Do democratic institutions forge a demand for democracy?
An investigation of Latin American citizens attitudes
Jakson Alves de Aquino
Federal University of Ceará (Brazil)
Michigan State University (USA)
[email protected]
Presented at the
73 Annual Midwest Political Science Association Conference
Chicago, April 16–19, 2015
rd
Abstract
Recent research on Latin America have found that younger people are willing to live under
democracy less than older people. The economic performance of political regimes is sometimes considered important to define these attitudes. In this research, I used data from AmericasBarometer and other country level data to calculate variables that measure respondent’s exposure to both democracy and economic events. Using multilevel models, I found that higher
demand for democracy by older people is dependent on their exposure to democracy during
their adult life, and I did not find long term effects of economic events. I interpret the findings
as meaning that people living under democracy are subject to socialization processes that make
them demand democracy. The methodology used in this research has the the potential of helping to disentangle how much of the influence of national events and institutions operates at the
national and at the individual levels.
1
Introduction
Elites, because not numerous, can much more easily overcome collective action problems than the
mass of lower class people. Usually, changes in the political regime are pushed by the elites, but they
can not succeed if the mass offers strong opposition. Hence, the strength of common citizens desire
to live under a democratic regime is important for both democratization and democracy breakdown.
One of the basic drives of life is the willingness to survive, and, at least in capitalist societies,
people keep striving to improve their standard of life far beyond the minimum requirements for
survival. In a contemporary capitalist society, the economic growth and the distribution of wealth
are two of the national variables most correlated with survival and standard of life, and not surprisingly, national economic performance is usually seen as a key factor to make people decide whether
to support a political regime. Once survival is no longer a problem, the importance of freedom increases, and people living under democratic regimes may learn to appreciate the peaceful resolution
of conflicts and the higher degree of freedom that characterize democracies when compared with
authoritarian regimes.
In this article, I investigate the long term effects of economic performance and political regimes
on individuals manifest demand for democracy in twelve Latin America countries. I use AmericasBarometer survey data to measure the demand for democracy, and combine these data with
country level variables to measure how much individuals have experienced democracy and how the
economy has performed during their adult lives.
2
Demand for democracy
Mattes and Bratton (2007, footnote 3) argue that generalized notions of system support sometimes
blends regime preferences and regime evaluations, and, in this article, I opted for using the expression Demand for democracy to refer to how much people are willing to live under a democratic
regime. According to Chu et al. (2008, p. 77), the survey question most widely used to measure
demand for democracy is:
1
Which of the following statements do you agree with the most:
1. For people like me it doesn’t matter whether a government is democratic or non-democratic, or
2. Democracy is preferable to any other form of government, or
3. Under some circumstances an authoritarian government may be preferable to a democratic
one.
The demand for democracy is higher when measured by abstract questions such as the above
one. More specific contexts give rise to weaker manifest preference for democracy (Chang, Chu
and Park, 2007; Mattes and Bratton, 2007, p. 72).
Canache (2012) examined respondents’ answers to an open question about the meaning of
democracy from the 2006–2007 AmericasBarometer and found that the word democracy may be
associated to political concepts, such as freedom, rule of law, political equality and participation,
but also to societal outcomes like economic prosperity and social equality, and negative meanings.
According to Inglehart (2003), economic development creates favorable conditions for democratization but democratization is not necessarily favorable to economic development. People worried with survival are more prone to support any political regime that seems promising in raising
their standard of living than people who do not see any important threat to the satisfaction of their
basic material needs. The later have higher propensity to value freedom of expression, tolerate cultural diversity and trust other people. Therefore, they form a better base of support for democracy.
In summary, economic development nurtures self expression values and these, then, form a better
environment for democracy to thrive (Inglehart, 2003, p. 56). This theory has found support in other
investigations. For example, using data from the World Values Survey from 1997, Ribeiro (2008)
has found a positive association between demand for democracy and post-materialist values among
Brazilians. Also, according to Andersen (2012, p. 28), people of higher income support democracy
more than people of lower income, especially in countries with low economic inequality.
However, Chu et al. (2008) have found empirical evidence that challenges the modernization
theory:
2
Contrary to the received view | that a rising level of economic development promotes “self-expression values” such as freedom of speech and participation in the decision-making process, we found that people’s economic evaluations had the strongest
impact on support for democracy in the high-income countries, and the weakest impact
in the low-income countries (Chu et al., 2008, p. 81–82).
If people support democracy because they believe that it will foster economic development and
decrease economic inequality, the support will be withdrawn if such expectations are not fulfilled in
a few years after democratization. In this case, it is expected an increase in the approval of populist
leaders that defend that the institutions of liberal democracy—such as partisan competition and
subordination of president to Congress—are more an obstacle than a way of realizing the peoples’
desires (Bratton and Mattes, 2001, p. 448; Seligson, 2007, p. 82).
On the contrary, if people support democracy because they believe in its intrinsic value, the
chances that the regime will survive to economic crises are higher (Mattes and Bratton, 2007).
Chang, Chu and Park (2007, p. 75) and Chu et al. (2008, p. 85) argue that it is harder for a citizen of
a democratic country to be happy with its democracy if the country was governed in the recent past
by an economically successful authoritarian regime, and according to Chang, Chu and Park (2007,
p. 77), people in East Asia developing countries became disillusioned with democracy because
economic and social conditions did not improve as expected after democratization.
Some authors argue that Latin America citizens are particularly worried about the economic
performance of their democracies (Lagos, 2008; Fernandez and Kuenzi, 2010), and Benton (2005)
has confirmed that Latin American voters punish incumbents by voting in nonincumbents when
they are blamed for economic adversities while Chu et al. (2008, p. 84) observe that in different
regions of the world economic and political factors have different weights in the explanation of
people’s evaluation of democratic regimes:
Trust in democratic institutions and the free and fair voting process does the most
to encourage popular approval of the way that democracy works. People’s evaluation
of national economic conditions also matters, and its impact lags only slightly behind
3
that of the various political indicators […]. This global pattern holds up well among
Africans, Asians, and Arabs. In Latin America, by contrast, perceived national economic conditions matter more than political factors, but not by much. (Chu et al., 2008,
p. 84)
The economies of Latin America colonies were organized to produce and transfer raw materials
to their metropolitan states. The enslavement of both native and African people was ubiquitous.
