Class Voting 13 May

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May 13, 2013

Class Voting in Latin America

Mariano Torcal, Scott Mainwaring, and Nicolás M. Somma*

Class voting has been an issue of long-standing interest to sociologists and political

scientists (Alford 1963; Bartolini 2000; Clark et al. 1993; Clark and Lipset 1991 and 2001;

Evans 1999a; Evans et al. 1991 and 1999; Franklin 1992; Heath et al. 1985; Hout et al. 1993

and 1995; Kelley et al. 1985; Knutsen 2004 and 2005; Manza and Brooks 1999; Nieuwbeerta

1995 and 2001; Nieuwbeerta and Ultee 1999; Weakliem 1989). With the resurgence of the

Latin American left since the election of Hugo Chávez in 1998 and subsequent victories by

Rafael Correa in Ecuador (2006) and Evo Morales in Bolivia (2005), interest in this old subject

has rekindled. Yet oddly, and in stark contrast to the situation in Western Europe, there are few

published cross-national studies of class voting in Latin America. The existing broad, regional-

scope assessments about class politics in Latin America have predominantly aroused from

historical-comparative research (Dix 1989; Collier and Collier 1991; Coppedge 1998; Roberts

2002) concluding that class voting in the region has been historically weak compared to

Western Europe (Torcal and Mainwaring 2003b).

In this paper, we confirm this conclusion from preceding studies using a broad

comparative perspective with the LAPOP survey data. Additionally, we show that

despite this generally weak class voting, there are significant cross-national differences.

These national differences do not correspond to the classic sociological or socio-

economic structural explanations that linked social structure to class voting. We offer

some tentative alternative explanations about cross-national differences in class voting.

These explanations are connected with institutional factors (mostly with the

institutionalization of the party system) and political agency. This last one, as we expect

*

Please do not share or distribute this preliminary version of this paper beyond participants in the Vanderbilt conference. Krystin Krause and María Victoria De Negri

provided excellent research assistance.

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to show in further versions, tends to be much more unstable not producing the

anchoring effect that class might have in many other democracies in Western Europe.

We do not fully prove these alternative explanations, but at we hope to supply some

preliminary evidence of their plausibility.

The analysis is based on the 2006 and 2008 LAPOP surveys. We use two

distinct independent variables to measure class. One is an index of household wealth,

and the other is the class categories created by Erikson and Goldthorpe (1992), which

have been used by most of the comparative literature in class voting in Western Europe

and the US. We also use two different dependent variables, presidential voting and

legislative voting, which do not prove to be very different when it comes to class

voting, except in the more institutional party system of Chile.

The theoretical framework

a) The weak importance of class voting in Latin America

The conventional wisdom has received support in case studies that have revealed

either the lack of or very weak associations between class and electoral preferences. For

instance, in a study of Venezuela, Lupu (2010) found that only in the 1998 election did

Chávez garner a disproportionate support from poor voters. In subsequent elections he

attracted large numbers of middle-class voters. Likewise, in a study of the 1988

presidential election in Mexico, Dominguez and McCann (1995) found that class and

vote intention was significantly associated only once. Upper-class professionals were

less likely to vote for center-left candidate Cuauhtémoc Cárdenas than middle class

individuals. The remaining contrasts between class and vote intention, as well as those

between education and vote intention, were not significant. The same can be said about

other cases such as Brazil where Singer (2009: 85) showed that in the 2002 presidential

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election the vote for Lula - the Worker’s Party candidate - “was not especially

associated with any social strata in particular.” Torcal and Mainwaring (2003b)

concluded that in the 1990s, Latin American voters were “not strongly anchored to

parties through the traditional social cleavages [including class] that Lipset and Rokkan

(1967) emphasized (…) They do not engage in class voting”

The conventional view, however, has not gone unchallenged. Comparative-

historical researchers, while acknowledging the weakness of Latin American class

politics when compared to Western Europe, have nonetheless suggested that some

countries (such as Chile and Uruguay) developed stronger class cleavages than the rest

(Dix 1989). Some quantitative studies discovered strong associations between class and

vote. For instance, in a longitudinal study of Venezuela, Heath (2009a:189) found that

although the bivariate association between class and vote declined between 1960 and

1995, it got stronger from the late 1990s until 2005 – that is, the first half of the Chávez

era. Heath (2009b) confirmed that support for Chávez was much higher among the

working class than among the middle class. In a study of Mexico, Klesner (2008) shows

cross-tabulations from survey data from 2000 and 1997 according to which PRI voters

are less educated and earn lower incomes than PAN voters. Consistent with this, he

finds that the PRI does better in municipios with low literacy levels while the PAN does

so in more educated ones.

The absence of class voting has also been disputed with the Argentine case.

Cataife (2011) found that in the Argentinean legislative election of 2009 those with

more education and higher income (measured with a proxy) voted more for the Unión

Cívica Radical while those with lower education and income leaned to the Partido

Justicialista led by Cristina Fernández de Kirchner. This is aligned with a traditional

class-voting hypothesis for Argentina – that the popular classes prefer Peronist

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candidates while the better off lean to the Radicals (see Canton and Jorrat 2002 for

similar results regarding presidential elections in the 1990s). This claim was supported

by Lupu and Stokes’s (2009) study of the class cleavage in Argentine presidential and

congressional elections from1912 to 2003. Applying ecological inference methods to

census and official electoral data, they revealed that from 1946 onwards “class divisions

expressed themselves in the party system, with the Radical Party becoming the party of

the middle class and Peronism the party of the descamisados (shirtless ones) and the

poor” (Lupu and Stokes 2009:78).

Using ecological (district) data for Lima, Peru, Cameron (1991) found strong

and significant bivariate associations between social structure and voting patterns. In

both presidential and municipal elections between 1978 and 1989, leftist parties did

better in districts with higher percentages of manual and informal workers, while

rightist parties were favored where employers and white-collar employees abounded.

Several studies concur that in the 2006 election Brazilian president Lula was

disproportionately favored by the vote of the poor, which were attracted by the higher

standards of living that resulted from targeted social programs and minimum wage

increases (Singer 2009; Hunter and Power 2007; Zucco 2006). Finally, there has been a

substantial debate on the extent of class voting in Chile, with studies reaching different

conclusions (Torcal and Mainwaring 2003a; Valenzuela, Scully and Somma 2007;

Scully 1992).

These studies have followed disparate approaches to estimate the effect of class voting,

using different operationalizations or different dependent variables from case to case. Most

focus on only one country. Additionally, the surveys they use do not follow uniform sampling

methods or resort to common questionnaires. For instance, there are many ways of measuring

social class, and each may yield different results when it comes to study class voting (Handlin

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2013). With few exceptions (Torcal and Mainwaring 2003b), these studies have not replicated

the standard class variables proposed by Erikson and Goldthorpe.

In this chapter we combine the geographical breadth of many comparative-historical

studies of class politics, which refer to the region as a whole, with the methodological

advantages of single-country studies, which are able to disentangle the influence of class

variables on voting behavior. We provide an assessment of class voting in 17 Latin American

countries using comparable survey data collected in 2006 (and occasionally in 2008) (and in the

future 2012) as well as uniform measures and models. To the best of our knowledge only

Torcal and Mainwaring (2003b) undertook a similar endeavor for Latin America. Nonetheless,

they studied only seven countries and used a single measure of class. By studying most Latin

American countries and including two different measures of stratification (household wealth

and the Erikson-Goldthorpe class variable) we hope to obtain more robust and comprehensive

conclusions.

This paper attempts to offer a preliminary comparative comprehensive

estimation of class voting in the region, trying to replicate with some important

adaptations the analysis of the class voting literature in the advanced industrial

democracies.

The effect of party electoral supply to explain cross-national differences

Although class voting in Latin America seems to be lower than in Western Europe

(Torcal and Mainwaring 2003b), there may be interesting variations across countries and over

time. This paper deals with cross-national variations in class voting. The comparative literature

beyond Latin America has been divided between authors who emphasize the political

construction of class voting (Chhibber and Torcal 1997; Esping-Andersen 1985; Przeworski

and Sprague 1986; Sartori 1969; Hout et al. 2001; Torcal and Mainwaring 2003a) and those

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who focus on structural and cultural bases of class voting (Inglehart 1984, 1990; Lipset 1964,

1981, 2001; Clark and Lipset 1991; Franklin 1992; Nieuwbeerta and Ultee 1999). The first

approach seems to have become dominant (Knutsen, 2010).

This top-down hypothesis about the formation of class voting in Western

Europe has two alternative approaches. The first one emphasizes both the political and

structural aspects of class voting to explain cross-national differences, arguing that class

voting was stronger in countries with a larger blue collar work force fostered by the

existence of a stronger welfare state, and indirectly by a longer and stable democratic

history. In other words, class voting is a long historical process that goes hand in hand

with the institutionalization of party systems in Western Europe.

This approach has been used to explain also the general absence of class voting

in Latin America. Specialists in the region consider that the cross-national differences

about class voting are the result from both historical political conditions related with the

relatively weak labor unions and leftist (socialist or communist) parties, extensive

clientelistic ties between political elites and the masses – which delay working-class

consciousness -, and the relevance of populist parties based on multi-class alliances –

which dilute working-class appeals. Weak class voting may have been also reinforced

by the market reforms implemented during the last three decades in the region, which

were associated with public sector downsizing as well as the expansion of informal,

precarious, and flexible labor markets.

