Ideological Dimensions and Left-Right Semantics in Latin America
Guillermo Rosas
[email protected]
Elizabeth J. Zechmeister
[email protected]
Duke University, Department of Political Science
Abstract: This paper presents a preliminary analysis of ideological divides and left-right semantics
among Latin American legislators. The data are taken from the 1997 Parliamentary Elites of Latin
America survey project, compiled by researchers at the Universidad de Salamanca, Spain. In the first
half of the paper, we explore the character of legislative “ideological” and “political” spaces in eleven
Latin American countries. In the second half, we examine the significance of left-right semantics in
these same countries. Our analysis of ideological divides reveals that parties in Latin America, even
those we might confidently label clientelistic, are organized around clear ideological dimensions.
Our analysis of left-right semantics shows that left-right labels are meaningfully related both to party
labels and to ideological dimensions in Latin America, though the party component outweighs the
ideological component in all cases.
This paper is part of a larger research project studying Latin American legislatures. In addition to the
authors, the project includes Sarah Brooks, Kirk Hawkins, Herbert Kitschelt, and Scott Morgenstern.
We are grateful to these people for their insights and support. Errors remain ours alone.
Prepared for delivery at the 2000 meeting of the Latin American Studies Association, Hyatt Regency
Miami, March 16-18, 2000.
1
I.
Introduction
Ideologies structure and simplify political choices. They aggregate a multiplicity of issues into a
small number or dimensions from which voters can reasonably calculate a rational political choice
(e.g., Downs 1957; Hinich and Munger 1994). Many Latin American countries, however, are
perceived to have non-programmatic political systems in which parties attract voters by distributing
selective incentives or ensure victory through fraud and/or coercion. Other countries in Latin
America appear to have political systems in which parties, structured along competitive divides, relay
clear signals to voters of their relative positions in the political space. In the first half of this paper,
we offer a preliminary analysis of a 1997 survey of Latin American legislators that explores the
character of the legislative “ideological” and “political” space in eleven countries. Our results
suggest that parties in Latin America, even those we might perceive as non-programmatic, are
organized around clear ideological dimensions.
Ideologies condense the political system into a lower-dimensionality space. However, to
make an informed choice voters must still locate themselves and the parties that compete for their
vote with respect to these ideologies. In political systems with multiple competitive ideological
dimensions and more than two parties, the complexity of the calculation the voter must make can be
extreme. Left and Right are tools that voters may use to further simplify the political space. By
using left-right semantics, voters can conceivably array the political parties across a single dimension
(Inglehart & Klingemann 1976). At the very least, left-right semantics can provide voters with cues
with which to understand the relationship of one party to another.
In the second half of this paper, we explore the significance of left-right semantics in Latin
America. Some of the questions we are interested in are the following: Do “left” and “right” partyplacements by legislators correspond to scholars’ interpretations of these parties’ ideological
positions? What cognitive meanings are attached to Left and Right in Latin America? How are the
ideological dimensions that we identify in the first part of our paper related to left-right party
positioning? In this analysis, our results show that left-right semantics are meaningfully related both
to party labels and to ideological dimensions in Latin America, though the party component
outweighs the more substantive ideological component in all cases.
II.
The Data
We analyze data from the 1997 Parliamentary Elites of Latin America project, directed by
Manuel Alcántara (Universidad de Salamanca) and financed by Spain’s Comisión Interministerial de
Ciencia y Tecnología. The Salamanca survey was administered in eighteen Latin American
countries, which include almost all of continental Latin America. For the purpose of cross-national
comparison, we kept eleven of these countries: Argentina, Bolivia, Brazil, Chile, Colombia, Costa
Rica, Ecuador, Mexico, Peru, Uruguay, and Venezuela. Data limitations forced us to leave out El
Salvador, while limited time led us to leave out the Dominican Republic, Guatemala, Honduras,
Nicaragua, Panama, and Paraguay. Be that as it may, our sample is fairly representative. It includes
countries with large and small indigenous minorities, low- and middle-income countries, and longstanding democracies or societies with lengthy histories of party competition alongside countries that
have recently transited to democracy and others with dubious democratic credentials.
The survey codes legislators’ answers to 104 questions in 257 variables. Respondents were all
2
national representatives to their respective country’s lower chamber at the time of the interview (or to
the unicameral legislature, in the case of Costa Rica, Ecuador, El Salvador and Peru). The sample
size varies by country in both absolute and relative terms, going from a low of 46 observations in El
Salvador to 123 in Mexico. The survey targeted politicians from all political parties represented in a
country’s national assembly. In our analysis, respondents from all parties are included, but we often
report results only for parties with more than six, or in other cases, two respondents. Table 1 reports
legislative party shares and sample sizes for each of our twelve cases. As Table 1 shows, some of
our samples over-represent the parties, while others are under-representative. In later analysis in
which country is the unit of analysis, we weight our data to correct for these distortions. The weights
we use are reported in the last column of Table 1.
INSERT TABLE 1
We use legislators’ responses to 26 questions in order to define the content of the legislative
“space” across the Latin American countries in our analysis. These questions cover a wide range of
relevant issues. In our analysis of left-right semantics, we also use a question that asked legislators to
place their party on a left-right scale. Appendix A contains information on the creation of the
weights, and on the methodology we use to construct multidimensional legislative spaces from our 26
variables. Appendix B contains a list of the variables that we use in our analysis.
III.
Mapping ideological divides in Latin American legislatures
Defining ideological and political spaces. Ideology provides voters with a convenient, cost-saving
tool with which to differentiate and choose among parties. As Downs originally noted, ideologies
save voters the cost of realizing their own stance on every single issue, the candidates’ or parties’
placement on these same issues, and the distance between the two. Ideologies provide voters with a
cue, a cognitive “shortcut” into the opinions and programs of candidates. Ideologies form a space of
low dimensionality in which the average voter is capable of distinguishing among the general
tendencies of the different candidates and parties (Downs 1957; Hinich and Munger 1994). Ideology,
therefore, is important to the functioning of a programmatic party system because it allows voters to
make rational vote choices that reflect their ideal issue positions while minimizing information costs
from learning the exact locations (platforms) of parties.
The programmatic character of many a political party —and, consequently, the relevance of
ideologies as platform signals— can be questioned on empirical grounds. Indeed, some Latin
American countries are perceived as having non-programmatic political systems. Parties in these
systems attract voters by distributing selective incentives (clientelistic parties) or through the
charisma of their leaders (personalistic parties). Alternatively, they ensure victory through outright
fraud and/or coercion. Other countries in Latin America appear to have political systems in which
parties, structured along competitive divides, relay clear signals to voters of their relative positions in
the political space. Among the latter, Southern Cone countries, particularly Chile, are oftentimes
portrayed as programmatic systems, where voters need know only a party’s name in order to grasp its
relative position on various issues. What we purport to show is that legislators in Latin America,
even those that belong to clientelistic or personalistic parties, share a modicum of beliefs that makes
it possible and extremely useful to talk about ideologies.
We resort to dimensional models to define the content of political ideologies in Latin American
3
legislatures. These models are forceful metaphors; they allow us to represent cross-country variance
in the placement of legislators and parties. They allow insights into the underlying dimensions that
structure political competition, into the policy preferences of individuals, and into the relative
ideological cohesiveness of different legislative factions and parties. We conceive of “legislative
spaces” as decomposable into four levels:
1. Issue space: This is the most superficial level. Furthermore, it is the only directly “observable”
level, for it consists of a legislator’s actual responses to straightforward questions. The issue
space has a potentially infinite number of dimensions. In our tests, however, we only include
twenty-six variables to represent the issue space. Our choice of variables was constrained by
sample quality (please refer to the appendix), but was informed by theoretical considerations. In
consequence, our variables tap into legislators’ dispositions and attitudes towards various policy
and social issues. We included indicators that the copious literature on West European political
systems has identified as correlates of underlying societal cleavages (such as opinions about state
intervention in markets or religiosity). We also included indicators of issues that are hot topics of
contention and debate in contemporary Latin America (corruption, violence, crime, and the role
of the military). Finally, we included legislator’s opinions on the intrinsic value of democracy
and the desirability of elections and of political parties as vehicles of interest aggregation and
representation.
2. Ideological space: Though the issue space contains a large number of dimensions, a rational
choice approach to ideology contends that this need not impose excessive informational costs on
voters. Instead, a much simpler ideological space underlies the issue space, providing summaries,
as it were, of politicians’ stances on different issues. The ideological space is of much lower
dimensionality —oftentimes 2 or 3 dimensions suffice to summarize the issue space— and it
provides the information that a citizen requires in making her prospective voting decisions. This
second level is not directly observable, but its contents can be fathomed through analysis of the
issue space. We achieve this via factor analysis (see appendix for details). We interpret the
resulting factors as the relevant ideological dimensions that underlie legislators issue stances.
3. Political space: Individuals differ in their positions in the ideological space; ideological
dimensions, indeed, are those which explain most variance in individual stances in the issue
space. Yet, though ideological dimensions divide legislators, they need not divide parties.
Religion, for example, might be divisive among legislators, but it might not provide enough
explanatory power to discriminate among parties. In other words, not every ideological
dimension is a political dimension (but every political dimension is an ideological dimension).
Thus, we hypothesize the existence of a political space that is of dimensionality lower than or
equal to that of the ideological space. We infer the features of the political space in each of our
eleven legislatures via regression analysis.
4. Competition space: Yet a fourth level can be distinguished in our typology. Though political
dimensions allow us to discriminate among parties, they need not be the main locus of partisan
strife. In West European party systems, for example, religiosity (proxied by church attendance) is
a good predictor of the partisan identification of a voter. This does not mean that parties compete
along the religious dimension to attract voters. Similarly, we believe that not every political
dimension in Latin American legislatures is “active”. Hence, we suggest that this bottom level
competition space is of dimensionality lower than or equal to that of the ideological space.
4
Unfortunately, this hypothesis is not directly verifiable using data from the Salamanca surveys.
In consequence, we limit our analysis to the ideological and political space that underlies
legislators’ issue positions in Latin America, i.e., levels 2 and 3 above.
To summarize, we posit that the “legislative space” can be successively reduced from the
original issue space, to an ideological, a political, and finally a competitive space with less
dimensions (respectively, ú26>úi$úp$úc). In the remainder of this section, we describe the nature
and content of the ideological and political spaces in eleven Latin American legislatures.
Ideological dimensions. This section describes variance in the shape and content of ideological
spaces in Latin American legislatures. Before we do so, we develop our understanding of which
“ideological labels” might correspond to “statistical factors”. A priori, we anticipate that our 26
variables should cluster in seven ideological dimensions:
1. Economic governance: This dimension contains two questions about preferred ownership patterns
in industry and provision of services and a third question regarding price controls. We posit that
this ideological dimension correlates with opinions on the optimal locus of economic activity.
More than signaling a legislators’ opinion about public vs. private ownership, this dimension
conveys the faith that a legislator places on the self-regulating market either as a means to achieve
economic growth or as a desirable outcome that requires no further justification (variables 49, 50,
64).
2. Social protection: A related aspect of government intervention in economic activity is the
provision of safety nets, state-sponsored institutions aimed at ameliorating the risk that market
participants bear in case of an adverse economic outcome (variables 65, 69, 70, 71, 72). We have
no strong expectations regarding the relationship between economic governance and social
protection. On the one hand, proponents of “market socialism” might find market governance
palatable only when accompanied by state-sponsored protection mechanisms.1 On the other hand,
believers in the market mechanism might prefer little state intervention in economic governance
and in the provision of safety nets. When the latter happens, i.e., when privatization and social
protection variables appear in the same factor, we find it simpler to refer to them as state/market.
We interpret the state/market dimension as the traditional economic distributive divide.
3. Financial openness/closure: We interpret this dimension as one relating to the optimal degree of
national financial openness. Yet, our label is not beyond dispute. Variables 57, 59, and 61 really
ask legislators about their tolerance to foreign ownership of privatized firms. Thus, these variables
conflate two issues: the desirability of foreign direct investment, on the one hand, and the
possibility of foreign control of strategic industries, on the other. An alternative name for this
dimension would thus be “economic nationalism”. On the basis of factor analysis results, we later
discern which of these interpretations is more accurate (variables 54, 57, 59, 61).
4. Law and order: We include in this dimension six variables, all of which tap into legislators’ views
on threats, internal or external, to the state or to society. Yet, our expectations about how these
variables should relate to one another are not totally clear. For one, two of these variables are
feeling thermometers (v34 and v35), a third one is ordered categorical (v80), and two more are
1
With a stretch, we could say that their preferences over economic governance and safety nets are non-separable.
5
really “salience” measures (v87 and v168). Moreover, though we can conceive of a legislator
preferring to endow the state with absolute authority to combat terrorism, labor unrest,
delinquency, and corruption, it is more likely that most legislators will look at these sources of
threat differentially —and would therefore favor strong state responses to terrorist threats but not
to corruption. In any case, how opinions are distributed is just the empirical issue that we set to
investigate. What this dimension ought to reveal is a “loose” ideological tolerance for threats to
the status quo (variables 34, 35, 80, 87, 149, 168).
5. Tradition/secular: This dimension reflects differences of opinion on the importance of upholding
traditional values versus adopting more secular or liberal views on morality. A more daring
interpretation would see this factor as a reflection of nineteenth century struggles on the proper
place of the Catholic church in the body politic, perhaps even as the ideological remnant of a
structural Church-State cleavage (Lipset & Rokkan 1967) (variables 210, 235, 236, 240).