The cultural inheritance of the colonial era is a highly hierarchical society and also a distinction
between poor and rich people so strong that poor non white people are seen as somewhat less than
humans and are treated with notably less dignity than the rich decedents of white Europeans. This
context exerts a strong pressure over democracy. As Lagos argues, Latin America is a region with
[…] extremely limited social mobility: 86 percent of those born in the last generation to parents with only primary education themselves attain only primary education.
[…] An individual’s future is determined by birth, and people expect democracy to
change this (Lagos, 2008, p. 124).
In a country with an authoritarian regime, high social inequality may have strong effects on the
prospects of democratization. While most people may see a change in the regime as an opportunity
to decrease social inequality, the elites may be afraid of being more heavily taxed with the democratization of the society. If the society is democratic, high inequality increases the risk of breakdown
because the elites would not find strong resistance from the mass of people (Houle, 2009; Freeman and Quinn, 2012; Córdova and Seligson, 2010). The perspective of democratization is higher
for authoritarian countries with turbulent political past, with a history of relatively frequent regime
transitions. According to Houle (2009, p. 615), however, the number of regime transitions is not a
key predictor of democratic consolidation.
Zarate Tenorio (2014) investigated the relationship between collective protest and social spending in Latin America and found that the organized labor was successful in making governments
spend more in social security and welfare while protest by other groups does not affect spending in
4
education and health. Hence, a democratic environment is favorable for decreasing social inequality
not only because voters may choose leaders who promise egalitarian policies, but also because the
disadvantaged have more freedom to protest and, consequently, to influence the decision making
process.
Berger and Luckmann (1966) presented a sophisticated theory on how people develop patterns
of behavior during daily interactions with other people, and how they become unconscious of the
origins of their social habits. In Berger and Luckmann’s theory, the patterns of behavior acquired
during the first years of life—from the interactions with parents and other persons highly important
for infants—have an enduring imprinting in individuals personality. They refer to this first stage of
becoming a member of the society as primary socialization.
Although children and adolescents are not emancipated citizens yet, periodic elections make
their parents’ political preferences more salient and may contribute to a vision of electoral democracy as something normal (Sears and Valentino, 1997). The national political regime might be used
as a model on how to make decisions and, thus, contribute to the institution of democratic procedures within other institutions, such as schools (Torney-Purta, 2002). An environment of freedom
of speech may also favor open classroom discussions, which help in the development of sophisticated reasoning on social issues by the use of logic to check the internal coherence of arguments
and of empirical evidences to support arguments. Moreover, open discussions help people to understand and tolerate other’s positions (Rossi, 2006, p. 113). In summary, if the institutions of Latin
American political regimes successfully indoctrinate children and teenagers with the values most
favorable to the maintenance of political systems at theses early phases of life, we will find a correlation between demand for democracy and how authoritarian or democratic the regime was when
individuals were young.
However important the primary socialization may be to the formation of the personality of an
individual, politics usually is not a subject very frequently discussed in most homes. Politics matters more when individuals are mature enough to understand abstract concepts such as government,
political party, and democracy, and when their interactions with strangers become more frequent.
5
Thus, over the basic values developed at their parents’ home, individuals political ideas may evolve
mainly after primary socialization is no longer the main process shaping the individual values and
attitudes. This process of continuous adaptation to the larger society, which goes on for the individuals’ entire life, Berger and Luckmann called secondary socialization. If the influence of political
regimes are exerted mainly through processes of secondary socialization, we will find significant
correlation between the contact the individual has had during their adult lives with democratic and
autocratic regimes. Regime transitions may be periods particularly disruptive to the daily lives of
common citizens, and may also have their own influence on attitudes formation. I devise two possibilities: (1) individuals who witnessed many regime transitions become used to them and see the
overthrow of elected officials as a normal way of solving national problems, or, on the contrary, (2)
they think that it is not worthwhile the violence sometimes required to depose a chief of State and
free and fair elections would be a proper way of choosing a new leader.
As we have seen, some authors argue that the evaluation of how competent the government was
in dealing with the national economy is an important criterion used by people to choose among
candidates in national elections. But what is the long term impact of the national economy over individuals attitudes toward democracy? Do people perform some kind of either conscious or unconscious computation of how good for the economy the political regimes were during the democratic
and authoritarian periods under which they have lived? If the answer to this question is yes, we
should find a positive correlation between demand for democracy and an experience of democracy
and high economic growth, low rates of inflation and reduction of social inequality and/or autocracy and low economic growth, high rates of inflation and increase in inequality (and the inverse: a
negative correlation with an experience of democracy and low economic growth, high inflation and
increase in inequality and/or autocracy and high growth, low inflation and decrease of inequality).
The process of socialization (primary and secondary) is far from being an atomistic process
in which individuals develop opinions and attitudes based solely on their own experiences. They
talk with each other, share their experiences and form their opinions together. According to Jost,
Ledgerwood and Hardin (2008, p. 173),
6
“people are motivated to achieve mutual understanding or ‘shared reality’ with specific others in order to (i) establish, maintain, and regulate interpersonal relationships
[…] and (ii) perceive themselves and their environments as stable, predictable, and
potentially controllable”.
If this phenomenon happens in a national scale and is strong enough to overcome more individualistic and dyadic processes of socialization, we could find correlation between two variables only
at the national level. Alternatively, this process of cultural transmission may find strong boundaries
within countries (Flockhart, 2006), and in this case we would find the development of national
class cultures. The poor people could have values and attitudes diverse from the most affluent; the
organized working class and non organized laborers could have different ideologies.
