Do democratic institutions forge a demand for democracy?An investigation of Latin American citizens attitudes

Jakson Alves de AquinoFederal University of Ceará (Brazil)Michigan State University (USA)

jaa@ufc.br

Presented at the73rd Annual Midwest Political Science Association Conference

Chicago, April 16–19, 2015

Abstract

Recent research on Latin America have found that younger people are willing to live underdemocracy less than older people. The economic performance of political regimes is some-times considered important to define these attitudes. In this research, I used data from Ameri-casBarometer and other country level data to calculate variables that measure respondent’s ex-posure to both democracy and economic events. Using multilevel models, I found that higherdemand for democracy by older people is dependent on their exposure to democracy duringtheir adult life, and I did not find long term effects of economic events. I interpret the findingsas meaning that people living under democracy are subject to socialization processes that makethem demand democracy. The methodology used in this research has the the potential of help-ing to disentangle how much of the influence of national events and institutions operates at thenational 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 surpris-

ingly, 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 in-

creases, 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 Amer-

icasBarometer 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 expres-

sion 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-demo-

cratic, or

2. Democracy is preferable to any other form of government, or

3. Under some circumstances an authoritarian governmentmay 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 democ-

ratization but democratization is not necessarily favorable to economic development. People wor-

ried 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 cul-

tural 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 pro-

motes “self-expression values” such as freedom of speech and participation in the de-

cision-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

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that of the various political indicators […]. This global pattern holds up well among

Africans, Asians, and Arabs. In Latin America, by contrast, perceived national eco-

nomic 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 genera-

tion 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 democra-

tization 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; Free-

man 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 spend-

ing 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

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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 democ-

racy 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 proce-

dures 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 sophisti-

cated 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 un-

derstand 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 cor-

relation 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 mat-

ters 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 individ-

uals’ 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 pos-

sibilities: (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 in-

dividuals attitudes toward democracy? Do people perform some kind of either conscious or uncon-

scious 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 autoc-

racy 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 spe-

cific 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 individ-

ualistic 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, respon-

dent’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 interest-

ing 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 inter-

views 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 (THEWORLD

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.1We 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, andVanderbilt University) for making the data available.

2See Table 6, at Appendix A for a list of indexes created through principal component analysis.

8

BrazilG

ini

1960 2011

−10

10

Pol

ity IV

0.30

0.65

r = −0.21

Colombia

Gin

i

1960 2011−

1010

Pol

ity IV

0.30

0.65

r = −0.25

Dominican Republic

Gin

i

1960 2011

−10

10

Pol

ity IV

0.30

0.65

r = −0.12

Ecuador

Gin

i

1960 2011

−10

10

Pol

ity IV

0.30

0.65

r = 0.44

Guatemala

Gin

i

1960 2011

−10

10

Pol

ity IV

0.30

0.65

r = −0.88

Honduras

Gin

i

1960 2011

−10

10

Pol

ity IV

0.30

0.65

r = 0.18

Mexico

Gin

i

1960 2011

−10

10

Pol

ity IV

0.30

0.65

r = −0.59

Panama

Gin

i

1960 2011

−10

10

Pol

ity IV

0.30

0.65

r = 0.47

Peru

Gin

i

1960 2011

−10

10

Pol

ity IV

0.30

0.65

r = −0.40

Paraguay

Gin

i

1960 2011

−10

10

Pol

ity IV

0.30

0.65

r = 0.71

El Salvador

Gin

i

1960 2011

−10

10

Pol

ity IV

0.30

0.65

r = −0.21

Uruguay

Gin

i

1960 2011

−10

10

Pol

ity IV

0.30

0.65

r = 0.26

Polity Gini

Figure 1: Polity IV and Gini Index — 1960–2011

9

BrazilIn

flatio

n

Gro

wth

3.20

2947

.73

−0.

070.

10

r = 0.14 r = −0.38

Colombia

Infla

tion

Gro

wth

2.28

33.7

1

−0.

080.

05r = 0.73 r = 0.47

Dominican Republic

Infla

tion

Gro

wth

−3.

9051

.46

−0.

160.

13

r = 0.25 r = −0.06

Ecuador

Infla

tion

Gro

wth

2.28

96.0

9

−0.

100.

20

r = 0.47 r = −0.38

Guatemala

Infla

tion

Gro

wth

−0.

8041

.22

−0.

050.

05

r = 0.09 r = 0.08

Honduras

Infla

tion

Gro

wth

1.09

33.9

7

−0.

080.

07

r = 0.41 r = 0.04

Mexico

Infla

tion

Gro

wth

0.59

131.