6. Postmodernism: We interpret this dimension as akin to Inglehart’s “postmodernism”. Notice,
however, that our previous tradition/secular dimension might already capture some of the traits
that belong in this “value-based cleavage” (Knutsen 1989). In addition, these variables do not
code legislators’ stances on human rights or environmental issues; rather, they ask legislators how
salient these issues are. By including variables 90 and 92 in the original data matrix, we implicitly
assume that those legislators that consider these issues as salient tend to have similar views on
them. This is, admittedly, an heroic assumption. We are willing to make it only in a first
approximation to the study of legislative ideologies. Moreover, wording on variable 90 confounds
two separate issues, namely, human rights and minority rights (variables 90, 92).
7. Authoritarianism: Our last dimension captures legislators’ commitment to democracy as the
proper way to solve political disputes, and thus taps into preferences about regime form and about
the subjective limits to political dissent. Note however that v26 (“parties are needed for
democracy”) might be interpreted not as tapping into authoritarian propensities at all, but into
preferences for a populist system in which parties do not mediate between citizens and
government. In this populist interpretation, legislators with high scores on v26 might not be
opposed to democracy, whatever they mean by it, but to parties as the main vehicles of political
representation (variables 11, 15, 26).
How, then, does the content of ideological dimensions compare in different Latin American
legislatures? Our answer to this question is twofold. First, we compare the features of the
ideological space when all legislators are included, assessing both the substantive contents of
ideology and their interpretability (i.e., how “recognizable” each dimension is). Second, we assess
whether this content changes when we drop small party legislators. By doing so, we try to
understand whether newcomers or fringe parties change the legislative ideological landscape.
Tables 2 and 3 summarize the results of factor analysis. The results reported in table 2
correspond to an analysis of all respondents, regardless of party membership. The original samples
on which we base our analysis over-represent certain parties. In an effort to minimize sample bias,
we weighted each legislator by the share of its party in the legislature (details in the appendix). Table
3, in contrast, presents results obtained from excluding small party legislators from the sample (and
6
keeps weights on legislators from larger parties).2 Hence, table 2 offers insights into the ideological
dimensions that underlie legislators’ opinions, whereas table 3 restricts this analysis to legislators that
belong to larger parties. We start by looking at table 2.
Table 2 contains information on the three (or four) most important factors in each legislature.
The λ statistic is the eigenvalue of the reduced matrix, and it is presented here with its attendant
“proportional explanatory power”. Let us be clear about what this statistic reveals. In Argentina, for
example, factor 1 alone describes 34% of common variance in the original issue space, whereas
factors 2 and 3 account for a further 19% and 13% respectively.3 Factor I is by far the most divisive
ideological dimension in the Argentinean legislature. Notice that in some other countries each factor
accounts for a similar amount of common variance (18 to 20% for each factor in Ecuador). In these
cases, we cannot talk about a preeminent ideological dimension. In alternative statistical analyses,
those countries where one ideological dimension appears as preeminent always returned the same
variables in the same factor, and all factors in the same order, regardless of method of factor
extraction. In other words, ideological dimensions in these countries are insensitive to factorization
methods.4 Conversely, countries where factors have similar explanatory importance are sensitive to
factorization methods, though alternative results do not vary widely. As a matter of fact, alternative
factorization methods mostly determine the order in which factors appear, not their substantive
content.
We followed a simple rule in deciding which variables make up each factor. In all cases, only
variables with factor loadings larger than 0.5 appear under each heading. (In parenthesis, we also
added those variables with loadings larger than 0.46).5 In 34 out of 38 of our country/factor dyads,
we are able to provide unequivocal interpretations about the underlying ideological dimensions.
These tend to correspond quite closely to our a priori expectations, except in two cases. First, law
and order variables do not appear together; they never define a single factor. Single variables within
this category make their appearance now and then, scattered alongside more interpretable categories.
We conclude that despite our a priori expectations, these six variables are not the issue correlates of
an underlying law and order ideological dimension. Second, opinions on the pertinence of allowing
monitoring and help from the World Bank and the IMF (v54) do not load highly in the factor where
questions regarding foreign ownership of domestic industry appear. This lends credence to our
alternative interpretation above, namely, that this latent dimension has more to do with economic
nationalism than with stances on financial integration or isolation. (Hence, hereinafter we will refer
to this dimension as economic nationalism).6
2
This statement is a bit misleading. We consider a party “small” when the sample includes less than seven respondents.
In general, parties with less than seven respondents coincide with fringe parties in the legislature.
3
This of course begs the question of what proportion of total variance in the original issue space is “common”. In tables 2
and 3, the number below each country’s name conveys this information. In Argentina, again, the estimated average
common variance per variable is 0.48. Average common variance goes from a low of 0.4 in Venezuela to 0.5 in Chile.
The appendix offers a detailed justification of our choice of methods.
4
We used iterated principal factors as an alternative extraction method. We also varied the principal factor method, using
the square of the maximum correlation of a variable with any other, rather than the square of the multiple correlation with
all other variables, as the estimate of communality.
5
Complete results can be obtained from the authors.
6
Note, moreover, that our use of the word “ideology” reflects how divisive a dimension is. It does not mirror the
coherence of each dimension. If legislators in country X are divided by a dimension in which notions about abortion
correlate with preferences on financial openness, well, that’s just the way things are. Our use of the word ideology does
not gauge the ability or inability of legislators to recognize their own positions in the issue space. Our building
7
Five factors —f1 and f3 in Bolivia, f3 in Colombia, f3 in Ecuador, and f3 in Uruguay— include
variables from too many different groups to make interpretation easy. These are not cases where
different ideological dimensions overlap, as seems to occur in Chile’s first factor. Rather, they
comprise what seems a haphazard collection of issues. One could dismiss these factors as bringing in
“noise”. But the fact that we cannot unequivocally assign ideological labels to these four factors —
and the fact that we can do so in the other 34 cases— means that disregarding them as noise would be
just ad hoc and plain wrong. The alternative position is to say that ideologies in these countries,
particularly in Bolivia, lack the internal coherence that we find natural to ascribe to dimensions such
as, say, economic left and right, or pro-clerical and anti-clerical, in other legislatures.
We have more to say about the content of ideological dimensions in Latin America. First,
however, we focus our attention on the simplicity or “compactness” of the ideological space. One
can say that a legislature where three different factors each account for a similar amount of variance
is much more complex, or less compact, than a legislature where the first factor accounts for a
disproportionate amount of variance. Consider, for example, Chile and Ecuador. In the former, the
first factor accounts for 37% of common variance. The second factor, albeit important, accounts for
much less variance (22%), and the third factor for an even more distant 15%. Issue positions in Chile
seem to be largely determined by one underlying factor. In Ecuador, conversely, each of four factors
explains about 20% of common variance. Were we to use a legislator’s score on factor 1 to predict
her stance on a particular issue, we would be more likely to get a wrong forecast in Ecuador than in
Chile. In other words, legislative issue positions in Chile are much more predictable —much
simpler— than in Ecuador.
Hence, we can place Latin American legislatures in one of three boxes, depending on whether
they resemble Chile or Ecuador, or whether they occupy an intermediate position. Several ways to
categorize countries are possible, from indices of concentration or effective number of ideological
dimensions to descriptive statistics derived from the explanatory power of each factor. Our rule is
much simpler: A legislature is ideologically simple if the first factor accounts for more than 30% of
common variance, intermediate if the first two factors account for 50% of common variance, and
complex otherwise. Notice that “complexity” of the legislature and number or relevant ideological
dimensions are not synonymous. Table 4 shows the results of this typology:
Table 4. Ideological complexity of Latin American legislatures.
Simple
Complex
Argentina
Bolivia
Brazil
Chile
Mexico
Colombia
Peru
Uruguay
Costa Rica
Venezuela
Ecuador
The simplest legislatures are those of Argentina, Chile, and Peru; the most complex ones, those
of Brazil, Colombia, Costa Rica, and Ecuador. It is amazing that the simpler legislatures share so
many common traits at the ideological level. Indeed, Argentina and Peru —which could not be more
different in the nature of their party systems, electoral rules and, of course, democratic status— share
assumption is that legislators have clear preferences on every issue. Thus, the fact that law and order does not generally
appear as an ideological dimension means that all legislators, regardless of partisanship, share similar beliefs and
preferences, not that they lack clear positions, let alone that these positions are incoherent.
8
an extremely similar legislative preference structure. In all three countries we find that the three most
divisive dimensions are state/market, tradition/secular, and economic nationalism. Though Chile
shares this basic ideological structure, its first factor tells a more colorful story about the nature of
legislators’ preferences. In Chile, the first factor pits those that prefer free markets, smaller
bureaucracies, and have fewer qualms about recognizing their authoritarian dispositions against those
that would have more state intervention in the economy and feel more committed to democracy come
what may. In addition, the former tend to give less emphasis to the importance of upholding human
and minority rights and tend to be less emphatic about the importance of protecting the environment.
Later on, when we look at results from discriminant analysis, we will look at the spatial position of
parties along this factor.
The more complex legislatures —Brazil, Colombia, Costa Rica, and Ecuador— can be further
divided in two groups. On the one hand, Brazil and Costa Rica are examples of legislatures (almost)
equally divided by interpretable factors. Brazil shares with Argentina, Chile, and Peru the
prevalence of a state/market divide as its first factor, and the presence of two other important divides,
namely, tradition/secular and economic nationalism. In Costa Rica we can observe that the
economic ideological dimension (state/market) is decomposed in two factors: economic governance
and social protection. Costa Rican legislators disagree both because of their preferences for markets
over state as the locus of economic activity and because of their ideas about the role of the state in
providing insurance against negative market outcomes. Curiously, Costa Rica is the only country
where economic governance and social protection appear as separate and controversial. In
Colombia, Ecuador, Mexico, and Uruguay, social protection is controversial, but economic
governance is not.
On the other hand, Colombia and Ecuador both include a third factor that lacks clear
interpretation but which accounts for ca. 17% of common variance. Be that as it may, both countries
show unmistakable traces of a religious divide (f2 in Colombia, f4 in Ecuador). In Colombia,
moreover, differences of opinion over social protection are important; it is difficult to say whether
this is also true for Ecuador, where factors 2 and 3 both pick variables associated with the social
protection dimension. This occurrence is anomalous in the context of our eleven countries; we
cannot offer a convincing explanation of why this might be so.
As for the intermediate categories, Mexico and Uruguay show two interpretable factors. In both
cases, the first dimension divides proponents of extensive safety nets versus advocates of laissezfaire. The second dimension in Mexico is definitely tradition/secular, whereas in Uruguay this
dimension appears only as factor 3, and then only accompanied by controversial views about
delinquency as a threat to democracy. The Venezuelan ideological space is muddled by the
appearance of religious and economic variables in the first two factors. Though we still labeled
factors 1 and 2, our confidence about the existence of clear ideological dimensions underlying issue
positions in Venezuela is much diminished. The same can be said about Bolivia, where only factor 2
lends itself to clear interpretation as the tradition/secular dimension.
Latin American political systems have undergone radical changes during the 1990s. In the
Southern Cone, democratic consolidation has been accompanied by the appearance of new political
actors alongside older, more entrenched parties. In Mexico, the slow erosion of a hegemonic party
has been accompanied by the progress of political options on the left and right. By 1997, new parties
and messianic military populists laid siege to Venezuela’s stable partidocracia. Similarly, Peru’s
9
political system suffered from a newfound dislike among voters for traditional parties —or, as
Kenney shows, for parties tout court (Kenney 1998). Thus, our preliminary conclusions about the
size and shape of the ideological space might be influenced by our decision to include legislators
from all political corners in our sample. It is possible that by bringing into the legislature new views
on old issues, latecomers and fringe parties are distorting the traditional ideological space. If this
were the case, some of our less interpretable results might be due to the flux of ideological change in
the legislature, where the stability of yesteryear broke down and a new equilibrium has not yet
appeared. It is also possible, however, that newcomers are reinforcing the opinions held by
traditional party legislators. Indeed, it is possible that non-traditional party legislators are bringing
more ideological coherence to an otherwise disjointed legislature. We look into these possibilities by
comparing briefly our results with those of table 3. Strictly speaking, “small” parties are those for
which we have less than seven respondents, so the real issue here is whether the inclusion of these
legislators is driving our conclusions.
Our original samples for Venezuela and Uruguay do not include “small” parties, i.e., every
legislator belongs to a party with at least six other respondents. Thus, these two countries are
excluded from this exercise. In Mexico, excluding small party legislators drops one observation only,
so we do not expect drastic changes in our conclusions. Such is our expectation for Chile and Costa
Rica, where we lose only four observations. In the rest of the countries, there are drastic reductions
in sample sizes.7 Hence, due to differences in sample sizes, the results of tables 2 and 3 are not
directly comparable. This disclaimer notwithstanding, we contend that a comparison between tables
2 and 3 offers valuable insights into the ideological composition of Latin American legislatures.
Latin American legislatures can be categorized in three groups depending on the comparison
between tables 2 and 3. The first group gathers countries where the exclusion of small party
legislators brings no fundamental changes. This category includes the trivial cases of Chile, Costa
Rica, and Mexico. More interestingly, changes in the Peruvian ideological space are also minimal.
Despite a high rate of attrition in our observations (from N=87 to N=71) the three factors that we
observe in table 2 remain stable. Their contents do not change, nor do the order of factors. The
second group comprises Argentina and Bolivia, where dropping small legislators brings about
changes in the content of at least one factor. In Bolivia, table 3 presents a more interpretable first
factor, one that conjoins at least two dimensions, namely, tradition/secular and economic
governance. However, variables 61 and 80 still appear with high loadings in factor one, and factors 2
and 3 remain hopelessly uninterpretable. It is difficult to find rhyme or reason in the Bolivian
legislature. In Argentina, factors 1 and 2 remain virtually unchanged, suggesting a very stable
ideological space, but the contents of the third dimension are completely different when small parties
are dropped from the analysis. Finally, a third category includes Brazil, Colombia, and Ecuador.
