 04-10, Germany 49-10, Ghana 79-
80, 01-10, Greece 46-66, 75-10, Grenada 74-78, 84-10, Guatemala 96-10, Guinea-Bissau, 00-
02, 05-10, Guyana 92-10, Honduras 57-62, 82-10, Hungary 90-10, Iceland 46-10, India 50-10,
Indonesia 04-10, Ireland 46-10, Israel 48-10, Italy 48-10, Jamaica 62-10, Japan 52-10, Kenya
02-10, Kiribati 79-10, Korea, South 60, 98-10, Laos 58, Latvia 91-10, Lesotho 66-69, 93-97,
02-10, Liberia 09-10, Lithuania 91-10, Luxembourg 46-10, Macedonia 91-10, Madagascar 92-
10, Malawi 94-10, Malaysia 57-68, 08-10, Maldives 08-10, Mali 92-10, Malta 64-10, Marshall
Islands 86-10, Mauritius 68-10, Mexico 97-10, Micronesia 86-10, Moldova 91-10, Mongolia
92-10, Montenegro 06-10, Myanmar (Burma) 48-61, Namibia 90-10, Nauru 68-10, Nepal 08-
10, Netherlands 46-10, New Zealand 45-10, Nicaragua 90-10, Niger 93-95, 2000-10, Nigeria
08-10, Norway 46-10, Pakistan 73-76, 88-98, 08-10, Palau 94-10, Panama 90-10, Papua-New
Guinea 75-10, Paraguay 92-10, Peru 56-61, 63-67, 80-91, 01-10, Philippines 46-71, 87-10,
Poland 91-10, Portugal 76-10, Romania 92-10, Russia 93-98, Samoa 07-10, San Marino 46-10,
Sao Tome and Principe 91-10, Senegal 00-10, Serbia 06-10, Serbia and Montenegro 2000-02,
Seychelles 76, 07-10, Sierra Leone 61-66, 02-10, Slovakia 93-10, Slovenia 91-10, Solomon
Islands 80-99, 04-10, Somalia 60-68, South Africa 94-10, Spain 78-10, Sri Lanka 60-10, St.
Kitts and Newis 83-10, St. Lucia 79-10, St. Vincent and the Grenadines 79-10, Sudan 56-57,
23
Suriname 76-79, 88-89, 91-10, Sweden 46-10, Switzerland 46-10, Taiwan 96-10, Thailand 92-
05, 08-10, Trinidad & Tobago 62-10, Turkey 46-53, 61-70, 73-79, 83-10, Tuvalu 78-10,
Ukraine 91-10, United Kingdom 46-10, United States of America 46-10, Uruguay 52-70, 85-
10, Vanuatu 80-10, Venezuela 69-04, Zambia 91-92, 01-10,
24
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