83

−0.

100.

07

r = −0.16 r = −0.35

Panama

Infla

tion

Gro

wth

−0.

0716

.27

−0.

150.

15

r = −0.38 r = 0.15

Peru

Infla

tion

Gro

wth

0.19

7481

.66

−0.

150.

11

r = 0.17 r = 0.05

Paraguay

Infla

tion

Gro

wth

−0.

8637

.26

−0.

080.

10

r = −0.02 r = −0.18

El Salvador

Infla

tion

Gro

wth

−2.

6831

.94

−0.

110.

07

r = 0.10 r = 0.03

Uruguay

Infla

tion

Gro

wth

4.36

125.

34

−0.

110.

09

r = −0.30 r = 0.15

Polity Inflation Growth

Figure 2: Polity IV, Inflation and Economic growth — 1960–2011

10

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 eco-

nomic 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 period3See: 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) recommen-

dation, 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 Economic variable ResultDemocracy + +Democracy − −Autocracy + −Autocracy − +

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 democ-

racy (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 ex-

pected 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, theGross 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 measuringmany

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

and higher in Uruguay than in the other countries.

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HND GTM PER SLV PRY ECU BRA DOM COL MEX PAN URY

−3

−2

−1

01

Country

Inde

x

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

regressionmodels. 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 correla-

tion 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.4The multilevel regression analyses were performed by the function lmer from lme4 package (Bates et al., 2014).

14

Table 1: Demand for democracy: null modelEstimate Std. Error t value

(Intercept) 0.00 0.08 0.05

BIC 49877.42Num. obs. 18027Num. groups: country 12Variance: country.(Intercept) 0.076Variance: Residual 0.927

4.1 Control variables

Before including the independent variables in the HLMmodels, 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 variablesModel 1 Model 2 Model 3 Model 4

(Intercept) −0.02 −0.84 2.31 0.46(−0.16) (−1.69) (2.24) (2.37)

GDP in 2011 0.10(0.37)

Polity in 2012 0.11(1.72)

Gini Index in 2011 −0.05(−2.24)

Violent crime −4.22(−2.50)

BIC 49887.99 49888.14 49888.53 49879.04Num. obs. 18027 18027 18027 18027Num. groups: Country 12 12 12 12Variance: Country.(Intercept) 0.08 0.06 0.06 0.05Variance: Residual 0.93 0.93 0.93 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 vari-

ation of Demand for democracy. But the individuals’ biographical trajectory and current socioe-

conomic 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 Amer-

ica, 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 ef-

fect 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 vari-

able 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 variablesBiographical Opinion All Selected

(Intercept) −0.57 (−7.68) −0.02 (−0.59) −0.36 (−7.09) −0.34 (−6.74)Age 0.01 (12.59) 0.01 (10.02) 0.00 (9.56)Years of education 0.02 (10.82) 0.01 (5.12) 0.01 (5.31)Household monthly income 0.02 (8.15) 0.01 (4.01) 0.01 (5.19)Household income (Increased) 0.10 (4.91) 0.04 (1.92)Dwelling location (Urban) −0.10 (−5.75) −0.06 (−3.61) −0.06 (−3.46)Support for peaceful protests 0.16 (20.30) 0.15 (17.74) 0.15 (18.06)Support for violent protests −0.14 (−19.90) −0.13 (−16.64) −0.13 (−17.12)Statism 0.10 (14.03) 0.11 (13.57) 0.10 (13.51)Political information 0.08 (11.64) 0.07 (8.00) 0.07 (8.06)Political tolerance 0.08 (9.82) 0.08 (9.69) 0.08 (9.96)Alienation −0.05 (−6.26) −0.03 (−3.93) −0.03 (−4.13)Feeling of security 0.05 (7.33) 0.05 (6.25) 0.05 (7.15)Political participation −0.04 (−4.99) −0.05 (−6.06) −0.05 (−6.94)Support for government 0.03 (2.60) 0.04 (3.35) 0.05 (4.49)Trust in political institutions 0.07 (7.00) 0.07 (7.08) 0.07 (7.18)Approval of homosexuals in office 0.05 (7.05) 0.05 (6.52) 0.05 (6.56)Left-Right position 0.03 (5.04) 0.04 (4.72) 0.04 (5.12)Satisfaction with economy 0.02 (2.81) 0.02 (2.51)People are (Trustworthy) 0.04 (2.57) 0.02 (1.27)Experience of corruption −0.01 (−1.95) −0.01 (−1.95)Civic participation −0.01 (−1.55) −0.02 (−1.98)

BIC 42476.30 46680.74 40103.75 41489.49Num. obs. 15453 17665 15182 15728Num. groups: Country 12 12 12 12Variance: Country.(Intercept) 0.05 0.02 0.02 0.02Variance: Residual 0.90 0.81 0.80 0.80⋆ Country level variable.