Here, factor substantive contents are virtually unchanged, but the order in which factors appear,
which is to say their relative explanatory power, shifts a bit. We noticed before that these are
ideologically complex legislatures, in the sense that each factor accounts for a similar amount of
common variance. Hence, even though there are changes in the order in which factors appear, this
shift need not signal extreme sensitivity to the exclusion of small parties. As with table 2, the relative
explanatory power of each factor in Brazil, Colombia, and Ecuador remains about equal.
7
Attrition rates are as follows: Argentina 22%, Bolivia 24%, Brazil 32%, Chile 5%, Colombia 13%, Costa Rica 8%,
Ecuador 23%, Mexico 2%, Peru 18%, Uruguay 0%, Venezuela 0%.
10
We have so far described the ideological space of Latin American legislatures with regard to the
criterion of “complexity”. In statistical terms, complexity refers to how much common variance is
explained by the array of latent factors (with λ≥1.5) that we obtain from factor analysis. We have
also cursorily commented on the contents of some of these factors. We now consider in more detail
cross-country variation in the appearance of the four most conspicuous ideological dimensions:
economic governance, social protection, tradition/secular, and authoritarianism.
The most common factor is the economic one. As we noted before, the economic factor does
not share the same contents across nations. Most importantly, there are differences in the variables
that form the economic factor. Any of four mutually exclusive outcomes can obtain: (i) both
economic governance and social protection reinforce each other (our state/market ideology); (ii)
economic governance and social protection are equally divisive but appear in different factors; (iii)
only one of these ideologies appears as divisive; or (iv) none is divisive. In practice, (iv) is never the
case in our sample. In other words, economic issues have pride of place in accounting for variance in
legislators’ placements in the issue space. It is not surprising that most policy disagreements among
legislators are of an economic nature. That is, after all, where the money is, and public choices are
more often than not about the distribution of scarce resources. What is surprising is that economic
variables not always appear in the same factors. We believe that the varying contents of the
economic ideological dimension across nations are not haphazard. One conjecture is that these
contents reflect how different Latin American countries grappled with structural reform in the 1980s
and 1990s and, more importantly, they reflect the historical existence of strong parties of the left.
Probing into this interpretation is beyond the scope of this paper.
It is indeed the case that all of our ideologically simple countries —Argentina, Chile, and
Peru— share a very divisive state/market dimension. In these countries, the “economic right” agrees
to the following propositions: industry and services should be privatized, price controls are harmful,
and social protection and basic subsidies should not be provided by the state. Though Brazil appears
in our category as an ideologically complex country, a state/market dimension is unmistakably
present as well. Our results confirm Huber and Inglehart’s (1995) expert survey, which documented
that the “economic or class conflict” is the main political cleavage in Argentina, Brazil, and Chile.8
Huber and Inglehart added Mexico to this set, a conclusion partially supported by our analysis.
However, in 1997 issues of economic governance did not divide the legislatures of Colombia,
Mexico, Uruguay, and, to a certain extent, Venezuela. In these four countries, factor one picks up
distributive conflict, but legislators differ only in their preferences for social protection. In other
words, either there had been disagreement about economic governance (privatization and markets)
but the question had been permanently settled or questions about the relative merits of markets and
government had not surfaced yet.9 Finally, Costa Rica alone is an example of (ii) above. Factor 1
clearly shows the prevalence of the economic governance (and the tradition/secular) dimension,
whereas social protection appears only in factor 2, which is orthogonal to the first factor. Table 5
summarizes the discussion.
8
Norden would agree with this conclusion: “Probably the most important of these divisions in Latin America is that
between social classes, with many political parties defined primarily by their purported representation of working-class,
middle-class or upper-class interests” (Norden 1998: 437-438).
9
Frequency distributions for variables 49 and 50 in Colombia, Mexico, and Uruguay are strongly unimodal, with most
legislators choosing the middle point. Venezuela’s distributions are slightly lopsided towards high scores.
11
Table 5. Importance of economic divides in Latin American legislatures.
Strong social protection
Strong, non-reinforcing, social
Strong, reinforcing
dimension
protection and economic
state/market dimension
governance dimensions
(social protection plus
economic governance)
Costa Rica
Colombia
Argentina
Ecuador (?)
Chile
Mexico
Peru
Uruguay
Venezuela
There is no doubt, then, that an economic ideological dimension is pervasive throughout Latin
America. Given that Latin American political parties have seldom resorted to campaigning on
religious or ethical grounds, it would be more surprising to find traces of a religious cleavage in these
legislatures. To be true, issues relating to Church-State relations, alongside a deep center-periphery
cleavage, tended to dominate nineteenth-century politics (Dix 1989), and even today there is no
consensus on the role that the Catholic Church (or other religious organizations for that matter)
should play in public affairs. It would be extremely informative to compare the countries in our
sample with those countries where Evangelist sects have successfully challenged Catholic
dominance. Be that as it may, we find throughout our sample that a behavioral divide separates
politicians that regularly attend religious services from their less-devoted brethren. In most cases,
this behavioral divide is reinforced by an attitudinal split, with the religiously inclined showing
conservative stances on abortion and divorce.
In one way or another, variables associated with a religious latent dimension appear in all our
cases. In Bolivia, Ecuador, Peru, Uruguay, and Venezuela, variables that indicate attitudes towards
abortion and divorce do not factor highly on any dimension, even when variables 210 (“church
attendance”) and 240 (“religiosity”) do. In other words, legislators in these countries share a more
consensual opinion about both abortion and divorce. This consensus is for a very liberal position on
divorce; on abortion, most legislators place themselves in the intermediate position, which means that
they are in favor of allowing it only in specific, legally sanctioned cases (the questionnaire is mute
about what these cases might be).
More interestingly, legislatures vary on whether the religious dimension appears independently
or overlapping a different ideological dimension. The distribution of preferences in a body politic
holds important implications for the character of political strife, consensus-building, fragmentation
and polarization of political party systems. Our analysis suggests different degrees of ideological
fragmentation across Latin American legislatures. To see this, consider first the cases of Argentina,
Bolivia, Brazil, Chile, Ecuador, Mexico and Peru, where all religious variables appear in one factor,
which is separate from all other dimensions. In these countries, the religious dimension cuts across
the economic dimension, making for a more ideologically fragmented legislature. What this means is
that there is little correlation between a legislator’s position on, say, economic governance and his
religious stance.
There is, finally, an ideological dimension that we expected to be paramount in explaining
variance in issue positions. We refer to the authoritarian divide. Though most Latin American
societies have achieved progress in the consolidation of democracy, the relatively recent experience
12
of harsh right wing dictatorships might have left indelible imprints in the minds of citizens and
politicians. Be that as it may, we find that a systematic authoritarian divide is appreciable only in
Chile, where it overlaps with the state/market and postmodern dimensions. In the next section, we
map party positions along Chile’s factor 1, and we show that this factor indeed divides the
authoritarian, market-oriented right, from the democratic, interventionist left.
Political dimensions. Throughout this paper, we have referred to a basic space that underlies
legislators’ opinions, attitudes, beliefs, and values. We have called it the legislative “ideological
space” and we have represented it as a low-dimensional Cartesian space in which each axis stands for
one “ideological divide”. We concluded that the economic, religious, and economic nationalism
dimensions —and, to a lesser degree, the regime divide— are generally powerful predictors of
legislators’ stances on twenty-six issues. If each of these four ideological dimensions or divides were
to perfectly separate legislators in equal-sized groups, and if every dimension were to cut across each
other, we would encounter a configuration in which 24 ideological “blocs” would enjoy
representation in the legislature. This number is obviously greater than the largest number of parties
in any Latin American legislature. This is so because (i) some divides are overlapping rather than
cross-cutting, as we argued in the previous section, and (ii) parties do not really compete over the
whole legislative ideological space.
For various reasons, the ideological space is not commensurate with the political space. An
ideological dimension might be extremely divisive, allowing us to account for individual legislators’
stances on a broad array of related issues. This need not mean that this same ideological dimension
will also divide parties, i.e., it need not be a political divide. Consider “religion”, for example.
Religious convictions and beliefs might very well separate individuals in a legislature. This need not
mean that believers will self-select in party A, while atheists will join the ranks of party B. For all we
know, both parties might have their share of believers and atheists. Which ideological dimensions
happen to be political dimensions is an empirical matter. We could learn about the political space
through a number of statistical techniques. Essentially, we try to see whether partisanship is a good
predictor of a legislator’s position on ideological dimension x. Ideally, discriminant analysis is best
suited to reveal which factors (ideological dimensions) discriminate among parties. For the time
being, however, we stick to regression analysis to discern which ideological divides map into
political divides. In this second part of the paper, we consider only those parties for which the survey
reports more than seven respondents. With this proviso in mind, we turn to table 6, which presents
our results.
We estimated three models per country, one model for each factor (we omit results for factor 4
in Brazil and Ecuador, which were statistically insignificant). In each model, the dependent variable
is continuous, and it codes legislators’ factor scores. We regress these scores on a set of dummy
variables, one for each “big” party (the intercept is not estimated). Needless to say, these models are
not full specifications of the variables that make for legislators’ placements. Rather, they are
measures of the strength of association between parties and factors. In practice, these models amount
to using parties as predictors of a legislator’s placement on different ideological dimensions; they are
equivalent to a difference of means test where the null hypothesis is that the party’s mean is zero. As
an alternative, we also carried out difference of means tests (for every party on every factor in every
country) in an attempt to find out whether the party mean is statistically different from the grand
mean —the mean placement of all legislators regardless of party. Though this is a more intuitive test,
the grand means on all factors are close enough to zero to make this test redundant. Where this is not
13
so (most notably in Colombia), regression analysis results and difference of means tests coincide with
regard to the statistical significance of party mean placements. Hence, we only report results from
the regression analysis.
We conclude that ideological dimension x is also a political dimension if partisanship appears as
a statistically significant predictor of a legislator’s placement in factor x. It is possible that only the
coefficients for one or two parties are significant; we would then have to make a judgment call on
whether to call that a political dimension or not. To avoid this call, we first look at the F-statistic in
each model. Where the F-statistic is above 0.1, we fail to reject the null hypothesis that the
coefficients for all parties are jointly zero. An insignificant F-statistic precludes us from asserting
that party means are different from zero; in other words, that ideological dimension is not a political
dimension. The F-test eliminates eleven ideological dimensions; most of these dimensions are the
ones that correspond to factor 3 —the exceptions are Ecuador, Mexico, and Uruguay. Notice also
that no political dimensions exist, by our standards, in Peru. A more stringent test is to consider the
adjusted-R2 statistic, which describes the goodness of fit of the model. Even with a significant Fstatistic, the explanatory power of a political dimension might be so weak that we cannot predict the
position of a legislator from her partisanship. In Chile, the first two dimensions show outstanding
measures of goodness of fit (0.51 and 0.50), whereas factor 1 in Bolivia and Costa Rica and factor 2
in Colombia show R2 statistics under 0.1. Difference of means tests for party placements along these
factors corroborate that mean party placements are not significantly different from the grand mean.
Which ideological dimensions are also political? How are parties distributed along these?
Table 7 summarizes this information. Rows contain information on politically active dimensions.
The first entry registers the “grand mean”, or mean legislator placement along that factor —abusing
the spatial metaphor, we consider this the “centroid” or “origin” of that political dimension. The rest
of the entries show mean party placements along that factor (with standard deviations in parenthesis).
These scores can be loosely interpreted as showing the relative left-right position of parties along
each political dimension, but they should be read in conjunction with results in table 6. For example,
Brazilian parties could be ranked from left to right according to their mean party position. This
yields a commonsensical order, from PT on the “extreme” left to PFL on the “extreme” right, and
PMDB and PSDB occupying middle positions close to the grand mean. If we look at the
corresponding entry in table 6, however, we find that the only significant coefficient is that for the
PT. In Brazil, we can confidently assert that PT legislators are the ones that turn the state/market
ideological dimension into a political one.
Again, these results should be interpreted with caution; we certainly do not pretend that these
scores signal some sort of collective optimum for each party. We do note, however, that in general
the induced mean party positions are consistent with our preconceptions of where different parties
“stand”. For us, the one glaring anomaly is the social protection political dimension in Mexico,
where PRI legislators are, on average, placing themselves more to the left than their PRD colleagues.
Be that as it may, we discuss the variegated meanings of left and right in Latin America in the
last section of this paper. We close this section by submitting two alternative typologies of Latin
American legislatures according to the number of dimensions in the political space and to the
substantive content of these dimensions. First, we illustrate the number of political dimensions in
Latin American legislatures in table 8.
14
Table 8. Political dimensions in Latin American legislatures.
One
Two
Three
Chile
Mexico
Argentina
Venezuela
Uruguay
Bolivia
Brazil
Colombia
Costa Rica
Ecuador
A more interesting classification of the eleven Latin American legislatures results from
considering whether religion and economics are political dimensions. The results are offered in table
9, a self-explanatory four-fold table. Here, each of the four entries signal whether both dimensions
are politically consensual —in the sense that they do not determine the self-selection of politicians
into different parties—, both are politically active, or one is muted and the other active. Why is it
that economic issues are muted in some legislatures? Where (and why) is religion politically
divisive? We leave these questions for future research into the ideological make-up of Latin
American politics.
Table 9. Classification of legislatures according to the contents of political dimensions.