In addition to country level variables, used as indicators of historic, social and political contexts,
many individual level variables have been pointed by the literature as having explanatory power on
attitudes toward democracy and will be used in this investigation as control variables: perception of
corruption, trust in institutions, interpersonal trust, evaluation of government performance, respondent’s ideological position feelings of insecurity due to high criminality rate, and others (Bratton
and Mattes, 2001; Bohn, 2012; Doyle, 2011; Chang, Chu and Park, 2007; Fernandez and Kuenzi,
2010; Gunther and Monteiro, 2003; Mattes and Bratton, 2007; Seligson, 2007). Specially interesting for this research is age, since recent studies on public opinion on democracy in Latin America
have found that the youth is less supportive of democracy than older adults, a fact that undermines
the prospects of democracy consolidation (Lagos, 2008, p. 112; Seligson, 2007, p 92). Seligson,
for instance, says:
Across the region as a whole […] the results regarding age and populism should be
seen as sobering. For they suggest that as the young people of today become tomorrow’s
electoral majorities, populism’s appeal against the many checks, balances, rules, and
frustrations of liberal democracy will only grow (Seligson, 2007, p. 92).
7
3
Data
The 2012 AmericasBarometer dataset has 494 variables and 28021 cases, corresponding to interviews conducted in 18 countries (LAPOP, 2012).1 However, I had to eliminate the data from five
countries due to either missing or invariability of data at the country level: Belize is missing from
Polity IV, Costa Rica and Jamaica have no variation in Polity IV scores, and Guyana, Haiti and
Nicaragua are missing from Penn Table. I also deleted 136 cases with missing age and 302 cases
with more than 2 missing values among the 4 variables that I used to build the index of demand for
democracy, remaining 18027 cases in the dataset.
In 2012, AmericasBarometer asked 13 questions on attitudes toward democracy. A principal
component analysis including all 13 questions reveals that the questions’s replies represent four
distinct dimensions of attitude toward democracy, but in this paper I will only explore the first
dimension, which corresponds to a demand for democracy and is the dependent variable explained
in this paper.2
The variables reflecting the political and economic contexts were calculated from the historical
series of Polity IV in 2012 (Marshall, Jaggers and Gurr, 2014), Gini index in 2011 (Solt, 2014),
Gross Domestic Product in 2011 (Feenstra, Inklaar and Timmer, 2013) and Inflation (THE WORLD
BANK, 2015). Figure 1 shows the variation of Polity IV (black line), Gini Index (red) from 1960
to 2011. The Gini data include information on how reliable the data is and the band following the
red line indicates the 95% confidence interval of the Gini value (Feenstra, Inklaar and Timmer,
2013). The correlation between the two variables is below each graphic. It is notable how the Gini
data become reliable only in recent years. Figure 2 shows Polity IV (black line), Inflation (red) and
Gross Domestic Product Growth (blue). The left Y axis shows the minimum and maximum values
of the Inflation, and the right axis shows the limits of Economic growth. The correlations between
Polity IV and the two other variables is shown below each graphic.
1
We thank the Latin American Public Opinion Project (LAPOP) and its major supporters (the United States Agency
for International Development, the United Nations Development Program, the Inter-American Development Bank, and
Vanderbilt University) for making the data available.
2
See Table 6, at Appendix A for a list of indexes created through principal component analysis.
8
−10
Polity IV
−10
10
Polity IV
−10
Polity IV
10
0.65
−10
0.30
r = 0.71
2011
Polity IV
10
0.65
El Salvador
r = −0.21
2011
Polity IV
10
0.65
Uruguay
Polity
Gini
r = 0.26
1960
Figure 1: Polity IV and Gini Index — 1960–2011
9
−10
−10
0.30
Gini
Polity IV
−10
0.30
Gini
Polity IV
−10
10
0.65
Gini
0.30
Paraguay
1960
Honduras
2011
2011
Gini
Polity IV
−10
10
0.65
0.30
Gini
2011
r = 0.18
r = −0.40
1960
Guatemala
r = −0.88
10
0.65
0.65
0.30
−10
10
0.65
0.30
Gini
2011
1960
Peru
1960
Ecuador
r = 0.44
2011
Gini
Polity IV
10
0.65
0.30
Gini
2011
1960
r = 0.47
1960
Dominican Republic
r = −0.12
Panama
0.30
−10
2011
1960
2011
Gini
Polity IV
10
0.65
0.30
Gini
r = −0.25
r = −0.59
1960
Colombia
1960
Polity IV
2011
1960
10
0.65
0.30
r = −0.21
1960
Mexico
Gini
−10
0.30
Gini
Polity IV
10
0.65
Brazil
2011
1.09
r = 0.41
Honduras
r = 0.04
Polity
Inflation
10
Growth
Growth
r = −0.02
r = 0.10
r = −0.30
Growth
r = 0.05
Paraguay
r = −0.18
El Salvador
r = 0.03
Uruguay
r = 0.15
Growth
Figure 2: Polity IV, Inflation and Economic growth — 1960–2011
−0.15
Growth
7481.66
0.11
Peru
0.10
0.19
r = 0.17
−0.07
−0.15
r = 0.15
−0.08
37.26
Growth
16.27
0.05
0.15
Panama
0.07
−0.86
r = −0.38
3.20
0.59
−0.10
0.10
Growth
131.83
Inflation
Growth
2947.73
Inflation
−0.07
r = −0.35
−0.11
31.94
Growth
Inflation
−0.08
33.71
r = −0.16
0.09
−2.68
Inflation
Growth
0.13
2.28
Inflation
0.07
Mexico
−0.11
r = 0.08
125.34
r = −0.06
−0.16
51.46
Dominican Republic
Inflation
Growth
Ecuador
0.20
−3.90
r = 0.47
4.36
r = 0.09
r = −0.38
−0.10
96.09
Inflation
Colombia
Inflation
Growth
Guatemala
0.05
2.28
r = 0.47
−0.05
41.22
r = 0.25
0.07
−0.80
Inflation
r = 0.73
r = −0.38
Inflation
Growth
33.97
Inflation
r = 0.14
−0.08
Inflation
Brazil
I used country level data to calculate both country and individual level variables that measure
how much countries as whole and each respondent in particular were exposed to political and economic upheavals. The country level variables correspond to the last 50 years of the data, that is, the
period 1963–2012. I consider that this period is long enough for the crystallization of opinions and
attitudes that evolve at the national level. The individual level variables correspond to the adult life
of respondents, that is, from the year that they turned 18 years old to 2012. The only exception is
the mean score of Polity IV when the respondent was an adolescent (age between 13 and 17).