But what about cross-national time variations in class voting in the region?

There is a complementary explanation, formulated mostly as a result of the increasing

presence of leftist incumbent governments in the region, which emphasizes the role of

political agency as a more active and recent promoter of class voting. For instance

Heath (2009b) attributes the polarization of the class cleavage in Venezuela to the

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leadership and charisma of Chávez rather than to changes in the social structure or the

demands of the working class. Hence it is a story about changes in the “political

supply.” Handlin (2012) agrees that there was a recent increase of class voting in

Venezuela, but links it to the implementation of social programs that mobilized the poor

and strengthened their attachments to the incumbent United Socialist Party. In the same

line, some studies that tracked changes across time with quantitative data suggest that

class voting may come and go as a result of changes in the political supply. Stokes and

Lupu (2009) found that in Argentina, periods of economic crises and sociopolitical

upheavals temporarily eroded the traditional alignments between voters and parties,

increasing middle-class support for Peronists as well as lower-class support for

Radicals. Along similar lines, Cameron (1991: 298) notes that the Peruvian APRA lost

working-class support after the emergence of the United Left, but recovered it after

1985 when Alan Garcia took the lead of the party. Finally, according to Zucco (2006)

the social bases of the Brazilian Workers Party changed notably between 1994 and

2006, adopting the working-class profile that Lula was seeking for since its beginnings.

Some of these studies use aggregated units (such as regions or districts), leaving

unanswered the question about how individuals from different classes vote.1 These

studies are also missing a much comprehensive comparative study of class voting in the

region to be able at least to grasp the plausibility of this discussion and hypothesis. This

is the second goal of this paper.

Dependent and independent variables

We use two different dependent variables: presidential and legislative vote. The

presidency is where the power is, and it is the primary focal point of elections throughout Latin

1

Another line of studies has resorted to the surveys of Latin American political elites carried out by theUniversidad de Salamanca under the direction of Manuel Alcántara (see e. g. Lupu and Carnes 2012). In

this chapter, we are concerned with the political behavior of the masses rather than elites.

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America. It is also worth analyzing legislative voting because legislatures in Latin America

have important powers and because legislative voting might be, for a slice of the electorate, a

clearer expression of “sincere” voting. Because presidential elections ultimately have only one

winning candidate, politicians engage in strategic interparty coordination to form electoral

alliances in presidential elections. As a result, many citizens might not be able to vote for their

first choice party in presidential elections. Moreover, strategic voters do not want to waste their

presidential vote, so they might cast their ballot for their second most preferred candidate.

We primarily use the 2006 wave of the Latin American Public Opinion Project

(LAPOP) survey to assess class voting. For legislative voting in Argentina, Bolivia, and Brazil,

we use the 2008 wave of LAPOP because data were not available for 2006.

In the multinomial models presented below, the party (for legislative voting) or

candidate (for presidential voting) located most to the right among parties that obtained more

than 10% of the valid preferences among survey respondents is the reference category. We

determined the most conservative party or candidate by the mean ideological self-placement of

voters who supported that party or candidate.

Our primary independent variable is the class of the respondent. We constructed

this variable in two different ways, both of which have some advantages over the other.

Our first measure is based on household wealth, including items such as plumbing,

computers, land line phones, cell phones, and automobiles. The 2006 LAPOP enables

us to measure household wealth for almost every respondent. Household wealth-based

measures are commonly used as an indicator of class (Handlin 2013).

Second, we use a measure intended to roughly approximate the Erikson-

Goldthorpe (1992) class schema. It has been frequently employed in the literature on

class voting in Western Europe (Evans 1992; Evans 1999: 8-11; Clark 2001: 19-20) but

is almost absent in studies on voting patterns in Latin America (exceptions are Torcal

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and Mainwaring 2003a, Torcal and Mainwaring 2003b, and Heath 2009a).2 In contrast

to wealth-based measures, the Erikson-Goldthorpe schema is based on individuals’

position in production processes. Individuals’ political preferences (including their vote

choice) are formed not only in relation to their income or household wealth, but also as

a result of their work experiences and relationships. Historically, unionized blue collar

workers were more likely to form and support leftist parties than small owners who had

the same income and living standards. The latter were at least stereotypically inclined to

be conservative. Likewise, individuals employed in the informal sector in contemporary

Latin America were presumably historically less likely to support leftist parties than

poor members of the working class.

Measuring Household Wealth

First, we provide estimates of class voting based on a measure of household

wealth. We estimated household wealth using a principal component analysis of ten

household assets listed in the AmericasBarometer surveys, as described by Córdova

(2009). The principal component analysis used dichotomous variables to indicate

whether or not a household contains any of the following material goods or assets: a

television, a refrigerator, a landline telephone, a cellular phone, one vehicle, two

vehicles, three vehicles, a washing machine, a microwave oven, indoor plumbing, an

indoor bathroom, or a computer. As Córdova (2009) explains, formally, the wealth

index for household I is the linear combination,

yi = α 1(

x1 − x1

s1) +α 2(

x2 − x2

s2

) + ...+α k ( xk − xk

sk )

where and sk are the mean and standard deviation of the asset x k and α is the weight

for each variable xk for the first principal component. By definition, the first principal

2 For studies that resort to discrete class categories based on occupational measures, see

Dominguez and McCann (1995), and Canton and Jorrat (2002).

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component across households or individuals has a mean of zero and a variance of λ,

which corresponds to the largest eigenvalue of the correlation matrix of x. The first

principal component y yields a wealth index that assigns a larger weight to assets that

vary the most across households so that an asset found in all households is given a

weight of zero (McKenzie 2005). The first principle component or wealth index can

take positive as well as negative values (Córdova 2009: 3). We modified Córdova’s

household wealth measure slightly because we did not use weights to differentiate

between urban and rural areas. For our purpose, if a household does not have indoor

plumbing, a refrigerator, an indoor bathroom, a television, or the other household goods

mentioned above, it does not matter if it is in an urban or rural area; we still regard it is

poor.

We use household wealth rather than income for several reasons.3 First, the

question on income was not commensurable across countries in the 2006 survey. It

would be difficult to compare class voting across countries without a measure of class

that was directly comparable across countries. Second, a measure of wealth based on

household goods is more stable than one based on income. A middle class person could

leave the labor market for a short time without experiencing a pronounced decline in

household wealth (Booth and Seligson 2009: 115-116). Thus, the income measure could

be misleading (i.e., have poor validity). Third, wealth based on household goods

correctly codes relatively well-off retired individuals, whereas an income question

might record these individuals as having very low or no income. Again, the validity of

the measure based on household goods should be higher. Fourth, misreporting is

probably much higher on income than on household wealth (Handlin 2013: 150-151).

3

For an excellent recent discussion of the advantages and disadvantages of differentconceptualizations and operationalizations of “class,” see Handlin 2013. We draw on

his discussion of the advantages of using household wealth rather than reported income.

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Fifth, if we used income, we would need to adjust for size of household. A certain

household income could be more than adequate for one person but put a household of

seven below the poverty line. A measure based on household wealth is much less

vulnerable to this problem. Finally, there were fewer missing cases for household

wealth (only five out of 28,216 respondents compared to 3613 missing observations for

the family income question). We excluded Panama because of some problems in the

household wealth data in 2006.

The classic hypothesis in some class voting literature – i. e. the rich vote for the

right and the poor for the left (Lipset 1960: 234)4--is supported if we obtain negative

and significant associations between household wealth and the dependent variable.

For both household wealth and our other measure of class, we employ simple

models with three demographic variables as controls in addition to our primary variable

of interest (household wealth or class): population size where the respondent lives

(metropolitan area and large cities =1; medium cities, small cities, and rural = 0), 5 sex

(male=1, female=2), and age. Without these control variables, we could get biased

results. If, for example, a high percentage of skilled workers were men and if men voted

disproportionately for the left, what might in a univariate analysis appear to be class

voting could in fact be gender voting. In most countries, rural areas vote

4 Lipset (1960: 234) wrote that “More than anything else, the party struggle is a conflict

among classes, and the most impressive single fact about political party support is that

in virtually every economically developed country the lower-income groups vote

mainly for parties of the left, while the higher income groups vote mainly for parties of

the right.”5 This dichotomous variable parsimoniously captures the relationship between

population size and the ideology of the presidential candidate for whom respondents

voted. Respondents from country capitals and large cities voted for more leftist

presidents than respondents from smaller localities. Contrary to our ex-ante

expectations, respondents of medium cities were slightly more conservative in

presidential voting than respondents of small cities and rural areas. These differences

were not statistically significant, so rather than using the five discrete categories for population size that appeared in the original survey, we created the dichotomous

variable.

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disproportionately for conservative parties, and they are also on average considerably

poorer than large cities. Therefore, if we did not control for large city residence, it might

appear that wealthy households voted for the left, when in fact what is going on is that

big cities vote more for the left in many countries.