Yes
Religious dimension
politically active?
No
IV.
Economic dimension politically active?
Yes
No
Chile, Mexico,
Bolivia, Colombia
Uruguay,
Venezuela
Argentina, Brazil,
Peru
Costa Rica,
Ecuador
Left-right semantics, parties, and legislative ideological and political spaces
Interpreting the meaningfulness of left-right semantics. The remainder of this paper examines the
cognitive and substantive significance of left-right semantics among Latin American legislators.
While widely used, labels of ideological dimensions vary along with the political context of a given
country. In the United States, the terms “liberal” and “conservative” dominate ideological discourse,
though the two party system itself also provides clear endpoints to the ideological dimension
(Inglehart & Klingemann 1976; Conover & Feldman 1981). In Europe, on the other hand, voters’
self-placements on “left”-“right” ideological scales are key determinants of party support and vote
choice (Inglehart & Klingemann 1976; Fleury & Michael Lewis-Beck 1993; Evans, Heath & Lalljee
1996; Knutsen 1997). The positions with which these terms are linked vary across space and time,
and are not limited to a single ideological dimension (Kitschelt & Hellemans 1990; Nathan & Shi
1996; Evans & Whitefield 1998).
Inglehart and Klingemann (1976) propose that ideological dimensions are comprised of two
primary components: partisanship and value or issue orientations. The partisan component is a
15
cognitive component in that it merely distinguishes among parties regardless of issue linkages. The
ideological component is a substantive component because it carries actual issue content to political
actors. In different European countries, these components are of varying significance. Inglehart and
Klingemann typically find that the partisan component of left-right self-placement is stronger than its
linkage to values or issues. This finding is significant because it comments on the types of cues
voters are given with which to make rational voting calculations. If the partisan component
dominates among the country’s elite as well as individual voters then the utility of a left-right
framework for guiding vote choice is diminished. At the extreme, the use of left and right would
only signal a given party to the voters, rather than a cluster of issue and value positions.
Following Inglehart and Klingemann’s seminal article on left-right semantics (1976), we
examine, first, whether left and right play a role in party identification or labeling. Second, we
explore the underlying substantive meanings of left and right across Latin American countries. For
left-right discourse to be a meaningful tool, we hope to find both components present in the usage of
left and right in Latin American politics. In the last section, then, we jointly compare each
component’s relationship to left-right semantics.
By analyzing party placement by legislators, this study differs from other studies of left-right
semantics (including those listed above) that rely on mass survey data or expert surveys. The study
of the usage of ideological labels by political elites is of interest for at least two reasons. First,
studies have shown that individuals with more education and higher levels of political involvement
are more likely to use such labels in a substantively significant manner (Klingemann 1979; Kitschelt
& Hellemans 1990; Evans, Heath & Lalljee 1996). Second, left-right labels are generally transmitted
to the masses through their use by elites (Key 1966). If political elites use ideological labels without
making consistent linkages between these, their parties, and issue positions then the masses will have
less meaningful cues to use in the electoral choice process.
Left–right party placements by country. Before proceeding to our more specific analyses, we first
created a general picture of left-right party placement across Latin America countries. Figure 1
contains graphs of the response frequencies for each country. The graphs show the general
tendencies within countries. The data are weighted to reflect the actual distribution of legislators in
that country’s lower house at the time of the survey. The left-right integer scale runs from one to ten,
so the exact middle of the scale, 5.5, is not an option. Most respondents likely interpreted 5 as
representing the middle of the scale. Some caution must be used when making comparisons across
the graphs, given that left-right semantics may have different meanings in each country.
As the data show, the modal response for all countries except Bolivia and Chile is 5.
Interestingly, in the case of Bolivia, the modal response is 8, with a large number of the other
responses also falling on the right side of the scale. The mean party-placement for Bolivia is 6.50,
the furthest to the right among all the countries. Colombia and Peru also show a substantial number
of responses on the right. Bolivia and Colombia come closest to displaying clear bimodal
distributions. In contrast to these cases, several countries show a stronger tendency toward the left of
the scale. For example, Uruguay has very few legislators who place their party on the right side of
the scale, and none that choose locations in the extreme positions of 9 or 10. With a mean partyplacement of 4.38, Uruguay ranks the most leftist of all the countries. Venezuela shows a similar, but
less extreme pattern, and Brazil also shows a significant tendency toward the left, while also having a
number of legislators at the other extreme. Finally, Argentina, Costa Rica, Ecuador, and Mexico all
16
have more normal distributions, showing a more balanced response pattern with an affinity for the
center.
INSERT FIGURE 1
The partisan component of left-right semantics. Given the tendency toward the mean shown in
the above graphs, one might expect that left-right semantics do not play very meaningful roles.
However, we expect more detailed analysis to show the opposite. Left-right semantics are used
frequently in Latin America, and likely carry both cognitive and substantive meanings. Following
previous work on left-right semantics, however, we anticipate that the partisan component will
outweigh the more substantive, ideological component. Therefore, we first turn our attention to the
relevance of left-right semantics as party labels.
Inglehart and Klingemann (1967) propose that left and right are more clearly associated in
European’s minds with certain parties than with distinct values or issues. Their argument is that, to a
great extent, left-right semantics are used merely as alternative party labels. The significance of
Inglehart and Klingemann’s “partisan component” is made more clear by a quote they take from
Butler and Stokes: “Voters come to think of themselves as Right or Left very much as a
Conservative in Birmingham or Scotland used to think of himself as a “Unionist”, because that is
what his party is called locally (Butler and Stokes 1969, 260).” In other words, left-right placements
may not necessarily indicate preferences over a certain set of issues or values, but may only indicate
party affiliation. The authors refer to this as a “political culture” model of ideological labels. Recent
studies support Inglehart and Klingemann’s argument. For example, Knutsen (1997) finds that in
both 1981 and 1990 the partisan component of left-right semantics remained dominant in Europe,
though not quite as strong as identified by Inglehart and Klingemann.
We discern the significance of the party label component in two ways. First, we examine the
mean left-right placements of Latin American legislators by party. We want to see, first, if the
ordering provided by left-right semantics corresponds to scholars’ typical expectations about the
parties’ relationships to one another along a single dimension. Second, we examine how closely
party members cluster along the left-right scale. We propose that the tighter the clustering, the more
meaningful the cognitive aspect of left-right semantics to those party members. A glimpse into the
answer to this question with respect to individual parties and party families can be taken from the
standard deviations calculated for the means. We then probe this aspect further by examining, at the
country level, the correlation between an individual’s party’s “real” placement and the individual’s
own placement of his/her party. In other words, we move up a level of analysis to discern the overall
connection between left-right semantics and party labels for each country’s legislature.
Table 10 presents the mean left-right placement of Latin American legislators by party.
Because we are now examining tendencies at the party level, the data are not weighted. Parties from
which the survey contains two or less respondents are excluded from this analysis. The mean
responses would not be as reliable, and these are generally parties on the political periphery. Most
important to note is that the ordering of the mean placements corresponds nearly exactly with
common understandings of the left-right positioning of these parties. For example, in El Salvador,
the party associated with the popular movement of the 1980s is positioned on the left, the Christian
Democrats place themselves in the center, and the conservative ARENA is on the right. In Mexico,
17
the reformist PRD is on the left, the dominant, centrist ruling party is in the center, and the
economically liberal PAN is on the right. In addition, party families, namely communist and socialist
parties, are placed consistently in the same general location with respect to other parties in each
system.
INSERT TABLE 10
There are few exceptions to the correspondence between common understandings of the leftright placement of these parties and the data. One case that does not conform exactly to expectations
is that of the PFL in Brazil. Scholars of Brazil generally think of the PSB and the PFL as marking the
two poles of a left-right continuum. However, in our survey, the less programmatic PPB occupies the
space furthest to the right. Another difference between our expectations and the data is the case of
Venezuela where Causa R is slightly further toward the center than Acción Democrática. However,
given that Causa R has attempted to portray itself as more centrist since the late 1980s, this finding is
not all the remarkable (López-Maya 1997). Finally, in Chile, the RN and UDI parties are in reversed
order from that identified by political experts in Huber and Inglehart (1995). However, the distance
between them is minimal.
When we turn our attention to the standard deviations presented in Table 10, we see that an
interesting trend among the data is that the partisan component of left-right semantics is most
meaningful among leftist parties. These parties are in greater agreement, on average, over their
party’s placement on a left-right scale than their centrist or rightist counterparts. The standard
deviations of the parties’ mean placements tend to increase moving from left to right on the scale.
This is especially clear in the cases of Argentina, El Salvador, Mexico, Peru, and Venezuela. The
number of respondents per party is small, and therefore we should not be too confident that the
standard deviations within our sample match reality. If true, however, this tendency is interesting for
a couple of reasons. First, the result runs counter to the data analyzed by Inglehart and Klingemann
(1976), which show larger standard deviations among leftist parties in the self-placements of
European citizens. Second, the era of market liberalization in Latin America has been quite harmful
to leftist parties whose extreme protectionist platforms are increasingly illegitimate. We would
therefore expect less cohesiveness among leftist parties as they struggle to redefine themselves.
So far we have seen that the ordering of the mean party placements appears to correspond
very well with common understandings of party positions. In order to compare whole legislatures,
we calculate correlations between party identification and left-right placement for each of the
countries in our analysis. We follow Inglehart and Klingemann (1976) in using the mean scores
presented above as indicators of the parties’ positions on a left-right scale. We then examine the
relationship between an individual’s party’s “real” placement and the individual’s own placement of
his/her party.
INSERT TABLE 11
Table 11 shows the results of this bivariate analysis. The correlations range from a high of
0.833 to a low of 0.383. Clearly the most surprising result is that Brazil ranks the highest in the
relationship between party and left-right party placement. With the exception of the PT, Brazil’s
parties tend to be non-programmatic, with politicians trading party labels whenever it suits them
(Ames 1994). It should be noted, however, that the preliminary analysis in this section focuses on
18
left-right labels as party labels. The high correlation we see for Brazil does not imply anything about
the substantive content of these labels. Along with Brazil, Uruguay, Bolivia, Chile, Ecuador, and
Mexico also show a strong attachment between left-right semantics and party labels. On the side of
the ladder, left-right semantics are only weakly related to party placement in Peru, Costa Rica, and
Colombia. Interestingly, none of our previous typologies of legislatures (all centered on ideological
divisions) explain this result.
What factors, then, might explain differences in the “meaningfulness” of left-right labels
among countries? Inglehart and Klingemann (1976) suggest at least two potential explanations.
First, they argue that the number of parties matters in determining the salience of left-right semantics.
Left-right semantics are used to organize, or simplify, the ideological space. In countries with only
two political alternatives, this organizational tool is less necessary than in multi-party systems. In
two-party systems, the parties themselves provide ideological endpoints. In multi-party systems, leftright semantics provide a means for voters to array parties along a single Downsian dimension.
Second, Inglehart and Klingemann report that, in their study of European countries, intensity of
polarization is an even better predictor of the meaningfulness of left-right semantics than number of
parties. Extreme polarization within the party system may make the stakes more important in terms
of clearly identifying one’s party along the left-right dimension, or may mean that the meaningfulness
of left-right semantics is being driven by the cohesiveness of small extreme parties on the left-right
dimension.
As a brief exploration of the variance in partisan components to left-right semantics, we
subjected each of the above hypotheses to bivariate correlation analysis. To test the first hypothesis,
we calculated the correlation between the relationship between party position and party placement
(from Table 11) and the number of major parties in each legislature.10 The correlation between these
variables is 0.60. We then examined the relationship between our measure of the importance of the
partisan component (again, the correlation results from Table 11) and the intensity of polarization
within each legislature. We measured intensity of correlation by the distance between the most leftist
and most rightist parties, according to the means presented in Table 10. The correlation for
polarization is 0.80. These results confirm Inglehart and Klingemann’s claim that intensity of
polarization is a more important indicator of the meaningfulness of left-right semantics than number
of parties, though both are clearly important.
The ideological component of left-right semantics. We have seen that, to differing degrees, leftright semantics provide alternative labels for parties in Latin America. Do they also provide cues as
to the ideological leanings of these parties? Are left-right semantics used to simplify the legislative
ideological and political spaces we identified earlier? This section of the paper explores the
substantive, or ideological, component of left-right semantics in Latin America.
To examine the relationship between left-right semantics and ideological dimensions, we
regress left-right party placement on the ideological factors we identified in the first half of this
paper. Specifically, we test the ability of these factors to predict the left-right position of a country’s
legislators. The results presented in Table 12 show that left-right semantics do correspond with
ideological dimensions in every country in our analysis. In nine of the 11 countries, some type of
economic dimension is highly correlated with left-right semantics. Also, in 7 of the countries the
10
The number of parties includes only those parties with more than two respondents in the survey.
19
tradition/secular, or religious, dimension predicts left-right positioning. A postmodern dimension is
related to left-right semantics in Mexico, but not in the other cases where this factor appears. These
results show that traditional ideological dimensions are linked to left-right semantics in Latin
America. In most all countries, being “left” means being secular and protectionist.
INSERT TABLE 12
While it is useful to know that left-right semantics are linked to substantive content, these
linkages likely only provide voters with meaningful cues if they are linked to the dimensions that
comprise the legislative political space. As we defined earlier, the political space is defined by
ideological dimensions that divide parties, not just legislators. Therefore, we next explored whether
left-right semantics are more often connected with ideological dimensions that we identified as
belonging to the political space within a given legislature. Interestingly, there does appear to be a
tendency for these factors to predict left-right positions more often than ideological dimensions that
do not belong to the political space. Of the 19 factors we identified that do not divide parties, only 7
(37%) of them are related to left-right placement. On the other hand, of the 16 factors that do create
political divides, only 3 (19%) of these do not help predict left-right positioning.