I used the Polity IV variable that attributed scores ranging from −10 to +10 to almost all years,
including periods of transition (Marshall, Jaggers and Gurr, 2014, p. 15). Countries with scores
from +6 to +10 are considered democratic.3 I subtracted 5 from the Polity IV scores to make
authoritarian regimes to have negative scores and democratic regimes to have positive scores. This
procedure has made the range of scores about three times longer for authoritarian regimes (from
−15 to 0) than for democratic ones (from 1 to 5). To make the two ranges equal, I divided the
values < 0 by 3 before calculating the variables that involve multiplication. Based on Polity IV, I
created four variables at both country level and individual level:
• Number of years of democracy.
• Number of years of authoritarian regime.
• Mean value of Polity IV.
• Number of transitions, that is, when Polity IV score increased to above 5 or decreased to
below 6.
The variable that was used to evaluate the effect of social inequality on Demand for democracy
was the yearly Gini index difference which is the difference between the Gini index of a year and
the previous year. That is, a positive value means an increase in the country’s inequality when
compared to the previous year. In some Latin America countries, the Gini index data goes back as
far as 1964, while for others the first year with data is decades later. Paraguay was the last country
to start having Gini index data, on 1991. The Gini dataset has 55% of missing values in the period
3
See: http://www.systemicpeace.org/polityproject.html.
11
1964–1990, but only 2% of missing values during 1991–2012.
The annual economic growth was calculated from Penn World Table 8.0 data. The Penn World
Table 8.0 has data from 1950 to 2011, what makes it possible to calculate the growth rate for the
period 1951-2011. For the respondents who turned 18 after 2011, I used the 2011 Polity IV value as
the mean value of Polity IV · Economic growth; for those who turned 18 before 1951, I used only
data from the period 1951–2011. Following Feenstra, Inklaar and Timmer (2013, p. 30) recommendation, I used the variable RGDPNA (Real Gross Domestic Product based on National Accounts)
to calculate the growth rate. For each year, I centered the country growth rates around the mean
growth rate value of all countries in the table (and not only the countries in this study).
Both deflation and high inflation are considered detrimental for the economy, and according to
Billi and Kahn (2008) the optimal rate of inflation is around 1%. Hence, I use the absolute value of
the rate of inflation centered at 1%. The greatest deflation was −4 (transformed to 5 in our variable),
and was registered at Dominican Republic on 1961; the highest inflation rate was 7482 (transformed
to 7481), registered at Peru on 1990. From the 604 data points available, in only 31 country–years,
the inflation rate was between 0 and 1, and hence, became negative when transformed.
For each of the tree economic datasets (Gini index, Economic growth and Inflation), I created
both the country and the individual level variables in two different ways:
• The difference between the mean value of the economic variable in democratic years and
its mean value in non-democratic years. I attributed the value 0 to these variables when the
respondents’ adult life was entirely lived under democracy. The variables calculated in this
way do not use the full range of Polity IV scores and, thus, are less fine grained.
• The mean value of the multiplication of the economic variable and Polity IV for each year
(explained below).
The calculus of the variables that involve the multiplication of Polity IV and economic variables
was done in two steps: (1) multiplication of Polity IV and the economic indicator for each year of
respondents’ adult life; (2) calculation of the mean value of the multiplications. Because the value
of Polity IV might be positive or negative, and the value of the economic variables also might be
12
positive or negative, for each year and for each respondent, we have the possible results shown in
Figure 3.
Polity IV
Democracy
Democracy
Autocracy
Autocracy
Economic variable
+
−
+
−
Result
+
−
−
+
Figure 3: Possible results of multiplication variables
For each year, the variable will have a positive value if either the country was democratic and
the economic variable was positive or the country was autocratic and the economic variable was
negative. The value will be negative in the inverse circumstances. For example, because economic
growth is regarded as a positive event by most people, the values of Polity IV · Economic growth
will be positive in the circumstances that we hypothesize to forge favorable attitudes towards democracy (or negative attitudes toward autocracy) and will be negative in the inverse circumstances. In
other words, we expect a positive correlation between the variables Demand for democracy and
Polity IV · Economic growth. Because both inflation and inequality are negative things, it is expected a negative correlation of Demand for democracy and both Mean Polity IV · Inflation and
Mean Polity IV · yearly Gini index difference.
In summary, we have a set of 21 variables to evaluate the long term effects of political and
economic events on individual’s attitudes toward democracy: 10 variables at the country level and
the equivalent to the same 10 variables plus Polity IV during adolescence at the individual level.
Many other variables will be used as control. At the country level, the Gross Domestic Product in
2011, The Gini index in 2011, the Polity IV score in 2012, and the Proportion of violent crime. This
last one is derived from the AmericasBarometer. At the individual level, we will use variables from
the AmericasBarometer, as detailed in the Appendix A. I opted for creating indexes measuring many
of the opinions and attitudes explored by the AmericasBarometer survey, and including as control
variables in the final HLM models all indexes that proved to be statistically significant. With this
procedure, I expect to decrease to a minimum the risk of variable selection bias: if the variables
13
created to measure the socialization processes have significant effect on Demand for democracy it
will not be because a relevant control variable that is present in the data is missing from the analysis.
4
Results
Figure 4 shows the distribution of the Index of demand for democracy by country. Most countries
have about the same level of demand for democracy, but the demand is visibly lower in Honduras
−1
−3
−2
Index
0
1
and higher in Uruguay than in the other countries.
HND
GTM
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●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
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●
●
●
●
●
●
●
●
●
●
●
PER
SLV
ECU
BRA
DOM
COL
PRY
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
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●
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●
●
●
●
MEX
PAN
URY
Country
Figure 4: Index of demand for democracy by country
According to Luke (2004, p. 32), it is not appropriate to show significant tests in multilevel
regression models. Thus, in the regressions presented in this paper, I consider statistically significant
the coefficients whose associated t statistics have high absolute values.4
Table 1 presents the multilevel null model for our dependent variable. The intraclass correlation coefficient is 0.08, that is, less than 10% of the variation is potentially explained by variables
at the country level. Although this value is low, I opted for conducting multilevel regressions to
check what country level variables have significant impact over the demand for democracy when
controlled by the individual levels variables.