We do not include questions about political or social attitudes or behavior

because doing so could dampen the effects of class on voting. Class could work through

political and social attitudes and behavior and indirectly affect voting preference. We

are interested in the combined direct and indirect effects of class.

Household Wealth and Presidential Vote

We carried out a multinomial logistic model in each country using LAPOP

2006. The dependent variable is categorical, and indicates the candidate for whom

respondents voted for in the last presidential election (variable vb3_06 in the dataset).

We removed from the models respondents who did not answer the question, did not

know for whom they voted, or stated that they did not vote. We used robust standard

errors in all models. The number of valid observations ranges from a minimum of 582

(Paraguay) to a maximum of 2016 (Ecuador).

Table 1 shows the statistically significant (p<.10) results. Although we included

all candidates in the regressions, to save space and focus attention on the most

important results, we list only the candidates who obtained at least 10% of the valid

vote according to survey responses.

The number in the “Change in probabilities” column is based on a simulation. It

shows the percentage change in the probability that a very wealthy respondent

compared to a very poor respondent (as we shift from the lowest to the highest value for

household wealth in a given country) would vote for a given candidate as opposed to

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the conservative reference candidate. A positive value indicates that controlling for age,

sex, and residence in a large city, wealthier voters were more likely than poor voters to

prefer the more progressive candidate. A negative value shows that wealthy individuals

are less likely than poor voters to support the more progressive of the two candidates.

For Argentina, for example, the wealthiest voters were a whopping 53% less likely than

the poorest to vote for Cristina Fernández de Kirchner rather than Roberto Lavagna. 6

Conversely, in the competition between Lavagna and Elisa Carrio, household wealth

had no impact on voting.

Table 1 here

In the simulations, the control variables are held constant at their mean values

for a given country. In addition to Fernández de Kirchner, three other leftist and center-

left candidates won great support from poor voters. In Bolivia, poor voters

overwhelmingly preferred Evo Morales to Jorge Quiroga; they voted 52% more than the

wealthiest respondents for Morales. In Brazil, the poorest voted 27% more than the

wealthy for Lula. In Peru, the poorest voted 38% more than the wealthiest for Ollanta

Humala. In addition, Hugo Chávez (-4%), center-left candidate Alvaro Colom in

Guatemala (-7%), and center-left candidate Cuauhtémoc Cárdenas in Mexico (-5%)

fared somewhat better among the poorest than the wealthiest voters.

But this result is far from consistent across all countries. Most notably, in El

Salvador, in the competition with ARENA’s candidate Antonio Saca, the old

Communist Party leader and FMLN candidate Schafik Handal won 24% more among

the wealthiest voters than he did among the poorest. Given the very strong connections

between business groups and ARENA, and given the revolutionary and largely rural

genesis of the FMLN, this result is deeply surprising. In the competition with the most

6 Throughout this chapter, all simulations include the effects of the three control

variables held constant at a given country’s means.

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conservative candidate, Daniel Ortega in Nicaragua, Michelle Bachelet in Chile, and

Tabaré Vázquez in Uruguay did no better among the poorest voters than among the

wealthiest.

The row for “average change” provides a crude summary of how powerful class

voting based on household wealth was in different countries. It is simply the average of

the statistically significant change in probabilities (the difference between how the

wealthiest and poorest voted). Non-significant coefficients count as 0 change in

probabilities. Based on data from a single year, Bolivia (-52%), Costa Rica (+37%),

Argentina (-27%), Brazil (-27%), El Salvador (+24%), and Peru (-23%) had strong class

voting in presidential elections. In Bolivia, Argentina, Brazil, and Peru, class voting

occurred along the lines Lipset (1960) predicted: the poor were more likely than the

wealthy to support the more progressive candidate. In Costa Rica and El Salvador, the

opposite pattern prevailed. There was no class voting in Chile, Ecuador, and Honduras.

Table 2 shows how often there is a negative association between higher

household wealth and leftist presidential voting, as Lipset’s classic hypothesis suggests.

We computed the percentage of significant negative associations between household

and vote in all paired comparisons between major presidential candidates. We also

verified the number of “wrong” associations (with positive numbers in Table 1 above)

and of insignificant associations. These three figures for each of the countries are shown

in Table 2. For instance, Mexico provides two comparisons of voter groups (Fox’s

voters vs. Cárdenas’s, and Fox’s voters vs. Labastida’s). In both comparisons, wealthier

voters were more likely than poor voters to support Fox.

Table 2 here

In nine of the twenty-two comparisons, poor voters were more likely than

wealthy voters to prefer the less conservative candidates, consistent with Lipset’s

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(1960) hypothesis. Conversely, in three paired comparisons, wealthy voters preferred

candidates to the left of the most conservative candidate. One of these was the very

puzzling case of more support among poor than wealthy voters for the conservative

candidate Antonio Saca (ARENA) over Schafik Handal of the leftist FMLN. The other

two involved centrist or center-left candidates whose primary base of support was the

urban middle class: Ottón Solis of the Citizens’ Action Party in Costa Rica and Carlos

Gaviria, who finished a distant second to Alvaro Uribe in Colombia’s 2006 presidential

election. Both campaigned more on civic than class issues.

In ten of the 22 paired comparisons of candidates, household wealth had no

statistically significant influence on the vote. It is not infrequent in Latin America that

relatively wealthier respondents prefer leftist candidates while the poorer respondents

prefer rightist ones. Urban educated middle classes often prefer progressive candidates,

while conservative candidates and parties have sometimes made significant inroads in

the lower classes (e. g. the PRI in Mexico and Fernando Collor de Melo, the winning

presidential candidate in Brazil in 1989; also recall that Brooks and Manza 1999

documented a shift from traditional class voting to this new type of class voting in the

US during the 1960s, and that Lipset (1960: 87-126) wrote long ago about working

class authoritarianism).

Among the candidates listed in Table 1, three had unequivocal profiles as radical

leftists: Evo Morales, who won the Bolivian election in 2005; Hugo Chávez, who was

the president in Venezuela; and Ollanta Humala in Peru. 7 If, as we hypothesized briefly

above, class voting emerges from strong class signals and conflicts created by

campaigns, political styles, and policies, class voting should be strong in these cases.

7 Levitsky and Roberts (2011) and Weyland et al. (2010) view Morales, Chávez, and

Rafael Correa as the leading expressions of the radical left. Humala unambiguouslysituated himself in this camp in the 2006 presidential campaign before switching to a

much more moderate platform in his victorious 2011 election.

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The data strongly confirm this hypothesis for two of these three candidates. Morales (-

52%) and Ollanta (-38%) fared vastly better among the poorest voters than among the

wealthiest. For Chávez (-4%), the difference was far less profound but nevertheless

statistically significant.

Household Wealth and Congressional Voting

In some countries of Latin America, legislative vote results diverge dramatically

from presidential results,8 and, as noted above, the former might give sharper insight

into “sincere” voter preferences. Hence, we analyze class voting (first by household

income) in congressional elections. The data in this section come from the 2006

LAPOP. The specific survey question is “For which party did you vote for deputy in the

last elections.” This question was not asked in Argentina, Bolivia, Brazil, the

Dominican Republic, Honduras, or Paraguay, so we do not include them in the analysis.

For Venezuela, there were relatively few respondents for the reference category, making

it impossible to estimate the model.

Table 3 presents the results. Models have the same control variables (sex, age,

and residence in large cities) as in Table 1. Again, the models include all parties but we

report results only of parties that won at least 10% of the vote among respondents who

said they voted for a deputy.

Table 3 here

Table 4 synthetically summarizes the results of Table 3. Summarized in this

gross way, class voting in the direction hypothesized by Lipset is weaker in legislative

than presidential voting. In only five paired comparisons were poorer voters more

8 In Brazil, for example, in 2010, the PT and PSDB combined for 80% of the first round

presidential vote compared to 27% of the vote for the Chamber of Deputies. Theeffective number of candidates in the 2010 presidential election was 2.75. The effective

number of parties (in votes) for the Chamber of Deputies was four times higher, 11.2.

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inclined than wealthier voters to choose the more left of the two parties. (The number

for presidential voting was nine paired comparisons.) In three comparisons, wealthier

voters were more likely than the poor to support the more progressive options. Nine

cases were statistically insignificant.

Table 4 here

Only a few of the differences between poor and wealthy voters follow a

stereotypical story of poor people voting in large proportions for leftist parties. In Chile,

wealthy voters were less likely than poor voters to choose the center-left Socialists over

the right wing UDI (-8%), and the gap between wealthy and poor voters was even

greater for the centrist Christian Democrats (-23%) in legislative elections. This pattern

is a contrast to the null results in presidential voting.

In Peru, consistent with our findings for the presidential election, poorer voters

were considerably more likely than wealthier voters to prefer the party label captured by

Ollanta Humala, the UPP, to the conservative Unidad Nacional (-16%). However, the

difference in the wealth profile of UPP voters was much more pronounced in the

presidential election (-38% versus -16%), suggesting that poor voters were drawn to the

charismatic figure of Humala without voting en masse for the UPP’s deputies.

Unfortunately, for purposes of testing our hypothesis that radical left candidates and

parties should be especially likely to induce class voting, the Peruvian case, which

supports this hypothesis, is the only one that has data for legislative voting.