While we have seen that ideological dimensions are connected to left-right semantics, these
significant coefficients do not tell us how much ideological dimensions contribute to the variance in
left-right semantics within each country. R2s report how much of the variance in the dependent
variable, left-right party placement in this case, is explained by the independent variables. The R2s
reported in Table 12 show a similar pattern in terms of the meaningfulness of a left-right dimension
as we saw in our analysis of the party label component of left-right semantics. Countries in which
left-right semantics were less clearly linked to party labels (low correlations in Table 11, e.g.,
Colombia, Peru and Costa Rica) also tend to be countries in which left-right semantics are less linked
to ideologies. In these three countries, the R2 statistic is equal to, or less than, 0.10, suggesting that
ideological linkages explain very little of the variance in legislators’ left-right party placements.
Finally, in order to explore the cross-legislature variation in the results, we subjected these
data to similar correlation analyses as in the case of the partisan component. In this case, correlation
analysis shows that, once again, countries with more parties and countries with higher degrees of
polarization are more likely to be countries in which left-right semantics are more “meaningful”. The
correlation between number of parties and the connection between ideologies and left-right
semantics11 is 0.75, and the correlation between party polarization and the ideology regression R2 is
0.73.
Partisan vs. ideological components of left-right semantics. Inglehart and Klingemann (1976),
Knutsen (1997) and others have shown that left-right semantics in European countries are more
closely connected to party labels than to underlying ideological dimensions. Inglehart and
Klingemann argued that party identification, as the more concrete and close-to-home cue, would
normally be used for an evaluation of politics, and hence this component would outweigh the
ideological component of left-right self-placement. Their principal finding was that among the
European mass public, one’s sense of belonging to the left or right reflected party affiliations more
11
The connection between ideologies and left-right semantics is measured by the R2 of the regression, as reported in
Table 12.
20
than issue preference or value orientations. The partisan component thus emerges as stronger than
the ideological component (Inglehart and Klingemann, 1976: 260).
To conclude our analysis, we compare the amount of variance in left-right placement that is
explained by party identification to that explained by ideological positioning. Our data show that
Inglehart and Klingemann’s result holds in all the Latin American legislatures we examine.
INSERT TABLE 13
Table 13 contains the R2s obtained from regressing left-right party placement on our
ideological factors and party labels, respectively. In every country party label is more robustly
connected to left-right placement than all the ideological dimensions combined. If we break down
the analysis into bivariate correlations (see Table 13), we see that no single ideological dimension is
more closely related to left-right semantics than party label. Nonetheless, in more than one-half the
countries, at least one ideological factor is correlated with party label at a moderate level. This
suggests that at least some ideological component of left-right semantics is indirectly related to leftright placement through party labels.
In sum, the results show that, while left-right semantics do carry some substantive meaning
across Latin America, their primary function is as alternative party labels. Parties may be commonly
understood within a given political system to be “left” or “right” without individuals necessarily
clearly or consistently connecting substantive ideological dimensions to these placements. These
results vary across countries, and in countries where the partisan component is weakly linked to leftright semantics, the ideological component is similarly weak.
V. Conclusion
We have found that Latin American legislatures are more structured than generally acknowledged, at
least in terms of ideologies. Latin American legislators might not always vote in line with their
parties, hold blind loyalties to national leaders or voting constituencies, or even compete on
programmatic bases. Yet, considerable evidence shows that parties group like-minded politicians
more often than not. We also discovered that Left and Right convey meanings that are shared by
legislators in the same country. These meanings are frequently attached to various economic issue
dimensions, though the ideological component of left-right semantics is not as important as the
partisan component, much as in Western Europe.
At this point, our research into the ideological patterns that structure electoral competition in
Latin America is only starting. Our findings are based on inspection of legislatures at one single
point in time. Until we muster evidence from past and future legislatures, we cannot be sure that the
ideological divisions that we have identified are enduring. Moreover, ideological divisions at the
elite level might turn out to be completely out of line with ideological divisions at the mass level. In
countries with such an inegalitarian distribution of wealth and opportunity, it would not be surprising
to find out that the meanings that citizens attach to Left and Right are not at all similar to those that
politicians use. In future research, we purport to map out the ideological divides that structure
citizens’ beliefs and attitudes. Hence, we might some day be able to determine whether Latin
American parties provide the quality of representation that makes democracy work.
21
We also plan to further explore the results we have presented in these preliminary analyses.
In the first place, we would like to look more closely at cross-national variations in the dimensions
that comprise the legislative ideological and political spaces. We hope to determine whether the
ideologies stem from long-standing divisions such as societal cleavages and/or whether they are the
result of recent events, perhaps economic crises and the move toward structural adjustment. Second,
we would like to explore further the relationship between the party and ideological components of
left-right semantics. Our bivariate correlation results showed that in several countries, at least one
ideology is highly correlated with our party variable. It may be that in these countries ideological
meaning is indirectly linked to left-right semantics through the party component. According to
Knutsen (1997), if the ideological component is causally prior to the party component, then it may
have a larger impact than one would suspect at first glance. Finally, by stepping back from our partylevel and country-level analysis, we hope to determine whether the significance of left-right
semantics changes across party families in Latin America.
22
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24
Appendix A. Survey data and methods. We analyze data from the 1997 Parliamentary Elites of
Latin America project, directed by Manuel Alcántara (Universidad de Salamanca). The survey codes
legislators’ answers to 104 questions in 257 variables. Respondents were all national representatives
to their respective country’s lower chamber at the time of the interview (or to the unicameral
legislature, in the case of Costa Rica, Ecuador, and Peru). This survey represents a quantum leap in
terms of data availability for Latin American legislatures. Be that as it may, its contents somewhat
limit the kind of analyses that we can carry out. Moreover, its usefulness for statistical purposes
depends on controlling potential bias in various country databases. This appendix shows how we
tackle data limitations and lays bare our methodological assumptions.
First, we consider the problems of sample bias and missing observations. Table 1 reports
legislative party shares and sample sizes for eleven countries. As table 1 makes clear, some samples
over- or under-represent certain parties. There seems to be no consistent bias in the cross-country
representation of small over large parties or Leftist over Rightist parties. Yet, the proportion of
respondents in each of our samples definitely does not mirror the proportion of legislators in the
legislature at the time of the interview. Given that our first purpose is to describe political ideologies
in the legislature as a whole, over/under-sampling might introduce bias in our claims. Thus, for
example, we might falsely conclude that distributive concerns are paramount in a legislature if leftleaning legislators are over-represented in the sample. We could correct this bias by randomly
dropping respondents from over-represented parties, until sample proportion falls in line with
proportion in the legislature. However, this approach would lead to a high rate of attrition, which
would make statistical analysis meaningless in countries with smaller sample sizes.
Instead, we chose to weight each observation by the party share of seats in a legislature. If pj is
party j’s share of seats in a legislature and sj its sample proportion, then w=pj/sj is the weight
attributed to each legislator in party j. If the ratio of over- (under-) representation (w) is close to 1,
then weighting legislators’ responses by w is not problematic. This is true for most parties in most
countries. Unfortunately, w is either too large or too small in many cases. For example, small parties
in El Salvador are under-represented by a ratio w=5.95. Were we to keep El Salvador in our analysis,
we would in practice count the responses of a small party legislator six times. Conversely, Christian
Democrats in this same legislature are over-represented, with w=0.37. Each Christian Democrat
would count as one third of a legislator. This excessive weighting could introduce a different kind of
bias. Standard deviations for small party Salvadoran legislators would be artificially narrow, biasing
our results towards finding statistical significance where none might exist. In order to diminish this
kind of bias, we exclude countries with lop-sided ratios of misrepresentation. The last column in
table 1 reproduces the ratio w for each country included in our analysis. Note, in particular, that
respondents from large parties in Bolivia, as well as small party politicians in Colombia and Chile,
are notoriously underrepresented. We discuss some possible implications of under-representation in
the text.
The Salamanca databases include variables with large proportions of missing values due to lack
of response. As a general rule, we excluded from our analysis variables with a proportion of missing
values larger than 25% of the observations. Among the 26*11 variables that we did include, eight
show a proportion of missing values of ca. 20%.12 We cross-inspected these against other variables
12
These include r50 in Argentina, r57 in Brazil, r57, r59 and r61 in Chile, r49 and r240 in Ecuador, and r50 in Uruguay.
Please refer to the list of variables in the appendix.
25
in the database and concluded that these missing values appear randomly and do not bias our sample
in any discernible way. Hence, we included these variables in our analysis. In order to preserve a
complete data set, we substituted missing values with the variable’s mean. Again, this might
understate variance in variables with large proportions of missing values. Still, some of these
variables (for example r50 in Argentina or r57, r59 and r61 in Chile) appear with large factor
loadings in some factors, convincing us of their importance in explaining total variation in legislators’
stances despite bias towards lower variance.
After eliminating some indicators because of the statistical constraints alluded to above, we
settled on our battery of twenty-six variables for theoretical reasons. All 26 variables are
standardized to a –1 to 1 scale with discrete intervals. The rest of our statistical analysis starts from
these eleven “corrected” j*26 data matrices (one per country, with j respondents per country). In a
nutshell, our starting data matrices (i) eliminate sample bias by weighting observations and (ii)
maximize the number of variables in the set by filling in missing values.
We perform factor and regression analyses on each country matrix. In order to make our
analysis more transparent we now spell out the steps that we took to arrive at our results. Factor
analysis is a statistical technique that aims at summarizing variance in a number k of variables by
resorting to a number m<k of latent dimensions (factors or components). Given the assumptions of
factor analysis, the researcher faces a number of choices that introduce a fair amount of discretion
into otherwise mechanical procedures. Two decisions are of utmost importance: (i) the number of
factors that are kept as a “summary” of the larger data set and (ii) the proportion of variance in each
variable that is considered “common”.13 What decision one makes about (ii) is likely to have
important interpretive consequences. Principal component analysis assumes that variance in the
original data matrix is all “caused” by latent components. Factor analysis assumes that only part of
this variance, the common variance, can be attributed to latent factors. This assumption is not
problematic. Indeed, it is perfectly plausible that only part of the variance of variable k1 can be traced
back to factor m1, and that the rest of the variance is unique to variable k1. What is problematic is that
one cannot always know the size of the common variance beforehand. Thus, prior estimates about
the size of communality become critical. Where principal components starts with a correlation
matrix with 1’s along the diagonal, factor analysis substitutes the diagonal elements with these prior
estimates of communality.
We used the “factor” procedure in SAS, set to the “principal factors” method (PF). For each
variable, PF uses the squared multiple correlation with all other variables as an estimate of
communality. Given that our purpose is to explore the latent “ideological” space underlying the
visible “issue” space, we feel justified in using factors rather than principal components. Factors
make the underlying dimensions more interpretable. This is so because loadings for variables that
contribute highly to a factor (common variance) are per force larger than loadings for variables that
contribute highly to a principal component (total variance). Moreover, we compared the performance
of both procedures (principal components and principal factors) for Argentina and Mexico; both
methods yielded similar results in both cases. Ease of interpretation led us as well to rotate factors
using the varimax procedure.
13
Answers to (i) and (ii) are related. Justifying each and every one of our assumptions would lead us into a larger
statistical debate that we prefer to circumvent. The interested reader is referred to Jolliffe (1986).
26
Appendix B. List of variables
All variables standardized to a -1 to 1 scale; the direction of the responses was reversed in some cases
to conform to more intuitive notions of “left” and “right”. A value of 1 (-1) means total agreement
(disagreement) with the statement that defines each variable.
Variables Defining the Legislative space (listed by anticipated ideological dimensions):
Economic governance/Privatization
v49
Privatize industry
v50
Privatize services
v64
Price controls bad
Social protection/Social policy
v65
Do not sponsor job creation
v69
Do not provide housing
v70
Do not provide social security
v71
Do not provide unemployment insurance
v72
Basic subsidies bad
Financial openness/closure / Economic Nationalism
v54
Let IMF in
v57
US investment good
v59
European investment good
v61
Latin American investment good
Law and Order
v34
Delinquency/robbery are threats
v35
Labor unrest threatens democracy
v80
Use force against terrorists
v87
Violence an important problem
v149 Army needed for sovereignty
v168 Corruption always existed
Traditional values/Cultural libertarianism
v210 I go to church
v235 No abortion
v236 No divorce
v240 I’m very religious
Post-modern sensibilities
v90
Human/minority rights are important
v92
Environmental issues are important
Authoritarian propensities
v11
Democracy is never the best system
v15
Elections are never the best way
27
v26
Parties not needed for democracy
Other Variables
v132
Left-Right party-placement is a continuous variable in the range (left) 1 to 10 (right).
v132b Parties are a series of dummy variables specific to each country.