4
The multilevel regression analyses were performed by the function lmer from lme4 package (Bates et al., 2014).
14
Table 1: Demand for democracy: null model
Estimate
Std. Error
(Intercept)
0.00
BIC
49877.42
Num. obs.
18027
Num. groups: country
12
Variance: country.(Intercept)
0.076
Variance: Residual
0.927
4.1
t value
0.08
0.05
Control variables
Before including the independent variables in the HLM models, we will see the impact of the control
variables on Demand for democracy. Only variables whose correlation with Demand for democracy
has a t statistics > |3| will be included in the final HLM models.
First, we will check what country level variables have correlations with demand for democracy
significant enough to be included in further analyses (Table 2).
Table 2: Demand for democracy explained by country level variables
Model 1
Model 2
Model 3
Model 4
(Intercept)
GDP in 2011
−0.02
(−0.16)
0.10
(0.37)
−0.84
(−1.69)
2.31
(2.24)
0.46
(2.37)
0.11
(1.72)
Polity in 2012
−0.05
(−2.24)
Gini Index in 2011
−4.22
(−2.50)
Violent crime
BIC
49887.99
Num. obs.
18027
Num. groups: Country
12
Variance: Country.(Intercept)
0.08
Variance: Residual
0.93
49888.14
18027
12
0.06
0.93
49888.53
18027
12
0.06
0.93
49879.04
18027
12
0.05
0.93
Gross Domestic Product in 2011 has near zero impact over the Demand for democracy (t =
15
0.37). The current level of democracy, measured by the Polity IV score in 2012, has a positive
effect on the Demand for democracy, although not statistically significant (t = 1.72). As expected,
the correlation is positive: respondents of more democratic countries have a higher demand for
democracy. The Gini index in 2011 has a negative effect on Demand for democracy. Citizens of
countries with higher inequality have a lower demand for democracy, but the significance of the
correlation is still below our threshold (−2.24). The country rate of Violent crime also has a clear
impact on Demand for democracy, but below the threshold for a control variable (t = −2.50).
The variables that measure opinions and attitudes have the most significant impact on the variation of Demand for democracy. But the individuals’ biographical trajectory and current socioeconomic conditions have an impact on their opinions and attitudes. Hence, before presenting a
model including only the most significant explanatory variables, I will present three models: (1)
biographical and sociodemographic variables, (2) opinion and attitude variables, and (3) all control
variables.
The first model in Table 3 includes biographical and socioeconomic variables used in this paper
as control variables. As others who have researched attitudes toward democracy in Latin America, we found that older people demand democracy more than young people. Number of years of
schooling, Household monthly income and Increase in household income have strong positive effect on the Demand for democracy, as expected by modernization theory. The negative effect of
Dwelling location is unexpected. Actually, if Dwelling location were the only explanatory variable in a HLM model, its effect on Demand for democracy would not be significant (t = −0.54).
Its t value becomes significant when we add to the model either Years of education (−3.33) or
Household monthly income (−4.24).
In the Opinion model, the variable with the strongest positive impact is Support for peaceful
protests and the one with the strongest negative impact is Support for violent protests. Actually,
Demand for democracy, Support for peaceful protests and Support for violent protests are positively
correlated with each other; it is only when controlled by Support for peaceful protests that the
correlation between Demand for democracy and the Support for violent protest becomes negative.
16
Table 3: Demand for democracy explained by control variables
Biographical
Opinion
All
17
(Intercept)
−0.57 (−7.68)
Age
0.01 (12.59)
Years of education
0.02 (10.82)
Household monthly income
0.02 (8.15)
Household income (Increased)
0.10 (4.91)
Dwelling location (Urban)
−0.10 (−5.75)
Support for peaceful protests
Support for violent protests
Statism
Political information
Political tolerance
Alienation
Feeling of security
Political participation
Support for government
Trust in political institutions
Approval of homosexuals in office
Left-Right position
Satisfaction with economy
People are (Trustworthy)
Experience of corruption
Civic participation
BIC
Num. obs.
Num. groups: Country
Variance: Country.(Intercept)
Variance: Residual
⋆
Country level variable.
42476.30
15453
12
0.05
0.90
−0.02 (−0.59)
0.16 (20.30)
−0.14 (−19.90)
0.10 (14.03)
0.08 (11.64)
0.08
(9.82)
−0.05 (−6.26)
0.05
(7.33)
−0.04 (−4.99)
0.03
(2.60)
0.07
(7.00)
0.05
(7.05)
0.03
(5.04)
0.02
(2.81)
0.04
(2.57)
−0.01 (−1.95)
−0.01 (−1.55)
46680.74
17665
12
0.02
0.81
−0.36 (−7.09)
0.01 (10.02)
0.01
(5.12)
0.01
(4.01)
0.04
(1.92)
−0.06 (−3.61)
0.15 (17.74)
−0.13 (−16.64)
0.11 (13.57)
0.07
(8.00)
0.08
(9.69)
−0.03 (−3.93)
0.05
(6.25)
−0.05 (−6.06)
0.04
(3.35)
0.07
(7.08)
0.05
(6.52)
0.04
(4.72)
0.02
(2.51)
0.02
(1.27)
−0.01 (−1.95)
−0.02 (−1.98)
40103.75
15182
12
0.02
0.80
Selected
−0.34 (−6.74)
0.00
(9.56)
0.01
(5.31)
0.01
(5.19)
−0.06 (−3.46)
0.15 (18.06)
−0.13 (−17.12)
0.10 (13.51)
0.07
(8.06)
0.08
(9.96)
−0.03 (−4.13)
0.05
(7.15)
−0.05 (−6.94)
0.05
(4.49)
0.07
(7.18)
0.05
(6.56)
0.04
(5.12)
41489.49
15728
12
0.02
0.80
The other three highest correlations tell us that Latin American citizens who demand democracy
also favor big governments, and, as expected, are politically well informed and tolerant. Most other
variables also have the expected effect on Demand for democracy, one important exception being
the negative effect of Political participation. Actually, if it were the only explanatory variable in
a HLM model, its effect would be insignificant (t = 0.56). It only has a negative effect when
controlled by Support for peaceful protest, Alienation, Trust in political institutions and Index of
information. Interpersonal trust, Experience of corruption and Civic participation are less relevant
for Demand for democracy in Latin America than claimed by part of the recent political science
literature.