In Mexico, consistent with past work on this issue, wealthy voters were far less

likely than poor voters (-29%) to support the PRI over the PAN. This finding is

consistent with a hypothesis that poor voters would prefer the more leftist of two

parties, and it is also consistent (and even more powerful than) our above finding for the

Mexican presidential election. By 2000, the PRI was a center-right party, so this is not a

17



stereotypical case in which the poor voted for the left. Interestingly, the household

wealth profile of the center-left PRD did not differ from that of the PAN.

Three cases are statistically significant, but wealthier voters supported the more

leftist of the two paired parties. Consistent with our finding for the 2004 presidential

election, the most surprising statistically significant result is that in El Salvador

wealthier voters reported that they were more likely than poor voters (+27%) to support

the leftist FMLN over the conservative ARENA. Consistent with the findings for

presidential elections, in Costa Rica, wealthier voters were much more likely (+31%)

than poor voters to prefer the center-left Citizen Action Party over the centrist National

Liberation Party. Finally, in Nicaragua, wealthier voters were relatively more likely

than poor voters (+10%) to choose leftist Daniel Ortega over the conservative

candidate. Given the hostile relationship between business groups and the FSLN when

it governed from 1979 to 1990, this finding is very surprising.

The final column of Table 4 provides a crude summary measure of whether the

pattern of class voting in legislative and presidential elections was largely similar or

somewhat different in each country. We scored a country as somewhat different if 1) for

any pair of parties, the household wealth variable was significant with one dependent

variable but not with the other; or 2) overall (as opposed to any specific pair of parties)

there was no statistically significant class voting for one kind of election but there was

for the other.9

Overall, there was a high level of consistency between presidential and

legislative results. In four of the nine countries, there were minor differences in class

9 In principle, we would also have coded a country as somewhat different if a paired

comparison was significant in both kinds of elections but with opposite changes in

probabilities (that is, the wealthier were more likely than the poor to vote for Party X’s presidential candidate, but less likely than the poor to vote for Party X’s deputies). Not

surprisingly, there were no such cases.

18



voting between presidential and legislative voting. In Chile and Nicaragua, there was no

class voting in the presidential election, but there was in legislative voting. In Colombia,

the opposite was true. In Mexico, in the competition between the PRD and PAN, the

wealthiest voters were 5% less likely than the poorest to choose the center-left

presidential candidate, Cuauhtémoc Cárdenas, over the PAN, but the household wealth

variable did not differentiate PRD and PAN candidates for deputy. In the other five

countries, the results were highly similar for presidential and congressional voting.

Class: Erikson and Goldthorpe’s Schema

The Erikson and Goldthorpe (1992) schema begins with employment status, i.e.,

the distinction between self-employed, employers, and employees. Two individuals

with the same occupation are usually parts of different classes in the Erikson and

Goldthorpe schema if their employment statuses are different. For example, a self-

employed accountant belongs to the petty bourgeoisie while an accountant who is an

employee for a firm is usually routine nonmanual. LAPOP 2006 provides employment

status for both those active in the labor force and those unemployed (variable OCUP1A

in the original questionnaire, and ocup1a in the pooled dataset).

The second and final consideration in the Erikson-Goldthorpe schema is an individual’s

occupation. They developed a fine-grained occupational coding that has been used in many

surveys in Western Europe. Accordingly, we used the question about the respondent’s

occupation (variable OCUP1 in the original questionnaire and ocup1_06 in the pooled dataset)

as the second step in coding respondents’ class. 10

10

Unfortunately the occupation and employment status variables were not asked in thesurveys of Brazil, Bolivia and Ecuador. This forced us to discard these countries from the

analysis since it is impossible to approximate the Erikson and Goldthorpe schema for them.

19



Unfortunately for our purposes, the 2006 LAPOP questionnaire does not allow for such

fine-grained distinctions; it had only eleven occupational categories compared to the ISCO88

and ISCO08 international five digit categories often used in the comparative surveys in

Western Europe that have followed Erikson and Goldthorpe. LAPOP’s categories are not

detailed enough on the occupation question to accurately code all respondents based just on

employment status and occupation. For this reason, we depart from Erikson-Goldthorpe and

use questions on education (variable ED in the questionnaire and ed in the dataset) and

household wealth to help build some class categories.

Using education and household wealth is essential to approximate Erikson-

Goldthorpe with LAPOP’s questions, and it is also consistent with their spirit. For

example, the service class is with few exceptions well educated and well off.

We began with the version of the Erikson-Goldthorpe schema with five class

categories. The service class (large owners, professionals, administrators, managers,

and high level supervisors) is the most privileged in terms of economic position. The

petty bourgeoisie includes small owners, farmers, and self-employed workers in

primary production. The routine non-manual class includes non-manual workers in

administration and commerce and sales personnel. The final two classes are skilled and

unskilled workers.

The Erikson and Goldthorpe schema was developed with the advanced

industrial democracies in mind. Using this schema for coding class in Latin American

countries requires some adjustments because of the deep cross-regional differences in

class structure. For the Latin American cases, we added a sixth class category that is not

part of the Erikson-Goldthorpe schema: the marginal (or poor) self-employed. This

category is essential for understanding class in Latin America. The poor self-employed

informal sector category constitutes a sizable part of most Latin American societies. It

20



is much larger and much poorer in most of Latin America than anywhere in Western

Europe. These six class categories, which are based on objective positions in the class

structure, differ from categories based on subjective (self-reported) class, income, or

household wealth.

Appendix 1 provides details of how we classified survey respondents into class

categories based on the LAPOP 2006 survey. Following Erikson and Goldthorpe, we first

divided respondents by employment status into four groups: 1) employees 2) employers; 3)

self-employed; and 4) unpaid workers. 11 The second step was to examine each LAPOP

occupational category (the first column). Where employment status and occupation did not

suffice to code class, Appendix 1 indicates how we used education and/or household wealth to

determine class.

For example, without using education and household wealth, we had no way to decide

whether owners (employment status) who were managers or technicians should be classified as

petty bourgeoisie or service class. Among these groups (and several others), we coded

individuals who had at least fifteen years of education and were in the top 20% of the

household wealth measure for the region as a whole and were in the top 20% of the household

wealth measure for their own country as service class.12 The education and household wealth

11 The category of unpaid workers does not exist as a separate category in Erikson and

Goldthore’s schema. Trabajador no remunerado o sin pago in the mother

questionnaire. There are only 80 cases in this category (less than 1% of the variable).12 Like Handlin (2013: 153-155), we used separate education and household wealth

measures rather than combining them because the service class is both (with few

exceptions) well educated and relatively well-off. A very high score for household

wealth should not compensate for low education (again, with few exceptions). We used

both a regional and country-specific measure of wealth because wealth is both absolute

(i.e., assessed by international standards) and relative (i.e., country-specific). An

individual who is in the upper echelon of the middle class in Bolivia (and hence might

be service class) would not be as comparatively well off, and hence might not be service

class, in the United States; this is why we needed a measure that considers country-

specific conditions. On the other hand, social scientists customarily think of wealth withsome reference to cross-national standards. In very poor societies, a lower percentage

should be categorized as service class.

21



thresholds are lenient separately for determining who should be categorized as service class,

but jointly they create a reasonable threshold. We coded owners who were managers or

technicians who had less than fifteen years of education or were in the bottom 80% of

household wealth for the region as a whole or for their country as petty bourgeoisie.

We also used household wealth to determine which self-employed individuals should be

categorized as “poor self-employed;” we included only those in the bottom 50% of household

wealth for the region as a whole. Unfortunately, LAPOP does not provide information on

occupation or employment status for the heads of households for students, retired, and

housewives, so we could not include those categories.

Table 5 shows the breakdown into six classes in the twelve countries included in our

analysis. The stark cross-national differences in class composition conform closely to what one

would expect on the basis of differences in level of development. The service class is much

larger in the more developed countries (Uruguay, Chile, Costa Rica, Mexico) than in the poor

countries (Nicaragua, Paraguay, Honduras, Guatemala). The bivariate correlation between the

size of the service class and per capita GDP is very high at .75.

Table 5 here

Conversely, the marginal self-employed class is substantially larger in the poor

countries. The bivariate correlation between the size of the marginal self-employed class and

per capita GDP is impressive at -.86.

The size of the skilled working class should be and is higher in the more developed

countries. The bivariate correlation between the size of the skilled working class and per capita

GDP is again high at .73. The distribution of classes by country lends strong credibility to the

validity of the coding.

Table 6 shows the mean household wealth of the six classes in the sixteen countries.

The service class should consistently be the wealthiest, and it is by a large margin in all

22



countries. The measure of mean country household wealth correlates very strongly (.90) with

per capita GDP. Cross-national differences in the mean household wealth of the service class

are relatively minor, reflecting the fact that all Latin American countries have an affluent upper

strata. Not surprisingly, skilled and unskilled workers fare much better in the wealthier

countries. The correlation between per capita GDP and mean household wealth of unskilled

workers is remarkably high at .91. The country means and the number of observations in Table

2 include individuals who were not categorized by class.