28
Appendix C: Party Abbreviations
ARGENTINA
FREPAS Frente del País Solidario
UCR
Unión Cívica Radical
PJ
Partido Justicialista
UCEDE Unión del Centro Democrático
BOLIVIA
MBL
Movimiento Bolivia Libre
CONEPA Conciencia de Patria
MIR
Movimiento de la Izquierda
UCS
Unión Cívica Solidaridad
MNR
Movimiento Nacionalista
ADN
Acción Democrática Nacionalista
BRAZIL
PSB
PT
PCdoB
PSDB
PMDB
PFL
PTB
PPB
Partido Socialista Brasiliero
Partido dos Trabalhadores
Partido Communista do Brasil
Partido da Social Democracia
Partido do Movimiento
Partido da Frente Liberal
Partido Trabalhista Brasileiro
Partido Progressista Brasileiro
ECUADOR
Pachakuti Movimiento Nuevo-País Pachakutik
ID
Izquierda Democrática
DP
Democracia Popular
PRE
Partido Roldosista Ecuatoriano
FRA
Frente Radical Alfarista
PSC
Partido Social Cristiana
MEXICO
PRD
Partido de la Revolución
PRI
Partido Revolucionario Institucional
PAN
Partido Acción Nacional
PERU
APRA
UPP
AP
C95/NM
Renovac
Alianza Popular Revolucionaria
Unión por el Perú
Acción Popular
Cambio ‘95/Nueva Mayoría
Renovación
URUGUAY (parties and factions)
FP
Frente Popular
Comunista Comunismo
CHILE
Socialista Partido Socialista
Socialista
Socialismo
PPD
Partido por la Democracia
VertArti
Vertiente Artigista
PDC
Partido Democrática Cristiano
AUruguay Asamblea Uruguay
UDI
Unión Democrática Independiente PC
Partido Colorado
RenoNacl Renovación Nacional
ForoBat
Foro Batllista
PN
Partido Nacional
Herrerismo Herrerismo
COLOMBIA
PLiberal Partido Liberal
Manos obra Manos a la Obra
PConserv Partido Conservador
NueEspac Nuevo Espacio
COSTA RICA
PLN
Partido de Liberación Nacional
PUSC
Partido Unidad Social Cristiana
VENEZUELA
MAS
Movimiento al Socialismo
AD
Acción Democrática
CausaR
Causa R
CONVER Convergencia
COPEI
Partido Social Cristiano
29
Table 1. Party shares and sample sizes*
COUNTRY PARTY
Argentina PJ
UCR/Frepaso
Other
MNR
ADN
MIR
UCS
Other
PMDB
Brazil
PFL
PSDB
PT
Other
PDC
Chile
PPD
PS
RN
UDI
Other
Colombia PSC
PL
Other
Costa Rica PLN
PUSC
Other
PSC
Ecuador
PRE
DP
Pachakutik
Other
PRI
Mexico
PAN
PRD
Other
Cambio ’95/NM
Peru
UPP
APRA
Other
P. Colorado
Uruguay
P. Nacional
Frente Amplio
Other
Venezuela AD
COPEI
Causa R
MAS/Convergencia
Bolivia
SEATS (%)
118 (45.9)
110 (42.8)
29 (11.3)
26 (20.0)
25 (19.2)
21 (16.2)
25 (19.2)
107 (20.9)
89 (17.3)
64 (12.5)
49 (9.6)
204 (39.7)
39 (32.5)
16 (13.3)
11 (9.16)
23 (19.2)
17 (14.2)
14 (11.7)
28 (16.9)
84 (50.9)
53 (32.1)
28 (49.1)
25 (43.9)
4 (7.0)
27 (32.9)
19 (23.2)
12 (14.6)
8 (9.8)
16 (19.6)
239 (39.1)
122 (26.6)
125 (25.7)
14 (2.8)
67 (56)
17 (14)
8 (7)
28 (16)
32 (32.3)
31 (31.1)
31 (31.1)
5 (5.1)
55 (27.6)
54 (27.1)
40 (20.1)
50 (25.1)
SAMPLE (%)
23 (33.8)
UCR: 19 (27.9)
Frepaso: 11 (16.2)
15(22.1)
23 (31.1)
9 (12.2)
7 (9.5)
17 (22.9)
18 (24.3)
16 (23.2)
12 (17.4)
10 (14.5)
9 (13.0)
22 (31.9)
31 (32.9)
10 (10.6)
13 (13.8)
23 (24.5)
12 (12.8)
5 (5.3)
14 (22.2)
41 (65.1)
8 (12.7)
25 (48.1)
23 (44.2)
4 (7.7)
23 (32.4)
14 (19.7)
10 (14.1)
8 (11.3)
16 (22.6)
63 (51.2)
35 (28.5)
23 (18.7)
2 (1.6)
52 (59.7)
12 (13.7)
7 (8.0)
16 (18.4)
22 (30.1)
21 (28.7)
25 (34.2)
5 (6.8)
18 (26.1)
16 (23.2)
13 (18.8)
MAS: 8 (11.6)
Convergencia: 9 (13.0)
WEIGHT W
1.357988
0.970522
0.970522
0.511312
0.643086
2.081967
2.021052
0.707424
0.790123
0.900862
0.994252
0.862068
0.738462
1.244514
0.987842
1.254717
0.663768
0.783673
1.109375
2.207547
0.761261
0.781874
2.527559
1.020790
0.993213
0.909090
1.015432
1.177665
1.035461
0.867256
0.867256
0.763672
0.933333
1.374332
1.750000
0.938023
1.021898
0.875000
0.869565
1.073089
1.083624
0.909357
0.750000
1.168103
1.057471
1.069149
1.020325
1.0203250
* Please see Appendix C for a list of party abbreviations and names.
30
Table 2. Ideological dimensions in Latin America
(Initial factor method: Principal factors. Sample weighted by party share, all parties.)
COUNTRY
Argentina
0.48
(N= 68)
Bolivia
0.42
(N= 74)
Brazil
0.47
(N= 69)
FACTOR 1
FACTOR 2
FACTOR 3
State/Market
Tradition/Secular
Economic nationalism
λ1=4.2802 (34%)
λ2=2.4139 (19%)
λ3=1.5859 (13%)
Privatize industry
Privatize services
Price controls bad
Don’t sponsor jobs
Don’t provide housing
Don’t provide soc.sec.
Don’t provide dole
Basic subsidies bad
I go to church
No abortion
No divorce
I’m very religious
US investment bad
EU investment bad
State/Market (?)
Tradition/Secular
λ1=3.2524 (30%)
λ2=2.5349 (23%)
State/Market (?)
Postmodernism (?)
λ3=2.3392 (21%)
(Privatize industry)
Privatize services
Price controls bad
Don’t provide dole
I go to church
(No divorce)
I’m very religious
FACTOR 4
Privatize industry
Don’t sponsor jobs
(Let IMF in)
(US investment good)
Labor unrest is threat
Corruption
Rights not important
(Env. not important)
(No divorce)
State/Market
Tradition/Secular
Postmodernism
Economic nationalism
λ1=2.8792 (24%)
λ2=2.4917 (20%)
λ3=2.2363 (18%)
λ4=1.8725 (15%)
Privatize industry
Privatize services
Price controls bad
Don’t provide housing
Don’t provide dole
Basic subsidies bad
I go to church
No abortion
No divorce
I’m very religious
(Don’t provide dole)
US investment bad
EU investment bad
Rights not important
Env. not important
(Army needed for sv’y)
31
Table 2. Ideological dimensions in Latin America (cont’d)
COUNTRY
Chile
0.50
(N= 94)
FACTOR 1
FACTOR 2
FACTOR 3
State/Market
Authoritarianism
Postmodernism
λ1=4.7798 (37%)
Tradition/Secular
Economic nationalism
λ2=2.9113 (22%)
λ3=1.6915 (13%)
Privatize industry
Privatize services
Price controls bad
Don’t sponsor jobs
Don’t provide dole
Basic subsidies bad
Army needed for sov’y
US investment bad
EU investment bad
LA investment bad
I go to church
No abortion
No divorce
I’m very religious
FACTOR 4
Rights not important
Env. not important
Colombia
0.44
(N= 63)
Dem. not best system
Parties not needed
Social protection
Tradition/Secular
λ1=2.8466 (25%)
λ2=2.6505 (23%)
(Price controls bad)
Don’t sponsor jobs
Don’t provide housing
(Don’t provide dole)
Basic subsidies bad
LA investment good
State/Market (?)
Nationalism (?)
λ3=1.9305 (17%)
Privatize industry
I go to church
No abortion
No divorce
I’m very religious
US investment bad
Army needed for sv’y
(Delinquency is threat)
(Rights not important)
Costa Rica
0.45
(N= 52)
Social protection
Economic nationalism
λ2=2.6029 (22%)
λ3=2.1484 (19%)
Price controls bad
Don’t provide housing
Basic subsidies bad
US investment bad
EU investment bad
LA investment bad
(Env. not important)
Economic nationalism
Social protection
λ1=2.3771 (20%)
λ2=2.2035 (18%)
Social protection (?)
Social order (?)
λ3=2.1893 (18%)
US investment bad
EU investment bad
LA investment bad
Price controls bad
Don’t sponsor jobs
(Don’t provide housing)
(Don’t provide soc.sec.)
Don’t provide dole
(Basic subsidies bad)
Elections not best way
(Army needed for sv’y)
Use force vs. terrorists
Economic governance
Tradition/Secular
λ1=2.9168 (25%)
Privatize industry
Privatize services
I go to church
No abortion
(No divorce)
Ecuador
0.46
(N= 71)
Tradition/Secular
λ4=2.0369 (17%)
I go to church
I’m very religious
32
Table 2. Ideological dimensions in Latin America (cont’d)
COUNTRY
Mexico
0.43
(N= 123)
Peru
0.45
(N= 87)
Uruguay
0.48
(N= 73)
Venezuela
0.40
(N= 66)
FACTOR 1
FACTOR 2
FACTOR 3
Social protection
Tradition/Secular
Postmodernism
λ1=3.0549 (27%)
λ2=2.9487 (26%)
λ3=1.7136 (15%)
Price controls bad
Don’t sponsor jobs
Don’t provide housing
Don’t provide soc.sec.
Don’t provide dole
(Basic subsidies bad)
State/Market
I go to church
No abortion
No divorce
I’m very religious
LA investment bad
Tradition/Secular
Economic nationalism
λ1=3.5842 (31%)
λ2=2.2295 (19%)
λ3=2.0897 (18%)
Privatize industry
Privatize services
(Price controls bad)
Don’t sponsor jobs
Don’t sponsor housing
Don’t provide soc.sec.
Don’t provide dole
(Basic subsidies bad)
I go to church
I’m very religious
US investment good
EU investment good
LA investment good
Rights are important
Social protection
Economic nationalism
λ1=3.4309 (28%)
λ2=2.7851 (22%)
Tradition/Secular
?
λ3=2.4081 (19%)
Price controls bad
Don’t sponsor jobs
Don’t provide housing
Don’t provide soc.sec.
Don’t provide dole
Basic subsidies bad
Social protection
Tradition/Secular
λ1=2.7741 (27%)
US investment bad
EU investment bad
LA investment bad
(Let IMF in)
Delinquency is threat
(Labor unrest is threat)
I go to church
I’m very religious
Tradition/Secular
Postmodernism
λ2=2.5949 (25%)
λ3=1.5887 (15%)
Price controls bad
Don’t provide dole
Basic subsidies bad
(Privatize services)
(Rights not important)
Env. not important
(Let IMF in)
(I go to church)
I’m very religious
I go to church
I’m very religious
Rights not important
Env. not important
LA investment bad
(Elections not best way)
33
Table 3. Ideological dimensions in Latin America
(Initial factor method: Principal factors. Sample weighted by party share, large parties.)
COUNTRY
Argentina
0.48
(N= 54)
Bolivia
0.44
(N= 56)
Brazil
0.46
(N= 47)
FACTOR 1
FACTOR 2
FACTOR 3
State/Market
Tradition/Secular
Law and Order
λ1=3.6869 (30%)
λ2=2.6512 (21%)
λ3=1.8647 (15%)
Privatize industry
Privatize services
Don’t sponsor jobs
Don’t provide housing
(Don’t provide soc.sec.)
Don’t provide dole
Basic subsidies bad
Economic governance
Tradition/Secular
λ1=3.2484 (29%)
I go to church
No abortion
No divorce
I’m very religious
(Price controls bad)
?
?
λ2=2.7152 (24%)
λ3=2.3935 (21%)
Privatize services
Price controls bad
(Don’t provide hous’g)
Don’t provide dole
Don’t sponsor jobs
Corruption
Labor unrest is threat
LA investment good
No divorce
Rights not important
Use force vs. terrorists
Parties not needed
I go to church
I’m very religious
Social protection
Tradition/Secular
Economic nationalism (?)
λ1=2.8085 (23%)
λ2=2.6919 (22%)
λ3=2.2840 (19%)
(Privatize industry)
Don’t provide soc.sec.
Don’t provide dole
Basic subsidies bad
I go to church
No abortion
No divorce
I’m very religious
US investment bad
EU investment bad
LA investment bad
Delinquency is threat
Labor unrest is threat
Rights not important
Env. not important
34
Table 3. Ideological dimensions in Latin America (cont’d)
COUNTRY
Chile
0.49
(N= 90)
FACTOR 1
FACTOR 2
FACTOR 3
State/Market
Postmodernism
Authoritarianism
λ1=4.3158 (34%)
Tradition/Secular
Economic nationalism
λ2=3.0786 (24%)
λ3=1.7655 (14%)
Privatize industry
Privatize services
Price controls bad
Don’t sponsor jobs
Basic subsidies bad
Army needed for sov’y
US investment bad
EU investment bad
FACTOR 4
I go to church
No abortion
No divorce
I’m very religious
(Use force vs. terrorists)
Rights not important
(Env. not important)
Colombia
0.43
(N= 55)
Costa Rica
0.45
(N= 48)
Dem. not best system
(Elections not best way)
Parties not needed
Social protection
Economic nationalism
Tradition/Secular
λ1=2.8950 (26%)
λ2=2.2085 (20%)
λ3=2.1424 (19%)
(Price controls bad)
Don’t sponsor jobs
Don’t provide housing
Don’t provide soc.sec.