Still in the Opinion model, it is important to note that Support for government and Trust in
political institutions are positively correlated with Demand for democracy, although their t values
are less significant than some other opinion and attitudes variables. Since almost all countries in
this study currently have a Polity IV > 5, this confirms that, to some degree, people who manifest
a Demand for democracy, in fact, are simply satisfied with the current democratic government
and other political institutions. Indeed, as Table 4 shows, the correlation between Demand for
democracy and both Support for government and Trust in political institutions is the lowest in the
country with the lowest Polity IV score and it is the highest in the country with the highest Polity
IV.
The third model puts together all variables from the first two models. One variable that measures economic wellbeing—Increasing in household income—and Satisfaction with the national
economy lost their statistical significance, while Household monthly income remained significant.
Not surprisingly, people are more worried with their personal finances than with their country
economies. Finally, the model Selected includes only the variables whose coefficients had a corresponding t > |3|. These variables will be used as controls in the final models (Table 5).
18
Table 4: Pearson correlations between Demand for democracy and two other variables in 12 countries
Correlations
Country
Polity IV
Supp. gov. Trust inst.
Ecuador
Honduras
Colombia
Mexico
Paraguay
Guatemala
Dominican Republic
El Salvador
Brazil
Panama
Peru
Uruguay
4.2
5
7
7
8
8
8
8
8
8
9
9
10
0.02
0.09
0.09
0.08
0.11
0.11
0.12
0.12
0.16
0.09
0.17
0.25
0.05
0.23
0.12
0.08
0.11
0.27
0.11
0.08
0.15
0.11
0.20
0.30
Independent variables
The cells of Table 5 show the t statistics associated with the estimate of the effect on Demand for
democracy of the independent variables and—in the last column—the control variable Age. The
country level variables are in the first rows. Each model includes only one of the independent
variables because all the individual level variables created to evaluate the impact of socialization
processes on the respondent’s demand for democracy are based on Age and, thus, it is expected a
considerable degree of collinearity between them. The Table has three sets of HLM models. In the
No controls column, we can see the effect of each independent variable when there is no control
variable in the models. The next column shows the effects of the independent variables when all
selected control variables (from the column Selected of Table 3), but Age, are added to the model.
The control variables, although included in these models, are not displayed in the table because
their coefficients and statistical significance changed only slightly when compared with the results
of Table 3. Finally, the last two columns show the results when Age is also included in the models:
one column shows the t statistics of the independent variable and the other shows the significance
of Age. When commenting on the effects of independent variables shown in Table 5, I will be less
19
exacting than I was when selecting the control variables and will refer to |t| > 2 as significant.
Table 5: Demand for democracy explained by socialization: statistical significance (t values) of
selected correlations in 63 HLM models
All controls
All controls
Independent variable
No controls
except Age Ind. var. Age
N. democratic years⋆
N. authoritarian years⋆
Mean Polity IV⋆
N. transitions⋆
Mean Polity IV · Econ. growth⋆
Growth difference⋆
Mean Polity IV · Gini. diff⋆
Gini difference⋆
Mean Polity IV · Inflation⋆
Inflation difference⋆
Mean Polity · Economic growth
Growth difference
Mean Polity · Inflation
Inflation difference
Mean Polity · Gini yearly diff.
Gini difference
Polity IV when adolescent
N. regime transitions witnessed
N. years under democracy
N. years under autocracy
Mean Polity during adult life
⋆
1.06
−1.06
0.45
−0.70
0.17
1.21
−0.03
0.26
0.81
−2.19
−1.32
−1.36
−1.51
−2.56
4.77
−0.42
−4.32
4.62
8.05
4.77
−5.16
0.32
−0.32
0.34
−0.62
0.84
1.55
0.05
−0.14
0.07
−1.88
−2.04
−1.02
−1.29
−2.18
4.80
0.78
−6.06
6.14
9.68
6.34
−6.13
0.32
−0.32
0.28
−0.75
0.81
1.48
0.05
−0.14
0.05
−2.00
0.67
−0.27
1.05
−1.41
0.58
−0.43
0.44
−1.72
2.76
−2.75
2.02
9.56
9.56
9.55
9.57
9.55
9.54
9.56
9.56
9.56
9.58
9.23
9.51
9.54
9.42
8.11
9.54
7.41
7.53
2.30
7.66
7.63
Country level variable. For diagnostic statistics of the models, see Appendix B.
The only country level variable that is barely significant when the control variables are added
to the models is Inflation difference (t = −2.00). Hence, we have only weak empirical evidence
supporting the hypothesis that the process of formation of attitudes toward democracy happens at a
national level.
Looking at the individual level variables, it is worth noting that, in spite of the addition of many
control variables, the results shown in the second column present only minor differences when
compared with the first column. However, all the individual level independent variables suffered
huge changes in their t values after the inclusion of Age in the models. This means that many of
them are not much more than a transformed Age variable. Hence, from now on, I will mostly restrict
20
my comments to the results of the individual level variables in models including all controls.
The 6 individual level variables measuring the impact of the national economy over respondent’s demand for democracy did not show significant results. Moreover, we have both negative
and positive values in all 3 pairs of variables derived from National economic data: Growth (0.67
and −0.27), Inflation (1.05 and −1.41) and Gini (0.58 and −0.43). Indeed, the control variable
measuring Satisfaction with the national economy (Table 3) was not significant enough to be selected for inclusion in these final models. These results contradict part of the literature on public
opinion in Latin America and elsewhere that have found demand for democracy as significantly
dependent on the evaluation of the economy.
The value of Polity IV when the respondent was adolescent was not significant (t = 0.44). The
immediate interpretation of this finding is that individuals were not subject to a process of primary
socialization dependent on the current political regime or, if this process occurred, it was not strong
enough to not be superseded by the ongoing process of secondary socialization. An alternative interpretation is that although many respondents were already living in democratic countries when they
were adolescents, they were being socialized by adults that have lived mainly under authoritarian
regimes and, thus, their primary socialization was not favorable to democracy.