17

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 mea-

sures 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 corre-

sponding 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 coun-tries

Country Polity IV Correlations

Supp. gov. Trust inst.

Ecuador 5 0.02 0.05Honduras 7 0.09 0.23Colombia 7 0.09 0.12Mexico 8 0.08 0.08Paraguay 8 0.11 0.11Guatemala 8 0.11 0.27Dominican Republic 8 0.12 0.11El Salvador 8 0.12 0.08Brazil 8 0.16 0.15Panama 9 0.09 0.11Peru 9 0.17 0.20Uruguay 10 0.25 0.30

4.2 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) ofselected correlations in 63 HLM models

Independent variable No controls All controlsexcept Age

All controls

Ind. var. Age

N. democratic years⋆ 1.06 0.32 0.32 9.56N. authoritarian years⋆ −1.06 −0.32 −0.32 9.56Mean Polity IV⋆ 0.45 0.34 0.28 9.55N. transitions⋆ −0.70 −0.62 −0.75 9.57Mean Polity IV · Econ. growth⋆ 0.17 0.84 0.81 9.55Growth difference⋆ 1.21 1.55 1.48 9.54Mean Polity IV · Gini. diff⋆ −0.03 0.05 0.05 9.56Gini difference⋆ 0.26 −0.14 −0.14 9.56Mean Polity IV · Inflation⋆ 0.81 0.07 0.05 9.56Inflation difference⋆ −2.19 −1.88 −2.00 9.58Mean Polity · Economic growth −1.32 −2.04 0.67 9.23Growth difference −1.36 −1.02 −0.27 9.51Mean Polity · Inflation −1.51 −1.29 1.05 9.54Inflation difference −2.56 −2.18 −1.41 9.42Mean Polity · Gini yearly diff. 4.77 4.80 0.58 8.11Gini difference −0.42 0.78 −0.43 9.54Polity IV when adolescent −4.32 −6.06 0.44 7.41N. regime transitions witnessed 4.62 6.14 −1.72 7.53N. years under democracy 8.05 9.68 2.76 2.30N. years under autocracy 4.77 6.34 −2.75 7.66Mean Polity during adult life −5.16 −6.13 2.02 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 muchmore 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 respon-

dent’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 se-

lected 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 inter-

pretation 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 biograph-

ical 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 eco-

nomic 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 multi-

plication 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 individ-

ual 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 insti-

tutions 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, ChristianHoule, KangwookHan, and undergraduate students fromMichigan StateUniversity (USA), and Ednaldo Ribeiro from Maringá State University (Brazil). Of course, I amresponsible for remaining shortcomings. This work was conducted at theMichigan State Universitywith a fellowship conceded by CAPES – Brazilian Federal Agency for Support and Evaluation ofGraduate 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 Variable label Load

Demand for democracy

Democracy is the best form of government 0.59Democracy is preferable to authoritarian government 0.60Iron fist or everyone participation 0.60Strong leader or electoral democracy 0.71

Support for government

Current administration fights poverty 0.81Current administration promotes democracy 0.81Current administration combats corruption 0.82Current administration improves safety 0.80Current administration manages economy well 0.81

Continues in the next page…5I used R (RCore Team, 2014) to do the datamanipulation and analysis, using the function principal from package

psych (Revelle, 2014) to do principal component analysis.6The 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 Variable label Load

Evaluation of the job of current president 0.66Evaluation of the job of congressmen and senators 0.52

Satisfaction witheconomy

Evaluation of country’s economy 0.72Is the economy better or worse? 0.74Evaluation of personal economy 0.74Is personal economy better or worse? 0.74

Alienation Those who govern are interested in what you think 0.80Do you understand political issues? 0.80

Feeling of security Do you feel safe in your neighborhood? 0.81Is you neighborhood affected by gangs? 0.81

Experience ofcorruption

Has a police office asked for bribes? 0.83Did government employee asked for bribes? 0.83

Trust in politicalinstitutions

The courts guarantee a fair trial 0.54Do you respect political institutions? 0.61Citizens’s rights are well protected 0.70Are you proud of your political system? 0.73Should you support the political system? 0.68Do you trust the justice system? 0.75Do you trust the Electoral Tribunal? 0.70Do you trust the National Legislature? 0.72Do you trust the National Police? 0.61Do you trust political parties? 0.66Do you trust the President? 0.65Do you trust the Supreme Court? 0.75Do you trust the local government? 0.59