(Don’t provide dole)
Basic subsidies bad
Economic governance
Tradition/Secular
Postmodernism
λ1=3.0646 (26%)
(Let IMF in)
US investment bad
(EU investment bad)
I go to church
No abortion
No divorce
I’m very religious
Privatize industry
Privatize services
Labor unrest is threat
Social protection
Financial
integration/isolation
λ2=2.6140 (22%)
λ3=2.1826 (19%)
Price controls bad
Don’t provide housing
Basic subsidies bad
US investment bad
EU investment bad
LA investment bad
Economic nationalism
Tradition/Secular
λ2=2.2049 (19%)
λ3=2.1409 (19%)
US investment bad
EU investment bad
LA investment bad
(Privatize industry)
I go to church
No abortion
Ecuador
0.44
(N= 56)
Rights not important
Social protection
Authoritarianism
λ1=2.2290 (19%)
Don’t provide dole
(Basic subsidies bad)
Use force vs. terrorists
Delinquency is threat
Elections not best way
I go to church
(No divorce)
I’m very religious
Social protection
Authoritarianism
λ4=1.9874 (17%)
Don’t sponsor jobs
Don’t provide soc.sec.
Env. not important
Parties not needed
35
Table 3. Ideological dimensions in Latin America (cont’d)
COUNTRY
Mexico
0.43
(N= 122)
Peru
0.45
(N= 71)
FACTOR 1
FACTOR 2
FACTOR 3
Social protection
Tradition/Secular
Postmodernism
λ1=3.1614 (28%)
λ2=2.8493 (25%)
λ3=1.6808 (15%)
Price controls bad
Don’t sponsor jobs
Don’t provide housing
Don’t provide soc.sec.
Don’t provide dole
(Basic subsidies bad)
State/Market
Postmodernism
λ1=3.6961 (31%)
I go to church
No abortion
No divorce
I’m very religious
LA investment good
Rights not important
Env. not important
Tradition/Secular
Economic nationalism
λ2=2.0817 (18%)
λ3=2.0779 (18%)
Privatize industry
Privatize services
Don’t sponsor jobs
Don’t sponsor housing
Don’t provide soc.sec.
(Don’t provide dole)
I go to church
I’m very religious
US investment good
EU investment good
LA investment good
Delinquency is threat
Use force vs. terrorists
Uruguay
0.48
(N= 73)
Venezuela
0.40
(N= 66)
Rights not important
Env. not important
Social protection
Economic nationalism
λ1=3.4309 (28%)
λ2=2.7851 (22%)
Price controls bad
Don’t sponsor jobs
Don’t provide housing
Don’t provide soc.sec.
Don’t provide dole
Basic subsidies bad
Social protection
Tradition/Secular
λ1=2.7741 (27%)
US investment good
EU investment good
LA investment good
(Let IMF in)
Delinquency is threat
(Labor unrest is threat)
I go to church
I’m very religious
Tradition/Secular
Postmodernism
λ2=2.5949 (25%)
λ3=1.5887 (15%)
Price controls bad
Don’t provide dole
Basic subsidies bad
(Privatize services)
(Rights not important)
Env. not important
(Let IMF in)
(I go to church)
I’m very religious
I go to church
I’m very religious
Tradition/Secular
(?)
λ3=2.4081 (19%)
LA investment good
(Elections not best way)
36
Table 6. Mean party placements on principal factors
(OLS regression on party dummies, no intercept estimate)
COUNTRY
PARTY
PJ
UCR
Argentina
FREPASO
FACTOR 1
0.2930*
(0.1548)
-0.4342**
(0.1740)
-0.7032**
(0.2287)
F-value
p>F
Adj. R2
MNR
ADN
Bolivia
MIR
UCS
6.422
0.0009
0.2315
0.1442
(0.1692)
0.6048**
(0.2705)
-0.5062
(0.3067)
0.0945
(0.1968)
F-value
p>F
Adj. R2
PMDB
PFL
Brazil
PSDB
PT
2.170
0.0853
0.0771
-0.0511
(0.1958)
0.3784
(0.2261)
-0.0838
(0.2477)
-0.6828**
(0.2611)
F-value
p>F
Adj. R2
-0.6511***
(0.1155)
-0.3770*
(0.1939)
-0.6622***
(0.1784)
0.7098***
(0.1341)
0.8445***
(0.1857)
PDC
PPD
PS
Chile
2.456
0.0599
0.1102
RN
UDI
F-value
p>F
Adj. R2
19.597
0.0001
0.5082
DEPENDENT VARIABLE
FACTOR 2
0.1252
(0.1788)
-0.1029
(0.2009)
-0.4742*
(0.2641)
1.326
0.2762
0.0178
-0.3439*
(0.1807)
0.5354*
(0.2888)
-0.7153**
(0.3275)
0.1944
(0.2102)
3.171
0.0209
0.1342
0.1844
(0.1989)
0.2569
(0.2297)
-0.1158
(0.2517)
-0.4719
(0.2653)*
1.371
0.2597
0.0306
0.4672***
(0.1184)
-0.9358***
(0.1987)
-1.2109***
(0.1828)
0.0974
(0.1375)
0.6393**
(0.1903)
18.677
0.0001
0.4955
FACTOR 3
-0.9766
(0.1742)
-0.0098
(0.1958)
-0.0241
(0.2573)
0.109
0.9547
-0.0521
-0.1449
(0.1665)
0.3233
(0.2662)
0.3495
(0.3018)
-0.0664
(0.1937)
0.923
0.4579
-0.0056
-0.0236
(0.1842)
-0.0904
(0.2127)
0.1522
(0.2329)
-0.2902
(0.2455)
0.505
0.7321
-0.0440
0.0591
(0.1578)
0.1251
(0.2649)
-0.1345
(0.2437)
-0.0665
(0.1832)
0.1964
(0.2536)
0.280
0.9230
-0.0417
37
Table 6. Mean party placements on principal factors (cont’d)
COUNTRY
PARTY
PC
Colombia
PL
FACTOR 1
0.4415*
(0.2565)
0.1458
(0.1499)
F-value
p>F
Adj. R2
PLN
Costa
Rica
PUSC
-0.2718
(0.1777)
0.3196*
(0.1852)
F-value
p>F
Adj. R2
PSC
PRE
Ecuador
1.955
0.1517
0.0335
DP
PACH
2.659
0.0808
0.0647
0.3277**
(0.1557)
0.0260
(0.2039)
0.1638
(0.2412)
-0.4380
(0.2697)
F-value
p>F
Adj. R2
-1.2514**
(0.1127)
0.6148***
(0.1524)
-0.2386
(0.1879)
PRI
PAN
Mexico
1.886
0.1269
0.0595
PRD
F-value
p>F
Adj. R2
C95
UPP
Peru
APRA
F-value
p>F
Adj. R2
7.622
0.0001
0.1400
0.1888
(0.1258)
-0.5068*
(0.2619)
-0.2213
(0.3429)
2.137
0.1035
0.0459
DEPENDENT VARIABLE
FACTOR 2
0.4832**
(0.2040)
-0.0305
(0.1192)
2.838
0.0675
0.0626
-0.4926**
(0.1514)
0.6395***
(0.1578)
13.505
0.0001
0.3426
-0.1307
(0.1776)
0.0452
(0.2325)
0.1318
(0.2751)
-0.1008
(0.3076)
0.229
0.9208
-0.0583
-0.1210
(0.0860)
1.0017***
(0.1164)
-0.7669***
(0.1435)
34.879
0.0001
0.4545
0.1017
(0.1256)
-0.2074
(0.2615)
-0.1945
(0.3424)
0.536
0.6592
-0.0200
FACTOR 3
0.3598
(0.2379)
0.1204
(0.1390)
1.517
0.2286
0.0185
-0.0693
(0.1913)
0.0145
(0.1994)
0.068
0.9341
-0.0404
0.3911**
(0.1430)
0.2836
(0.1873)
-0.5052**
(0.2216)
-1.2155***
(0.2477)
9.761
0.0001
0.3849
0.3025**
(0.1025)
0.0762
(0.1387)
-0.5273**
(0.1710)
6.174
0.0006
0.1129
0.1751
(0.1727)
-0.0479
(0.2644)
-0.3926
(0.3462)
1.073
0.3665
0.0031
38
Table 6. Mean party placements on principal factors (cont’d)
COUNTRY
PARTY
PC
PN
Uruguay
FA
FACTOR 1
0.2290
(0.1692)
0.4306**
(0.1692)
-0.7024***
(0.1587)
F-value
p>F
Adj. R2
COPEI
AD
CAUSA R
Venezuela
MAS
CONV.
9.300
0.0001
0.2652
0.3428*
(0.1901)
0.2354
(0.1901)
-0.6902**
(0.2237)
-0.3426
(0.2852)
0.0763
(0.2689)
F-value
p>F
Adj. R2
3.165
0.0132
0.1409
DEPENDENT VARIABLE
FACTOR 2
0.5482**
(0.1895)
-0.1683
(0.1895)
-0.3765**
(0.1778)
4.545
0.0059
0.1335
0.5779**
(0.1776)
-0.0777
(0.1776)
-0.6924**
(0.2090)
-0.4719*
(0.2665)
0.3052
(0.2512)
5.272
0.0004
0.2445
FACTOR 3
0.2116
(0.1600)
0.5408**
(0.1600)
-0.7306***
(0.1501)
12.284
0.0001
0.3291
0.0000
(0.2044)
-0.2500
(0.2044)
0.2918
(0.2405)
0.0259
(0.3066)
0.0534
(0.2890)
0.602
0.6985
0.0470
*** p<0.001, ** p<0.05, * p<0.1
39
Table 7. Mean party placement in the political space.
COUNTRY
DIMENSION
µ (sd)
Argentina
State/Market
-0.166
(0.857)
Bolivia
Tradition/Secular
-0.086
(0.936)
Brazil
State/Market
-0.069
(0.836)
State/Market,
Authoritarianism
Chile
-0.072
(0.919)
Tradition/Secular
-0.018
(0.933)
Colombia
Tradition/Secular
0.100
(0.789)
Costa Rica
Social protection
0.049
(0.942)
Ecuador
Social protection?
-0.025
(0.901)
Social protection
0.000
(0.976)
Tradition/Secular
0.079
(0.932)
Postmodernism
0.081
(0.870)
Social protection
-0.044
(0.931)
Mexico
Uruguay
Economic
nationalism
Tradition/Secular
Social protection,
Tradition/Secular
Venezuela
Tradition/Secular
-0.015
(0.962)
-0.024
(0.923)
-0.009
(0.876)
-0.015
(0.873)
µ1 (sd)
µ2 (sd)
µ3 (sd)
µ4 (sd)
µ5 (sd)
PJ
0.293
(0.936)
MNR
-0.344
(1.007)
PMDB
-0.051
(0.837)
PDC
-0.651
(0.609)
PDC
0.467
(0.571)
PC
0.483
(0.661)
PLN
-0.493
(0.585)
PSC
0.391
(0.668)
PRI
-0.251
(0.882)
PRI
-0.121
(0.716)
PRI
0.302
(0.802)
PC
0.229
(0.878)
PC
0.548
(0.786)
PC
0.212
(0.949)
COPEI
0.343
(0.992)
COPEI
0.578
(0.779)
UCR
0.434
(0.627)
ADN
0.535
(0.718)
PFL
0.378
(0.606)
PPD
-0.377
(0.558)
PPD
-0.936
(0.923)
PL
-0.030
(0.794)
PUSC
0.639
(0.908)
PRE
0.283
(0.863)
PAN
0.615
(1.044)
PAN
1.002
(0.643)
PAN
0.076
(0.781)
PN
0.431
(0.959)
PN
-0.168
(0.869)
PN
0.541
(0.755)
AD
0.235
(0.695)
AD
-0.077
(0.774)
FREPASO
-0.703
(0.460)
MIR
-0.716
(0.457)
PSDB
-0.084
(1.028)
PS
-0.663
(0.714)
PS
-1.211
(0.484)
UCS
0.194
(0.842)
PT
-0.683
(0.536)
RN
0.709
(0.638)
RN
0.097
(0.634)
UDI
0.844
(0.727)
UDI
0.639
(0.796)
DP
-0.505
(0.730)
PRD
-0.238
(0.695)
PRD
-0.767
(0.675)
PRD
-0.527
(0.922)
FA
-0.702
(0.503)
FA
-0.376
(0.985)
FA
-0.731
(0.510)
CAUSAR
-0.690
(0.854)
CAUSAR
-0.692
(0.573)
PACH
-1.215
(0.333)
MAS
-0.343
(0.686)
MAS
-0.472
(0.649)
CONV
0.076
(0.578)
CONV
0.305
(0.951)
µ (sd)=grand mean, standard deviation; µX (sd)=mean placement of party x, standard deviation.
40
Table 7. Party placement correlations along factors 1, 2 and 3
Argentina
Bolivia
Brazil
Chile
Ecuador
f2
f3
f2
f3
f2
f3
f2
f3
f2
f3
f1
0.748
-0.370
0.965
-0.637
0.856
0.062
-0.537
0.242
0.550
-0.944
f2
El Salvador
0.340
Mexico
-0.466
Peru
0.454
Uruguay
-0.689
Venezuela
-0.249
f2
f3
f2
f3
f2
f3
f2
f3
f2
f3
f1
0.209
0.226
-0.953
-0.003
1.000
0.294
-0.892
0.461
-0.674
-0.792
f2
-0.905
-0.298
0.294
-0.011
0.779
41
Table 10. Left-Right Party-Placement by Latin American Legislators, Party Averages
ARGENTINA
FREPASO
UCR
PJ
UCEDE
Main Parties
Total*
COLOMBIA
Mean
3.50
4.53
5.24
8.00
5.32
5.02
Std. Dev.