Table 6 here

Erikson-Goldthorpe Class Voting

These six class variables are dummy variables in the statistical analysis. The reference

class category in all comparisons is the petty bourgeoisie, traditionally seen as a class with

conservative political predilections.

Table 7 shows the results for presidential candidates for whom at least 10% of survey

respondents voted according to the survey. Table 8 shows the results for legislative voting.

Again, to save space, we do not show results for the control variables and show only the

statistically significant results.

Tables 7 and 8 here

A negative sign in Table 7 or 8 indicates that a given class was disproportionately

favorable to the more conservative (i.e., the reference) candidate or party, and a positive sign

means that the class voted disproportionately for the less conservative candidate or party. The

number shows the change in the likelihood that a given class would vote for one candidate over

another, relative to voting among the petty bourgeoisie. For example, in Argentina, in Table 7,

controlling for age, sex, and large city residence, unskilled workers were 1% more likely than

the petty bourgeoisie to vote for Cristina Fernández rather than Roberto Lavagna, among

23



unskilled workers and petty bourgeois who voted for one of these two candidates. In Bolivia,

two classes displayed a strong class vote against or in favor of Evo Morales. The service class

voted strongly (27% more in absolute terms) compared to the petty bourgeoisie for center-right

candidate Jorge Quiroga. Conversely, compared to the petty bourgeoisie, unskilled workers

tilted heavily toward Morales; 19% more unskilled workers voted for Morales compared to his

vote among the petty bourgeoisie (again, among unskilled workers and petty bourgeoisie who

voted for one of these two candidates).

In all countries but Chile, the results for legislative elections are very similar to those for

presidential elections (Table 7). In Chile, in legislative elections, unskilled workers and the

marginal self-employed voted more than the petty bourgeoisie for the three core parties of the

Concertación: the Christian Democrats, the Socialists, and the Party for Democracy.

For class analysis, the comparison of the working class (skilled workers, unskilled

workers, and marginal-self employed) is more politically relevant than the comparison between

the petty bourgeoisie and the service class or routine non-manual. As a simple way of

synthesizing Tables 7 and 8, Table 9 shows the percentage of statistically significant

comparisons between skilled workers, unskilled workers, or the marginal self-employed, on the

one hand, and the petty bourgeoisie, on the other. For example, in Table 7, for Argentina there

are six paired comparisons between skilled workers, unskilled workers, or the marginal self-

employed and the petty bourgeoisie. Only one of the six (17%) is statistically significant. The

final column adds the statistically significant coefficients (as an absolute value) for each

country and divides by the number of cells for that country in Table 7, and multiples by 100%.

The result is an easy-to-interpret preliminary summary measure of the strength of class voting.

For example, for Nicaragua, we took the only significant value (17%) in Table 7 in the three

working class comparisons (skilled workers, unskilled workers, and marginal self-employed)

and divided by three to derive the 5.7% figure in Table 9.

24



Table 9 here

Countries with strong class voting are the exception rather than the norm. Using the

Erikson-Goldthorpe schema, class voting in presidential elections was weak in Argentina,

Costa Rica, the Dominican Republic, El Salvador, Honduras, Mexico, Paraguay, Uruguay, and

Venezuela.

Table 9 again registers sharp cross-country variance. Class voting in presidential

elections was strongest in Guatemala, Peru, Bolivia, Nicaragua, and Brazil. Two of the three

countries with competitive radical leftist candidates, Bolivia (with Evo Morales) and Peru (with

Ollanta Humala) had strong class voting in presidential elections. Peru also had the highest

score for the legislative vote (for Bolivia, there is no data). We believe this is not by chance. In

their discourse and sometimes in their practice, radical leftist presidents emphasize solidarity

with the poor and economic redistribution, and they often criticize the wealthy as enemies of

the nation (Hawkins 2010). Class issues have been front stage of the national political scenes in

these countries.13 We hypothesize that strong class polarization provoked by presidents and

highly competitive presidential candidates is favorable to strong class voting. In contrast, class

voting was weak for the presidency in Venezuela.

There was some class voting in legislative elections in all of these countries except

Costa Rica and El Salvador, where there was none. Peru, Chile, and Guatemala had the highest

scores for class voting in legislative elections.

Assessing Lipset’s Hypothesis with the Erikson-Goldthorpe Variable

To what degree do the Latin American cases circa 2006 support Lipset’s hypothesis that

the poor vote for the left and the wealthy for the right? Table 10 synthetically summarizes the

results of Table 7 (presidential voting) and Table 8 (legislative voting) according to class

13 On characteristics of the radical left and its differences in relation to the moderate

left, see Levitsky and Roberts (2011); Weyland et al. (2010).

25



patterns (rather than by country). The second (presidential) and fifth (legislative) columns show

the consistency with Lipset’s hypothesis for each of the five classes other than the petty

bourgeoisie. Each major presidential candidate other than the most conservative candidate

counts as one case. The final column shows the number of statistically insignificant cases.

Table 10 here

Three findings stand out. First, the statistically significant results are overwhelmingly

consistent with Lipset’s hypothesis. For presidential voting, twenty-one of the twenty-five

statistically significant results are consistent with his theoretical expectations. For legislative

voting, all sixteen statistically significant results are consistent with his hypothesis. Overall,

then, 37 of 41 statistically significant results support Lipset.

The four exceptions are not terribly disruptive of Lipset’s claim. In two paired

comparisons, the service class voted more progressively than the petty bourgeoisie. The other

two exceptions involved campaigns with blurred ideological messages. One was the

competition between two conservative candidates (Joaquín Lavín of the UDI and Sebastián

Piñera of Renovación Nacional in Chile) among skilled workers in Chile. The other was the

competition among unskilled workers between center-right populist candidate Alvaro Uribe

and centrist Carlos Gaviria in Colombia. Unskilled workers were more likely than the petty

bourgeoisie to support Uribe.

Second, although the statistically significant results support Lipset’s hypothesis, the

solid majority of cells (76% for presidential voting and 80% for legislative voting) are not

significant. To some degree, the prevalence of non-statistical results stems from relatively small

numbers of individuals in each class—but as we saw earlier, even with the much larger number

of individuals for household wealth, class is often not a powerful factor in determining vote.

Thus, the results largely support the idea that class voting in Latin America is not strong, with

the caveat that it varies greatly by country.

26



Third, unskilled workers and the marginal self-employed engaged in far more class

voting than other classes. These two categories occupy the bottom of the wealth hierarchy in

Latin America. The marginal self-employed have historically been known for obstacles to

collective action and political mobilization. In contemporary Latin America, however, several

leftist and center-left presidential candidates have successfully appealed to this sector. President

Lula in Brazil (-12%), center-left candidate Alvaro Colom in Guatemala (-13%), center-left

candidate Cuauhtémoc Cárdenas in Mexico (-4%), and leftist candidate Ollanta Humala in Peru

(-16%) did well among the marginal self-employed. In light of some older literatures about

their low levels of politicization and their difficulties of engaging in collective action, it is

striking that the marginal self-employed along with unskilled workers engaged in far more

class voting in legislative elections than other classes. Likewise, a handful of leftist and center-

left candidates successfully mobilized the vote of unskilled workers: Evo Morales in Bolivia (-

19%), Alvaro Colom in Guatemala (-2%), Cuauhtémoc Cárdenas in Mexico (-3%), Daniel

Ortega in Nicaragua (-17%), and Ollanta Humala in Peru (-3%). Only in Bolivia and

Nicaragua, however, was there a large difference in how leftist and center-left candidates fared

among unskilled workers compared to the petty bourgeoisie.

This pattern of leftist and center-left electoral success among unskilled workers and the

marginal self-employed was far from uniform. For example, Michelle Bachelet in Chile,

Schafik Handal in El Salvador, Tabaré Vázquez in Uruguay, and Hugo Chávez in Venezuela

did not fare statistically better among unskilled workers or the marginal self-employed than

among the petty bourgeoisie.

Results in legislative voting were very similar. Several leftist and center-left parties

have done disproportionately well among unskilled workers and/or the marginal self-employed.

Examples include the Socialists and the PPD in Chile; the PRD in Mexico; and Humala’s 2006

party, the Union for Peru (Unión por el Peru) in Peru.

27



Table 10 shows very weak class voting by routine non-manual workers and—

surprisingly—skilled workers.

Consistency between Household Wealth and Erikson-Goldthorpe Measures of

Class

How consistent are the results between the two different measures of class? For

presidential voting, the results are very similar in ten countries. In Bolivia and Peru, there was

strong class voting with both measures of class. The results are also consistent for Brazil, Chile,

Colombia, Guatemala, Honduras, Paraguay, and Uruguay.

In Nicaragua, the household wealth measure shows no difference between Daniel

Ortega of the leftist FSLN and the Enrique Bolaños of the conservative PLC. With the Erikson-

Goldthorpe measure of class, compared to his results among the petty bourgeoisie, Ortega did

better than Bolaños in the service class, non-manual routine, and unskilled workers. Because

the three classes in which Ortega enjoyed comparative success ranged from the wealthiest in

Nicaragua (the service class) to the poor (unskilled workers, see Table 7), this finding for the

Erikson-Goldthorpe variable is consistent with the null finding for household wealth, but it

presents a more differentiated picture.