Political information

How often do you use the internet? 0.60How often do you pay attention to news? 0.48What is the name of the current U.S. president? 0.78How long is the presidential term in your country? 0.63

Civic participation

Do you attend meetings of religious organization? 0.52Do you attend meetings of parents association? 0.64Do you attend meetings of community committee? 0.72Do you attend meetings of professional association? 0.56

Political participation

Do you attend meetings of a political party? 0.68How much interest do you have in politics? 0.63How often have you tried to change others vote? 0.65Did you work for any candidate or party? 0.69

Support for peacefulprotests

Do you approve people in legal demonstrations? 0.81Do you approve people organized to solve community prob-lems?

0.84

Do you approve people working for political campaigns? 0.78

Support for violentprotests

Do you approve people organized to overthrow a government? 0.79Do you approve people seizing private property to protest? 0.81Do you approve people blocking roads to protest? 0.72

Continues in the next page…

25

…continuation of last page

Index Variable label Load

Do you approve people taking the law into their own hands? 0.61

Political tolerance

Do you approve right to vote of people who say bad thingsabout form of government?

0.73

Do you approve manifestation of people who says bad thingsabout form of government?

0.77

Do you approve people who says bad things about form ofgovernment being permitted to run for public office?

0.85

Do you approve people who says bad things about form ofgovernment on tv?

0.84

Statism

Government should own most important enterprises 0.48Government should be responsible well-being 0.82Government should create jobs? 0.84Government should provide health care 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 5No controls All controls except Age All controls

BIC N V.C V.R BIC N V.C V.R BIC N V.C V.R

N. democratic years⋆ 49894 18027 0.08 0.93 41576 15728 0.02 0.81 41508 15728 0.02 0.80N. authoritarian years⋆ 49894 18027 0.08 0.93 41576 15728 0.02 0.81 41508 15728 0.02 0.80Mean Polity IV⋆ 49892 18027 0.08 0.93 41573 15728 0.02 0.81 41505 15728 0.02 0.80N. transitions⋆ 49890 18027 0.08 0.93 41572 15728 0.02 0.81 41503 15728 0.02 0.80Mean Polity IV · Econ. growth⋆ 49883 18027 0.08 0.93 41563 15728 0.02 0.81 41495 15728 0.02 0.80Growth difference⋆ 49880 18027 0.07 0.93 41561 15728 0.02 0.81 41493 15728 0.02 0.80Mean Polity IV · Gini. diff⋆ 49889 18027 0.08 0.93 41571 15728 0.02 0.81 41503 15728 0.02 0.80Gini difference⋆ 49893 18027 0.08 0.93 41574 15728 0.02 0.81 41506 15728 0.02 0.80Mean Polity IV · Inflation⋆ 49892 18027 0.08 0.93 41574 15728 0.02 0.81 41506 15728 0.02 0.80Inflation difference⋆ 49886 18027 0.06 0.93 41568 15728 0.02 0.81 41500 15728 0.01 0.80Mean Polity · Economic growth 48382 17476 0.08 0.93 40350 15273 0.02 0.80 40288 15273 0.02 0.80Growth difference 49885 18027 0.08 0.93 41566 15728 0.02 0.81 41499 15728 0.02 0.80Mean Polity · Inflation 49895 18027 0.08 0.93 41575 15728 0.02 0.81 41508 15728 0.02 0.80Inflation difference 49888 18027 0.07 0.93 41569 15728 0.02 0.81 41504 15728 0.02 0.80Mean Polity · Gini yearly diff. 49368 17857 0.08 0.92 41163 15588 0.02 0.80 41120 15588 0.02 0.80Gini difference 49896 18027 0.08 0.93 41576 15728 0.02 0.81 41508 15728 0.02 0.80Polity IV when adolescent 49880 18027 0.08 0.93 41542 15728 0.02 0.80 41510 15728 0.02 0.80N. regime transitions witnessed 49874 18027 0.08 0.93 41537 15728 0.02 0.80 41503 15728 0.02 0.80N. years under democracy 49835 18027 0.07 0.92 41486 15728 0.02 0.80 41503 15728 0.02 0.80N. years under autocracy 49877 18027 0.08 0.93 41539 15728 0.02 0.80 41503 15728 0.02 0.80Mean Polity during adult life 49870 18027 0.08 0.93 41539 15728 0.02 0.80 41503 15728 0.02 0.80⋆ Country level variable.

27

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