The Number of regime transitions witnessed has a negative impact (t = −1.72). The result
indicates that past political turmoil is detrimental to citizen’s attitudes toward democracy.
As expected, the Number of years lived under democracy (t = 2.76) and the Mean value of
Polity IV during the respondent’s adult life (t = 2.02) have positive impact while Number of years
under autocracy have a negative effect (t = −2.75) on Demand for democracy. These results are
in accordance with the hypothesis that individuals living in a democratic regime gradually develop
attitudes favorable to democracy. But the most important result of Table 5 is that, in 20 out of the 21
models including all control variables, the correlations between Demand for democracy and Age are
much more significant (t > 7) than the correlations between Demand for democracy and each one
of the independent variables, but when confronted with the Number of years lived under democracy
(t = 2.76) the t value of Age drops to 2.30. Interestingly, the Number of years lived under autoc-
21
racy, although as significant regarding the t statistics, does not have the same power of offsetting
the significance of Age. My interpretation of this result is that people increase their demand for
democracy in Latin America as they become older because they have lived longer in an electoral
democracy. That is, the results support the hypothesis that, in Latin America, electoral democracy
triggers a process of secondary socialization that forges positive attitudes toward democracy.
5
Conclusion
Opinion and attitudinal variables were the ones with the highest impact on demand for democracy.
Among them, support for peaceful protests and support for violent protests were the variables with
the strongest impact on the index of demand for democracy.
Regarding the main goal of this research, we have found evidence that exposure to democratic
institutions increases the demand for democracy but did not find evidence that national economic
events influence this attitude toward democracy.
The evaluation of country’s economy and the evolution of respondent’s own income have had
the expected impact, but were much less significant than many other political, social and biographical variables. Indeed, they were not significant enough to be selected as control variables to be
included in the final HLM models. The variables created to measure the long term effect of economic events on attitudes toward democracy proved not to be significantly related with Demand
for democracy. Contrary to my expectations, the more fine grained variables (based on the multiplication of Polity IV and economic variables year by year) did not have a more preeminent effect
on Demand for democracy than the simpler variables (the difference between the average values of
economic variables in democratic and in authoritarian years), and this reinforces the evidence that
national economic events do not play an central role in Latin Americans demand for democracy.
Respondents of AmericasBarometer who experienced democratic institutions for longer time
present higher demand for democracy. The youth is less supportive of democracy than the elders,
but if the same socialization processes that have contributed for a higher demand for democracy
among the older people is still effective in gradually shaping youngster attitudes, we can expect
22
that their political attitudes will be more favorable toward democracy in the future. The findings of
this investigation do not corroborate the reasons for pessimism with the consolidation of democracy
present in the recent literature on public opinion in Latin America.
Most studies that investigate the effects of the evolution of national variables over opinions and
attitudes aggregate the data of surveys conducted over time and analyze the resulting time-series.
In this investigation, I opted for a different approach: the computation of variables at the individual level based on series of country level variables. Due to the small number of countries in this
research, we did not find significant correlation of what I am calling national level socialization
variables and Demand for democracy, but this methodology applied to a larger number of countries
has the potential of helping to disentangle how much of the influence of national events and institutions operates at the national level (shaping the national culture) and how much it operates at the
individual level (increasing the variation in opinions and attitudes).
The most direct approach to investigate the effect of institutions and events on the attitudes of
people is to measure their attitudes before and after the events or the exposure to institutions, but
it is remarkably hard to do longitudinal research when the institutions and events span for decades.
The approach of this investigation helps to cope with the problem of missing survey in past decades.
Acknowledgments
I am grateful to people who have read previous versions of the paper and made useful comments:
Michael Bratton, Christian Houle, Kangwook Han, and undergraduate students from Michigan State
University (USA), and Ednaldo Ribeiro from Maringá State University (Brazil). Of course, I am
responsible for remaining shortcomings. This work was conducted at the Michigan State University
with a fellowship conceded by CAPES – Brazilian Federal Agency for Support and Evaluation of
Graduate Education within the Ministry of Education of Brazil.
23
Appendix A — Preparation of individual level variables
It is rarely possible to elaborate a single question that measures adequately and comprehensively an
opinion or attitude corresponding to a relevant theoretical concept. It is advisable to make various
questions, weighing different aspects of a topic or asking respondents about different situations
where they may manifest an opinion or attitude. This is what the AmericasBarometer questionnaire
does frequently, and, in this research, most individual level variables are the result of principal
component analysis with varimax rotation.5
While building the indexes, missing values were replaced by random samples proportional to
each country’s distribution of values. The missing values of Number of times that the respondent
was victim of crime in the last 12 months and Anyone in household victim of crime were converted
into zero; questions Name of USA president and Term duration of president of respondent’s country
had their missing values replaced with the value “Incorrect”. I did not replace the missing values
of the remaining variables which were not used to build indexes.
Table 6 presents the indexes built through principal component analyses as well as the variables
used to build them and the factor load of each variable in its index.6 The indexes are the extracted
component scores.
Table 6: Indexes, their component variables and factor loads
Index
Demand for democracy
Support for government
Variable label
Load
Democracy is the best form of government
Democracy is preferable to authoritarian government
Iron fist or everyone participation
Strong leader or electoral democracy
Current administration fights poverty
Current administration promotes democracy
Current administration combats corruption
Current administration improves safety
Current administration manages economy well
0.59
0.60
0.60
0.71
0.81
0.81
0.82
0.80
0.81
Continues in the next page…
5
I used R (R Core Team, 2014) to do the data manipulation and analysis, using the function principal from package
psych (Revelle, 2014) to do principal component analysis.
6
The question labels were shortened to fit the table width. The full questionnaire is available at: http://www.
vanderbilt.edu/lapop/core-surveys.php.