In Mexico, results were very similar in the competition between the PAN and the PRD,

but somewhat different in the competition between the PAN and the PRI. The Erikson-

Goldthorpe measure does not show any class voting between the PRI and the PAN, whereas

with household wealth, the most affluent voters were less likely than the poor (-17%) to favor

the PRI over the PAN.

In three countries, the two measures of class suggest different pictures. In Argentina, the

most affluent voters were much less likely (-53%) than the poorest to favor Cristina Fernández

rather than Roberto Lavagna. The Erikson-Goldthorpe measure detected only weak class voting

28



among unskilled workers. In Costa Rica, affluent voters favored Ottón Solis (+37%) more than

poor voters did, but the Erikson-Goldthorpe measure shows no class voting. In El Salvador,

affluent voters supported the FMLN candidate (+24%) more than the poorest voters; again, the

Erikson-Goldthorpe measure shows no class voting.

For legislative elections, most results are again similar with the two measures of class.

For Colombia, Guatemala, Mexico, Nicaragua, and Peru, the results are strikingly similar

across both measures. For three of the four Chilean parties (not counting the reference party),

they are also similar: the Socialists, the Christian Democrats, and National Renovation. For the

Party of Democracy (PPD), the results differ some across the two measures. The PPD has the

same household wealth profile as the UDI, but with the Erikson-Goldthorpe schema, the PPD

does comparatively better than the UDI among unskilled workers and the marginal self-

employed.

Costa Rica is the outlier. As was also true in presidential voting, the two measures of

class yield different results. The wealthier voters were much more likely (+31%) than the poor

to vote for the Citizen Action Party, but the Erikson-Goldthorpe variable did not show class

voting.

How can we square the results in the three countries with important differences in

presidential voting and the one with important differences in congressional voting? We are

confident that both sets of results are correct, and we do not have an immediate answer for why

the differences are so striking. The samples are different; the Erikson-Goldthorpe variable

includes only individuals who are in the labor force. Also, the theoretical constructs are

different. The N with the household wealth measure is much higher because the Erikson-

Goldthorpe measure entails dividing respondents into six different classes. The larger N

reduces standard errors and makes it more likely to obtain a statistically significant result.

Finally, the continuous nature of the house wealth variable might make it more likely to detect

29



differences among classes.

Change Over Time

We need to write this section

Conclusions

We need to write the conclusions. For lack of time, here we present a few bullet points.

1. Overall, class voting in Latin America is fairly modest.

2. The magnitude of class voting varies greatly by country.

3. Bolivia and Peru are the only countries that by both measures of class had strong

class voting in the 2006/08 LAPOP. They were two of the three countries with strong radical

leftist presidential candidates. Radical left candidates and presidents constantly emphasize class

issues, and as a result, the probability of sharper class divisions in elections increases.

Nevertheless, modest class voting in Venezuela shows that this tendency is not inexorable.

4. The magnitude of class voting varies greatly by class in the Erikson-Goldthorpe

schema. Unskilled workers and the marginal self-employed engaged in far more class voting

than other classes. It is not surprising that voting patterns among the service class did not

diverge markedly from those of the petty bourgeoisie. It is, however, notable that the voting

patterns of skilled workers were similar to those of the petty bourgeoisie, diverging in only four

of the thirty-seven cases (combining the presidential and legislative vote) in Table 10.

5. To the degree that there is class voting in Latin America, it is almost always

consistent with Lipset’s hypothesis. But contra Lipset’s hypothesis, strong class voting is not

the norm in most countries.

6. It is difficult to explain differences in class voting among Latin American cases based

on structural variables such as the level of poverty, the level of inequality, or the level of

development. In the 1990s, class voting was strongest in Chile and Uruguay, two of the most

30



developed countries in the region (Torcal and Mainwaring 2003b). Circa 2006, it was strongest

in one poor country (Bolivia) and one middle income country (Peru), and it was weak in

Uruguay and modest in Chile.

31



Table 1: Household wealth and Presidential Vote (2006-2008)

Country Candidate

andpercentage of vote in survey

Change in

votingprobabilities

frompoorest towealthiest

voters

Pseudo R-

Square

N

Argentina Cristina E. Fernández deKirchner (FPV)

(38.5%)

-

(0.53)

0.05

331

Elisa M.A. Carrio (CC)(27.1%)

233

Roberto Lavagna (UNA)(Reference) (18.8%)

-162

Average change 0.27 860

Bolivia Evo Morales (MAS)(64.1%)

-(0.52)

0.05

940

Poder Democrático Social(PODEMOS)

(Reference) (23.2%)

341


Brazil Luiz I. Lula da Silva (PT, PcdoB,PRB)

(78%)

-(0.27)

0.06

836

Partido de la SocialdemocraciaBrasileña

(Reference) (19.5%)

209


Chile Michelle Bachelet (Partidos porla Concertación)

(60.7%)0.02

536

Sebastián Piñera (RN)(21.4%)

189

Unión Demócrata Independiente

(Reference) (14.5%)128

Average change 0 883

Colombia Carlos Gaviria Díaz (PoloDemocrático Alternativo)

(15.8%)

+

(0.14)0.04

129

Partido Liberal(Reference) (74.6%)

611

Average change 0.14 819Costa Rica Otton Solís (PAC)

(37.3%)+

(0.37)0.04

367

Partido Liberación Nacional

(PLN)(Reference) (46.3%)

456


Dominican Rep. Hipólito Mejía (PRD)(26.8%)

0.02

275

Partido de la LiberaciónDominicana


Average change 0 1026Ecuador Lucio Edwin Gutiérrez Borbua

(Partido Sociedad Patriotica 210.03 1218

32



Enero)

(59.9%)Partido Renovador Institucional

Acción Nacional (PRIAN)(Reference) (19.8%)

402


El Salvador Schafik Hándal (FMLN)(37.5%)

+(0.24)

0.07

307

Alianza RepublicanaNacionalista (ARENA)

(Reference) (54.1%)

443


Guatemala Frente RevolucionarioGuatemalteco

(11.9%)

0.02

82

Unidad Nacional de la Esperanza(UNE)

(18.9%)

-0.07 130

Gran Alianza Nacional (GANA)(Reference) (53.8%) 370


Honduras Manuel Zelaya (PLH)(58.4%)

0.02674

Partido Nacional(Reference) (38.6%)

446


Mexico Francisco Labastida (PRI)

(28.7%)

-

(0.17)

0.02

258

Cuauhtemoc Cárdenas (PRD)(10.4%)

-(0.05)

94

Alianza por el cambio

(PAN/PVEM)(Reference) (60.9%)

548


Nicaragua Daniel Ortega (FSLN)(48.5%)

0.01

450

Partido Liberal

Constitucionalista (PLC)(Reference) (47.9%)

444


Paraguay Julio Cesar Franco (PLRA)

(22.7%)0.05

133

Partido Colorado(Reference) (65.6%)

384


Peru Ollanta Humala (Unión por elPerú (UPP)

(35.5%)

-(0.38)

0.04

431

Alan García (Partido ApristaPeruano )

(28.6%)

-(0.08)

348

Unidad Nacional(Reference) (22.7%)

276


Uruguay Tabaré Vázquez (Frente Amplio-Encuentro)

(60.7%) 0.06

564

Jorge Larrañaga (PartidoNacional)

258

33



(27.8%)Partido Colorado



Venezuela Hugo Chávez (MVR, PPT,PODEMOS, PCV)

(79.3%)

-(0.04)

0.01

743

Nuevo Tiempo



Source: 2006 LAPOP for most countries; 2008 LAPOP for Argentina, Bolivia, Brazil andVenezuela.

34



Table 2Summary of statistical associations between household wealth and first round

presidential vote by country

Country Year of presidential

election priorto 2006/2008

LAPOP survey

number of pairedcomparisons in

which higherhousehold wealth is

associated with

more conservative

presidential vote

number of pairedcomparisons in

which higherhousehold wealth is

associated with

more leftist

presidential vote

number of pairedcomparisons with

no significantassociations

Argentina 2007 1 0 1

Bolivia 2005 1 0 0

Brazil 2006 1 0 0

Chile 2005 0 0 2

Colombia 2002 0 1 0

Costa Rica 2006 0 1 0

Dom. Republic 2004 0 0 1Ecuador 2002 0 0 1

El Salvador 2004 0 1 0

Guatemala 2003 1 0 1

Honduras 2005 0 0 1

Mexico 2000 2 0 0

Nicaragua 2001 0 0 1

Peru 2006 2 0 0

Paraguay 2003 0 0 1

Uruguay 2004 0 0 1

Venezuela 2006 1 0 0

Total - 9 3 10

Source: Based on Table 1

35



Table 3: Household wealth and Legislative Voting in Latin America (2006-2008)

Countries Political partyand

percentage of vote

Change invoting

probabilitiesfrom poorest

to wealthiestvoters

PseudoR-

Square

N

Chile Partido Socialista(22.0%)

-0.08

0.01

Partido por la Democracia(20.1%)

Partido Demócrata Cristiano

(19.8%)

-

0.23Renovación Nacional

(18.9%)UDI (reference)