1.27
1.28
1.64
2.00
1.55
1.75
Freq.
10
17
21
3
51
60
BOLIVIA
MBL
CONEPA
MIR
UCS
SyD
MNR
ADN
Main Parties
Total*
Mean
4.25
4.40
5.57
6.06
6.67
7.68
8.00
6.09
6.39
Std. Dev.
0.50
1.14
0.98
0.85
1.15
1.13
1.12
0.98
1.76
Freq.
4
5
7
16
3
22
9
66
71
Mean
1.75
2.00
2.00
4.11
4.53
5.75
6.67
7.33
4.27
4.61
Std. Dev.
0.50
1.07
1.73
0.78
0.99
1.76
1.53
1.21
1.20
2.19
Freq.
4
8
3
9
15
12
3
6
60
66
BRAZIL
PSB
PT
PCdoB
PSDB
PMDB
PFL
PTB
PPB
Main Parties
Total*
Mean
5.53
7.29
6.41
5.89
Std. Dev.
1.92
1.82
1.87
2.04
Freq.
40
14
54
61
Mean
5.00
6.22
5.61
5.52
Std. Dev.
1.28
1.09
1.18
1.31
Freq.
23
23
46
50
Mean
3.43
3.67
4.50
4.57
5.00
6.83
4.67
5.18
Std. Dev.
1.27
0.58
1.27
1.22
0.00
1.44
0.96
2.00
Freq.
7
3
10
14
3
23
60
67
Mean
3.07
4.70
7.28
5.01
5.27
Std. Dev.
0.88
0.95
1.78
1.20
2.26
Freq.
15
10
18
43
45
Mean
3.23
5.40
6.45
5.03
5.26
Std. Dev.
0.92
0.97
1.48
1.12
1.59
Freq.
22
62
33
117
118
PLiberal
PConserv
Main Parties
Total*
COSTA RICA
PLN
PUSC
Main Parties
Total*
ECUADOR
Pachakutik
ID
DP
PRE
FRA
PSC
Main Parties
Total*
EL SALVADOR
FMLN
PDC
ARENA
Main Parties
Total*
MEXICO
CHILE
Socialista
PPD
PDC
UDI
RenoNacl
Main Parties
Total*
Mean
2.62
4.36
4.42
6.42
6.48
4.86
4.99
Std. Dev.
0.87
1.12
0.81
2.02
0.99
1.16
1.77
Freq.
13
11
31
12
23
90
93
PRD
PRI
PAN
Main Parties
Total*
42
Table 10, cont’d.
PERU
APRA
UPP
AP
C95/NM
Renovac
Main Parties
Total*
VENEZUELA
Mean
4.14
5.58
5.67
6.27
7.33
5.80
5.90
Std. Dev.
0.90
0.90
1.15
1.50
1.53
1.20
1.61
Freq.
7
12
3
48
3
73
82
Mean
2.96
4.00
5.00
5.60
4.39
4.39
Std. Dev.
0.84
0.82
0.56
1.05
0.82
0.82
Freq.
25
4
20
20
69
69
MAS
AD
CausaR
CONVERG
COPEI
Main Parties
Total*
Mean
3.67
4.50
4.60
4.71
5.75
4.65
4.90
Std. Dev.
0.58
0.89
0.55
1.80
1.06
0.98
1.39
Freq.
3
16
5
7
16
47
50
URUGUAY
FP
Nuevo Espacio
PC
PN
Main Parties
Total*
*all parties, including minor parties not listed here
Table 11. Meaningfulness of Left-Right Semantics as Party Identifiers:
Correlation Between Party’s “Real” Left-Right Placement and Legislators’ Party Placements
Brazil
Uruguay
Bolivia
Chile
Ecuador
Mexico
Argentina
Venezuela
Peru
Costa Rica
Colombia
0.833
0.812
0.788
0.776
0.726
0.700
0.583
0.527
0.467
0.465
0.383
Note: Data from 1997 survey of Latin American legislators. Only parties with greater than two
respondents are included.
43
Table 12. Ideological Components of Left-Right Party Placement: Country-by-Country OLS Regression Results
Related to Left-Right Semantics
Factor
Argentina
1 State/Market*
2 Tradition/Secular
3 Economic Nationalism
Adjusted Regression R2
Bolivia
1 State/Market (?)**
2 Tradition/Secular
3 State/Market & Modern/Postmodern (?)
Adjusted Regression R2
Brazil
1 State/Market
2 Tradition/Secular
3 Modern/Postmodern
4 Economic Nationalism
Adjusted Regression R2
Chile
1 State/Market;Authorit./Democracy
2 Tradition/Secular
3 Economic Nationalism
Adjusted Regression R2
Colombia
1 Social Protection
2 Tradition/Secular
3 State/Market & Nationalism (?)
Adjusted Regression R2
Costa Rica
1 Eco. governance & Tradition/Secular
2 Social Protection
3 Economic Nationalism
Adjusted Regression R2
Y**
Y
0.22
Y
0.38
Related to Left-Right Semantics*
Ecuador
1 Economic Nationalism
2 Social Protection
3 Social Protection & Social Order (?)
4 Tradition/Secular
Adjusted Regression R2
Mexico
1 Social Protection
2 Tradition/Secular
3 Postmodernism
Adjusted Regression R2
Peru
1 State/Market
2 Tradition/Secular
3 Economic Nationalism
Adjusted Regression R2
Y
Y
Y
Y
0.20
Y
Y
Y
0.38
Y
0.03
0.45
0.52
Uruguay
1 Social Protection
2 Economic Nationalism
3 Tradition/Secular
Adjusted Regression R2
0.08
Venezuela
1 Social Protection & Tradition/Secular
2 Tradition/Secular
3 Postmodernism
Adjusted Regression R2
Y
Y
Y
Y
Y
Y
0.54
Y
0.07
Y
Y
0.10
* Ideological factors/divides in italics are ideologies in the political space ** ‘Y’ indicates a P-value # 0.10; two-tailed.
** Question marks indicate “messy” factors for which it was difficult to discern a clear ideological dimension.
45
Table 13. Ideological vs. Partisan Component of Left-Right Party Placement
ARGENTINA
Regression R2s1
ideology regression
N
51
Adjusted R2
0.22
Bivariate Correlations
LRPP2
LRPP
1
party variable
0.54
factor 1
0.41
factor 2
0.38
factor 3
0.16
party regression
N
Adjusted R2
party variable3
factor 1
factor 2
factor 3
1.00
0.64
0.30
0.18
1.00
0.21
0.07
1.00
0.05
1.00
BOLIVIA
Regression R2s
ideology regression
N
66
Adjusted R2
0.38
Bivariate Correlations
LRPP
LRPP
1.00
party variable
0.78
factor 1
0.63
factor 2
-0.27
factor 3
-0.01
party regression
N
Adjusted R2
66
0.60
party variable
factor 1
factor 2
factor 3
1.00
0.47
0.01
0.10
1.00
-0.20
0.04
1.00
0.04
1.00
BRAZIL
Regression R2s
ideology regression
N
60
Adjusted R2
0.45
Bivariate Correlations
LRPP
LRPP
1.00
party variable
0.82
factor 1
0.52
factor 2
0.40
factor 3
0.02
factor 4
0.03
51
0.28
party regression
N
Adjusted R2
60
0.67
party variable
factor 1
factor 2
factor 3
factor 4
1.00
0.47
0.42
0.01
-0.01
1.00
-0.11
-0.03
0.02
1.00
-0.09
-0.02
1.00
-0.08
1.00
46
Table 13, cont’d.
CHILE
Regression R2s
ideology regression
N
90
Adjusted R2
0.52
Bivariate Correlations
LRPP
LRPP
1.00
party variable
0.74
factor 1
0.62
factor 2
0.41
factor 3
-0.08
party regression
N
90
Adjusted R2
0.54
party variable
factor 1
factor 2
factor 3
1.00
0.59
0.48
0.01
1.00
0.09
0.10
1.00
0.00
1.00
COLOMBIA
Regression R2s
ideology regression
N
54
Adjusted R2
0.08
party regression
N
54
Adjusted R2
0.13
Bivariate Correlations
LRPP
party variable
LRPP
1.00
party variable
0.38
1.00
factor 1
-0.02
0.13
factor 2
0.32
0.32
factor 3
0.20
0.10
COSTA RICA
Regression R2s
ideology regression
N
46
Adjusted R2
0.10
Bivariate Correlations
LRPP
LRPP
party variable
factor 1
factor 2
factor 3
1.00
0.46
0.34
0.23
0.05
factor 1
factor 2
factor 3
1.00
-0.15
-0.04
1.00
0.14
1.00
factor 4
party regression
N
46
Adjusted R2
0.20
party variable
factor 1
factor 2
factor 3
1.00
0.32
0.63
0.09
1.00
0.06
0.05
1.00
0.05
1.00
factor 4
47
Table 13, cont’d.
ECUADOR
Regression R2s
ideology regression
N
60
Adjusted R2
0.20
party regression
N
Adjusted R2
Bivariate Correlations
LRPP
party variable
LRPP
1.00
party variable
0.69
1.00
factor 1
0.18
0.26
factor 2
-0.12
-0.06
factor 3
0.45
0.57
Factor 4
0.11
0.03
MEXICO
Regression R2s
ideology regression
N
117
Adjusted R2
0.38
Bivariate Correlations
LRPP
LRPP
1.00
party variable
0.68
factor 1
0.40
factor 2
0.44
factor 3
0.24
60
0.47
factor 1
factor 2
factor 3
1.00
0.12
-0.05
0.05
1.00
-0.12
0.04
1.00
0.09
party regression
N
Adjusted R2
117
0.45
party variable
factor 1
factor 2
factor 3
1.00
0.37
0.66
0.20
1.00
0.02
0.05
1.00
-0.01
1.00
PERU
Regression R2s
ideology regression
N
73
2
Adjusted R
0.03
Bivariate Correlations
LRPP
party variable
LRPP
1.00
party variable
0.44
1.00
factor 1
0.27
0.34
factor 2
0.02
0.22
factor 3
-0.05
0.07
party regression
N
Adjusted R2
73
0.18
factor 1
factor 2
factor 3
1.00
-0.06
-0.02
1.00
-0.06
1.00
48
Table 13, cont’d.
URUGUAY
Regression R2s
ideology regression
N
69
Adjusted R2
0.54
Bivariate Correlations
LRPP
LRPP
1.00
party variable
0.81
factor 1
0.43
factor 2
0.14
factor 3
0.67
party regression
N
Adjusted R2
69
0.65
party variable
factor 1
factor 2
factor 3
1.00
0.51
0.18
0.64
1.00
0.03
0.12
1.00
0.06
1.00
VENEZUELA
Regression R2s
ideology regression
N
66
Adjusted R2
0.07
Bivariate Correlations
LRPP
party variable
LRPP
1.00
party variable
-0.38
1.00
factor 1
-0.23
0.18
factor 2
-0.23
0.41
factor 3
0.07
0.06
party regression
N
Adjusted R2
66
0.13
factor 1
factor 2
factor 3
1.00
0.09
0.02
1.00
0.07
1.00
1
R2s taken from the following two regressions: LRPP=f(factor 1, factor 2 … factor n) and LRPP=f(party variable); 2 LRPP
= Left-Right Party Placement; 3 Party variable = parties’ “real” positions on left-right dimension (created from mean
response to party placement question for each party with more than two respondents)
Note: Missing values were dropped from regressions to maximize the comparability of the R2 statistics.
49
Figure 1. Distribution of Latin American Legislators in Left-Right Party-Placement
Chile
(n=93, mean=4.99)
Argentina
(n=60, mean=5.02)
0.5
0.25
0.4
0.2
0.3
0.15
0.2
0.1
0.1
0.05
0
0
1
2
3
4
5
6
7
8
9
1
10
2
3
Bolivia
(n=71, mean=6.39)
4
5
6
7
8
9
10
7
8
9
10
7
8
9
10
Colombia
(n=61, mean=5.89)
0.35
0.3
0.25
0.2
0.15
0.1
0.05
0
0.4
0.35
0.3
0.25
0.2
0.15
0.1
0.05
0
1
2
3
4
5
6
7
8
9
1
10
2
3
Brazil
(n=66, mean=4.61)
4
5
6
Costa Rica
(n=50, mean=5.52)
0.3
0.5
0.25
0.4
0.2
0.3
0.15
0.2
0.1
0.1
0.05
0
0
1
2
3
4
5
6
7
8
9
10
1
2
3
4
5
6
50
Figure 1, cont’d.
Peru
(n=82, mean=5.90)
Ecuador
(n=67, mean=5.18)
0.5
0.4
0.35
0.3
0.25
0.2
0.15
0.1
0.05
0
0.4
0.3
0.2
0.1
0
1
2
3
4
5
6
7
8
9
10
1
2
El Salvador
(n=46, mean=4.80)
3
4
5
6
7
8
9
10
7
8
9
10
7
8
9
10
Uruguay
(n=69, mean=4.38)
0.25
0.4
0.35
0.3
0.25
0.2
0.15
0.1
0.05
0
0.2
0.15
0.1
0.05
0
1
2
3
4
5
6
7
8
9
1
10
2
Mexico
(n=118, mean=5.26)
3
4
5
6
Venezuela
(n=50, mean=4.90)
0.4
0.35
0.3
0.25
0.2
0.15
0.1
0.05
0
0.4
0.35
0.3
0.25
0.2
0.15
0.1
0.05
0
1
2
3
4
5
6
7
8
9
10
1
2
3
4
5
6
51