24
…continuation of last page
Index
Satisfaction with
economy
Alienation
Feeling of security
Experience of
corruption
Trust in political
institutions
Political information
Civic participation
Political participation
Support for peaceful
protests
Support for violent
protests
Variable label
Load
Evaluation of the job of current president
Evaluation of the job of congressmen and senators
Evaluation of country’s economy
Is the economy better or worse?
Evaluation of personal economy
Is personal economy better or worse?
Those who govern are interested in what you think
Do you understand political issues?
Do you feel safe in your neighborhood?
Is you neighborhood affected by gangs?
Has a police office asked for bribes?
Did government employee asked for bribes?
The courts guarantee a fair trial
Do you respect political institutions?
Citizens’s rights are well protected
Are you proud of your political system?
Should you support the political system?
Do you trust the justice system?
Do you trust the Electoral Tribunal?
Do you trust the National Legislature?
Do you trust the National Police?
Do you trust political parties?
Do you trust the President?
Do you trust the Supreme Court?
Do you trust the local government?
How often do you use the internet?
How often do you pay attention to news?
What is the name of the current U.S. president?
How long is the presidential term in your country?
Do you attend meetings of religious organization?
Do you attend meetings of parents association?
Do you attend meetings of community committee?
Do you attend meetings of professional association?
Do you attend meetings of a political party?
How much interest do you have in politics?
How often have you tried to change others vote?
Did you work for any candidate or party?
Do you approve people in legal demonstrations?
Do you approve people organized to solve community problems?
Do you approve people working for political campaigns?
Do you approve people organized to overthrow a government?
Do you approve people seizing private property to protest?
Do you approve people blocking roads to protest?
0.66
0.52
0.72
0.74
0.74
0.74
0.80
0.80
0.81
0.81
0.83
0.83
0.54
0.61
0.70
0.73
0.68
0.75
0.70
0.72
0.61
0.66
0.65
0.75
0.59
0.60
0.48
0.78
0.63
0.52
0.64
0.72
0.56
0.68
0.63
0.65
0.69
0.81
0.84
0.78
0.79
0.81
0.72
Continues in the next page…
25
…continuation of last page
Index
Political tolerance
Statism
Variable label
Load
Do you approve people taking the law into their own hands?
Do you approve right to vote of people who say bad things
about form of government?
Do you approve manifestation of people who says bad things
about form of government?
Do you approve people who says bad things about form of
government being permitted to run for public office?
Do you approve people who says bad things about form of
government on tv?
Government should own most important enterprises
Government should be responsible well-being
Government should create jobs?
Government should provide health care
0.61
0.73
0.77
0.85
0.84
0.48
0.82
0.84
0.80
I used as single items the biographical or sociodemographic variables and also some opinion and
attitude variables that were not significantly correlated with others that at first glance seemed to be
measuring similar phenomena: Age, Years of schooling, Evolution of household income, Location
of household (Rural or Urban), Approval of homosexuals in public offices, the respondent auto
positioning in the Left-Right scale.
I calculated the national proportion of respondents who reported being victim of aggressive
crimes (unarmed robbery with assault or physical threats, armed robbery, assault but not robbery,
rape or sexual assault, or kidnapping) to create the variable labeled Violent crime.
Appendix B — Diagnostic statistics of final HLM regressions
26
Table 7: Diagnostic statistics of models shown in Table 5
No controls
All controls except Age
27
N. democratic years⋆
N. authoritarian years⋆
Mean Polity IV⋆
N. transitions⋆
Mean Polity IV · Econ. growth⋆
Growth difference⋆
Mean Polity IV · Gini. diff⋆
Gini difference⋆
Mean Polity IV · Inflation⋆
Inflation difference⋆
Mean Polity · Economic growth
Growth difference
Mean Polity · Inflation
Inflation difference
Mean Polity · Gini yearly diff.
Gini difference
Polity IV when adolescent
N. regime transitions witnessed
N. years under democracy
N. years under autocracy
Mean Polity during adult life
⋆
Country level variable.
All controls
BIC
N
V.C
V.R
BIC
N
V.C
V.R
BIC
N
V.C
V.R
49894
49894
49892
49890
49883
49880
49889
49893
49892
49886
48382
49885
49895
49888
49368
49896
49880
49874
49835
49877
49870
18027
18027
18027
18027
18027
18027
18027
18027
18027
18027
17476
18027
18027
18027
17857
18027
18027
18027
18027
18027
18027
0.08
0.08
0.08
0.08
0.08
0.07
0.08
0.08
0.08
0.06
0.08
0.08
0.08
0.07
0.08
0.08
0.08
0.08
0.07
0.08
0.08
0.93
0.93
0.93
0.93
0.93
0.93
0.93
0.93
0.93
0.93
0.93
0.93
0.93
0.93
0.92
0.93
0.93
0.93
0.92
0.93
0.93
41576
41576
41573
41572
41563
41561
41571
41574
41574
41568
40350
41566
41575
41569
41163
41576
41542
41537
41486
41539
41539
15728
15728
15728
15728
15728
15728
15728
15728
15728
15728
15273
15728
15728
15728
15588
15728
15728
15728
15728
15728
15728
0.02
0.02
0.02
0.02
0.02
0.02
0.02
0.02
0.02
0.02
0.02
0.02
0.02
0.02
0.02
0.02
0.02
0.02
0.02
0.02
0.02
0.81
0.81
0.81
0.81
0.81
0.81
0.81
0.81
0.81
0.81
0.80
0.81
0.81
0.81
0.80
0.81
0.80
0.80
0.80
0.80
0.80
41508
41508
41505
41503
41495
41493
41503
41506
41506
41500
40288
41499
41508
41504
41120
41508
41510
41503
41503
41503
41503
15728
15728
15728
15728
15728
15728
15728
15728
15728
15728
15273
15728
15728
15728
15588
15728
15728
15728
15728
15728
15728
0.02
0.02
0.02
0.02
0.02
0.02
0.02
0.02
0.02
0.01
0.02
0.02
0.02
0.02
0.02
0.02
0.02
0.02
0.02
0.02
0.02
0.80
0.80
0.80
0.80
0.80
0.80
0.80
0.80
0.80
0.80
0.80
0.80
0.80
0.80
0.80
0.80
0.80
0.80
0.80
0.80
0.80
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