Colombia Polo Democrático Independiente(11.3%)

Partido de la U(24%)

Partido Liberal (reference)


Costa Rica PAC(31.8%)

+0.31

PLN (reference)


El Salvador FMLN(45.1%)

+0.27

0.06

ARENA (reference)

Average change 0.27 834Ecuador Partido Social Cristiano

(20.7%)0.04Partido Sociedad Patriotica 21 de

Enero(25.4%)

Izquierda Democrática(12.1%)

Partido Renovador Institucional

Acción Nacional (PRIAN)(reference)


Guatemala Frente Republicano

Guatemalteco(13.8%)

0.03Unidad Nacional de la Esperanza

(UNE)(17.2%)

Partido Avanzada Nacional

(14.7%)

Gran Alianza Nacional (GANA)(reference)


Mexico PRI

(40.4%)

-

0.290.03

PRD(18.0%)PAN (reference)

36




Nicaragua FSLN(55.1%)

+0.10

0.02Partido LiberalConstitucionalista (PLC)

(reference)

Average change 0.10 744Peru Unión por el Perú (UPP)

(19.7%)-

(0.16)

0.05

Partido Aprista Peruano(APRA)

(26.9%)

-(0.03)

Alianza por el Futuro(12.4%)

Unidad Nacional (reference)


Venezuela DEPENDENT VARIABLEVERY SKEWED WITH FEWCASES IN THE REFERENCE

PARTY

Source: 2006 LAPOP

37



Table 4Summary of statistical associations between household wealth and legislative vote

by country

Country number of paired

comparisons in

which higher

household wealth

is associated with

more conservative

vote

number of paired

comparisons in

which higher

household wealth

is associated with

more leftist vote

number of paired

comparisons with

no significant

associations

Similar to or

somewhat

different from

results for

presidential voting

Chile 2 0 2 different

Colombia 0 0 2 different

Costa Rica 0 1 0 similar

Ecuador 0 0 2 similar

El Salvador 0 1 1 similar

Guatemala 0 0 3 similarMexico 1 0 1 different

Nicaragua 0 1 0 different

Peru 2 0 0 same

Total 5 3 11

Source: Based on Table 3

38



Table 5Distribution of Erikson-Goldthorpe Classes by Country

Servi

Class

Petty

Bourgeoi

Routine

Non-Ma

Skilled

Workers

Unskille

Workers

Marginal

self-employed

Total Numbe Per capita

Argentina 7.0 22.9 23.3 8.8 34.7 4.4 100 731 NA

Bolivia 3.9 14.9 17.8 4.2 15.7 43.4 100 1393 4,350

Brazil 4.2 23.9 13.1 3.7 30.0 25.0 100 593 10,093

Chile 13.8 22.8 13.4 14.0 30.7 5.4 100 636 14,520

Colombia 6.3 25.2 9.8 11.3 21.9 25.6 100 767 8,479

Costa Ric 12.8 31.1 11.8 15.1 26.1 3.1 100 704 10,453

Dominica

Republic

5.6 22.6 12.8 9.0 26.7 23.3 100 703 8,387

Guatemala 3.2 19.7 13.1 3.8 22.7 37.6 100 758 4,297

Honduras 2.6 17.3 10.0 7.0 32.0 31.2 100 770 3,519

Mexico 6.5 31.2 10.9 11.2 26.8 13.4 100 753 12,481

Nicaragua 3.0 13.9 10.7 3.6 21.9 46.9 100 698 3,249

Paraguay 2.2 22.7 7.2 6.3 23.3 38.3 100 695 4,626

Peru 5.8 18.5 14.4 7.6 12.1 41.8 100 780 8,555

El Salvad 6.9 16.5 11.0 11.4 24.5 29.6 100 709 5,978

Uruguay 7.3 22.6 16.8 18.7 31.2 3.5 100 603 12,642

Venezuela 5.9 28.1 23.4 17.2 16.1 9.2 100 726 10,973

Source: Based on LAPOP 2006 for all countries except Argentina, Bolivia, Brazil, and

Venezuela; based on LAPOP 2008 for Argentina, Bolivia, Brazil, and Venezuela.

Source for per capita GDP in 2010: World Bank, World Development Indicators,

Purchasing Parity Power, constant 2005 international dollars.

39



Table 6: Mean Household Wealth by Erikson-Goldthorpe Class and Country

Service

Class

Petty

Bourgeois

Routine

Non-Manua

Skilled

Workers

Unskilled

Workers

Marginal Poor

employed

Country

Mean

Number

Argentina 3.0 1.9 1.9 1.8 1.6 -0.6 1.3 1487

Bolivia 2.6 0.7 -0.4 -1.4 -0.9 -1.9 -1.0 2976

Brazil 2.8 1.7 1.3 1.0 0.6 -1.2 0.5 1487

Chile 3.3 1.8 1.7 1.4 0.8 -1.0 1.3 1517

Colombia 2.8 1.1 0.8 0.8 -0.5 -1.1 0.1 1491

Costa Rica 3.3 2.1 2.1 1.8 0.9 -0.7 1.6 1500

Dominican

Republic

2.9 1.1 0.4 0.4 -0.6 -1.6 -0.2 1516

Guatemala 3.1 1.2 0.6 0.6 -0.7 -1.8 -0.5 1498

Honduras 3.0 1.1 0.4 -0.0 -1.1 -2.0 -0.6 1585

Mexico 3.2 1.6 1.6 1.3 0.6 -1.3 0.7 1560

Nicaragua 2.7 0.3 -0.2 -0.2 -1.5 -2.1 -1.4 1762

Paraguay 2.7 1.0 0.2 0.6 -0.7 -1.8 -0.5 1160

Peru 2.6 0.6 0.1 0.5 -0.3 -1.7 -0.5 1500

El Salvador 2.9 1.0 0.4 0.3 -1.2 -1.8 -0.5 1729

Uruguay 3.3 2.0 2.1 1.6 0.8 -0.8 1.2 1200

Venezuela 3.1 1.6 1.7 1.2 0.7 -1.1 1.1 1510

Source: Based on LAPOP 2006 for all countries except Argentina, Bolivia, Brazil, and

Venezuela; based on LAPOP 2008 for Argentina, Bolivia, Brazil, and Venezuela.

40



Table 7: Class voting for presidential elections in Latin America with the Erikson and Goldthorpe class schema (2006-2008)

Country Presidential candidateand

percentage of vote in LAPOPsurvey

ServiceClass

Non-manualWorkers

SkilledWorkers

UnskilledWorkers

MarginalClass

Pseudo R-Square

N

Argentina Cristina E. Fernández deKirchner (FPV)

(38.5%)

+(0.01)

0.05172

Elisa M.A. Carrió (CC)

(27.1%)139

Roberto Lavagna (UNA)(Reference) (18.8%)

96

Average change 0 0 0 0.005 0

Bolivia Evo Morales (MAS)(64.1%)

-(0.27)

+(0.19)

0.05

500

Poder Democrático Social(PODEMOS)


Average change 0.27 0 0 0.19 0

Brazil Luiz I. Lula da Silva (PT, PcdoB,PRB)(78%)

+(0.12)

0.06

836

Partido de la SocialdemocraciaBrasileña


Average change 0 0 0 0 0.12

Chile Michelle Bachelet (Partidos porla Concertación)

(60.7%)0.05

536

Sebastián Piñera (RN)(21.4%)

-(0.22)

189

Unión Demócrata Independiente(Reference) (14.5%)

128

Average change 0 0 0.11 0 0

41



Colombia Carlos Gaviria Díaz (PoloDemocrático Alternativo)

(15.8%)

+(0.18)

-(0.09)

0.06129

Partido Liberal(Reference) (74.6%)

611

Average change 0.18 0 0 0.09 0

Costa Rica Otton Solís (PAC)(37.3%)

0.06

367

Partido Liberación Nacional(PLN)

(Reference) (46.3%)

456

Average change 0 0 0 0 0

Dominican Rep. Hipólito Mejía (PRD)(26.8%)

0.02

275

Partido de la LiberaciónDominicana



El Salvador Schafik Hándal (FMLN)(37.5%)

0.07

307

Alianza RepublicanaNacionalista (ARENA)




(11.9%)

0.04

82


(18.9%)

+(0.32)

+(0.14)

+(0.16)

130

Gran Alianza Nacional (GANA)(Reference) (53.8%)

370

Average change 0 0 0.16 0.07 0.08

Honduras Manuel Zelaya (PLH)(58.4%)

0.05 674

42



Partido Nacional(Reference) (38.6%)

446


Mexico Francisco Labastida (PRI)(28.7%)

0.02

258

Cuahtemoc Cardenas (PRD)(10.4%)

+(0.03)

+(0.04)

94

Alianza por el cambio(PAN/PVEM)


Average change 0 0 0 0.02 0.02Nicaragua Daniel Ortega (FSLN)

(48.5%)+

(0.24)+

(0.17)+

(0.17)

0.04

444

Partido LiberalConstitucionalista (PLC)


Average change 0.24 0.17 0 0.17 0

Paraguay Julio Cesar Franco (PLRA)(22.7%)

-(0.21)

0.08133

Partido Colorado(Reference) (65.6%)

384

Average change 0.21 0 0 0 0

Peru Ollanta Humala (Unión por elPerú (UPP)

(35.5%)

-(0.13)

+(0.03)

+(0.16)

0.06

431

Alan García (Partido ApristaPeruano )(28.6%)

+(0.09)

+(0.12)

348

Unidad Nacional(Reference) (22.7%)

276

Average change 0.07 0 0 0.06 0.14

Uruguay Tabaré Vázquez (Frente Amplio-Encuentro)

(60.7%)

+(0.13) 0.07

564

Jorge Larrañaga (Partido + 258

43



Nacional)(27.8%)

(0.06)

Partido Colorado(Reference) (8%)

74

Average change 0 0.10 0 0 0

Venezuela Hugo Chávez (MVR, PPT,PODEMOS, PCV)

(79.3%)

-(0.23)

0.02743

Nuevo Tiempo(Reference) (20.7%)

194

Average change 0.23 0 0 0 0

Source: LAPOP 2006 survey for all countries except Argentina, Bolivia, and Brazil; LAPOP 2008 for Argentina, Bolivia, Brazil, and Venezuela.

44



Table 8: Class voting for Legislative Elections in Latin America with the Erikson and Goldthorpe class schema (2006)

Country Political Partiesand

percentage of vote

ServiceClass

Non-manualWorkers

SkilledWorkers

UnskilledWorkers

MarginalClass

Pseudo R-Square

N

Chile Partido Socialista(22.0%)

+(0.06)

+(0.19)

0.06

49

Partido por la Democracia(20.1%)

+(0.06)

+(0.27)

65

Partido Demócrata Cristiano(19.8%)

+(0.09)

47

Renovación Nacional(18.9%)

48

UDI (reference)

Average change 0 0 0 0.05 0.23

Colombia Polo Democrático Independiente(11.3%)

+(0.14)

35

Partido de la U(24%)

70

Partido Liberal (reference)

Average change 0 0 0 0 0.07

Costa Rica PAC(31.8%)

PLN (reference)


El Salvador FMLN(45.1%) 0.05

ARENA (reference)



(13.8%)0.05

54

Partido Avanzada Nacional - 36

45



(PAN)(14.7%)

(0.16)


(17.2%)

+(0.14)

81

Gran Alianza Nacional (GANA)(reference)

Average change 0 0 0.05 0 0.05

Mexico PRI(40.6%)

+(0.12)

0.03

150

PRD(18.0%)

+(0.04)

62

PAN (reference)

Average change 0 0 0 0.06 0.02

Nicaragua FSLN(55.1%)

+(0.17)

0.04 215

Partido Liberal Constitucionalista(PLC) (reference)

Average change 0 0.17 0 0 0

Peru Unión por el Perú (UPP)(19.7%)

-(0.13)

+(0.13)

0.05100

Partido Aprista Peruano (APRA)(26.9%)

+(0.09)

+(0.12)

130

Alianza por el Futuro(12.4%)

Unidad Nacional (reference)

Average change 0.04 0 0 0.03 0.08

Venezuela DEPENDENT VARIABLEVERY SKEWED WITH FEWCASES IN THE REFERENCE

PARTY

Source: Based on LAPOP 2006 .

46



Table 9

Synthetic summary of class voting in presidential and legislative elections, Erikson-

Goldthorpe schema, by country

Country Presidential voting Legislative voting

% significant, wor

compared to petty

bourgeoisie

Sum of significant

change in probabil

divided by numbe

cells *100, worker

compared to petty

bourgeoisie

% of statistically

significant cells,

working class co

to petty bourgeoisi

sum of significant

change in

probabilities

divided by

number of cells *

100%,

working class co

to petty bourgeoisi

Argentina 17 0.2 - -

Bolivia 33 6.3 - -

Brazil 33 4.0 - -

Chile 17 3.7 42 5.8

Colombia 33 3.0 17 2.3

Costa Rica 0 0 0 0

Dominican Republic 0 0

El Salvador 0 0

Guatemala 50 10.3 22 3.3

Honduras 0 0

Mexico 33 1.2 33 2.7

Nicaragua 33 5.7 0 0

Paraguay 0 0

Peru 67 6.7 50 6.2

Uruguay 0 0

Venezuela 0 0 - -

47



Total 23 2.5 27 3.3

Note: Column 5 is the sum of the absolute values of the changes in probabilities.

Source: Based on Tables 7 and 8.

48



Table 10

Assessing Lipset’s Hypothesis:Summary of statistical associations between Erikson-Goldthorpe Class and Vote

Presidential Vote Legislative Vote

Class # cases where poorer

voted for more progre

candidate

# cases where poorer

voted

for conservativecandidates

# cases without

class voting

# cases where poorer c

voted for more progres

candidate

# cases where poorer

voted

for conservativecandidates

# cases witho

class voting

Service class 4 2 15 1 0 15

Routine

non-manual

3 0 18

1 0 15

Skilled

workers

2 1 18

1 0 15

Unskilled work 7 1 13 6 0 10

Marginal

self-employed

5 0 16

7 0 9

49





PrivateEmployers(OCUP1A)

Employees14

(Government or

private) Self-employed15

Unpaid worker

Occupation16

Subdivided byeducation (ED)

and wealth

Our class coding Subdivided byeducation (ED)

and wealth

Our class codingSubdivided by education

(ED) and wealth

Our class coding Our class coding

Professional, manager

15 + years

education andwealth top 20%*

Service class 15 years +

education &wealth top 20%*

Service class15 + years education and

wealth top 20%*Service class Routine non-manual

less than 15 years

education ORwealth bottom80%**

Petty bourgeoisie less than 15 years

of education ORwealth bottom80%**

Routine non-manual

< 15 years of education ORwealth bottom 80%**

Petty bourgeoisie

Technician

15 + yearseducation and

wealth top 20%*

Service class 15 years +education &

wealth top 20%*

Service class15 + years education and

wealth top 20%*Service class

Skilled worker

less than 15 years

education OR

wealth bottom80%**

Petty bourgeoisie less than 15 years

of education OR

wealth bottom80%**

Routine non-

manual

If not service class and

wealth top 50%**Petty bourgeoisie

Wealth bottom 50% Marginal self-employed

Office worker (oficinista)

15 + yearseducation and

wealth top 20%*

Service class 15 years +education &

wealth top 20%*

Service classIf 15 + years education andwealth top 20%*

Service classRoutine non-manual

less than 15 years

education ORwealth bottom

80%**

Petty bourgeoisie Less than 15

years ofeducation OR

wealth bottom

Routine non-manual

If education < 15 or wealth bottom 80%**

Petty bourgeoisie

14 In the LAPOP 2006 mother questionnaire (Spanish version) the variable with this information is OCUP1A. In the 2006 pooled dataset the

variable is ocup1a.15

Trabajador por cuenta propia in the mother questionnaire.16

In the LAPOP 2006 mother questionnaire (Spanish version) the variable with this information is OCUP1. In the 2006 pooled dataset the

variable is ocup1_06.

51



80%**

Comerciante

15 + years

education and

wealth top 20%*

Service class 15 years +

education &

wealth top 20%*

Service classIf 15 + years education AND

wealth top 20%*Service class

Routine non-manual

less than 15 years

education ORwealth bottom80%**

Petty bourgeoisie Less than 15

years ofeducation ORwealth bottom

80%**

Routine non-

manual


wealth top 50%Petty bourgeoisie

wealth bottom 50% Marginal self-employed

Campesino o agricultor

15 + years

education and

wealth top 20%*

Service class 9 + years

education AND

wealth top 50%

Skilled worker wealth top 50% Petty bourgeoisie

Unskilled worker

less than 15 years


80%**

Petty bourgeoisie < 9 years


50%

Unskilled worker wealth bottom 50% Marginal self-employed

Peón agrícola NA NA Unskilled worker NA NA Unskilled worker

Artisan

Petty bourgeoisie 9 + years

education andwealth top 50%

Skilled worker wealth top 50% Petty bourgeoisie

Unskilled worker

< 9 yearseducation OR

wealth bottom

50%

Unskilled

workerswealth bottom 50% Marginal self-employed

Domestic service NA NA Unskilled worker NA NA Unskilled worker

Other services

15 + years

education andwealth top 20%*

Service class 15 + years

education ANDwealth top 20%*

Service class If 15 + years education ANDwealth top 20%* Service class

Unskilled worker

less than 15 years

education OR

wealth bottom80%**

Petty bourgeoisie9+ years

education and

wealth top 50%

Routine non-

manual if not in

service class


wealth top 50%Petty bourgeoisie

< 9 yearseducation OR

Unskilled worker wealth bottom 50% Marginal self-employed

52



wealth bottom

50%

Skilled worker Petty bourgeoisie Skilled worker wealth top 50% Petty bourgeoisie Skilled worker


Unskilled worker Petty bourgeoisie Unskilled worker wealth top 50% Petty bourgeoisie Unskilled worker


• Top 20% of household wealth within the individual’s country and for the region as a whole.

** Bottom 80% of household wealth within the individual’s country OR for the region as a whole.

53



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Documents

Class Voting 13 May